Extreme precipitation estimation using satellite-Based PERSIANN-CCS algorithm

Satellite Rainfall Applications for Surface Hydrology

Volumn , Issue , 2010, Pages 49-67

  Hsu, Kuo Lin ^a   Behrangi, Ali ^a   Imam, Bisher ^a   Sorooshian, Soroosh ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Extreme precipitation; Hurricane Katrina; Image segmentation; Probability matching method; Self organizing feature map

Indexed keywords

EID: 84891382236     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-90-481-2915-7_4     Document Type: Chapter

References (33)

1. Atlas, D., D. Rosenfeld, and D. B. Wolff, 1990: Climatologically turned reflectivity-rainrate relationship and links to area-time integrals. Journal of Applied Meteorology, 29, 1120-1135
2. Ba, M. B. and A. Gruber, 2001: GOES multispectral rainfall algorithm (GMSRA). Journal of Applied Meteorology, 40, 1500-1514
3. Behrangi, A., K. Hsu, B. Imam, S. Sorooshian, and R. J. Kuligowski, 2009a: Evaluating the utility of multi-spectral information in delineating the areal extent of precipitation. Journal of Hydrometeorology, In 10, 684-700
4. Behrangi, A., K. L. Hsu, B. Imam, S. Sorooshian, G. J. Huffman, and R. J. Kuligowski, 2009b: PERSIANN-MSA: A precipitation estimation method from satellite-based multi-spectral analysis. Journal of Hydrometeorology, In press
5. Bellerby, T., M. Todd, D. Kniveton, and C. Kidd, 2000: Rainfall estimation from a combination of TRMM Precipitation Radar and GOES multi-spectral satellite imagery through the use of an artificial neural network. Journal of Applied Meteorology, 39, 2115-2128
6. Bellerby, T., 2004: A feature-based approach to satellite precipitation monitoring using geostationary IR imagery. Journal of Hydrometeorology, 5, 910-921
7. Bellerby, T., K. Hsu, and S. Sorooshian, 2009: LMODEL: A satellite precipitation algorithm using cloud development modeling and model updating. Part 1: Model development and calibration. Journal of Hydrometeorology, In press
8. Capacci, D. and B. J. Conway, 2005: Delineation of precipitation areas from MODIS visible and infrared imagery with artificial neural networks. Meteorological Applications, 12, 291-305
9. Cheng, M., R. Brown, and C. G. Collier, 1993: Delineation of precipitation areas using Meteosat infrared and visible data in the region of the United Kingdom. Journal of Applied Meteorology, 32, 884-898
10. Desbois, M., G. Seze, and G. Szejwach, 1982: Automatic Classification of Clouds on METEOSAT imagery: Application to high-level clouds. Journal of Applied Meteorology, 21, 401-412
11. Dobrin, B. P., T. Viero, andM. Gabbouj, 1994: Fast watershed algorithms: analysis and extensions. Nonlinear Image Processing V,2180, 209-220, SPIE
12. Griffith, C. G., W. L. Woodley, P. G. Grube, D. W. Martin, J. Stout, and D. N. Sikdar, 1978: Rain estimation from geosynchronous satellite imagery - visible and infrared studies. Monthly Weather Review, 106, 1153-1171
13. Hsu, K., X. Gao, S. Sorooshian, and H. V. Gupta, 1997: Precipitation estimation from remotely sensed information using artificial neural networks. Journal of Applied Meteorology, 36, (9), 1176-1190
14. Hsu, K., H. Gupta, X. Gao, and S. Sorooshian, 1999: Estimation of physical variables from multichannel remotely sensed imagery using a neural network: Application to rainfall estimation. Water Resources Research, 35, 1605-1618
15. Hsu, K., Y. Hong, and S. Sorooshian, 2007: Rainfall estimation using a cloud patch classification map. Measurement of Precipitation from Space: EURAINSAT and Future. Edited by V. Levizzani, P. Bauer, and F. J. Turk, Springer Publishing Company, 745 pages, Hardcover, ISBN#978-1-4240-5834-9, pp. 329-343
16. Hsu, K., T. Bellerby, and S. : Sorooshian, 2009. LMODEL: A Satellite Precipitation Algorithm Using Cloud Development Modeling and Model Updating. Part 2: Model Updating. In press
