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

Abstract

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 12 km 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) 6 h 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 2 years, 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.

Comparison of Data Fusion Methods in Fusing Satellite Products and Model Simulations for Estimating Soil Moisture on Semi-Arid Grasslands

“…Moreover, this method effectively ensures the representativeness of the samples using the Gaussian distribution, which reduces computation costs and leads to more accurate results [86]. The efficiency of the EnKF method in SM estimation has been well demonstrated [87].…”

East Asia Reanalysis System (EARS)

“…With the ongoing development of atmospheric sciences, high-resolution atmospheric reanalysis data are much needed. In view of this demand, a large number of high-resolution regional reanalysis products have been produced for various parts of the world (e.g., Mesinger et al, 2006;Jakob et al, 2017;Vidal et al, 2010;Usui et al, 2017;Yang et al, 2022). However, little attention has been paid to East Asia, although China's first generation of 70 global atmospheric reanalysis (CRA40) was released recently.…”

“…Recently, Yang et al (2022Yang et al ( ) developed 10-year (2010Yang et al ( -2019 planned a project, intending to produce a high-resolution regional atmospheric reanalysis 100 dataset for East Asia, with high quality for mesoscale weather system study and regional climate analysis. For this purpose, the EARS was launched in late 2014 and a 39-year reanalysis dataset is now available to the public.…”

East Asia Reanalysis System (EARS)

“…With the ongoing development of atmospheric sciences, high-resolution atmospheric reanalysis data are much needed. In view of this demand, a large number of high-resolution regional reanalysis products have been produced for various parts of the world (e.g., Mesinger et al, 2006;Jakob et al, 2017;Vidal et al, 2010;Usui et al, 2017;Yang et al, 2022). However, little attention has been paid to East Asia, although China's first generation of global atmospheric reanalysis (CRA40) was released recently, with a horizontal resolution of approximately 34 km and a temporal resolution of 6 h. Only low-resolution global reanalysis products have been used for the region, including the National Centers for Environmental Prediction-Department of Energy Reanalysis version 2 (NCEP2) (Kanamitsu et al, 2002), the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis-Interim (ERA-Interim) (Dee et al, 2011), the Japanese 55year Reanalysis (JRA55) (Kobayashi et al, 2015), and the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) (Gelaro et al, 2017).…”