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[CIDC FTP Data]
[GISS Surface Air Temperature Data on FTP]
Data Access
Global Mean Surface Air Temperature Anomalies from NASA
Goddard Institute for Space Studies(GISS)
[rule]
Readme Contents
Data Set Overview
Sponsor
Original Archive
Future Updates
The Data
Characteristics
Source
The Files
Format
Name and Directory Information
Companion Software
The Science
Theoretical Basis of Data
Processing Sequence and Algorithms
Scientific Potential of Data
Validation of Data
Data Access and Contacts
FTP Site
Points of Contact
References
[rule]
Data Set Overview
Global mean monthly, seasonal and annual temperature anomalies are
given. The anomalies are variations from the means determined for
the base period 1951-1980. These data are an update of the
analyses described by Hansen and Lebedeff (1987 & 1988).
Discussions of the data are given in the references below. The
input data for these analyses come from about 2000 meteorological
stations around the world, This work was done at the Goddard
Institute for Space Studies (GISS) by Dr. James Hansen and his
colleagues. Their complete analysis considers regional as well as
global mean temperature variations. In the brief summary presented
at this site only the global means are given.
Sponsor
The production and distribution of this data set are
funded by NASA's Earth Science enterprise. The data are
not copyrighted; however, we request that when you
publish data or results using these data please
acknowledge as follows:
The authors wish to thank Dr. James Hansen and
his colleagues at the Goddard Institute for
Space Studies for the production of this data
set, and the Distributed Active Archive Center
(Code 902) at the Goddard Space Flight Center,
Greenbelt, MD, 20771, for putting these data
in their present format and distributing them.
These distribution activities were sponsored
by NASA's Earth Science enterprise.
Original Archive
This data set was constructed by the Surface Air
Temperature Study Group at the Goddard Institute for
Space Studies. This is also the location of the primary
archive and the source for detailed information
concerning this data set.
Future Updates
This data set will be updated as new data is made
available.
The Data
Characteristics
GISS Temperature Analysis
Parameters Mean Global Surface Air Temperature
Anomalies
Units 0.01 Degrees Celsius
-130 to +90 (monthly)
Typical Range
-60 to +50 (annual)
Temporal Coverage January 1866- September 1997
Temporal Resolution: monthly, seasonal and annual means
Spatial Coverage Global
Spatial Resolution Global
Source
The input data for these analyses are principally the
Monthly Climatic Data of the World (MCDW) from about
2000 meteorological stations around the world,
supplemented for the most recent several months by NOAA
near real time data for most of these stations. The MCDW
data set is maintained by the National Oceanic and
Atmospheric Administration (NOAA) in cooperation with
the World Meteorological Organization.
The Files
Format
The GISS Surface Air Temperature Anomalies Global Mean
data set consist of a single, 16KB, ASCII-formatted
file.
Name and Directory Information Naming Convention
Directory Path
/data/inter_disc/surf_temp_press/tmp_dev/giss/
Please make note that the data is in a table (ASCII) format
Companion Software
None.
The Science
Theoretical Basis of Data
The surface air temperature and the sea surface
temperature are basic weather and climate parameters.
They are normally measured by thermometers. The present
data set was established to examine long term trends;
for this reason temperature changes from the 1951-1980
mean are presented rather than the temperatures
themselves. A good approximation to the actual annual
global-mean temperature is obtained by adding 14 degrees
C to the anomalies. The basic problems in examining
multidecade temperature trends concern calibration and
sampling errors or deficiencies.
Some meteorological stations report above normal warming
trends over the last hundred years because cities have
grown up around them. The extra heat generated in the
city causes urban meteorological stations to have a
higher average temperature than rural stations. Since
stations tend to cluster in urban regions some have
argued that the global warming trend is exaggerated in
the existing data. The GISS analysis does not correct
for the urban heat island effect, but their analysis
shows that the overall effect is small.
