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首页> 外文期刊>Atmosphere >Assessing the Impact of Surface and Upper-Air Observations on the Forecast Skill of the ACCESS Numerical Weather Prediction Model over Australia
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Assessing the Impact of Surface and Upper-Air Observations on the Forecast Skill of the ACCESS Numerical Weather Prediction Model over Australia

机译:评估地面和高空观测对澳大利亚ACCESS数值天气预报模型的预报技巧的影响

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The impact of the Australian Bureau of Meteorology’s in situ observations (land and sea surface observations, upper air observations by radiosondes, pilot balloons, wind profilers, and aircraft observations) on the short-term forecast skill provided by the ACCESS (Australian Community Climate and Earth-System Simulator) global numerical weather prediction (NWP) system is evaluated using an adjoint-based method. This technique makes use of the adjoint perturbation forecast model utilized within the 4D-Var assimilation system, and is able to calculate the individual impact of each assimilated observation in a cycling NWP system. The results obtained show that synoptic observations account for about 60% of the 24-h forecast error reduction, with the remainder accounted for by aircraft (12.8%), radiosondes (10.5%), wind profilers (3.9%), pilot balloons (2.8%), buoys (1.7%) and ships (1.2%). In contrast, the largest impact per observation is from buoys and aircraft. Overall, all observation types have a positive impact on the 24-h forecast skill. Such results help to support the decision-making process regarding the evolution of the observing network, particularly at the national level. Consequently, this 4D-Var-based approach has great potential as a tool to assist the design and running of an efficient and effective observing network.
机译:澳大利亚气象局的原位观测(陆地和海面观测,无线电探空仪,飞行员气球,风廓线仪和飞机观测的高空观测)对ACCESS(澳大利亚社区气候与气候变化局)提供的短期预报技能的影响Earth-System Simulator)全球数值天气预报(NWP)系统使用基于伴随的方法进行评估。该技术利用了4D-Var同化系统中使用的伴随摄动预测模型,并且能够计算出循环NWP系统中每个同化观测的个体影响。获得的结果表明,天气观测约占24小时预报误差减少的60%,其余部分由飞机(12.8%),无线电探空仪(10.5%),风廓线仪(3.9%),飞行员气球(2.8 %),浮标(1.7%)和船只(1.2%)。相反,每次观测的最大影响来自浮标和飞机。总体而言,所有观察类型都对24小时预报技能产生积极影响。这些结果有助于支持有关观测网络发展的决策过程,特别是在国家一级。因此,这种基于4D-Var的方法具有巨大的潜力,可作为一种工具来协助设计和运行高效且有效的观测网络。

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