Author: Art Rangno

PROLOGUE

Dr. Reynolds, the sole author of this monumental review I critique  has done a masterful job of surveying an enormous amount of cloud seeding literature in his “draft” report to his former employer, the Bureau of Reclamation.  The BOR was  the primary sponsor of cloud seeding programs throughout the West in the 1960s to the 1980s.  However, as was also seen in a recent review of the 2009 Springer book,  “Impacts of Aerosols on Precipitation,” such a task appears to be too much despite Reynold’s valiant efforts to “get it right.”   Reynold’s discussions of the benchmark randomized experiments in Colorado that led to the nation’s largest, most costly randomized orographic cloud seeding experiments, the Colorado River Basin Pilot Project, is an example of the problem of having too much to review and not enough time to scrutinize the details of so much literature.

Reynold’s review is well-written, most of the necessary citations are in it that help the reader to understand the topic.    That is,  except for those elements in his review that I am perhaps, a little too familiar with and I feel must be addressed in this VERY belated review of his 2015 draft report.

“Too familiar?”

That’s what happens to someone who has spent thousands of volunteer hours (crackpot alert!) rectifying faulty cloud seeding and cloud claims in peer-reviewed journal articles because he felt, “Someone has to do something about this!” (Second crackpot alert, with possible megalomaniacal implications).   I was employed as a weather forecaster for the Colorado River Basin Pilot Project for all of its five winter operating seasons, 1970/71 through 1974/75.  No one can know about that project and the faulty literature it was based on more than me.  I came in naive and idealistic about the scientific literature on cloud seeding;  I didn’t leave that way

I was not asked to review Reynold’s 2015  review before he posted his report to the BOR  online as a “draft,” the status it retains as of today.   I contacted Dr. Reynolds recently and informed him that I had a few comments on and corrections to his review.  He replied that he was not interested in correcting his review or making changes at this time.  This seemed odd to me, so here we are.

Also, in the spirit of “author disclosure,” I should mention that Dr. Reynolds was also an informal reviewer of my manuscript co-authored with Prof. Dave Schultz, Manchester U., on the history of the BOR-funded Colorado River Basin Project.  It was recently rejected by the J. Appl. Meteor.  due to length.  We are in the process of seeing where that manuscript can be trimmed down without losing  important parts of the story.

The comments pn Reynold’s review would have likely been unnecessary had I reviewed it beforehand, or if Dr. Reynolds  wished to consider my comments and corrections today.    I was well known to Dr. Reynolds as an expert on clouds, cloud seeding, and the weather  in Colorado and Israel ;  he had previously cited my work his 1988 article in the Bull. Amer. Meteor. Soc.   With Professor Peter V.  Hobbs in tow, I dissected those landmark experiments in Colorado and Israel and showed they were, as Foster and Huber (1997) described faulty science,  “scientific mirages.”  They were “low-hanging fruit” that poor peer reviews of manuscripts had let in, mostly, appearing Amer. Meteor. Soc. journals.  It didn’t take a genius to unravel them.

Dr. Reynold’s comprehensive  review can be found here.  It is too long to be a blog post here that includes my embedded comments.  Since I am only commenting on certain sections,  I have extracted only those portions of Reynold’s review where I have made comments.  It may be that only those familiar with this topic, orographic cloud seeding, will be interested, but, oh, well….  It has to be done even if for only ONE person!

My goal is to be objective and not short change Reynolds’ work on what is really an astounding effort.  It would take me two lifetimes to do what Dr. Reynolds has done.

I also believe Dr. Reynold’s made a great effort to be objective in discussing a topic that almost always brings controversy.  The literature in this field is filled with pro-seeding partisans that have often edited results so that cloud seeding has been presented with a happier face than it should have been.  After all, no one got a job saying cloud seeding doesn’t work (is not viable for producing worthwhile amounts of water.)

Considering his background in the cloud seeding arena, Reynolds final conclusion, copied below, must be considered an example of high integrity and his conclusion is one that this author fully agrees as of this date:

“5.3.2 Final Conclusion 

Based on both the historical evidence and the last decade of research, it is reasonable to conclude that artificial enhancement of winter snowpack over mountain barriers is possible. It is very difficult to quantify the seasonal increases to be expected both in snowpack and subsequent spring runoff. This is because each target area has to be investigated as to the meteorology of the winter clouds and their seedability, and the engineering aspects of effectively seeding the clouds to maximize increases. Winter orographic cloud seeding should thus continue to be supported both from the scientific and operational community working together to further the science and operational outcomes. It must be stated however, that as of yet, no rigorous scientific study conducted as a randomized confirmatory seeding experiment with pre-defined primary response variables and requiring an established threshold of statistical significance has demonstrated that seeding winter orographic clouds increases snowfall. As such, the “proof” the scientific community has been seeking for many decades is still not in hand. “

================THE REVIEW=================

My comments, corrections and question on Dr. Reynolds review begins below and are in a red font.   Highly relevant citations are missing  and there are citations in the Reynold’s references that do not appear in the text.  The missing ones, annotated with a “u” ,  have been added at the end of this review.

The portions of Reynold’s review that I examined begins here:

———————————————————————-

1.0 Introduction 

1.1. Introduction to Winter Orographic Cloud Seeding In its most basic form, artificial seeding of clouds for precipitation enhancement can be divided into two broad categories: 1 – cloud seeding to enhance rainfall i.e. summer convection, 2 – winter orographic cloud seeding to enhance snowfall. The scope of this paper is only concerned with the latter. Winter orographic cloud seeding occurs when very small particles, typically silver iodide, are introduced into a cloud which is below freezing. The cloud moisture collects onto the small particles, freezing the moisture into tiny ice crystals which continue to grow until they become too heavy to remain in the cloud and then fall out as precipitation (typically snow). This process can happen rapidly on the windward slopes of mountains allowing the snow to fall near the crest of the mountain which causes a local enhancement to the amount of precipitation that would have fallen naturally (Figure 1.1).

The situation is complicated if the natural crystals are becoming rimed and due to riming, fall more quickly.  Adding more ice crystals via cloud seeding may result in raising their trajectories by reducing riming and the snow may not be increased snow where it is wanted, or will evaporate in the descending, drying  air on the lee side.  The schematic below would be valid for naturally non-precipitating clouds.  

The properties of clouds that don’t naturally precipitate vary with location.  Maritime clouds along the west coasts of continents generally can precipitate without ice.  Farther inland, where the clouds become impacted by natural and anthropogenic aerosols, ice is generally required for precipitation and may not develop until cloud tops are cooler than about -12°C.  These latter non-precipitating clouds make viable seeding targets.

Figure 1.1 – Simple model of winter orographic cloud seeding. 1 – Introduction of seeding material, 2 forced ascent due to topography, 3 – enhanced precipitation falling out of cloud. 

1.3 Relevance and Need for a Reassessment of the Role of Winter Orographic Cloud Seeding to Enhance Water Supplies in the West 

Weather modification is most commonly conducted through “cloud seeding,” the introduction of chemical agents with the intent of affecting precipitation processes. A number of academic and private entities exist that offer services to states and local governments with the aim of increasing water supplies through inducing precipitation volumes above which would occur naturally. From the 1960s through the 1980s, Reclamation was involved in a variety of weather modification initiatives in the west under Project Skywater. This project included the Colorado River Basin Pilot Project, the High Plains Experiment (summer only), and the Sierra Cooperative Pilot Project. Project Skywater was terminated in 1988, but Reclamation continued to be involved with weather modification efforts. Reclamation participated in the development of the California Department of Water Resource’s design and conduct of the Oroville Reservoir Runoff Enhancement Project from 1988 until 1994. Reclamation also supported other efforts through the mid-2000s, including the Weather Damage Modification Program. 

Based upon scientific literature through 2006 and discussions with experts in the field, the efficacy of weather modification appears to be unsettled. In 2003, the National Research Council (NRC) report “Critical Issues in Weather Modification Research” (NRC 2003), concluded that “there is still no convincing scientific proof of the efficacy of intentional weather modification efforts”. The NRC goes on to state that new technology allows for potential new research to help understand the process of precipitation and if weather modification is a viable means to increase water supplies. 

The NRC 2003 review of cloud seeding cited above  did not measure up to the one the NRC published in 1973.  I reviewed NRC 2003.  If anyone cares, can be found here:         

 A Critical Review of NRC 2003 Critical issues in weather modification NATIONAL ACADEMIES PRESS

As seems to be typical of reviews, there was just too much literature to review for the scientists involved, and also likely, not a top priority for those assigned to this task having other research on their plates.   Prof. Hobbs, with my acquiescence, helped compromise this review by declining an offer by Prof. Garstang, chair of the review committee, to review before it was published, a huge mistake.  Garstang admonished  Peter to not to comment on it AFTER it came out.  But that’s exactly what Peter told me we would do if needed.  I nodded and went back to my desk.  He said we would have “more impact” by doing that.  I hope you appreciate getting stories from behind the scenes.

In 2002-2003, Reclamation funded, through earmarks, weather modification studies in the states of Nevada, Utah, California, North Dakota, and Texas. The studies did not provide convincing scientific evidence that weather modification reliably generates additional water. However, there are a number of studies, including from within Reclamation (Hunter 2004 – cited within LBAO (Lahontan Basin Area Office) EA discussed later), that indicate that cloud seeding can significantly increase precipitation amounts for targeted locations. 

Statement on the Application of Winter Orographic Cloud Seeding For Water Supply and Energy Production 

In 2005, Reclamation primarily stopped involvement in weather modification efforts at the program level. As identified within Q&As developed by the Research and Development Office explaining Reclamations abandonment of the practice: 

•Weather modification is not an operational function of Reclamation.

•In a letter dated December 13, 2005, sent to then-Texas Senator Kay Bailey Hutchison(R), the White House Office of Science and Technology Policy (OSTP) said there aresignificant concerns about liability and legal ramifications of weather modification,including whether weather modification can be demonstrated to actually be effective.

Since 2006, continuing drought conditions, and a strong interest amongst some Reclamation stakeholders, Reclamation engaged in two research projects related to weather modification in support of cold-season snowfall enhancement. 

•In 2010 the Mid-Pacific Region’s LBAO finalized an Environmental Assessment (LBAOEA) proposing to provide $1.35 million from Reclamation’s Desert Terminal LakesProgram to the Desert Research Institute (DRI) for a cloud seeding project in the WalkerRiver Basin.

•At a March 12, 2014 meeting of the Upper Colorado River Commission, weather modification was specifically identified as one of three activities that the Upper Basin states propose to include within their drought contingency plans. The Upper Basin states asked that Reclamation provide partial support for Wyoming’s eighth year (2014) of an ongoing weather modification study / program being conducted with the National Center for Atmospheric Research (NCAR). This request resulted in Reclamation’s Upper Colorado Region obligating $200,000 to the State of Wyoming for weather modification research and development efforts conducted by NCAR, with these monies obligated through an amendment to an existing cooperative agreement between Reclamation R&D and Universities Corporation for Atmospheric Research.

The Upper Basin states have noted that state and private entities in Colorado and Utah spend over $1M and $500,000 respectively on weather modification, and estimate efficacy between 6% and 20%. At the low end, the Upper Basin states identify that a benefit of 6% is inexpensive water within the Colorado River Basin. The Upper Basin states have argued that Reclamation’s documents from the 1960s – 1980s identified positive results of weather modification.

This above section needs supporting references for the assertions made about seeding results, the benefit claim, and who are those “Upper Basin States”?  Otherwise these statements should be taken with extra caution.

1.5 Brief History of Federal and State Authorizations for Weather Modification 

The following is taken from Chisolm and Grimes (1979): 

In 1968, the Colorado River Basin Project Act of 1968 (Public Law 90-537) was passed by Congress to provide for the further comprehensive development of water resources of the Colorado River Basin and for the provision of additional and adequate water supplies for use in the upper as well as lower Colorado River Basin. Under Title II of this Act, the Secretary of the Interior was authorized to prepare and implement an augmentation plan to meet the water requirements of the new projects created by the Act (Central Arizona Project and Colorado River Storage Project), existing projects and water allotments, and the 1944 water treaty with Mexico. 

Augmentation was one of the main issues in the deliberation on the Act. The Act defines augmentation as, “ ‘augment’ or ‘augmentation’ when used herein with reference to water means to increase supply of the Colorado River system or its tributaries by introduction of water into the Colorado River system, which is in addition to the natural supply of the system.” The Statement of the Managers on the part of the House with regard to augmentation stated “all possible sources of water must be considered, including water conservation and salvage, weather modification, desalinization and importation from areas of surplus.”

The Colorado River Basin Pilot Project (CRBPP) was the Bureau’s first major effort on weather modification in Colorado under the auspices of Project Skywater and P. L. 90-537. The purpose of the Colorado River Basin Pilot Project was to provide for scientific and economic evaluation of precipitation augmentation technology and to increase precipitation. The specific objectives to be achieved were (l) to establish and operate a ground-based meteorological network in and near the San Juan Mountains of Colorado to provide data input in the selection of suitable storms for seeding, and (2) to establish and operate a ground-based silver iodide seeding system to increase snowfall in the project target area. The field phase of CRBPP began with the winter of 1969-1970 (installation of gauges and seeding generator siting) while the random seeding phase began with the 1970-71 season and ran through the 1974-75 season (not the 1973-74 season as the author stated).

Date corrections are needed from the original text, not a good sign of the author’s knowledge concerning the CRBPP.  What is incomprehensible is that the goal of replicating the large percentage increases in snowfall reported in three randomized experiments by the author’s former home institution, Colorado State University, is left out of this rationale for the CRBPP.  Surely, the author knew, also as a long term BOR cloud seeding division employee, that those experiments were the primary motivation for the BOR to spend $40-50 million (in 2023 dollars) on the CRBPP.

At about the time of completion of CRBPP in Colorado, the Bureau began funding Project Snowman in Utah. Project Snowman was conducted for the Bureau by Utah State University’s Water Research Laboratory. The objective of this four-year project was to develop cold-cloud seeding technology using airborne generators and ground-based generators located in the northern portion of the Wasatch Mountains.

References are also needed here.

The Bureau’s early work on precipitation augmentation in Colorado was based on a fairly extensive background of research activities. Three major research efforts in winter seeding contributed directly to the Bureau’s CRBPP project in the Upper Colorado River Basin. These were: 

1. The National Science Foundation sponsored research experiments by Colorado State University at Climax, Colorado, during the 1960’s.

