气候变化领域集成服务门户(CCPortal): Evaluation of 12-Years Chinese Regional Reanalysis (1998–2009): Comparison of Dynamical Downscaling Methods With/Without Local Data

CCPortal

DOI	10.1029/2020JD034259
	Evaluation of 12-Years Chinese Regional Reanalysis (1998–2009): Comparison of Dynamical Downscaling Methods With/Without Local Data
	Lu Y.; Fang J.; Pan Y.; Wang S.; Zhou P.; Yang Y.; Shao M.; Tang J.
发表日期	2021
ISSN	2169897X
卷号	126 期号:11
英文摘要	High-resolution regional reanalysis is one of the most powerful tool to study local and regional high-impact weather events, climate extremes and climate change impact. In this study, two high-resolution Chinese Regional Reanalysis (CNRR) datasets with a resolution of 18 km over 1998–2009, which are produced using the Gridpoint Statistical Interpolation (GSI) data assimilation system and spectral nudging (SN) technique, were assessed. The reliability of the surface and upper air variables of the CNRR datasets was evaluated by comparing with in situ observations and the European Centre for Medium-Range Forecasts (ECMWF) ERA-Interim (ERAIN) and ERA5 global reanalysis dataset. The evaluation of climatological and seasonal spatial distribution of near-surface variables shows that the CNRR can provide more accurate near-surface variables than the driving ERAIN global reanalysis, and CNRR-GSI shows advantages against ERA5 in representing near-surface atmosphere during cold season especially for daily maximum temperature. However, care should be taken when using the CNRR precipitation dataset, especially for heavy rainfall cases. CNRR datasets are also able to generate high-quality upper atmospheric products especially in CNRR-GSI experiment, which assimilates long time series of local observations. CNRR-GSI can better represent the lower-level horizontal wind and temperature than ERA5. By using the three-dimensional variational data assimilation (3D-Var) method, CNRR-GSI outperforms the CNRR-SN and the driving global reanalyzes. With the increase of the computing resources, the potential opportunities for improving CNRR can be expected by applying more advanced methods. © 2021. American Geophysical Union. All Rights Reserved.
英文关键词	data assimilation; evaluation; regional reanalysis; spectral nudging
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/185172
作者单位	Key Laboratory of Mesoscale Severe Weather/Ministry of Education, Nanjing University, Nanjing, China; School of Atmospheric Sciences, Nanjing University, Nanjing, China; School of Environment, Nanjing Normal University, Nanjing, China
推荐引用方式 GB/T 7714	Lu Y.,Fang J.,Pan Y.,等. Evaluation of 12-Years Chinese Regional Reanalysis (1998–2009): Comparison of Dynamical Downscaling Methods With/Without Local Data[J],2021,126(11).
APA	Lu Y..,Fang J..,Pan Y..,Wang S..,Zhou P..,...&Tang J..(2021).Evaluation of 12-Years Chinese Regional Reanalysis (1998–2009): Comparison of Dynamical Downscaling Methods With/Without Local Data.Journal of Geophysical Research: Atmospheres,126(11).
MLA	Lu Y.,et al."Evaluation of 12-Years Chinese Regional Reanalysis (1998–2009): Comparison of Dynamical Downscaling Methods With/Without Local Data".Journal of Geophysical Research: Atmospheres 126.11(2021).