Satellite rainfall estimates: new perspectives for meteorology and climate from the EURAINSAT project

Satellite meteorology is facing a crucial period of its history since recent missions have revealed instrumental for quantitative rainfall measurements from space and newly conceived missions are at hand. International partnership is rapidly developing and research projects keep the community focused on rapidly developing research and operational issues. A perspective is given through the structure of EURAINSAT, a project of the 5th Framework Programme of the European Commission. Its key objective is the development of algorithms for rapidly-updated satellite rainfall estimations at the geostationary scale. The project is fostering international research on satellite rainfall estimations building a bridge between Europe and the U.S. for present and future missions.

[1]  R. Scofield,et al.  The Operational GOES Infrared Rainfall Estimation Technique , 1998 .

[2]  S. Sorooshian,et al.  Evaluation of PERSIANN system satellite-based estimates of tropical rainfall , 2000 .

[3]  P. Bauer Over-Ocean Rainfall Retrieval from Multisensor Data of the Tropical Rainfall Measuring Mission. Part I: Design and Evaluation of Inversion Databases , 2001 .

[4]  A General Form of Kuo's Cumulus Parameterization , 1985 .

[5]  Robert F. Adler,et al.  Estimation of Monthly Rainfall over Japan and Surrounding Waters from a Combination of Low-Orbit Microwave and Geosynchronous IR Data , 1993 .

[6]  Robert F. Adler,et al.  Rain Estimation from Satellites: An Examination of the Griffith-Woodley Technique , 1984 .

[7]  P. Bauer,et al.  Algorithms for the retrieval of rainfall from passive microwave measurements , 1994 .

[8]  R. Houze,et al.  The MAP special observing period , 2001 .

[9]  W. Menzel,et al.  Introducing GOES-I: The First of a New Generation of Geostationary Operational Environmental Satellites , 1994 .

[10]  P. A. Watson,et al.  Prediction of attenuation on satellite-Earth links for systems operating with low fade margins , 1994 .

[11]  W. Petersen,et al.  On the relationship between cloud‐to‐ground lightning and convective rainfall , 1998 .

[12]  Eric A. Smith,et al.  Use of the MSG SEVIRI channels in a combined SSM/I, TRMM and geostationary IR method for rapid updates of rainfall , 2000 .

[13]  J. Susskind,et al.  Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations , 2001 .

[14]  A. Gruber,et al.  GOES Multispectral Rainfall Algorithm (GMSRA) , 2001 .

[15]  Ziad S. Haddad,et al.  The TRMM 'Day-1' Radar/Radiometer Combined Rain-Profiling Algorithm , 1997 .

[16]  M. Todd,et al.  A Combined Satellite Infrared and Passive Microwave Technique for Estimation of Small-Scale Rainfall , 1999 .

[17]  Woodley,et al.  Deep convective clouds with sustained supercooled liquid water down to -37.5 degrees C , 2000, Nature.

[18]  W. Cotton,et al.  New RAMS cloud microphysics parameterization part I: the single-moment scheme , 1995 .

[19]  Dong-Bin Shin,et al.  The Evolution of the Goddard Profiling Algorithm (GPROF) for Rainfall Estimation from Passive Microwave Sensors , 2001 .

[20]  Ye Hong,et al.  A Texture-Polarization Method for Estimating Convective–Stratiform Precipitation Area Coverage from Passive Microwave Radiometer Data , 2001 .

[21]  F. Marzano,et al.  Combined cloud-microwave radiative transfer modeling of stratiform rainfall , 2000 .

[22]  P. A. Watson,et al.  Attenuation and countermeasures in millimeter‐wave point‐to‐multipoint networks , 1993 .

[23]  Itamar M. Lensky,et al.  Estimation of Precipitation Area and Rain Intensity Based on the Microphysical Properties Retrieved from NOAA AVHRR Data , 1997 .