“1” above is not a sufficient description of the motivation for the CRBPP.  The Climax experiments were reported on numerous occasions in the peer-reviewed literature as cloud seeding successes when air mass temperatures were high (i. e., high 500 hPa and 700 hPa equivalent temperatures as by Grant and Mielke 1967u, Kahan et al. 1969u, Grant et al. 1969u, Mielke et al. 1970u, 1971u, among others).  The BOR had a LOT of peer-reviewed evidence on which to base the CRBPP and in particular, in the Grant et al. 1969u Interim Report to the BOR that described the results of the Climax I results, and the preliminary results of Climax II and the Wolf Creek Pass experiments.  The findings in these three experiments, as described by Grant et al. 1969u,  were remarkably supportive of one another.  Climax II was a confirmatory experiment; nothing was changed from Climax I.

2. The operational research funded by the State of Colorado during the 1960′ s at several mountain passes, particularly Wolf Creek Pass in the San Juan Mountains, and,

The Wolf Creek Pass experiment mentioned above was a six winter season,  fully RANDOMIZED  experiment where entire winter seasons were randomized.  This experiment was critical to where the CRBPP was located since it appeared to have produced more water than seeding had in northern Colorado where the Climax experiments took place.

3. The Bureau sponsored experiments in the Park Range near Steamboat Springs, Coloradoduring the late 1960’s.

Rhea et al.’s 1969u “Final Report” to the  BOR concerning the Park Range Project  is eventually cited by Reynold’s, but is not in Reynold’s references.  This report was a “heads up” on all the problems that would be “rediscovered” during the CRBPP (e.g, as reported in Willis and Rangno 1971u).

The results of the Colorado River Pilot Project indicated the need for further verification and improvement in technology before a large augmentation program could be undertaken again.

This is a vague description of the CRBPP results, perhaps intentionally so. Why not just say what happened for the reader right here in plain language?   “The results of the earlier CSU experiments could not be replicated in the CRBPP (Elliott et al. 1978u followed by a citation to the “Comments” on Elliott et al’s findings by Rangno and Hobbs 1980-the latter reference is contained in Reynold’s references but is not discussed in his review.   Later, it was discovered that those early optimistic CSU results and the microphysical foundation on which they rested on were all ersatz leaving no real basis for the CRBPP  (e.g., Mielke 1979u, Rangno 1979u, Hobbs and Rangno 1979u, Rhea 1983, Rangno and Hobbs 1987u, 1993, 1995a, u)”

The Wolf Creek Pass seeding effort was designed to test whether a viable signal in runoff from Wolf Creek Pass could be produced by seeding all winter.  The Wolf Creek Pass experiment, conducted from the winters of 1964/65 through 1969/70 produced stunning results when the three randomly chosen seeded seasons were compared with the long historical runoff record (Grant et al. 1969u, Morel-Seytoux and Saheli 1973u).  Furthermore, the results of seeding on  individual days during the seeded winters appeared to replicate the results of Climax I.  It doesn’t get any better than this for a trifecta of apparent cloud seeding successes!  

But, it was all a mirage (e.g., Rangno 1979u), which makes this story so interesting from a scientific viewpoint.

Thus, the Bureau’s research program continued.

Winter experiments were conducted outside of the Colorado River Basin at: Elk Mountain, Wyoming (University of Wyoming) Bridger Range, Montana (Montana State University) Jemez Mountains, New Mexico (New Mexico State University) Pyramid Lake Pilot Project (University of Nevada) In addition, the Bureau continued to provide supplemental funds to Colorado State University’s NSF research and to Utah State University’s state -sponsored research project. Through the Emergency Drought Act of 1977 the Bureau granted over $2 million to six states for supplemental support of their cloud seeding projects including over $1 million to the States of Colorado and Utah for cloud seeding in the Colorado River Basin. 

1.6 Current Policy Statements from American Meteorological Society and World Meteorological Organization on Efficacy of Winter Orographic Cloud Seeding 

The two leading organizations representing the atmospheric science scientific establishment, the World Meteorological Organization and the American Meteorological Society, have both issued policy statements on the efficacy of winter orographic cloud seeding. These are relevant to review given the NRC 2003 conclusions. 

The current statement from the World Meteorological Organization (WMO 2010) on weather modification in general and relating specifically to winter orographic cloud seeding efficacy is stated below. 

“The scientific status of weather modification, while steadily improving, still reflects limitations in the detailed understanding of cloud microphysics and precipitation formation, as well as inadequacies in accurate precipitation measurement. Governments and scientific institutions are urged to substantially increase their efforts in basic physics and chemistry research related to weather modification and related programmes in weather modification. Further testing and evaluation of physical concepts and seeding strategies are critically important. The acceptance of weather modification can only be improved by increasing the numbers of well executed experiments and building the base of positive scientific results.” 

“Cloud seeding has been used on both cold clouds, in which glaciogenic seeding aims to induce ice-phase precipitation, and warm clouds, where hygroscopic seeding aims to promote coalescence of water droplets. There is statistical evidence, supported by some observations, of precipitation enhancement from glaciogenic seeding of orographic supercooled liquid and mixed-phase clouds and of some clouds associated with frontal systems that contain supercooled liquid water. “ 

The current AMS policy statement (AMS 2010) does not address specifically the efficacy of winter orographic cloud seeding but much like the NRC 2003 report identifies uncertainty and risk with much the same conclusions. These are listed below. 

UNCERTAINTY – Planned weather modification programs benefit from a comprehensive understanding of the physical processes responsible for desired modification effects. Recent improvements in the composition and techniques for dispersion of seeding agents, observational technology, numerical cloud models, and in physical understanding of cloud processes permit evermore detailed design and targeting of planned weather modification effects, and more accurate specification of the range of anticipated responses. While effects are often immediately evident in simple situations, such as when cloud seeding is used to clear supercooled fog and low stratus cloud decks, in more complex cloud systems it is often difficult to determine a seeding effect on a cloud-by-cloud basis. In these more complex situations, large numbers of events must be analyzed to separate the response to cloud seeding from natural variability in cloud behavior. Rigorous attention to evaluation of both operational and research programs is needed to help develop more effective procedures and to improve understanding of the effects of cloud seeding. Research and operational programs should be designed in a way that will allow their physical and statistical evaluation. Any statistical assessment must be accompanied by physical evaluation to confirm that the statistical results can be attributed to the seeding through a well-understood chain of physical events. It should be noted, though, that in practice large potential benefits can warrant relatively small investments to conduct operational cloud seeding despite some uncertainty in the outcome. 

The text in blue font seems like PR, Dave, and should be updated due to the lack of proof of seeding induced increases in snow we now have. Neiburger (1969u, WMO Tech Note) warned that such thinking usually excludes the idea that seeding might result in decreases in precipitation in addition to mistargeting, faulty operations.  

1969 CLOUD SEEDING REVIEWS MORRIS NEIBURGER ocr

RISK MANAGEMENT – Unintended consequences of cloud seeding, such as changes in precipitation or other environmental impacts downwind of a target area, have not been clearly demonstrated, but neither can they be ruled out. In addition, cloud seeding materials may not always be successfully targeted and may cause their intended effects in an area different than the desired target area. This brings us to the ethical concern that activities conducted for the benefit of some may have an undesirable impact on others; weather modification programs should be designed to minimize negative impacts.. At times unintended effects may cross political boundaries, so international cooperation may be needed in some regions. Precipitation augmentation through cloud seeding should be viewed cautiously as a drought-relief measure because opportunities to increase precipitation are reduced during droughts. A program of precipitation augmentation is more effective in cushioning the impact of drought if it is used as part of a water management strategy on a long-term basis, with continuity from year to year, whenever opportunities exist to build soil moisture, to improve cropland, and to increase water in storage. From time to time methods have been proposed for modifying extreme weather phenomena, such as seeding severe thunderstorms with aerosols to diminish tornado intensity, or seeding tropical cyclones to cause changes in their dynamics and steer them away from land and/or diminish their intensity. Some experimentation has taken place in these areas, but current knowledge of these complex weather systems is limited, and the physical basis by which seeding might influence their evolution is not well understood. Weather modification techniques other than cloud seeding have been used in various areas of the world for short periods of time to achieve goals similar to those of cloud seeding. Much less is known about the effects of these other techniques, and their scientific basis is even further from being demonstrated, either statistically or physically, than it is for cloud seeding. Application of weather modification methods that are not supported by statistically positive results combined with a well-understood physical chain of processes leading to these results, and that can also be replicated by numerical cloud modeling, should be discouraged.

Other organizations such as the North American Interstate Weather Modification Council, The Weather Modification Association, the American Society of Civil Engineers, and the Western States Water Council have also adopted policy statements or adopted resolutions relating to the use of weather modification for increasing snowpack and water supply. These are referenced in Ryan (2005) and will not be repeated here. Most if not all of these statements are much more positive in their support of the application of weather modification for enhancing snowpack and runoff despite the lack of evidence as reported in NRC 2003.

To the uninitiated reader to the field of weather modification/cloud seeding, it will seem odd that there are government entities that will pay huge sums of tax payer monies for cloud seeding with no viable evidence that it does anything, evidence being in the form of randomized experiments, the “gold standard” of scientific proof.  

Why would those entities take such chances?  

If you haven’t guessed by now, it’s because those government entities are telling their constituents directly or implicitly that they are doing SOMETHING about a drought.  It’s a great ploy, and usually works except in the minds of those who know the science.  

What science?  

Two modern randomized experiments testing to see if cloud seeding can increase precipitation in mountainous regions (Wyoming and in northern Israel) ended with  no indications that cloud seeding increased precipitation.  These null findings have been published by Rasmussen et al. 2018u for Wyoming, and by Benjamini et al. 2023u for Israel.  Now you know.  

Did the “null” finding reported by Rasmussen et al. 2018 terminate cloud seeding in Wyoming?  Of course  not.  It just looks too good to the public that you’re doing something about water needs.  

1.7 Generalized Concepts of Winter Orographic Cloud Seeding 

It is useful to review the general principles of winter orographic snowfall and whether this process could be modified or enhanced by artificial means. The basic physical concepts associated with seeding winter orographic clouds are not debated even though there is considerable debate over weather modification and its efficacy. These basic physical concepts are reviewed in the following section. There are several text books and encyclopedia articles available for a more in-depth discussion or broader overview of the physical basis of cloud seeding (Hess 1974; Dennis 1980; Dennis 1987; and Heymsfield 1992). 

Dennis in his (1980) Academy Press book, “Weather Modification by Cloud Seeding,” relied heavily on the 1977 BOR Monograph Number 1 (yes, it was deemed that important by the BOR to name it as NUMBER ONE),  became outdated almost immediately when external critics (guess who?) found serious flaws in that “meta-analysis.”     The BOR study, published in 1978u (Vardiman and Moore) was retracted in 1980  by Rottner et al. 1980 as critical “Comments” on their paper by, yep, Rangno and Hobbs (1980) were being published.  Thus, Dennis (1980) might be reconsidered as a reference here.  The BOR was too willing to believe in cloud seeding success mirages that led to this major embarrassment.

Too, much of the cloud seeding literature in Hess (1974) has been overturned in reanalyses or has not been replicated, as in the recent Wyoming and Israel experiments.  But, “hey,” you can read about global cooling in Hess (1974), thought to be underway at that time.

Figure 1.2 from Ludlam (1955), reproduced below, describes the process that remains to this day the fundamental conceptual model associated with winter orographic cloud seeding. Figure 1.2 shows a shallow orographic cloud, where the liquid condensate produced by forced assent over a mountain barrier is unable to be converted to snowfall before the air descends and evaporates in the lee of the mountain. During wintertime the freezing level (height of the 0^oC isotherm) varies dependent on the origin of the air mass impinging on the mountain barrier.  This varies from north to south with the freezing level being lower in altitude at the northern latitudes of the western US and the inter-mountain west where the air masses that impact this area are usually modified maritime polar or continental polar.

and height allowing the crystals to grow at the expense of the cloud water that in (a) was lost to the lee, bringing this moisture down on the windward side of the mountain.

1.2a is the non-precipitating cloud that forms the low, demonstrable end of seeding potential.

The text in blue in the body of the paragraph may be true, but….. warm air masses during times of upper level ridges along the West Coast shunt warm air mass storms into the central and northern Rockies, so this “paradigm” often does not hold.  Surface temperatures may be well below freezing, but much higher temperatures usually exist aloft in those warm aloft regions of winter storms.  The Climax I experiment, for example, had numerous warm aloft storms overrunning colder air with west-northwest flow due to this synoptic scenario.   Quantification of this claim would have been very informative and would have pinned it down for the reader…and me!

Freezing levels are usually below ground level in mountainous regions except in the warmest storms. In the Ludlum model, it is assumed the orographic cloud has a significant depth of cloud below 0 ^oC and thus the cloud moisture is said to be supercooled. The critical uncertainty with regard to successful conversion of the unused cloud condensate to snowfall prior to passing over the crest is the location, duration, temperature and concentration of the supercooled liquid water (SLW).

As Ludlum describes it may take as much as 1500 seconds once artificial ice crystals are initiated to grow and fall out before passing to the lee of the mountain crest.  This can vary by several tens of minutes based on SLW concentration, temperature vertical profile and winds.

The process of crystal growth is almost always much fast than “as much as” 25 minutes to fallout cited by Ludlum  (e.g., Auer et al. 1969, Cooper and Vali 1981).

So the critical factors for achieving success are getting the seeding agent into the cloud at the right location where it will generate enough ice embryos such that they will utilize the available SLW prior to passing over the crest. There are many complex interactions that have made it very difficult to demonstrate the efficacy of winter orographic cloud seeding to the satisfaction of the scientific community. These factors are described in the following paragraphs. 

So true.

 1.7.1 The Initiation, Growth and Fallout of Snow in Winter Orographic Clouds 1.7.1.1 Converting Supercooled Liquid Water (SLW) to Snow

Supercooled liquid water (SLW) in the atmosphere is made up of tiny cloud droplets that are colder than 0 oC. There are two processes in nature by which SLW in the atmosphere can freeze to initiate snowfall: 1. Heterogeneous nucleation or 2. Homogeneous nucleation. Heterogeneous nucleation occurs when the supercooled liquid drop comes in contact with what is called an ice nucleus (IN) that emulates the crystalline structure of ice and causes the droplet to freeze. These can be dust particles, biological particles or a combination of the two. These aerosols can come from as far away as Asia and Africa initiating cloud ice in orographic clouds in the western US (Cremean et al. 2013). They are made of very small particles of tenths of microns in size. They are most active at cloud top and tend to activate the growth of snowflakes from the top of the cloud down. The warmer the cloud top the less percentage of ice makes up the cloud (Cremean et al. 2013).

