Maps of instantaneous precipitation (mm/hr) generated from MW conical scanning radiometers in sun synchronous orbit
Precipitation range | threshold | target | optimal |
> > 10 mm/h | 90 | 80 | 25 |
> 1-10 mm/h | 120 | 105 | 50 |
< 1 mm/h | 240 | 145 | 90 |
The relationship linking passive microwave brightness temperatures to precipitation has a variable degree of complexity depending on background surface, cloud microphysical and macrophysical structure, environmental conditions, channel frequency, viewing geometry and spatial resolution. In P-IN-SSMIS this relationship is obtained through the use of Cloud Resolving Model (CRM) simulations, which provide the microphysical structure and the meteorological/environmental parameters needed to fully describe a precipitating cloud system, coupled to a Radiative Transfer Model, for calculating simulated satellite TB vectors consistent with the SSMIS PMW radiometers' channel frequencies, viewing angles and IFOV sizes. A large physically-based database is generated and used in the a-priori knowledge 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. training phase of an artificial neural network algorithm. Window channels and absorption bands channels are used, exploiting the differential effect of liquid drops or ice particles at different frequencies associated to weighting functions peaking in different atmospheric layers.
Sano, P., Casella, D., Mugnai, A., Schiavon, G., Smith, E. A., & Tripoli, G. J. (2013). Transitioning from CRD to CDRD in Bayesian retrieval of rainfall from satellite passive microwave measurements: Part 1. Algorithm description and testing. IEEE transactions on geoscience and remote sensing, 51(7), 4119-4143. Casella, D., Panegrossi, G., Sano, P., Dietrich, S., Mugnai, A., Smith, E. A., ... & Mehta, A. V. (2013). Transitioning from CRD to CDRD in Bayesian retrieval of rainfall from satellite passive microwave measurements: Part 2. Overcoming database profile selection ambiguity by consideration of meteorological control on microphysics. IEEE transactions on geoscience and remote sensing, 51(9), 4650-4671. Smith, E. A., Leung, H. Y., Elsner, J. B., Mehta, A. V., Tripoli, G. J., Casella, D., ... & Sanò, P. (2013). Transitioning from CRD to CDRD in Bayesian retrieval of rainfall from satellite passive microwave measurements: Part 3-Identification of optimal meteorological tags. Natural Hazards and Earth System Sciences, 13(5), 1185.
Belgium
2012
Belgium
2011
Hungary
2011
Hungary
2011
Italy
2012
Italy
2011
Poland
2013
Poland
2011
Slovakia
2012
Algorithm Theoretical Baseline Document (ATBD)
2.1
Product User Manual (PUM)
2.1
Product Validation Report (PVR)
1.1
Operational Reports