References

Adler, R., G. J. Huffman, A. Chang, et al. 2003. The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979-present). Journal of Hydrometeorology 4(6):1147-1167. doi: http://dx.doi. org/10.1175/1525-7541.

Aghakouchak, A., L. Cheng, O. Mazdiyasni, and A. Farahmand. 2014. Global warming and changes in risk of concurrent climate extremes: Insights from the 2014 California drought. Geophysical Research Letters 41:8847-8852. doi: http://dx.doi. org/10.1002/2014GL062308.

AghaKouchak, A., A. Farahmand, J. Teixeira, et al. 2015. Remote sensing of drought: Progress, challenges and opportunities. Reviews of Geophysics 53(2):452-480. doi: http://dx.doi.org/10.1002/2014RG000456.

Anagnostou, E. N., V. Maggioni, E. Nikolopoulos, T. Meskele, F. Hossain, and A. Papadopoulos. 2010. Benchmarking high-resolution global satellite rainfall products to radar and rain-gauge rainfall estimates. IEEE Transactions on Geoscience and Remote Sensing 48(4):1667-1683.

AghaKouchak, A., and A. Mehran. 2013. Extended contingency table: Performance metrics for satellite observations and climate model simulation. Water Resources Research 49:7144-7149. doi: http://dx.doi.org/10.1002/wrcr.20498.

AghaKouchak, A., and N. Nakhjiri. 2012. A near real-time satellite-based global drought climate data record. Environmental Research Letters 7(4):044037. doi: http://dx.doi.org/10.1088/1748-9326/7/4/044037.

Anderson, M. C., C. R. Hain, B. Wardlow, J. R. Mecikalski, and W. P. Kustas. 2011. Evaluation of drought indices based on thermal remote sensing of evapotrans- piration over the continental U.S. Journal of Climate 24:2025-2044.

Anderson, M. C., C. R. Hain, B. Wardlow, A. Pimstein, J. R. Mecikalski, and W.P. Kustas. 2012. A thermal-based Evaporative Stress Index for monitoring surface moisture depletion. In Remote Sensing for Drought: Innovative Monitoring Approaches, eds. B. Wardlow, M. C. Anderson, and J. Verdin, 145-167. Boca Raton, FL: CRC Press.

Anderson, M. C., and W. P. Kustas. 2008. Thermal remote sensing of drought and evapotranspiration. Eos Transactions American Geophysical Union 89(26): 233-234.

Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. A. Otkin, and W. P. Kustas. 2007. A climatological study of evapotranspiration and moisture stress across the continental U.S. based on thermal remote sensing: II. Surface moisture climatology. Journal of Geophysical Research 112: D11112. doi: http://dx.doi.org/11110. 11029/12006JD007507.

Arkin, P. A., R. Joyce, and J. E. Janowiak. 1994. The estimation of global monthly mean rainfall using infrared satellite data: The GOES Precipitation Index (GPI). Remote Sensing Reviews 11(1—4):107—124. doi: http://dx.doi. org/10.1080/02757259409532261.

Ashouri, H., K.-L. Hsu, S. Sorooshian, et al. 2015. PERSIANN-CDR: Daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bulletin of the American Meteorological Society 96(1):69-83.

Asrar, G., R. B. Myneni, and E. T. Kanemasu. 1989. Estimation of plant canopy attributes from spectral reflectance measurements. In Theory and Applications of Optical Remote Sensing, eds. G. Asrar, 252-296. New York: Wiley.

Baret, F., and G. Guyot. 1991. Potentials and limits to vegetation indices for LAI and APAR assessments. Remote Sensing of Environment 35:161-173.

Behrangi, A., E. J. Fetzer, and S. L. Granger. 2016. Early detection of drought onset using near surface temperature and humidity observed from space. International Journal of Remote Sensing 37:3911-3923.

Behrangi, A., P. Loikith, E. Fetzer, H. Nguyen, and S. Granger. 2015. Utilizing humidity and temperature data to advance monitoring and prediction of meteorological drought. Climate 3:999.

Bolten, J. D., and W. T. Crow. 2012. Improved prediction of quasi-global vegetation conditions using remotely-sensed surface soil moisture. Geophysical Research Letters 39:L19406. doi: http://dx.doi.org/10.1029/2012GL053470.

