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Evaluation of the Temperature Trend and Climate Forcing in the Pre- and Post Periods of Satellite Data Assimilation

  • Alfred M. PowellJr.
  • Jianjun Xu
Chapter

Abstract

Based on multiple linear regression analysis, three temperature datasets from two reanalyses and one set of satellite observations have been used to evaluate the different responses in the winter [December–February (DJF)] period in the pre- and post periods of satellite data assimilation as they relate to a selected set of climate forcings: solar, the stratospheric quasi-biennial oscillation (QBO), El Niño Southern Oscillation (ENSO), and stratospheric aerosol optical depth (AOD). The two periods are defined as 1958–1978 when no satellite data was available to be assimilated and the 1979–2002 period when satellite data was assimilated in the operational forecast models. The multiple regression analysis shows that the solar response of the DJF temperatures in the three datasets shows large-scale similarities although there are differences over the southern middle-high latitudes and some tropical areas. The stratospheric response showed the strongest DJF temperature anomalies related to solar variability occurring over the Arctic, but its sign is negative in 1979–2002 and positive in 1958–1978. The temperature features may be partially explained by the impacts of the solar cycle, El Niño Southern Oscillation, stratospheric quasi-biennial oscillation, stratospheric aerosols, and other factors. In contrast, the tropospheric response, with a dynamic wavelike structure, occurs over the middle latitudes. The tropospheric differences between the two periods are not clearly resolved and raise questions about the efficacy of the observations and our ability to use the observations effectively.

Keywords

Aerosol Optical Depth Total Solar Irradiance Reanalysis Dataset Solar Variability Stratospheric Aerosol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The NCEP/NCAR monthly reanalysis data were obtained from NOAA/CDC Web site. The ERA-40 reanalysis data were obtained from the ECMWF Web site and the solar sunspot number from the NOAA/NGDC Web site. The authors would like to thank these agencies for providing the data. Special thanks to Dr. C. Zou from NOAA/NESDIS/STAR for many excellent discussions and the MSU temperature datasets that were provided.

This work was supported by the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS), and Center for Satellite Applications and Research (STAR). The views, opinions, and findings contained in this publication are those of the authors and should not be considered an official NOAA or US Government position, policy, or decision.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Center for Satellite Applications and Research (STAR) in the National Oceanic and Atmospheric Administration (NOAA) located at the NOAA Center for Weather and Climate Prediction (NCWCP)College ParkUSA
  2. 2.Department of GGS, Environmental Science and Technology Center (ESTC)/College of Science (COS)George Mason University (GMU)FairfaxUSA

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