A critical review of the design, execution and evaluation of cloud seeding experiments

Transcription

1 A critical review of the design, execution and evaluation of cloud seeding experiments Roelof T. Bruintjes WMA Meeting September 2013, Santiago Research Applications Program, National Center for Atmospheric Research, P.O. Box 3000, Boulder, Colorado,

2 Fundamentals What are clouds made of?

3 Cloud droplets Condensation on hygroscopic particles (a specific kind of water-soluble aerosol) Droplet growth by condensation Condensation occurs through diffusion of water vapor Cloud droplets are typically in the size range of 5-25 µm (i.e., very small) They have a very small terminal velocity Result: No precipitation from only cloud droplets. The water stays in the cloud

4 Warm rain process Collision and coalescence of droplets falling at different terminal velocities leads to raindrop formation Raindrops are millimeters in size Cloud droplets are 100 times smaller in diameter

5 Ice crystals I Ice nuclei are a different kind of aerosol

6 The cold rain process Co-existence of ice crystals and supercooled droplets leads to rapid vapor growth of crystals, followed in suitable convective clouds by accretional growth (riming), fall-out, and melting as rain Graupel

7

8 Microphysical processes in precipitation development Deposition/Evaporation during melting Evaporation/Condensation Autoconversion CLOUD WATER Collection RAIN Condensation Freezing Collection AEROSOLS + WATER VAPOR Riming Melting Collection of ice by rain Riming Collection Evaporation during melting Initiation Deposition Splintering CLOUD ICE Conversion Collection SNOW Deposition Collection Shedding Melting GRAUPEL HAIL Collection Melting PRECIPITATION FALLOUT

9 Total aerosol, cloud condensation nuclei (CCN), and ice nuclei (IN) concentrations as a function of temperature. In order to enhance precipitation the concept of seeding is to seed with appropriate CCN or IN to make precipitation develop more efficiently.

10 Aerosol change: natural and anthropogenic Saharan dust Mexico 1998 Indonesian smoke from fires in 1997 Industries

11 General considerations for planning cloud seeding for rain enhancement Introduction Project Phases Problems to be considered Conclusion

12 Weather modification is: Multidisciplinary & complex technology Dealing with complex and a wide range and scales of meteorological phenomena Often unexpected final results Needs investment and resources

13 It should not be approached as a simple operation but rather a well planned and organized project including: A clearly and quantitatively specified objective Well defined Conceptual Model Appropriate technology and human resources A good evaluation scheme

14 PROJECT PHASES Start Stop Conceptual model Operational Interpretation of the results and conceptual model Design Evaluation Feasibility study Implementation

15 Need Water resources? Reservoirs, ground water CONCEPTION Domestic & Industrial use? Hydropower generation? Important studies Geographical information Conceptual model Literature Other experiences Preliminary investigations Climatological data Microphysical investigations Numerical model simulation

16 The Design Define the general plan for the project including: Objectives and goals Target area Project period Conceptual model and physical hypothesis Operational plan for seeding The data collection system The evaluation scheme

17 Feasibility study Determine the length of the project needed to achieve statistically significant results Statistical simulation Assess the benefit to cost ratio by Assessing the economic impact of any additional water on each use, assuming a given rate of rain increase: 5%, 10%, 15%, etc. Calculating the cost of the project

18 The implementation Perform the project based on an operational plan which includes: The selection criteria for seeding The seeding material and targeting and dispersion system The procedure for data collection Field data checks Monitor and control Equipment and operation Measurements and human resources

19 The evaluation The project evaluation should be considered as multiple aspects: Physical evaluation- as far as possible of the chain of events in the rain process Statistical evaluation of the rain on the ground and its subsequent influences on surface and underground water Economic impact of added water on different uses Post evaluation: Assess other side effects of the project

20 Exploratory Evaluation Assess the possible variation of the seeding response with respect to some physical, meteorological and geographical parameters Data stratification Analyze the rain increase using data subsets constructed after stratification Decision

21 Problems to be considered With respect to: Concept and Design Implementation Evaluation

22 Concept and design

23 Numerical model guidance for design, execution and evaluation of projects

24 Implementation Personnel availability and changes Data collection and quality control Meteorological conditions Drought Severe weather Technical problems Equipment maintenance, spares, etc.