Bolten, J. D., W. T. Crow, X. Zhan, T. J. Jackson, and C. A. Reynolds. 2010. Evaluating the utility of remotely sensed soil moisture retrievals for operational agricultural drought monitoring. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 3(1):57-66.

Brown, J. F., B. D. Wardlow, T. Tadesse, M. J. Hayes, and B. C. Reed. 2008. The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation. GIScience and Remote Sensing 45(1):16-46.

Burgan, R. E., R. A. Hartford, and J. C. Eidenshink. 1996. Using NDVI to Assess Departure from Average Greenness and Its Relation to Fire Business. Gen. Tech. Rep. INT-GTR-333, U.S. Department of Agriculture, Forest Service, Intermountain Research Station, Ogden, Utah.

Chan, S., R. Bindlish, P. E. O'Neill, et al. 2017. Assessment of the SMAP level 2 passive soil moisture product. IEEE Transaction on Geoscience and Remote Sensing 54(8):4994-5007.

Chappell, A., L. J. Renzullo, T. H. Raupach, and M. Haylock. 2013. Evaluating geostatistical methods of blending satellite and gauge data to estimate near real-time daily rainfall for Australia. Journal of Hydrology 493(17):105-114.

Dai, A. 2012. Increasing drought under global warming in observations and models. Nature Climate Change 3(1):52-58.

Damm, A., L. Guanter, E. Paul-Limoges, et al. 2015. Far-red sun-induced chlorophyll fluorescence shows ecosystem-specific relationships to gross primary production: An assessment based on observational and modeling approaches. Remote Sensing Environment 166:91-105.

De Roo, A. P. J., C. G. Wesseling, and W. P. A. Van Deursen. 2000. Physically based river basin modelling within a GIS: The LISFLOOD model. Hydrological Processes 14(11-12) :15-3 0.

Diamond, H. J., T. R. Karl, M. A. Palecki, et al. 2013. U.S. climate reference network after one decade of operations: Status and assessment. Bulletin of the American Meteorological Society 94(4):485-489.

Ebert, E., J. Janowiak, and C. Kidd. 2007. Comparison of near real time precipitation estimates from satellite observations and numerical models. Bulletin of the American Meteorological Society 88(1):47-64.

Entekhabi, D., E. Njoku, P. O'Neill, et al. 2010. The Soil Moisture Active and Passive (SMAP) mission. Proceedings of the IEEE 98(5):704-716.

Flexas, J., J. M. Escalona, S. Evain, et al. 2002. Steady-state chlorophyll fluorescence (Fs) measurements as a tool to follow variations of net CO2 assimilation and stomatal conductance during water-stress in C3 plants. Physioligia Plantarum 114(2):231-240.

Frankenberg, C., J. B. Fisher, J. Worden, et al. 2011. New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity. Geophysical Research Letters 38:L17706. doi: http://dx.doi. org/10.1029/2011GL048738.

Frankenberg, C., C. O'Dell, J. Berry, et al. 2014. Prospects for chlorophyll fluorescence remote sensing from the Orbiting Carbon Observatory-2. Remote Sensing of Environment 147:1-12.

Funk, C., P. Peterson, M. Landsfeld, et al. 2015. The climate hazards infrared precipitation with stations—A new environmental record for monitoring extremes. Scientific Data 2:150066.

Gebremichael, M. 2010. Framework for satellite rainfall product evaluation. Geophysical Monograph Series 191:265-275.

Hain, C. R., W. T. Crow, M. C. Anderson, and M. T. Yilmaz. 2015. Diagnosing neglected moisture source/sink processes with a thermal infrared-based two- source energy balance model. Journal of Hydrometeorology 16:1070-1086.

Hao, Z., A. AghaKouchak, N. Nakhjiri, and A. Farahmand. 2014. Global integrated drought monitoring and prediction system. Scientific Data 1:140001.

Hayes, M. J., M. D. Svoboda, D. A. Wilhite, and O. V. Vanyarkho. 1999. Monitoring the 1996 drought using the standardized precipitation index. Bulletin of the American Meteorological Society 80(3):429-438.

