1. Comparison of Oceanic Warm Rain from AMSR-E and CloudSat Matt Lebsock Chris Kummerow

2. Motivation Radiosonde data [Ohtake, 1963] – Warm rain falls in all tropical ocean basins in all seasons more frequently than expected Shipboard Weather Reports [Petty, 1995] – Drizzle and isolated showers are the preferred form of precipitation in many regions DYCOMS-II [VanZanten et al., 2005] – ‘on roughly a third of the flights mean surface rates approached or exceeded 0.5 mmd -1 ’ ’ RICO [Snodgrass et al., 2009] – in situ: 2.23 mmd -1 – PR: 1.05 mmd -1 – GPCP: 1.25 mmd -1 VOCALS [Wood et al., 2011] – POC boundary: 10-20 mmd -1 – Open Cells: several mmd -1 – Closed cell: 90% evaporation of drizzle And many more….

3. Motivation from CloudSat Areas in the subtropical eastern ocean basins where rain fraction exceeds 5%. Dominated by warm rain. Small spatial scales (~5km)  This rain poses a significant challenge to AMSR-E. Spatial scale Moderate emmsission signature No ice scattering  Is it important?

4. CloudSat Algorithm Sensitivity: Reflectivity vs. Attenuation Reflectivity Solution Attenuation Solution Rain Rates Observations Challenges 1.Attenuation 2.Multiple-scattering 3.Limited sensitivity at high rates Opportunities 1.Extreme sensitivity to light/moderate rain 2.~1km Spatial resolution  Useful for quantifying rain from shallow isolated moist convection that other sensors may miss

5. CloudSat vs. AMSR-E Key Points 1.Regions of under-catch by the CloudSat algorithm in the deep tropics can be related to saturation of the CloudSat signal in the heaviest rain. 1.CloudSat observes more rain than AMSR-E in regions that have been historically difficult for the passive microwave sensors:  The storm tracks  The subtropical ocean basins  AMSR-E version GPROF-2004.  AMSR-E subset to CloudSat ground track (2007-2008).  Common data screening methodology has been employed to both datasets. (1) (2) (3)

6. Daily Average Precipitation (2006-2009) Areal Mean Precipitation (mm/day) 2C-Rain-Profile0.23 2C-PRECIP-COLUMN0.36 CloudSat w/ Z-R0.28 EPIC In Situ (Comstock et al. 2004) 0.20 New CloudSat rain rates perform better than initial estimates. 1.Reflectivity based solution 2.Evaporation modeled Climatological Validation of CloudSat: Southeast Pacific Courtesy of Anita Rapp (TAMU)

7. Distribution of Warm Rain Accumulation dominated by frequency of occurrence, not intensity Accumulation maxima: – East-Pac ITCZ – Trade Cumulus regions.

8. Dependence on Cloud Depth

9. Regime Dependence Warm rain rates are maximized at moderate boundary layer depths and moisture contents Suppressed Ice phase prevalent

10. Conceptual Model Inversion EastWest

11. CloudSat vs. AMSR-E: Warm Rain 1.AMSR-E subset to CloudSat ground Track 2.Common Data screening: – 1 degree boxes in which CloudSat observes no clouds colder than 273 K retained. – Warm rain near deep convection or cirrus screened.  AMSR-E warm = f * CloudSat warm  f = 11%

12. How much warm rain does GPROF miss? Ocean 60N/60SGlobal CloudSat Warm Rain0.34 [mm/day]0.23 [mm/day] AMSR-E Missed (f = 11%)0.30 [mm/day]0.20 [mm/day] ~ 5 W/m 2 Ocean 60N/60SGlobal CloudSat Warm Rain (screened)0.11 [mm/day]0.071 [mm/day] AMSR-E Missed (screened)0.10 [mm/day]0.062 [mm/day] Screened Scenes All Scenes

13. GPROF 2010? AMSR-E (GPROF-2010) produces more light rain. Designed to reproduce Precipitation Radar results. PR still misses most warm rain. Courtesy of Wes Berg (CSU) GPROF 2004 GPROF 2010

14. Summary CloudSat rain rates suggest that GPROF-2004 may miss up to 0.2 mmd -1 globally. – Small spatial extent (~5km) – Light/moderate rates – Warm tops GPROF-2010 will increase light rain rates however regional differences will most likely leave room for further improvement. The dominant mode of missed rain is shallow cumulus in the trades and the ITCZ (Not drizzle) in regimes with moderate boundary layer depths and moisture contents. 1.Difficult to distinguish from cloud emission 2.No scattering signal