Time-Expanded Sampling for Ensemble-Based Filters: Assimilation Experiments with Real Radar Observations |
| |
| Authors: | LU Huijuan Qin XU YAO Mingming and GAO Shouting |
| |
| Institution: | Research Center for Numerical Prediction, China Meteorological Administration, Beijing 100081,NOAA/National Severe Storms Laboratory, Norman, Oklahoma, USA,Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, USA,Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029 |
| |
| Abstract: | By sampling perturbed state vectors from each ensemble prediction run at
properly selected time levels in the vicinity of the analysis time, the
recently proposed time-expanded sampling approach can enlarge the ensemble
size without increasing the number of prediction runs and, hence, can reduce
the computational cost of an ensemble-based filter. In this study, this
approach is tested for the first time with real radar data from a tornadic
thunderstorm. In particular, four assimilation experiments were performed to
test the time-expanded sampling method against the conventional ensemble
sampling method used by ensemble-based filters. In these experiments, the
ensemble square-root filter (EnSRF) was used with 45 ensemble members
generated by the time-expanded sampling and conventional sampling from 15
and 45 prediction runs, respectively, and quality-controlled radar data were
compressed into super-observations with properly reduced spatial resolutions
to improve the EnSRF performances. The results show that the time-expanded
sampling approach not only can reduce the computational cost but also can
improve the accuracy of the analysis, especially when the ensemble size is
severely limited due to computational constraints for real-radar data
assimilation. These potential merits are consistent with those previously
demonstrated by assimilation experiments with simulated data. |
| |
| Keywords: | ensemble-based filter radar data assimilation time-expanded sampling super-observation |
| 本文献已被 CNKI SpringerLink 等数据库收录！ |
| 点击此处可从《大气科学进展》浏览原始摘要信息 |
| 点击此处可从《大气科学进展》下载免费的PDF全文 |
|
