This study focuses on two intensive observing periods (IOPs) that cause heavy rainfall over California during the atmospheric river (AR) Reconnaissance Program in 2019. The impacts of dropsonde and satellite observations on the forecasts of the two AR-related heavy rainfall are investigated through both forecast sensitivity to observations (FSO) and observing system experiments (OSEs). In the first case (IOP3), satellite and dropsonde data coverage were relatively independent, whereas in the second case (IOP5), the satellite coverage was more extensive and substantially overlapped with dropsonde coverage. The FSO experiments indicate that the dropsondes improve the atmospheric forecast by a greater contribution per observation than that of an individual satellite instrument. In the OSEs, the heavy rainfall forecast presents a higher improvement when assimilating both dropsondes and satellite radiances. In IOP3, the dropsonde data slightly amplify the improvement achieved from the satellite data in terms of structure and location of the AR and attendant precipitation. In IOP5, the improvement from dropsonde data is more evident in the forecast of heavy precipitation. The influence of the dropsonde data in each case is broadly consistent with the relative coverage of dropsonde and satellite data. The best forecast performance acquired from the assimilation of both dropsonde and satellite data indicates the complementarity between the two data sources. Based on circulation analyses and further experiments assimilating satellite radiances from temperature channels and humidity channels separately, the improved rainfall forecasts are found to be related to the improvements in the three-dimensional circulation structure impacted by temperature characteristics.

本研究重点关注在 2019 年大气河流 (AR) 侦察计划期间导致加利福尼亚上空暴雨的两个密集观测期 (IOP)。预报对观测的敏感性（FSO）和观测系统实验（OSE）。在第一种情况（IOP3）中，卫星和投降式探空仪的数据覆盖相对独立，而在第二种情况（IOP5）中，卫星覆盖范围更广，并且与投降式探空仪的覆盖范围基本重叠。FSO 实验表明，与单个卫星仪器相比，投降式探空仪每次观测对大气预报的贡献更大。在 OSE 中，强降雨预报在同化投降探空仪和卫星辐射时有更高的改进。在 IOP3 中，下投式探空仪数据略微放大了卫星数据在 AR 的结构和位置以及伴随的降水方面所取得的改进。在IOP5中，从dropsonde数据的改进在强降水的预报中更为明显。在每种情况下，下落式探空仪数据的影响与下落式探空仪和卫星数据的相对覆盖范围大体一致。从下落式探空仪和卫星数据的同化中获得的最佳预测性能表明两个数据源之间的互补性。基于循环分析和进一步的实验，分别同化来自温度通道和湿度通道的卫星辐射，