Sidebar:  An interesting feature, first observed in the 1950s (e.g., Cunningham 1957u) and afterward was the “upside down” storm structure where few ice crystals were found at low cloud top temperatures consisting mostly of supercooled liquid water with increasing ice crystal concentrations below the top. The increasing concentrations of ice crystals were mostly due to the fragmentation of delicate ice crystals. The most recent description of this scenario was by Rauber and Tokay (1991u) and Hobbs and Rangno (1985).

Lower down, within a km of the surface, ground observations have shown that riming and and aggregation occur that increase snowfall rates. This lower region near mountains cannot be sampled by aircraft if precipitation is falling and as a result, has mainly been documented  in ground observations (e.g, Hobbs 1975). Thus, aircraft observations can often be seen as under measuring ice particle concentrations in mountainous regions.  For example, we at the University of Washington often overflew shallow orographic clouds with liquid tops at >-10C with snow falling out underneath, but we couldn’t sample them because the tops were too close to the tops of the Cascade Mountains.

When clouds are dominated by warm rain processes, the aerosol makeup of the cloud is more sea salt and biological particles which act as condensation nuclei producing larger cloud droplets which grow to raindrops via collision coalescence. Homogeneous nucleation occurs when the air temperature drops below -40 ^oC and the water droplet spontaneously freezes without the aid of a nucleating agent. The most basic hypothesis in winter orographic cloud seeding is that in the presence of SLW droplets, ice crystals will grow at the expense of the drops. This means the drops will convert back to vapor allowing the crystals to grow by vapor deposition unless too many ice crystals have resulted from seeding in which case they might not grow at all. The driver for crystal growth is related to the concentration of SLW and the temperature regime of the SLW (Ryan et al. 1976; Heymsfield 1992; Pruppacher and Klett 1978).

In the presence of moderately high concentrations of SLW and with somewhat preferred growth temperatures (Ryan et al. 1976, Figure 1.3) enough of the initial ice crystals can grow and then begin to aggregate into larger flakes leading to higher fall speeds and earlier fall-out. If these artificial crystals encounter additional SLW as they fall back toward the mountain crest, the individual crystals or aggregates may collect these SLW drops (called riming) which will also increase the crystals fall-speed. If the naturally created ice crystals are unable to utilize all the available SLW, and some SLW evaporates to the lee of the mountain, the cloud is said to be less than 100% efficient. This provides the opportunity for the artificial injection of a nucleating agent to create the additional ice crystals necessary to bring the residual cloud water to the ground before it is lost to the lee of the mountain. This is the basic principles described in Ludlam’s model. 

Aerial Seeding window 

Ground based seeding temperatures 

General seeding window based on Figure 1.5 and observed SLW 

As Super and Heimbach (2005) noted, the frequency of occurrence of SLW is temperature dependent with higher frequencies and amounts at (higher) supercooled temperatures. This is true for all mountain ranges where SLW has been observed. There are two main reasons for this. First, the amount of water vapor in the atmosphere can be higher at warmer (higher) temperatures. Second, as the atmosphere cools and clouds form and reach temperatures lower than -10 ^oC, and especially at -20 ^oC, an abundance of natural ice can occur that depletes the supercooled cloud water. Thus, there is less SLW available for cloud seeding to enhance the natural precipitation process as the air approaches these temperatures. It should be noted that studies (Reinking et al. 2000; Super 2005) have found significantly higher amounts of SLW (.5 to 1 mm integrated SLW) in wave clouds during winter storms and noted that others had observed such amounts during brief periods in other western mountain locations. However, the overwhelming amount of observations utilizing microwave radiometers (Heggli and Rauber 1988; Huggins 2009; Super and Heimbach 2005), in-situ aircraft observations, and mountain top icing rate meters indicate that SLW is concentrated in the lowest 1000m along the windward slopes of mountain ranges during passing winter storms. The primary SLW zone rapidly dissipates downwind of the crest because of warming produced by subsidence and by depletion from conversion to snowfall (Boe and Super 1986; Rauber et al. 1986; Rangno 1986 (the rapid dissipation of SLW, one of my main points), Huggins 1995; Super 2005; Huggins 2009).  There are observations that confirm the simple conceptual model espoused by Ludlam when natural ice does not form. The location of many of the research studies referenced in this report along with other locations that will be referenced later in this report are shown in Figure 1.4b. One can compare these locations to Figure 1.4a which shows the location where operational winter orographic cloud seeding is conducted circa 2006 per Griffith et al. 2006. Coastally influenced areas would be west of the Sierra Nevada and Cascades while the intermountain region refers to areas east of these two ranges. 

The actual temperature relationship to SLW occurrence varies geographically. For the intermountain west, where the cloud drop size distributions are more numerous at the smaller drop sizes (10 to 15 microns; what is referred to as a continental drop size distribution), lower temperatures are reached before a sufficient number of natural ice crystals develop to utilize the available SLW. Thus, SLW can exist, at least briefly, at temperatures as low as -15 to -20 ^oC. Super and Heimbach (2005) provide a comprehensive review of SLW climatology in the intermountain west. 

In more coastal regions, such as the Sierra Nevada and Cascades, the drop size distribution can be broad (what is referred to as a maritime drop size distribution). The drops can begin to collide and coalesce because of the varying fall speeds of the drops with a broader distribution of cloud droplets (extending into and above 30 microns diameter). This leads to larger cloud drops (approaching drizzle size) that can be carried upslope into coastal mountains like the Cascades and Sierra Nevada ranges where just a few of these droplets can freeze leading to rime splintering or secondary ice-crystal production (Hallett and Mossop 1974; Dong and Hallett 1989; Mossop 1985). This can, and has been observed to lead to high concentrations of ice crystals with cloud temperatures warmer than -10 ^oC (Reinking 1978; Cooper 1986; Marwitz 1986; Hobbs and Rangno 1985; Rauber 1992).

Nieman et al 2005u reported  occurrences of the “warm rain” process in Northern California and Oregon were common.  Will cloud seeding increase precipitation if nature is providing rain via collisions with coalescence?

Other factors (Rango  (sic) 1986) can lead to high ice crystal concentrations with relatively high cloud top temperatures. Mixing of very dry air into cloud tops can initiate cloud droplet freezing (e.g., Koenig 1968; Hobbs and Rangno 1985). This has been observed in the Cascades, Sierra Nevada and southern Utah. In the post-frontal airmass, where most of the shallow orographic clouds exist, very dry air can exist above cloud top. This is caused by sinking air parcels in the region behind the upper-level jet-stream that usually passes just ahead of the surface cold front  (Heggli and Reynolds 1985). Thus the coastal mountain clouds will have a lesser degree of supercooling, meaning that the clouds will be only marginally supercooled as natural ice production will utilize the available SLW within moderately supercooled clouds. Reynolds (1995) documented that over an 8 year period in the northern Sierra Nevada, 80% of the hours reporting SLW from mountain-top icing rate meters were at temperatures warmer than -4 ^oC. Reynolds (1996) also reported that 70% of the hours with precipitation had icing (riming?) reported. Approximately 300 hours of icing were reported per season. However, some seasons had average temperatures during icing warmer than -2 oC which may be too warm for any known seeding agent to work effectively unless seeded aloft using aerial seeding. Studies examining mountain top temperatures in Colorado and Utah revealed that SLW in clouds is mildly supercooled in a large portion of all storm passages, which means clouds are too warm for effective AgI seeding (Super 2005). Refer to Figure 1.5 for activation levels of the various cloud seeding agents currently used or proposed.

Why aren’t supercooled non-precipitating clouds’ occurrences documented for whole seasons as in Ludlams’s simple case? Seems this information would form a great starting point that could determine how much seeding can unequivocally increase snow.  The reader would like to know.

There are many studies (Heggli et al. 1983; Boe and Super 1986; Rauber and Grant 1986; Heggli and Rauber 1988; Super and Huggins 1993; Super 2005; Huggins 2009) that state SLW within a cloud varies rather rapidly with time over any given point. Due to this variability in SLW, identifying seeding potential within winter orographic storms will require identification of the proper seeding agent and delivery technique and applied at the correct time and location (Hunter 2007; Huggins 2009). Huggins (2009) suggests that any cloud seeding program will necessarily be treating clouds that at any given time may not have sufficient SLW (when the seeding agent arrives) given its variability. This begs the question as to whether seeding in these situations may have negative impacts on snowfall production. This will be further discussed in Section 1.7.4. Even though the location of SLW concentrations is known, the exact lower threshold for SLW concentrations to be sufficient for enhancing snowfall has not been quantified. It is believed to be greater than .05 mm integrated in the vertical derived from microwave radiometers (threshold used by Super and Heimbach 2005 and Manton et al 2011). However, Murakami (2013) used .2 mm as the lower threshold for determining cloud seeding feasibility and theorized that .3mm was probably the minimum threshold for viable increases in orographic precipitation enhancement.

For what durations of this SLW threshold? Did those these researchers report how long it lasted?  Did they make any seasonal estimates of these occurrences?  The reader would want to know.

This is a critical question as frequency distributions of SLW concentrations from radiometer data (Reynolds 1988) indicate that 85% of the SLW reported were at concentrations below .2 mm (Figure 1.5).What constitutes a necessary and sufficient concentration of SLW for effective cloud seeding is still in debate. 

Several studies (Rosenfeld 2000; Givati and Rosenfeld 2004; Rosenfeld and Givati, 2006; Griffith et al. 2005; Hunter 2007) have described decreases in orographic precipitation due to pollution.

The above requires some exhaustive comments:

Reynolds was unaware that when the claims of Givati and Rosenfeld concerning air pollution were examined by external skeptics they have not been substantiated.   I think this same view should be taken with Givati and Rosenfeld (2006) for pollution effects on West Coast precipitation.  We need this latter study to be validated by an external skeptic!  Yes, I am excited here.

I suspect, as in the Givati and Rosenfeld’s (2005) Israel study, where more than 500 standard gauges and 82 or so recording gauges were available to cherry-pick whatever result one wants, this may well have been  done in the 2006 study.   Kessler et al. (2006u), in an evaluation of the Israeli operational seeding program wrote: “No supporting evidence was found for the thesis of Givati and Rosenfeld (2005) regarding the decline in the Orographic (sic) precipitations due to the increase of air pollution.”

The air pollution claims, while superficially credible except for their sudden hypothesized appearance in Israel after 1990 when operational seeding produced a slight indication of decreased rainfall (Kessler et al. 2006u), were also evaluated by several independent groups and scientists: Alpert et al. (2008u, 2009u); Halfon et al. (2009u); Levin 2009u.   The Givati and Rosenfeld (2005) claims were also addressed in a review by Ayers and Levin (2009u). All these independent re-analyses and reviews of the hypothesized effect of air pollution on rainfall found the argument that air pollution had canceled seeding-induced increases in rain in Israel unconvincing.   In the few cases that Dr. Rosenfeld’s papers have been reviewed by external skeptics, they don’t hold up.  Ask Prof. Levin, Tel Aviv University, Professor Sandra Yuter, North Carolina State University, Nathan Halfon, Tel Aviv University, or me.   Hence, Caveat Emptor!

This specifically impacts the collision coalescence process and what is called warm rain, i.e. no ice processes involved. These studies discuss that pollution can slow down the collision coalescence process by narrowing the drop-size distribution. This, in turn, slows down the warm rain process and would have the largest impacts in the low-elevation coastal ranges along the west coast where the freezing level is well above the elevations of the coastal mountains, i.e. around Los Angeles where it has been proposed to reduce precipitation. Typically the decrease in orographically enhanced precipitation is greatest downwind of a major metropolitan area that is producing pollution. Givati and Rosenfeld (2004) showed precipitation losses near orographic features downwind of coastal urban centers corresponding to 15-25% of the annual precipitation.

Caveat emptor re Givati and Rosenfeld’s findings!

This loss of precipitation can be greater than the gain claimed by precipitation enhancement techniques in portions of California (Hunter 2007). Hindman et al (2006) noted that the trend over the past 20 years, from cloud droplet measurements at Storm Peak in the northern Rockies, has shown a decrease in CCN and an increase in cloud drop size. The conclusion was a decrease in upwind CCN concentrations (less pollution) but no relationship was found with precipitation rate. Thus, the change in cloud droplet spectra was not impacting riming growth efficiency (Borys et al 2003). It was noted by Creamean (2013) that pollutants, such as from human activity, were found mostly in the boundary layer and with frequently higher concentrations preceding surface cold fronts. The pollutants become trapped in the stable air as the air warms aloft and surface flows tend to be from the southeast to east tapping polluted sources from the central valley of CA. Once the front passed, the air-mass off the ocean did not contain these pollutants. It is the post–frontal cloud systems that have been identified as the most seedable in the northern and central Sierra (Heggli and Reynolds, 1985). It is not anticipated that pollutants play a significant role in these post-frontal shallow orographic clouds.

It should be noted that a more recent survey article by Tanre’ et al (2009), reviewed the impact of aerosols on precipitation and concluded: “Even though we clearly see in measurements and in simulations the strong effect that aerosol particles have in cloud microphysics and development, we are not sure what is the magnitude or direction of the aerosol impact on precipitation and how it varies with meteorological conditions. Even the most informative measurements so far on the effect of aerosols on precipitation do not include simultaneous quantitative measurements of aerosols, cloud properties, precipitation and the full set of meteorological parameters.”

Thanks to Tanre’ et al. (2009)!

The current CALWATER II experiment running this winter in California is an attempt to provide such information.

(Did it?)

The main limitation is very similar to the problems inherent in quantifying the impacts of artificial seeding of winter orographic clouds. That is the observing systems that we apply to quantifying the impacts have large measurement uncertainties and are of a magnitude similar to the expected aerosol influence on precipitation. Tanre’ notes that satellite and radar measurements have 20-30% errors in the measurement of aerosol optical depth, while aircraft sampling in-cloud can introduce changes in the cloud that can compromise the utility of the aircraft observations. In-deed measurements of surface precipitation, especially snowfall water equivalent can have 10-15% measurement uncertainty given gauge location and thus exposure to wind, minimum threshold/resolution, and such problems as capping. These types of measurement uncertainties require longer term on-going statistical analyses to reduce the random noise in the observations much like is required for cloud seeding experiments, thus reducing the influence of measurement uncertainty so as to extract the small signal that might exist. 

