The authors wish to thank the editor, associate editor, and anonymous reviewers for their constructive suggestions to improve the quality of our manuscript. This work was financially supported in part by the United States Geological Survey (USGS Project ID 2009TX334G) through the project “Hydrological Drought Characterization for Texas under Climate Change, with Implications for Water Resources Planning and Management.”
Grinsted, A., , J. C. Moore, , and S. Jevrejeva, 2004: Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes Geophys., 11, 561–566.
Han, P., , P. X. Wang, , S. Y. Zhang, , and D. H. Zhu, 2010: Drought forecasting based on the remote sensing data using ARIMA models. Math. Comput. Modell., 51 (11–12), 1398–1403.
Hoff, P., 2009: A First Course in Bayesian Statistical Methods. Springer Verlag, 270 pp.
Karl, T. R., , and W. J. Koss, 1984: Regional and national monthly, seasonal, and annual temperature weighted by area, 1895-1983. National Climatic Data Center Historical Climatology Series 4-3, 38 pp.
Karl, T. R., , C. N. Williams Jr., , P. J. Young, , and W. M. Wendland, 1986: A model to estimate the time of observation bias associated with monthly mean maximum, minimum and mean temperatures for the Unites States. J. Climate Appl. Meteor., 25, 145–160.
Karl, T. R., , F. Quinlan, , and D. S. Ezell, 1987: Drought termination and amelioration: Its climatological probability. J. Climate Appl. Meteor., 26, 1198–1209.
Kim, T., , and J. B. Valdes, 2003: Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks. J. Hydrol. Eng., 8, 319–328.
Kumar, V., , and U. Panu, 1997: Predictive assessment of severity of agricultural droughts based on agro-climatic factors. J. Amer. Water Resour. Assoc., 33, 1255–1264.
Maurer, E. P., 2007: Uncertainty in hydrologic impacts of climate change in the Sierra Nevada, California, under two emissions scenarios. Climatic Change, 82, 309–325, doi:10.1007/s10584-006-9180-9.
Mishra, A. K., , and V. R. Desai, 2005: Drought forecasting using stochastic models. J. Stochastic Environ. Res. Risk Assess., 19, 326–339.
Mishra, A. K., , V. R. Desai, , and V. P. Singh, 2007: Drought forecasting using a hybrid stochastic and neural network model. J. Hydrol. Eng., 12, 626–638.
National Climatic Data Center, 2002: U.S. national percent area severely to extremely dry and severely to extremely wet. NCDC Dataset. [Available online at http://www.ncdc.noaa.gov/oa/climate/research/2002/may/uspctarea-wetdry.txt.]
Özger, M., , A. K. Mishra, , and V. P. Singh, 2012: Long lead time drought forecasting using a wavelet and fuzzy logic combination model: A case study in Texas. J. Hydrometeor., 13, 284–297.
Palmer, W. C., 1965: Meteorological drought. U.S. Weather Bureau Research Paper 45, 58 pp.
Quiring, S. M., 2009: Developing objective operational definitions for monitoring drought. J. Appl. Meteor. Climatol., 48, 1217–1229.
Wilhite, D. A., , and M. J. Hayes, 1998: Drought planning in the United States: Status and future directions. The Arid Frontier, H. J. Bruins and H. Lithwick, Eds., Kluwer, 33–54.
Wood, A. W., , L. R. Leung, , V. Sridhar, , and D. P. Lettenmaier, 2004: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climatic Change, 15, 189–216.