Cloud Seeding for Snowfall Enhancement:Cloud Seeding for Snowfall Enhancement:Concepts, Evidence of Effects and New Evaluation Concepts, Evidence of Effects and New Evaluation

TechniquesTechniques

Arlen W. HugginsArlen W. Huggins

Desert Research Desert Research InstituteInstitute

Reno, Nevada, USAReno, Nevada, USA

Cloud Seeding Research SymposiumCloud Seeding Research SymposiumMelbourne, AustraliaMelbourne, Australia

7-9 May 20077-9 May 2007

Cloud Seeding for Snowfall Enhancement:Cloud Seeding for Snowfall Enhancement:Concepts, Evidence of Effects and New Evaluation Concepts, Evidence of Effects and New Evaluation

TechniquesTechniques

Review a conceptual modelReview a conceptual model Details of the steps in the modelDetails of the steps in the model Examples of research resultsExamples of research results Trace chemical evaluation techniquesTrace chemical evaluation techniques Needs in future researchNeeds in future research

A Brief Review of Winter Seeding ConceptsA Brief Review of Winter Seeding Concepts

Seeding material must be reliably producedSeeding material must be reliably produced Seeding material must be successfully transported to Seeding material must be successfully transported to clouds over the intended targetclouds over the intended target

Clouds must contain supercooled liquid water Sufficient dispersion of seeding materialSufficient 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 Seeding material must reach the temperature needed for substantial ice crystal formationfor substantial ice crystal formation

Depends of seeding material Ice crystals must reside in cloud long enough for growth Ice crystals must reside in cloud long enough for growth and fallout over the target areaand fallout over the target area

Conceptual Diagram of Orographic Cloud SeedingConceptual Diagram of Orographic Cloud Seeding

Ground-based seeding with silver iodide

-5C

-10C

Ice-forming Activity of Seeding MaterialsIce-forming Activity of Seeding Materials

InstrumentationInstrumentation

Availability of supercooled liquid waterAvailability of supercooled liquid water

An excess of SLW is needed at relatively cold temperaturesAn excess of SLW is needed at relatively cold temperatures Studies over many mountainous areas have shownStudies 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 temperatureSLW 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 snowfallSeasonal SLW flux often 50 – 100% of seasonal snowfall Suggests significant cloud seeding potential

SLW over a mountain barrierSLW over a mountain barrier

Transport and Dispersion of Seeding MaterialTransport and Dispersion of Seeding Material

Verification of T and D is CriticalVerification 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 verificationMethods 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:T and D Examples:Measurements from a Measurements from a

fixed sitefixed site

Ice Nuclei Counts(NCAR counter)

SLW also verified(Microwave radiometer)

T and D T and D Examples:Examples:

Measurements Measurements from mobile from mobile

platformsplatforms

Tracer gas andice nuclei measurements

Wasatch PlateauAgI seeding froma single site

Plume dimension similar to results in other areas

AircraftDetection

GroundDetection

Cloud Microphysical Responses to SeedingCloud Microphysical Responses to Seeding

Verification of the initiation, growth and fallout of ice crystalsVerification 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 verificationMethod 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 Measurements of microphysical of microphysical

effects from effects from seeding:seeding:

Use of fixed Use of fixed instrument sites, instrument sites,

aircraft instruments, aircraft instruments, and mobile ground-and mobile ground-

based platformsbased platforms

Microphysical Microphysical seeding effect seeding effect

examplesexamples

Wasatch PlateauAgI seeding froma single site

Aircraft data show aerosol and ice crystal seeding plumes

6 km or 16.7 min downwind of seeding site

Microphysical Microphysical seeding effect seeding effect

examplesexamples

Wasatch PlateauAgI seeding froma single site

Aircraft data show aerosol and ice crystal seeding plumes

15 km or 41.7 min downwind of seeding site

23

Microphysical Microphysical seeding effect seeding effect

examplesexamples

2nd Peak Pass 73rd Peak Pass 7

Microphysical seeding effect examples:Microphysical seeding effect examples:An aircraft case studyAn aircraft case study

10 min

19 min

22 min

30 min

39 min

Time afterseeding

Seeding Effects in PrecipitationSeeding Effects in Precipitation

Last link in the “chain” and hardest to verifyLast 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 verificationMethods of verification

Ground-based particle imaging probes Precipitation gauges Radar occasionally useful Statistical assessments of target area precipitation

Radar detection of Radar detection of seeding plumeseeding plume

from Wasatch Plateau from Wasatch Plateau case that documented case that documented aerosol and ice crystal aerosol and ice crystal

plumesplumes

Precipitation from Precipitation from gauges inside and gauges inside and

outside seeding outside seeding plumeplume

Some of the Best EvidenceSome of the Best Evidenceof Precipitation Increasesof Precipitation Increases

Physical evidence from case studiesPhysical 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 evidenceStatistical 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 Summary Points on Wintertime Cloud Seeding ResearchSeeding 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 Use of trace chemistry in evaluating cloud seeding projectsseeding projects

Map of Ag/In Ratios (Almanor in northern Sierra Nevada)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 NevadaTargeting 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 A new evaluation method based on snow chemistry analysis and high resolution precipitation measurementsand high resolution precipitation measurements

• Dual tracer approach using AgI and In2O3

• 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 Targeting Effectiveness for 2005 Season of the Snowy 2005 Season of the Snowy Precipitation Enhancement Precipitation Enhancement Research Project (SPERP)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 Targeting Effectiveness and Estimates of Precipitation Estimates of Precipitation

Increases for 2005 Season Increases for 2005 Season of SPERP (based on snow of SPERP (based on snow

chemistry technique)chemistry technique)

Map shows PRELIMINARY results of estimated precipitation increases (blue circles)

Squares are ground generator sites

Comparison of results from Comparison of results from 2004 and 2005 SPERP 2004 and 2005 SPERP

SeasonsSeasons

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 NeededSome 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