1.7.1.3 Artificial Stimulation of Snowfall by Seeding Agents

Artificial stimulation of snowfall is conducted through the application of aerosols that mimic natural ice nuclei to enhance the heterogeneous freezing of available SLW or by chilling the air below -40 oC to initiate homogenous nucleation. It is well known that the effectiveness of the heterogeneous seeding agent is highly temperature dependent. Artificial cloud nucleating substances (AgI, CO2, Liquid propane, SNOWMAX) are dependent on the presence of SLW at temperatures slightly below 0 oC for CO2, propane, and SNOWMAX (Ward and Demott 1989) or below -5 C to -8 oC for AgI mixtures (Figure 1.6). 

Figure 1.6 – Seeding activation versus temperature for seeding agents that have been used or proposed

These seeding agents act in different ways. Solid or liquid CO2 and liquid propane work by homogenous nucleation. These seeding agents need to be directly released in the presence of SLW for them to be effective. AgI and SNOWMAX work by heterogeneous nucleation, meaning they mimic the structure of natural ice nuclei. They do not have to be released directly into cloud or SLW. The aerosol can be carried aloft into clouds and when it encounters SLW at the right temperatures will begin generating ice crystals by contact nucleation. As shown in Figure 1.6, SNOWMAX works at the warmer (higher) end of the SLW temperature spectrum and its effectiveness does not vary greatly with temperature. To the author’s knowledge, SNOWMAX is not used in any operational seeding program but is used almost exclusively for snowmaking at ski resorts. The effectiveness of AgI to nucleate ice crystals increases by orders of magnitude from -5 oC to -12 oC (Super 2005). It should be noted that under transient water supersaturations, AgI can activate more rapidly and at temperatures near -5 oC through the condensation freezing mechanism (Pitter and Finnegan 1987). Chai (1993) explained the only way AgI could have been an effective seeding agent in the Lake Almanor seeding experiment (Moony and Lunn 1969) was through the fast activating condensation freezing process.

Mooney and Lunn (1969)… The westerly case where it was reported there had been large increases in snow reported due to seeding, was not reported for Phase II of the Lake Almanor experiment (Bartlett et al. 1975u). This omission should be unsettling to any objective scientist.

If the AgI is burned below cloud base or at temperatures warmer than -5 o C, the aerosol will not produce sufficient ice embryos until temperatures colder than -8 oC are reached (Super and Heimbach 2005). Huggins (2009) found the best temperatures for SLW in the Bridger Range Experiment occurred at < -9 ^oC using AgI, which suggests the AgI acted through contact or deposition nucleation. The central reason to explore propane seeding is its characteristic to be effective in mildly supercooled clouds that would be too warm for AgI. Propane dispensers tend to be more reliable, less complicated and less expensive than AgI generators. SLW temperatures in CO frequently range from -4 to -13 oC depending upon location and elevation (Boe and Super 1986; Rauber and Grant 1986; Huggins 1995; Super 2005; Huggins 2009). Due to the mildly supercooled nature of some CO locations, propane could be a useful alternative to AgI generators (Boe and Super 1986; Hindman 1986). The cloud base in California is often warmer than 0 ^oC while the top of the SLW near the mountain crest is usually > -12 oC (Heggli et al. 1983; Heggli and Rauber 1988; Huggins 2009). This is why propane was adopted by Reynolds (1995) as the seeding agent of choice in the Lake Oroville Runoff Enhancement Program (LOREP) in northern California (see Figure 1.4b). 

Cloud base altitude is an important consideration when siting propane dispensers which must be in-cloud or just below cloud base (at ice saturation) to be effective (Super 2005). Super and Heimbach (2005) indicate that even in the intermountain region, a significant number of hours with SLW are at temperatures where the release of AgI at elevations below -5 oC and out of cloud would not reach elevations cold enough to activate a sufficient quantity of the AgI to effectively “seed” the cloud and produce meaningful increases in snowfall. Thus, the 300 to 600 hours of reported SLW over the intermountain region during the 5 month snowfall season would require a mixture of seeding delivery methods including a mixture of high elevation ground released AgI and liquid propane or seeding from multiple aircraft. 

All weather helicopters with ceilings above 20,000 feet ASL  might be useful for targeting small watersheds when shallower clouds are present.

1.7.2 Transport and Dispersion of Seeding Material

1.7.2.1 Ground Releases 

Flow over complex terrain is not a simple and straightforward problem therefore making targeting a challenge. Trying to disperse AgI from ground based generators has proven to be very difficult (Super and Heimbach 2005). There are two critical issues here. One is whether a parcel of air starting out near the foothills or a valley location will be carried over the mountain in the prevailing wind direction or whether it will flow around the mountain. This is determined by the static stability of the air mass and the strength of the flow perpendicular to the mountain, often noted by the Froude number. When the velocity of the flow is strong enough to overcome the air parcels static stability, a Froude number greater than 1 is produced, meaning the parcel of air will pass over the mountain and not flow around the mountain. The depth of the boundary layer is also very important as ground based cloud seeding efforts are located within this layer. If AgI is released below cloud or at temperatures warmer than -5 oC, the aerosol will have to be carried up into the cloud to a level where the temperature is colder than -8 oC. If the boundary layer is shallow and does not allow the aerosol to reach the appropriate temperature level or that level is reached very near the crest of the mountain, there will be no impact on the windward slopes of the mountain. The depth of the boundary layer is a function of low level wind shear (Xue 2014), which is the change in direction or velocity of wind with height. The stronger the wind shear, the greater the depth of the boundary layer. Strong low level flow perpendicular to the mountain, along with strong wind shear and at times weak embedded convection, will provide the mechanism for lifting the aerosol up the mountain. This allows dispersal of the aerosol to seed more cloud volume. If the temperatures are cold enough and SLW is continuous, an increase in snowfall will occur on the windward slopes and increase the precipitation efficiency of the orographic cloud. The targeting issue has been described by many weather modification researchers (Super and Heimbach 2005; Reynolds 1988; Warburton et al. 1995a and b) as the single most critical issue that has compromised the success of both operational as well as research field projects. Again, reason to emphasize that effective cloud seeding is an engineering problem. 

It has been shown that ample seeded crystals with sufficient concentration need to be dispersed so that a substantial volume of cloud over the target is treated for more than trace snowfall rates to occur (Super 2005; Huggins 2009). The seeding material must be injected into the SLW in sufficient quantities to generate 50 to 100/L or more initial ice embryos. This will then utilize the available SLW and fall out of the cloud prior to the snowflakes passing over the summit of the mountain and sublimating in the lee of the mountain. An example of the use of a rather simple targeting model (GUIDE, Rauber et al , 1988) used in the Lake Oroville Runoff Enhancement Project (LOREP ) to target ground-based liquid propane seeding effects is shown in Figure 1.7. This project used the tracer SF6 co-released with the propane from two sites to validate the GUIDE and assure accurate targeting. The GUIDE plumes as shown both horizontally and vertically along with the vertical motion field from a locally released rawinsonde. 1.7.2.2 Seeding from Valley Locations Many operational cloud seeding projects have placed AgI generators in valley locations as they are easily accessible and can be manually ignited when needed. However, a considerable body of evidence indicates valley released AgI plumes are often trapped by stable air (high static stability), especially when valley-based inversions are present (Langer et al. 1967; Rhea 1969-cited but does not appear in Reynolds references; Super 2005). Often times in past projects AgI plumes from valley located generators were not tracked sufficiently to determine exactly where the aerosol plumes drifted (Smith and Heffernan 1967; Super 2005). As noted earlier, this is a recurring issue that has been raised in many winter orographic cloud seeding articles ( Elliott et al. 1978u, Rangno 1979u; Reynolds 1988; Super 2005; Hunter 2007; Huggins 2009). The aerosols may pool in the valley or may move in a direction around the mountain, only to be carried aloft when the static stability of the airmass decreases and low level winds increase. This usually occurs near and behind the surface cold fronts associated with winter storms. Thus, the AgI aerosol may travel far distances from the target but is unlikely to have appreciable effects far from a target due to the low concentrations that eventuate after many hours or days of travel. 

1.7.2.4 Seeding from Airplanes or Helicopters

Seeding by aircraft can be an alternative mechanism in locations where there is insufficient time to activate the seeding agent and grow the crystals to sufficient size for fallout to occur on the windward slopes of the barrier. These situations mainly occur within coastal mountains where the SLW near the crest of the mountain is only slightly sub-cooled. Typically the clouds extend up to a kilometer above and well upwind of the crest such that cloud top temperatures are -6 oC to -8 oC or lower. In these situations, the aircraft or helicopter can fly (hover above) in the tops of the clouds and either drop crushed dry ice, AgI droppable flares, or ignite AgI wing-tip generators or stationary flares that will directly inject the seeding material into the cloud. The dispersion would be especially enhanced in the downwash below a helicopter. Using crushed dry ice or droppable flares will create a curtain of ice crystals some 1000 m below the aircraft. This will spread at a rate of 1-2 m/s dependent upon the amount of vertical wind shear (Borovikov et al. 1961u, Hill 1980; Reynolds 1988). For these seeding curtains to merge together over the intended target area, the length of the seed line cannot be more than 30 to 40 km long (Deshler et al. 1990). However, the watershed of a large river basin can be several hundred kilometers wide. One aircraft will treat only a small portion of the watershed (see Figure 1.8). In addition, the duration of the seeding aircraft is usually about 2 to 4 hours, with the possibility of the aircraft having to descend to deice several times during the seeding mission. Aircraft operations are also expensive. For these reasons, many operational seeding programs use ground based seeding platforms, even if they are only viable a small percentage of the time. 

1.7.4 Extended Area Effects fromWinter Orographic Cloud Seeding (ones that have not been sufficiently investigated for lucky draws/synoptic biases)

The reason why I added this to the title is that I deem this part of the survey the weakest part.  No one talks about how low the concentrations of AgI would be in far away, so-called downwind affected regions, and god save anyone who looks at synoptics for a bias! Meltesen et al.(1978) did look at synoptic bias for the claimed downwind seeding increases from Climax and look what they found;  a synoptic bias that produced the illusion of downwind increases in snow!

Hunter (2009) prepared an extensive literature review of the current state of knowledge on extra or extended area effects from winter orographic cloud seeding. The main impetus for this report was to present any documented evidence that determined that seeding on one mountain barrier resulted in a possible reduction of the amount of precipitation downwind. This has been coined “Robbing Peter to pay Paul”. Hunter provided the following table which is reproduced here (not all references are included in Section 6). In every case, the seeding agent was silver iodide. These results indicate that once the AgI nuclei are released into the atmosphere, they can remain active for many hours, if not several days. If pooled in high concentrations, the AgI nuclei can seed areas well away from the intended target areas. However, the impacts of these extra-area effects are just as uncertain as the increase documented in the primary target areas. That is, without strong physical observations to compare with rigorous statistical analyses, there is still a significant level of uncertainty as to the efficacy of seeding with AgI to increase precipitation within large areas outside the intended target area. 

Table 1.2 here

The little bit of seeding (hour long pulses) or in six h blocks during the last season of the Park Range Project, made this claim ludicrous.  By 1979 it was recognized that a Type I statistical error (Mielke 1979u) affected both Climax experiments.  One of the interesting facets of Climax I that  prevented the seeding researchers from recognizing a Type I error was attributing heavier snow on seeded days upwind of Climax to seeding at Climax (Kahan et al. 1969u) 

1.7.5 Statistical Analyses

Statistical analyses have been a key part of assessing past cloud seeding experiments. Credence has usually only been given to those experiments that have been randomized and run as a confirmatory experiment. Key historical projects such as Climax and the series of Israeli cloud seeding experiments run as confirmatory, and meeting or exceeding the level of statistical significance set out in the experimental design, have come under further scrutiny and found to suffer from what is called Type 1 errors (Mielke 1979u; Rhea 1983; Rangno and Hobbs 1987u, 1993; Rangno and Hobbs 1995a,u,  b; Rosenfeld 1997, Rangno and Hobbs 1997a,u, b u).

Rosenfeld’s (1997) “Comments” cited by Reynolds were replied to by Rangno and Hobbs (1997a,u) in short form, and “Comprehensively” at the Cloud and Aerosol Research Group’s website. This dual approach was favored by Professor Peter V. Hobbs.

http://carg.atmos.washington.edu/sys/research/archive/1997_comments_seeding.pdf

Its surprising that Dr. Reynolds did not know of our responses to Dr. Rosenfeld’s many specious comments

============================

Some background on the Israeli work I did: these many exchanges led the Israel National Water Authority to form an independent panel to evaluate its operational seeding program targeting Lake Kinneret (aka, Sea of Galilee), Israel’s primary water source (Y. Goldreich, 2018, personal communication). The expert panel  that was constituted could find no evidence of increased rain the in the catchment of Lake Kinneret between 1975 and 2002  (Kessler et al. 2006).  The independent panel’s findings reversed the optimistic findings of Nirel and Rosenfeld (1995) of a statistically significant 6% increases in rain through 1990. The panel could also not replicate the 6% increase reported by Nirel and Rosenfeld using the same control stations.  Here is what Kessler et al. (2006) reported in graphical form. 

Why is this Israeli discussion important in Reynolds’ review?

The preliminary findings shown in this figure caused Rosenfield to immediately look for an “out,” and with more than 500 standard gauges and 82 recording gauges in Israel (!)  he found it by cherry-picking and claiming what Reynolds suggests in his review: air pollution was decreasing rain as much as cloud seeding was increasing it.  Givati and Rosenfeld’s conclusions did not stand up to independent investigators as was documented earlier, nor by the subsequent investigations for California cited by Reynolds.

This is typical in scientific statistical testing. It is considered less incorrect to not detect a relationship when one exists rather than detect a relationship when one does not exist. Other statistical methods, such as the use of covariates, can be useful in determining the statistical success of seeding operations (Dennis 1980; Mielke et al. 1981; Gabriel 1999; Gabriel 2002; Huggins 2009). A problem common to the statistical method of historical regression is the assumption that climate has been stable over many decades (Hunter 2007) which is called stationarity, and not declaring covariates in advance of experimentation.

1.8 Summary 

From the information summarized above it is worth reviewing the key questions as outlined for winter orographic clouds as listed in Table 1.1. 

What is the location, duration, and degree of supercooling of cloud liquid water in winter orographic clouds? 

