2025-04-21 中国科学院(CAS)
＜関連情報＞
- https://english.cas.cn/newsroom/cas_media/202504/t20250421_1041632.shtml
- https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024MS004525
再生可能エネルギー応用のための粉塵と数値天気予報の効率的な統合 The Efficient Integration of Dust and Numerical Weather Prediction for Renewable Energy Applications
Xi Chen, Mei Chong, Shian-Jiann Lin, Zhi Liang, Paul Ginoux, Yuan Liang, Bihui Zhang, Qian Song, Shengkai Wang, Jiawei Li, Yimin Liu
Journal of Advances in Modeling Earth Systems Published: 16 January 2025
DOI:https://doi.org/10.1029/2024MS004525
Abstract
The growing demand for renewable energy underscores the importance of accurate dust forecasting in regions with abundant wind and solar resources. However, leading real-time global numerical weather prediction (NWP) models often lack dust modules due to computational constraints. Current “Near-Real-Time” dust forecasting services can only run after the completion of NWP, failing to meet the timeliness requirements for reporting power generation plans to the grids. This work proposes a global dust-weather integrated (iDust) model development paradigm, efficiently incorporating dust modules into the dynamical core. Using about one-eighth additional computing power, iDust extends global 12.5 km resolution NWP with dust prediction capabilities. iDust’s forecasting abilities are evaluated against ECMWF CAMS forecast and NASA MERRA2 reanalysis, including verifications over China from March to May 2023 and three extreme dust events. Results show that iDust outperforms its counterparts in dust storm forecasting intensity and timing. Using iDust, global 12.5-km 10-day hourly dust storm forecast simulations initiated at 00UTC can produce results by 06UTC, enabling timely forecasting of severe dust storms with concentrations exceeding 1,000 μg/m3. This novel capability of iDust can meet the urgent forecasting needs of the renewable energy industry for extreme dust conditions, supporting the green energy transition.
Key Points
- The dust-dycore integrated iDust serves timely dust storm forecasts with high fidelity and long lead time for the renewable energy industry
- iDust captures extreme wind with high-resolution dynamics and accurately represents severe dust storms, even without initial dust data
- Accurate, high-resolution dynamics promise to enhance the skill of long-range dust transport simulations
Plain Language Summary
Leading economies need a green energy transition to avoid disastrous consequences caused by climate change. Barren regions are ideal for wind and solar power but are vulnerable to dust storms, which pose challenges for renewable energy operations. Traditional dust forecasting systems struggle with the added high computational cost of the sophisticated aerosol packages, leading to delayed, lower-resolution forecasts, and hindering the effective operation and risk management of renewable energy facilities. To address this problem, this work proposes iDust, an innovative paradigm that efficiently integrates dust storm forecasting into a global high-resolution weather forecasting model, utilizing only an additional one-eighth computational resources, extending the NWP with dust prediction capabilities. iDust enables timely forecasting of severe dust storms with concentrations exceeding 1,000 μg/m3 and dust transport over long distances. The new paradigm of iDust integrated weather forecasting model construction expands the coverage of operational forecasting systems to include the prediction of damaging dust storms, providing in-depth customized support for emerging solar and wind power industries.