Hobbins, M. T., A. Wood, D. J. McEvoy, et al. 2016. The evaporative demand drought index. Part 1: Linking drought evolution to variations in evaporative demand. Journal of Hydrometeorology 17(6):1745-1761.

Hong, Y., K. Hsu, X. Gao, and S. Sorooshian. 2004. Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system. Journal of Applied Meteorology and Climatology 43(12):1834-1853.

Hossain, F., and E. N. Anagnostou. 2004. Assessment of current passive-microwave- and infrared-based satellite rainfall remote sensing for flood prediction. Journal of Geophysical Research: Atmospheres 109(D7): 1-14.

Hou, A. Y., R. K. Kakar, S. Neeck, et al. 2014. The global precipitation measurement mission. Bulletin of the American Meteorological Society 95:701-722.

Houborg, R., M. Rodell, B. Li, R. Reichle, and B. F. Zaitchik. 2012. Drought indicators based on model-assimilated Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage observations. Water Resources Research 48(7):W07525. doi: http://dx.doi.org/10.1029/2011WR011291.

Hsu, K., X. Gao, S. Sorooshian, and H. Gupta. 1997. Precipitation estimation from remotely sensed information using artificial neural networks. Journal of Applied Meteorology 36(9):1176-1190.

Huffman, G., R. Adler, D. Bolvin, et al. 2007. The TRMM multi-satellite precipitation analysis: Quasi-global, multiyear, combined-sensor precipitation estimates at fine scale. Journal of Hydrometeorology 8(1):38-55.

Huffman, G. J., D. T. Bolvin, D. Braithwaite, K. Hsu, R. Joyce, and P. Xie. 2014. NASA global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG). NASA Algorithm Theoretical Basis Document (ATBD). Version 4.4. http://pmm.nasa.gov/sites/default/files/document_files/IMERG_ATBD_ V4.4.pdf Accessed June 23, 2017.

Hutchinson, C. F. 1991. Use of satellite data for famine early warning in sub-Saharan Africa. International Journal of Remote Sensing 12:1405-1421.

Ji, L., and A. J. Peters. 2003. Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sensing of Environment 87:85-98.

Joyce, R., and P. A. Arkin. 1997. Improved estimates of tropical and subtropical precipitation using the GOES Precipitation Index. Journal of Atmospheric and Oceanic Technology 14(5):997-1011.

Joyce, R., J. Janowiak, P. 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(3):487-503.

Kalma, J. D., T. R. McVicar, and M. F. McCabe. 2008. Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data. Surveys in Geophysics 29(4):421-469.

Karnieli, A., N. Agam, R. T. Pinker, et al. 2010. Use of NDVI and land surface temperature for drought assessment: Merits and limitations. Journal of Climate 23:618-633.

Katiraie-Boroujerdy, P. S., N. Nasrollahi, K. Hsu, and S. Sorooshian. 2013. Evaluation of satellite-based precipitation estimation over Iran. Journal of Arid Environments 97:205-219.

Kerr, Y., A. Al-Yarri, N. Rodriguez-Fernandez, et al. 2016. Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation. Remote Sensing of Environment 180:40-63.

Kerr, Y. H., P. Waldteufel, J. P. Wigneron, et al. 2010. The SMOS mission: New tool for monitoring key elements of the global water cycle. Proceedings of the IEEE 98(5):666-687.

Kiladze, R. I., and A. S. Sochilina. 2003. On the new theory of geostationary satellite motion. Astronomical and Astrophysical Transactions 22(4-5):525-528.

Kogan, F. 1990. Remote sensing of weather impacts on vegetation. International Journal of Remote Sensing 11:1405-1419.

Kogan, F. 1995. Application of vegetation index and brightness temperature for drought detection. Advances in Space Research 15:91-100.

Kogan, F., and J. Sullivan. 1993. Development of global drought-watch system using NOAA/AVHRR data. Advances in Space Research 13:219-222.

Koster, R. D., M. J. Suarez, A. Ducharne, M. Stieglitz, and P. Kumar. 2000. A catchment- based approach to modeling land surface processes in a general circulation model 1. Model structure. Journal of Geophysical Research 105:24809-24822.

Kumar, S. V., R. H. Reichle, R. D. Koster, W. T. Crow, and C. D. Peters-Lidard. 2009. Role of subsurface physics in the assimilation of surface soil moisture observations. Journal of Hydrometeorology 10:1534-1547.

Kummerow, C., Y. Hong, W. Olson, et al. 2001. The evolution of the Goddard profiling algorithm (GPROF) for rainfall estimation from passive microwave sensors. Journal of Applied Meteorology 40(11):1801-1820.

Kummerow, C., W. S. Olson, and L. Giglio. 1996. A simplified scheme for obtaining precipitation and vertical hydrometeor profiles from passive microwave sensors. IEEE Transactions on Geoscience Remote Sensing 34(5):1213-1232.

Kustas, W., and M. Anderson. 2009. Advances in thermal infrared remote sensing for land surface modeling. Agricultural and Forest Meteorology 149(12):2071-2081.

Maggioni, V., M. R. Sapiano, R. F. Adler, Y. Tian, and G. J. Huffman. 2014. An error model for uncertainty quantification in high-time-resolution precipitation products. Journal of Hydrometeorology 15(3):1274-1292.

McEvoy, D. J., J. L. Huntington, M. T. Hobbins, et al. 2016. The evaporative demand drought index. Part II: CONUS-wide assessment against common drought indicators. Journal of Hydrometeorology 17(6):1763-1779.

McKee, T. B., N. J. Doesken, and J. Kleist. 1995. Drought monitoring with multiple time scales. Ninth Conference on Applied Climatology, Dallas, Texas, January 15-20, pp. 233-236.

McVicar, T. R., and P. B. Bierwirth. 2001. Rapidly assessing the 1997 drought in Papua New Guinea using composite AVHRR imagery. International Journal of Remote Sensing 22:2109-2128.

Mishra, A. K., and V. P. Singh. 2010. A review of drought concepts. Journal of Hydrology 391(1):202-216.

Moran, M. S. 2003. Thermal infrared measurement as an indicator of plant ecosystem health. In Thermal Remote Sensing in Land Surface Processes, eds. D. A. Quattrochi, and J. Luvall, 257-282. Philadelphia, PA: Taylor and Francis.

Nasrollahi, N., K. Hsu, and S. Sorooshian. 2013. An artificial neural network model to reduce false alarms in satellite precipitation products using MODIS and CloudSat observations. Journal of Hydrometeorology 14(6):1872-1883.

NCDC (National Climatic Data Center). 2014. Billion Dollar U.S. Weather Disasters. http://www.ncdc.noaa.gov/oa/reports/billionz.html (accessed January 20, 2017).

Otkin, J. A., M. C. Anderson, C. Hain, I. E. Mladenova, J. B. Basara, and M. Svoboda. 2013. Examining rapid onset drought development using the thermal infrared-based evaporative stress index. Journal of Hydrometeorology 14(4):1057-1074.

Otkin, J. A., M. C. Anderson, C. Hain, and M. Svoboda. 2015. Using temporal changes in drought indices to generate probabilistic drought intensification forecasts. Journal of Hydrometeorology 16:88-105.

Otkin, J. A., M. C. Anderson, C. Hain, et al. 2016. Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought. Agricultural and Forest Meteorology 218-219:230-242.

Palmer, W. C. 1968. Keeping track of crop moisture conditions, nationwide: The new crop moisture index. Weatherwise 21(4):156-161.

Peters, A. J., D. C. Rundquist, and D. A. Wilhite. 1991. Satellite detection of the geographic core of the 1988 Nebraska drought. Agricultural and Forest Meteorology 57:35-47.

Peters, A. J., E. A. Walter-Shea, L. Ji, A. Vina, M. Hayes, and M. D. Svoboda. 2002. Drought monitoring with NDVI-based Standardized Vegetation Index. Photogrammetric Engineering and Remote Sensing 68(1):71-75.

Prakash, S., A. K. Mitra, A. AghaKouchak, Z. Liu, H. Norouzi, and D. S. Pai. 2016b. A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region. Journal of Hydrology 1-12 doi: http://dx.doi. org/ 10.1016/j.jhydrol.2016.01.029.

