Regional Analysis

Mid-Western U.S. Heavy Summer-Precipitation in Regional and Global Climate Models: The Impact on Model Skill and Consensus Through an Analogue Lens

Extreme precipitation events pose a significant threat to public safety, natural and managed resources, and the functioning of society. Changes in such high-impact, low-probability events have profound implications for decision-making, preparation and costs of mitigation and adaptation efforts. Understanding how extreme precipitation events will change in the future and enabling consistent and robust projections is therefore important for the public and policymakers as we prepare for consequences of climate change.

Projection of extreme precipitation events, however, particularly at the local scale, presents a critical challenge: the climate model-based simulations of precipitation that we currently rely on for such projections—general circulation models (GCMs)—are not very realistic, mainly due to the models’ coarse spatial resolution. This coarse resolution precludes adequate representation of highly influential, small-scale features such as moisture convection and topography. Regional circulation models (RCMs) provide much higher resolution and better representation of such features, and are thus often perceived as an optimum approach to producing more accurate heavy precipitation statistics than GCMs. However, they are much more computationally intensive, time-consuming and expensive to run.

In a previous paper, the researchers developed an algorithm that detects the occurrence of heavy precipitation events based on climate models’ well-resolved, large-scale atmospheric circulation conditions associated with those events—rather than relying on these models’ simulated precipitation. The algorithm’s results corresponded with observations with much greater precision than the model-simulated precipitation.

In this paper, the researchers show that the performance of the new algorithm in detecting heavy precipitation event is not dependent on the model resolution and even better than that of precipitation simulated from RCMs. The algorithm thus presents a robust and economic way to assess extreme precipitation frequency across a broad range of GCMs and multiple climate change scenarios with minimal computational requirements.   

David L. Chandler | MIT News Office 
April 6, 2018

Putting a price on carbon, in the form of a fee or tax on the use of fossil fuels, coupled with returning the generated revenue to the public in one form or another, can be an effective way to curb emissions of greenhouse gases. That’s one of the conclusions of an extensive analysis of several versions of such proposals, carried out by researchers at MIT and the National Renewable Energy Laboratory (NREL).

Carbon taxes could make significant dent in climate change, study finds
Impacts of air pollutants from fire and non-fire emissions on the regional air quality in Southeast Asia

Particulate pollution-driven severe haze events in Southeast Asia have become more intense and frequent in recent years, degrading air quality and threatening human health. While widespread biomass burning is a major source of these events, particulate pollutants from other human activities also play a key role in degrading the region’s air quality. In this study, MIT Joint Program and collaborating researchers conducted numerical simulations to examine the contributions of aerosols emitted from fire (via biomass burning) vs. non-fire (including fossil fuel combustion, road and industrial dust, land use and land-use change) sources to the degradation of air quality and visibility over Southeast Asia. Covering 2002-2008, these simulations were driven by emissions from: (a) fossil fuel burning only, (b) biomass burning only, and (c) both (a) and (b).

Across the ASEAN 50 cities, these model results reveal that 39% of observed low visibility days (LVDs) can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20% by fossil fuel burning alone, a further 8% by biomass burning alone, and a further 5% by a combination of fossil fuel and biomass burning. The remaining 28% of observed LVDs remain unexplained, likely due to emissions sources not yet identified.

Further analysis of the 24-hour PM2.5 Air Quality Index (AQI) indicates that compared to the simulated result of the standalone non-fire emissions case, the coexisting fire and non-fire PM2.5 case can substantially increase the chance of AQI being in the moderate or unhealthy pollution level from 23% to 34%. The premature mortality among major Southeast Asian cities due to degradation of air quality by particulate pollutants is estimated to increase from ~4110 per year in 2002 to ~6540 per year in 2008.

Finally, the study includes an exploratory experiment of using machine learning algorithms to forecast the occurrence of haze events in Singapore. All results suggest that besides minimizing biomass burning activities, an effective air pollution mitigation policy for Southeast Asia must consider controlling emissions from non-fire anthropogenic sources.

Modeling Unit Commitment in Political Context: Case of China’s Partially Restructured Electricity Sector

Restructuring an electricity sector entails a complex realignment of political and economic institutions, which may both delay and distort the achievement of market conditions that are reasonably competitive. In research and planning for policy interventions in power systems under these varied regulatory environments, typical operational models may neglect important areas in which engineering constraints and political realities combining together can substantially change outcomes, leading to poor understanding of underlying causes of inefficiency and to inappropriate recommendations. We develop tractable formulations of a common power systems model used on a daily basis--the unit commitment optimization--which consider important political factors in the Northeast grid region of China. We demonstrate the importance of these interactions on operations and provide a set of options for researchers to explore further pathways for China's ongoing power system reforms. For example, wind integration, a key policy priority, is inhibited by the interaction of institutions limiting short- and long-term sources of flexibilities in inter-provincial trade.

Next Steps in Tax Reform

The GOP tax reform, now adopted as the 2017 Tax Cuts and Jobs Act, aimed to cut business taxes to stimulate investment, lower some personal taxes, eliminate deductions and tax credits to help pay for the tax reductions, and reduce the shifting of profits abroad by U.S. companies. Some of these objectives have been achieved, but at the cost of a potentially substantial increase in the fiscal deficit, among other problems. As a result, corrections will be needed in future years.

Many of the Act’s undesirable features reflect its drafters’ inability to come up with sufficient revenue to compensate for the tax reductions. This paper explores a carbon dioxide (CO2) tax as perhaps the only measure that’s consistent with the declared tax-reform principles of the GOP leadership, likely to draw Democratic support, and large enough to compensate for the Act’s revenue-losing provisions. After summarizing the process that led to the Act and its major shortcomings, the researchers—applying the MIT U.S. Regional Energy Policy (USREP) model—show how, when the Act is opened up for repairs, a CO2 tax could help correct its flaws while serving environmental goals.

The greening of Northwest Indian subcontinent and reduction of dust abundance resulting from Indian summer monsoon revival

Due to an extremely dry climate and strong winds, the Northwest Indian Subcontinent (NWIS) undergoes heavy and frequent dust storms in the spring and summer. These dust storms can travel all the way from the NWIS (which encompasses southeastern Afghanistan, Pakistan and northwestern India) to North India and the Arabian Sea, blocking sunlight and degrading air quality in their path.

In their previous paper in Nature Climate Change, the co-authors found a positive trend of Indian summer monsoon (ISM) rainfall during the past 15 years—a revival of a major monsoon system that had declined for decades—and they analyzed its causes. In this paper, they show that the ISM revival is expanding rainfall distribution further northwestward, a development that could bring more rainfall to the NWIS. This increased rainfall could, in turn, boost vegetation growth and reduce the abundance of dust in the region.

Using satellite and other observations, the researchers demonstrate that the increasing monsoon rainfall is causing wetter soil and more vegetated areas in the Thar Desert and surrounding arid regions in the NWIS, resulting in lower levels of soil/mineral dust emissions in the area. Projected changes in vegetation growth and dust abundance in the NWIS has important implications for regional agricultural productivity and air quality.

Achieving the Paris Agreement goals of climate stabilization requires a transformation of energy system over the upcoming decades. Russia, as a fossil fuel producer, will have to adjust its economy to reflect lower export earnings from oil, coal, and natural gas. Using a global energy-economic modeling framework, we will assess the impacts of energy transformation policies and the resulting global market dynamics on Russian economy, including the changes in its sectoral output, energy mix, and GDP.

Russia in the Post-Paris world: a new energy landscape

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