In this study, the East Asia Regional Reanalysis (EARR) is developed for the period 2013-14 and characteristics of the EARR are examined in comparison with ERA-Interim (ERA-I) reanalysis. The EARR is based on the Unified Model with 12-km horizontal resolution, which has been an operational numerical weather prediction model at the Korea Meteorological Administration since being adopted from the Met Office in 2011. Relative to the ERA-I, in terms of skill scores, the EARR performance for wind, temperature, relative humidity, and geopotential height improves except for mean sea level pressure, the lower-troposphere geopotential height, and the upper-air relative humidity. In a similar way, RMSEs of the EARR are smaller than those of ERA-I for wind, temperature, and relative humidity, except for the upper-air meridional wind and the upper-air relative humidity in January. With respect to the near-surface variables, the triple collocation analysis and the correlation coefficients confirm that EARR provides a much improved representation when compared with ERA-I. In addition, EARR reproduces the finescale features of near-surface variables in greater detail than ERA-I does, and the kinetic energy (KE) spectra of EARR agree more with the canonical atmospheric KE spectra than do the ERA-I KE spectra. On the basis of the fractions skill score, the near-surface wind of EARR is statistically significantly better simulated than that of ERA-I for all thresholds, except for the higher threshold at smaller spatial scales. Therefore, although special care needs to be taken when using the upper-air relative humidity from EARR, the near-surface variables of the EARR that were developed are found to be more accurate than those of ERA-I.
Bibliographical noteFunding Information:
The authors appreciate three reviewers for their valuable comments. This study was supported by a National Research Foundation of Korea (NRF) grant funded by the South Korean government (Ministry of Science and ICT) (Grant 2017R1E1A1A03070968), the Korea Meteorological Administration Research and Development Program under Grant KMIPA 2015-5200, and an operation-oriented research project of the Numerical Modeling Center of the Korea Meteorological Administration. The authors appreciate Dr. Jun Kyung Kay for discussions at the earlier stages of the study and appreciate the Numerical Modeling Center and the National Center for Meteorological Supercomputer of the Korea Meteorological Administration and theMetOffice for providing computer facility support and resources for this study.
© 2017 American Meteorological Society.
All Science Journal Classification (ASJC) codes
- Atmospheric Science