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Climate reanalysis refers to physically-based numerical frameworks that simulate the state Earth's
climate through time, guided by frequent input of real-world observations (e.g., weather stations,
radiosonde, satellite, and ocean buoys). Reanalysis models are invaluable tools for understanding
climate variability and change, including across areas where direct observations are not
available. Climate Reanalyzer provides access to common meteorological variables for the most
widely used reanalysis models. More information about reanalysis can be found at
The initial release of ERA5 begins 1979, but a preliminary back extension 1950-1978 became available in November, 2020. ECMWF
the back extension contains unrealistically intense tropical cycles, and that a replacement version should be ready in late 2021.
The 1950-present ERA5 record (initial release + preliminary back extension) is available here at 0.5° resolution (regridded from 0.25°).
Model domain based on a polar stereographic projection with minimum latitudes ranging 27°N-41°N.
Gridded data products place point-based or spatially discontinuous observations of
Earth's climate (e.g., temperature, precipitation, wind, and sea surface temperature) onto
time-registered grids and fill in data gaps using methods of interpolation. As with reanalysis,
gridded datasets are useful for climate study in areas that may not have direct observations,
but where the intersection of surrounding input data can provide meaningful information. Climate
Reanalyzer provides access to several widely used gridded datasets.
Climate models afford physically-based simulations of energy and material flows through
the atmosphere, ocean, and other parts of the earth system. The most complex of these frameworks
are earth system models, where multiple systems are coupled and yield dynamic interactions.
Climate and earth system models are used to investigate past, present, and future climate
evolution based on changes in radiative forcing, such as from greenhouse-gas emissions. Since
1995, the international consortium
Coupled Model Intercomparison Project (CMIP) has organized a common set of experiments for
modeling groups to use in future climate studies. CMIP 5 and 6 multi-model ensemble mean results
(near-surface temperature, precipitation, and mean sea level pressure) are available from
Climate Reanalzyer for mid- and high-warming scenarios to the year 2100. Scenarios in CMIP5 are
based on Representative Concentration Pathways (RCP), and in CMIP6 on Shared Socioeconomic
Pathways (SSP). Further explanation on CMIP5 and 6 can be found
The ensemble mean CMIP 5 and 6 datafiles on this page where generated from the
KNMI Climate Explorer.
Climate Reanalyzer provides visualizations of existing publicly-available datasets and models. This website
is produced by the Climate Change Institute
at the University of Maine. Our institute has a 50-year
history of polar exploration, and research contributions to glaciology, climate science, and anthropology.
Send inquiries to reanalyzer at gmail.com.
Information on this site is for educational purposes only without any implied warranties. The Climate Institute
and University of Maine shall not be liable for damages or expenses resulting from the use of this website or
data contained within.
License and Citation
Climate Reanalyzer content is licensed under a
Creative Commons Attribution 4.0 International License
Figures may be used as-is in publications, newsletters, and websites provided that the ClimateReanalyzer.org
and data source labels are visible, or otherwise credited if image is modified.
To cite Climate Reanalyzer in a publication, please use this page-specific reference:
Birkel, S.D. 'Monthly Reanalysis Correlation Maps', Climate Reanalyzer (https://ClimateReanalyzer.org), Climate Change
Institute, University of Maine, USA. Accessed on [date image/data downloaded].