MICROPHYSICAL AND PRECIPITATION FORMATION PROCESSES AND RADAR SIGNATURES

Transcription

1 MICROPHYSICAL AND PRECIPITATION FORMATION PROCESSES AND RADAR SIGNATURES 4 TH International Workshop on Weather Modification 3 rd Workshop on Cloud Physics October 2010 Daegu, Korea

2 Projects Current cloud physics and radar-upgrade projects Recent int l projects involving equipment/software tech transfer, training, and outreach in the cloud physics/convective storm arena. Italy and Greece: Upgrade radar infrastructure, observational project training Mexico: Radar upgrades for NAME, previous rainfall studies Burkina Faso: Upgrade radar infrastructure and training Saudi Arabia and UAE: aerosol cloud interactions Indonesia: Infrastructure building and aerosolcloud interactions Argentina: software upgrades for hail studies

3 WEATHER MODIFICATION

4 Distribution of Ice and Water in a Convective Cloud In the atmosphere temperature decreases 10 o C per km with height in a dry environment and about 6 o C per km in a cloud

5 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

6 The aerosol/precip connection Aerosol environment has changed CCN/sulfates are about 70% anthropogenic with strong variation in emissions geographically Desert dust concentrations vary widely; appear to be important IN Clear anthropogenic effects (e.g., satellite evidence) Well known climate connections Direct (reflect incoming solar radiation back to space) Indirect (modify properties and lifetime of clouds) Linkage to precip understood in principle, but hard evidence is scanty and scattered; we lack quantitative/predictive skill

7 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

8 Precipitation Processes: QLD 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

9 Queensland, Australia Microphysical data16 February 2008 Temp versus time LWC versus time Cloud droplet size distribution Droplet size distribution Droplet concentrations versus time 2DC particle concentrations

10 Microphysical data 16 February DC particle size distribution 2DC particle concentration Temp versus time

11 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

12 Cloud base heights and warm cloud depths during Queensland project 22 November 2008 High cloud base No large drops at 0C First ice below -12C

13 Monthly lightning maps November 2007 to March 2008 Lower frequency of lightning in coastal regions due to potentially less LWC between -10 and -20 o C where naturally most charge buildup occurs

14 Microphysical relationships Total peak droplet concentrations (cm -3 ) as a function of standard deviation of the cloud droplet spectra for the 22 cases when penetrations were conducted in deep convection near cloud base in growing nonprecipitating parts of the cloud. Mean diameter of the cloud base doplet spectra as a function of standard deviation of the cloud droplet spectra for the 22 cases when penetrations were conducted in deep convection near cloud base in growing non-precipitating parts of the cloud.

15 Aerosol-cloud interactions Karnataka India BANGALORE Cloud base

16 Distribution of Ice and Water in a Convective Cloud FREEZING LEVEL IN INDIA CLOUD BASE WARMER THAN 15C In the atmosphere temperature decreases 10 o C per km with height in a dry environment and about 6 o C per km in a cloud

17 Aerosols, CCN and Cloud droplet concentrations (India) High concentrations of droplets due to pollution CCN and aerosol conc.

18 Broadening of cloud droplet spectra by re-circulation CCN effect: Difficult to form rain in clouds

19 Effects on Ice Processes Large drops freezing Secondary Ice Formation Concentrations between 200 to 400L -1 Concentrations: ~5-10L -1 Similar to concentrations of observed large drops POTENTIAL INVIGORATION OF CLOUD GROWTH DUE TO LATENT HEAT OF FREEZING

20 Radar Responses Strong invigoration of radar echo intensities after cloud penetrate below 0 o C Morning, only warm clouds Afternoon, Mixed phase convective clouds

21 COMBINED SATELLITE AND RADAR UAE randomized seeding experiment

22 Precipitation Formation 1. Aerosol size distributions and hygroscopicity 2. Thermodynamic structure of atmosphere 3. Effects on ice processes Three Aspects Capping inversion layers Large CCN?

23 Humidifying experiments with saltmineral aggregates 10% 51% 60% 70% 2 mm 76% 82%

24 Tentative explanation Long period of cumulus growth below the inversion Large dust particles coated with sulfates acting as droplet embryos Recycling of droplets in repeated updrafts and broadening of the spectrum Natural drizzle formation even before the rainstorm breaks through the inversion Efficient ice multiplication process and lots of cold rain in thunderstorms Efficient precip process without seeding Particle images: lots of drizzle drops

25 Lake Matano 40 km 60 km Lake Towuti Watershed Area 2477 km 2

26 CCN and aerosol measurements East coast measurements N CCN =182 S 0.23 N CCN =305 S 0.56 N CCN =1369 S 0.73 N CCN =170 S 0.93