•Concentrated in the lowest km on the windward slopes of mountain (Super andHeimbach, 2005)

•Highly variable in space and time given fluctuations in wind speed/direction and naturalprecipitation processes.

•Higher concentrations and higher frequency of SLW at warmer (sic) (higher) temperatures for all mountain ranges•SLW >.05 mm vertical integrated has been used as lower threshold for cloudseeding initiation.

Are their man-made pollutants or natural aerosols/particulates impacting the target clouds that could modify the cloud droplet spectra/IN concentrations to impede seeding effectiveness? 

•Pollutants acting as CCN can narrow the droplet spectrum and slow down the collision coalescenceprocess (warm rain) reducing rainfall downwind of major pollution sources.(Rosenfeld 2000; Givati and Rosenfeld 2004; Givati and Rosenfeld 2005.  See earlier discussion of the latter report.)

•It was found in SCPP that SIP (secondary ice production) produced high ice concentrations at relatively high cloud top temperatures (-5 to -10 ^oC)

•If pollutants narrow the droplet spectrum, then pollutants in theory should reduce SIP.

Mossop (1978u) found that increases in small (<14 um diameter) droplets combined with those >23 um diameter increased the efficiency of the riming-splintering process.  So it is possible, with the presence of larger droplets say, due to seaborne or other large aerosols combined with pollution sources, that the Hallett-Mossop riming-splintering process is enhanced.

•If high concentrations of pollution produce high concentration of cloud droplets in a narrow size range, this could reduce riming and reduce snowfall on the windward slopes of narrow mountain ranges where growth times are critical.

•A more recent survey article on the role of pollution on clouds and precipitation (Tanre’, 2009) concluded it was still uncertain as to the magnitude of the impact of pollution or whether pollution increases or decreases precipitation based on the meteorological setting.

•Dust (Saharan and Gobi desert) and aerosols (bacteria) acting as IN can enhance natural s

Are their significant enough differences in maritime influenced winter orographic clouds versus continental orographic clouds that strongly influence the natural precipitation process? 

•Yes. Maritime clouds with broader drop size distributions are subject to SIP and thus clouds are more efficient at higher temperatures.

•Continental clouds have relatively more SLW at lower temperatures given the lack of SIP.

•Evidence of this is well-documented when one compares SCPP and Washington studies with interior mountain studies.

====================End of Comments and Corrections  by ALR==========================

References that were uncited in the Reynolds review but were mentioned in this “review and enhancement.”

Alpert, P., N. Halfon, and Z. Levin, 2008: Does air pollution really suppress precipitation in Israel?  J. Appl. Meteor. Climatology, 47, 943-948.

Alpert, P., N. Halfon, and Z. Levin, 2009:  Reply to Givati and Rosenfeld.  J. Appl. Meteor. Climatology, 48, 1751-1754.

Auer, A. H., D. L. Veal, and J. D. Marwitz, 1969: Observations of ice crystals and ice nuclei observations in stable cap clouds.  J. Atmos. Sci., 26, 1342-1343.

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Bartlett, J. P.,  M. L. Mooney, and W. L. Scott, 1975:  Lake Almanor cloud seeding program.  Preprint, San Francisco Conference on weather modification, Amer. Meteor. Soc., 106-111.

Benjamini, Y, A. Givati, P. Khain, Y. Levi, D. Rosenfeld, U. Shamir, A. Siegel, A. Zipori, B. Ziv, and D. M. Steinberg, 2023:  The Israel 4 Cloud Seeding Experiment: Primary Results.   J. Appl. Meteor. Climate, 62, 317-327.  https://doi.org/10.1175/JAMC-D-22-0077.1

Borovikov, A. M., I. I. Gaivoronsky, E. G. Zak, V. V. Kostarev, I. P. Mazin, V. E. Minervin, A. Kh. Khrgian and S. M. Shmeter, 1961:  Cloud Physics. Gidrometeor. Izdatel. Leningrad. (Available from Office of Tech. Serv., U. S. Dept. of Commerce.)

Cooper, W. A., and G. Vali, 1981:  The origin of ice in mountain cap clouds.  J. Atmos. Sci., 38, 1244-1259.

Cunningham, R. M., 1957:  A discussion of generating cell observations with respect to the existence of freezing or sublimation nuclei.  In Artificial Stimulation of Rain, H. Weickmann, Ed.  Pergamon Press, NY.,  267-270.

Elliott, R. D., R. W. Shaffer, A. Court, and J. F. Hannaford, 1978:  Randomized cloud seeding in the San Juan Mountains, Colorado.  J. Appl. Meteor., 17, 1298–1318.

Foster, K. R., and P. W. Huber, 1997: Judging  Science–Scientific Knowledge and the Federal Courts.  The MIT Press, Cambridge, MA, 333pp.

Grant, L. O., and P. W. Mielke, Jr., 1967: A randomized cloud seeding experiment at Climax, Colorado 1960-1965.  Proc. Fifth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 5, University of California Press, 115-131.

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Halfon, N., Z. Levin, P. Alpert, 2009:  Temporal rainfall fluctuations in Israel and their possible link to urban and air pollution effects.  Environ, Res. Lett., 4, 12pp. doi:10.1088/1748-9326/4/2/025001

Hobbs, P. V., and A. L. Rangno, 1979: Comments on the Climax randomized cloud seeding experiments.   J. Appl. Meteor., 18, 1233-1237.

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Rangno, A. L., and P. V. Hobbs, 1987: A re-evaluation of the Climax cloud seeding experiments using NOAA published data.  J. Climate Appl. Meteor., 26,  757-762.

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https://doi.org/10.1175/1520-0450(1997)036%3C0272:R%3E2.0.CO;2

Rangno, A. L. and P. V. Hobbs, 1997b: Comprehensive Reply to Rosenfeld, Cloud and Aerosol Research Group, Department of Atmospheric Sciences, University of Washington, 25pp.  http://carg.atmos.washington.edu/sys/research/archive/1997_comments_seeding.pdf

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Vardiman, L, and J. A. Moore, 1978: Generalized criteria for seeding winter orographic clouds. J. Appl. Meteor., 17, 1769-1777.

PROLOGUE

Below is the impressive list of “Scientific Reviewers” of this volume before this belated review by yours truly happened, ones listed in the 2009 Springer book,  “Aerosol Pollution Impacts on Precipitation:  A Scientific Review.”  The authors of this book, including Chapter 8, had to review an enormous amount of literature which the reviewers also had to know in great detail.

From a reading of this book in those areas of my expertise, such a task is too much despite the authors’ valiant efforts to “get it right.”  Chapter 8  is an example of the problem of having too much to review and not enough time to scrutinize the details of so much literature in one topic.  Chapter 8 is well-written, most of the necessary citations are in it that help the reader to understand the topic.    It does an outstanding job of making a case about the, “Parallels and Contrasts” in deliberate seeding and aerosol pollution.  That is,  except for those elements in Chapter 8 that I am perhaps, a little too familiar with and feel must be addressed in this VERY belated review.

“Too familiar?”

That’s what happens to someone who has spent thousands of volunteer hours (crackpot alert!) rectifying faulty cloud seeding and cloud claims in peer-reviewed journal articles because he felt, “Someone has to do something about this!” (Second crackpot alert, possibly with megalomaniacal implications.)

It goes without saying that I was not asked to review Chapter 8 before it was published.  This would have made these comments unnecessary.  I was well known by the authors of this review as an expert on clouds, cloud seeding, and the weather in the two regions where landmark experiments are reviewed in Chapter 8; those in Colorado and Israel .   With Professor Peter V.  Hobbs in tow, I dissected those landmark experiments in Colorado and Israel and showed they were, as Foster and Huber (1997) described faulty science,  “scientific mirages.”  In fact, they were “low-hanging fruit” that poor peer reviews of manuscripts had let in the journals.  It didn’t take a genius to unravel them.

I read this chapter only recently after I was given the book by one of its authors.  I wondered if Chapter 8 had been reviewed at all by any of the illustrious reviewers listed by Springer since some oversights are so egregious.  However, I was pleased to see that almost all of my work with Prof. Hobbs on those benchmark experiments was cited, except the one I deemed most important.  Odd.

Some background 

Chapter 8 was originally assigned to Prof. Peter V. Hobbs, the director of my group at the University of Washington.  He was going to use portions of a rejected manuscript of mine on cloud seeding  and peer-review entitled, “Cloud Seeding and the Journal Barriers to Faulty Claims: Closing the Gaps.”  He described the segments he was going to use, the rise and fall of the Colorado and Israeli cloud seeding experiments, as, “pretty good.”   Peter was not easy to please.  That was the highest compliment I had ever received from him for my writing.   The manuscript, submitted in 1997,  was ultimately rejected in 1999 by the Bull. Amer. Meteor. Soc., I. Abrams, Editor,  and again in an updated version by  Advances in Meteorology in 2017 as “not the kind of paper we were looking for” in their issue on weather modification (L. Xue, Editor, personal communication).    But maybe its the kind you were looking for!  So, in a sense that manuscript has been rejected twice, sometimes the sign of something especially good.   (Off topic! Get Back, “Jojo,” as the Beatles sang.

Due to pancreatic cancer, Prof. Hobbs was unable to do this piece chapter and Prof. William R. Cotton, Colorado State University, who later has become a close friend,  took over with the additional “contributors” according to Springer,  Dean Terblanche, Zev Levin, Roelof Bruintjes, and Peter Hobbs, as listed by Springer, and all of whom I greatly admire, making these comments “difficult;” “Why am I doing this?”  Etc.

For review purposes, I have copied under the rubric of “fair use,” only those portions of Chapter 8 relevant to my expertise.   To repeat, overall, its a good review.  However, I have added commentaries in a red font following the original statements of the authors (black font) that need clarification, correction, or additions.  References to relevant articles that went uncited in Chapter 8 have been added at the end of this review and are appended with a “u” for uncited.  I have added after those all the references that WERE cited in this review and appear in the original text.  Mielke (1976) cited by the authors, does not appear in the list of their references.

========================================

List of illustrious reviewers of the Springer volume:

Chairperson: Dr.George Isaac, Environment Canada.                       (Name, affiliation, country).

Ayers, Greg,  CSIRO Marine and Atmospheric Research, Australia

Barth, Mary, National Center of Atmospheric Research, USA

Bormann, Stephan,  Johannes-Gutenberg-University, Germany

Choularton, Thomas, University of Manchester, UK.

DeMott, Paul, Colorado State University, USA.

Flossmann, Andrea, Laboratoirede Mitiorologie Physique/OPGC Universiti: Blaise Pascal/C RS, France

Kahn, Ralph, Jet Propulsion Laboratory, USA

Khain, Alexander, The Hebrew University ofJerusalem, Israel

Leaitch, Richard, Environment Canada, Canada

Pandis, Spyros, University of Patras, Greece

Rosenfeld, Daniel, The Hebrew University ofJerusalem, Israel.

Ryan, Brian, CSIRO Marine and Atmospheric Research, Australia

Twohy, Cynthia, Oregon State University, USA.

Vali, Gabor, University of Wyoming, USA.

Yau,  Peter, McGill University, Canada

Zipser, Ed, University of Utah, USA

=============================================

….and now, very belatedly reviewing Chapter 8, yours truly, the less illustrious,  Arthur L. Rangno,  retiree,                                                                                                                                                                                                Research Scientist IV, Cloud and Aerosol Research Group, Atmospheric Sciences Department, University of Washington, USA:

================

Chapter 8 in Aerosol Impacts on Precipitation:“Parallels and Contrasts Between Deliberate Cloud Seeding and Aerosol Pollution Effects”

8.1    Deliberate cloud seeding, with the goal of increasing precipitation by the injection of specific types of particles into clouds, has been pursued for over 50 years. Efforts to understand theprocesses involved have led to a significant body of knowledge about clouds and about the effects ofthe seeding aerosol. A number of projects focused on the statistical evaluation of whether a seeding effect can be distinguished in the presence of considerable natural variability. Both the knowledge gained from these experiments, and the awareness of the limitations in that understanding, are relevant to the general question of aerosol effects on precipitation. Definite proof from the seeding projects for an induced increase in precipitation as a result of the addition of seeding material to the clouds would represent a powerful demonstration of at least one type of dominant aerosol­ precipitation link in the clouds involved. Therefore, in this chapter we review the fundamental conceptsof cloud seeding and overview the parallels and contrasts between evaluations of deliberate and inadvertent modification of precipitation by aerosols. It is not our intent to provide a comprehensive assessment of the current status of cloud seeding research. We direct the reader to more compre­hensive weather modification assessments in NRC (2003), Cotton and Pielke (2007), Silverman (2001, 2003),and Garstang et al. (2005).

Deliberate cloud seeding experiments can be divided into two broad categories: glaciogenic seeding and hygroscopic seeding. Glaciogenic seeding occurs when ice-producing materials (e.g. dry ice (solid CO2), silver iodide, liquid propane etc.) are injected into a supercooled cloud for the purpose of stimulating precipitation by the ice particle mechanism (see Sect. 2.2). The underlying hypothesis for glaciogenic seeding is that there is commonly a deficiency of natural ice nuclei and therefore insufficient ice particles for the cloud to produce precipitation as efficiently as it would in the absence of seeding.

The second category of artificial seeding experiments is referred to as hygroscopic seeding. In the past this type of seeding was usually used for rain enhancement from warm clouds (see Cotton 1982 for a review of early hygroscopic seeding research).

However, more recently this type of seeding has been applied to mixed phase clouds as well. The goal of this type of seeding is to increase the concentration of collector drops that can grow efficiently into raindrops by collecting smaller droplets and by enhancing the formation of frozen raindrops and graupel particles. This is done by injecting into a cloud (generally at cloud base) large or giant hygroscopic particles (e.g., salt powders) that can grow rapidly by the condensation of water vapour to produce collector drops (see Sect. 2.3).

Static Glaciogenic Cloud Seeding

Static cloud seeding refers to the use of glaciogenic materials to modify the microstructures ofsupercooled clouds and precipitation. Many hundreds of such experiments have been carried over the past 50 years or so. Some are operational cloud seeding experiments (many of which are still being carried out around the world) which rarely provide sufficient information to decide whether or not they modified either clouds or precipitation. Others are well designed scientific experiments that provide extensive measurements and modeling studies that permit an assessment of whether artificial seeding modified cloud structures and, if the seeding was randomized, the effects of the seeding on precipitation. While there still is some debate of what constitutes firm “proof”(see NRC 2003; Garstang et al. 2005) that seeding affects precipitation, generally it is required that both strong physical evidence of appropriate modifications to cloud structures and highly significant statistical evidence be obtained.

