Diagnosing Observation Error Correlations for Doppler Radar Radial Winds in the Met Office UKV Model Using Observation-Minus-Background and Observation-Minus-Analysis Statistics
Diagnosing Observation Error Correlations for Doppler Radar Radial Winds in the Met Office UKV Model Using Observation-Minus-Background and Observation-Minus-Analysis Statistics
复制标题
DOI：
10.1175/mwr-d-15-0340.1
复制
发表时间：
2016-09
影响因子：
3.2
通讯作者：
Joanne A. Waller;D. Simonin;S. Dance;N. Nichols;S. Ballard
中科院分区：
文献类型：
--
作者：
Joanne A. Waller;D. Simonin;S. Dance;N. Nichols;S. Ballard
摘要随着允许对流的数值天气预报的发展，高分辨率观测资料在资料同化中的有效利用变得越来越重要。这些观测的业务同化，如多普勒雷达径向风（DRW），现在是常见的，虽然为了避免违反假设的不相关的观测误差的观测密度大大降低。为了提高所使用的观测数据的数量以及它们对预报的影响，需要引入完整的、潜在相关的误差统计。在这项工作中，观测误差统计计算的DRW被同化到气象局高分辨率英国。模型（UKV）使用诊断，该诊断利用观测减去背景和观测减去分析残差的统计平均值。这是第一次使用诊断来估计水平和沿波束观测误差统计的深入研究。新的成果获得…
AbstractWith the development of convection-permitting numerical weather prediction the efficient use of high-resolution observations in data assimilation is becoming increasingly important. The operational assimilation of these observations, such as Doppler radar radial winds (DRWs), is now common, although to avoid violating the assumption of uncorrelated observation errors the observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast requires the introduction of the full, potentially correlated, error statistics. In this work, observation error statistics are calculated for the DRWs that are assimilated into the Met Office high-resolution U.K. model (UKV) using a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. This is the first in-depth study using the diagnostic to estimate both horizontal and along-beam observation error statistics. The new results obtai...