1. Response of active and passive microwave sensors to precipitation at mid- and high altitudes Ralf Bennartz University of Wisconsin Atmospheric and Oceanic Sciences Department

2. Outline Introduction Comparison of ground-based radar with satellite data Combined active and passive mw modeling approach for future sensors AMSU precipitation classification: 89 versus 150 GHz Conclusions and Outlook

3. Passive microwave precipitation signal Emission signal from liquid precipitation: Most directly linked to surface precip, ocean only. Scattering signal from frozen precip-sized ice particles: Only indirectly linked to surface precipitation, Most directly linked to surface precipitation Over cold (water) surfaces only All types of surfaces More indirect

4. Observation geometry Altitude of radar beam (elevation 0.5°): @100km distance: 2.2 km @200km distance: 5.2 km 273 K isothermal typically at 2-3 km

5. Thunderstorm Graupel (Cold air outbreak) Frontal precipitation Radar reflectivity [dBz] Different precipitation events

6. Radar versus passive microwave precipitation estimate Thunderstorm Graupel (Cold air outbreak) Frontal precipitation Bennartz and Michelson (in press, Int. J. Rem. Sens.)

7. Simulating passive mw-response for current and future sensors and missions (AMSR, SSMIS,(E) GPM) Bennartz and Petty, JAM, 2001 Bennartz and Bauer Radio Sci. In press

8. Volume extinction at 85 GHz and 150 GHz

9. To SSM/I resolution To TMI resolution Every 2nd scanline

10. 85 GHz 150 GHz 150 GHz @ TMI-resolution 85 GHz @ TMI-resolution Graupel shower 85 & 150 GHz

11. 183-7 GHz 183-3 GHz 183-3 GHz @ TMI-resolution 183-7 GHz @ TMI-resolution Graupel shower 183-7 & 183-3 GHz

12. FrontalGraupel shower Intensive convection 85 GHz162545 150 GHz284442 183-7 GHz82218 183-3 GHz476 Maximum brightness temperature depressions

13. Sensitivity to surface emissivity (very dry atmosphere wvp = 6 kg/m2)

14. Sensitivity to surface emissivity (moist atmosphere, wvp= 35 kg/m2)

15. Sensitivity to surface emissivity (high cloud liquid water path, wvp=20 kg/m2)

16. High-latitude precipitation classification based on AMSU-data for nowcasting purposes (see presentation A. Thoss) Rain rate Class 1:Precipitation-free0.0 - 0.1 mm/h Class 2:Risk for precipitation0.1- 0.5 mm/h Class 3:Light/moderate precipitation0.5 - 5.0 mm/h Class 4:Intensive precipitation5.0 -... mm/h

17. RGB AVHRR ch3,4,5PC product RGB: red: very light green:light/moderate blue:intense Radar composite different projection! NOAA15 overpass 13 September 2000, 05:48 UTC

18. 150 GHz versus 89 GHz scattering index (land) Bennartz et al. (Met. Apps., 2002, 9, 177-189) 150 GHz enhances dynamic range of SI by a factor of 2 About 15% of the precip free areas are falsely identified as raining at 89 GHz. This is reduced to 2.6% at 150 GHz.

19. AQUA AMSR-E

20. Data coverage: August 2002-.... AQUA AMSR-E/AMSU/HSB Latitude range 50 N -70 N Network of 25 radars Radar reflectivities every 15 minutes Gauge-adjusted rain rates every 15 minutes volume scans of Gotland radar Combined active/passive dataset for high latitudes (UW-Madison/SMHI)

21. AMSR-E SSM/I

22. Conclusions  Scattering signal shows good correlation to rain rate,  Active+passive mw simulation tools in place and show good agreement with observations  However, sensitivity varies strongly with type of precipitation event  High frequencies (e.g. AMSU 150 GHz) show much better response than lower (AMSU 89 GHz). Sensitivity is about a factor of 1.5 to 2 better.  Sensitivity of scattering signal to variations in surface emissivity is only critical for very dry atmospheres  Collecting AQUA+radar data