Prakash, S., A. K. Mitra, D. S. Pai, and A. AghaKouchak. 2016a. From TRMM to GPM: How well can heavy rainfall be detected from space? Advances in Water Resources 88:1-7.

Qiu, J., W. T. Crow, G. S. Nearing, X. Mo, and S. Liu. 2014. The impact of vertical measurement depth on the information content of soil moisture times series data. Geophysical Research Letters 41(14):4997-5004.

Reichle, R., G. De Lannoy, R. Koster, W. Crow, and J. Kimball. 2016. SMAP L4 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data. Version 2. Boulder, Colorado USA: NASA National Snow and Ice Data Center Distributed Active Archive Center. doi:http://dx.doi.org/10.5067/YK70EPDHNF0L.

Rodell, M., and J. S. Famiglietti. 2002. The potential of satellite-based monitoring of groundwater storage changes using GRACE: The High Plains aquifer, Central US. Journal of Hydrology 263(1-4):245-256.

Rouse, J. W. Jr., R. H. Haas, J. A. Schell, D. W. Deering, and J. C. Harlan. 1974. Monitoring the Vernal Advancement and Retro gradation (Green Wave Effect) of Natural Vegetation. NASA/GSFC Type III Final Report, Greenbelt, MD.

Senay, G. B., S. Bohms, R. K. Singh, et al. 2013. Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach. Journal of the American Water Resources Association 49(3):577-591.

Senay, G., S. Bohms, and J. P. Verdin. 2012. Remote sensing of evapotranspiration for operational drought monitoring using principles of water and energy balance. In Remote Sensing of Drought: Innovative Monitoring Approaches, eds. B. D. Wardlow, M. Anderson, and J. P. Verdin, 123-144. Boca Raton, FL: CRC.

Sepulcre, G., S. Horion, A. Singleton, H. Carrao, and J. Vogt. 2012. Development of a combined drought indicator to detect agricultural drought in Europe. Natural Hazards and Earth Systems 12(11):3519-3531.

Sheffield, J., G. Goteti, and E. Wood. 2006. Development of a 50-year high resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate 13:3088-3111.

Sheffield, J., E. Wood, and M. Roderick. 2012. Little change in global drought over the past 60 years. Nature 491(7424):435-438.

Sorooshian, S., P. Arkin, J. Eylander, et al. 2011. Advanced concepts on remote sensing of precipitation at multiple scales. Bulletin of the American Meteorological Society 92(10):1353-1357.

Sorooshian, S., K. Hsu, X. Gao, H. Gupta, B. Imam, and D. Braithwaite. 2000. Evolution of the PERSIANN system satellite-based estimates of tropical rainfall. Bulletin of the American Meteorological Society 81(9):2035-2046.

Sun, Y., R. Fu, R. Dickinson, J. Joiner, and C. Frankenberg. 2015. Drought onset mechanisms revealed by satellite solar-induced fluorescence: Insights from two contrasting extreme events. Journal of Geophysical Research: Biogeosciences 102:2427-2440.

Svoboda, M., D. LeComte, M. Hayes, et al. 2002. The Drought Monitor. Bulletin of the American Meteorological Society 83(8):1181-1190.

Tadesse, T., G. B. Demisse, B. Zaitchik, and T. Dinku. 2014. Satellite-based hybrid drought monitoring tool for prediction of vegetation condition in Eastern Africa: A case study for Ethiopia. Water Resources Research 50:2176-2190. doi:10.1002/2013WR014281.

Tadesse, T., T. Haigh, N. Wall, et al. 2016. Linking seasonal predictions into decisionmaking and disaster management in the Greater Horn of Africa. Bulletin of the American Meteorological Society 96(8): ES89-ES92. doi: http://dx.doi.org/10.1175/ BAMS-D-15-00269.1.

Tadesse, T., B. D. Wardlow, J. D. Brown, and K. Callahan. 2015. Assessing the vegetation condition impacts of the 2011 drought across the U.S. Southern Great Plains using the Vegetation Drought Response Index (VegDRI). Journal of Applied Meteorology and Climatology 54(1):153-169.

