GISTEMP

GISTEMP
Efbrazil · CC BY-SA 4.0 · source
Name	GISTEMP
Developer	NASA Goddard Institute for Space Studies
First release	1981
Latest release	ongoing
Programming language	Fortran, Python
License	Public domain (NASA)

GISTEMP

GISTEMP is a global surface temperature analysis developed at the NASA Goddard Institute for Space Studies that produces monthly and annual temperature anomaly datasets. It is used alongside datasets from National Oceanic and Atmospheric Administration, Met Office Hadley Centre, Berkeley Earth, and European Centre for Medium-Range Weather Forecasts for climate monitoring, policy assessment, and research. The product informs assessments by the Intergovernmental Panel on Climate Change, contributions to reports by the United Nations Framework Convention on Climate Change, and investigations by scientific bodies such as the National Academy of Sciences, Royal Society, and American Geophysical Union.

Overview

GISTEMP provides gridded estimates of near-surface air temperature anomalies by combining terrestrial and marine observations to produce global, hemispheric, and regional time series. The dataset has strong connections to observational systems including the Global Historical Climatology Network, the International Surface Temperature Initiative, and marine archives such as the ICOADS collection. It interfaces with reanalysis products from ERA5, MERRA-2, and JRA-55 while informing model evaluation for ensembles like CMIP5 and CMIP6 used by climate modeling centers such as NOAA GFDL, NCAR, and Met Office Hadley Centre.

Methodology

The methodological core combines station-based records and sea surface temperature fields into a 2°x2° grid using an anomaly-based interpolation scheme. Processing steps align with practices used in homogeneous series work by researchers at Columbia University, Princeton University, and Harvard University who study homogenization and trend detection. Spatial smoothing and kriging-like approaches are informed by statistical methods developed by communities around Geostatistics, applications in NOAA analyses, and contributions from statistical groups at University of Oxford and Stanford University.

Data Sources and Processing

Primary land station inputs come from the Global Historical Climatology Network and national meteorological services such as Met Éireann, Deutscher Wetterdienst, Japan Meteorological Agency, and Environment and Climate Change Canada. Marine inputs derive from compilations including the International Comprehensive Ocean-Atmosphere Data Set and ship and buoy observations maintained by National Centers for Environmental Information and Simple Ocean Data Assimilation efforts. Quality control, homogenization, and metadata linkage draw on collaborative efforts with archives like the World Data Center for Meteorology and projects such as the Surface Temperatures for the Last Global Warming (STL GW) initiative. Computational processing is performed using codebases developed at NASA Goddard Institute for Space Studies and reproducibility efforts that reference workflows from institutions like GitHub repositories maintained by university groups and national laboratories including Lawrence Berkeley National Laboratory.

Uncertainty and Bias Correction

Uncertainty quantification addresses instrument changes, station relocations, urbanization effects, and methodological choices through bootstrapping, sensitivity experiments, and comparisons across alternative homogenization schemes. Bias corrections account for ship intake, bucket measurements, and buoy adjustments, engaging literature from researchers at Scripps Institution of Oceanography, Woods Hole Oceanographic Institution, and the NOAA Atlantic Oceanographic and Meteorological Laboratory. Urban heat island assessments leverage urban datasets from NASA remote sensing missions like Landsat and MODIS and studies by urban climatology groups at Massachusetts Institute of Technology and University College London.

Validation and Comparisons

GISTEMP is routinely compared with independent reconstructions such as those from Berkeley Earth, HadCRUT4, and NOAA GlobalTemp as well as paleoclimate reconstructions involving PAGES network contributions and ice core analyses from Dome C and Greenland Ice Sheet Project. Intercomparisons involve benchmarking against reanalyses (ERA5, MERRA-2) and satellite products from missions like NOAA POES and Aqua, and evaluation by institutions including the European Space Agency and the Joint Panel on Climate Change. Peer-reviewed assessments in journals such as Nature, Science, and Journal of Climate document agreement in large-scale warming patterns while noting regional divergences.

Applications and Impact

GISTEMP informs climate attribution studies conducted by groups at Columbia University Earth Institute, University of Exeter, and national agencies involved in extreme event attribution. It underpins climate services used by World Meteorological Organization, adaptation planning by municipal authorities such as City of New York and Greater London Authority, and sectoral risk assessments in insurance firms and energy companies including Munich Re and BP. The dataset supports academic research across institutions like Imperial College London, ETH Zurich, and Australian National University and contributes to educational resources at museums and outreach programs including the Smithsonian Institution and American Museum of Natural History.

Category:Climate data