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CrIMSS EDR Validations for - Provisional Maturity Assessment – Part II Implications on using island-based CrIMSS EDR Matches in Validations.
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CrIMSS EDR Validations for - Provisional Maturity Assessment – Part II Implications on using island-based CrIMSS EDR Matches in Validations ByMurty Divakarla*, Mike Wilson*, Eric Maddy#, Changyi Tan*, XiaozhenXiong*, Antonia Gambacorta@, and Nick Nalli+IM Systems Group, Inc. at NOAA/STARXu Liu* and Susan Kizer*Langley Research CenterDeguiGu*, Xia L Ma*, and Denise Hagan*Northrop Grumman Aerospace Systems Chris Barnet*$ and Mitch Goldberg$NOAA/STAR, JPSS *Core group for CrIMSS-EDR algorithm Implementation, evaluation, Improvements through Discrepancy Reports to JPSS, user support, and, data source for Focus-Day(s) correlative data sets# STAR in-house Aqua-AIRS retrieval key consultant and data sets @Initial help on CrIS/ATMS bias-tuning data set +Coordinator for AEROSE and other ARM/CART dedicated RAOB campaignsPoint of Contact: Chris.Barnet@noaa.gov; Murty.Divakarla@noaa.gov
Presentation Outline • This presentation • CrIMSS EDRs with ECMWF over coastal cases (05/15/2012, 09/20/2012) to conclude coastal areas have issues. • Evaluations of CrIMSS EDRs around Kauai, Hawaii RAOB Locations • Kauai, Hawaii (Detailed-Evaluation of Matched Granules) • 05/15/2012, 05/12/2012 to indicate other granule matches will have similar characteristics • Implications on CrIMSS EDR Provisional Maturity • Is this applicable to TWP site? • Earlier Telecon Presentations – to look while you evaluate these results: • Evaluation of Focus-Day Data Sets (Murty’s Presentation : December 4th, Telecon) • IDPS 5.3 (Past), IDPS 6.3 (Present), IDPS 7.0 (Future) for 05/15/2012, 09/20/2012 (Global Evaluation) • Data Sets on FTP Site: CrIMSS Data Bank - (Changyi.Tan@noaa.govMurty.Divakarla@noaa.gov, Xiaozhen.Xiong@noaa.gov, Michael.Wilson@noaa.gov) • Evaluations with Heritage Algorithm (AIRS Retrieval) matches , Examination of EDR products over Hawaii RAOB locations • Presented in the AIRS Science Team Meeting, November, 2012 (Murty et al.,2012) • Evaluation of two different algorithms, the AIRS –Science Team heritage algorithm, and the CrIMSS official EDR Algorithm • effect of dust on two different retrieval algorithms – How it was perceived with proxy data, and how it is seen with real observations.
500mb Temp (K) Map (Descending)CLM-2002 NPP-CrIMSS, Aqua-AIRS and ECMWF
T(p), q(p) RMS Global (05/15/2012)IDPS 5.3 (Past), IDPS 6.3 (Present) and IDPS (7.0) Yield : IR+MW(Repeated from last week Murty’s presentation) CrIMSS IR+MW Global ALL N=318,000 MX7: 50% MX6.3:22% MX5.3: 4% T(p) RMS (K) q(p) RMS (%)
T(p), q(p) RMS Global, Land, Sea, Coast, ALL(05/15/2012)wrt ECMWF, IDPS (MX7.0) Yield : IR+MW(Repeated from December 5th telecon presentation, but coastal cases added) CrIMSS IR+MW MX7 Global ALL N=318,000 ALL: 50% Land: 53% Sea:50% COAST(--):45% T(p) RMS (K) q(p) RMS (%)
T(p), q(p) RMS Global, Land, Sea, Coast, ALL(09/20/2012)wrt ECMWF, IDPS (MX7.0) Yield : IR+MW(Repeated from December 5th telecon presentation, but coastal cases added) CrIMSS IR+MW MX7 Global ALL N=318,000 ALL: 51% Land: 55% Sea:50% COAST(--):42% T(p) RMS (K) q(p) RMS (%)
T(p), q(p) Bias Global, Land, Sea, Coast, ALL(05/15/2012)wrt ECMWF, IDPS (MX7.0) Yield : IR+MW(Repeated from December 5th telecon presentation, but coastal cases added) CrIMSS IR+MW MX7 Global ALL N=318,000 ALL: 50% Land: 53% Sea:50% Coast (--):45% T(p) Bias (K) q(p) Bias (%)
