Systematic anomalies over inland water bodies in satellite-based precipitation estimates

Geophysical Research Letters

Volumn 34, Issue 14, 2007, Pages

  Tian, Yudong ^a   Peters Lidard, Christa D ^b  

^a UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

^b NASA GODDARD SPACE FLIGHT CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; ESTIMATION; RADAR; RAIN GAGES; REMOTE SENSING; SATELLITE IMAGERY;

GROUND-BASED RADAR; RAIN RATE;

RAIN;

DATA SET; GROUND-BASED MEASUREMENT; HYDROLOGICAL CYCLE; IMAGE ANALYSIS; MICROWAVE IMAGERY; PIXEL; PRECIPITATION ASSESSMENT; SATELLITE DATA; SATELLITE IMAGERY;

EID: 34548597029     PISSN: 00948276     EISSN: None     Source Type: Journal    
DOI: 10.1029/2007GL030787     Document Type: Article

References (17)

1. Adler, R. F., P. R. Keehn, and I. M. Hakkainen (1993), Estimation of monthly rainfall over Japan and surrounding waters from a combination of low-orbit microwave and geosynchronous IR data, J. Appl. Meteorol., 32, 335-356.
2. Ebert, E. E., J. E. Janowiak, and C. Kidd (2007), Comparison of near-real-time precipitation estimates from satellite observations and numerical models, Bull. Am. Meteorol. Soc., 88, 47-64.
3. Ferraro, R. R., E. A. Smith, W. Berg, and G. J. Huffman (1998), A screening methodology for passive microwave precipitation retrieval algorithms, J. Atmos. Sci., 55, 1583-1600.
4. Gottschalck, J., J. Meng, M. Rodell, and P. Houser (2005), Analysis of multiple precipitation products and preliminary assessment of their impact on Global Land Data Assimilation System land surface states, J. Hydrometeorol., 6, 573-598.
5. Grody, N. C. (1991), Classification of snow cover and precipitation using the Special Sensor Microwave Imager, J. Geophys. Res., 96, 7423-7435.
6. Hansen, M. C., R. S. DeFries, J. R. Townsend, and R. Sohlberg (2000), Global land cover classification at 1 km spatial resolution using a classification tree approach, Int. J. Remote Sens., 21, 1331-1364.
7. Higgins, R. W., W. Shi, and E. Yarosh (2000), Improved United States precipitation quality control system and analysis, in NCEP/Climate Prediction Center Atlas, vol. 7, 40 pp., Natl. Cent. for Environ. Predict., Camp Springs, Md.
8. Huffman, G. J., R. F. Adler, P. Arkin, A. Chang, R. Ferraro, A. Gruber, J. Janowiak, A. McNab, B. Rudolph, and U. Schneider (1997), The global precipitation climatology project (GPCP) combined precipitation dataset, Bull. Am. Meteorol. Soc., 78, 5-20.
9. 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 (TMPA): Quasi-global, multi-year, combined-sensor precipitation estimates at fine scales, J. Hydrometeorol., 8, 38-55.
10. 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, J. Hydrometeorol., 5, 487-503.
11. Kidd, C., D. R. Kniveton, M. C. Todd, and T. J. Bellerby (2003), Satellite rainfall estimation using combined passive microwave and infrared algorithms, J. Hydrometeorol., 4, 1088-1104.
12. Kummerow, C. Y., et al. (2001), The evolution of the Goddard Profiling Algorithm (GPROF) for rainfall estimation from passive microwave sensors, J. Appl. Meteorol., 40, 1801-1840.
13. Lin, Y., and K. E. Mitchell (2005), The NCEP stage II/IV hourly precipitation analyses: Development and applications, paper presented at 19th Conference on Hydrology, Am. Meteorol. Soc., San Diego, Calif.
14. Seo, D. J. (1998), Real-time estimation of rainfall fields using radar rainfall and rain gauge data, J. Hydrol., 208, 37-52.
15. 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, Bull. Am. Meteorol. Soc., 81, 2035-2046.
16. Tian, Y., C. D. Peters-Lidard, B. J. Choudhury, and M. Garcia (2007), Multitemporal analysis of TRMM-based satellite precipitation products for land data assimilation applications, J. Hydrometeorol, in press.
17. Turk, F. J., and S. D. Miller (2005), Toward improving estimates of remotely-sensed precipitation with MODIS/AMSR-E blended data techniques, IEEE Trans. Geosci. Remote Sens., 43, 1059-1069.