Research in atmospheric sciences needs high-quality, high-resolution, long-time-series global and regional meteorological data. Unfortunately, neither observational data nor model output alone can satisfy such a requirement. As a promising solution, reanalysis of past observations with a consistent, state-of-the-art numerical model and data assimilation system aims at producing a high-quality climate data, which consists of numerous meteorological variables in a physically consistent and spatiotemporally regular manner. Atmospheric reanalysis products have been widely used in research related to the mechanisms of the earth's climate system, the study of predictability, climate monitoring, and climate change study. China Meteorological Administration (CMA) has started the ReAnalysis project (CRA) of CRA-40 since early 2014, aiming at producing its first-generation 40-yr (1979–2018) global atmosphere and land reanalysis data. In early 2018, a 10-yr (2007–2016) interim product (CRA-Interim) was generated with a 34-km horizontal resolution. More recently, CRA-40 is in production.
It is important for the users of CRA products to understand how the dataset is produced, what observations are used, and the advantages and limitations of the products. We invite contributions of original research and development articles that document the development of CRA atmosphere and land reanalysis systems and evaluate the performance of CRA products for weather and climate monitoring. Potential topics include but are not limited to:
@ Development of CRAatmosphere and land reanalysis systems
@Evaluation of CRA reanalysis products
@ Intercomparison of different reanalysis products
@ Observations processing used in CRA, including fusion of different data sources, quality control, and bias correction
Responsible Editors for the Special Issue:
Zhiquan Liu, MMM Laboratory, NCAR, Boulder, CO, USA, email@example.com
PhD from the University of Paul Sabatier (Toulouse III), France in 2002, currently a Project Scientist at MMM/NCAR. He leads the research and development of NCAR’s community WRF data assimilation system and is the deputy head of the Prediction, Assimilation, and Risk Communication (PARC) section of MMM. Since 2018, he has served as an Associate Editor of Journal of Geophysical Research–Atmosphere. He is a well-known expert in data assimilation with more than 20-yr experience. His recent research interests include convective-scale satellite and radar data assimilation, aerosol/chemical data assimilation, reanalysis, and development of new-generation data assimilation system.
Chunxiang Shi, National Meteorological Information Center, China Meteorological Administration (CMA), Beijing, China, firstname.lastname@example.org
PhD from Chinese Academy of Sciences in 2008. As a Chief Scientist in NMIC of CMA, she has led the research on data blending from multiple sources and its operational application. She has been building the first China real-time operational Land Data Assimilation System (CLDAS), and is now co-leading a research team to develop the CMA next generation 40-yr global atmosphere reanalysis project (CRA-40).
Youlong Xia, I.M. Systems Group at EMC\NCEP, College Park, Maryland, USA, email@example.com
PhD from Ludwig-Maximilians University of Munich, Germany in 1999. Serving as a Senior Research Scientist since 2006 at EMC/NCEP to coordinate and develop the North American Land Surface Data Assimilation System. His areas of interest include land surface modeling, model optimization and uncertainty estimate, drought/hydrologic monitoring and prediction, seasonal hydrological forecast system, data verification and evaluation, data assimilation, and so on.
Tianjun Zhou, Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, firstname.lastname@example.org
Dr. Tianjun Zhou’s research focuses on coupled atmosphere-ocean modeling, climate dynamics, climate change and variability, with emphasis on East Asia and the monsoons. He has published 218 papers in international SCI(E) journals. He was co-chair of the CLIVAR Asian-Australian Monsoon Panel (AAMP) from 2013 to 2014 and is currently a member of WCRP WGCM, a member of the GEWEX/CLIVAR Monsoons Panel, a member of CLIVAR/SPARC SSG. He also served as Lead Author of the IPCC WG1 AR5. He received AMS Journal of Climate Editors’ Award in 2012 and was on the list of “Elsevier most cited Chinese scholars” during 2014–2016.
Zijiang Zhou, National Meteorological Information Center, China Meteorological Administration (CMA), Beijing, China, email@example.com
Master's Degree from Peking University in 2004. In recent years, as the director of the Division of Meteorological Data Research, he has made a series of original achievements in the research of the observation facts and mechanism of sandstorms in China, and won the National Natural Science Award of China. At present, he is co-leading a research team in the field of quality control, fusion, and reanalysis of meteorological observations.
Submission open: September 15, 2019
Submission deadline: June 15, 2020
Publication time: As soon as the paper is accepted and edited. The Special Issue in virtual format will be compiled online and the Special Issue in print is available upon request.
Style and format instructions available at http://www.cmsjournal.net:8080/Jweb_jmr/EN/column/column23.shtml
Submission gateway: https://mc03.manuscriptcentral.com/acta-e
Journal of Meteorological Research (JMR), formerly Acta Meteorologica Sinica, is published internationally by the Chinese Meteorological Society and Springer Nature. JMR intends to promote the exchange of scientific and technical innovation and thoughts between Chinese and foreign meteorologists. It covers all fields of meteorology, including observational, modeling, and theoretical research and applications in weather forecasting and climate prediction, as well as related topics in geosciences and environmental sciences.
JMR contains academic papers, research/field program highlights, conference reports, and comprehensive discussions on meteorological research and operation undertaken both in China and worldwide.
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