Hansen et al. (1995) state:
"Errors in surface air temperature trends due
to changes of instrumentation, station
location, and diurnal sampling can be
substantial at individual locations and
require continuing attention (Karl and
Williams, 1987). The most serious problem is
probably urban heat island effects, which tend
to be systematic. Hansen and Lebedeff (1987)
found the global warming of the past century
in their analysis to be reduced 0.1 degree C
when cities of population more than 100,000
were excluded, and they estimated the total
global-mean urban effect to be 0.1-0.2 degrees
C. A more precise test for the United States,
based on comparing rural and MCDW stations,
revealed large differences in certain regions
such as southern California, but averaged over
the contiguous United States the temperature
change of MCDW and rural stations differed by
only 0.1 degrees C (Hansen et al., 1991)."
Processing Sequence and Algorithms
Surface air temperature has been measured at a large
number of meteorological stations for over one hundred
years, mainly at northern hemisphere land locations.
This GISS analysis uses data from about 2000
meteorological stations around the world. The earth's
surface is divided into 80 equal area "boxes", the full
dimension of a box side being about 2500 km. For the
locations of the boxes see Figure 2 in Hansen and
Lebedeff (1987). Each of the 80 boxes is subdivided into
an array of 10 by 10 equal-area "subboxes". The
temperature anomaly for a subbox is defined using all
stations located within 1200 km of the subbox's center.
Hansen et al. have carried out some quality control of
original data by examining, and comparing with nearby
stations, those values which differ by more than 5
standard deviations from their long term mean.
Undoubtedly some errors remain. They welcome
communications from users who find specific errors or
unusual behavior in the temperature data, which can help
them improve future versions of the dataset. The 100
subbox values in a box are used to find the box average.
Latitude zonal, hemispherical and global means are also
calculated. Details of the analysis method can be found
in Hansen and Lebedeff (1987). The results from subbox
to global mean are available from GISS.
The number of available stations and their distribution
was much smaller at the start of the time series, 1886,
than at present. The GISS analysis procedure is designed
to minimize the difficulties this presents in measuring
large scale regional and global temperature shifts. The
base period, 1951-1980, was chosen because there was
reasonably good global coverage available during this
period.
GISS has recently also started to produce a shorter
combined land and ocean temperature dataset. Better
global coverage is obtained by combining meteorological
station data with measurements of sea surface
temperature (SST). The SST data used by GISS are a
blended analysis of satellite and ship measurements by
Reynolds and Smith (1994) for the period 1982-present,
the satellite providing high resolution while the in
situ data provide bias correction. The SST data for
1950-1981 are based on only in situ data (Smith et al.
1996). The land-ocean ltemperature index provides a
measure of global temperature change which proves to be
in good agreement with the temperature change estimated
from the meteorological station network. The land-ocean
index has the advantage of providing a more detailed and
accurate description of change in marine regions. This
data is not available on this Interdisciplinary Data
site but it is available from GISS. The East Anglia
Temperature Deviations, which are available on this
site, also consist of blended land and ocean
measurements (Jones et al., 1991).
Scientific Potential of Data
This dataset can be used for numerous climate studies.
Some examples are:
* Global Warming (Houghton et al. 1995; Hansen et
al., 1996; Hansen and Lacis, 1990)
* Correlations between various terrestrial climate
variables ( Kyle et al., 1995; Ardanuy et al. 1992)
* Correlation of variations in the climate and solar
variability (Hoyt and Schatten 1993)
Validation of Data
The uncertainty in this data set of the estimated
temperature change in a given year is about 0.07C due to
just the incomplete sampling of the globe by the station
network. Thus the relative rank of different years is
uncertain for years whose temperatures differ by less
than that amount. However, the GISS land-sea temperature
index which uses sea surface temperatures to provide
coverage of most ocean areas has a smaller uncertainty.
This uncertainty should be kept in mind when comparing
the East Anglia and GISS temperature anomalies.