[24]  Jacques Testud,et al.  Study and Tests of Improved Rain Estimates from the TRMM Precipitation Radar , 2001 .

[25]  V. Ramanathan,et al.  Aerosols, Climate, and the Hydrological Cycle , 2001, Science.

[26]  R. Pielke,et al.  A comprehensive meteorological modeling system—RAMS , 1992 .

[27]  Chris Kidd,et al.  On rainfall retrieval using polarization-corrected temperatures , 1998 .

[28]  Peter Bauer,et al.  Outlook for Combined TMI–VIRS Algorithms for TRMM: Lessons from the PIP and AIP Projects , 1998 .

[29]  M. King,et al.  Cloud Retrieval Algorithms for MODIS : Optical Thickness , Effective Particle Radius , and Thermodynamic Phase , 2000 .

[30]  V. Levizzani,et al.  IR‐based satellite and radar rainfall estimates of convective storms over northern Italy , 2000 .

[31]  Eric A. Smith,et al.  Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. II: Emission-source and generalized weighting-function properties of a time-dependent cloud-radiation model , 1993 .

[32]  Rosenfeld,et al.  Suppression of rain and snow by urban and industrial air pollution , 2000, Science.

[33]  P. Bauer,et al.  A Melting-Layer Model for Passive/Active Microwave Remote Sensing Applications. Part I: Model Formulation and Comparison with Observations , 2001 .

[34]  Johannes Schmetz,et al.  Precipitation estimations from geostationary orbit and prospects for METEOSAT Second Generation , 2001 .

[35]  Emmanouil N. Anagnostou,et al.  Assessment of the Use of Lightning Information in Satellite Infrared Rainfall Estimation , 2000 .

[36]  W. Olson,et al.  An Assessment of the First- and Second-Generation Navy Operational Precipitation Retrieval Algorithms , 1998 .

[37]  D. Rosenfeld TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall , 1999 .

[38]  K. Okamoto,et al.  Rain profiling algorithm for the TRMM precipitation radar , 1997, IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development.

[39]  Mark Pinsky,et al.  Notes on the state-of-the-art numerical modeling of cloud microphysics , 2000 .

[40]  Clemens Simmer,et al.  Profiling Cloud Liquid Water by Combining Active and Passive Microwave Measurements with Cloud Model Statistics , 2001 .

[41]  Yinon Rudich,et al.  Desert dust suppressing precipitation: A possible desertification feedback loop , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[42]  M. B. Mathur,et al.  A New Method of Observed Rainfall Assimilation in Forecast Models , 2000 .

[43]  Eric A. Smith,et al.  Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. I: Brightness-temperature properties of a time-dependent cloud-radiation model , 1992 .

[44]  Itamar M. Lensky,et al.  Satellite-Based Insights into Precipitation Formation Processes in Continental and Maritime Convective Clouds , 1998 .

[45]  A. Pokrovsky,et al.  Simulating convective clouds with sustained supercooled liquid water down to −37.5°C using a spectral microphysics model , 2001 .

[46]  N. Tartaglione,et al.  Numerical Simulations of the 1994 Piedmont Flood: Role of Orography and Moist Processes , 1998 .

[47]  Larry M. McMillin,et al.  Constrained Regression in Satellite Meteorology , 1996 .

[48]  Marco Borga,et al.  Rainfall estimation by combining radar and infrared satellite data for nowcasting purposes , 1999 .

[49]  M. Baker,et al.  Lightning flash rate and type in convective storms , 1998 .

[50]  William L. Woodley,et al.  Deep convective clouds with sustained supercooled liquid water down to -37.5 °C , 2000, Nature.

[51]  E. Anagnostou,et al.  Overland Precipitation Estimation from TRMM Passive Microwave Observations , 2001 .

[52]  F. Marzano,et al.  Use of cloud model microphysics for passive microwave-based precipitation retrieval : Significance of consistency between model and measurement manifolds , 1998 .