17. Huffman, G. J., R. F. Adler, D. T. Bolvin, G. Gu, E. J. Nelkin, K. P. Bowman, Y. Hong, E. F. Stocker, and D. B. Wolff, 2007: The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales. Journal of Hydrometeorology, 8, 38-55
18. Hong, Y., K. Hsu, S. Sorooshian, and X. Gao, 2004: Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system. Journal of Applied Meteorology, 43, 1834-1852
19. Joyce, R. J., J. E. Janowiak, P. A. Arkin, and P. Xie, 2004: CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. Journal of Hydrometeorology, 5, 487-503
20. Kidd, C., D. R. Kniveton, M. C. Todd, and T. J. Bellerby, 2003: Satellite rainfall estimation using combined passive microwave and infrared algorithms. Journal of Hydrometeorology, 4, 1088-1104
21. Kohonen, T., 1995: Self-Organizing Map. Springer-Verlag, New York
22. Kurino, T., 1997: A satellite infrared technique for estimating "deep/shallow" precipitation. Satellite Data Applications: Weather and Climate, 19, 511-514
23. Marzano, F. S., M. Palmacci, D. Cimini, G. Giuliani, and F. J. Turk, 2004: Multivariate statistical integration of Satellite infrared and microwave radiometric measurements for rainfall retrieval at the geostationary scale. IEEE Transactions on Geoscience and Remote Sensing, 42, 1018-1032
24. National Weather Service, NOAA, 2006: Service Assessment: Hurricane Katrina, August 23-31, 2005
25. Nicholson, S. E., B. Some, J. McCollum, E. Nelkin, D. Klotter, Y. Berte, B. M. Diallo, I. Gaye, G. Kpabeba, O. Ndiaye, J. N. Noukpozounkou, M. M. Tanu, A. Thiam, A. A. Toure, and A. K. Traore, 2003a: Validation of TRMM and other rainfall estimates with a high-density gauge dataset for West Africa. Journal of Applied Meteorology, 42, Part I, 1337-1354
26. Nicholson, S. E., B. Some, J. McCollum, E. Nelkin, D. Klotter, Y. Berte, B. M. Diallo, I. Gaye, G. Kpabeba, O. Ndiaye, J. N. Noukpozounkou, M. M. Tanu, A. Thiam, A. A. Toure, and A. K. Traore, 2003b: Validation of TRMM and other rainfall estimates with a high-density gauge dataset for West Africa. Journal of Applied Meteorology, 42, Part II, 1355-1368
27. Osullivan, F., C. H. Wash, M. Stewart, and C. E. Motell, 1990: Rain estimation from infrared and visible GOES satellite data. Journal of Applied Meteorology, 29, 209-223
28. Sorooshian, S., K. Hsu, X. Gao, H. V. Gupta, B. Imam, and D. Braithwaite, 2000: Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bulletin of the American Meteorological Society, 81, 2035-2046
29. Todd, M., C. Kidd, D. R. Kniveton, and T. J. Bellerby, 2001: A combined satellite infrared and passive microwave technique for the estimation of small scale rainfall. Journal of Atmospheric and Oceanic Technology, 18, 742-755
30. Turk, F. J. and S. D. Miller, 2005: Toward improving estimates of remotely-sensed precipitation with MODIS/AMSR-E blended data techniques. IEEE Transactions on Geoscience and Remote Sensing, 43, 1059-1069
31. Ushio, T., T. Kubota, S. Shige, K. Okamoto, K. Aonashi, T. Inoue, N. Takahashi, T. Iguchi, M. Kachi, R. Oki, T. Morimoto, and Z. Kawasaki, 2008: A Kalman filter approach to the Global Satellite Mapping of Precipitation (GSMaP) from combined passive microwave and infrared radiometric data. Journal of Meteorology Society Japan, 87A, 137-151
32. Vincent, L. and P. Soille, 1991:Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13, (6), 583-598
33. Vincent, G., R. A. Scofield, and W. P. Mensel, 1998: The operational GOES infrared rainfall estimation technique. Bulletin of the American Meteorological Society, 79, 1883-1898. Xu, L., X. Gao, S. Sorooshian, and P. A. Arkin, 1999: A microwave infrared threshold technique to improve the GOES precipitation index. Journal of Applied Meteorology, 38, 569-579.