My comprehensive, “critical” review and enhancement of NRC 2003 is here.  Compared to the 1973 NRC review, the NRC 2003 one was merely a superstructure, a Hollywood movie set, not the real deal.  

The reason?  

Too much literature to review in depth even for the illustrious authors of the NRC 2003 report.   Professor Garstang did ask my boss, Prof. Peter V. Hobbs to participate in the 2003 review, but he declined the offer telling me that it would be better if we “commented” on the 2003 review after it was published if necessary.  I nodded and went back to my desk.  Peter usually knew best.  Fate intervened.  Peter came down with pancreatic cancer and our review  of the 2003 report never happened until I got to it years later.

• Glaciogenic Seeding of Cumulus Clouds

The static seeding concept has been applied to supercooled cumulus clouds and tested in a variety of regions. Two landmark experiments (Israeli I and Israeli II), carried out in Israel, were described in the peer-reviewed literature. The experiments were carried out by researchers at the Hebrew University of Jerusalem (HUJ), hereafter the experimenters. These two experiments were the foundation for the general view that under appropriate conditions, cloud seeding increases precipitation (e.g. N.R.C. 1973; Sax et al. 1975; Tukey et al. 1978a, b; Simpson 1979; Dennis 1980; Mason 1980,1982; Kerr 1982; Silverman 1986; Braham 1986; Cotton 1986a, b; Cotton and Pielke 1992, 1997; Young1993).

Nonetheless, reanalysis of those experiments by Rangno and Hobbs (1993-sic) suggested that the appearance of seeding-caused increases in rainfall in the Israel I experiment was due to “lucky draws” or a Type I statistical error.

The correct year for Rangno and Hobbs is 1995, not 1993 .   Having the wrong year in a reference is a not a good sign right off the bat.  

The first evidence for a lucky draw in Israeli I was presented by Wurtele (1971u) when she reported that the little seeded Buffer Zone between the two targets exhibited the greatest statistical significance in rainfall in either target on Center seeded days.  Wurtele (1971u) quoted the Israeli I chief meteorologist that the Buffer Zone could only have been inadvertently seeded but 5-10% of the time, and “probably less.”  Wurtele should have been cited.  The wind analysis when rain was falling at the launch site near the BZ in Rangno and Hobbs (1995) supports the chief meteorologist’s view.  It would have taken a very bad pilot to have seeded the BZ if he had been instructed not to.

Furthermore, Rangno and Hobbs (1993 sic) argued that during Israel II naturally heavy rainfall over a wide region encompassing the north target area gave the appearance that seeding caused increases in rainfall over the north target area.

The first evidence for naturally heavy rain over a wide region in Israel II, including both targets on north target seeded days, was presented by Gabriel and Rosenfeld (1990u), a critical article  that somehow that went uncited by the authors of Chapter 8.   Gabriel and Rosenfeld stated that the degree of heavy rain on north target seeded days in the south target, from a historical study, was “clearly statistically significant.” 

Rangno and Hobbs (1995) added to that evidence by analyzing rainfall over wide region that included Lebanon and Jordan on north target seeded days.  The Rangno and Hobbs (1995) analysis corroborated the statement by Gabriel and Rosenfeld (1990) concerning a lopsided draw on north target seeded days of Israeli II that affected most of Israel.  In fact, the greatest apparent effect of cloud seeding on north target seeded days was in the south target at Jerusalem (Rangno and Hobbs 1995)!

Deeply troubling, too,  is why the “full results” of the Israeli II experiment by Gabriel and Rosenfeld (1990u) was not cited in a supposed review of those experiments.  The null result of the “full analysis” of Israel II which incorporated random seeding in the South target,  had been omitted in previous reporting by Gagin and Neumann (1976u, 1981).  The “full” results reported by Gabriel and Rosenfeld (1990u) was an extremely important development:  Israeli II had not replicated Israeli I when evaluated in the same way.  Furthermore, the a priori design of Israeli II specified by the Israel Rain Committee mandated that a crossover evaluation be carried out (Silverman 2001).

However, the null result of Israeli II left some questions in the minds of Gabriel and Rosenfeld (1990u).  Were actual rain increases in the north canceled out by decreases in rain on seeded days in the south target resulting in a null overall result?

This idea was later posited by Rosenfeld and Farbstein (1992) as a valid explanation and the disparate results was attributed to dust/haze.  This hypothesis ignored the fact that unusually heavy rain fell on the south target when the north was being seeded.   This left little chance for the south target’s seeded days to overcome this lopsided disadvantage, thus  leaving the impression that seeding had decreased rainfall when rainfall on the control and seeded days in the south target were compared.  Why this was not clear remains a puzzle.

At the same time, lower natural rainfall in the region encompassing the south target area gave the appearance that seeding decreased rainfall over that target area. But this speculation could not explain the positive effect when the north target area was evaluated against the north upwind control area.

Levin et al. 2010u (and unavailable to these authors) also reanalyzed Israeli II and found that a synoptic bias had produced the misperception of seeding effects downwind from the coastal control region mentioned above.    Levin et al’s 2010u conclusions corroborated the Rangno and Hobbs (1995) evaluation of Israeli II described inappropriately as “speculation” by the authors of Chapter 8.  

Details of this controversy can be found in the March 1997 issue of the Journal of Applied Meteorology (Rosenfeld 1997; Rangno and Hobbs 1997a; Dennis and Orville 1997; Rangno and Hobbs1997b; Woodley 1997; Rangno and Hobbs 1997c;  Ben-Zvi 1997; Rangno and Hobbs 1997d; Rangno and Hobbs 1997e). Some of these responses clarified issues; others have left a number of questions unanswered.

The authors should have indicated for the reader what questions were left unanswered.  

However, the exchanges between pro-seeding partisans and Rangno and Hobbs (1997) were extremely important because they led the Israel National Water Authority to form an independent panel of experts to ascertain what the result of operational seeding of the watersheds around Lake Kinneret (aka, Sea of Galilee) was over the decades.  Operational seeding began during the 1975/76 rain season.

The reports of the independent panel (Kessler et al. 2002u, 2006u) were apparently unknown to the authors of this review.  Key elements of the final 2006 report were reprised by Sharon et al. (2008u):  Twenty-seven winter seasons  (75/76 through 01/02)  of operational seeding had not led to an indication that rain had been increased, due to cloud seeding,  an astounding result considering the cost of seeding for so long a period.

Below is a graphical presentation of the independent panel’s findings in their 2006 final report:

Figure 1. The results of operational seeding on the watersheds of Lake Kinneret (aka, Sea of Galilee) as reported by Kessler et al. 2006.  (a) is that result of seeding on rainfall reported by Nirel and Rosenfeld (1995), b-d are the results found for various periods, including the very same era evaluated by Nirel and Rosenfeld (1995).[1]

————-footnote———-

[1] The findings of Kessler were challenged by seeding partisans at the HUJ and who claimed that “air pollution” was decreasing rain as much as cloud seeding was increasing it.  While this was a convenient explanation, it was not found credible by many subsequent independent investigators, including by Kessler et al. (2006).

—————————continuing with Chapter 8————–

8 Deliberate Cloud Seeding and Aerosol Pollution Effects

It is interesting to note that in the Israeli experiments the effects of artificial seeding with silver iodide appeared to be an increase in the duration of precipi­ tation, with little if any effect on the intensity of precipitation (Gagin 1986; Gagin and Gabriel 1987), a finding compatible with the “static” seeding hypothesis.

The ersatz Colorado State University cloud seeding experiment results had exactly the same outcome as those described above in Israel.  In retrospect, the duration findings from both the Colorado and Israeli scientists were huge red flags that a natural bias on seeded days had occurred in these experiments as was shown in later reanalyses by external skeptics (e.g., Rhea 1983u, Rangno and Hobbs 1987).

Givati and Rosenfeld (2005) wrote, “that cloud seeding with silver iodide enhances precipitation especially where the orographic enhancement factor (see Chapter 6) was the largest. Likewise, the pollution effects reduced precipitation by the greatest amount at the same regions”. They suggestedthat this is because the shallow and short-living orographic clouds are particularly susceptible to such impacts. This suggests that attempts to alter winter precipitation should be concentrated on orographic clouds. Or interpreted in terms of inadvertent modification of clouds; winter orographic clouds may be the most susceptible to precipitation modification by pollution.

The Israeli “experimenters,” who cost their government so much in wasted cloud seeding effort, could not walk away and apologize for their misguided findings and withheld results.  So Givati and Rosenfeld (2005) generated the argument that pollution was exactly canceling out cloud seeding effects!  Of course, the air pollution argument was nonsense, the result of cherry picking amid the 500 or so Israeli rain gauges in Israel.   Here’s what the uncited Kessler et al. (2006u) report had to say about the Givati and Rosenfeld (2005) claims about air pollution:

“No supporting evidence was found for the thesis of Givati and Rosenfeld (2005) regarding the decline in the Orographic precipitations (sic) due to the increase of air pollution.”

The air pollution claims by Givati and Rosenfeld (2005), while superficially credible,  except for their sudden hypothesized appearance that canceled out cloud seeding effects, were also evaluated by several independent groups and scientists in later publications not available to the authors of this review:  Alpert et al. (2008u); Halfon et al. (2009u);  Levin (2009u), Ayers and Levin (2009u).  All these independent re-analyses and reviews of the hypothesized effect of air pollution on rainfall found the argument that air pollution had canceled seeding-induced increases in rain unconvincing.

This also suggests that the conceptual model on which the Israeli cloud seeding experiments was based is not exactly as postulated. The seeding was originally aimed at the convective clouds that formed over the narrow coastal plain, with the intent of nucleating ice crystals and forming graupel earlier in the cloud life cycle (Gagin and Neumann 1974), thus leading to increased rainfall in the catchment basin of the Sea of Galilee to the east of the Galilee Mountains. However, the report of Givati and Rosenfeld (2005) concluded that “cloud seeding did not enhance the convective precipitation, but rather increased the orographic precipitation on the upwind side of the Mountains, probably by the Bergeron-Findeisen process.”

The above is not what Kessler et al. (2006u) concluded.   It was a shame that the authors did not know about Kessler et al.’s report.

To update this review, the idea posited by Rosenfeld and Givati (2005) about seeding orographic clouds, promoted by these authors, was tested in Israel-4, a seven season randomized experiment (Benjamini et al. 2023u).  Seeding in the orographic north of Israel resulted in no viable effect on rainfall.  This should not be surprising.

The lack of enhancement of the convective clouds in Israel might be explained by their tendency to mature and dissipate inland during the winter storms. Seeding of mature convective clouds cannot affect them much. The lack of enhancement is also consistent with the microphysically maritime nature of the convective clouds.

The authors seem to be unaware that for decades the cloud seeding experimenters had reported in their many publications that the clouds of Israel were “continental” in nature (e.g., Gagin and Neumann 1974, 1976u, Gagin 1975u), that is, they contained high droplet concentrations that made them extremely “un-maritime.”  This in turn helped generate scientific consensus that seeding such clouds had produced viable results on rainfall  in Israeli I and Israeli II because it was hard for them to rain and needed cloud seeding  (e.g., Kerr 1982, Silverman 1986, Dennis 1989).

This appears to be caused mainly due to the natural hygroscopic seeding by sea spray or mineral dust particles coated with soluble material (Levin et al.1996, 2005) in the winter storms that enhance the warm precipitation (Rosenfeld et al. 2001) as well as promoting the formation of ice hydrometeors that is followed by ice multiplication (Hallett and Mossop 1974).

In a surprising oversight in a supposed “scientific review,” the authors do not cite Rangno (1988) who described so long ago the clouds of Israel as we know them today; ones that rain via warm rain processes and precipitate regularly via the ice process when top temperatures are >-10°C, all contrary to the many reports of the cloud seeding experimenters (e.g., Gagin 1986).

Moreover, it has not been satisfactorily determined why the Israeli cloud seeding experimenters could not discern the natural precipitating characteristics of their clouds with all the tools available to them for so many decades.  Did the wind not blow over the Mediterranean during Israeli I and II, thus did not “maritimize” clouds when Prof. Gagin was observing them with his radars and sampling them with his research aircraft?

I spent 11 weeks in Israel from early January through mid-March 1986 studying the precipitating nature of Israeli clouds. I spoke with Israel Meteorological Service forecasters, and the chief forecaster of the Israeli randomized experiments.   Not surprisingly, they were all aware of the natural character of their rain clouds that so eluded the cloud seeding researchers at the HUJ; faulty descriptions of clouds were published by HUJ seeding researchers repeatedly in peer-reviewed journals.  How did this happen?

These suggestions are supported by the results of glaciogenic cloud seeding in Tasmania, which targeted a hilly area by seeding along an upwind coastline. The seeding in Tasmania was shown to enhance precipitation from the stratiform orographic clouds, but not from the convective clouds (Ryan and King 1997). This is consistent with the microphysical conclusions of Rangno and Hobbs (1993 sic), who asserted that, cloud seeding as done in Israel could not have possibly caused the statistically documented rain enhancement from the convective clouds there.

Again, the correct year for Rangno and Hobbs is 1995.  

The minimal amount of cloud seeding in Israeli I should have been discussed. The experimenters realized this post facto of Israel-1 and added a second seeding aircraft and no less than 42 ground generators (NRC 1973) when conducting Israel II.  The difference in released seeding material in Israeli II from the ~1000 grams released in all of Israeli I (Gabriel and Neumann (1967) has to be stupefying and raises questions.

Do the authors of this chapter really think that only 70 h of line seeding by a single aircraft upwind of each target per whole Israeli rain season could have produced a statistically significant result in rainfall in Israeli I?  Do they know that the coverage of convective clouds with rising air below cloud base is spotty,  that the rain that comes into Israel from the Mediterranean are “tangled masses” in various life cycle stages  (as described by Neumann et al. 1967)? 

Recently, Givati and Rosenfeld (2005) carried out a study in which the effects of pollution on rainfall suppression in orographic clouds were separated from the effects of cloud seeding in Israel. They concluded that the two effects have the opposite influence on rainfall, demonstrating the sensitivity of clouds to anthropogenic aerosols of different kinds. By analyzing the rainfall amounts in northern Israel during the last 53 years during days in which no seeding was carried out, they observed a decreasing trend of the orographic factor R₀ (discussed in Chapter 6) with time from the beginning of the study. They associated this decrease with the increase in aerosol pollution. The same trend, but shifted upward by 12-14%, was observed for days in which seeding was carried out. Thus, it appears that the opposing effects of air pollution and seeding appear to have nearly canceled each other.

