WE HAVE TWO RELATED OBJECTIVES FOR THIS PROPOSED PROJECT. THE FIRST IS MOTIVATED BY THE DESIRE TO FULLY EXPLORE THE INFORMATION CONTENT IN A-TRAIN DATA AS IT PERTAINS TO MBL SHALLOW CONVECTIVE CLOUDS. THIS ACTIVITY WHILE EXPANDING WHAT WE CAN LEARN FROM A-TRAIN ALSO HAS DIRECT APPLICATIONS TO DEVELOPING APPROACHES THAT CAN BE APPLIED TO THE NEXT GENERATION OF REMOTE SENSORS THAT ARE EXPECTED IN THE NEXT DECADE. THE SECOND OBJECTIVE IS MOTIVATED BY CONTEMPORARY INTEREST IN THE SOUTHERN OCEAN REGION DUE TO ITS CHARACTERISTICS AND SPECIFIC CHALLENGES IN UNDERSTANDING CLOUD AND PRECIPITATION PROCESSES. GIVEN THAT THIS REGION IS MOSTLY REMOVED FROM DIRECT ANTHROPOGENIC AND EVEN CONTINENTAL INFLUENCES WE CAN EXPLORE THE POTENTIAL FOR A-TRAIN DATA OVER THIS REGION TO ADDRESS FUNDAMENTAL QUESTIONS REGARDING CLOUD-PRECIPITATION PROCESSES AND EVEN CLIMATE FEEDBACKS ASSOCIATED WITH MBL CLOUDS. THESE OBJECTIVES CAN BE SUMMARIZED WITH SPECIFIC TASKS AS FOLLOWS: 1. AUGMENTED BY THE GEOSTATIONARY IMAGERY TIME SERIES EXPLORE THE CAPACITY FOR A-TRAIN DATA TO CHARACTERIZE THE CLOUD-PRECIPITATION MICROPHYSICAL PROCESSES IN MBL SHALLOW CONVECTIVE CLOUDS. THIS WILL ENTAIL THE FOLLOWING TASKS: A. ADAPT TRACKING ALGORITHMS TO FOLLOW BOUNDARY LAYER CLOUD COMPLEXES IN HIGH TEMPORAL AND SPATIAL RESOLUTION GEOSTATIONARY IMAGERY SEQUENCES THAT BRACKET A-TRAIN TRACKS. B. ESTIMATE THE LIFECYCLE STATES OF THE CLOUD ELEMENTS SAMPLED BY THE A-TRAIN SENSORS ALLOWING FOR MORE TAILORED APPLICATION OF CLOUD STATE PRIOR DATA IN RETRIEVALS. C. APPLY EXISTING CLOUD-PRECIPITATION PROCESS RETRIEVAL ALGORITHMS (MACE ET AL. 2016; MACE AND AVEY; 2017) TO A-TRAIN DATA TO DEVELOP LONG-TERM STATISTICS OF THE CLOUD-PRECIPITATION MICROPHYSICAL PROCESSES. D. EXPLORE NEW RETRIEVAL APPROACHES AS FOLLOWS: I. INCORPORATE ICE-PHASE PRECIPITATION SCATTERING PROPERTIES IN SHALLOW CONVECTIVE CLOUDS WHERE ICE PHASE IS INDICATED. II. INCORPORATE W-BAND PATH INTEGRATED ATTENUATION (PIA) IN RETRIEVAL ALGORITHM III. INCORPORATE CALIPSO ATTENUATION-DEPOLARIZATION RATIO RELATION IN RETRIEVAL ALGORITHM IV. USE MARKOV CHAIN MONTE CARLO TECHNIQUES TO CHARACTERIZE THE INFORMATION CONTENT OF SPECIFIC MEASUREMENT COMBINATIONS. 2. WITH ADVANCED RESEARCH-GRADE ALGORITHMS DEVELOPED WITH PRIOR FUNDING AND OBJECTIVE 1 ADDRESS RELEVANT SCIENCE QUESTIONS IN THE SOUTHERN OCEAN REGION: A. BY COMPOSITING CLOUDS INTO METEOROLOGICAL REGIMES BASED ON LARGE-SCALE FORCING USE EMERGENT CONSTRAINT TECHNIQUES (KLEIN ET AL 2015) TO EXAMINE THE SENSITIVITY OF MICROPHYSICAL PROPERTIES AND PRECIPITATION PRODUCING PROCESSES IN SHALLOW CONVECTION AS A FUNCTION OF TEMPERATURE REGIME AND LARGE-SCALE FORCING. EXAMINE CLOUD PHASE FEEDBACKS AND PHASE PARTITIONING IN MBL CLOUDS AS A FUNCTION OF SEASON AND LARGE-SCALE REGIME.