Richardson Mark T, Kahn Brian H, Kalmus Peter M
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA USA.
JIFRESSE, University of California, Los Angeles, CA USA.
Commun Earth Environ. 2024;5(1):472. doi: 10.1038/s43247-024-01614-1. Epub 2024 Aug 30.
Predicting heavy precipitation remains scientifically challenging. Here we combine Atmospheric Infrared Sounder (AIRS) temperature and moisture soundings and weather forecast winds to predict the formation of thermodynamic conditions favourable for convection in the hours following satellite overpasses. Here we treat AIRS retrievals as air parcels that are moved adiabatically to generate time-varying fields. Over much of the Central-Eastern Continental U.S. during the non-winter months of 2019-2020, our derived convective available potential energy alone predicts intense precipitation. For hourly precipitation above the all-hours 99.9 percentile, performance is marginally lower than forecasts from a convection permitting model, but similar to the ERA5 reanalysis and substantially better than using the original AIRS soundings. Our results illustrate how mesoscale advection is a major contributor to developing heavy precipitation in the region. Enhancing the full AIRS record as described here would provide an alternative approach to quantify multi-decade trends in heavy precipitation risk.
预测强降水在科学上仍然具有挑战性。在此，我们结合大气红外探测器（AIRS）的温度和湿度探测数据以及天气预报风场，来预测在卫星过境后的数小时内有利于对流的热力学条件的形成。在此，我们将AIRS反演数据视为绝热移动的气块，以生成随时间变化的场。在2019 - 2020年非冬季的美国中东部大部分地区，仅我们推导的对流有效位能就能预测强降水。对于高于全年99.9百分位数的每小时降水量，其预测性能略低于允许对流的模型的预测，但与ERA5再分析结果相似，且远优于使用原始AIRS探测数据的预测。我们的结果表明中尺度平流是该地区强降水发展的主要贡献因素。如本文所述增强完整的AIRS记录，将为量化强降水风险的数十年趋势提供一种替代方法。
