top banner
top banner

NASA Project Detail - PMM / IMERG

Integration of PERSIANN-CCS in the Next-Generation GPM Multi-Sensor Precipitation Retrieve Algorithm

Introduction

Maximizing the utility of satellite precipitation observations in operational hydro-meteorological applications requires precipitation measurements in near-real time and at fine spatial and temporal resolutions. With NASA's Global Precipitation Measurement (GPM) Multi-Satellite Working Group, this project has a specific goal to develop a next-generation GPM multi-sensor precipitation retrieval algorithm, "IMERG" (Integrated Multi-satellitE Retrievals for GPM). IMERG is designed to develop a merged precipitation algorithm for use in GPM. It combines the precipitation estimates from various satellite passive microwave (PMW) sensors into half-hourly fields and provides them to both the CPC Morphing-Kalman Filter (CMORPH-KF, Joyce and Xie 2011) and the PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System) re-calibration scheme. The proposed activities will support developing, testing, and implementing the re-calibration of PERSIANN-CCS algorithm in GPM IMERG. GPM ground validation (GV) data and the national radar network will be used to validate the estimation.

The objectives for this project are to:

  1. Develop the IMERG multi-sensor precipitation retrieval algorithm with the overarching goal to minimize lead time while maintaining high-quality precipitation estimates at high resolution.
  2. Continue the development and quality improvement of PERSIANN-CCS including the integration of passive microwave rainfall information to adjust PERSIANN-CCS rainfall estimates.
  3. Perform product validation using National Weather Service Stage IV radar estimates, National Severe Storm Laboratory Q2 radar data and the GPM ground validation testbed and field campaign measurements.