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Measurement Uncertainty and Error Propagation
of Satellite-based Precipitation Sensors

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Philosophy, Methodology and Data Publications and Presentations
Progresses and New Results References


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. Amer. Meteor. Soc., 82, 1377-1396.

Arkin, P. A., and P. P. Xie (1994), The global precipitation climatology project: First Algorithm Intercomparison Project,  Bull. Amer. Meteor. Soc., 75, 401-419.

Bell, T. L. and P. K. Kundu, 1996: A study of the sampling error in satellite rainfall estimates using optimal averaging of data and a stochastic model. J. Climate, 9, 1251-1268.

Bell, T. L. and P. K. Kundu, 2000: Dependence of satellite sampling error on monthly averaged rain rates: Comparison of simple models and recent studies. J. Climate, 13, 449-462.

Bell, T. L. and P. K. Kundu, 2003: Comparing satellite rainfall estimates with rain gauge data: Optimal strategies suggested by a spectral model. J. Geophys. Res., 108, 4121.

Bell, T. L., P. K. Kundu, and C. D. Kummerow, 2001: Sampling errors of SMM/I and TRMM rainfall averages: Comparison with error estimates from surface data and a simple model. J. Appl. Meteor., 40, 938--954.

Caires, S., and A. Sterl, 2003: Validation of ocean wind and wave data using triple collocation, J. Geophys. Res., 108, 3098, doi:10.1029/2002JC001491.

Chen, M., W. Shi, P. Xie, V. B. S. Silva, V. E. Kousky, R. Wayne Higgins, and J. E. Janowiak, 2008: Assessing objective techniques for gauge-based analyses of global daily precipitation. J. Geophys. Res., 113, D04110, doi:10.1029/2007JD009132.

Crow, W. T., 2010: Acquiring observation error covariance information for land data assimilation systems. AMS 24th Conf. Hydrology, January 17-21, Atlanta, GA.

Daly, C., R.P. Neilson, and D.L. Phillips, 1994: A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteor., 33, 140-158.

Daly, C., W. P. Gibson, G.H. Taylor, G. L. Johnson, P. Pasteris. 2002. A knowledge-based approach to the statistical mapping of climate. Climate Research, 22: 99-113.

Ebert, E.E., J.E. Janowiak, and C. Kidd, 2007: Comparison of near real time precipitation estimates from satellite observations and numerical models. Bull. Amer. Met. Soc., 88, 47-64.

Ferraro, R. R., F. Weng, N. C. Grody and L. Zhao, 2000:, Precipitation characteristics over land from the NOAA-15 AMSU sensor. Geophys. Res. Lett., 27, 2669-72.

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. Hydrometeor., 6, 573-598.

Higgins, R. W., W. Shi, and E. Yarosh, 2000: Improved United States precipitation quality control system and analysis. NCEP/Climate Prediction Center Atlas 7, 40 pp., National Centers for Environmental Prediction, Camp Springs, Maryland.

Hsu, K., X. Gao, S. Sorooshian, and H.V. Gupta, 1997: Precipitation estimation from remotely sensed information using artificial neural networks. J. App. Meteor., 36, 1176-1190.

Huffman, G. J, 1997: Estimates of root-mean-square random error for finite samples of estimated precipitation, J. Appl. Meteor., 36, 1191-1201.

Huffman, G. J., and Coauthors, 2007: The TRMM multi-satellite precipitation analysis (TMPA): Quasi-global, multi-year, combined-sensor precipitation estimates at fine scales. J. Hydrometeor., 8, 38-55.

Huffman, G. J., R. F. Adler, D. T. Bolvin, and E. J. Nelkin, 2009: The TRMM Multi-satellite Precipitation Analysis (TMPA). in Satellite Applications for Surface Hydrology, F. Hossain and M. Gebremichael, Eds., Springer, in press.

Iguchi, T., T. Kozu, R. Meneghini, J. Awaka, and K. Okamoto, 2000: Rain-profiling algorithm for the TRMM precipitation radar, J. Appl. Meteorol., 39, 2038-2052.

Janssen, P. A. E. M., S. Abdalla, H. Hersbach, and J.R. Bidlot, 2007: Error estimation of buoy, satellite, and model wave height data. J. Atmos. Oceanic Technol., 24, 1665-1677.

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. Hydrometeor., 5, 487.503.

Joyce, R. J., P. Xie, and Y. Yarosh, 2008: A Kalman filter approach to blend various satellite rainfall estimates in CMORPH . 4th International Precipitation Working Group Meeting, Oct. 12-16, Beijing, China.

