Monthly Reanalysis Correlations


Input 1

Dataset info
Variable
Level
Month

Input 2

Dataset
Variable
Level
Climate Index
Upload Timeseries
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Column
Map Subtitle

Map Options

Region
Conf Int
Contour Plot 

Reanalysis Models

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 Reanalysis.org.

Gridded Observations

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 (Historical + Future Projections)

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 here. The ensemble mean CMIP 5 and 6 datafiles on this page where generated from the KNMI Climate Explorer.