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Apr 17, 2009F. Iturbide-Sanchez A Regressed Rainfall Rate Based on TRMM Microwave Imager Data and F16 Rainfall Rate Improvement F. Iturbide-Sanchez, K.

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Presentation on theme: "Apr 17, 2009F. Iturbide-Sanchez A Regressed Rainfall Rate Based on TRMM Microwave Imager Data and F16 Rainfall Rate Improvement F. Iturbide-Sanchez, K."— Presentation transcript:

1 Apr 17, 2009F. Iturbide-Sanchez A Regressed Rainfall Rate Based on TRMM Microwave Imager Data and F16 Rainfall Rate Improvement F. Iturbide-Sanchez, K. Garrett, W. Chen, and S.-A. Boukabara

2 Apr 17, 2009F. Iturbide-Sanchez Outline I.F16 Rainfall Rate Improvement. II.Regressed Rainfall Rate Based on TRMM Microwave Imager (TMI) 2A12 data. III.MiRS Rainfall Rate Validation with CPC Precipitation.

3 Apr 17, 2009F. Iturbide-Sanchez I. F16 Rainfall Rate Improvement.

4 Apr 17, 2009F. Iturbide-Sanchez Rainfall rate values retrieved from F16 SSMIS have shown suspicious or noisy rainfall rate values particularly over middle latitudes regions. F16 Rainfall Rate

5 Apr 17, 2009F. Iturbide-Sanchez N18 Rain Rate MetopA Rain Rate F16 Rain Rate F16 Rainfall Rate

6 Apr 17, 2009F. Iturbide-Sanchez These areas of anomalous rainfall rates coincide with failed convergence of the MIRS 1DVAR algorithm on the first retrieval attempt, therefore assuming there is rain present in the field-of-view. F16 Convergence

7 Apr 17, 2009F. Iturbide-Sanchez The cause of the failed convergence was hypothesized to be from constrictive Radiative Transfer Model (RTM) uncertainty used. Therefore, each value of the RTM uncertainties associated with the SSMIS channels were increased in order to reduce the constraint for fitting TBs simulated from the retrieved scene. Channel1289101112131415161718 Frequency (GHz)50.352.8150190 H186 H184 H19.35 H19.35 V22.23537 H37 V91.655 H91.655 V RTM Uncertainty Before0.9030.7483.2191.5531.3241.3681.7971.3111.3722.3381.6171.4752.637 RTM Uncertainty After0.9030.7483.2191.5531.3241.3681.7971.3111.3723.3382.3171.4752.637 Change in % with respect to previous Value0.00 42.7743.290.00 It was identified that the RTM uncertainties on both the vertical and horizontal 37 GHz channels need to be increased in order to improve the capability of the 1DVAR algorithm to detect rain over middle latitude regions. F16 RTM Uncertainity

8 Apr 17, 2009F. Iturbide-Sanchez F16 RR Before Boosting RTM Uncertainty (Asc) F16 Rainfall Rate Improvement 1/2 F16 RR After Boosting RTM Uncertainty (Asc)

9 Apr 17, 2009F. Iturbide-Sanchez F16 Rainfall Rate Improvement 2/2 F16 RR Before Boosting RTM Uncertainty (Des) F16 RR After Boosting RTM Uncertainty (Des) A climatological sea ice mask could be used to remove false alarms near the polar coast.

10 Apr 17, 2009F. Iturbide-Sanchez F16 Rainfall Rate Improvement when Using a Seasonal Sea Ice Mask 1/2 A climatological sea ice mask is used to remove false alarms near the polar coast. Within this mask high probability that sea-ice exists. Mask changes on monthly basis. F16 RR Before Boosting RTM Uncertainty (Asc) F16 RR After Boosting RTM Uncertainty (Asc)

11 Apr 17, 2009F. Iturbide-Sanchez F16 RR Before Boosting RTM Uncertainty (Des) F16 RR After Boosting RTM Uncertainty (Des) A climatological sea ice mask is used to remove false alarms near the polar coast. Within this mask high probability that sea-ice exists. Mask changes on monthly basis. F16 Rainfall Rate Improvement when Using a Seasonal Sea Ice Mask 2/2

12 Apr 17, 2009F. Iturbide-Sanchez Improved F16 Rainfall Rate compared to N18 and MetopA Rainfall Rates N18 Rain Rate MetopA Rain Rate F16 Rain Rate

13 Apr 17, 2009F. Iturbide-Sanchez II. Regressed Rainfall Rate Based on TRMM Microwave Imager (TMI) 2A12 Data.

14 Apr 17, 2009F. Iturbide-Sanchez TRMM Microwave Imager (TMI) 2A12 Data The TMI 2A12 data contains profiles of hydrometeors (cloud liquid, cloud ice, precipitation water), as well as rainfall rate. Such parameter are retrieved from TMI brightness temperatures by blending the radiometric data with dynamical cloud models. The TRMM-TMI data had been averaged from 5 km to 50 km resolution (similar to AMSU-A spatial resolution).

