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Climate change projections for the Texas High Plains and Rolling Plains


Potential changes in future climate in the Texas Plains region were investigated in the context of agriculture by analyzing three climate model projections under the A2 climate scenario (medium–high emission scenario). Spatially downscaled historic (1971–2000) and future (2041–2070) climate datasets (rainfall and temperature) were downloaded from the North American Regional Climate Change Assessment Program (NARCCAP). Climate variables predicted by three regional climate models (RCMs) namely the Regional Climate Model Version3–Geophysical Fluid Dynamics Laboratory (RCM3-GFDL), Regional Climate Model Version3–Third Generation Coupled Global Climate Model (RCM3-CGCM3), and Canadian Regional Climate Model–Community Climate System Model (CRCM-CCSM) were evaluated in this study. Gaussian and Gamma distribution mapping techniques were employed to remove the bias in temperature and rainfall data, respectively. Both the minimum and maximum temperatures across the study region in the future showed an upward trend, with the temperatures increasing in the range of 1.9 to 2.9 °C and 2.0 to 3.2 °C, respectively. All three climate models predicted a decline in rainfall within a range of 30 to 127 mm in majority of counties across the study region. In addition, they predicted an increase in the intensity of extreme rainfall events in the future. The frost-free season as predicted by the three models showed an increase by 2.6–3.4 weeks across the region, and the number of frost days declined by 17.9 to 30 %. Overall, these projections indicate considerable changes to the climate in the Texas Plains region in the future, and these changes could potentially impact agriculture in this region.

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We thank the Texas A&M AgriLife Research for funding this study through the Cropping Systems Initiative. We also thank Seth McGinnis, Associate Scientist at the National Center for Atmospheric Research–University Cooperation for Atmospheric Research (NCAR-UCAR), for providing assistance with NARCCAP climate datasets and bias correction. We apprecaite the valuable support provided by Sai Murali Krishna and Pradeep Garigipati of Computer Science department at Texas A&M University in computer programing. We also appreciate the valuable feedback provided by Karen Davis, Florence Davis, and Nancy Vazquez of Texas A&M University Writing Center on earlier version of this paper.

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Correspondence to Srinivasulu Ale.

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Modala, N.R., Ale, S., Goldberg, D.W. et al. Climate change projections for the Texas High Plains and Rolling Plains. Theor Appl Climatol 129, 263–280 (2017).

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  • Rainfall Event
  • Bias Correction
  • Extreme Rainfall Event
  • Cumulative Distribution Frequency
  • Bias Correction Method