Tadesse, T., B. D. Wardlow, M. J. Hayes, M. D. Svoboda, and J. F. Brown 2010. The Vegetation Condition Outlook (VegOut): A new method for predicting vegetation seasonal greenness. GIScience and Remote Sensing 47(1):25-52.

Tang, G., Y. Ma, D. Long, L. Zhong, and Y. Hong. 2016a. Evaluation of GPM Day-1 IMERG and TMPA Version-7 legacy products over Mainland China at multiple spatiotemporal scales. Journal of Hydrology 533:152-167.

Tang, G., Z. Zeng, D. Long, et al. 2016b. Statistical and hydrological comparisons between TRMM and GPM level-3 products over a midlatitude basin: Is day-1 IMERG a good successor for TMPA 3B42V7? Journal of Hydrometeorology 17(1):121-137.

Thomas, A. C., J. T. Reager, J. S. Famiglietti, and M. Rodell. 2014. A GRACE-based water storage deficit approach for hydrological drought characterization. Geophysical Research Letters 41(5):1537-1545.

Tian, Y., C. Peters-Lidard, J. Eylander, et al. 2009. Component analysis of errors in satellite-based precipitation estimates. Journal of Geophysical Research 114:D24101. doi: http://dx.doi.org/10.1029/2009JD011949.

Tucker, C. J., C. O. Justice, and S. D. Prince. 1986. Monitoring the grasslands of the Sahel 1984-1985. International Journal of Remote Sensing 7:1571-1581.

Turk, F. J., G. D. Rohaly, J. Hawkins, et al.1999. Meteorological applications of precipitation estimation from combined SSM/I, TRMM and infrared geostationary satellite data. In Microwave Radiometry and Remote Sensing of the Earth's Surface and Atmosphere, eds. P. Pampaloni, and S. Paloscia, 353-363. Utrecht, The Netherlands: VSP Int. Sci. Publisher.

Unganai, L. S., and F. N. Kogan. 1998. Drought monitoring and corn yield estimation in southern Africa from AVHRR data. Remote Sensing of Environment 63:219-232.

Vicente-Serrano, S. M., S. Begueria, and J. I. Lopez-Moreno. 2010. A multiscalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index. Journal of Climate 23:1696-1718.

Wardlow, B. D., T. Tadesse, J. F. Brown, K. Callahan, S. Swain, and E. Hunt. 2012. The Vegetation Drought Response Index (VegDRI): An integration of satellite, climate, and biophysical data. In Remote Sensing of Drought: Innovative Monitoring Approaches, eds. B. D. Wardlow, M. A. Anderson, and J. Verdin, 51-74. Boca Raton, FL: CRC.

Werick, W., G. Willeke, N. Guttman, J. Hosking, and J. Wallis. 1994. National drought atlas developed. EOS Transactions American Geophysical Union 75(8):89.

Wilhite, D. A., ed. 2005. Drought and Water Crises: Science, Technology, and Management Issues. Boca Raton, FL: CRC.

Wilhite, D. A., and M. H. Glantz. 1985. Understanding the drought phenomenon: The role of definitions. Water International 10:111-120.

Xia, Y., K. Mitchell, M. Ek, et al. 2012. Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products. Journal of Geophysical Research 117:D03109. doi: http://dx.doi. org/10.1029/2011JD016048.

Yong, B., D. Liu, J. J. Gourley, et al. 2015. Global view of realtime TRMM multisatellite precipitation analysis: Implications for its successor global precipitation measurement mission. Bulletin of the American Meteorological Society 96:283-96.

Yang, L., B. Wylie, L. L. Tieszen, and B. C. Reed. 1998. An analysis of relationships among climatic forcing and time-integrated NDVI of grasslands over the U.S. northern and central Great Plains. Remote Sensing of Environment 65:25-37.

Zaitchik, B. F., M. Rodell, and R. H. Reichle. 2008. Assimilation of GRACE terrestrial water storage data into a land surface model: Results for the Mississippi River Basin. Journal of Hydrometeorology 9(3):535-548. doi: http://dx.doi. org/10.1175/2007JHM951.1.

 
Source
< Prev   CONTENTS   Source   Next >