Two widely-used statistical downscaling datasets were used to produce deliverables for the State of Delaware: the Localized Constructed Analogs Version 2 (LOCA2) trained by the Livneh-unsplit data with 6km spatial resolution and the Seasonal Trends and Analysis of Residuals, Empirical-Statistical Downscaling Model (STAR-ESDM) trained by NClimGrid-Daily data with a 5km spatial resolution. Both of these datasets were used in the recent Fifth National Climate Assessment (NCA5) and have undergone a number of comparative studies, which serve as immeasurable guides to the development of a meaningful final product for our assessment. Thirteen CMIP6 models were selected for this study. Ensemble means and medians were created for Delaware climate divisions to help compare to a serially complete historical record.
Climate indicators of interest were identified based on conversations with state practitioners and their needs. In addition to the common temperature and precipitation variables, Delaware practitioners are interested in understanding how to prepare for changes in extreme heat stressors that would dramatically affect both human and agricultural environments, including the large poultry industry. Key extremes indicators such as prolonged high heat days (heat waves), changes in growing season length, and precipitation intensities will likely have serious impacts to the ecosystems in and around Delaware as well as the economy.
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