Evaluation of the precipitation of the East Asia regional reanalysis system mainly over mainland China

Wang, Shuyu; Liang, Xudong; Yin, Jinfang; Xie, Yanxin; Fan, Huiyi

doi:10.1002/joc.7940

Cited by 6 publications

(6 citation statements)

References 55 publications

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“…The ERAS reanalysis system covering the whole East Asia, South Asia and most part of central Asia (Figure 1) is established utilizing the WRF model version 3.9.1 and driven by 6‐hourly ERA‐Interim reanalysis data (Dee et al, 2011). More detail on the model setting and assimilation system can be found in Yang et al (2022). To illustrate the regional features clearly, the model domain is separated to seven subregions, including China mainland, northeast of China (NEC; 42°–53°N, 114°–134°E), north China (NC; 34°–42°N, 107°–123°E), Yangtze River basin (YRB; 26°–34°N, 107°–123°E), south China (SC; 18°–26°N, 107°–123°E), the Tibetan Plateau (TP; 24°–40°N, 73°–105°E) and northwest of China (NWC; 40°–48°N, 77°–100°E) (Figure 1).…”

Section: Methodsmentioning

confidence: 99%

“…The ERAS reanalysis system covering the whole East Asia, South Asia and most part of central Asia (Figure 1) is established utilizing the WRF model version 3.9.1 and driven by 6-hourly ERA-Interim reanalysis data (Dee et al, 2011). More detail on the model setting and assimilation system can be found in Yang et al (2022). To illustrate the regional features clearly, the model domain is…”

Section: Model and Domain Configurementioning

confidence: 99%

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The extreme precipitation and added value of East Asia regional reanalysis system

Yang,

Liang,

Yin

et al. 2023

Intl Journal of Climatology

Self Cite

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In the study, we evaluate extreme precipitation of the East Asia regional reanalysis system (EARS‐CMA), ERA‐Interim and ERA5 applying Tropical Rainfall Measuring Mission 3B42V7 (TRMM), Climate Prediction Center Morphing Method satellite‐gauge blended product (CMORPH) and CN05.1 over land‐only East Asia in 2008–2017. The added value of EARS‐CMA is also calculated to identify the small‐scale processes at different timescales and spatial resolutions. Compared to TRMM, CMORPH has a better agreement with CN05.1 for the annual, summer and winter spatial pattern and amplitude of most extreme precipitation indices. EARS‐CMA is capable to reproduce amplitude and locations of most extreme precipitation indices for annual and summertime precipitation over China mainland against CN05.1. For land‐only East Asia, ERA5 can reproduce the closest spatial features of various extreme precipitation indices to CMORPH for annual, summer and winter precipitation, followed by EARS‐CMA. All reanalysis datasets show worse skill on the spatial characteristics of duration indicators than on other extreme precipitation indices against CN05.1, but perform better than TRMM and CMORPH. The real added value, potential added value and relative added value of EARS‐CMA show that EARS‐CMA can capture the mesoscale processes over south China, Yangtze River basin, Tibetan Plateau and Indo‐China efficiently, especially the daily and subseasonal timescales over the Tibetan Plateau subregion, which benefits from fine‐scale topographical detail over the complex terrain region in the regional climate model. Also, higher extreme precipitation of aggregating EARS‐CMA than ERA‐Interim can be obtained at the same resolution, which implies that the added value obtained with EARS‐CMA is not merely the contribution of a higher resolution, but also the physical processes resolved by the dynamical downscaling technique.

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Section: Methodsmentioning

confidence: 99%

Section: Model and Domain Configurementioning

confidence: 99%

The extreme precipitation and added value of East Asia regional reanalysis system

Yang,

Liang,

Yin

et al. 2023

Intl Journal of Climatology

Self Cite

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“…It is interpolated from data collected at approximately 2000 national observation stations since 1961. This dataset is widely used for climate simulation validation in China [21][22][23]. Similarly, BCC-CSM2-MR was also developed by the National Climate Center of the China Meteorological Administration, and its land surface component is BCC-AVIM2, the atmospheric model component is BCC-AGCM3-MR, horizontal spatial resolution is T106 (~110 km), vertical stratification reaches 46 layers, and the top layer of the model is 1.459 hPa [24].…”

Section: Datamentioning

confidence: 99%

Dynamical Downscaling of Daily Extreme Temperatures over China Using PRECIS Model

