Brought to a Boil
The development of partisan polarization over the Green New Deal
Abel Gustafson et al.
Nature Climate Change, December 2019, Pages 940–944
In early 2019, a US climate change and economic renewal policy proposal called the Green New Deal (GND) rose from obscurity to national prominence in just four months. This situation created a natural field experiment in which to study the emergence of partisan polarization. Here, we report findings from two nationally representative surveys of registered US voters that measured familiarity with and support for the GND shortly before and after the issue entered the national spotlight. Initially, there was low public awareness of the GND but majority support for it across party lines. Four months later, voters had become much more familiar with the GND and partisan polarization had increased significantly due to a sharp decrease in support among Republicans. In fact, Republicans who had heard the most about the GND were the least likely to support it. In contrast, support for the GND remained high among Democrats, and did not vary substantially across degrees of familiarity. We also identify a likely mechanism: a ‘Fox News effect’. That is, among Republicans, Fox News viewing was a significant predictor of both familiarity with the GND and opposition to it, even when controlling for alternative explanations.
Temperature and mental health: Evidence from the spectrum of mental health outcomes
Jamie Mullins & Corey White
Journal of Health Economics, forthcoming
This paper characterizes the link between ambient temperatures and a broad set of mental health outcomes. We find that higher temperatures increase emergency department visits for mental illness, suicides, and self-reported days of poor mental health. Specifically, cold temperatures reduce negative mental health outcomes while hot temperatures increase them. Our estimates reveal no evidence of adaptation, instead the temperature relationship is stable across time, baseline climate, air conditioning penetration rates, accessibility of mental health services, and other factors. The character of the results suggests that temperature affects mental health very differently than physical health, and more similarly to other psychological and behavioral outcomes. We provide suggestive evidence for sleep disruption as an active mechanism behind our results and discuss the implications of our findings for the allocation of mental health services and in light of climate change.
Forecasted attribution of the human influence on Hurricane Florence
Kevin Reed et al.
Science Advances, January 2020
Changes in extreme weather, such as tropical cyclones, are one of the most serious ways society experiences the impact of climate change. Advance forecasted conditional attribution statements, using a numerical model, were made about the anthropogenic climate change influence on an individual tropical cyclone, Hurricane Florence. Mean total overland rainfall amounts associated with the forecasted storm’s core were increased by 4.9 ± 4.6% with local maximum amounts experiencing increases of 3.8 ± 5.7% due to climate change. A slight increase in the forecasted storm size of 1 to 2% was also attributed. This work reviews our forecasted attribution statement with the benefit of hindsight, demonstrating credibility of advance attribution statements for tropical cyclones.
Climate change now detectable from any single day of weather at global scale
Sebastian Sippel et al.
Nature Climate Change, January 2020, Pages 35–41
For generations, climate scientists have educated the public that ‘weather is not climate’, and climate change has been framed as the change in the distribution of weather that slowly emerges from large variability over decades. However, weather when considered globally is now in uncharted territory. Here we show that on the basis of a single day of globally observed temperature and moisture, we detect the fingerprint of externally driven climate change, and conclude that Earth as a whole is warming. Our detection approach invokes statistical learning and climate model simulations to encapsulate the relationship between spatial patterns of daily temperature and humidity, and key climate change metrics such as annual global mean temperature or Earth’s energy imbalance. Observations are projected onto this relationship to detect climate change. The fingerprint of climate change is detected from any single day in the observed global record since early 2012, and since 1999 on the basis of a year of data. Detection is robust even when ignoring the long-term global warming trend. This complements traditional climate change detection, but also opens broader perspectives for the communication of regional weather events, modifying the climate change narrative: while changes in weather locally are emerging over decades, global climate change is now detected instantaneously.
Climate variability reduces employment in New England fisheries
Proceedings of the National Academy of Sciences, 26 December 2019, Pages 26444-26449
Climate change is already affecting fish productivity and distributions worldwide, yet its impact on fishing labor has not been examined. Here I directly link large-scale climate variability with fishery employment by studying the effects of sea-surface pressure changes in the North Atlantic region, whose waters are among the world’s fastest warming. I find that climate shocks reduce not only regional catch and revenue in the New England fishing sector, but also ultimately county-level wages and employment among commercial harvesters. Each SD increase from the climatic mean decreases county-level fishing employment by 13%, on average. The South Atlantic region serves as a control due to its different ecological response to climate. Overall, I estimate that climate variability from 1996 to 2017 is responsible for a 16% (95% CI: 10% to 22%) decline in county-level fishing employment in New England, beyond the changes in employment attributable to management or other factors. This quantitative evidence linking climate variability and fishing labor has important implications for management in New England, which employs 20% of US commercial harvesters. Because the results are mediated by the local biology and institutions, they cannot be directly extrapolated to other regions. But they show that climate can impact fishing outcomes in ways unaccounted by management and offer a template for study of this relationship in fisheries around the world.
