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The early-warning effects of assimilation of the observations over the large-scale slope of the 'World Roof' on its downstream weather forecasting

机译：The early-warning effects of assimilation of the observations over the large-scale slope of the "World Roof" on its downstream weather forecasting

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摘要

To improve the numerical simulation of the severe snow storms occurred in the south of China and the middle/lower reaches of Changjiang River during January of 2008, the observations from the automatic weather stations (AWS) over the Qinghai-Xizang Plateau (QXP) and its surrounding areas were assimilated into the Weather Research and Forecasts (WRF) model using multi-cycle 3-dimensional variational data assimilation (3DVAR). Due to the large-scale special topography of the QXP and its surrounding areas which may reach up to the mid-troposphere, the AWS located at different height on the deep slope of the plateau are different to those located on plains and take a role analogous in some extent to that of radio soundings in obtaining the vertical "profile" information of the atmosphere, and have the advantages in the aspects of sampling frequency, location/height fixing, and synchronization. The information captured by these AWS may carry the early-warning "strong signals" in the upstream sensitive area for the downstream weather systems to the east of the plateau and thus the assimilation of these AWS data is expected to lead to significant improvements on the simulation of the severe weather system occurred in its downstream areas through adjusting the 3-dimensional structures of the atmospheric thermal-dynamics for the initial conditions of the model. This study indicates that the assimilated information of moisture, temperature and pressure carried in the observations of AWS over the Qinghai-Xizang Plateau and its surrounding areas is very important and useful in the forecasting of precipitation in its downstream areas.
机译：为了改善2008年1月在中国南部和长江中下游发生的暴风雪的数值模拟，从青藏高原（QXP）和使用多周期3维变分数据同化（3DVAR）将其周围区域同化为“天气研究和预报（WRF）”模型。由于QXP及其周边地区的大规模特殊地形可能会延伸到对流层中部，因此位于高原深处不同高度的AWS与平原地区的AWS有所不同，其作用类似在某种程度上与无线电探空仪相比，在获取大气层的垂直“轮廓”信息方面具有优势，并且在采样频率，位置/高度固定和同步方面具有优势。这些AWS捕获的信息可能会在高原东部的下游天气系统的上游敏感区域中携带预警“强信号”，因此，这些AWS数据的同化有望导致模拟的显着改善通过针对模型的初始条件调整大气热力学的3维结构，在其下游地区发生了恶劣天气系统的变化。这项研究表明，青藏高原及其周边地区的AWS观测所携带的水分，温度和压力的同化信息对于预测下游地区的降水非常重要且有用。

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