A practical guide to a space-time stochastic error model for simulation of high resolution satellite rainfall data

Satellite Rainfall Applications for Surface Hydrology

Volumn , Issue , 2010, Pages 145-167

  Hossain, Faisal ^a   Tang, Ling ^a   Anagnostou, Emmanouil N ^b   Nikolopoulos, Efthymios I ^b  

^a Tennessee Technological University   (United States)

^b UNIVERSITY OF CONNECTICUT   (United States)

Author keywords

Infrared; Passive microwave; Satellite rainfall; Uncertainty

Indexed keywords

EID: 77953339213     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-90-481-2915-7_9     Document Type: Chapter

References (22)

1. Anagnostou, E. N. and W. F. Krajewski. (1997). Simulation of radar reflectivity fields: Algorithm formulation and evaluation. Water Resources Research, vol. 33, 6, pp. 1419-1428
2. Bras, R. L. and I. Rodriguez-Iturbe. (1976). Rainfall generation: A non-stationary time-varying multidimensional model. Water Resources Research, vol. 12, 3, pp. 450-456
3. Ciach, G. J., W. F. Krajewski, and G. Villarini. (2007). Product-error-driven uncertainty model for probabilistic quantitative precipitation estimation with NEXRAD data. J. Hydrometeorology., vol. 8, pp. 1325-1347
4. Eagleson, P. S.. (1972). Dynamics of flood frequency. Water Resources Research, 8, 878-898
5. Ebert, E. E.. (2008). Fuzzy verification of high resolution gridded forecasts: A review and proposed framework. Meteorological Applications, In press
6. Fowler, H. J., C. G. Kilsby, P. E. O'Connell, and A. Burton. (2005). A weather-type conditioned multi-site stochastic rainfall model for the generation of scenarios of climatic variability and change. Journal of Hydrology, vol.8, 1-4, pp. 50-66
7. Gebremichael, M. and W. F. Krajewski. (2004). Characterization of the temporal sampling error in space-time-averaged rainfall estimates from satellites. Journal of Geophysical Research, vol. 109, D11, doi: D11110 0.1029/2004JD004509
8. Hong, Y., K. -L. Hsu, S. Sorooshian, and X. Gao. (2005). Self-organizing nonlinear output (SONO): A neural network suitable for cloud patch-based rainfall estimation from satellite imagery at small scales. Water Resources Research, vol. 41, W03008, doi:10.1029/ 2004WR003142
9. Hossain, F. and E. N. Anagnostou. (2006). A two-dimensional satellite rainfall error model. IEEE Transactions on Geosciences and Remote Sensing, vol. 44, pp. 1511-1522, DOI: 10.1109/TGRS.2005.863866
10. Hossain, F. and G. J. Huffman. (2008). Investigating error metrics for satellite rainfall at hydrologically relevant scales. Journal of Hydrometeorology, vol. 9, 3, pp. 563-575
11. Huffman, G. J.. (1997). Estimates of root mean square random error for finite samples of estimated precipitation. Journal of Applied Meteorology, vol. 36, pp. 1191-1201
12. Huffman, G. J.. (2005). Hydrological applications of remote sensing: Atmospheric states and fluxes - precipitation (from satellites) (active and passive techniques. Encyclopedia for Hydrologic Sciences, eds. M. G. Anderson and J. McDonnell. ISBN: 978-0-471-49103-3
13. 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 Multi-satellite Precipitation Analysis: Quasi-Global, Multi-Year, Combined-Sensor Precipitation Estimates at Fine Scale. Journal of Hydrometeorology, vol. 8, pp. 38-55
14. Jordan, P. W., A. W. Seed, and P. E. Weinmann. (2003). A stochastic model of radar measurement errors in rainfall accumulations at catchment scale. J. Applied Meteorology, vol. 4, pp. 841-855
15. Joyce, R. L., 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, vol. 5, pp. 487-503
16. 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, vol. 4, 1088-1104
17. Lee, K. H. and E. N. Anagnostou. (2004). Investigation of the nonlinear hydrologic response to precipitation forcing in physically based land surface modeling. Canadian Journal of Remote Sensing, 30, 5, pp.706-716
18. Mantoglou, A. and J. L. Wilson. (1982). The Turning Bands method for simulation of random fields using line generation by a spectral method. Water Resources Research, vol.18, 5, pp. 1379-1394
19. Sorooshian, S., K. -L. Hsu, X. Gao, H. V. Gupta, B. Imam, and D. Braithwaite. (2000). Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bulletin of American Meteorological Society, vol. 81, pp. 2035-2046
20. Steiner, M., T. L. Bell, Y. Zhang, and E. F.Wood. (2003). Comparison of two methods for estimating the sampling-related uncertainty of satellite rainfall averages based on a large radar dataset. Journal of Climate, vol. 16, pp. 3759-3778
21. Stewart, R. E., J. D. Marwitz, and J. C. Pace. (1984). Characteristics through melting layer of stratiform clouds. Journal of Atmospheric Science, 41, 22, pp. 3227-3237
22. Waymire, E. and V. K. Gupta. (1981). The mathematical structure of rainfall representations. 1. A review of the stochastic rainfall models. Water Resources Research, vol. 17, 5, pp. 1261-1272.