 Overview
The National Climatic Data Center is evaluating global and hemisphere timeseries calculated from a merged land and sea surface temperature reconstruction developed by Smith and Reynolds (2005). The Smith and Reynolds analysis (SR05) merges a new analysis of in situ SST anomalies [Smith and Reynolds, 2004] with an analysis of Land Surface Temperature (LST) anomalies from a gridded version of the Global Historical Climatology Network (GHCN) [Peterson and Vose, 1997]. The LST analysis is produced using the same methods as the SST analysis. The analysis method is briefly discussed here, but interested readers should see Smith and Reynolds [2004, 2005] for details.
Both the SST and LST components of the SR05 are created by separately analyzing the low- and high-frequency anomalies. Low-frequency anomalies are analyzed by spatial and temporal filtering when enough data are available. Spatial filtering is done by averaging anomalies over 10-15 degree latitude-longitude regions, and temporal filtering is done by averaging and median filtering over 15 year running periods. Separate low-frequency analysis is done to minimize the damping of those signals. Damping of the low-frequency may occur if it is analyzed by projecting it onto a set of stationary modes that do not fully resolve all of its variations.
The high-frequency residuals from this low-frequency analysis are analyzed separately by fitting them to a set of screened covariance modes representing large-scale monthly temperature patterns. It is assumed that the base period for the modes is long enough to resolve the high frequency variations. The sum of the low- and high frequency anomalies gives the total anomaly. In addition to the anomaly, an error estimate is also computed for the merged analysis.
Although the SR05 analysis is spatially complete, regions such as the Polar Latitudes are nearly always sampled poorly and the anomalies there are damped toward zero in the SR05 analysis. As expected, the SR05 sampling error estimate is large for the poorly-sampled regions. To prevent poorly-sampled regions from damping the global average, regions with large sampling errors are excluded from the global average. Sampling error, normalized by anomaly standard deviation, is used to define excluded regions. After testing several cut offs, it was decided to exclude regions with a normalized sampling error of 0.5. The amount of global area excluded is greatest in the 19th century, when it is 20%-30%. For the 20th century the area excluded is 20% or less, and after 1950 it is less than 15%.
References
Peterson, T. C., and R. S. Vose (1997), An Overview of the Global Historical Climatology Network Temperature Database, Bull. Am. Meteorol. Soc., 78,
2837-2849.
Smith, T. M., and R. W. Reynolds (2004), Improved extended reconstruction of SST (1854-1997), J. Clim., 17, 2466-2477.
Smith, T. M., and R. W. Reynolds (2005), A global merged land air and sea surface temperature reconstruction based on historical observations (1880-1997), J. Clim., 18, 2021-2036.
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