Rhetoric and Reality: Jobs and the Energy Provisions of the American Recovery and Reinvestment Act
Taekyoung Lim, Tatyana Guzman & William Bowen
Energy Policy, forthcoming
In February 2009, President Barack Obama signed into law the American Recovery and Reinvestment Act (ARRA), the largest single expenditure package in U.S. history. The ARRA was legislatively intended as a macroeconomic stimulus to temporarily revive the economy after the Great Recession of 2008. At a microeconomic level, much of the package took the form of grants intended to stimulate the country's energy economy. The purpose of the present research was to evaluate the effectiveness of these large-scale federally-funded-grants in terms of creating jobs related to the energy efficiency and renewable energy sectors throughout the country. The focus was specifically upon the grants implemented through the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). The results show that all else held equal, these ARRA expenditures were, by-in-large, successful at stimulating job creation in the relevant energy sectors.
Can a Growing World be Fed when the Climate is Changing?
Simon Dietz & Bruno Lanz
London School of Economics Working Paper, November 2019
We study the capacity to meet food demand under conditions of climate change, economic and population growth. We take a novel approach to quantifying climate impacts, based on a model of the global economy structurally estimated on the period 1960 to 2015. The model integrates several features necessary to study the problem, including an explicit agriculture sector, endogenous fertility, directed technical change and fossil/renewable energy. We estimate the world economy is more than one trillion dollars smaller, and world population more than 80 million smaller, than would have been the case without climate change. This is despite substantial adaptation having taken place in general equilibrium through R&D and agricultural land expansion. Policy experiments with the model suggest that optimal GHG taxes are high and future temperatures held well below 2°C.
Mass balance of the Greenland Ice Sheet from 1992 to 2018
Andrew Shepherd et al.
In recent decades, the Greenland Ice Sheet has been a major contributor to global sea-level rise, and it is expected to be so in the future. Although increases in glacier flow and surface melting have been driven by oceanic and atmospheric warming, the degree and trajectory of today’s imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet’s volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. Although the ice sheet was close to a state of balance in the 1990s, annual losses have risen since then, peaking at 335 ± 62 billion tonnes per year in 2011. In all, Greenland lost 3,800 ± 339 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.6 ± 0.9 millimetres. Using three regional climate models, we show that reduced surface mass balance has driven 1,971 ± 555 billion tonnes (52%) of the ice loss owing to increased meltwater runoff. The remaining 1,827 ± 538 billion tonnes (48%) of ice loss was due to increased glacier discharge, which rose from 41 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. Between 2013 and 2017, the total rate of ice loss slowed to 217 ± 32 billion tonnes per year, on average, as atmospheric circulation favoured cooler conditions and as ocean temperatures fell at the terminus of Jakobshavn Isbræ. Cumulative ice losses from Greenland as a whole have been close to the IPCC’s predicted rates for their high-end climate warming scenario, which forecast an additional 50 to 120 millimetres of global sea-level rise by 2100 when compared to their central estimate.
Satellite observations reveal extreme methane leakage from a natural gas well blowout
Sudhanshu Pandey et al.
Proceedings of the National Academy of Sciences, 26 December 2019, Pages 26376-26381
Methane emissions due to accidents in the oil and natural gas sector are very challenging to monitor, and hence are seldom considered in emission inventories and reporting. One of the main reasons is the lack of measurements during such events. Here we report the detection of large methane emissions from a gas well blowout in Ohio during February to March 2018 in the total column methane measurements from the spaceborne Tropospheric Monitoring Instrument (TROPOMI). From these data, we derive a methane emission rate of 120 ± 32 metric tons per hour. This hourly emission rate is twice that of the widely reported Aliso Canyon event in California in 2015. Assuming the detected emission represents the average rate for the 20-d blowout period, we find the total methane emission from the well blowout is comparable to one-quarter of the entire state of Ohio’s reported annual oil and natural gas methane emission, or, alternatively, a substantial fraction of the annual anthropogenic methane emissions from several European countries. Our work demonstrates the strength and effectiveness of routine satellite measurements in detecting and quantifying greenhouse gas emission from unpredictable events. In this specific case, the magnitude of a relatively unknown yet extremely large accidental leakage was revealed using measurements of TROPOMI in its routine global survey, providing quantitative assessment of associated methane emissions.