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The Relation Between SST, Clouds, Precipitation and Wave Structures Across the Equatorial Pacific

The Relation Between SST, Clouds, Precipitation and Wave Structures Across the Equatorial Pacific. Anita D. Rapp and Chris Kummerow 14 July 2008. AMSR Science Team Meeting. Lau and Wu (2003). Motivation.

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The Relation Between SST, Clouds, Precipitation and Wave Structures Across the Equatorial Pacific

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  1. The Relation Between SST, Clouds, Precipitation and Wave Structures Across the Equatorial Pacific Anita D. Rapp and Chris Kummerow 14 July 2008 AMSR Science Team Meeting

  2. Lau and Wu (2003) Motivation • Recent studies have shown that warm rain systems in the Tropics may be sensitive to the underlying SST • There have been many studies tying cloud feedbacks to SST, but it is also important to understand the relationship between the clouds and precipitation with SST

  3. Why are warm rain systems important to the climate system? • Warm rain systems are prevalent in the Tropics and contribute to the total tropical rainfall • They affect the radiation budget, mostly through their interaction with shortwave radiation • In the absence of other changes, a reduction in warm rain cloud amount would allow more solar radiation to reach the surface • Also affect the hydrologic cycle through their moistening of the lower troposphere which preconditions the atmosphere for deep convection • A reduction in the amount of evaporating warm rain clouds could alter the recycling timescales for deep convection

  4. Are these systems responding to SST? Original idea was to look at retrievals from a variety of sensors and algorithms to see how warm rain systems respond to SST. No rain Rain

  5. What to do? • Modify microwave optimal estimation algorithm to - • Ingest deconvolved microwave Tbs • Take into account partially cloud-filled pixels • Calculate emission/scattering for raining pixels • Data - • TMI brightness temperatures • 10,19, 37, 21, 85 GHz Tbs • VIRS cloud fraction • PR precipitable water and rain height • RSS TMI-derived SST 30° S – 30° N, 130° E – 170° W

  6. TMI Deconvolution • Used to place all microwave channels on a common spatial resolution • Method utilizes footprint overlap between adjacent pixels • Modifies footprint resolution while minimizing error propagation Enhanced cloud scale features Sharpened coast lines

  7. Basic OE Algorithm Minimize Cost Function: • Ingest Observed Brightness Temperatures (TBs) • Prior Knowledge of Atmospheric State (Water Vapor, Wind, Cloud Water) Adjust Water Vapor, Wind, Cloud Water Simulate TBs Iterate Establish Convergence Criteria Retrieval (Determine Validity of Retrieval)

  8. Modifications to OE Algorithm • New inputs - • Ingest deconvolved TMI Tbs • VIRS cloud fraction calculated within TMI footprint • Specify the rain column from PR-derived rain water and rain height Modify cost function - TBCLDincludes scattering and extinction from calculated from PR rain water VIRS Cloud fraction within TMI footprint

  9. Results

  10. Sensitivity to Resampling

  11. Sensitivity to Cloud Fraction

  12. Sensitivity to Rain Water

  13. Results w/ SST No rain Rain

  14. Testing Influence on Deep Convective Time Scales • One of the most obvious deep convective events in the Tropics is the Madden-Julian Oscillation • MJO identified by numerous studies in April – May 2001 • Study time series of surface, atmospheric and cloud properties • Examine the influence of properties of warm rain systems on lower tropospheric moistening

  15. MJO Case Study Results

  16. Further Testing Influence on Tropospheric Water Vapor • Examine easterly waves in the Pacific • Determine whether the properties of warm rain clouds are correlated with tropospheric moistening From Serra & Houze (2002) From Serra et al. (2006)

  17. Tropical Disturbance Results

  18. Summary • When effects of resolution, partially cloudy pixels, and rainfall are taken into account, visible and microwave sensor retrievals show better agreement • Results indicate a change in the behavior of cloud properties from non-raining to raining clouds • LWP changes little with SST for non-raining clouds, but strongly decreases with SST in warm rain clouds • Microwave retrieval error diagnostics indicate that deconvolution and cloud fraction information generally improves the retrieval, but very low cloud fraction and rainfall information can influence it in either direction • MJO case study suggests that warm rain systems are correlated to moistening in low - mid levels • Indicates that behavior of warm rain systems may be tied to recycling timescales of deep convection

  19. Summary and Discussion • Easterly wave composites show that properties of non-raining clouds are fairly invariant with passage of wave • Easterly wave composites also show that cloud properties associated with warm raining systems are correlated with moistening • Need to study more equatorial wave cases to try to cement link between properties of warm rain clouds and lower tropospheric moistening • Techniques used in this study could be applied to AMSR-E by combining it with other instruments in the A-Train by using information from MODIS and/or AIRS, CloudSat, and Calipso

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