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Evaluation of multi-decadal UCLA-CFSv2 simulation and impact of interactive atmospheric-ocean feedback on global and regional variability

  • Jiwoo Lee
  • Yongkang Xue
  • Fernando De Sales
  • Ismaila Diallo
  • Larry Marx
  • Michael Ek
  • Kenneth R. Sperber
  • Peter J. Gleckler
Article

Abstract

This paper evaluates multi-decadal simulations of the UCLA version of Climate Forecast System version 2, in which the default Noah land surface model has been replaced with the Simplified Simple Biosphere Model version-2. To examine the influence of the atmosphere–ocean (AO) interaction on the variability, two different simulations were conducted: one with interactive ocean component, and the other constrained by the prescribed sea surface temperature. We evaluate the mean seasonal climatology of precipitation and temperature, along with the model’s ability to reproduce atmospheric variability at different scales over the globe, including extratropical modes of atmospheric variability, and long-term trends of global and hemispheric temperature and regional precipitation. Here, we particularly selected two monsoon regions, East Asia and West Africa, where the simulation of multi-decadal variations which has heretofore been a challenging task, to examine decadal variation of monsoon precipitation. In general, temperature anomaly trends were better captured than those of precipitation in both simulations. Results suggest that the AO interaction, represented as latent heat flux, contributes to improve reproducibility of global-wide climatology, extratropical modes of atmospheric variability, and variability in the multi-decadal climate simulation, as well as for inter-decadal variability of the East Asian summer monsoon.

Keywords

Multi-decadal simulations UCLA-CFSv2 Atmospheric-ocean interaction SSiB2 Modes of variability Decadal variability 

Notes

Acknowledgements

The authors thank anonymous reviewers for providing valuable comments. This material is based upon work supported by the National Science Foundation under Grant no. AGS-1419526. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin (URL: http://www.tacc.utexas.edu) for providing High-Performance Computing (HPC) resources that have contributed to the research results reported within this paper. The work of K. Sperber, P. Gleckler, and (in part) J. Lee was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. The efforts of these 3 authors are supported by the Regional and Global Climate Modeling Program of the United States Department of Energy’s Office of Science. The CMAP precipitation data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at http://www.esrl.noaa.gov/psd/. The OAFlux data were provided by the WHOI OAFlux project (http://oaflux.whoi.edu) funded by the NOAA Climate Observations and Monitoring (COM) program. The simulation result of this study is open to public upon request to authors, and we welcome other research groups to use the data to comprehensively analyze the impact on other regions.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Lawrence Livermore National Laboratory (LLNL)LivermoreUSA
  2. 2.University of California Los Angeles (UCLA)Los AngelesUSA
  3. 3.San Diego State University (SDSU)San DiegoUSA
  4. 4.Center for Ocean-Land-Atmosphere Research (COLA) and George Mason UniversityFairfaxUSA
  5. 5.National Center for Environmental Prediction (NCEP)National Oceanic and Atmospheric Administration (NOAA)College ParkUSA

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