A global map of uncertainties in satellite-based precipitation measurements

Geophysical Research Letters

Volumn 37, Issue 24, 2010, Pages

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

^a UNIVERSITY OF MARYLAND   (United States)

^b NASA GODDARD SPACE FLIGHT CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LANDFORMS; RAIN; RAIN GAGES;

COLD SEASON; COMPLEX TERRAINS; CONVECTIVE PRECIPITATION; DATA SETS; ERROR CHARACTERISTICS; ERROR FEATURE; GLOBAL MAP; GLOBAL UNCERTAINTY; GLOBAL VIEW; HIGH LATITUDES; LAND SURFACE; MEASUREMENT UNCERTAINTY; OCEANIC REGIONS; PRECIPITATION MEASUREMENT; RAIN RATES; RELATIVE UNCERTAINTY; SEASONAL VARIATION; SOUTH AMERICA; TIBETAN PLATEAU; VALIDATION DATA; WATERBODIES;

UNCERTAINTY ANALYSIS;

COAST; COMPUTER SIMULATION; DATA SET; ESTIMATION METHOD; LATITUDE; MAPPING METHOD; MEASUREMENT METHOD; PRECIPITATION INTENSITY; SATELLITE IMAGERY; SEASONAL VARIATION; TROPICAL ENVIRONMENT; UNCERTAINTY ANALYSIS;

CHINA; QINGHAI-XIZANG PLATEAU; SOUTH AMERICA;

EID: 79251468728     PISSN: 00948276     EISSN: None     Source Type: Journal    
DOI: 10.1029/2010GL046008     Document Type: Article

References (18)

1. Adler, R. F., A. J. Negri, P. R. Keehn, and I. M. Hakkarinen (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, doi:10.1175/1520-0450(1993) 0322.0.CO;2.
2. Adler, R. F., C. Kidd, G. Petty, M. Morissey, and H. M. Goodman (2001), Intercomparison of global precipitation products: The Third Precipitation Intercomparison Project (PIP-3), Bull. Am. Meteorol. Soc., 82, 1377-1396, doi:10.1175/1520-0477(2001)0822.3.CO;2.
3. Adler, R. F., J.-J. Wang, G. Gu, and G. J. Huffman (2009), A ten-year tropical rainfall climatology based on a composite of TRMM products, J. Meteorol. Soc. Jpn., 87A, 281-293, doi:10.2151/jmsj.87A.281.
4. 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, doi:10.1175/BAMS-88-1-47. (Pubitemid 46351194)
5. 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, doi:10.1175/JHM437.1. (Pubitemid 41685191)
6. Hsu, K., X. Gao, S. Sorooshian, and H. V. Gupta (1997), Precipitation estimation from remotely sensed information using artificial neural networks, J. Appl. Meteorol., 36, 1176-1190, doi:10.1175/1520-0450 (1997)0362.0.CO;2.
7. Huffman, G. J. (1997), Estimates of root-mean-square random error for finite samples of estimated precipitation, J. Appl. Meteorol., 36, 1191-1201, doi:10.1175/1520-0450(1997)0362.0.CO;2.
8. 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, doi:10.1175/JHM560.1. (Pubitemid 46444451)
9. Janowiak, J. E., V. E. Kousky, and R. J. Joyce (2005), Diurnal cycle of precipitation determined from the CMORPH high spatial and temporal resolution global precipitation analyses, J. Geophys. Res., 110, D23105, doi:10.1029/2005JD006156. (Pubitemid 43141247)
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, doi:10.1175/1525-7541(2004)0052.0.CO;2.
11. Kubota, T., et al. (2007), Global precipitation map using satellite-borne microwave radiometers by the GSMaP project: Production and validation, IEEE Trans. Geosci. Remote Sens., 45, 2259-2275, doi:10.1109/ TGRS.2007.895337.
12. Lin, X., and A. Y. Hou (2008), Evaluation of coincident passive microwave rainfall estimates using TRMM PR and ground measurements as references, J. Appl. Meteorol. Climatol., 47, 3170-3187, doi:10.1175/ 2008JAMC1893.1.
13. McCollum, J. R., and R. R. Ferraro (2005), Microwave rainfall estimation over coasts, J. Atmos. Oceanic Technol., 22, 497-512, doi:10.1175/ JTECH1732.1.
14. Okamoto, K., T. Iguchi, N. Takahashi, K. Iwanami, and T. Ushio (2005), The global satellite mapping of precipitation (GSMaP) project, IEEE Trans. Geosci. Remote Sens., 8, 3414-3416.
15. Sapiano, M.R.P., andP.A.Arkin (2009),Anintercomparison and validation of high-resolution satellite precipitation estimates with 3-hourly gauge data, J. Hydrometeorol., 10, 149-166, doi:10.1175/2008JHM1052.1.
16. Tian, Y., C. Peters-Lidard, J. Eylander, R. Joyce, G. Huffman, R. Adler, K.-L. Hsu, F. J. Turk, M. Garcia, and J. Zeng (2009), Component analysis of errors in satellite-based precipitation estimates, J. Geophys. Res., 114, D24101, doi:10.1029/2009JD011949.
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, doi:10.1109/ TGRS.2004.841627.
18. Vila, D. A., L. G. G. De Goncalves, D. L. Toll, and J. R. Rozante (2009), Statistical evaluation of combined daily gauge observations and rainfall satellite estimates over continental South America, J. Hydrometeorol., 10, 533-543, doi:10.1175/2008JHM1048.1.