These global and hemispheric temperature anomaly time series, which incorporate land and marine data, are continually updated and expanded by P. Jones of the Climatic Research Unit (CRU) with help from colleagues at the CRU and other institutions. Some of the earliest work in producing these temperature series dates back to Jones et al. (1986a,b,c). Other related work includes Jones (1988, 1994) and Jones and Briffa (1992).

The land portion of the database from which the time series are computed consists of surface air temperature (SAT) data (land-surface meteorological data and fixed-position weather ship data) that have been corrected for nonclimatic errors, such as station shifts and/or instrument changes (Jones 1994). The reanalysis of land surface data by the CRU (Jones 1994) resulted in (1) the inclusion of over 1000 additional stations, (2) a new reference period common to all stations (1961-1990; previously 1950-1979), and (3) increased grid-box resolution of the temperature anomalies (5° X 5°).

The marine data used in the present analysis are compiled at the Hadley Centre of the United Kingdom Meteorological Office (Parker et al. 1995) and consist of sea surface temperatures (SSTs) that incorporate in situ measurements from ships and buoys. The SST data have been corrected for different types of buckets used before 1942 (Folland and Parker 1995; Parker et al. 1994, 1995). These SSTs also were converted to anomalies with respect to the 1961-1990 mean.

The two constituent data sets (SAT and SST) were combined using the algorithm developed by Parker et al. (1994). The resulting data set has been used extensively in various Intergovernmental Panel on Climate Change (IPCC) reports (e.g., Nicholls et al. 1996) and the global-mean temperature changes evident in the record have been interpreted in terms of anthropogenic forcing influences and natural variability (e.g., Wigley et al. 1997).

Jones et al. (1997a) assessed the uncertainty (standard error) of these temperature anomaly series (through 1995) on interannual and interdecadal timescales by estimating errors due to large-scale sampling. They did so using the observational data described above and complementary results from multicentury control integrations of three coupled general circulation models (GCMs). Readers interested in the details of the error estimation procedure and results pertaining to various regions, seasons, models, and timescales are encouraged to see Jones et al. (1997a), but a few main findings related to the global series are as follows. For mean annual observed data on the interannual timescale, the 95% confidence interval for estimates of the global-mean surface temperature since 1951 is ± 0.12°C. Prior to 1900, the confidence interval widens to ± 0.18°C. Equivalent values on the decadal timescale are smaller: ± 0.10°C (1951-1995) and ± 0.16°C (1851-1900).

Detailed Information taken from: http://cdiac.esd.ornl.gov/trends/temp/jonescru/jones.html

Click on the links below to view data coverage maps for a particular time period. Percentage of non-missing data per time period is plotted.

(1861-1880, 1881-1900, 1901-1920)

(1921-1940, 1941-1960, 1961-1980)

(1981-2000)

Updated: 5/27/03
Maintained by asphilli@ucar.edu