Improving Short-Term QPF Using Geostationary Satellite All-Sky Infrared Radiances: Real-Time Ensemble Data Assimilation and Forecast during the PRECIP 2020 and 2021 Experiments
Improving Short-Term QPF Using Geostationary Satellite All-Sky Infrared Radiances: Real-Time Ensemble Data Assimilation and Forecast during the PRECIP 2020 and 2021 Experiments
复制标题
使用对地静止卫星全天红外辐射改善短期 QPF：PRECIP 2020 和 2021 实验期间的实时集合数据同化和预测
DOI：
10.1175/waf-d-22-0156.1
复制
发表时间：
2023
影响因子：
2.9
通讯作者：
Bell, Michael M.
中科院分区：
文献类型：
--
作者：
Zhang, Yunji;Chen, Xingchao;Bell, Michael M.
太平洋极端降雨预测活动（precep）旨在提高我们对东亚夏季风极端降雨过程的认识。在2022年野外活动之前，在2020 - 2021年夏季实时运行了一个基于对流允许的集合数据同化和预报系统（PSU WRF-EnKF系统），吸收来自地球静止的hima -8和goes -16卫星的全天红外（IR）辐射，每天提供48小时的集合预报，用于天气简报和讨论。这是第一次在一个允许对流分辨率的实时预报系统中进行几个季节的全天红外数据同化。与排除全天红外辐射的回顾性预报相比，实时预报的降雨预报在统计上有显著改善，至少可达4-6小时，这与吸收密集地面多普勒天气雷达观测所获得的改进时间尺度相当。与不吸收全天红外辐射的对应实验相比，全天红外辐射的同化也降低了大尺度环境的预报误差，有助于保持更合理的集合分布。结果表明，在未来，利用这些高时空分辨率的卫星观测资料改进常规短期定量降水预报具有很大的潜力。在2020/21年夏季，PSU WRF-EnKF数据同化和预报系统在2022年太平洋极端降水预测活动（PRECIP）之前实时运行，将地球静止卫星的全天（晴空和多云）红外辐射同化为数值天气预报模式，并提供集合预报。本研究首次利用多年、多区域、实时集合预报系统评估了同化全天红外辐射对短期定性降水预报的影响。结果表明，同化全天红外辐射可将降雨预报提高到至少4-6小时，与同化雷达观测的影响相当，有利于预报大尺度环境，也有利于反映大气的不确定性。
The Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) aims to improve our understanding of extreme rainfall processes in the East Asian summer monsoon. A convection-permitting ensemble-based data assimilation and forecast system (the PSU WRF-EnKF system) was run in real time in the summers of 2020–21 in advance of the 2022 field campaign, assimilating all-sky infrared (IR) radiances from the geostationaryHimawari-8andGOES-16satellites, and providing 48-h ensemble forecasts every day for weather briefings and discussions. This is the first time that all-sky IR data assimilation has been performed in a real-time forecast system at a convection-permitting resolution for several seasons. Compared with retrospective forecasts that exclude all-sky IR radiances, rainfall predictions are statistically significantly improved out to at least 4–6 h for the real-time forecasts, which is comparable to the time scale of improvements gained from assimilating observations from the dense ground-based Doppler weather radars. The assimilation of all-sky IR radiances also reduced the forecast errors of large-scale environments and helped to maintain a more reasonable ensemble spread compared with the counterpart experiments that did not assimilate all-sky IR radiances. The results indicate strong potential for improving routine short-term quantitative precipitation forecasts using these high-spatiotemporal-resolution satellite observations in the future.Significance StatementDuring the summers of 2020/21, the PSU WRF-EnKF data assimilation and forecast system was run in real time in advance of the 2022 Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP), assimilating all-sky (clear-sky and cloudy) infrared radiances from geostationary satellites into a numerical weather prediction model and providing ensemble forecasts. This study presents the first-of-its-kind systematic evaluation of the impacts of assimilating all-sky infrared radiances on short-term qualitative precipitation forecasts using multiyear, multiregion, real-time ensemble forecasts. Results suggest that rainfall forecasts are improved out to at least 4–6 h with the assimilation of all-sky infrared radiances, comparable to the influence of assimilating radar observations, with benefits in forecasting large-scale environments and representing atmospheric uncertainties as well.