Developing an Online Information System Prototype for Global Satellite Precipitation Algorithm Validation and Intercomparison

Abstract Over the decades, significant progress has been made in satellite precipitation product development. In particular, temporal resolution and timely availability have been improved by blended techniques. The resulting products, including near-real-time precipitation products, are widely used in various research and applications. However, the lack of support for user-defined areas or points of interest poses a major obstacle to quickly gaining knowledge of product quality and behavior on a local or regional scale. Current online operational intercomparison and validation services have not addressed this issue adequately. This paper describes an ongoing work to develop an online information system prototype for global satellite precipitation algorithm validation and intercomparison, to overcome current shortcomings by providing dynamic and customized information to users on the expected bias and accuracy of the products, and to give algorithm developers a better understanding of the strengths and wea...

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

[2]  J. Janowiak,et al.  A Real–Time Global Half–Hourly Pixel–Resolution Infrared Dataset and Its Applications , 2001 .

[3]  Florian Meier,et al.  Dynamics and predictability of a heavy dry-season precipitation event over West Africa - sensitivity experiments with a global model. , 2009 .

[4]  Chris Kidd,et al.  Satellite Rainfall Estimation Using a Combined Pasive Microwave and Infrared Algorithm. , 2003 .

[5]  Matthew M. Mills,et al.  Iron and phosphorus co-limit nitrogen fixation in the eastern tropical North Atlantic , 2004, Nature.

[6]  Gilberto A. Vicente Global Satellite Datasets: Data Availability for Scientists and Operational Users , 2007 .

[7]  William Teng,et al.  Online Visualization and Analysis: A New Avenue to use Satellite Data for Weather, Climate, and Interdisciplinary Research and Applications , 2007 .

[8]  Darren R. Peck,et al.  Colony-specific foraging behaviour and co-ordinated divergence of chick development in the wedge-tailed shearwater Puffinus pacificus , 2005 .

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

[10]  Kuolin Hsu,et al.  Estimation of physical variables from multichannel remotely sensed imagery using a neural network: Application to rainfall estimation , 1999 .

[11]  Gregory Leptoukh,et al.  Giovanni: A Web Service Workflow-Based Data Visualization and Analysis System , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[12]  Frank S. Marzano,et al.  Multivariate Probability Matching for Microwave Infrared Combined Rainfall Algorithm (MICRA) , 2007 .

[13]  G. P. Cressman AN OPERATIONAL OBJECTIVE ANALYSIS SYSTEM , 1959 .

[14]  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.

[15]  Peter Allerup,et al.  Accuracy of Point Precipitation Measurements , 1980 .

[16]  G. Huffman,et al.  A Screening Methodology for Passive Microwave Precipitation Retrieval Algorithms , 1998 .

[17]  Gregory G. Leptoukh,et al.  Online analysis enhances use of NASA Earth science data , 2007 .

[18]  P. Arkin,et al.  Improved Estimates of Tropical and Subtropical Precipitation Using the GOES Precipitation Index , 1997 .

[19]  Alan H. Strahler,et al.  Monitoring the response of vegetation phenology to precipitation in Africa by coupling MODIS and TRMM instruments , 2005 .

[20]  P. Xie,et al.  Global Precipitation: A 17-Year Monthly Analysis Based on Gauge Observations, Satellite Estimates, and Numerical Model Outputs , 1997 .

[21]  Xiaoling Chen,et al.  An Assessment of the Biases of Satellite Rainfall Estimates over the Tibetan Plateau and Correction Methods Based on Topographic Analysis , 2008 .

[22]  Bart Nijssen,et al.  Effect of precipitation sampling error on simulated hydrological fluxes and states: Anticipating the Global Precipitation Measurement satellites , 2004 .

[23]  H. Koschmieder,et al.  METHODS AND RESULTS OF DEFINITE RAIN MEASUREMENTS , 1934 .

[24]  Elizabeth E. Ebert,et al.  Methods for Verifying Satellite Precipitation Estimates , 2007 .

[25]  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 .

[26]  F. Joseph Turk,et al.  Toward Improvements in Short-time Scale Satellite-Derived Precipitation Estimates using Blended Satellite Techniques , 2007 .

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