Evaluating Detection Skills of Satellite Rainfall Estimates over Desert Locust Recession Regions

Abstract This paper evaluates rainfall detection capabilities of seven satellite rainfall estimates over the desert locust recession regions of the world. The region of interest covers the arid and semiarid region from northwestern Africa to northwestern India. The evaluated satellite rainfall products are the African rainfall climatology (ARC), rainfall estimation algorithm (RFE), Tropical Rainfall Measuring Mission 3B42 and its real-time version (3B42RT), NOAA/Climate Prediction Center morphing technique (CMORPH), and two versions of the Global Satellite Mapping of Precipitation moving vector with Kalman filter (GSMaP-MVK and GSMaP-MVK+). The reference data were obtained from the Desert Locust Information Service of the United Nations Food and Agriculture Organization (FAO). The FAO data are qualitative information collated by desert locust survey teams from different countries during field campaigns. Such data can only be used to assess the rainfall detection capabilities of the satellite products. The...

[1]  A. Gruber,et al.  Discrepancy between Gauges and Satellite Estimates of Rainfall in Equatorial Africa , 2000 .

[2]  T. Oki,et al.  An Evaluation of Over-Land Rain Rate Estimates by the GSMaP and GPROF Algorithms: The Role of Lower-Frequency Channels , 2009 .

[3]  Sharon E. Nicholson,et al.  The nature of rainfall variability over Africa on time scales of decades to millenia , 2000 .

[4]  Keith Cressman,et al.  Preventing desert locust plagues: optimizing management interventions , 2007 .

[5]  Ralph Ferraro,et al.  TRMM 2A12 Land Precipitation Product - Status and Future Plans , 2009 .

[6]  Natalie M. Mahowald,et al.  Mineral aerosol and cloud interactions , 2003 .

[7]  J. I. Magor,et al.  Preparedness to prevent Desert Locust plagues in the Central Region: an historical review: Part 2. Appendices , 2007 .

[8]  J. U. Hielkema,et al.  Operational use of environmental satellite remote sensing and satellite communications technology for global food security and locust control by FAO: The ARTEMIS and DIANA systems , 1994 .

[9]  T. Takemi.  Evaporation of rain falling below a cloud base through a deep atmospheric boundary layer over an arid region , 1999 .

[10]  K. Iwanami,et al.  High precision and high resolution global precipitation map from satellite data , 2008, 2008 Microwave Radiometry and Remote Sensing of the Environment.

[11]  C. Ropelewski,et al.  Validation of satellite rainfall products over East Africa's complex topography , 2007 .

[12]  A. Herman,et al.  Objectively determined 10-day African rainfall estimates created for famine early warning systems , 1997 .

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

[14]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

[15]  D. Rosenfeld.  Aerosols, Clouds, and Climate , 2006, Science.

[16]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[17]  Pietro Ceccato,et al.  The desert locust upsurge in West Africa (2003 – 2005): Information on the desert locust early warning system and the prospects for seasonal climate forecasting , 2007 .

[18]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[19]  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.

[20]  Yale Mintz,et al.  Evaporation of rain falling from convective clouds as derived from radar measurements , 1988 .