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This document presents preliminary results from the validation and tuning of the CrIMSS EDR algorithm, conducted by Xu Liu at NASA Langley Research Center. The analysis includes a review of Microwave (MW) convergence data from various dates, highlighting the performance of the algorithm over oceanic regions versus land. Initial findings indicate that while the OPS performs well over oceans, improvements in bias tuning are necessary to enhance convergence rates and overall EDR performance, particularly due to challenges with MW emissivity backgrounds over land. Ongoing tuning efforts are detailed.
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Preliminary Results of CrIMSS EDR algorithm validation and tuning Xu Liu NASA Langley Research Center Susan Kizer SSAI, Hampton, VA 23681 12 June 2012 CrIMSS EDR Telecon and Product Review
MW convergence for Feb. 24, 2011 CrIMSS data • Left: First stage MW retrieval Chisq before tuning the apriori information and constraints • Left: First stage MW retrieval Chisq before tuning the apriori information and constraints
MW convergence for May 15, 2011 CrIMSS data • Left: First stage MW retrieval Chisq before tuning the apriori information and constraints • Left: First stage MW retrieval Chisq before tuning the apriori information and constraints
MW convergence for May 15, 2011 CrIMSS data • Left: First stage MW retrieval Chisq using November 11, 2011 ATMS tuning • Left: First stage MW retrieval Chisq using May 15, 2011 tuning
CrIMSS EDR Performance Over Ocean for Feb. 24, 2011 data • Green curves are the RMS, STD, and BIAS of MW only retrieval • Blues curves are the RMS, STD, and BIAS of MW+IR only retrieval
Conclusions • The OPS performs relatively well over ocean • Improved bias tuning will increase the convergence rate and EDR performance • The poor convergence over land is due to the unrealistic MW emissivity background and covariance climatology • EDR performance is good after preliminary tuning • Algorithm tuning is still on going • Sy matrix • Sx matrix and Xa • Bias tuning • Scene classification