The air pollution canceling cloud seeding claims by Rosenfeld and colleagues have not been deemed credible to those who have investigated them, listed previously.  

Another noteworthy experiment was carried out in the high plains of the U.S. (High Plains Experiment (HIPLEX-1) Smith et al.(1984).Analysis of this experiment revealed the important result that after just 5 min, there was no statistically significant difference in the precipitation between seeded and non-seeded clouds, (Mielke et al. 1984). Cooper and Lawson( 1984) found that while high ice crystal concentrations were produced in the clouds by seeding, the cloud droplet region where the crystals formed evaporated too quickly for the incipient artificially produced ice crystals to grow to appreciable sizes. Instead, they formed low density, unrimed aggregates having the water equivalent of only drizzle drops, which were too small to reach the ground before evaporating. Schemenauer and Tsonis( 1985) affirmed the findings of Cooper and Lawson in a reanalysisof the HIPLEX data emphasizing their own earlier findings (Isaac et al. 1982) that cloud lifetimes were too short in the HIPLEX domain for seeding to have been effective in the clouds targeted for seeding (i.e. Those with tops warmer than -12°C). Although the experiment failed to demonstrate statistically all the hypothesized steps, the problems could be traced to the physical short lifetimes of the clouds (Cooper and Lawson 1984; Schemenauer and Tsonis 1985). This in itself is a significant result that shows the ability of physical measurements and studies to provide an understanding of the underlying processes in each experiment. The results suggested that a more limited window of opportunity exists for precipitation enhancement than was thought previously.  Cotton and Pielke (1995) summarized this window of opportunity as being limited to: Clouds that are relatively cold-based and continental; Clouds with top temperatures in the range -1O° to-25°C, and a timescale confined to the availability of significant supercooled water before depletion by entrainment and natural precipitation processes.

Today, this window would even be viewed as too large, since many cold based continental clouds with tops>-25°C have copious ice particle concentrations(e.g., Auer et al. 1969u, Cooper and Saunders 1980u, Cooper and Vali 1981u, Grant et al. 1982u.  These references were added to make them more appropriate for inland mountain locations). The HIPLEX results also indicated that small clouds make little contribution to rainfall.

This begs the question, should we expect a similar window of effectiveness for inadvertent IN pollution?

 8.1.1. Seeding Winter Orographic Clouds

The static mode of cloud seeding has also been applied to orographic clouds. Precipitation enhancement of orographic clouds by cloud seeding has several advantages over cumulus clouds. The clouds are persistent features that produce precipitation even in the absence of large-scale meteorological disturbances. Much of the precipitation is spatially confined to high mountainous regions thus making it easier to set up dense ground based seeding and observational networks. Moreover, orographic clouds are less susceptible to a “time window” as they are steady clouds that offer a greater opportunity for successful precipitation enhancement than cumulus clouds. A time window of a different type does exist for orographic clouds, which are related to the time it takes a parcel of air to condense to form supercooled liquid water and ice crystals while ascending to the mountain crest.

Missing in this discussion is the time that ice forms in orographic clouds after the leading edge forms as a droplet cloud. Ice particles have been shown to form a short distance downwind at surprisingly high temperatures as reported by Auer et al (1969u), Cooper and Vali (1981u).  

What then is the effect of introducing ice by AgI at an upwind edge where ice is already going to form immediately downwind in those situations?  Does this case represent a productive seeding possibility?  This scenario should have been discussed by the Chapter 8 authors.

The special case described here of non-precipitating clouds, where cloud seeding will be effective without question is not quantified.  How often do they occur, and how thick are they?  What is their cloud top temperature?  Are bases low enough so that the light, seeding-induced snowfall will reach the ground?  Will it be enough to justify the cost of seeding, by ground or aircraft?

The Chapter 8 authors were not aware of Rangno (1986u) who displayed the rapid changes in cloud characteristics that made seeding even orographic clouds problematic due to those changes in cloud top temperatures and in wind directions over periods of just 3-4 hours.

So many questions, so few answers by the authors, elements that point to the extreme difficulty of proper reviews in any field in meteorology!

If winds are weak, then there may be sufficient time for natural precipitation processes to occur efficiently. Stronger winds may not allow efficient natural precipitation processes but seeding may speed up precipitation formation. Stronger winds may not provide enough time for seeded icecrystals to grow to precipitation before being blown over the mountain crest and evaporating in the sinking sub saturated air to the lee of the mountain. A time window related to the ambient winds, however, is much easier to assess in a field setting than the time window in cumulus clouds.

The landmark randomized cloud seeding experiments at Climax, near Fremont Pass, Colorado (referred to as Climax I and Climax II), Colorado, reported by Grant and Mielke(1967) and Mielke et al.( 1970,1971) suggested increases in precipitation of 50% and more on favorable days (e.g. Grant and Mielke 1967; Mielke et al. 1970,1971), and the results were widely viewed as demonstrating the efficacy of cloud seeding (e.g. NRC 1973; Sax et al. 1975; Tukey et al. l978a, b; American Meteorological Society 1984),even by those most skeptical of cloud seeding claims(e.g. Mason 1980,1982). Nonetheless, Hobbs and Rangno (1979), Rangno and Hobbs (1987, 1993) question both the randomization techniques and the quality of data collected during those experiments and conclude that the Climax II experiment failed to confirm that precipitation can be increased by cloud seeding in the Colorado Rockies.

It appears that these cited critical papers by the present writer were not read by the authors of this review.  Hobbs and Rangno (1979), a study originated and carried out by the second author, demonstrated that the claims about a physical foundation for the Climax experiments were bogus.  These important findings was left out of the discussion above.   The experimenters had claimed out of thin air (Grant and Mielke 1967) that the stratifications by 500 mb temperatures were reliably connected to cloud top ones.

Moreover, the precipitation per day (PPD) does not decrease at Climax (or elsewhere in the Rockies) after a 500 mb temperature of -20°C is exceeded as the experimenters claimed (e.g., Grant et al. 1969u, 1974u, Chappell 1970u).  Rather, the PPD continues to increase at temperatures above -20°C as shown in Rangno 1979, Hobbs and Rangno (1979).   The decrease in PPD that occurred during Climax I when the 500 mb temperature was >-20° C was indicative of a bias in the draw on the Climax I control days rather than representative of PPD climatology. 

Hobbs and Rangno (1979) further demonstrated that the master’s thesis repeatedly invoked by the experimenters in support of the 500 mb/cloud top temperature correspondence claim (e.g., Grant and Elliott 1974) did no such thing,  but rather proved just the opposite.  This was due to the way that meteorological data were assigned to experimental days by the experimenters (i. e., as described by Fritsch in Grant et al. 1974u).   Critical papers were not read by the authors.  Q. E. D.

Quoting the authors from their paragraph above:  “the quality of the data collected during those experiments”.

This is a euphemism for what Rangno and Hobbs (1987) found.

The experimenters repeatedly described the NOAA-maintained recording gauge in the center of the Climax target as “independently” collected data (e.g., Mielke et al. 1970).  Rangno and Hobbs simply went to the NOAA hourly precipitation data publication for Colorado and used those data to evaluate the Climax experiments. Those published data were not the same as those used by the experimenters. 

The experimenters had, in fact, reduced the recording charts at that key gauge in Climax II themselves as revealed by Mielke 1995, and in doing so, helped the seeded day cases (Rangno and Hobbs 1987).  Climax II, not so lucky in its storm draw on seeded days as Climax I, was plagued by “helpful” errors.  Thirty-two of 43 differences in precipitation between that used by the experimenters and that in the NOAA publication helped the seeded cases.  The chance that such results came from an unbiased source can be rejected at a P value of 0.0001.

Climax I, however, benefitting from a storm draw on seeded days that favored the appearance of a cloud seeding effect in its first half of conduct,  had virtually no errors in data.

What do we make of this?  Circle the wagons? 

Or come to a logical conclusion that someone helped the Climax experiment replicate Climax II?  At this time, mid-way through Climax II, the Bureau of Reclamation’s cloud seeding division had begun spending hundreds of thousands of dollars on the planning of the Colorado River Basin Pilot Project.  There was, therefore, enormous pressure on the experimenters to have Climax II replicate Climax I.  

We let the reader decide what may have happened.

———-

Inexplicably, the authors of this chapter omit the reanalysis of Mielke et al. (1981) by Rhea (1983u).  Indeed, this author’s own independent reanalysis of the Climax experiments (rejected in 1983) was partially because reviewers’ thought Rhea’s reanalysis, simultaneously under review and that came to the same result, was more robust.  Rhea showed that the mismatch between the time the control gauges were read and when the Climax target gauges were read resulted in the false impression that Climax II had replicated Climax I.  When the gauges were synchronized by Rhea (1983u), the Climax II seeding increases disappeared (as they also did using the published NOAA data in Rangno and Hobbs (1987).

A background note:  Grant et al. 1983u, however, strongly criticized the Rhea reanalysis before it was published.  Rhea altered his reanalysis along the lines suggested by Grant et al. prior to publication.  Nevertheless, Grant et al. did not revise their published comment to account for Rhea’s revisions.  Grant, in a personal note to Rhea at that time, did not know why he and his group had not altered their criticism of Rhea’s revised manuscript.

The published record concerning Rhea’s reanalysis is, therefore confusing; the experimenters appeared to critique Rhea’s paper while not actually doing so.

Even so, in their reanalysis, Rangno and Hobbs(1993) did show that precipitation increased by about 10% in the combined Climax I and II experiments.

First, the so-called “10% increase in precipitation for all of the Climax I and II experiments was “built in” by the choice of control stations mid-way through Climax I by the experimenters  as demonstrated in Rangno and Hobbs (1993).   We are sure the authors did not read that 1993 paper.  Control stations should have been selected prior to the Climax I experiment as good design demands.  Otherwise, the temptation to cherry-pick control stations that prove what the experimenters already believe becomes too big a temptation and that is surely what happened in Climax I at the half-way point.

If the seeding effect is real, it will continue following a cherry-picked group of control stations.  If there is no further sign of seeding, as shown in “Climax 1B,” the second half of Climax I by Rangno and Hobbs (1993) then we know that the gauges were picked because it showed what the experimenters believed before the experiment even began.  The lack of any sign of an effect of cloud seeding on precipitation continued through all of Climax II as well (Rangno and Hobbs 1993).

Finally, 1000 re-randomizations of the Climax data performed by the University Washington Academic Computer Center by Irina Gorodnoskya (unpublished data) showed that the 10% claimed increase in precipitation by the authors above was in the noise of these experiments.  It should not be quoted as an increase in snow due to seeding as the authors do here.

This should be compared, however, to the original analyses by Grant and Mielke (1967), Grant and Kahan (1974), Grant and Elliott (1974), Mielke et al. (1971), Mielke et al. (1976) and Mielke et al. (1981) that indicated greater than 100% increase in precipitation on seeded days for Climax I and 24% for Climax II.

Two other randomized orographic cloud seeing experiments, the Lake Almanor Experiment (Mooney and Lunn 1969) and the Bridger Range Experiment (BRE) as reported by Super and Heimbach (1983) and Super (1986) suggested positive results.

Of concern is that the “cold westerly” case in Phase I of the Lake Almanor experiment, where large seeding effects were reported was not reported in Phase II (Bartlett et al. 1975).   Also, the large increases (40%) in snow  reported in Phase I for cold westerly cases, is suspect since such clouds are likely to develop high natural ice particle concentrations naturally.  The Lake Almanor Phase I  is badly in need of a reanalysis by external skeptics;  its results should not be taken at face value.

 However, these particular experiments used high elevation AgJ generators, which increase the chance that the Agl plumes get into the supercooled clouds. Moreover, both experiments providedphysical measurements that support the statistical results (Super and Heimbach 1983, 1988).

There have been a few attempts to use mesoscale models to evaluate cloud seeding programs. Cottonet al. (2006) applied the Colorado State University Regional Atmospheric Modeling System(RAMS)to thesimulation of operational cloud seeding in the central Colorado Mountains in the 2003-2004 winterseason. The model included explicit representation of surface generator production of Agl at thelocations, burn rates, and times supplied by the seeding operator. Moreover, the model explicitlyrepresented the transport and diffusion of the seeding material, its activation, growth of icecrystals and snow,and precipitation to the surface. Detailed evaluation of model forecast orographicprecipitation was performed for 30 selected operational seeding days. It was shown that the model could be a useful forecasting aid in support of the seeding operations. But the model over-predictednatural precipitation, particularly on moist southwest flow days. The model also exhibited virtually no enhancement in precipitation due to glaciogenic seeding. There are a number of possiblecauses for the lack of response to seeding, such as over prediction of natural precipitation, which prevented the effects of seeding from being seen. In addition, the background CCN and INconcentrations are unknown, therefore lower CCN concentrations than occurred would make the cloudsmore efficient in precipitation production, thus reducing seeding effectiveness.

Finally, Ryan and King(1997) reviewed over 14 cloud seeding experiments covering much of southeastern, western,and central Australia, as well as the island of Tasmania. They concluded that static seeding over the plains of Australia is not effective. They argue that for orographic stratiform clouds, there is strong statistical evidence that cloud seeding increased rainfall, perhaps by as much as 30% over Tasmania when cloud top temperatures are between -10 and -l2°C in southwesterly airflow. The evidence that cloud seeding had similar effects in orographic clouds overthe mainland of southeastern Australia is much weaker. Note that the Tasmanian experiment had bothstrong statistical and physical measurement components and thus meets, or at least comes close to meeting, the NRC (2003) criteria for scientific “proof.” Cost/benefit analysis ofthe Tasmanian experiments suggests that seeding has a gain of about 13:1. This is viewed as a real gain to hydrologic energy production.

A complication revealed in the analysis of some of the Australian seeding experiments is thatprecipitation increases were inferred one to three weeks following seeding in several seedingprojects(e.g. Bigg and Turton 1988). Bigg and Turton ( I988) and Bigg ( 1988, 1990, 1995) suggestedthat silver iodide seeding can trigger biogenic production of additional ice nuclei. The latter research suggests that fields sprayed with silver iodide release secondary ice nuclei particles at intervals of up to ten days.

