iDust - The deep integration of dust and numerical weather prediction for renewable energy applications

The increasing demand for renewable energy highlights the importance of accurate dust process forecasting in regions with abundant wind and solar resources, as it can create significant value for the sector. However, leading real-time operational global numerical weather prediction (NWP) models often lack dust modules due to computational resource limitations and application scenarios. 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 power grids. This work proposes a global dust-weather integrated (iDust) model development paradigm, incorporating dust modules into the dynamical core. Utilizing approximately one-eighth of additional computing power extends the global 12 km resolution NWP with dust prediction capabilities. To evaluate the forecasting capabilities of iDust, a comparative study is conducted with the ECMWF CAMS forecast and NASA MERRA2 reanalysis, including verifications over China during March to May in 2023, as well as three extreme dust events. The results demonstrate that iDust has better intensities and timings than its counterparts in dust storm forecasting. Using iDust, the global 12-km 10-day hourly dust storm forecast simulation initiated at 00UTC can obtain results by 06UTC, enabling timely forecasting of severe dust storms with concentrations exceeding 1000 μg/m³ on a global scale. iDust's novel capability can fill the urgent forecasting needs of the renewable energy industry for extreme dust weather conditions, promoting the goal of the green energy transition.