DRI Cloud Seeding Forum - Science and Program History


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DRI Cloud Seeding Forum - Science and Program History

  1. 1. History and Scientific Basis of Cloud SeedingForum on Cloud Seeding in the Humboldt River Basin to Increase Snowpack Reno, Nevada 22 October 2012 Arlen W. Huggins Desert Research Institute Reno, Nevada, USA
  2. 2.  Brief history of cloud seeding Cloud seeding conceptual model Validation of the conceptual model Past and current research Trace chemical evaluation techniques Hydrologic modeling to assess impact onstreamflow Environmental issues Summary
  3. 3. Wintertime Seeding Conceptual Model• Seeding material must be reliably produced• Seeding material must be successfully transported to clouds over the intended target • Clouds must contain supercooled liquid water (SLW)• Dispersion of seeding material • Significant cloud volume must be affected by ice nuclei, so • Significant numbers of ice crystals can be formed• Seeding material must reach the temperature needed for ice crystal formation • Depends on seeding material• Ice crystals must reside in cloud long enough for growth and fallout over the target area
  4. 4. Conceptual Diagram of Orographic Cloud Seeding Ground-based seeding with silver iodide-10C -5C
  5. 5. Past Research• Ice nucleating properties of various substances• Transport and dispersion of seeding material – Mapping plumes with aircraft or mobile ground platforms – Plume dispersion models• Supercooled liquid water measurements – Aircraft sensors, mountain top icing sensors, microwave radiometers• Seeding-induced (microphysical) changes to clouds – In cloud aircraft measurements – Mobile ground-based measurements – Ground-based remote sensing measurements – Inference from trace chemical analysis of snowfall• Seeding-induced changes to precipitation/snowfall – Randomized experiments – Detailed case studies with high-resolution precipitation measurements (gauges or laser imaging probes)
  6. 6. Ice-forming Activity of Seeding MaterialsNote with AgIthat a very smallmass is neededto produce a verylarge number ofice nucleatingparticles
  7. 7. Weather stationPlume of ice controls dispensercrystalsSeeding materials & delivery methods
  8. 8. Availability of supercooled liquid water Seeding potential relies on an excess of SLW 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 can be 50 – 100% of seasonal snowfall  Suggests significant cloud seeding potential
  9. 9. SLW over a mountain barrier
  10. 10. Ag and In Concentrations Radiometer LW Icing Sensor Counts Precipitation TemperatureAssessing conditions for seeding
  11. 11. 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 positioned part way 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
  12. 12. T and D Examples: Measurements Aircraft from mobile Detection platformsWasatch PlateauAgI seeding froma single siteTracer gas andice nucleimeasurements Ground DetectionPlume dimensionsimilar to results inother areas
  13. 13. T and D Examples: Measurements from a fixed siteSeeding plume verified withIce nuclei measurements(NCAR counter)SLW also verified(Microwave radiometer)
  14. 14. Measurements of microphysical effects from seeding: Use of fixed instrument sites, aircraft instruments, andmobile ground-based platforms
  15. 15. DRI Particle Dispersion Model ResultsTwo DRI groundGenerator sitesPart ofDual-tracerIce CrystalEnhancementExperiment
  16. 16. 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
  17. 17. Microphysicalseeding 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
  18. 18. Microphysicalseeding effect examplesWasatch PlateauAgI seeding froma single siteAircraft data showaerosol and icecrystal seedingplumes15 km or 41.7 min downwindof seeding site
  19. 19. Microphysical seeding effect examples:Time after seeding An aircraft case study 10 min 19 min 22 min 30 min 39 min
  20. 20. 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 experiment in UT with significant results – 1-hour seeded periods had ~20% more precipitation than unseeded periods Methods of verification  Ground-based particle imaging probes  Precipitation gauges  Radar occasionally useful  Statistical assessments of target area precipitation
  21. 21. Radar detection of a seeding plumefrom Wasatch Plateaucase that documentedaerosol and ice crystal plumes
  22. 22. Precipitation from gauges inside and outside seeding plumeVertical dashed lines enclose the time period of the seeding effect at each gauge site
  23. 23. 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 the 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
  24. 24. Current Research Projects• Australian Snowy Mountain Project – Funded by Australian government and conducted by Snowy Hydro (power company) – 5-year study with randomized seeding of a single target – Published results showed a statistically significant 14% increase in target precipitation for “seeded” events – Statistical results strongly supported by trace chemical assessment• U. of Wyoming airborne radar study – Radar signal increase noted during seeding periods – Radar signal increase corresponds to a significant precipitation rate increase
  25. 25. Hydrologic Modeling to Assess the Impact of Cloud Seeding HRU Setup for Walker River HRUs outlined in redwere given a 10% seeding impact
  26. 26. Seeded Year Month Precip ET Storage P-Runoff (inches) (inches) (inches) (inches) Hydrologic 2003 2003 10 11 1.029 2.451 0.447 0.459 1.421 3.128 0.470 0.285 Modeling: 2003 2004 12 1 9.512 1.626 0.342 0.396 11.397 12.047 0.900 0.580Simulation of 2004 2 11.132 0.386 22.432 0.361 2004 3 4.048 1.009 23.910 1.561 Seeding 2004 4 1.732 2.427 18.362 4.853 2004 5 0.000 2.765 11.537 4.060 Effects* ************************************************************************* Total 31.530 8.231 11.537 13.070 Not seeded Year Month Precip ET Storage P-Runoff*Estimated at (inches) (inches) (inches) (inches)10% for 2003 10 0.932 0.397 1.262 0.402selected HRU’s 2003 11 2.274 0.463 2.829 0.244 2003 12 8.64 0.348 10.353 0.768 2004 1 1.471 0.401 10.896 0.526 2004 2 10.124 0.388 20.293 0.339 2004 3 3.653 1.02 21.381 1.545 2004 4 1.558 2.386 16.073 4.481 2004 5 0 2.672 9.835 3.566 ************************************************************************* Total 28.652 8.075 9.835 11.871 Difference 2.878 0.156 1.702 1.199 % Difference 10.0 1.9 17.3 10.1
  27. 27. Use of trace chemistry in evaluating cloud seeding projects  The element silver in silver iodide has a very low background concentration in natural snowfall (~4 PPT).  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.
  28. 28. Trace chemical response to seeding during an Australian experimentAg is part of the ice nucleant (AgI)In is an non-ice nucleating tracer A ratio of Ag to In that exceeds one indicates ice nucleation by AgI is contributing to the snowfall
  29. 29. 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 also validated by physical measurements New modeling (atmospheric and hydrologic) and radar methods being used to evaluate cloud seeding projects Trace chemical techniques used to validate targeting and the process of ice nucleation by seeding