RE CALIBRATED PERSIANN CCS IS ONE OF THE ALGORITHMS USED IN INTEGRATED MULTISATELLITE RETRIEVALS FOR GPM TO PROVIDE HIGH RESOLUTION PRECIPITATION ESTIMATIONS ACROSS THE TIME PERIOD OF NASA GLOBAL PRECIPITATION MEASUREMENT AND TROPICAL RAINFALL MEASUREMENT MISSIONS. IN THIS STUDY WE PLAN TO IMPROVE THE WARM RAIN ESTIMATION FROM THE PERSIANN CCS ALGORITHM. THE CURRENT SATELLITE BASED CLOUD IMAGE SEGMENTATION THRESHOLD OF THE PERSIANN CCS ALGORITHM IS SET TO 253K. UNDER THE CURRENT SETTING RAINFALL FROM WARMER CLOUDS IS NOT ESTIMATED. WE PLAN TO IMPROVE DETECTION AND ESTIMATION OF WARM RAIN FROM THE CURRENT ALGORITHM BY SETTING A HIGHER TEMPERATURE THRESHOLD FOR CLOUD IMAGE SEGMENTATION AND RAINFALL ESTIMATION. THE PROPOSED RESEARCHWILL IMPROVE RECALIBRATED PERSIANN CCS ESTIMATION IN SUPPORT OF NASA GPM IMERG. THE END GOAL OF THE PROPOSED RESEARCH IS TO IMPROVE THE ACCURACY OF PERSIANN CCS AND ENHANCE OUR ABILITY TO SUPPORT NASA GPM TO MONITOR GLOBAL PRECIPITATION FOR HYDROLOGIC APPLICATIONS