The Collaborative Distributed Evaluation System for Earth System Models is toolset that enables users to evaluate and compare multiple Earth System Models (ESMs). This system follows a distributed and collaborative approach, facilitating data sharing, model sharing, and collaborative analysis among users. The Collaborative Evaluation System for distributed Earth System Models is widely applicable, serving the needs of researchers, policymakers, and stakeholders involved in climate change research, impact assessments, and policy decision-making. It is a valuable resource for those who need to evaluate and compare the performance of different ESMs.
1. Model evaluation and comparative analysis
The Collaborative Distributed Evaluation System for Earth System Models integrates the outputs of 50 ESMs from 29 model development institutions in CMIP6. The evaluation system combines the results of historical, piControl, abrupt-4xCO2, 1pctCO2, amip, ssp126, ssp245, ssp370, and ssp585 simulation experiments, enabling the evaluation of more than 40 coupled processes and 13 basic analysis functions with the capacity for online evaluation and comparative analysis over 100000 cases. The Collaborative Distributed Evaluation System for Earth System Models also integrates various observational data for benchmark analysis.
2. Benchmark analysis of individual ESMs
The Collaborative Distributed Evaluation System for Earth System Models supports 28 evaluation and comparison analysis contents, mainly including three aspects: (1) historical period evaluation, (2) benchmark and climate feedback analysis, (3) East Asian monsoon region evaluation. Historical period evaluation includes the simulation evaluation of land, ocean, and atmosphere components of 40 CMIP6 models. Benchmark and climate feedback analysis mainly include benchmark analysis of global land GPP, NPP, carbon turnover time, vegetation carbon storage, soil carbon storage, and carbon allocation, as well as feedback analysis of land-atmosphere. East Asian monsoon region evaluation includes climatology and interannual variability analysis of atmospheric output variables in the region.
3. Datasets
In the section of dataset, users can access those databases used in the benchmarking analysis. Detailed information about data processing procedure, data type, projection, resolution, temporal coverage and file format are also provided. The datasets encompass a wide range of information, covering crucial processes and states within the atmosphere, land, and ocean. Totally, there are 27 datasets about atmospheric varibles, 11 datasets involved with land ecosystem carbon-water cycle key processes, and 18 datasets about oceanic processes and states.