Abstract
This study employs the Weather Research and Forecasting (WRF) model to dynamically downscale climate projections from the Community Climate System Model version 4 (CCSM4) using 12 km and 4 km high grid resolutions. The performance of the WRF-CCSM4 configuration is evaluated against observational data from the automated weather observing systems of Kuwait (AWOSK). The analysis focuses on future predictions for maximum soil temperature during the summer months from May to September for the period 2050–2060. The findings indicate a projected increase in average soil temperatures of 1–3°C across the Arabian Peninsula and Kuwait. Notably, the results demonstrate that the 4-km high-resolution WRF domain, is more effective framework for accurate weather and climate predictions in this region. These insights underscore the importance of high-resolution modeling in understanding and mitigating the impacts of climate change, particularly in arid environments like Kuwait and the broader Arabian Peninsula.
| Original language | English |
|---|---|
| Article number | 1511608 |
| Journal | Frontiers in Climate |
| Volume | 6 |
| DOIs | |
| State | Published - 10 Dec 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 13 Climate Action
Keywords
- CCSM4
- WRF
- climate change
- future climate predictions
- soil temperature
Fingerprint
Dive into the research topics of 'Dynamic downscaling of climate projections using WRF-CCSM4: future soil temperature predictions for the Arabian Peninsula and Kuwait'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver