A multi-disciplinary assessment of the southeastern United States climate

Abstract

The southeastern United States (SUS) is a region that exhibits considerable climate variability throughout the year along with high-impact weather extremes of severe weather and land-falling Atlantic tropical cyclones in the summer and fall, freeze events in the winter season, and tornadoes in the spring season. The SUS region has rapidly grown in terms of human population for last several decades that further exposes vulnerabilities to the frailties of nature. Furthermore, in the recent times, the agricultural production of the region has grown significantly with the rise in consumption and demand for bio fuels, increase in price and demand for commodity and food crops and increasing irrigation infrastructure that is subsidized by the state governments in the SUS. Similarly, the coastal development and capitalization of natural marine resource environment have also risen with the growing wealth of the population. All of these developments have led to an increasing interest in the understanding of the climate variations and change on the built and the natural environments of the SUS. This special issue is a manifestation of such an interest in the SUS with contributions from several climate-related inter-disciplinary groups including the Southeast Climate Consortium (SECC; http://seclimate. org/), the Florida Climate Institute (FCI; http://floridacli mateinstitute.org/), the University of Florida Water Institute (http://waterinstitute.ufl.edu/), and the Florida Water & Climate Alliance (FloridaWCA; http://www.floridawca.org). There are 15 research papers in this special issue covering climate science and its applications in hydrology, ecology, economy, crop science, and social science. It is quite apparent from the diverse set of papers that the demand for ‘‘reliable’’ regional-scale climate data over the SUS is of considerable interest for climate impact assessment. As a result, there are several papers in this collection which dwell on developing the regional-scale climate information from dynamic downscaling (e.g., Misra et al. 2012), or from statistical downscaling (e.g., Asefa and Adams 2013) or from a combination of statistical and dynamical downscaling (e.g., Hwang et al. 2013). Asefa and Adams (2013) introduced in their paper a new statistical bias correction technique for regional climate projections over central Florida based on a Bayesian approach that weights on the reliability of the global climate model in reproducing the observed climate. Hwang et al. (2013) highlight the merit of using dynamically downscaled and statistically bias-corrected climate data for hydrological applications over the Tampa Bay watershed. Misra et al. (2012) show the advantage and fidelity of dynamically downscaling the twentieth-century global atmospheric reanalysis (20CR) to 10 km grid resolution. For example, they demonstrate that data inhomogeneity issues over SUS in the 20CR are greatly ameliorated by the internal variations resolved by the dynamic downscaling to 10-km grid resolution. The interest in regional-scale climate information over SUS is also evidenced in a number of papers in this special issue investigating the reliability of some of the existing high-resolution regional climate datasets. LaRow (2012) analyzes the surface wind and precipitation in land-falling Atlantic tropical cyclones over the SUS from one of the existing global reanalyses downscaled to 10 km grid resolution. Similarly, Obeysekera (2013) interrogates the reliability of the meteorological variables used in the calculation of the surface evapotranspiration from the V. Misra (&) Department of Earth, Ocean and Atmospheric Science & Florida Climate Institute & Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL, USA e-mail: vmisra@fsu.edu