15 Apr 17, 2009F. Iturbide-Sanchez Correlation Between TMI-2A12 Rainfall Rate and Cloud Liquid Water (CLW) To provide seasonal variability to the derived regressed rainfall rate, the TMI-2A12 data used in this exercise was from August 2008 and February 2009.

16 Apr 17, 2009F. Iturbide-Sanchez Correlation Between TMI-2A12 Rainfall Rate and Ice Water Path (IWP) Over LandOver Ocean

17 Apr 17, 2009F. Iturbide-Sanchez Correlation Between TMI-2A12 Rainfall Rate and Rain Water Path (RWP) Over LandOver Ocean

18 Apr 17, 2009F. Iturbide-Sanchez Regressed Rain Rate Based on TMI 2A12 Products Regressed RR=Ao +A1 (IWP) + A2 (RWP) + A3 (CLW) Regressed Rain Rate (mm/hr) TMI-2A12 Rain Rate (mm/hr) Regressed Rain Rate (mm/hr) TMI-2A12 Rain Rate (mm/hr) A multiple linear regression method was used to compute the correlation coefficients between TRMM-2A12 Rainfall Rate and IWP, RWP and CLW. The computed correlation coefficients were used to compute the Regressed MIRS Rainfall Rate. Computed Correlation Coefficients

19 Apr 17, 2009F. Iturbide-Sanchez Comparison: MSPPS and TMI 2A12-Based Regressed Rain Rates MSPPS-Based MIRS Rainfall Rate (current) TMI 2A12-Based MIRS Rainfall Rate More light rain values are detected MIRS RR=Ao +A1 (IWP MIRS ) + A2 (RWP MIRS ) + A3 (CLW MIRS )

20 Apr 17, 2009F. Iturbide-Sanchez Improvement Collocations Between TRMM-PR, N18, N19, F16 and MetopA are being performed on daily basis. For MetopA, more than 10,000 collocations have been found over land and about 30,000 over ocean. Collocations Between TRMM-PR and MetopA over Land Comparison: TMI 2A12-Based Regressed Rain Rate vs TRMM 2B31 Precipitation (Radar-based) 1/4 MSPPS-Based MIRS RR (current) TMI 2A12-Based MIRS RR

21 Apr 17, 2009F. Iturbide-Sanchez Collocations Between TRMM-PR and MetopA over Land Improvement Comparison: TMI 2A12-Based Regressed Rain Rate vs TRMM 2B31 Precipitation (Radar-based) 2/4 MSPPS-Based MIRS RR (current) TMI 2A12-Based MIRS RR

22 Apr 17, 2009F. Iturbide-Sanchez Collocations TRMM-PR vs MetopA over Ocean Improvement Comparison: TMI 2A12-Based Regressed Rain Rate vs TRMM 2B31 Precipitation (Radar-based) 3/4 MSPPS-Based MIRS RR (current) TMI 2A12-Based MIRS RR

23 Apr 17, 2009F. Iturbide-Sanchez Collocation TRMM-PR vs MetopA over Ocean Improvement Comparison: TMI 2A12-Based Regressed Rain Rate vs TRMM 2B31 Precipitation (Radar-based) 4/4 MSPPS-Based MIRS RR (current) TMI 2A12-Based MIRS RR

24 Apr 17, 2009F. Iturbide-Sanchez III. MiRS Rainfall Rate Validation with CPC Precipitation.

25 Apr 17, 2009F. Iturbide-Sanchez Record daily CPC Precipitation Record FMSDR data over USA from N18, MetopA and F16 sensors Generate MIRS Precipitation Estimate Compare CPC and MIRS Precipitation on daily basis time Correlation, False Alarm Ratio, etc MIRS vs CPC Precipitation MIRS RR V A MIRS RR V B MIRS RR V C MiRS Rainfall Rate Validation with CPC Precipitation

26 Apr 17, 2009F. Iturbide-Sanchez

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