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01 SRIP Report Ch01 Earlyon -- Early online release -- Chapter 1: Introduction Chapter lead authors Masatomo Fujiwara Faculty of Environmental Earth Science, Hokkaido University Japan (1) NorthWest Research Associates Gloria L. Manney USA (2) Department of Physics, New Mexico Institute of Mining and Technology (1) Atmospheric, Oceanic and Planetary Physics, University of Oxford Lesley J. Gray United Kingdom (2) NERC National Centre for Atmospheric Science Jonathon S. Wright Department of Earth System Science, Tsinghua University China Co-authors Canadian Centre for Climate Modelling and Analysis, Environment and Climate James Anstey Canada Change Canada (1) Meteorological Institute, Ludwig-Maximilians-University Munich Thomas Birner (2) Institute of Atmospheric Physics, German Aerospace Center (DLR Oberpfaffenhofen) Germany previously at: Department of Atmospheric Science, Colorado State University, USA Sean Davis Chemical Sciences Laboratory, National Oceanic and Atmospheric Administration USA Edwin P. Gerber Courant Institute of Mathematical Sciences, New York University USA V. Lynn Harvey Laboratory for Atmospheric and Space Physics, University of Colorado USA Michaela I. Hegglin Department of Meteorology, University of Reading United Kingdom Cameron R. Homeyer School of Meteorology, University of Oklahoma USA John A. Knox Department of Geography, University of Georgia USA Kirstin Krüger Department of Geosciences, University of Oslo Norway Alyn Lambert Jet Propulsion Laboratory, California Institute of Technology USA Climate Prediction Center, National Oceanic and Atmospheric Administration Craig S. Long USA (retired) Japan Agency for Marine-Earth Science and Technology Patrick Martineau Japan previously at: Research Center for Advanced Science and Technology, the University of Tokyo Beatriz M. Monge-Sanz Atmospheric, Oceanic and Planetary Physics, University of Oxford United Kingdom Michelle L. Santee Jet Propulsion Laboratory, California Institute of Technology USA Institute of Space and Atmospheric Studies, University of Saskatchewan Susann Tegtmeier Canada previously at: GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany Simon Chabrillat Royal Belgian Institute for Space Aeronomy Belgium European Centre for Medium-Range Weather Forecasts David G.H. Tan United Kingdom (retired) David R. Jackson Met Office United Kingdom Saroja Polavarapu Climate Research Division, Environment and Climate Change Canada Canada (1) Cooperative Institute for Research in Environmental Sciences, University of Colorado Gilbert P. Compo USA (2) Physical Sciences Laboratory, National Oceanic and Atmospheric Administration Rossana Dragani European Centre for Medium-Range Weather Forecasts United Kingdom Wesley Ebisuzaki National Oceanic and Atmospheric Administration USA Yayoi Harada Japan Meteorological Agency Japan Chiaki Kobayashi Japan Meteorological Agency Japan (1) National Aeronautics and Space Administration Krzysztof Wargan USA (2) Science Systems and Applications, Inc. Jeffrey S. Whitaker National Oceanic and Atmospheric Administration USA Fujiwara et al. (2017a) have published a shortened version of this chapter. 1 2 SPARC Reanalysis Intercomparison Project (S-RIP) Final Report -- Early online release -- 1.1 Motivation and goals methodologies used to construct the reanalysis data sets (see, e.g., Fujiwara et al., 2017a for examples). There is a need, therefore, for a coordinated intercomparison of re- An atmospheric reanalysis system consists of a global analysis data sets with respect to key diagnostics that can forecast model, input observations, and an assimilation help to clarify the causes of these differences. The results scheme, which are used in combination to produce best es- can then be used to provide guidance on the appropriate timates (analyses) of past atmospheric states. Whereas op- use of reanalysis products in scientific studies, particular- erational analysis systems are continuously updated with ly those of relevance to SPARC. Forecasting and research the intention of improving numerical weather predictions, centres that produce reanalyses also benefit from coordi- reanalysis systems are (typically) fixed throughout their nated user feedback, which helps to drive improvements in lifetime. Using a fixed assimilation–forecast model sys- the next generation of reanalysis products. tem to produce analyses of observational data previous- ly analysed in the context of operational forecasting (the The SPARC Reanalysis Intercomparison Project (S-RIP) “re” in “reanalysis”) helps to prevent the introduction of was initiated in 2011 and officially started in 2013 to con- inhomogeneities in the analysed fields due to changing as- duct a coordinated intercomparison of all major global at- similation-forecast model systems (Trenberth and Olson, mospheric reanalysis data sets. While the focus is on the 1988; Bengtsson and Shukla, 1988; see also Fujiwara et al., stratosphere, the intercomparison also encompasses the 2017a), although artificial changes still arise from oth- troposphere and lower mesosphere where appropriate. er sources (especially from changes in the quality and/or quantity of the input observational data). The goals of S-RIP are as follows: The Stratosphere-troposphere Processes And their Role i. To create a communication platform between SPARC-re- in Climate (SPARC) project is one of the four core pro- lated researchers and the reanalysis centres; jects of the World Climate Research Programme (WCRP). Researchers interested in SPARC use global atmospheric ii. To better understand the differences among current reanalysis products (Table 1.1) (1) to understand a wide reanalysis products and their underlying causes and to range of processes and variability in the atmosphere, (2) to contribute to future reanalysis improvements; and validate chemistry climate models, and (3) to investigate and identify climate change (e.g., SPARC, 2010; Randel et iii. To provide guidance to reanalysis data users by docu- al., 2004; SPARC, 2002, and references therein). Even for menting the results of this reanalysis intercomparison more recent reanalyses, however, different results may in peer reviewed papers and this S-RIP report. be obtained for the same diagnostic due to the different This chapter discusses the scope and plans of S-RIP based Table 1.1: Global atmospheric reanalysis data sets avail- on the S-RIP Implementation Plan (February 2014) and able as of July 2018. See Appendix for the abbreviations. updated information. Reanalysis Centre Name of the Reanalysis Product 1.2 Scope ERA-40, ERA-Interim, ERA- ECMWF 1 20C, CERA-20C, ERA5 The S-RIP activity focuses predominantly on reanalyses, JMA JRA-25/JCDAS, JRA-55 although some chapters include diagnostics from opera- NASA MERRA, MERRA-2 tional analyses when appropriate. Available reanalysis data NCEP-NCAR R1, NCEP-DOE R2, sets (as of July 2018) are listed in Table 1.1. The guidelines for NOAA/NCEP CFSR/CFSv2 2 the choice of reanalysis data sets are detailed below. Many of the chapters focus primarily on newer reanalysis sys- NOAA and Univ. Colorado 20CR tems that assimilate upper-air measurements and produce 1 Some ERA5 data have been available since July 2018, ERA5 data at relatively high resolution (i.e., ERA-Interim, JRA- data from 1979 onward have been available since Janu- 55, MERRA, MERRA-2, and CFSR). The ERA5 reanalysis, ary 2019, and a preliminary version of ERA5 1950-1978 data which was released during the latter stages of the activity, have been available since November 2020. Because most is not fully evaluated but is included in some intercompar- of the studies in this report were finalized before ERA5 was isons. Selected long-term reanalyses that assimilate only readily available, full evaluation of ERA5 has not been surface meteorological observations (e.g., NOAA-CIRES made. However, Chapter 2 includes information on the 20CR, ERA-20C, and CERA-20C) are also evaluated where ERA5 system, and some chapters show some ERA5 results. appropriate. Some chapters include comparisons with old- 2 CFSR is for the period from January 1979 to December 2010, and er reanalyses (NCEP-NCAR R1, NCEP-DOE R2, ERA-40, CFSv2 is for the period from January 2011 to present. We strongly and JRA-25/JCDAS), because these products have been ex- recommend explicitly referring to the combination “CFSR/CFSv2” tensively used in the past and are still being used for some in documenting any study that uses these products across the studies, and because such comparisons can provide insight 2010 - 2011 transition. into the potential shortcomings of past research results. -- Early online release -- -- Early online release -- Chapter 1: Introduction 3 Other chapters only include a subset of these reanalysis data Demonstrated suitable: the reanalysis product could sets, since some reanalyses have already been shown to per- be directly validated using observational or physical form poorly for certain diagnostics or do not extend high constraints and was found to be in close agreement enough (e.g., pressures less than 10 hPa) in the atmosphere. with expectations At the beginning of each chapter an explanation is given as to why specific reanalysis data sets were included or excluded. Suitable with limitations: the reanalysis product could be directly validated using observational or physical The minimum intercomparison period is 1980 - 2010. This constraints and exhibited limited agreement; or, ap- period starts with the availability of MERRA-2 shortly after propriate constraints were unavailable but reanalysis the advent
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