THE RESEARCH FOCUS WILL BE TO DEVELOP A DEEP LEARNING APPLICATION TO ENHANCE THE RESOLUTION OF GPM DATA FOR IMPROVED IDENTIFICATION OF CONVECTIVE SCALE PRECIPITATION FEATURES PARTICULARLY OUTSIDE THE RANGE OF GROUND-BASED WEATHER RADAR. THIS RESOLUTION ENHANCEMENT TECHNOLOGY IS CALLED SUPER-RESOLUTION OR DOWNSCALING. DEEP LEARNING CONVOLUTIONAL NEURAL NETWORKS (CNNS) WILL BE USED TO LEARN FEATURES THAT CAN INFER HIGH-RESOLUTION INFORMATION FROM LOW-RESOLUTION VARIABLES BUILDING ON A PROTOTYPE DEVELOPED BY THE PI OF THIS PROPOSAL IN COLLABORATION WITH GPM MISSION SCIENTISTS.