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Optimizing Multiple Scattering Calculations in the CRTM

Optimizing Multiple Scattering Calculations in the CRTM. Tom Greenwald, Ralf Bennartz and Jim Davies University of Wisconsin. JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012. Motivation. Address speed/accuracy tradeoffs in CRTM multiple scattering calculations

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Optimizing Multiple Scattering Calculations in the CRTM

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  1. Optimizing Multiple Scattering Calculations in the CRTM Tom Greenwald, Ralf Bennartz and Jim Davies University of Wisconsin JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

  2. Motivation • Address speed/accuracy tradeoffs in CRTM multiple scattering calculations • Develop 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

  3. Methods • Scattering indicator (SI) based on successive order of scattering (Stephens 1994) • Simple analytical function • Depends on optical depth and single-scatter albedo • Enhancements to Stephens formulation • Include effects of gas absorption • Extend to multiple layers using a vertically weighted single-scatter albedo (Bennartz and Greenwald 2011) JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

  4. Methods Cont’d • Apply 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 JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

  5. Examples 0.5 K 0.5 K JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

  6. Results – Hurricane Katrina Temperature Sounding Channel (55.5 GHz) Water Vapor Sounding Channel (1831 GHz) JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

  7. Results - Hurricane Katrina Tb error Streams Mean Error 55 GHz 1831 GHz % Optimum Streams 0 2 4 6 8 16 Error (K)

  8. Results – Marine Sc 150 GHz JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

  9. Results – Marine Sc Tb error Streams Mean Error 37H GHz 150 GHz % Optimum Streams 0 2 4 6 8 16 Error (K)

  10. Results – Frontal System South Atlantic Temperature Sounding Channel (54.4 GHz) Queen Mary’s Peak on Tristan da Cunha Water Vapor Sounding Channel (1833 GHz) JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

  11. Results – Frontal System Tb error Streams 54.4 GHz 1833 GHz 0 2 4 6 8 16 Error (K) Mean Error % Optimum Streams

  12. Accomplishments • Developed 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) JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

  13. Plans • Fine-tune selection rules • Explore 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 aerosols • Include in CRTM v2.2 release JCSDA 10th Workshop on Satellite Data Assimilation, October 10-12, 2012

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