Abstract
This paper describes the datasets from the Scenario Model Intercomparison Project (ScenarioMIP) simulation experiments run with the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System Model, GridPoint version 3 (CAS FGOALS-g3). FGOALS-g3 is driven by eight shared socioeconomic pathways (SSPs) with different sets of future emission, concentration, and land-use scenarios. All Tier 1 and 2 experiments were carried out and were initialized using historical runs. A branch run method was used for the ensemble simulations. Model outputs were three-hourly, six-hourly, daily, and/or monthly mean values for the primary variables of the four component models. An evaluation and analysis of the simulations is also presented. The present results are expected to aid research into future climate change and socio-economic development.
Highlights
Climate change and sustainable development are at the frontier of international geoscience research in the 21st century
According to the Fifth Intergovernmental Panel on Climate Change (IPCC) Assessment Report, it is clear that human activity affects the climate system and recent anthropogenic emissions of greenhouse gases are the highest in history
ScenarioMIP uses the integrated assessment models (IAMs) to generate quantitative predictions of greenhouse gas emissions, atmospheric component concentrations, and land-use changes that may occur under different shared socioeconomic pathways (SSPs) energy scenarios
Summary
Climate change and sustainable development are at the frontier of international geoscience research in the 21st century. Measurements of economic risk are science-based tools used by governments to make important decisions related to climate change They are core components of previous IPCC scientific assessment reports. Phase 6 of the Coupled Model Intercomparison Project (CMIP6) uses six integrated assessment models (IAMs), various shared socioeconomic paths (SSPs), and the latest trends in anthropogenic emissions and land-use changes to generate new prediction scenarios. These scenarios form part of CMIP6 and are referred to as the Scen-. ScenarioMIP uses the IAMs to generate quantitative predictions of greenhouse gas emissions, atmospheric component concentrations, and land-use changes that may occur under different SSP energy scenarios.
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