Technical documentation: Global climate model sea surface datasets
On this page
- Data and processing
- Reference period for anomaly results (projected change)
- Equal model weighting
- Model range through the use of ensemble percentiles
- Best practice
- Use limitation
- Contact information
Multi-model sea surface datasets based on global climate model (GCMs) projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are provided. Multi-model ensembles of modelled output and projected changes based on three GCMs are available, as well as the individual model simulations. Multi-model output are available for historical simulations and three emission scenarios, RCP2.6, RCP4.5 and RCP8.5, at a 1x1 degree grid resolution. Projected changes are expressed as anomalies with respect to the reference period of 1986-2005. Sea surface variables and additional details are listed in Table 1.
Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.
Table 1. Main characteristics
|Variables and units||
Dissolved inorganic carbon concentration at surface (mol/m³)
pH at surface
Sea surface salinity (psu)
Total alkalinity at surface (mol/m³)
Sea surface temperature (K)
|Spatial resolution||1x1 degree grid resolution|
1900 to 2100
20-year averages of projected change are available for: 2016-2035; 2046-2065; 2081-2100
Monthly, seasonal, and annual
Seasons: The standard meteorological seasons are used: March to May (spring), June to August (summer), September to November (autumn/fall), and December to February (winter).
Data and processing
The three CMIP5 GCMs included in this dataset (listed in Table 1) are available through the Program For Climate Model Diagnosis and Intercomparison (PCMDI) site (downloaded 15 April 2014). Only the GCMs with available historical and scenario output (RCP2.6, RCP4.5 and RCP8.5) for all of the five variables, dissolved inorganic carbon concentration at surface, pH at surface, sea surface salinity, total alkalinity at surface and sea surface temperature, were included. Multi-model ensembles of actual and anomaly values were constructed using the results of these GCMs interpolated to a common 1x1 degree grid. Individual model results are also available for download.
Only concentration-driven experiments are used (i.e., those in which concentrations rather than emissions of greenhouse gases are prescribed) and only one ensemble member from each model is selected, even if multiple realizations exist with different initial conditions and different realizations of natural variability. Hence each model is given equal weight.
Reference period for anomaly results (projected change)
Projected changes are expressed as anomalies with respect to the reference period of 1986-2005 (i.e., differences between the future period and the reference period). Therefore, twenty-year averages of projected change (in the sea surface variable) for the three future time periods (2016-2035; 2046-2065; 2081-2100) are with respect to the reference period of 1986-2005.
Equal model weighting
The different CMIP5 models used for the projections are all considered to give equally likely projections in the sense of 'one model, one vote'. Models with variations in physical parameterization schemes are treated as distinct models.
Model range through the use of ensemble percentiles
As local projections of climate change are uncertain, a measure of the range of model projections is normally provided, i.e., ensemble minimum and maximum values, in addition to the median response of the model ensemble. In this case, with only three models available, the minimum, maximum and median results are simply the appropriately ordered values from the three individual models. It should be emphasized that this range does not represent the full uncertainty in the projection. The distribution combines the effects of natural variability and model spread. In addition, please note that there may be other GCMs that produce simulations for sea surface variables available on the PCMDI site. However, only the GCMs with output for all five variables (listed in Table 1) in their historical and future scenario simulations (for RCP2.5, RCP4.5 and RCP8.5) were included for consistency.
Given the range of natural climate variability and uncertainties regarding future greenhouse gas emission pathways and climate response, changes projected by one climate model should not be used in isolation. Rather, it is good practice to consider a range of projections from multiple climate models (ensembles) and emission scenarios.
While likelihoods are not associated with particular climate change scenarios, the use of a range of scenarios may help convey to users the potential spread across a range of possible emission pathways.
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