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