Test of Microphysical Schemes (WRF) with C3VP Snow Events

J.-J. Shi, T. Matsui, S. Lang A. Hou, G. S. Jackson, C. Peters-Lidard

W. Petersen, R. Cifelli, S. RutledgeWei-Kuo Tao

• Objectives

• Cases: a lake event followed by a synoptic event

• NASA Unified WRF - Satellite Simulator

• Comparison: Observation (Snow Fall, CloudSat, AMSU) vs simulated

• Summary and future work

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Simulated DBz

Objectives

• To improve our understanding of precipitation processes at high latitudes

• To utilize the Earth satellite simulator to identify the strengths and weaknesses of model-simulated microphysical processes

• To provide consistent 4-D thermodynamic and dynamic cloud data sets for GPM snow retrieval

• To examine the sensitivity of microphysical schemes on precipitation processes associated with snowstorms

NASA Unified WRFChrista Peters-Lidard, Wei-Kuo Tao, Mian Chin

Scott Braun, Jonathan Case, Arthur Hou, Sujay Kumar, William Lau, Toshi Matsui, Roger Shi, Qian Tan, Sara Zhang

Objectives is to Integrated Modeling of Aerosol, Cloud, Precipitation and Land Processes at Satellite-Resolved Scales

Blue Boxes: Goddard Physical Packages

Goddard Bulk Microphysical Scheme

• Warm Rain (Soong and Ogura 1973)• Ice-Water Saturation Adjustment (Tao et al. 1989)• Option for 3ICE-Graupel (Rutledge and Hobb 1984) or 3ICE-Hail (Lin et al. 1983) scheme (Tao and

Simpson 1989, 1993; McCumber et al. 1990)The sum of all the sink processes associated with one species will not exceed its mass - (water budget balance)All transfer processes from one type of hydrometeor to another are calculated based on one thermodynamic state (ensure all processes are equal)

• 3ICE Modification (Tao et al. 2003a)Saturation adjustmentConversion from Ice to Snow

• 2ICE scheme (Tao et al. 2003b)Ice and Snow

• 3ICE-Graupel Modification (Lang et al. 2007)Conversion from cloud to snowDry growth of graupel

Observation ImprovedCFAD - Radar Reflectivity

dBZ

Z(km)

MM5

WRF <-- GCE qg

qg

qs

qs

CFAD: Contoured Frequency Altitude Diagram (i.e., stacked PDFs)

Lang, S., W.-K. Tao, R. Cifelli, W. Olson, J. Halverson, S. Rutledge, and J. Simpson, 2007: Improving simulations of convective system from TRMM LBA: Easterly and Westerly regimes. J. Atmos. Sci., 64, 1141-1164.

Tao, W.-K., J. Simpson, D. Baker, S. Braun, M.-D. Chou, B. Ferrier, D. Johnson, A. Khain, S. Lang, B. Lynn, C.-L. Shie, D. Starr, C.-H. Sui, Y. Wang and P. Wetzel, 2003a: Microphysics, radiation and surface processes in the Goddard Cumulus Ensemble (GCE) model, A Special Issue on Non-hydrostatic Mesoscale Modeling, Meteorology and Atmospheric Physics, 82, 97-137.

Resolutions: 9, 3, and 1 km Grid sizes: 301X241, 430X412, and 457X45731 vertical layerst = 30 secondsStarting time: 00Z 1/20/2007Initial and Boundary Conditions: NCEP/GFS

Physics:

• Cu parameterization: Grell-Devenyi scheme (for the outer grid only)

• *Cloud microphysics (6) + sensitivity tests (2)

• Radiation: Goddard shortwave and RRTM longwave

• PBL parameterization:

Mellor-Yamada-Janjic TKE scheme

• Surface Layer: Monin-Obukhov (Janjic) scheme

• Land Surface Model: Noah

WRF C3VP Simulation20 - 22 January 2007 (a lake event followed by a synoptic event)

1 Goddard 3ICE - Graupel1a Goddard 2ICE (Cloud Ice and Snow)2 WSM6 (3ICE)

2a? WSM5 (cloud ice and graupel)3 Purdue – Lin (3ICE)4 Thompson (3ICE)5 Goddard 3ICE (no condensation)6 Goddard 3ICE (no melting from ice

to cloud water)

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January 20 (Lake Effect) January 22 (Synoptic Event)

Simulated Snow Fall

January 20 January 22

January 20 (Lake Snow) -->

<-- January 22 (Synoptic Event)

Radar ReflectivityObservation

Observation

Simulation

Simulation

Satellite SimulatorSimulate satellite observables (radiance and backscattering) from model-simulated (or

assigned) geophysical parameters.

Scientific Objective:

• Evaluate and improve NASA modeling systems by using direct measurements from space-born, airborne, and ground-based remote sensing.

