Earth Systems

Seasonal resource conditions favor a summertime increase in North Pacific diatom–diazotroph associations

In the North Pacific Subtropical Gyre (NPSG), an annual pulse of sinking organic carbon is observed at 4000 m between July and August, driven by large diatoms found in association with nitrogen fixing, heterocystous, cyanobacteria: Diatom–Diazotroph Associations (DDAs). Here we ask what drives the bloom of DDAs and present a simplified trait-based model of subtropical phototroph populations driven by observed, monthly averaged, environmental characteristics. The ratio of resource supply rates favors nitrogen fixation year round. The relative fitness of DDA traits is most competitive in early summer when the mixed layer is shallow, solar irradiance is high, and phosphorus and iron are relatively abundant. Later in the season, as light intensity drops and phosphorus is depleted, the traits of small unicellular diazotrophs become more competitive. The competitive transition happens in August, at the time when the DDA export event occurs. This seasonal dynamic is maintained when embedded in a more complex, global-scale, ecological model, and provides predictions for the extent of the North Pacific DDA bloom. The model provides a parsimonious and testable hypothesis for the stimulation of DDA blooms.

Description and Evaluation of the MIT Earth System Model (MESM)

The future of the Earth’s energy, water and land resources will depend, in part, on how the climate will change in coming decades. To generate meaningful projections of global climate change, one must take into account two major sources of uncertainty—first, in the level of external forcings to the climate system; and second, in the magnitude of the climate system’s response to those forcings. The MIT Earth System Model (MESM) provides the flexibility and computational speed required to analyze/account for climate system uncertainty while also representing the detailed physics, chemistry and biology that’s typical of more computationally intensive Earth system models—all at significantly less cost. 

The computational efficiency of this model allows researchers to run large ensembles of simulations for robust uncertainty quantification within a short time frame. The MESM thus provides an effective tool for modeling the climate system and quantifying uncertainty of its response to external forcings. MESM simulations can be used as a basis for climate risk assessment to energy, water and land resources.

Recently upgraded, the MESM consists of three main components—land, ocean and atmosphere—and represents the processes that shape each component’s evolution and the interactions among these components, essentially serving as an Earth simulator. Despite simplifications made in the model to make it faster and cheaper to run, such as a zonally averaged atmospheric sub-model, the MESM shows generally comparable results to those of more complex models. Comparing the performance of the MESM with that of more computationally intensive Earth system models, researchers at the MIT Joint Program on the Science and Policy of Global Change and collaborating institutions show that the MESM effectively simulates changes in the observed climate system since the mid-19th century as well as the main features of the present-day climate system. In simulations of the impact of varying levels of external forcings on the climate system, the MESM’s results also compares favorably with those produced by more computationally intensive models.

On the representation of aerosol activation and its influence on model-derived estimates of the aerosol indirect effect

Particles matter, especially when airborne. Whether emitted from artificial sources such as power plants and internal combustion engines, or natural sources such as volcanic eruptions, airborne particulates or aerosols not only impact human health but also the global climate. The more particles emitted into the atmosphere, the more water droplets are likely to form around those particles inside clouds. Clouds with more droplets are thicker and brighter, so they reflect more solar radiation, thereby cooling the climate system in a process called the aerosol indirect effect. While much is known about the physics of how aerosols impact cloud formation, it’s hard to measure just how big a role the indirect effect plays in offsetting global warming. Today’s estimates of the magnitude of the indirect effect are highly uncertain; it may well have masked as much as 80 percent of warming during the 20th century due to carbon dioxide (CO2) emissions alone.

Lowering that uncertainty will become critical throughout this century if more and more countries significantly reduce their greenhouse gas (GHG) emissions in pursuit of the Paris Agreement’s goal of keeping the rise in global mean surface temperature since preindustrial times to well below 2 degrees Celsius. Any major cut in airborne particulates will reduce the indirect cooling effect considerably, resulting in additional warming that climate models will need to estimate as precisely as possible.

To help meet this challenge, Daniel Rothenberg, who until recently served as a research assistant at the MIT Joint Program on the Science and Policy of Global Change and a PhD student and postdoctoral fellow in the Department of Earth, Atmospheric and Planetary Sciences, has developed concepts and software aimed at reducing the uncertainty in the magnitude of the indirect effect.

Key to achieving this goal is to more precisely represent aerosol activation, the process by which aerosols form water droplets in clouds, in climate models. During this process, individual aerosol particles becomes cloud droplets, the building blocks out of which clouds are formed. Just as dew condenses on grass and leaves on a cold morning, water vapor in the atmosphere condenses onto airborne particulates. Now, in a new study in the journal Atmospheric Chemistry and Physics, Rothenberg—in collaboration with his PhD advisor, Joint Program Senior Research Scientist Chien Wang, and Alexander Avramov of Emory University (a former postdoctoral associate at the MIT Center for Global Change Science)—advances a method that represents aerosol activation with far greater accuracy and computational efficiency than existing approaches.  

