Optimizing Multiple Scattering Calculations in the CRTM

Tom Greenwald, Ralf Bennartz and Jim DaviesUniversity of Wisconsin

JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

MotivationAddress speed/accuracy tradeoffs in CRTM

multiple scattering calculationsDevelop a scattering indicator to find a priori

the optimum number of streams for the solver (i.e., minimum streams needed to achieve a desired accuracy)

JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012 2

MethodsScattering indicator (SI) based on successive order of

scattering (Stephens 1994)Simple analytical functionDepends on optical depth and single-scatter albedo

Enhancements to Stephens formulation Include effects of gas absorptionExtend to multiple layers using a vertically weighted

single-scatter albedo (Bennartz and Greenwald 2011)

3JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

Methods Cont’dApply thresholds to the SI to automatically increase the

numbers of streams (aka “selection rules”) Source of cloud profiles: WRF model simulations

Hurricane Katrina (1.5 km) California marine stratocumulus (2 km) South Atlantic frontal system (3 km)

Limit to microwave sensors for now; define target accuracy as 0.5 K (typical radiometric sensitivity)

CRTM 16-stream solution used as a reference to quantify error

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Examples

0.5 K0.5 K

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Results – Hurricane KatrinaTemperature Sounding Channel (55.5 GHz) Water Vapor Sounding Channel (1831 GHz)

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Results - Hurricane Katrina

0 2 4 6 8 16

 

Tb error Streams

55 G

Hz

183

1 GH

z

Mean Error

% Optimum Streams

7Error (K)

Results – Marine Sc

150 GHz

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Results – Marine Sc

0 2 4 6 8 16

 

Tb error Streams

37H

GHz

150

GHz

Error (K)

% Optimum Streams

Mean Error

9

Results – Frontal SystemSouth Atlantic

TemperatureSoundingChannel (54.4 GHz)

Water VaporSoundingChannel (1833 GHz)

Queen Mary’s Peak on Tristan da Cunha

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Results – Frontal System

0 2 4 6 8 16

 

Tb error Streams

54.4

GHz

18

33

GHz

Error (K)

Mean Error

% Optimum Streams

11

AccomplishmentsDeveloped a method of automatically selecting the

optimum number of streams in the CRTM Generally, optimum values achieved 85-100% of the time Suboptimal (40-75%) in water vapor bands Factors of 5-10 speedup for temperature sounding channels

Modified CRTM code to include new method (FWD/TL only) CRTM v2.1

Number of streams option (overrides auto-selection) Successive Order of Interaction (SOI) RT solver

Publication: Bennartz and Greenwald (2011, QJRMS)

12JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

PlansFine-tune selection rulesExplore use of other SIs (e.g., Mie size

parameter) in strongly scattering and absorbing conditions

Write adjoint code Extend method to IR sensors for clouds and

aerosolsInclude in CRTM v2.2 release

13JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012