Optimal spin-up time exploration of the WRF model by using various hydrometeor species as the initial conditions
Abstract
Despite the widely application of the WRF model in extreme rainfall simulations (Liu et al, 2020), there is a lack of consensus and clear guidance on its optimal spin-up time. In most numerical weather prediction model researches, a spin-up time of 12 hours is often regarded as the best choice directly without enough validation. Moreover, since the length of spin-up time mainly depends on the domain size and boundary condition disturbances, the optimal spin-up time for each rainfall simulation should be different. Thus, it is important to find a way to estimate the shortest spin-up time without too many trial-and-error simulation tests.
Most of WRF rainfall simulations only use one hydrometeor specie, relative/specific humidity, as one of the initial conditions. But ERA5 as the latest global dataset offers more up to 5 hydrometeor parameters, which could be valuable for the extreme rainfall simulations. These hydrometeors including specific humidity, specific cloud liquid water content, specific cloud ice water content, specific rain water content and specific snow water content. By using these hydrometeors as input parameters, the performance of WRF is improved and the length of spin-up time reduced especially for the short-term simulations. In addition, rainfall simulations are significantly affected by the initial weather conditions. Therefore, it is not always the case that a longer spin-up time could produce a better simulation. And it is found that the optimal spin-up time for each rainfall event could be estimated by observing the changes of hydrometeor species before the rainfall event. The main objectives of this study are: (1) to develop a simple method to estimate the optimal spin-up time of WRF rainfall simulation; (2) to investigate the relationship between the initial weather conditions and simulation results; (3) to explore which hydrometeor change has the greatest impacts on WRF performances; (4) to validate the quality of the hydrometeor parameters in the ERA5 dataset; Results are useful in simplifying the model configuration optimization process and improving the application of WRF rainfall simulations in various fields (Wang et al, 2020). Key Words: Spin-up time, WRF, Initial conditions, hydrometeor species References Liu, Y., Chen, Y., Chen, O., Wang, J., Zhuo, L., and Han, D.: Exploration of WRF simulations of extreme rainfall in Egypt, EGU General Assembly 2020, Online, 4-8 May 2020, EGU2020-10538, https://doi.org/10.5194/egusphere-egu2020-10538, 2020 Wang, J., Chen, O., Chen, Y., Liu, Y., Zhuo, L., Rico-Ramirez, M., and Han, D.: Flood inundation mapping with multi-satellite soil moisture observations, EGU General Assembly 2020, Online, 4-8 May 2020, EGU2020-9225, https://doi.org/10.5194/egusphere-egu2020-9225, 2020- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMA183.0007L
- Keywords:
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- 3314 Convective processes;
- ATMOSPHERIC PROCESSES;
- 3355 Regional modeling;
- ATMOSPHERIC PROCESSES;
- 1817 Extreme events;
- HYDROLOGY;
- 4313 Extreme events;
- NATURAL HAZARDS