Maximizing ozone signals among chemical, meteorological, and climatological variability

The ability to separate out a distinct signal from ambient noise in reams of scientific data is critical to detecting a meaningful trend or turning point in the data. That’s especially true when it comes to identifying signals of improving or declining air quality trends, whose magnitude can be smaller than that of underlying natural variations or cycles in chemical, meteorological and climatological conditions. This discrepancy makes it challenging to track how concentrations of surface air pollutants such as ozone change as a result of policies or other causes within a particular geographical region or timeframe.

A case in point is any attempt to estimate whether there has been any change in summertime mean ozone concentration over the Northeastern U.S., which can vary from place to place as well as from year to year. To obtain a reliable estimate in the most computationally efficient manner, one would need to know the minimum geographical area required to capture the full range of localized ozone concentrations, as well as the minimum number of years to sample to rule out short-term natural variability of atmospheric conditions—such as an abnormally hot summer or El Niño year—that may skew the numbers.

Now a team of researchers from the MIT Joint Program on the Science and Policy of Global Change and collaborating institutions has developed a method to optimize air quality signal detection capability over much of the continental U.S. by applying a strategic combination of spatial and temporal averaging scales. Presented in a study in the journal Atmospheric Chemistry and Physics, the method could improve researchers’ and policymakers’ understanding of air quality trends and their ability to evaluate the efficacy of existing and proposed emissions-reduction policies.

Even “modest” action to limit climate change could help prevent the most extreme water-shortage scenarios facing Asia by the year 2050, according to a new study led by MIT researchers.

The study takes an inventive approach to modeling the effects of both climate change and economic growth on the world’s most heavily populated continent. Roughly 60 percent of the global population lives in Asia, often with limited access to water: There is less than half the amount of freshwater available per inhabitant in Asia, compared to the global average.

Study: Climate action can limit Asia’s growing water shortages

The ability to separate out a distinct signal from ambient noise in reams of scientific data is critical to detecting a meaningful trend or turning point in the data. That’s especially true when it comes to identifying signals of improving or declining air quality trends, whose magnitude can be smaller than that of underlying natural variations or cycles in chemical, meteorological and climatological conditions.

Tracking air quality changes across space and time

Particles matter, especially when airborne. Whether emitted from artificial sources such as power plants and internal combustion engines, or natural sources such as volcanic eruptions, airborne particulates or aerosols not only impact human health but also the global climate. The more particles emitted into the atmosphere, the more water droplets are likely to form around those particles inside clouds. Clouds with more droplets are thicker and brighter, so they reflect more solar radiation, thereby cooling the climate system in a process called the aerosol indirect effect.

Targeting one of climate modeling’s biggest uncertainties
The Impact of Climate Change Policy on the Risk of Water Stress in Southern and Eastern Asia

In March 2016 a team of MIT Joint Program researchers published a study in PLOS One that found a high risk of severe water stress in Asia by 2050. An MIT News article on that study led to several stories in media outlets, from CNBC to Voice of America. Since that study was published, the same research team has been working to assess the extent to which climate mitigation and adaptation practices could reduce the future risk of water stress in a region that’s home to 60 percent of the world’s population. Reducing that risk could both save lives and help ensure sustainable growth in the area.

In a paper accepted by Environmental Research Letters, the team focused on the impact of climate change on the risk of water stress in Southern and Eastern Asia (SEA) by midcentury, and how climate mitigation could lower that risk.

Using models that link climate, hydrology, socio-economics and water management, they produced large ensemble projections of future water supplies and use in response to scenarios of climate change and socioeconomic growth by midcentury. These large ensembles were needed in order to capture all plausible outcomes in the regional and global patterns of future climate and socio-economic change. The researchers examined the most likely outcomes of these projections as well as what could occur at the extremes (low-probability cases). They found that while population and economic growth contributes to increased risk of water stress (water-use near or exceeding supply) across the region, unconstrained climate change enhances that risk in China and reduces it in India. They also noted that in the most extreme cases, climate change results in a severe increase in water stress in both nations, where annual freshwater use would routinely exceed supply.   

To evaluate the potential benefit of climate mitigation on water-stress risk throughout the SEA region, the research team considered a large-ensemble scenario under a modest reduction in greenhouse gas emissions (comparable to the current COP21 international agreement). They found that the avoided climate changes eliminate the likelihood of the extreme outcomes described above. Furthermore, the researchers projected that the policy would reduce the additional population (since the year 2000) in the SEA region under threat of facing at least heavily water-stressed conditions from climate change and socioeconomic growth from 200 million to 140 million—a 30-percent decrease.  

Yet even with mitigation, the researchers estimated that there’s a 50 percent chance that 100 million people across the SEA region will experience a 50 percent increase in water stress and a 10 percent chance they will experience a doubling of water stress by 2050. The team maintained that to address these unavoidable risks, SEA nations will ultimately need to implement widespread adaptive measures. And that will be the subject of the researchers’ next study.

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