Special Sensor Microwave Imager (SSM/I) Intersensor Calibration and Impact on Precipitation Trend

1. Special Sensor Microwave Imager (SSM/I) Intersensor Calibration and Impact on Precipitation Trend Song Yang, Fuzhong Weng, Banghai Yan, and Ninghai Sun NOAA/NESDIS/STAR Camp Springs, MD 20746 4th Workshop of International Precipitation Working Group (IPWG), Beijing, Oct 13-17, 2008

2. Outline • Why need SSM/I TDR Calibration • SCO Calibration Technique • Impacts on TDRs/EDRs/CDRs • Impacts on Rainfall Climate Trend • Conclusions

3. Ascending Descending Overall SSM/I Oceanic Rain-free Ta Difference against Scan Central Pixel before Calibration(60°S-60°N)

4. Oceanic Rain-Free Monthly Mean Ta Ta (K) 37V SSM/I Intersensor Bias of Oceanic Rain-Free Monthly Mean Ta Ta Bias (K) SSM/I Monthly Oceanic Rain-free TDRTime Seriesbefore Calibration

5. SSM/I Orbit Draft F13 provides the stable and longest time series for inter-sensor calibration

6. North Pole Region South Pole Region DMSP Satellite SCO Intersections

7. 19H Std  2 |Ta|  20 Std  2 Std  5 F14 22V F14 100 140 180 220 260 300 100 140 180 220 260 300 100 140 180 220 260 300 100 140 180 220 260 300 F11 F11 F11 F11 Analysis of SCO Pixels Ta - Water t  30 sec & d  3 Km)

8. 85 H Std  2 |Ta|  20 Bias °K F13-F11 SCO Pixels Ta Bias (Water - with scan angle adjustment) F13-F14 SCO Pixels Ta Bias - Water(t  30 sec & d  3 Km, with scan angle adj.)

9. SSM/I TDR Bias Correction Coefficients F13 as Reference Satellite

10. Oceanic Rain-Free Monthly Mean Ta Ta (K) 37V Before Calibration SSM/I Intersensor Bias of Oceanic Rain-Free Monthly Mean Ta Ta Bias (K) Ta Bias (K) Oceanic Rain-Free Monthly Mean Ta Ta (K) 37V After Calibration SSM/I Intersensor Bias of Oceanic Rain-Free Monthly Mean Ta SSM/I Monthly Oceanic Rain-free TDR Time Series after Calibration(F13 as Reference Satellite)

11. Before Calibration After Calibration SSM/I Intersensor Bias of Oceanic Rain-Free Monthly Ta

12. Mean SSM/I TDR Absolute Bias F13 as Reference Satellite

13. Before Calibration After Calibration Comparison ofSSM/I Monthly Oceanic Rain-free TDR before and after Calibration [e(K), S (K/10yr)] SSM/I Monthly Oceanic Rain-free TDR Trend (F13 as Reference Satellite)

14. F14 SSM/I Monthly Mean Surface Rainrate for December 2006 from NOAA Heritage Rain Algorithm and Matched TRMM 3B42 Before Calib. After Calib. Matched 3B42 0.5°x0.5° grid scale

15. F14 SSM/I Monthly Mean Surface Rainrates for December 2006 from NOAA Heritage Rain Algorithm 0.5°x0.5° grid scale Before Calib. After Calib. 29% bias deduction with calibrated TDR against matched TRMM 3B42 Rain products Difference (aft - bef)

16. F14 SSM/I Monthly Mean Total Precipitable Water (TPW) for December 2006 from NOAA Heritage Rain Algorithm Before Calib. After Calib. 11% bias deduction with calibrated TDR against radiosonde measurement Difference (aft - bef)

17. F14 SSM/I Monthly Mean Sea Ice Concentration (%) Near North Pole Region for December 2006 from NOAA Heritage Algorithm Before Calib. After Calib. Difference (aft - bef)

18. Climate Trend of Monthly Precipitation from SSM/I and GPCP SSM/I GPCP

19. Climate Trend of Oceanic Total Precipitable Water Path

20. Conclusions The importance of SSM/I intersensor calibration is presented. NOAA/NESDIS SCO-based calibration scheme can dramatically reduce the intersensor biases of SSM/I TDRs. Test results indicate that the SSM/I TDR calibration scheme shows significant impacts on EDRs/CDRs. Although the bias correction of SSM/I TDRs is small, the calibration has a significant impact on TDR’s trend. The very small decreasing trend of precipitation is evident, however, this trend could not be treated as the “truth” because of uncertainties associated with the calibrations and SSM/I sampling issue.