1. Dec 12, 2008F. Iturbide-Sanchez Review of MiRS Rainfall Rate Performances F. Iturbide-Sanchez, K. Garrett, S.-A. Boukabara, and W. Chen

2. Dec 12, 2008F. Iturbide-Sanchez Leverage of International Precipitation Working Group (IPWG) Assessment System

3. Dec 12, 2008F. Iturbide-Sanchez Assessment of MiRS at the International Precipitation Working Group (IPWG) Project Daily MIRS and MSPPS Precipitation Estimates Daily Satellite Precipitation Estimates Based on microwave observations The recent addition of the MSPPS precipitation estimate at the IPWG project is relevant for the validation/comparison of the MIRS precipitation estimate, since both use the same microwave satellite sensors (NOAA18 and MetopA).

4. Dec 12, 2008F. Iturbide-Sanchez Rainfall Rate Comparisons (Correlation) Time-series of Correlations between Microwave-Only Estimates and Daily Gauge Analysis (left) and Radar Observations (right). The Radar vs Rain Gauge statistic is the black-solid line. The MSPPS Precipitation Estimate is available since Julian day 332. Over about two months, the MIRS has shown comparable performance to well-known precipitation estimate algorithms. MSPPS and MiRS exhibit similar correlation patterns. Upper Bound

5. Dec 12, 2008F. Iturbide-Sanchez Rainfall Rate Comparisons (False Alarm Ratio) The lower the false alarm rate, the better MiRS appears to exhibit a lower false alarm rate than other precipitation algorithms, including MSPPS. Time-series of False Alarm Ratio between Microwave-Only Estimates and Daily Gauge Analysis (left) and Radar Observations (right). The Radar vs Rain Gauge statistic is the black-solid line. The MSPPS Precipitation Estimate is available since Julian day 332. Lower Bound

6. Dec 12, 2008F. Iturbide-Sanchez Rainfall Rate Comparisons (Probability of Detection) Time-series of Probability of Detection between Microwave-Only Estimates and Daily Gauge Analysis (left) and Radar Observations (right). The Radar vs Rain Gauge statistic is the black-solid line. The MSPPS Precipitation Estimate is available since Julian day 332. MiRS exhibit comparable detection rate with other satellite precipitation estimates, but particularly seems to exhibit a slightly lower detection rate than MSPPS Upper Bound

7. Dec 12, 2008F. Iturbide-Sanchez Comparison Between MIRS and MSPPS Time-Averaged Global Precipitation Composites (Daily, Pentad, Monthly)

8. Dec 12, 2008F. Iturbide-Sanchez Monthly composites of MiRS (left) and MSPPS (right) Rainfall Rate. Confirmation of the improvement over the sea ice edges (significant reductions in false alarms). MIRS MSPPS MiRS/MSPPS Monthly Composites

9. Dec 12, 2008F. Iturbide-Sanchez MiRS/MSPPS Pentad Composites Pentad composites of MiRS (left) and MSPPS (right) Rainfall Rate. Confirmation of the improvement over the sea ice edges (significant reductions in false alarms). MIRS MSPPS

10. Dec 12, 2008F. Iturbide-Sanchez MiRS/MSPPS Daily Rainfall Rate Significant Coastal False Alarms MiRS and MSPPS Precipitation Estimate based on NOAA-18 (left) and Metop-A (right) Rainfall Rate samples MIRSMSPPS

11. Dec 12, 2008F. Iturbide-Sanchez Comparison to TRMM and MSPPS Over Land and Ocean (Latitudinal Distribution and Density Histograms of Precipitation)

12. Dec 12, 2008F. Iturbide-Sanchez Daily Comparison (MiRS/MSPPS/TRMM) Latitudinal Dependence Latitude distribution (bin width = 5º) of MIRS, MSPPS and TRMM Rainfall Rate. Note: it is not possible to use TRMM as a reference along sea ice edges, due to the limited coverage of TRMM Note also that Radars along those areas are not available as far as we know False alarms along sea-ice edge OceanLand

13. Dec 12, 2008F. Iturbide-Sanchez Daily Comparison (MiRS/MSPPS/TRMM) Histograms Histograms with 0.5 mm/hr bin size. LAND (All Latitudes) OCEAN (All Latitudes) OCEAN (TRMM Latitudes) MSPPS distribution narrows (unexpected). MIRS broadens slightly. It would be expected that the percentage of higher rain rates would increase when filtering out high latitudes. TRMM more sensitive to lower rain rates by design Good consistency over land between MiRS and TRMM/PR

14. Dec 12, 2008F. Iturbide-Sanchez Summary 1/2 Throughout its comparison with rain gauges and radar observations, MIRS precipitation estimate has shown its capability to perform similar to well-known microwave satellite precipitation estimates. MiRS rainfall is a physically-based procedure that accounts for both liquid (absorption) and Ice (scattering) signatures (MSPPS retrieves rainfall rate based on ice). MiRS assessment over land and ocean is performed mainly by comparisons to: a) Rain gauges. b) Ground-based Radars. c) TRMM/PR. d) MSPPS.

15. Dec 12, 2008F. Iturbide-Sanchez Comparison results between MiRS and MSPPS over land and ocean has shown that:  MiRS has shown better detection of warm rainfall events.  MiRS rainfall rate has shown significant reduction of false alarms over the sea ice edges. Comparison results between MiRS, TRMM and MSPPS over land and ocean has shown that:  Good consistency overall between MiRS, TRMM and MSPPS  Over ocean, MSPPS and MiRS look consistent.  Over land, TRMM PR seems consistent with MiRS.  TRMM (active/passive instrument) detects lower amounts of rain by design than MiRS and MSPPS. Summary 2/2

16. Dec 12, 2008F. Iturbide-Sanchez

17. Dec 12, 2008F. Iturbide-Sanchez The MIRS Rain Rate computation is “sensor independent” and based on the MIRS core products. It uses the MIRS core products that have shown the highest correlation with a well- known reference rain rates (MSPPS Rain rate in this phase). All sensors that MiRS is going to be applied to in the future, contain similar capabilities to the AMSU/MHS pair used in this release. These sensors are DMSP-F16 & F18 SSMIS, NOAA-N’ AMSU/MHS and NPP and/or NPOESS /ATMS. Rainfall Rate Regression MIRS Core Products and Parameters Rain Rate (mm/hr) A i are coefficients generated by a multi-linear regression approach using the MIRS products and a reference rain rate. Over Land IWP and RWP Over Ocean IWP, RWP, TPW, CLW, Water Vapor at 950mb, Temperature at 950mb, Geopotential Thickness, Freezing Level Height, Skin Temperature Rainfall Rate (Algorithm Description)

18. Dec 12, 2008F. Iturbide-Sanchez General comparison between rainfall rates generated by MiRS using AMSR-E (left) and Metop- A AMSU/MHS pair (right) Assessment of MiRS-AMSR-E Rainfall (AMSR-E: Purely imager sensor ) Using the same coefficients for all sensors (independent variables being geophysical parameters and not sensor-specific variables) is scientifically sound as far as the future applications of MiRS are concerned. However, different sensor configurations will lead to different accuracies. MiRS precipitation procedure has shown its potentiality to be applicable to sensors with similar capabilities. Retrieving scientifically reasonable values of rainfall rate confirming that the approach is sound. AMSR-E Metop-A

19. Dec 12, 2008F. Iturbide-Sanchez