Cloud Seeding for Snowfall Enhancement: Concepts, Evidence of Effects and New Evaluation Techniques Arlen W. Huggins Desert Research Institute Reno, Nevada, USA Cloud Seeding Research Symposium Melbourne, Australia 7-9 May 2007

Cloud Seeding for Snowfall Enhancement: Concepts, Evidence of Effects and New Evaluation Techniques  Review a conceptual model  Details of the steps in the model  Examples of research results  Trace chemical evaluation techniques  Needs in future research

A Brief Review of Winter Seeding Concepts  Seeding material must be reliably produced  Seeding material must be successfully transported to clouds over the intended target  Clouds must contain supercooled liquid water  Sufficient dispersion of seeding material  Significant cloud volume must affected by ice nuclei, so  Significant numbers of ice crystals can be formed  Seeding material must reach the temperature needed for substantial ice crystal formation  Depends of seeding material  Ice crystals must reside in cloud long enough for growth and fallout over the target area

Conceptual Diagram of Orographic Cloud Seeding Ground-based seeding with silver iodide -5C -10C

Ice-forming Activity of Seeding Materials

Instrumentation

Availability of supercooled liquid water  An excess of SLW is needed at relatively cold temperatures  Studies over many mountainous areas have shown  SLW is present at some stage on nearly every winter storm  SLW exhibits considerable temporal and spatial variability  SLW is found mainly over the windward slope and can extend upwind  Maximum SLW exists from below mountain crest to ~1km above  SLW temperature  Depends a lot on barrier height and geographic location  Rocky Mountains: SLW base -2 to -10 C SLW top -10 to -15 C  Sierra Nevada: SLW base often > 0 C SLW top -12 C or higher  Seasonal SLW flux often 50 – 100% of seasonal snowfall  Suggests significant cloud seeding potential

SLW over a mountain barrier

Transport and Dispersion of Seeding Material  Verification of T and D is Critical  Documented in several research studies of 1970s, 1980s and 1990s  Key element in success of randomized Bridger Range experiment  Consistently successful T&D from high altitude generators  Generators at least halfway up the windward slope  Methods of verification  Aircraft or ground-based detection of tracer gases  Aircraft or ground-based ice nucleus counters  Dispersion models for feasibility assessments (with verification)  Trace chemical analysis of snowfall from the target

T and D Examples: Measurements from a fixed site Ice Nuclei Counts (NCAR counter) SLW also verified (Microwave radiometer)

T and D Examples: Measurements from mobile platforms Tracer gas and ice nuclei measurements Wasatch Plateau AgI seeding from a single site Plume dimension similar to results in other areas Aircraft Detection Ground Detection

Cloud Microphysical Responses to Seeding  Verification of the initiation, growth and fallout of ice crystals  Strong evidence from ground-based seeding experiments in Bridger Range (MT), Grand Mesa (CO) and Wasatch Plateau (UT)  Significant IC enhancement (>5x background) found in seeding plumes  Best evidence found in cloud regions colder than -9 C with cloud tops warmer than -20 C.  Method of verification  Aircraft or ground-based particle imaging probes  Aircraft detection required flying within 300 m of mountain peaks  Ground-base instruments at fixed location, or mobile

Measurements of microphysical effects from seeding: Use of fixed instrument sites, aircraft instruments, and mobile ground- based platforms

Microphysical seeding effect examples Wasatch Plateau AgI seeding from a single site Aircraft data show aerosol and ice crystal seeding plumes 6 km or 16.7 min downwind of seeding site

Microphysical seeding effect examples Wasatch Plateau AgI seeding from a single site Aircraft data show aerosol and ice crystal seeding plumes 15 km or 41.7 min downwind of seeding site 2 3

Microphysical seeding effect examples 2 nd Peak Pass 7 3 rd Peak Pass 7

Microphysical seeding effect examples: An aircraft case study 10 min 19 min 22 min 30 min 39 min Time after seeding

Seeding Effects in Precipitation  Last link in the “chain” and hardest to verify  Physical evidence from ground-based seeding experiments on the Grand Mesa (CO) and Wasatch Plateau (UT)  Statistical evidence from randomized experiments in Bridger Range and northern Sierra Nevada – supporting physical evidence  One randomized propane case in UT with significant results  Methods of verification  Ground-based particle imaging probes  Precipitation gauges  Radar occasionally useful  Statistical assessments of target area precipitation

