Earth Systems

Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2ºC global mean warming from pre-industrial by 2100. Evaluating the outcomes of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world's forests: emissions scenarios, the global system climate response (i.e., climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO2 fertilization effects may considerably reduce the range of projections.

Climate model uncertainty in impact assessments for agriculture: A multi-ensemble case study on maize in sub-Saharan Africa

Almost 25 percent of the world’s malnourished population lives in sub-Saharan Africa (SSA), and depends on maize (corn) for much of its caloric intake. The most widely produced crop by harvested area in SSA, maize is also highly sensitive to drought. Because maize in this region is grown largely on rain-fed rather than irrigated land, any future changes in precipitation patterns due to climate change could significantly impact crop yields. Assessing the likely magnitude and locations of such yield changes in the coming decades will be critical for decision-makers seeking to help their nations and regions adapt to climate change and minimize threats to food security and rural economies that are heavily dependent on agriculture.

Toward that end, a team of five researchers with the MIT Joint Program on the Science and Policy of Global Change has applied a broad range of multi- and individual climate model ensembles to project climate-related changes to maize yields throughout most of the 21st century. Accounting for uncertainty in climate model parameters—which is pronounced in high-producing semiarid zones—the researchers project widespread yield losses in the Sahel region and Southern Africa, insignificant change in Central Africa, and sub-regional increases in East Africa and at the southern tip of the continent. The wide range of results highlights a need for risk management strategies that are adaptive and robust to uncertainty, such as the diversification of rural economies beyond the agricultural sector.

The results appear in the early online edition of the journal Earth’s Future. Funded by MIT’s Abdul Latif Jameel World Water and Food Security Lab as a two-year project, “Advancing Water and Food Sustainability through Improved Understanding of Uncertainties in Climate Change and Climate Variability,” the study’s principal investigators are Susan Solomon, Lee and Geraldine Martin Professor of Environmental Studies in the Department of Earth, Atmospheric and Planetary Sciences; and Kenneth Strzepek, research scientist in the MIT Joint Program.

On January 20 a new administration entered the White House determined to cut spending on climate change and environmental protection programs, and reduce restrictions on greenhouse gas emissions that contribute to global warming. To help the MIT community better understand what’s at stake, graduate students with the MIT Joint Program on the Science and Policy of Global Change presented seven courses on climate science and policy during the 2017 MIT Independent Activities Period.

Climate science and policy: Now more than ever!
Ecosystem fluxes of hydrogen in a mid-latitude forest driven by soil microorganisms and plants

Molecular hydrogen (H2) is an atmospheric trace gas with a large microbe-mediated soil sink, yet cycling of this compound throughout ecosystems is poorly understood. Measurements of the sources and sinks of H2 in various ecosystems are sparse, resulting in large uncertainties in the global H2 budget. Constraining the H2 cycle is critical to understanding its role in atmospheric chemistry and climate. We measured H2 fluxes at high frequency in a temperate mixed deciduous forest for 15 months using a tower-based flux-gradient approach to determine both the soil-atmosphere and the net ecosystem flux of H2. We found that Harvard Forest is a net H2 sink (−1.4 ± 1.1 kg H2 ha−1) with soils as the dominant H2 sink (−2.0 ± 1.0 kg H2 ha−1) and aboveground canopy emissions as the dominant H2 source (+0.6 ± 0.8 kg H2 ha−1). Aboveground emissions of H2 were an unexpected and substantial component of the ecosystem H2 flux, reducing net ecosystem uptake by 30% of that calculated from soil uptake alone. Soil uptake was highly seasonal (July maximum, February minimum), positively correlated with soil temperature and negatively correlated with environmental variables relevant to diffusion into soils (i.e., soil moisture, snow depth, snow density). Soil microbial H2 uptake was correlated with rhizosphere respiration rates (r = 0.8, P < 0.001), and H2 metabolism yielded up to 2% of the energy gleaned by microbes from carbon substrate respiration. Here, we elucidate key processes controlling the biosphere–atmosphere exchange of H2 and raise new questions regarding the role of aboveground biomass as a source of atmospheric H2 and mechanisms linking soil H2 and carbon cycling. Results from this study should be incorporated into modeling efforts to predict the response of the H2 soil sink to changes in anthropogenic H2 emissions and shifting soil conditions with climate and land-use change.

When hearing the words “greenhouse gas,” most people think immediately of carbon dioxide. This is indeed the greenhouse gas that is currently producing the greatest impact on the Earth’s rapidly changing climate. But it is far from the only one making its mark, and for mitigating climate change it’s important to be able to compare the effects of the various gases that contribute to warming the planet.

But that’s not easy to do.

Explained: Greenhouse gases
Probabilistic Projections of 21st Century Climate Change Over Northern Eurasia

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.

The top 2 inches of topsoil on all of Earth’s landmasses contains an infinitesimal fraction of the planet’s water — less than one-thousandth of a percent. Yet because of its position at the interface between the land and the atmosphere, that tiny amount plays a crucial role in everything from agriculture to weather and climate, and even the spread of disease.

The behavior and dynamics of this reservoir of moisture have been very hard to quantify and analyze, however, because measurements have been slow and laborious to make.

Study tracks “memory” of soil moisture

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