Observations show that the 50-year drying trend (weakening of India summer monsoon) in north central India reversed in the past decade. The finding indicates improved water security and reduced socioeconomic impacts for the region in coming decades.

Background: The Indian summer monsoon (ISM) delivers about 80% of the Indian subcontinent’s annual precipitation and thus impacts the livelihood of more than 1/5 of the world’s population. The timing (typically June – September) and location of the ISM has far-reaching impacts—including floods and droughts—on farming and many other economic activities, and on the availability of water for people and livestock. These factors are of particular concern for north central India, which experienced a significant reduction in summer monsoon rainfall in the second half of the 20th century, resulting in degraded water security and widespread socioeconomic impacts.

Main point: Based on global climate models and multiple hypotheses, scientists expected this drying trend to continue unabated into the 21st century, but a new study in Nature Climate Change shows that the trend has reversed.

Findings: Using data obtained from ground-based and satellite measurements, researchers at the MIT Joint Program on the Science and Policy of Global Change find that since 2002, monsoon rainfall has increased in north central India at a rate of 1.34 millimeters per day per decade. They ascribe the revival of ISM precipitation to a combination of stronger warming over the Indian continent and slower rates of warming over the Indian Ocean. Today’s global climate models—and several hypotheses that have been proposed to explain the long-lasting drying trend in the second half of the 20th century—fail to capture the observed rainfall revival and corresponding trends in the underlying land-ocean temperature differences. In addition, the researchers find that this trend reversal of the Indian summer monsoon  significantly mismatches the overall behavior of Northern Hemispheric monsoonal systems, raising the question of whether conditions unique to India, such as high concentrations of anthropogenic aerosols, are causing this phenomenon.

Significance: Prediction of long-term monsoonal rainfall variations is critical to securing water supplies and planning agricultural and other economic activities in monsoonal regions. Enhanced knowledge about such variations can also help scientists to improve current Earth-system models to more accurately project future climate change.

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling (IGSM) framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socio-economic changes on water availability for irrigation in the US as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socio-economic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e. cotton and forage), or in specific regions (i.e the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of US irrigated areas, the overall reduction in US crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO2 fertilization effect compared to an unconstrained GHG emission scenario.

Sustaining rapid economic growth and satisfying increasing energy demand while limiting greenhouse gas (GHG) emissions is a central challenge in India. Proposed policy solutions should be evaluated according to their impacts on the energy system and the economy to identify efficient policies. I have developed an energy-economic model for India that provides a comprehensive foundation for analyzing energy technologies and policies. This novel model based on a general equilibrium approach simulates the Indian economy, with detailed inter-sectoral linkages, and facilitates an understanding of economy-wide impacts of policies. The model allows for analysis of tradeoffs among different technology and policy choices in terms of their costs and efficiency in GHG emissions reduction.

While comprehensive carbon pricing is arguably the most economically efficient measure for emissions reduction, political considerations often favor technology-specific choices. Support for renewable energy factors prominently in India’s climate change mitigation strategy. To study the impact of policies that promote renewable energy, the model represents renewable electricity in detail. Impact of incentives and scale factors are also incorporated in projecting renewables expansion. I simulate India’s Nationally Determined Contributions (NDCs) to the Paris Agreement and compare their effectiveness, benchmarking them against the theoretical least-cost alternative of broad-based carbon pricing. Specifically, India’s NDCs include targets on non-fossil electricity capacity expansion and CO₂ emissions intensity of GDP (GoI 2015a). This work provides valuable quantitative insights on the impact of these policy measures, and fills a critical knowledge gap in the design and implementation of effective climate policies in India.

My findings suggest that compared to a reference case of no policy constraint, the average cost of reducing a tonne of CO₂ is lowest in a scenario with an emissions intensity target implemented via CO₂ pricing, and more than 43 times higher in the pure non-fossil electricity target scenaio. Further, emissions intensity targets result in a 6.3% drop in total electricity demand, as the cost of fossil fuel based electricity increases. As CO₂ emitting electricity sources become more expensive, non-fossil sources - particularly solar and wind - increase in the mix. Enforcing non-fossil electricity capacity targets leads to an additional 15.6% drop in total electricity demand as average electricity prices increase to account for a higher share of costlier non-fossil electricity. Non-fossil electricity capacity targets also result in leakage of emissions to non-electricty energy sectors. The magnitude of differences among these results depends on wind and solar electricity costs. Cheaper costs of wind and solar power lead to lower welfare losses and electricity demand levels that are comparable across scenarios.