Refining Regional Climate Projections for Louisiana and Mississippi: Dynamical Downscaling with WRF Model in the Face of Projected Sea Level Rise

crossref(2024)

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Abstract
Global climate models (GCMs) lack the necessary spatial resolution to accurately depict the atmospheric and land surface processes that define the regional climate of any particular location. In contrast, regional climate models (RCMs) explicitly capture the interactions between the broad-scale weather patterns simulated by global models and the specific characteristics of the local terrain. In this work, the Weather Research and Forecasting (WRF) model is used for dynamical downscaling simulations for a historical period (2001-2005) and the future (2095-2099) forced by the NCAR’s Community Earth System Model, version 1 (CESM1), for Louisiana and Mississippi, United States. The future RCM was run with both a present-day and future land-sea mask, considering model projections of sea level rise along the Gulf of Mexico coast. The convection-permitting, high-resolution (4 km) model performs more satisfactorily for temperature than rainfall when validated against observations from meteorological stations and gridded rainfall data. The future RCM runs demonstrate significant projected changes in average and extreme temperatures and rainfall from the current climate over the model domain. The probable retreat of the coastline shifts the sea breeze landward from its present-day area, which generates heavier rainfall and more moderate temperatures at places presently relatively distant from the Gulf of Mexico. This study enhances the existing dynamical downscaling methodology by incorporating the impacts of anticipated sea level rise on the regional climate.
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