RAPID: Carbon Cycle-Climate Feedback Analysis in CMIP5 Models

University Of Maryland, College Park, College Park MD

Investigators

Abstract

This is one of 16 Rapid Response (RAPID) projects funded as the result of a Dear Colleague Letter (NSF 11-006) encouraging diagnostic analyses of climate model simulations prepared for the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). Research conducted in these projects is expected to lead to more detailed model intercomparisons, better understanding of robust model behaviors, and better understanding and quantification of uncertainty in future climate simulations. This project will analyze the Coupled Model Intercomparison Project (CMIP5) models with a focus on the strength of coupled carbon-climate feedback. The PI will analyze the ability of the latest suite of models, in simulating 19th -20th century co-variability in carbon cycle and climate, as well as projected future changes. The main tasks that will be undertaken are: (i) assessing the realism of the model simulations by comparison with observations; (ii) establishing criterion based on key observational constraints to group the models; (iii) analyzing the strength of carbon-climate feedbacks projected for the 21st century, comparing with earlier results and diagnosing the results in terms of response and feedback; (iv) using a model of intermediate complexity to further understand the CMIP5 model behaviors, such as sensitivity to carbon parameterizations. The principal investigator will also conduct regionally focused analysis for vulnerable carbon pools in such as the Arctic permafrost and subtropical semiarid and forested regions. The broader impact of the project lies in its support of the IPCC AR5, which is intended to provide information on climate change and its consequences to decision makers worldwide. This project will examine carbon-climate feedbacks in the current state-of-the-science models. The study will shed insights into both the deficiencies in current models as well as key observations and experiments needed to improve the models. Such an effort is critical to understanding the trajectory of future concentration of atmospheric CO2, aerosol radiative forcing and sensitivity of earth's climate to greenhouse gas increases.