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WRF simulation of a precipitation event over the Tibetan Plateau, China – an assessment using remote sensing and ground observations

机译:对中国青藏高原降水事件的WRF模拟-利用遥感和地面观测进行的评估

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Meteorological observations over the Tibetan Plateau (TiP) are scarce, and precipitation estimations over this remote region are difficult. The constantly improving capabilities of numerical weather prediction (NWP) models offer the opportunity to reduce this problem by providing precipitation fields and other meteorological variables of high spatial and temporal resolution. Longer time periods of years to decades can be simulated by NWP models by successive model runs of shorter periods, which can be described by the term "regional atmospheric reanalysis". In this paper, we assess the Weather Research and Forecasting (WRF) models capacity in retrieving rain- and snowfall on the TiP in such a configuration using a nested approach: the simulations are conducted with three nested domains at spatial resolutions of 30, 10, and 2 km. A validation study is carried out for a one-month period with a special focus on one-week (22–28 October 2008), during which strong rain- and snowfall was observed on the TiP. The output of the model in each resolution is compared to the Tropical Rainfall Measuring Mission (TRMM) data set for precipitation and to the Moderate Resolution Imaging Spectroradiometer (MODIS) data set for snow extent. TRMM and WRF data are then compared to weather-station measurements. Our results suggest an overall improvement from WRF over TRMM with respect to weather-station measurements. Various configurations of the model with different nesting and forcing strategies, as well as physical parameterisation schemes are compared to propose a suitable design for a regional atmospheric reanalysis over the TiP. The WRF model showed good accuracy in simulating snow- and rainfall on the TiP for a one-month simulation period. Our study reveals that there is nothing like an optimal model strategy applicable for the high-altitude TiP, its fringing high-mountain areas of extremely complex topography and the low-altitude land and sea regions from which much of the precipitation on the TiP is originating. The choice of the physical parameterisation scheme will thus be always a compromise depending on the specific purpose of a model simulation. Our study demonstrates the high importance of orographic precipitation, but the problem of the orographic bias remains unsolved since reliable observational data are still missing. The results are relevant for anyone interested in carrying out a regional atmospheric reanalysis. Many hydrological analyses and applications like rainfall-runoff modelling or the analysis of flood events require precipitation rates at daily or even hourly intervals. Thus, our study offers a process-oriented alternative for retrieving precipitation fields of high spatio-temporal resolution in regions like the TiP, where other data sources are limited.
机译:青藏高原(TiP)上的气象观测很少,而该偏远地区的降水估计也很困难。数值天气预报(NWP)模型的不断提高的功能提供了通过提供高时空分辨率的降水场和其他气象变量来减少此问题的机会。 NWP模型可以通过较短时期的连续模型运行来模拟几年至几十年的较长时期,这可以用术语“区域大气再分析”来描述。在本文中,我们使用嵌套方法评估了天气研究和预报(WRF)模型在TiP上以这种配置检索降雨和降雪的能力:模拟是在30、10,和2公里。进行了一个为期一个月的验证研究,特别关注了一个星期(2008年10月22日至28日),在此期间,在TiP上观测到强降雨和降雪。将每个分辨率的模型输出与用于降水的热带降雨测量任务(TRMM)数据集以及用于降雪程度的中分辨率成像光谱仪(MODIS)数据集进行比较。然后将TRMM和WRF数据与气象站的测量结果进行比较。我们的结果表明,相对于气象台测量,WRF优于TRMM。比较了具有不同嵌套和强迫策略的模型的各种配置以及物理参数化方案,以为TiP上的区域大气再分析提出合适的设计。 WRF模型在为期一个月的模拟期内模拟TiP上的降雪和降雨方面显示出了良好的准确性。我们的研究表明,没有什么比适用于高海拔TiP的最优模型策略,其边缘极其复杂的高山区和低海拔陆地和海洋地区更适合该模式的策略了。 。因此,根据模型仿真的特定目的,物理参数化方案的选择将始终是一个折衷方案。我们的研究表明了地形降水的高度重要性,但由于仍然缺乏可靠的观测数据,因此地形偏向的问题仍未解决。该结果与任何有兴趣进行区域大气再分析的人有关。许多水文分析和应用(例如降雨径流模型或洪水事件分析)都需要每天甚至每小时的降雨间隔。因此,我们的研究提供了一种以过程为导向的替代方法,以检索像TiP这样的区域,该区域的时空分辨率很高,而其他数据源是有限的。

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