25 Evaluation (1) Physical evaluation Difficulty to detect changes in the chain of events, need of: WHY?: Natural Variability; Limited understanding; etc Highly sophisticated tools, skilled operational crew and good scientists, Rigorous data collection and analysis procedures

26 Evaluation (2) Statistical evaluation Less possibility for good evaluation in case of strictly operational design Need for high density network in case of randomized experiment Radar versus raingauges

27 Evaluation (3) Economic evaluation: Impacts on reservoir and ground water levels Impacts on agricultural practices Annual variability

28 Evaluation Issues Spatial and temporal variability due to meteorological factors has a much greater influence than the enhancement factor (No random draw from the same distribution of potential values; (Beare et al., 2010). Identification of meteorological factors and use as covariates in the analyses (e.g. aerosol loading and thermodynamic profiles). Simple statistical tests insufficient in this environment and multivariate statistical process models that exhibit spatial and temporal dependence are more appropriate than a single test (e.g. aerosol loading).

29 Conclusion Cloud seeding should be planned, implemented and evaluated with the state of the art knowledge. Phasing the project gives a practical and controllable way to conduct a cloud seeding project, Regional scale effort for cloud seeding project is highly desired to share technology, facilities, knowledge, and databases.

30 PRELIMINARY STUDIES WHY? TEMPORAL AND SPATIAL VARIATIONS IN: Climatology of clouds and precipitation in a region Thermodynamic and wind structure of the atmosphere Aerosol and associated microphysical variations

31 Precipitation Processes: QLD Australia example (22 Jan. 2009) Continental cloud droplet spectra at cloud base Coalescence initiates before cloud top reaches 0 o C Drizzle/rain drops present as cloud rises through 0 o C level Temperature versus time 22 January 2009 Images of cloud droplets and drizzle/rain drops Cloud droplet size distributions at cloud base and 0 o C. Due to warm cloud bases (~20 o C) clouds initially develop warm rain process

32 Precipitation Processes: Mixed-phase/ice processes initiated by freezing of large drizzle/rain drops and subsequent initiation of natural seeding (ice splintering) process rapidly depleting cloud liquid water content Large drop freezing at ~-5 o C Initiation of ice splintering process Rapid conversion of LWC to ice Rapid depletion of LWC inhibiting lightning in these cases Temperature versus time 27 January 2009

33 MEXICO (based on Coahuila results) Costo por m 3 de agua adicional precipitado Escenario Volumen producido Volumen aprovechado Costo por m 3 Muy optimista 2,226,300 2,226,300 $ m 3 m 3 Optimista 1,815, ,100 $ m 3 m 3 Pesimista 340,700 m 3 68,140 m 3 $ Muy pesimista 340,700 13,628 $ m 3 m 3 Nota: costos en Mex.$ (2001)

34 New technologies and measurements Numerical models Dual polarization radar data providing new insights Satellite and remote sensor aerosol and cloud measurements providing real-time characterization of the characteristics. New airborne and in-situ measurements to better characterize cloud processes

35 Summary Variations in meteorological conditions can dominate the effects of seeding and are often times much larger than the effect of seeding ( times). These variations can occur in space and in time and can significantly affect the results from any randomized seeding experiments depending on a single statistical test assuming that the samples are randomly drawn from the same distribution of potential values (treatment application for these measurements was at random).

36 Summary cont. More statistically efficient means of analysis are required if we hope to gain significant results in realistic time frames such as multivariate statistical models by including covariates that influence the precipitation processes in a region to control for natural variations in rainfall. In contrast to pure randomization analysis, this type of analysis estimates the conditional contribution to rainfall by meteorological and for example aerosol effects.

37 THE END