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.

Evaluating the Competing Impacts of Global Emissions Reductions and Climate Change on the Distribution and Retention of selected POPs in Arctic Ocean

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.

Future of Ecosystems and Extremes: Using Diverse Environmental Data Sets in Support of Regional to Global Earth-System Models and Predictions

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.

A Paradigm Shift in Ecosystem and Environmental Modeling: An Integrated Stochastic, Deterministic, and Machine Learning Approach

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.

Quantifying Climate Feedbacks from Abrupt Changes in High-Latitude Trace-Gas Emissions

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.

Shifts in Extreme Precipitation Events Based on Resolved Atmospheric Changes
Vulnerability of carbon storage in North American boreal forests to wildfires during the 21st Century

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 Role of Vegetation in the Dynamics of West African Monsoons

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

Studying regional climate change based on uncertainty in climate parameters using CAM3

The MIT Integrated Global Systems Model (IGSM) version 2.3 is an intermediate complexity model that couples a zonally-averaged statistical dynamical atmospheric model with a full 3D ocean GCM and, therefore, simulates feedbacks associated with changes in ocean circulation. A fundamental feature of the IGSM2.3 is the ability to modify its climate sensitivity (through cloud adjustment), net aerosol forcing and ocean heat uptake rate (via the diapycnal diffusion coefficient). As such, the IGSM2.3 provides an efficient tool for generating probabilistic distribution functions of climate parameters (climate sensitivity, aerosol forcing and ocean heat uptake rate) using optimal fingerprint diagnostics. Probabilistic distributions of sea surface temperature (SST) and sea ice cover (SIC) changes for the 21st century can then be obtained using Latin-Hypercube sampling of climate parameters under various emissions scenarios. The emissions scenarios used in this study are based on the MIT Emissions Predictions and Policy Analysis (EPPA) model and include a no policy case where emissions of long-lived GHGs are uncertain, and a range of stabilization scenarios from stringent policy to milder policy.

In order to investigate future regional climate impacts, the MIT IGSM2.3 is coupled to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model version 3 (CAM3). For linkages between the IGSM2.3 and CAM3, the 3-D atmospheric model is driven by the IGSM2.3 SST anomalies with a climatological annual cycle taken from an observed dataset, instead of the full IGSM2.3 SSTs, to provide a better SST annual cycle and more realistic features between the ocean and atmospheric components. This approach yields a consistent regional distribution and climate change over the 20th century as compared to observational datasets. For each emissions scenario, an ensemble member of the IGSM2.3 SST/SIC probabilistic distribution drives CAM3 to span the multi-dimensional space of uncertainty in climate parameters. For consistency, for each set of IGSM2.3/CAM3 runs, the trace gas concentrations calculated by the atmospheric chemistry component of the IGSM2.3 is used to force CAM3. The cloud adjustment scheme used in the IGSM2.3 was implemented in CAM3, which allows modifying its climate sensitivity to match that of the IGSM2.3 setup that generates the SST field used to drive CAM3.

With this approach, regional climate impacts can be assessed under various emissions scenarios based on probability distributions of climate parameters. In this paper, preliminary results from these ensemble simulations are presented. A particular focus is placed on the distribution of extreme events. For example, the frequency, duration and intensity of extreme events such as heat waves, floods and droughts, precipitation and storm activities can be investigated, as well as other dynamical features such as jet stream modulation.

Pages

Subscribe to Earth Systems