27 Sulawesi microphysical measurements and precipitation processes

28 Sorowako Natural Environment and clouds Aerosol characteristics. Natural and INCO plume

29 INCO plume and rain?

30 Example Research Questions What is the background aerosol concentration: in various places, at different times of the year, during different meteorological conditions? To what extent would weather modification operations be dependent on these background concentrations? Rainmass Rain mass (kton) Mexican Randomized Experiment Q3 Q2 Q Time From Decision South African Experiment Time from decision

31 Aerosol and non-aerosol days classification for Mexican hygroscopic seeding data Typical non-aerosol day (<0.1 optical depth) Typical aerosol day (>.1 optical depth)

32 New Tools (NAS 2003) 1) New remote and in situ observational tools e.g., Polarimetric radars, Doppler lidar and airborne radars, MW radiometer, CPI, cell-tracking software 2) Cloud and precipitation physics modeling e.g., focus on CCN, ice nucleation processes

33 Radar estimate of rainfall within the TITAN framework The storm The TITAN experimental unit Objective radar estimate of rainfall TITAN identifies and tracks individual storms based on a specified reflectivity threshold

34 BASIC MULTIPARAMETER RADAR THEORY * ** * * ** ** * * * Pulsed Doppler Radar Reflectivity, dbz C = Radar Constant <P> = Average Received Power < P >= 2 C r In Rayleigh, s = Ss p 6 Z = ò D N( D) dd Hydrometeor type Cloud and drizzle drops Raindrop 5 i 2 [ K ] 6 l 4 D Shape Differential Reflectivity, Z ZHH Z DR = DR ZVV Ratio of co-polar returns Z =< 37 DR γ > Measure of the mean axis ratio (g) and bulk density reflectivity weighted axis ratio Z DR Reflectivity 0 db < 0 dbz 2 db > 20 dbz

35 CHALLENGES Reflectivity ~ (droplet size) 6 drizzle cloud droplets mixture of cloud and drizzle A million droplets of 10 mm give the same radar reflectivity as one droplet of 100 mm! A million droplets of 10 mm contain a thousand times as much water as one droplet of 100 mm. And so: one drizzle droplet changes the reflectivity significantly without changing the liquid water content. Ref: Herman Russchenberg, and Oleg Krasnov, 2004

36 Mass, Latent Heating Rates, Profiles Hydrometeor Identification Detection of cloud droplets Raindrop size distribution Effect of Bragg scatter is less at Ka-band Improved cloud microphysical retrieval (precipitation type, shape, size and concentration) using both dualwavelength and dual-polarization observations S-PolKa Radar Reflectivity (dbz) Differential Reflectivity (db) Particle classification Cloud particles Drizzle Light rain Moderate rain Heavy rain Hail Rain/hail mix Graupel/small hail Graupel/rain Dry snow Wet snow Oriented ice crystals Irregular ice crystals Super cooled liquid drople Insects Birds Ground clutter

37 Particle Typing Using Polarization radar data Hydrometeor Designations 1 Cloud Drops 10 Dry Snow 2 Drizzle 11 Wet Snow 3 Light Rain 12 Ice Crystals 4 Moderate Rain 13 Irregular Ice Cystals 5 Heavy Rain 14 Supercooled Liq. Drops 6 Hail 15 Insects 7 Rain/Hail 16 Birds 8 Graupel/Small Hail 17 Ground Clutter 9 Graupel/Rain Vertical cross sections through a stratiform rain observed in the Oregon Cascades on 28 November The panels from 0938 and 1009 UTC show radar reflectivity (top), differential reflectivity (middle), and hydrometeor designations (bottom). Emergence of multiple freezing levels is suggestive of the warm frontal zone passing through the cascades at this time.

38 Direct wind, precipitation rate and particle identification in clouds

39 Simultaneous versus switchable Measurements with NCAR S-POL

40 Lightning identification

41 Summary Aerosols are not the only controlling factor in precipitation from convective clouds. Precipitation can be both enhanced and decreased. Thermodynamics including moisture and temperature profiles and the modification of these during convection also has major influences. Especially inversion levels capping convection can play an important role in microphysical processes Spatial and temporal changes in natural concentration, sizes, and chemical composition of aerosols change microphysical and precipitation processes Affects of seeding may widely differ from one situation to the other. These effects may mask seeding effects in the evaluation of experiments unless stratified by these conditions

42 New integrated approach needed to study effects of aerosols, thermodynamics, dynamics on precipitation patterns Combined observational, modeling and theoretical approach. Observations: Surface and in-situ, satellites and multi-parameter radar Models: Two-way interactive development of pollution and natural aerosol transport, chemistry, physics, cloud microphysical and precipitation processes. Models also need to accurately capture thermodynamic structure of atmsophere. Theory: Aerosol physics and chemistry and interaction with cloud and precipitation processes. ISSUE The world is a complicated place. Take a look outside.

43