Assimilation of GNSS and Synoptic Data in a Convection Permitting Limited Area Model: Improvement of Simulated Tropospheric Water Vapor Content
Assimilation of GNSS and Synoptic Data in a Convection Permitting Limited Area Model: Improvement of Simulated Tropospheric Water Vapor Content
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DOI：
10.3389/feart.2022.869504
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发表时间：
2022-04
影响因子：
2.9
通讯作者：
A. Wagner;B. Fersch;P. Yuan;Thomas Rummler;H. Kunstmann
中科院分区：
文献类型：
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作者：
A. Wagner;B. Fersch;P. Yuan;Thomas Rummler;H. Kunstmann
通过有限区域模型 (LAM) 中的观测同化可以找到对某个地区气象状况的最佳估计。水蒸气是云和降水形成的重要组成部分。它在空间和时间上高度可变的性质通常在模型中没有得到充分体现。本研究通过同化从气候站获得的温度、相对湿度和表面压力，以及从全球导航卫星系统 (GNSS) 地面站获得的大地测量天顶总延迟 (ZTD) 和可降水水汽 (PWV) 数据，研究了天气研究和预报模型 (WRF) 中每个季节模拟水汽含量的改善情况。在四个案例研究中，我们分析了 2016 年至 2018 年每个季节对德国、法国和瑞士三国边境地区 650 × 670 km 区域的高分辨率对流解析 WRF 模拟（2.1 km）的结果。评估不同变量及其组合的 3D VAR 同化、背景误差选项以及同化的时间和空间分辨率的影响。从无线电探空仪导出的列值和剖面均得到解决。当以小时分辨率和 10 公里的空间细化距离同化 ZTD 和天气数据时，获得了最佳结果。结论是，仔细选择同化选项可以额外改善每个季节的模拟结果。还可以看到同化对水预算的明显影响。
The assimilation of observations in limited area models (LAMs) allows to find the best possible estimate of a region’s meteorological state. Water vapor is a crucial constituent in terms of cloud and precipitation formation. Its highly variable nature in space and time is often insufficiently represented in models. This study investigates the improvement of simulated water vapor content within the Weather Research and Forecasting model (WRF) in every season by assimilating temperature, relative humidity, and surface pressure obtained from climate stations, as well as geodetically derived Zenith Total Delay (ZTD) and precipitable water vapor (PWV) data from global navigation satellite system (GNSS) ground stations. In four case studies we analyze the results of high-resolution convection-resolving WRF simulations (2.1 km) between 2016 and 2018 each in every season for a 650 × 670 km domain in the tri-border-area Germany, France and Switzerland. The impact of 3D VAR assimilation of different variables and combinations thereof, background error option, as well as the temporal and spatial resolution of assimilation is evaluated. Both column values and profiles derived from radiosondes are addressed. Best outcome was achieved when assimilating ZTD and synoptic data at an hourly resolution and a spatial thinning distance of 10 km. It is concluded that the careful selection of assimilation options can additionally improve simulation results in every season. Clear effects of assimilation on the water budgets can also be seen.