4.6 Article

Comparison of trends and low-frequency variability in CRU, ERA-40, and NCEP/NCAR analyses of surface air temperature -: art. no. D24115

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
Volume 109, Issue D24, Pages -

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2004JD005306

Keywords

reanalysis; temperature trends

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[1] Anomalies in monthly mean surface air temperature from the 45-Year European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and the first National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis are compared with corresponding values from the Climatic Research Unit (CRU) CRUTEM2v data set derived directly from monthly station data. There is mostly very similar short-term variability, especially between ERA-40 and CRUTEM2v. Linear trends are significantly lower for the two reanalyses when computed over the full period studied, 1958 - 2001, but ERA-40 trends are within 10% of CRUTEM2v values for the Northern Hemisphere when computed from 1979 onward. Gaps in the availability of synoptic surface data contribute to relatively poor performance of ERA-40 prior to 1967. A few highly suspect values in each of the data sets have also been identified. ERA-40' s use of screen-level observations contributes to the agreement between the ERA-40 and CRUTEM2v analyses, but the quality of the overall observing system and general character of the ERA-40 data assimilation system are also contributing factors. Temperatures from ERA-40 vary coherently throughout the boundary layer from the late 1970s onward, in general, and earlier for some regions. There is a cold bias in early years at 500 hPa over the data-sparse southern extratropics and at the surface over Antarctica. One indicator of this comes from comparing the ERA-40 analyses with results from a simulation of the atmosphere for the ERA-40 period produced using the same model and same distributions of sea surface temperature and sea ice as used in the ERA-40 data assimilation. The simulation itself reproduces quite well the warming trend over land seen in CRUTEM2v and captures some of the low-frequency variability.

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