DESCRIPTION: PR-OBS-1
Precipitation rate at ground by MW conical scanners (with indication of phase)

Maps of instantaneous precipitation (mm/hr) generated from MW conical scanning radiometers in sun synchronous orbit

  • Coverage: Strips of ~ 1400 km swath crossing the H-SAF area [25-75°N lat, 25° W-45° E long] in direction approx. S-N or N-S
  • Cycle: Up to six passes/day (if three DMSP satellites are available) at approximately 05:30, 06:30, 08:00 ECT (descending mode) and 17:30, 18:30, 20:00 ECT (ascending mode)
  • Spatial Resolution: Approximately 30 km (SSMIS 37 GHz channel resolution).
  • Accuracy:
    Precipitation range threshold target optimal
    > 10 mm/h 90 80 25
    1-10 mm/h 120 105 50
    < 1 mm/h 240 145 90
    Accuracy requirements for product PR-OBS-1 [RMSE (%)]
  • Timeliness: 150 min from observing time
  • Dissemination: By dedicated lines to centres connected by GTS - By EUMETCast to most other users, especially scientific
  • Formats: BUFR with values on grid points corresponding to the SSMIS 37 GHz channel orbital projection

Short description of the basic principles for product generation

Measurements in both window and absorption bands of SSMIS The relationship that links passive microwave brightness temperatures to precipitation has a variable degree of complexity (from minimum at the lower frequencies over the sea to maximum at higher frequencies over land). Precipitation at the ground can be derived from the knowledge of the vertical structure of the precipitating cloud, in terms of hydrometeors and environmental conditions, and of how this influences the brightness temperatures at the different channels. In PR-OBS-1 this knowledge is obtained through the use of Cloud Resolving Model (CRM) simulations, which provide the microphysical structure and the meteorological parameters needed to fully describe a precipitating cloud system, coupled to Radiative Transfer Model, to build what is referred to as a Cloud Dynamic Radiation Database (CDRD). This database is used as a-priori knowledge in a Bayesian retrieval scheme. The scheme works on all types of background surface conditions, and uses synthetic dynamical and thermodynamical variables derived from ECMWF analysis/forecasts as further constraints in the retrieval process to reduce non-uniquess problem affecting the retrieval solution.