Precipitation rate at ground by MW cross track scanners

Maps of instantaneous precipitation (mm/hr) generated from MW cross-track scanning radiometers in sun synchronous orbit. Currently processing data from ATMS on board SNPP and Noaa20 satellites.

• Coverage: Strips of ~ 2250 km swath crossing the MSG 0 Degree Full Disk area [60°S-75°N lat, 60° W-60° E long]
• Cycle: Up to 4 passes/day at approximately 01:30ECT (descending mode) and 13:30 ECT (ascending mode)
• Spatial Resolution: Corresponds to the nominal resolution nominal resolution of ATMS high frequency channels, varying with the viewing scan angle from 15.82 x 15.82 km2/circular at nadir to 26 x 52 km2/ovate at the 45th scanning position.
• Accuracy:

  Precipitation range	threshold	target	optimal
  > > 1 mm/h	200	150	100

  • Accuracy requirements for product P-IN-ATMS [FSE (%)]
• Timeliness: 30 min from observing time
• Dissemination: By dedicated lines to centres connected by GTS - By EUMETCast to most other users, especially scientific
• Formats: NETCDF with values on grid points corresponding to the ATMS orbital projection. Also JPEG or similar for quick-look

P-IN-ATMS is based on a neural network approach and provides precipitation rate estimates from the Advanced Technology Microwave Sounder (ATMS). The algorithm optimally exploits the different characteristics of ATMS channels, and their combinations, including the brightness temperature (TB) differences of the 183.31 channels, with the goal of having a single neural network for different types of background surfaces. The training of the neural network is based on the use of a cloud radiation database, built from cloud-resolving model simulations coupled to a radiative transfer model, representative of the European and African precipitation climatology (LAT 60°S - 75°N, LON 60°W - 60°E). The algorithm provides the surface precipitation rate (mm/h), the phase of the precipitation, and a pixel-based confidence index for the evaluation of the reliability of the retrieval..

Sanò, P., Panegrossi, G., Casella, D., Marra, A. C., Di Paola, F., & Dietrich, S. (2016). The new Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for the cross-track scanning ATMS radiometer: description and verification study over Europe and Africa using GPM and TRMM spaceborne radars. Atmospheric Measurement Techniques, 9(11), 5441.