The Prediction and Data Assimilation for Cloud (PANDA-C) Project

The Prediction and Data Assimilation for Cloud (PANDA-C) project to improve prediction of global clouds using satellites.
Prediction of clouds and their cooling or warming effects are important both on time scales of hours to days (e.g. for solar energy) and on the longer time scales of climate.  The Prediction and Data Assimilation for Cloud (PANDA-C) project, funded by the United States Air Force, aims at improved prediction of global clouds by capitalizing on remotely sensed observations from satellites.  An added benefit of the project has been greatly expanded satellite data assimilation for MMM's MPAS model through use of tools from the Joint Effort for Data assimilation Integration (JEDI) developed by the Joint Center for Satellite Data Assimilation (JCSDA).
 
Shown are brightness temperatures from channel 9 of the Advanced Himawari Imager (AHI) aboard the Japanese geostationary weather satellite Himawari-8 (left) and a simulation of the same quantity based on a 6-hour MPAS forecast and using the Unified Forward Operator (UFO) in JEDI (right).