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首页> 外文期刊>Natural hazards and earth system sciences >Impact of ASAR soil moisture data on the MM5 precipitation forecast for the Tanaro flood event of April 2009
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Impact of ASAR soil moisture data on the MM5 precipitation forecast for the Tanaro flood event of April 2009

机译：ASAR土壤湿度数据对2009年4月塔纳罗洪水事件的MM5降水预报的影响

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摘要

The representation of land-atmosphere interactions in weather forecast models has a strong impact on the Planetary Boundary Layer (PBL) and, in turn, on the forecast. Soil moisture is one of the key variables in land surface modelling, and an inadequate initial soil moisture field can introduce major biases in the surface heat and moisture fluxes and have a long-lasting effect on the model behaviour. Detecting the variability of soil characteristics at small scales is particularly important in mesoscale models because of the continued increase of their spatial resolution. In this paper, the high resolution soil moisture field derived from ENVISAT/ASAR observations is used to derive the soil moisture initial condition for the MM5 simulation of the Tanaro flood event of April 2009. The ASAR-derived soil moisture field shows significantly drier conditions compared to the ECMWF analysis. The impact of soil moisture on the forecast has been evaluated in terms of predicted precipitation and rain gauge data available for this event have been used as ground truth. The use of the drier, highly resolved soil moisture content (SMC) shows a significant impact on the precipitation forecast, particularly evident during the early phase of the event. The timing of the onset of the precipitation, as well as the intensity of rainfall and the location of raino rain areas, are better predicted. The overall accuracy of the forecast using ASAR SMC data is significantly increased during the first 30 h of simulation. The impact of initial SMC on the precipitation has been related to the change in the water vapour field in the PBL prior to the onset of the precipitation, due to surface evaporation. This study represents a first attempt to establish whether high resolution SAR-based SMC data might be useful for operational use, in anticipation of the launch of the Sentinel-1 satellite.
机译：天气预报模型中陆地-大气相互作用的表示形式对行星边界层（PBL）产生了强烈影响，进而对预报产生了很大影响。土壤水分是土地表面建模中的关键变量之一，初始土壤水分不足会导致表面热量和水分通量产生重大偏差，并对模型行为产生长期影响。由于中尺度模型的空间分辨率不断提高，因此在中尺度模型中检测小尺度土壤特征的变化尤为重要。本文使用ENVISAT / ASAR观测值获得的高分辨率土壤湿度场来推导2009年4月塔纳罗洪水事件的MM5模拟的土壤湿度初始条件。与ASAR得出的土壤湿度场相比，干旱条件明显改善进行ECMWF分析。已根据预测的降水量评估了土壤水分对预报的影响，并将此事件的可用雨量计数据用作地面实况。使用较干燥且高度解析的土壤水分含量（SMC）对降水预测有重大影响，在事件的早期尤为明显。可以更好地预测降雨开始的时间，降雨强度和降雨/无雨区的位置。在模拟的前30小时内，使用ASAR SMC数据进行的预测的总体准确性显着提高。由于表面蒸发，初始SMC对沉淀的影响与沉淀开始之前PBL中水蒸气场的变化有关。这项研究是首次尝试确定基于SSAR的高分辨率SAR SMC数据是否可用于运营用途，从而有望发射Sentinel-1卫星。

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