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Atmosphere 2015, 6(3), 341-360; doi:10.3390/atmos6030341

A Comparison of ETKF and Downscaling in a Regional Ensemble Prediction System

1
College of Atmospheric Science, Nanjing University of Information & Science Technology, Nanjing 210044, China
2
Center of Numerical Weather Prediction of CMA, Beijing 100081, China
3
Key Laboratory of Meteorological Disaster, Ministry of Education College of Atmospheric Science, Nanjing University of Information & Science Technology, Nanjing 210044, China
4
Center of Meteorological Service of Zhejiang, Hangzhou 310017, China
*
Author to whom correspondence should be addressed.
Academic Editor: Anthony R. Lupo
Received: 14 January 2015 / Revised: 21 February 2015 / Accepted: 5 March 2015 / Published: 13 March 2015
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Abstract

Based on the operational regional ensemble prediction system (REPS) in China Meteorological Administration (CMA), this paper carried out comparison of two initial condition perturbation methods: an ensemble transform Kalman filter (ETKF) and a dynamical downscaling of global ensemble perturbations. One month consecutive tests are implemented to evaluate the performance of both methods in the operational REPS environment. The perturbation characteristics are analyzed and ensemble forecast verifications are conducted; furthermore, a TC case is investigated. The main conclusions are as follows: the ETKF perturbations contain more power at small scales while the ones derived from downscaling contain more power at large scales, and the relative difference of the two types of perturbations on scales become smaller with forecast lead time. The growth of downscaling perturbations is more remarkable, and the downscaling perturbations have larger magnitude than ETKF perturbations at all forecast lead times. However, the ETKF perturbation variance can represent the forecast error variance better than downscaling. Ensemble forecast verification shows slightly higher skill of downscaling ensemble over ETKF ensemble. A TC case study indicates that the overall performance of the two systems are quite similar despite the slightly smaller error of DOWN ensemble than ETKF ensemble at long range forecast lead times. View Full-Text
Keywords: regional ensemble prediction system; initial condition perturbation keyword; ensemble transform Kalman filter; dynamical downscaling regional ensemble prediction system; initial condition perturbation keyword; ensemble transform Kalman filter; dynamical downscaling
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Zhang, H.; Chen, J.; Zhi, X.; Wang, Y. A Comparison of ETKF and Downscaling in a Regional Ensemble Prediction System. Atmosphere 2015, 6, 341-360.

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