Guo,

Jia,

Wang

et al. 2024

Sustainability

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As global warming intensifies and the frequency of extreme weather events rises, posing a major threat to the world’s economy and sustainable development, accurate forecasting of future extreme events is of great significance to mankind’s response to extreme weather events and to the sustainable development of society. Global Climate Models (GCMs) have limitations in their applicability at regional scales due to their coarse resolution. Utilizing dynamical downscaling methods based on regional climate models (RCMs) is an essential approach to obtaining high-resolution climate simulation information in future. This study represents an attempt to extend the use of the Providing REgional Climates for Impacts Studies (PRECIS) regional climate model by employing the BCC-CSM2-MR model from the Beijing Climate Center to drive it, conducting downscaling experiments over China at a spatial resolution of 0.22° (25 km). The simulation and prediction of daily maximum and minimum temperatures across the China region are conducted, marking a significant effort to expand the usage of PRECIS with data from alternative GCMs. The results indicate that PRECIS performs well in simulating the daily maximum and minimum temperatures over the China region, accurately capturing their spatial distribution and demonstrating notable simulation capabilities for both cold and warm regions. In the annual cycle, the simulation performance of PRECIS is superior to its driving GCM, particularly during cold months (i.e., December and from January to May). Regarding future changes, the daily extreme temperatures in most regions are projected to increase gradually over time. In the early 21st century, the warming magnitude is approximately 1.5 °C, reaching around 3 °C by the end of the century, with even higher warming magnitudes exceeding 4.5 °C under the SSP585 scenario. Northern regions will experience greater warming magnitudes than southern regions, suggesting faster increases in extreme temperatures in higher latitudes. This paper provides forecasts of extreme temperatures in China, which will be useful for studying extreme events and for the government to make decisions in response to extreme events.

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“…Consequently, a simple comparison between the EARS and ERA-Interim is given here in terms of the accuracy of 3-h accumulated rainfall. Please refers to Yang et al (2023) for detailed analyses of the simulated rainfall properties of the EARS. Figure 14 shows the accuracy of 3-h rainfall for both EARS and ERA-Interim.…”

Section: Rainfallmentioning

confidence: 99%

East Asia Reanalysis System (EARS)

Jinfang

Liang

Xie

et al. 2023

Preprint

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Abstract. Reanalysis data plays a vital role in weather and climate study, as well as meteorological resource development and application. In this work, the East Asia Reanalysis System (EARS) was developed using the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolations (GSI) data assimilation system. The regional reanalysis system is forced by the European Centre of Medium-Range Weather Forecasts (ECMWF) global reanalysis EAR-Interim data at 6-h intervals; and hourly surface observations are assimilated by the Four-Dimension Data Assimilation (FDDA) scheme during the WRF model integration; upper observations are assimilated in a three-dimensional variational data assimilation (3D-VAR) mode at analysis moment. It should be highlighted that many of the assimilated observations have not been used in other reanalysis systems. The reanalysis runs from 1980 to 2018, producing a regional reanalysis dataset covering East Asia and surrounding areas at 12-km horizontal resolution, 74 sigma levels, and 3-hour intervals. Finally, an evaluation of EARS has been performed with the respect to the root mean square error (RMSE), based on the 10-year (2008–2017) observational data. Compared to the global reanalysis data of the EAR-Interim, the regional reanalysis data of the EARS are closer to the observations in terms of RMSE in both surface and upper-level fields. The present study provides evidence for substantial improvements seen in EARS compared to the ERA-Interim reanalysis fields over East Asia. The study also demonstrates the potential use of the EARS data for applications over East Asia and proposes further plans to provide the latest reanalysis in real-time operation mode. Simple data and updated information are available on Zenodo at https://doi.org/10.5281/zenodo.7404918 (Yin et al., 2022), and the full datasets are publicly accessible on the Data-as-a-Service platform of China Meteorological Administration (CMA) at http://data.cma.cn.

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Evaluation of the precipitation of the East Asia regional reanalysis system mainly over mainland China

Cited by 6 publications

References 55 publications

The extreme precipitation and added value of East Asia regional reanalysis system

The extreme precipitation and added value of East Asia regional reanalysis system

Dynamical Downscaling of Daily Extreme Temperatures over China Using PRECIS Model

East Asia Reanalysis System (EARS)

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