Development of East Asia Regional Reanalysis based on advanced hybrid gain data assimilation method and evaluation with E3DVAR, ERA-5, and ERA-Interim reanalysis

Eun Gyeong Yang, Hyun Mee Kim, Dae Hui Kim

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Abstract

The East Asia Regional Reanalysis (EARR) system is developed based on the advanced hybrid gain data assimilation method (AdvHG) using the Weather Research and Forecasting (WRF) model and conventional observations. Based on EARR, the high-resolution regional reanalysis and reforecast fields are produced with 12km horizontal resolution over East Asia for 2010-2019. The newly proposed AdvHG is based on the hybrid gain approach, weighting two different analyses for an optimal analysis. The AdvHG differs from the hybrid gain in that (1) E3DVAR is used instead of EnKF, (2) 6h forecast of ERA5 is used to be more consistent with WRF, and (3) the preexisting, state-of-the-art reanalysis is used. Thus, the AdvHG can be regarded as an efficient approach for generating regional reanalysis datasets thanks to cost savings as well as the use of the state-of-the-art reanalysis. The upper-air variables of EARR are verified with those of ERA5 for January and July 2017 and the 10-year period 2010-2019. For upper-air variables, ERA5 outperforms EARR over 2years, whereas EARR outperforms (shows comparable performance to) ERA-I and E3DVAR for January 2017 (July 2017). EARR represents precipitation better than ERA5 for January and July 2017. Therefore, although the uncertainties of upper-air variables of EARR need to be considered when analyzing them, the precipitation of EARR is more accurate than that of ERA5 for both seasons. The EARR data presented here can be downloaded from https://doi.org/10.7910/DVN/7P8MZT (Yang and Kim, 2021b) for data on pressure levels and https://doi.org/10.7910/DVN/Q07VRC (Yang and Kim, 2021c) for precipitation.

Original languageEnglish
Pages (from-to)2109-2127
Number of pages19
JournalEarth System Science Data
Volume14
Issue number4
DOIs
Publication statusPublished - 2022 May 2

Bibliographical note

Funding Information:
Acknowledgements. The authors appreciate the reviewers for their valuable comments. This study was carried out by utilizing the supercomputer system supported by the National Center for Meteorological Supercomputer of Korea Meteorological Administration and Korea Research Environment Open NETwork (KREONET) provided by the Korea Institute of Science and Technology Information. The authors gratefully acknowledge the late Fuqing Zhang for collaborations at the earlier stages of this study.

Funding Information:
Financial support. This study was supported by the National Research Foundation of Korea (NRF) grant funded by the South Korean government (Ministry of Science and ICT) (grant no. 2021R1A2C1012572) and the Yonsei Signature Research Cluster Program of 2021 (grant no. 2021-22-0003).

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All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)

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