Kubota, T.,  and Coauthors, 2007: Global precipitation map using satelliteborne microwave radiometers by the GSMaP Project : Production and validation. IEEE Trans. Geosci. Remote Sens., 45, 2259-2275.

Kubota, T., T. Ushio, S. Shige, S. Kida, M. Kachi, and K. Okamoto, 2009: Verification of high resolution satellite-based rainfall estimates around Japan using gauge-calibrated ground radar dataset. J. Meteor. Soc. Japan, 87A, 203-222.

Kummerow, C., and Coauthors, 2001: The evolution of the Goddard profiling algorithm (GPROF) for rainfall estimation from passive microwave sensors. J. Appl. Meteor., 40, 1801-1820.

Laughlin, C. R., 1981: On the effect of temporal sampling on the observation of mean rainfall. NASA Technical Report, Document ID: 19830017014, 8pp. Available at NASA Goddard Space Flight Center.

Lin, X., and A.Y. Hou, 2008: Evaluation of coincident passive microwave rainfall estimates using TRMM PR and ground measurements as references. J. Appl. Meteor. Climatol., 47, 3170.3187.

Lin, Y., and K. E. Mitchell, 2005: The NCEP Stage II/IV hourly precipitation analyses: Development and applications. 19th Conference on Hydrology, San Diego, CA, Amer. Meteor. Soc., Jan. 9-13.

McCollum, J. R., W. F. Krajewski, R. R. Ferraro, and M. B. Ba, 2002: Evaluation of biases of satellite rainfall estimation algorithms over the continental United States. J. Appl. Meteorol., 41, 1065-1080.

McCollum, J. R., and R. R. Ferraro, 2003: Next generation of NOAA/NESDIS TMI, SSM/I, and AMSR-E microwave land rainfall algorithms, J. Geophys. Res., 108, doi:10.1029/2001JD001512.

Nijssen, B., and D. Lettenmaier, 2004: Effect of precipitation sampling error on simulated hydrological fluxes and states: Anticipating the Global Precipitation Measurement satellites, J. Geophys. Res., 109, D02103, doi:10.1029/2003JD003497.

Okamoto, K., T. Iguchi, N. Takahashi, K. Iwanami, and T. Ushio, 2005: The global satellite mapping of precipitation (GSMaP) project. 25th IGARSS Proceedings, 3414-3416.

Sapiano, M. R. P., and P. A. Arkin, 2009: An intercomparison and validation of high-resolution satellite precipitation estimates with 3-hourly gauge data. J. Hydrometeor., 10, 149-166.

Scipal, K., T. Holmes, R. De Jeu, V. Naeimi, and W. Wagner (2008), A possible solution for the problem of estimating the error structure of global soil moisture data sets, Geophys. Res. Lett., 35, DOI: 10.1029/2008GL035599.

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. Amer. Meteor. Soc., 81, 2035-2046.

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. J. Clim., 16, 3759-3778.

Stoffelen, A., 1998: Toward the true near-surface wind speed: Error modeling and calibration using triple collocation, J. Geophys. Res., 103, 7755~7766.

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. Hydrometeor., 8, 1165-1183.

Tian, Y. and C. D. Peters-Lidard (2007), Systematic anomalies over inland water bodies in satellite-based precipitation estimates, Geophys. Res. Lett., 34, L14403.

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.

Tian, Y., C. D. Peters-Lidard, R. F. Adler, T. Kubota, and T. Ushio (2010), Evaluation of GSMaP precipitation estimates over contiguous U.S. J. Hydrometeor., 11, 566-574

Tian, Y., C. D. Peters-Lidard and J. B. Eylander (2010), Real-time error reduction for satellite-based precipitation estimates. J. Hydrometeor., 11, 1275–1285.

Tian, Y. and C. D. Peters-Lidard (2010), A global map of uncertainties in satellite-based precipitation measurements. Geophys. Res. Lett., 37, L24407.

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.  Rem. Sens., 43, 1059-1069.

Ushio T., and Coauthors, 2009: A Kalman filter approach to the Global Satellite Mapping of Precipitation (GSMaP) from combined passive microwave and infrared radiometric data. J. Meteor. Soc. Japan, 87A, 137-151.

Villarini, G., W. F. Krajewski, and J. A. Smith (2009), New paradigm for statistical validation of satellite precipitation estimates: Application to a large sample of the TMPA 0.25° 3-hourly estimates over Oklahoma, J. Geophys. Res., 114, D12106, doi:10.1029/2008JD011475.

Weng, F., Zhao, L., Ferraro, R.R., Poe, G., Li, X., and Grody, N. C., 2003:  Advanced Microwave Sounding Unit cloud and precipitation algorithms.  Radio Sci., 38, 8068-8079.

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