T(p), q(p) Bias Global, Land, Sea, Coast, ALL(09/20/2012)wrt ECMWF, IDPS (MX7.0) Yield : IR+MW CrIMSS IR+MW MX7 Global ALL N=318,000 ALL: 51% Land: 55% Sea:50% COAST(--):42% T(p) Bias (K) q(p) Bias (%)
Aerospace RAOB (Kunai, Hawaii) Location Specifics with ATMS BTs
Aerospace RAOB (Kauai, Hawaii) Location Specifics with ATMS BTs CH#1
Aerospace RAOB (Kauai, Hawaii) Location Specifics with ATMS BTs CH#1
Aerospace RAOB (Kauai, Hawaii) Location Specifics with ATMS BTs CH#2
Aerospace RAOB (Kauai, Hawaii) Location Specifics with ATMS BTs CH#3
Aerospace RAOB (Kauai, Hawaii) Location Specifics with ATMS BTs CH#8
Aerospace RAOB (Kauai, Hawaii) Land Fraction/ATMS TBs 05/15/2012, 05/12/2012
Aerospace RAOB (Kauai, Hawaii) Location Specifics MX7, MX6.3 MX5.3 05/12/2012
Summary • The CrIMSS EDRs matched to the Kauai (Hawaii) RAOB location most likely falls into coastal category whose RMS difference with ECMWF could be much larger than the sea-only category. • with-in the FOR the land fraction can be around 10-20% and also depends on how many FOVs are over the land vs. sea, and also the view angle. • The EDRs, thus, may not realistically represent a sounding from clear or cloud-clear ‘sea’ location which often is the expectation in this type of evaluation. • This leads to un-fair assessment of the CrIMSS EDRs when EDRs from heritage algorithm retrievals are evaluated with the same RAOBs. • The heritage algorithms may have a regression first guess that may mitigate some of these effects. • Results of evaluation, especially water vapor may be flawed and leads to wrong conclusions • If the goal is to evaluate IR+MW 2nd Stage retrieval, it is quite likely you may end-up with 1st Stage MW retrieval, and also a coastal profile with land fraction around 10-20% even if we are lucky to get 2nd stage convergence (IR+MW). • Next Telecon Presentation (RAOBs vs. ECMWF vs. CrIMSS EDRs) • Can we mitigate this effect by finding FOVs that fall entirely over the sea, and replace the ATMS-FOR-SDRs with the FOV TBs? • Can we avoid using surface sensitive ATMS channels (through channel selection in the EDR algorithm?
CrIMSS and AIRS Retrieval Matches Aerospace RAOB (Kauai, Hawaii) -05/15 Even after QC you will have many open ocean matches
CrIMSS IR+MW vs. ECMWFAIRS V6 pbest vs. ECMWF Global (D+N) : (L+S+C); CLDCLR, Clear RMS Collocated CrIs/AIRS matches. Solid Lines CrIMSS IR+MW Dashed Lines AIRS V6 RET pbest Global ALL N=177,000 AIRS: 38% dashed CrIMSS: 53% solid CLDCLR Clear N: 5,277 AIRS: (3%) dashed CrIMSS: solid 5331 T(p) RMS (K) q(p) RMS (%)
CrIMSS-AIRS Rets/ECMWF • The Matched AIRS-CrIS data set with other correlative measurements (e.g. ECMWF) over open oceans provides a better data set and can lead us to provisional maturity very easily. These can be considered as ‘Dedicated Matches’ synonymous to Dedicated RAOBs that are very sparse. • With a collocated ensemble this data sets is more powerful for evaluation because meteorology (location) should be the same but time of day and view angle may be slightly different. • With common accepted sample this becomes even more powerful since we are now looking at exactly the same cases • IR+MW Stage, as well as MW-stage vs. ECMWF/AIRS • You may find cases from all IDPS emulations (IDPS 5.3, 6.3 and MX7) because of large number of matched data sets • Cloud-Cleared : 177,000 cases for a single day • Clear (6326 ; 5520 ocean; 3308 ocean, night)and CLDCLR cases • Very encouraging results for matched cloud-free/cloud-cleared cases • EDR Evaluations of clear cases are similar to AIRS