• Support radiance-based data assimilation for NASA’s modeling systems.

• Support the NASA’s current and future satellite mission (e.g., TRMM, GPM, and A-Train) through providing the virtual satellite measurements as well as simulated geophysical parameters to satellite algorithm developers.

GCE, WRF, MMF output

Lidar SimulatorCALIPSO, ICESAT

Visible-IR simulatorAVHRR,TRMM VIRS, MODIS,

GOES

Radar SimulatorTRMM PR, GPM DPR, CloudSat

CPR

Microwave SimulatorSSM/I, TMI, AMSR-E, AMSU, and

MHS

ISCCP-like SimulatorISCCP DX product

MODIS clouds products

Braodband SimulatorERBE, CERES, TOVS, AIRS

Goddard Satellite Data Simulation Unit

CloudSat Simulated

WRF captures the multi-layered cloud system as seen by CloudSat. However, Ze in the mid-layer clouds appears to be stronger than the CloudSat measurements.

CFADs

CloudSat Simulated

Direct satellite and model comparison over the GPM Ground Validation domain. Goddard SDSUradar reflectivity and brightness temperature are computed from WRF simulations. a) CloudSatobserved CPR (94.15GHz) radar reflectivity (left) and WRF-SDSD-simulated 94.15GHz(right). b) AMSU-B observed brightness temperature at 183.31°æ 1GHz and183.31°æ 7GHz (left) with corresponding brightness temperatures simulated from the WRF-SDSU (right).

AMSU-B (Tb) Simulated Tb

CloudSat (CPR) Simulated (CPR)

3ICE 2ICE

Vertical profiles of domain- and 1st 24-hour time-average cloud species for the 3ICE (cloud ice, snow and graupel) and 2ICE (cloud ice and snow) schemes

OO Large precipitating particles (rain and graupel) did not form in either experiment ==> weak vertical velocities (~50 cm/s).OO Similar profiles for cloud water, cloud ice and snow for both experiments.O O Goddard 3ICE microphysical scheme responded well to the cloud dynamics and did not produce large precipitating ice (graupel).OO Presence of cloud water during snow event has been observed and simulated (also found in many other snow events)

Lin

WSM6

Thompson

Goddard

Sensitivity of microphysical schemes on the vertical profiles of domain and time-average cloud species (1st 24h of integration for lake effect event)

No cloud ice, large cloud water

Snow and graupel at groundCloud ice is dominant species, little cloud water

No cloud ice, little cloud waterSnow and graupel at ground

Test 1: Pimlt = 0 Test 2: reduced condensation

Synoptic Effect Storm

A. Heymsfield: No liquid water observed

What is the microphysical process to produce liquid water?

Control Run

No Melting No Condensation

Summary and Future Work

Preliminary WRF simulation captures the basic cloud properties as seen by ground-basedradar and satellite (CloudSat, AMSU-B) observations. However, the model under predictslow cloud for the lake effect snow case.

WRF simulation with two different microphysical schemes (3ICE and 2ICE scheme)shows almost identical results (due to weak vertical velocities and therefore no large precipitating liquid or ice presence).

WRF simulation with other WRF microphysical schemes (Thompson, Purue Lin and WSM6) shows a great sensitivity in vertical cloud profiles (important for both radiation Budget and hydrologic/energy cycles).

WRF-simulated cloud data set is available to GPM science team through the GoddardCloud library web-site (http://portal.nccs.nasa.gov/cloudlibrary/index2.html).

WRF simulation with higher-resolution initial conditions (NCEP Eta 32 km), more and higher vertical resolution (low and upper troposphere), microphysics (liquid phase)PBL will be conducted.

WRF-Earth satellite simulator with realistic ground emissivity is required.

Goddard SDSU development Plan

Priority Order

1. Code: MPI version.

2. Surface Properties: Land surface emissivity and bidirectional reflectance distribution function (BRDF) spectrum albedo.

3. Optical properties: Non-spherical optical properties (frozen particles and dust aerosols - MODIS, GoCART)

4. Radiative Transfer: 3D radiative transfer with full polarization

5. IO process: Options for GEOS5 Single Column Model (SCM) input (overlapping ensemble statistics)

Goddard WRF

MicrophysicsNew 3Ice-Graupel (see CFAD)2-Moment (cloud-aerosol interactions)Multi-moment (mass, concentration, shape)Hybrid (Spectral bin and bulk microphysics)

Observed WRF New 3Ice-Graupel

-->Reduce 40dBZ

at high altitude

Satellite (Earth) simulators (microwave, dual frequency precipitation radar, lidar, cloud radar, IR…) - identify the strengths/weakness of microphysics in a global context

Comparing CloudSat-observed and WRF-simulated Ze

Low cloud

Middle-high cloud

Multi-layer cloud