A storm-scale ensemble was conducted by WRF model during Beijing "7·21" extreme precipitation event. Three initial perturbation methods is tested. The first one is produced by ETKF update and forecast cycle which contained analysis uncertainty. The second method (DOWN) is downscaled from NCEP global forecast perturbation, and the third one is produced by blending ETKF and DOWN using barnes filter with wavelength of 180 km (80~280 km). Results show that each perturbation energy can grow with time, in which ETKF has more medium and small scale energy due to flow-dependent analysis uncertainty and DOWN has more large scale energy in early time. BLEND has the most perturbation energy during most forecast time. Energy from each perturbation all grow to medium scale (64~128 km) and the fastest growing composition are focused on small scale at early forecast hours, while the medium scale component grow slowly. These results motivate further studies on how to choose properly wavelength to construct a blending initial perturbation. When coming to the error of precipitation, spurious perturbation may lead to small spurious precipitation in early hours. Forecast perturbations for different methods all have better performance in sampling error during front precipitation than warm area precipitation. All in all, ETKF has advantage in small scale and lead time error sample and DOWN is better at large scale in the later forecast time, BLEND has both advantages of ETKF and DOWN during the whole forecast time. The threat score also show that BLEND has the best overall performance.
ZHUANG Xiaoran
,
MIN Jinzhong
,
WU Tianjie
,
DENG Xu
,
CAI Yuanchen
. Development Mechanism of Multi-scale Perturbation Based on Different Perturbation Methods in convection-allowing ensemble prediction[J]. Plateau Meteorology, 2017
, 36(3)
: 811
-825
.
DOI: 10.7522/j.issn.1000-0534.2016.00049
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