Climate Change Research

Climate Change Research

Modeling Sea Surface Temperature Using the WRF Numerical Model: Application in a Coastal Arid Region (Case Study: Northern Coasts of the Persian Gulf)

Document Type : Original Article

Authors
Hamid Abbaspour 1
Esmaeil Abbasi 2
Hana Etemadi 2
Iman Rousta 3
1 Master of Science in Marine Environment, Faculty of Nano and Biological Sciences and Technology, Persian Gulf University, Bushehr, Iran
2 Assistant professor of Environment Department, Persian Gulf Research Institute, Persian Gulf University, Bushehr, Iran
3 Associate Professor, Department of Geography, Yazd University, Yazd, Iran
10.30488/ccr.2026.581093.1334
Abstract
Climate change, as one of the most pressing challenges of the twenty-first century, has profoundly affected marine and coastal ecosystems, particularly coastal drylands. Rising sea surface temperatures (SST), the increased frequency of extreme climate events, and intensified thermal stresses are among the key consequences of this global phenomenon. In this context, the application of downscaling numerical models such as the Weather Research and Forecasting (WRF) model offers a novel approach for SST modeling in these environmentally sensitive regions. The Persian Gulf, recognized as one of the world's most significant coastal dryland ecosystems, is characterized by high annual evaporation, elevated salinity, shallow depth, and strong seasonal temperature fluctuations, rendering it particularly vulnerable to climate change. The primary objective of this study is to identify the most optimal configuration of physical parameterization schemes within the WRF model for simulating SST in the Persian Gulf. SST observational data were obtained from the Iran Meteorological Organization. The WRF model was executed using eight distinct configurations, and the model outputs were validated using the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). The results indicated that Configuration No. 5, which comprises the WSM 5-class microphysics, RRTM longwave radiation, Dudhia shortwave radiation, the Revised MM5 Monin Obukhov surface layer scheme, the Unified Noah land surface model, the YSU planetary boundary layer scheme, and the Kain–Fritsch cumulus parameterization scheme, exhibited the lowest error metrics and the highest correlation coefficient (0.985), and was therefore identified as the optimal configuration. The RMSE values for spring, summer, autumn, and winter were calculated as 0.036°C, 0.012°C, 0.028°C, and 0.011°C, respectively. Based on these findings, the WRF model outputs can serve as a suitable, high-precision alternative to the Bushehr meteorological buoy data for a range of applications, including climate change monitoring, fisheries management, the protection of coral reefs against bleaching induced by global warming, and the prediction of extreme temperature events in this coastal dryland region.
Keywords
Numerical simulation
Parameterization scheme
Meteorological buoy
Statistical validation
Persian Gulf
Subjects
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