Prediction of Seasonal and Annual Spatial Distribution of Dust over Iran Using the Coupled RegCM4 Model under RCP4.5 Scenario for the 2030–2040 and 2050–2060 Horizons

Document Type : Original Article

Authors

1 Fatemeh Dargahian: Associated Professor Research institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran.

2 هواشناسی اداره کل هواشناسی استان البرز، کرج، ایران

3 ..

4 دانش آموخته کارشناسی ارشد هواشناسی دانشگاه آزاد تهران شمال، تهران، ایران

5 Research Institute of Forests and Rangelands, AREEO, Tehran, Iran

‎10.22052/deej.2026.258710.1143

Abstract

Introduction
The present study was conducted with the aim of predicting the seasonal and annual spatial distribution of dust over Iran using the coupled RegCM4 model under the RCP4.5 climate scenario for the time horizons of 2030–2040 and 2050–2060. This research is of particular significance because, to date, no dynamic prediction of dust using dynamical downscaling by a regional model has been carried out within Iran. The majority of previous studies have either been limited to simulating current dust conditions or have merely utilized the outputs of international global models without the possibility of reconfiguring the model setup to suit Iran's specific climate characteristics. Consequently, the present study seeks to fill this critical gap by employing a regional climate model capable of resolving local-scale processes that govern dust emission, transport, and deposition.
Methodology
In this investigation, boundary condition data derived from the RegCM climate prediction model were utilized. These data possess a temporal resolution of six hours and extend up to the year 2100. Subsequently, these boundary data were ingested into the RegCM4 regional climate model, which was configured with a horizontal resolution of 40 kilometers to enable long-term dust prediction. The choice of 40 km resolution represents a trade-off between computational cost and the spatial accuracy required to detect major dust sources. All necessary meteorological variables, including temperature, precipitation, humidity, wind components, sea level pressure, and radiative fluxes, were extracted from the boundary dataset.

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Desert Ecosystem Engineering
Volume 15, Issue 51
September 2026

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