Improvements in Forecasting Intense Rainfall: Results from the FRANC (Forecasting Rainfall Exploiting New Data Assimilation Techniques and Novel Observations of Convection) Project
Improvements in Forecasting Intense Rainfall: Results from the FRANC (Forecasting Rainfall Exploiting New Data Assimilation Techniques and Novel Observations of Convection) Project
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DOI：
10.3390/atmos10030125
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发表时间：
2019-03
期刊：
影响因子：
2.9
通讯作者：
S. Dance;S. Ballard;R. Bannister;P. Clark;H. Cloke;T. Darlington;D. Flack;S. Gray;L. Hawkness‐Smit
中科院分区：
文献类型：
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作者：
S. Dance;S. Ballard;R. Bannister;P. Clark;H. Cloke;T. Darlington;D. Flack;S. Gray;L. Hawkness‐Smit
FRANC项目（利用新的数据同化技术和对流的新观测预报降雨）研究了通过减少初始条件的不确定性来改进对流降雨的数值天气预报。本文概述了该项目的成就。我们强调新的雷达技术：校正雷达回波的衰减;校正被靠近雷达的树木或塔阻挡超过90%的波束;直接同化雷达反射率和反射率活动。我们讨论了数据同化中的不确定性的处理：新的方法估计观测不确定性与新的应用多普勒雷达风，大气运动矢量和卫星辐射;一个新的算法，用于实施空间相关的观测误差统计业务数据同化;和创新的治疗潮湿的过程中的背景误差协方差模型。我们目前的结果表明，对流和对流制度的空间可预测性之间的联系，有可能让改进的预测解释。这项研究是由大学研究人员和英国气象局（英国）合作进行的。我们讨论了这种方法的好处和我们的研究的影响，这有助于改善对流降雨事件的业务预报。
The FRANC project (Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection) has researched improvements in numerical weather prediction of convective rainfall via the reduction of initial condition uncertainty. This article provides an overview of the project’s achievements. We highlight new radar techniques: correcting for attenuation of the radar return; correction for beams that are over 90% blocked by trees or towers close to the radar; and direct assimilation of radar reflectivity and refractivity. We discuss the treatment of uncertainty in data assimilation: new methods for estimation of observation uncertainties with novel applications to Doppler radar winds, Atmospheric Motion Vectors, and satellite radiances; a new algorithm for implementation of spatially-correlated observation error statistics in operational data assimilation; and innovative treatment of moist processes in the background error covariance model. We present results indicating a link between the spatial predictability of convection and convective regimes, with potential to allow improved forecast interpretation. The research was carried out as a partnership between University researchers and the Met Office (UK). We discuss the benefits of this approach and the impact of our research, which has helped to improve operational forecasts for convective rainfall events.