Contacts
Points of Contact
For information about or assistance in using any DAAC data,
contact
EOS Distributed Active Archive Center (DAAC) Code 902
NASA Goddard Space Flight Center
Greenbelt, Maryland 20771
Internet: daacuso@daac.gsfc.nasa.gov
301-614-5224 (voice)
301-614-5268 (fax)
Scientists whom you may contact about these data are:
* James Hansen (jhansen@giss.nasa.gov); phone: 212-678-5619
* Reto Ruedy (rruedy@giss.nasa.gov) 212-678-5600
* Makiko Sato (makikosato@giss.nasa.gov) 212-678-5618
Address: NASA Goddard Institute for Space Studies 2880 Broadway
New York, NY 10025
Click here to view the NASA Goddard Institute for Space Studies,
Surface Air Temperature Analyses Site.
References
Ardanuy, P.E., H.L. Kyle, and D. Hoyt, 1992: Global relationships
between the earth's radiation budget, cloudiness, volcanic
aerosols, and surface temperature, J. Climate, 10, 1120-1139
Hansen, J., and S. Lebedeff, 1987: Global trends of measured
surface air temperature. J. Geophys. Res. 92, 13,345-13,372.
Hansen, J., and S. Lebedeff. 1988. Global surface air
temperatures: Update through 1987. Geophys. Res. Lett. 15,
323-326.
Hansen, J.E., and A. Lacis, 1990: Sun and dust versus greenhouse
gases: An assessment of their relative roles in global climate
change, Nature, 346, 713-719.
Hansen, J., D. Rind, A. Del Genio, A. Lacis, S. Lebedeff, M.
Prather, R. Ruedy, and R. Karl, 1991: Regional greenhouse climate
effects, in Greenhouse-Gas_Induced Climatic Change, edited by M.
E. Schlesinger, pp 211-229, Elsevier, Amsterdam.
Hansen, J., H. Wilson, M. Sato, R. Ruedy, K. Shah, and E. Hansen.
1995. Satellite and surface temperature data at odds? Climatic
Change, 30, 103-117.
Hansen, J., R. Ruedy, M. Sato, and R. Reynolds, 1996: Global
surface air temperature in 1995: Return to pre-Pinatubo level.
Geophys. Res. Lett. 23, 1665-1668.
Houghton, J.T., L.G. Meira Filho, J. Bruce, H. Lee, B.A.
Callander, E. Haites, N. Harris and K. Maskell, Eds. 1995: Climate
Change 1994: radiative forcing of climate change and an evaluation
of the IPCC IS92 emission scenarios, Cambridge University Press,
339 pp.
Hoyt, D.V. and K.H. Schatten, 1993: A discussion of plausible
solar irradiance variations, 1700-1992, J. Geophys. Res., 98,
18895-18906.
Jones, P. D., T. M. L. Wigley, and G. Farmer, 1991: Marine and
land temperature data sets: a comparison and a look at recent
trends, in, Greenhouse-Gas-induced Climatic Change: A Critical
Appraisal of Simulations and Observations, M. E. Schlesinger, Ed.,
Elsevier Scientific Publishers, New York, 153-172.
Karl, T. R., and C. N. Williams, 1987: An approach to adjusting
climatological time series for discontinuous inhomogeneities, J.
Clim. Appl. Meteorol., 26, 1744-1763.
Kyle, H.L., M. Weiss and P. Ardanuy, 1995: Cloud, surface
temperature, and outgoing longwave radiation for the period from
1979 to 1990, J. Climate, 8, 2644-2658.
Reynolds, R.W., and T.M. Smith. 1994. Improved global sea surface
temperature analyses using optimal interpolation. J. Climate 7,
929-948.
Smith, T.M., R.W. Reynolds, R.E. Livezey, and D.C. Stokes. 1996.
Reconstruction of historical sea surface temperature using
empirical orthogonal functions. J. Climate 9, 1403-1420.
------------------------------------------------------------------------
[NASA] [GSFC] [Goddard DAAC] [cidc site]
NASA Goddard GDAAC CIDC
Last update: Fri Oct 24 10:17:56 EDT 1997
Page Author: Lee Kyle -- lkyle@daac.gsfc.nasa.gov
Web Curator: Daniel Ziskin -- ziskin@daac.gsfc.nasa.gov
NASA official: Paul Chan, DAAC Manager -- chan@daac.gsfc.nasa.gov