In summary, the “static” mode of cloud seeding has been shown to cause the expected alterations incloud microstructure including increased concentra­ tions of ice crystals, reductions of supercooled liquid water content, and more rapid production of precipitation elements in both cumuli (Isaac et al.1982; Cooper and Lawson 1984)and orographic clouds(Reynolds and Dennis 1986; Reynolds 1988;Super andBoe 1988; Super et al. 1988; Super and Heimbach 1988). The documentation of increases in precipitation on the ground due to static seeding of cumuli, however, has been far more elusive, with the Israeli experiment (Gagin and Neumann 1981) providing the strongest evidence that static seeding of cold-based, continental cumuli can cause significant increases of precipitation on the ground.  

Tukey et al. (1978b, Appendendix C, pC.1) wrote:   “The strongest evidence for rainfall enhancement involving the seven latest substantial experiments this task force has studied seems today to be that from the two Israeli experiments….”  The statement in blue (highlighted by this writer) which is almost the exact wording as that found in Turkey et al. (1978b) 30 years before the Springer book was published) is troubling indeed.    The assessment by Turkey et al. in 1978 was valid; it was not valid 30 years later when so much water has gone under the bridge concerning the Israeli cloud seeding experiments (or,  “too little water” due to cloud seeding).

Moreover,  citing Gagin and Neumann (1981) in 2009 as the strongest evidence in support of cloud seeding as they do,  demonstrated that the authors of this review were not aware of,  nor understood the literature in the topic they are supposedly reviewing.  The omission of critical literature by the authors as was proof of this assertion.

Why wasn’t I asked to review this manuscript in advance of publication since I am well-known as an expert on both the Colorado and Israel clouds, weather, and cloud seeding experiments?  Moreover, the authors of this review knew this.

The evidence that orographic clouds can cause significant increases in snowpack is far more compelling, particularly in the more continental and cold-based orographic clouds (Mielke et al. 1981; Super and Heimbach 1988).

The authors omit Rhea’s 1983u reanalysis of Mielke et al. 1981 and that of Rangno and Hobbs (1987) in remarking that “significant increases in snowpack” have been compellingly shown by Mielke et al. 1981.

Update to the orographic seeding claim above by the authors:  The NCAR Wyoming experiment, completed in 2013 (Rasmussen et al. 2018u), could find no viable evidence that seeding from ground generators had increased precipitation after six seasons of randomized seeding.

Perhaps, however, the most challenging obstacle to evaluating cloud seeding experiments to enhance precipitation, is the inherent natural variability of precipitation in space and time, and the inability to increase precipitation amounts to better than ~10%. This last obstacle puts great demands on the measuring accuracy and the duration of the experiments. Shouldn’t we expect similar obstacles in evaluating inadvertent effects of IN pollution on precipitation?

A well-stated description of the problem.

===================================================

 List of references mentioned in the critical review that were uncited by the authors, or are relevant papers for an enhancement of Chapter 8 that were unavailable to these authors because they were published after Chapter 8 appeared.

Alpert, P., N. Halfon, and Z. Levin, 2008: Does air pollution really suppress precipitation in Israel?  J. Appl. Meteor. Climatology, 47, 943-948.

Alpert, P., N. Halfon, and Z. Levin, 2009:  Reply to Givati and Rosenfeld.  J. Appl. Meteor. Climatology, 48, 1751-1754.

Auer, A. H., D. L. Veal, and J. D. Marwitz, 1969: Observations of ice crystals and ice nuclei observations in stable cap clouds.  J. Atmos. Sci., 26, 1342-1343.

Ayers, G., and Levin, 2009:  Air pollution and precipitation.  In Clouds in the Perturbed Climate System.  Their Relationship to Energy Balance, Atmospheric Dynamics, and Precipitation. J. Heintzenberg and R. J. Charlson, Eds.  MIT Press, 369-399.

Bartlett, J. P., M. L. Mooney, and W. L. Scott, 1975:  Lake Almanor Cloud Seeding Program.  Preprint, Weather Modification Conference, San Francisco, 106-110.

Benjamini, Y, A. Givati, P. Khain, Y. Levi, D. Rosenfeld, U. Shamir, A. Siegel, A. Zipori, B. Ziv, and D. M. Steinberg, 2023:  The Israel 4 Cloud Seeding Experiment: Primary Results.   J. Appl. Meteor. Climate, 62, 317-327.  https://doi.org/10.1175/JAMC-D-22-0077.1

Chappell, C. F.,  1970:  Modification of cold orographic clouds.  Atmos. Sci. Paper No. 173, Dept. of Atmos. Sci., Colorado State University, Fort Collins, 196pp.

Cooper, W. A., and C. P. R. Saunders, 1980:  Winter storms over the San Juan mountains.  Part II:  Microphysical processes.  J. Appl. Meteor., 19, 927-941.

Cooper, W. A., and G. Vali, 1981:  The origin of ice in mountain cap clouds.  J. Atmos. Sci., 38, 1244-1259.

Dennis, A. S., 1989: Editorial to the A. Gagin Memorial Issue of the J. Appl. Meteor., 28, 1013.  No doi.

Gabriel, K. R., and Y. Neumann, 1978:  A note of explanation on the 1961–67 Israeli rainfall stimulation experiment.  J. Appl. Meteor., 17, 552–556.

Gabriel, K. R., and Rosenfeld, D., 1990: The second Israeli rainfall stimulation experiment: analysis of precipitation on both targets. J. Appl. Meteor., 29, 1055-1067.  https://doi.org/10.1175/1520-0450(1990)029%3C1055:TSIRSE%3E2.0.CO;2

Grant, L. O., DeMott, P. J., and R. M. Rauber, 1982:  An inventory of ice crystal concentrations in a series of stable orographic storms.  Preprints, Conf. Cloud Phys., Chicago, Amer. Meteor. Soc. Boston, MA. 584-587. No doi.

Grant, L. O., J. G. Medina, and P. W. Mielke, Jr., 1983:  Reply to Rhea. J. Climate Appl. Meteor., 22, 1482–1484.

Grant, L. O., C. F. Chappell, L. W. Crow, J. M. Fritsch, and P. W. Mielke, Jr., 1974:  Weather modification: A pilot project.  Final Report to the Bureau of Reclamation, Contract 14-06-D-6467, Colorado State University, 98 pp. plus appendices.

Grant, L. O., Chappell, C. F., Crow, L. W., Mielke, P. W., Jr., Rasmussen, J. L., Shobe, W. E., Stockwell, H., and R. A. Wykstra, 1969:  An operational adaptation program of weather modification for the Colorado River basin.  Interim report to the Bureau of Reclamation, Department of Atmospheric Sciences, Colorado State University, Fort Collins, 98pp.  (Available from the Bureau of Reclamation, Library,   Federal Building, Denver, Colorado 80302.

Halfon, N., Z. Levin, P. Alpert, 2009:  Temporal rainfall fluctuations in Israel and their possible link to urban and air pollution effects.  Environ, Res. Lett., 4, 12pp. doi:10.1088/1748-9326/4/2/025001

Kessler, A., A. Cohen, D. Sharon, 2003:  Analysis of the cloud seeding in Northern Israel.  Interim report submitted to the Israel Hydrology Institute and the Israel Water Management of the Ministry of Infrastructure.

Levin, Z., N. Halfon, and P. Alpert, 2010: Reassessment of rain enhancement experiments and operations in Israel including synoptic considerations.  Atmos. Res., 97, 513-525.

                        http://dx.doi.org/10.1016/j.atmosres.2010.06.011

Levin, Z., N. Halfon, and P. Alpert: 2011:  Reply to the Comment by Ben-Zvi on the paper “Reassessment of rain experiments and operations in Israel including synoptic considerations” Atmos. Res., 99, 593-596.

Mielke, P. W., Jr., 1995:  Comments on the Climax I and II experiments including replies to Rangno and Hobbs.  J. Appl. Meteor., 34, 1228–1232.

National Research Council, 1973: Weather & Climate Modification: Progress and Problems. National Academy of Sciences, 258 pp., https://doi.org/10.17226/20418.

Neumann, J., K. R. Gabriel, and A. Gagin, 1967: Cloud seeding and cloud physics in Israel:  results and problems.  Proc. Intern. Conf. on Water for Peace.  Water for Peace, Vol. 2, 375-388.  No doi.

Rangno, A. L., 1979:  A reanalysis of the Wolf Creek Pass cloud seeding experiment.   J. Appl. Meteor., 18, 579–605.

Rangno, A. L., 1986:  How good are our conceptual models of orographic clouds?  In Precipitation Enhancement–A Scientific Challenge, R. R. Braham, Jr., Ed., Meteor. Monographs, 43, Amer. Meteor. Soc., 115-124. Invited paper, title assigned by A. S. Dennis.

 https://doi.org/10.1175/0065-9401-21.43.115

Rangno, A. L., 1988: Rain from clouds with tops warmer than -10 C in Israel.  Quart J. Roy. Meteor. Soc., 114, 495-513.

   https://doi-org/10.1002/qj.49711448011

Rasmussen, R. M., S. A. Tessendorf, L. Xue, C. Weeks, K. Ikeda, S. Landolt, D. Breed, T. Deshler, and B. Lawrence, 2018:  Evaluation of the Wyoming Weather Modification Pilot Project (WWMPP) using two approaches:  Traditional statistics and ensemble modeling.  J. Appl. Meteor. and Climate, 57, 2639-2660.

Rhea, J. O., 1983:  “Comments on ‘A statistical reanalysis of the replicated Climax I and II wintertime orographic cloud seeding experiments.'”  J. Climate Appl. Meteor., 22, 1475-1481.

Rosenfeld, D., 1998: The third Israeli randomized cloud seeding experiment in the south: evaluation of the results and review of all three experiments. Preprints, 14th Conf. on Planned and Inadvertent Wea. Modif., Everett, Amer. Meteor. Soc. 565-568. No doi.

Sharon, D., A. Kessler, A. Cohen, and E. Doveh, 2008:  The history and recent revision of Israel’s cloud seeding program.  Isr. J. Earth Sci., 57, 65-69.     https://DOI.org/10.1560/IJES.57.1.65.

Wurtele, Z. S., 1971: Analysis of the Israeli cloud seeding experiment by means of concomitant meteorological variables. J. Appl. Meteor., 10, 1185-1192.    https://doi.org/10.1175/1520-0450(1971)010%3C1185:AOTICS%3E2.0.CO;2

Totality of References  in Chapter 8.1, “Introduction” through 8.2.2 “Seeding Winter Orographic Clouds” 

=================================

American Meteorological Society, 1984: Statement on planned and inadvertent weather modification.  Bull. Amer. Meteor. Soc., 66, 447–448.

Ben-Zvi, A., 1997:  Comments on “A new look at the Israeli randomized cloud seeding experiments.” J. Appl. Meteor., 36, 255-256.

Bigg, E. K., 1988: Secondary ice nucleus generation by silver iodide applied to the ground. J. Appl. Meteor., 27, 453-488.

Bigg, E. K., 1990:  Aerosol over the southern ocean. Atmos. Res., 25, 583-600.

Bigg , E. K., 1995:  Tests for persistent effects of cloud seeding in a recent Australian experiment.  J. Appl. Meteor., 34, 2406-2411.

Bigg, E. K., and E. Turton, 1988: Persistent effects of cloud seeding with silver iodide.  J. Appl. Meteor., 27, 505-514

Braham, Roscoe R., Jr., 1986:  Rainfall enhancement–a scientific challenge.  Rainfall Enhancement–A Scientific Challenge, Meteor. Monogr., 21, No. 43,  1–5.

Cooper, W. A., and R. P. Lawson, 1984:  Physical interpretation of results from the HIPLEX-1 experiment.  J. Climate Appl. Meteor., 23, 523-540.

Cotton, W. R., 1982: Modification of precipitation from warm clouds. A review.  Bull. Meteor. Soc., 63, 146-160.

Cotton, W. R., 1986a: Testing, implementation, and evolution of seeding concepts–a review.  In Precipitation Enhancement–A Scientific Challenge, R. R. Braham, Jr., Ed., Meteor. Monographs, 43, Amer. Meteor. Soc., 63-70.

Cotton, W. R., 1986b: Testing, implementation, and evolution of seeding concepts–a review.  In Precipitation Enhancement–A Scientific Challenge, R. R. Braham, Jr., Ed., Meteor. Monographs, 43, Amer. Meteor. Soc., 139-149.

Cotton, W. R., and R. A. Pielke, 1992:  Human Impacts on Weather and Climate. ASteR Press, 271pp.

Cotton, W. R., and R. A. Pielke, 1995:  Human Impacts on Weather and Climate, 1st edition, Cambridge University Press, 288pp.

Cotton, W. R., and R. A. Pielke, 2007:  Human Impacts on Weather and Climate, 2nd edition, Cambridge University Press, 308pp.

Cotton, W. R., R. R. McAnelly, G. Carrio, P. Mielke, and C. Hartzell, 2006:  Simulations of snowpack augmentation in the Colorado Rocky Mountains.  J. Weather Modification, 38, 58-65.

Dennis, A. S., 1980:  Weather Modification by Cloud Seeding.  Academic Press, 267pp.

Dennis A. S., and H. D. Orville, 1997: Comments on “A new look at tbe Israeli cloud seeding experiments.” J. Appl. Meteor., 36, 277-278

Gagin, A., 1986:  Evaluation of “static” and “dynamic” seeding concepts through analyses of Israeli II experiment and FACE-2 experiments.  In Rainfall Enhancement–A  Scientific Challenge, Meteor. Monogr., 43, Amer. Meteor. Soc., 63–70.

Gagin, A., and K. R. Gabriel, 1987:   Analysis of recording rain gauge data for the Israeli II experiment. Part I:  Effects of cloud seeding on the components of daily rainfall.  J. Climate Appl. Meteor.,  26,   913–926.

Gagin, A., and J. Neumann, 1974: Rain stimulation and cloud physics in Israel. Weather and Climate Modification, W. N. Hess, Ed., John Wiley and Sons,  454–494.

Gagin, A., and J. Neumann, 1981:  The second Israeli randomized cloud seeding experiment: evaluation of results.  J. Appl. Meteor., 20, 1301–1311.

Garstang, M., R. Bruintjes, R. Serafin, H. Oroville, B. Boe, W. R. Cotton, J, Warburton, 2005:  Weather Modification; Finding common ground. Bull. Amer. Meteor. Soc. 86, 647-655.

Givati, A., and Rosenfeld, D., 2005: Separation between cloud-seeding and air pollution effects. J. Appl. Meteor. Climate, 44, 1298-1314.    https://doi.org/10.1175/JAM2276.1

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