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首页> 外文期刊>Pure and Applied Geophysics >A Study on the Impact of Observation Assimilation on the Numerical Simulation of Tropical Cyclones JAL and THANE Using 3DVAR
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A Study on the Impact of Observation Assimilation on the Numerical Simulation of Tropical Cyclones JAL and THANE Using 3DVAR

机译：利用3DVAR观测同化对热带气旋JAL和THANE数值模拟的影响研究。

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In this work, the impact of assimilation of conventional and satellite remote sensing observations (Oceansat-2 winds, MODIS temperature/humidity profiles) is studied on the simulation of two tropical cyclones in the Bay of Bengal region of the Indian Ocean using a three-dimensional variational data assimilation (3DVAR) technique. The Weather Research and Forecasting (WRF)-Advanced Research WRF (ARW) mesoscale model is used to simulate the severe cyclone JAL: 5–8 November 2010 and the very severe cyclone THANE: 27–30 December 2011 with a double nested domain configuration and with a horizontal resolution of 27 × 9 km. Five numerical experiments are conducted for each cyclone. In the control run (CTL) the National Centers for Environmental Prediction global forecast system analysis and forecasts available at 50 km resolution were used for the initial and boundary conditions. In the second (VARAWS), third (VARSCAT), fourth (VARMODIS) and fifth (VARALL) experiments, the conventional surface observations, Oceansat-2 ocean surface wind vectors, temperature and humidity profiles of MODIS, and all observations were respectively used for assimilation. Results indicate meager impact with surface observations, and relatively higher impact with scatterometer wind data in the case of the JAL cyclone, and with MODIS temperature and humidity profiles in the case of THANE for the simulation of intensity and track parameters. These relative impacts are related to the area coverage of scatterometer winds and MODIS profiles in the respective storms, and are confirmed by the overall better results obtained with assimilation of all observations in both the cases. The improvements in track prediction are mainly contributed by the assimilation of scatterometer wind vector data, which reduced errors in the initial position and size of the cyclone vortices. The errors are reduced by 25, 21, 38 % in vector track position, and by 57, 36, 39 % in intensity, at 24, 48, 72 h predictions, respectively, for the two cases using assimilation of all observations. Simulated rainfall estimates indicate that while the assimilation of scatterometer wind data improves the location of the rainfall, the assimilation of MODIS profiles produces a realistic pattern and amount of rainfall, close to the observational estimates.
机译：在这项工作中，研究了传统和卫星遥感观测（Oceansat-2风，MODIS温度/湿度剖面）的同化对印度洋孟加拉湾地区两个热带气旋的模拟，其中使用了三个维变异数据同化（3DVAR）技术。天气研究和预报（WRF）-高级研究WRF（ARW）中尺度模型用于模拟重旋风JAL：2010年11月5日至8日和极重旋风THANE：2011年12月27日至30日，具有双嵌套域配置和水平分辨率为27×9 km。每个旋风分离器进行五个数值实验。在控制运行（CTL）中，国家环境预测中心的全球预测系统分析和以50 km分辨率提供的预测被用于初始条件和边界条件。在第二次实验（VARAWS），第三次实验（VARSCAT），第四次实验（VARMODIS）和第五次实验（VARALL）中，分别使用常规表面观测，Oocesat-2海洋表面风向矢量，MODIS的温度和湿度剖面以及所有观测值来进行观测。同化。结果表明，地面观测的影响较小，在JAL旋风的情况下，对散射仪风速数据的影响相对较大;在THANE情况下，对于MODIS温度和湿度剖面，模拟强度和轨道参数的影响相对较大。这些相对影响与相应风暴中的散射仪风的面积覆盖和MODIS剖面有关，并且通过在两种情况下所有观测值的同化获得的总体较好结果得到了证实。航迹预测方面的改进主要归功于散射仪风矢量数据的同化，从而减少了旋风涡旋初始位置和大小的误差。对于使用所有观测值进行同化的两种情况，分别在24、48、72 h的预测时，矢量轨迹位置的误差分别降低了25％，21％，38％，强度降低了57％，36％，39％。模拟的降雨估计值表明，虽然散射仪风数据的同化可以改善降雨的位置，但MODIS剖面的同化却可以产生逼真的降雨模式和降雨量，接近观测值。

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