Radar detection of seeding plume from Wasatch Plateau case that documented aerosol and ice crystal plumes

Precipitation from gauges inside and outside seeding plume

Some of the Best Evidence of Precipitation Increases  Physical evidence from case studies  Wasatch Plateau (UT) experiments (1990s, 2004)  Ground releases of silver iodide and liquid propane  Precipitation rate increases of a few hundredths to > 1 mm/hour  Grand Mesa (CO) 1990s  Ground and aircraft releases of silver iodide  Precipitation rates in seeded periods >> than unseeded periods  Statistical results with supporting physical evidence  Bridger Range randomized experiment (1970s)  Double ratio analysis showed 15% increase in target  Increases in target were much greater in cold storms  Increases of 15% found within a few km of the source  Lake Almanor randomized experiment (1960s)  Statistically significant increase found with cold storm category  Supported by later trace chemical evaluations

Summary Points on Wintertime Cloud Seeding Research  All the links in the chain of the conceptual model have been verified in physical case studies  Ice crystal and precipitation enhancement have been verified through physical observations  Precipitation enhancement has been documented by statistical methods in several projects where results were validated by physical measurements  Research has revealed situations when cloud seeding is ineffective  Research has not supplied all the answers to every meteorological situation where cloud seeding is applied

 The element silver in silver iodide has a very low background concentration in snowfall.  Analyzing target area precipitation for evidence of Ag above background is one means of evaluating targeting effectiveness.  In a randomized seeding project using a target and control design trace chemistry can be used to verify that the control area is unaffected by seeding.  Can be used to address environmental concerns regarding Ag in snow, soil, water supplies, etc.  Non-ice nucleating particles used in combination with AgI can be used to differentiate between nucleation and scavenging processes in target area snowfall.  A seeding material ‘tagged’ with a trace element can be used to differentiate between seeding methods, like aircraft versus ground seeding. Use of trace chemistry in evaluating cloud seeding projects

Map of Ag/In Ratios (Almanor in northern Sierra Nevada) Ag/In ratio > 1 indicates Ag was removed by nucleation process

Targeting Effectiveness for Project in southern Sierra Nevada Map shows percentages of snow samples with Ag above background during the 1994 season Triangles are ground generator sites Primary Target

A new evaluation method based on snow chemistry analysis and high resolution precipitation measurements Dual tracer approach using AgI and In 2 O 3 Snow profile sites collocated with high resolution (~0.01 inch or less) recording precipitation gauges Trace chemical analysis defines sites with and without seeding effects (Ag/In ratio > expected) Gauge records used to define time period of seeding effect Profile without seeding effect used as no-seed (control) site –Analogous to comparing precipitation measurements inside and outside documented seeding plume locations –Trace chemistry is used to define the “plume” Similar time periods compared at “seeded” and “non-seeded” sites to compute the enhancement at the seeded site Technique can (potentially) be applied on a storm-by-storm basis and results integrated over a target area for an entire season

Targeting Effectiveness for 2005 Season of the Snowy Precipitation Enhancement Research Project (SPERP) Map shows percentages of snow samples with Ag/In ratio above expected value Squares are ground generator sites Primary Target

Targeting Effectiveness and Estimates of Precipitation Increases for 2005 Season of SPERP (based on snow chemistry technique) Map shows PRELIMINARY results of estimated precipitation increases (blue circles) Squares are ground generator sites

Comparison of results from 2004 and 2005 SPERP Seasons  2005 season had overall better targeting than 2004  2005 precipitation enhancement estimates were higher, but data quality was lower  2005 precipitation estimates were based on Ag/In vs ∆P relationship found in 2004

Some Thoughts on What is Still Needed  An evaluation of new or existing projects (which have not done so) to document the steps in the conceptual model  Conduct additional randomized experiments – the number with significant results and supporting physical data is quite small particularly in the past 20 years  Relatively small scale experiments to keep costs down  Use accepted statistical methods to determine the magnitude of seeding effects – predictor variables to strengthen the analyses and reduce the number of experiments needed  Support statistical studies with observations sufficient to allow understanding of the physical processes  Make use of advances in modeling and remote sensing to further our understanding of natural and/or modified cloud and precipitation processes