The interferometric synthetic aperture radar (InSAR) technique has demonstrated its ability to capture temporal variations in tropospheric water vapor, providing a valuable source of information for numerical weather prediction (NWP) models. Integrating InSAR data into NWP models has the potential to significantly enhance their forecasting capabilities, especially for predicting local extreme weather events. The challenge lies in extracting a single epoch from the InSAR differential observations. In this work, we introduced a method based on the least-squares approach to estimate single epochs using the ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWFs) as a first guess. By leveraging ERA5 data, distinct atmospheric components can be disentangled without additional assumptions or external measurements. Since ERA5 is globally available at 1-h temporal resolution, the proposed method can be applied in remote areas without in situ data, providing improved high-resolution maps at all times (day/night) and in all weather conditions.

中文翻译：

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使用 InSAR 数据提高 ERA5 可降水汽的精度和空间分辨率

干涉合成孔径雷达（InSAR）技术已证明其能够捕获对流层水汽的时间变化，为数值天气预报（NWP）模型提供宝贵的信息来源。将 InSAR 数据集成到 NWP 模型中可能会显着增强其预测能力，特别是预测当地极端天气事件。挑战在于从 InSAR 差分观测中提取单个历元。在这项工作中，我们引入了一种基于最小二乘法的方法，使用欧洲中期天气预报中心 (ECMWF) 的 ERA5 再分析数据作为初步猜测来估计单个历元。通过利用 ERA5 数据，无需额外假设或外部测量即可解开不同的大气成分。由于 ERA5 以 1 小时时间分辨率在全球范围内可用，因此所提出的方法可以应用于没有现场数据的偏远地区，从而在所有时间（白天/夜间）和所有天气条件下提供改进的高分辨率地图。