Earth Systems

The goal of this research is to better understand how changes in global emissions and climate are affecting the distribution, lifetime, and bioavailability of selected persistent organic pollutants (POPs) in the Arctic Ocean. POPs travel globally in air and water, are often highly bioaccumulative, and have the ability to cycle among environmental media enabling long-range transport to remote regions such as the Arctic.

This study aims to identify regions where the resiliency to withstand extreme weather and climate events is at risk, and therefore degrade the regions' ability to resist any changes. This will aid stakeholders and decision-makers as they prepare for and adapt to environmental change. By employing a variety of models, including MIT's Integrated System Model (IGSM), we will evaluate how a set of environmental stresses affects specific regions. This work will also develop a heuristic model to serve as more efficient and powerful predictive tool to help guide adaptation strategies.

System-based modeling is now widely used to quantify ecosystem and environmental elemental cycling (e.g., C and N), hydrological dynamics, and energy fluxes. In this context, deterministic differential equations link state variables and fluxes of ecosystems or environmental entities (e.g., lakes, forests, or areas of coastal ocean). Traditionally, these models are parameterized with limited observational data and then applied over extended temporal and spatial scales.

Our overall goal in this project is to quantify the potential for threshold changes in natural emission rates of trace gases, particularly methane and carbon dioxide, from pan-arctic terrestrial systems under the spectrum of anthropogenically forced climate warming, and the extent to which these emissions provide a strong feedback mechanism to global climate warming.

This project aims to combine remotely sensed and in situ measurements with reanalyses and climate model projections to quantify the changes in the frequency of extreme events.  The projections will be based on multi-model IPCC AR4 data archives in order to assess model structure differences.  The project addresses both extreme high precipitation amounts and persistent low precipitation amounts.  We recognize that model projections and atmospheric models in general do not resolve moist processes well.

The boreal forest contains large reserves of carbon. Across this region, wildfires influence the temporal and spatial dynamics of carbon storage. In this study, we estimate fire emissions and changes in carbon storage for boreal North America over the 21st century. We use a gridded data set developed with a multivariate adaptive regression spline approach to determine how area burned varies each year with changing climatic and fuel moisture conditions.We apply the process-based Terrestrial Ecosystem Model to evaluate the role of future fire on the carbon dynamics of boreal North America in the context of changing atmospheric carbon dioxide (CO2) concentration and climate in the A2 and B2 emissions scenarios of the CGCM2 global climate model. Relative to the last decade of the 20th century, decadal total carbon emissions from fire increase by 2.5–4.4 times by 2091–2100, depending on the climate scenario and assumptions about CO2 fertilization. Larger fire emissions occur with warmer climates or if CO2 fertilization is assumed to occur. Despite the increases in fire emissions, our simulations indicate that boreal North America will be a carbon sink over the 21st century if CO2 fertilization is assumed to occur in the future. In contrast, simulations excluding CO2 fertilization over the same period indicate that the region will change to a carbon source to the atmosphere, with the source being 2.1 times greater under the warmer A2 scenario than the B2 scenario. To improve estimates of wildfire on terrestrial carbon dynamics in boreal North America, future studies should incorporate the role of dynamic vegetation to represent more accurately post-fire successional processes, incorporate fire severity parameters that change in time and space, account for human influences through increased fire suppression, and integrate the role of other disturbances and their interactions with future fire regime. © Wiley Blackwell

The focus of this paper is the role of meridional distribution of vegetation in the dynamics of monsoons and rainfall over West Africa. We develop a moist zonally symmetric atmospheric model coupled with a simple land surface scheme to investigate these processes. Four primary experiments have been carried out to examine the sensitivity of West African monsoons to perturbations in vegetation patterns. Each perturbation experiment is identical to the control experiment except that a change in vegetation cover is imposed for a latitudinal belt of 10° in width. The numerical experiments demonstrate that West African monsoons and therefore rainfall depend critically on the location of the vegetation perturbations. While the magnitude of local rainfall is sensitive to changes in local vegetation, the location of the Inter-Tropical Convergence Zone (ITCZ) is not sensitive to changes in the vegetation northward or southward from the location of ITCZ in the control experiment. However, the location of the ITCZ is sensitive to changes of the vegetation distribution in the immediate vicinity of the location of the ITCZ in the control experiment. The modeling results indicate that changes in vegetation cover along the border between the Sahara desert and West Africa (desertification) have a minor impact on the simulated monsoon circulation. On the other hand, coastal deforestation may cause the collapse of the monsoon circulation and have a dramatic impact on the regional rainfall. The observed deforestation in West Africa is then likely to be a significant contributor to the observed drought.

© 1998 American Meteorological Society

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