Political Heat
Electoral Backlash or Positive Reinforcement? Wind Power and Congressional Elections in the United States
Johannes Urpelainen & Alice Tianbo Zhang
Journal of Politics, forthcoming
Abstract:
Divisive facilities, such as wind turbines, are important for society but controversial because they often carry local costs. Elections are the most important means for citizens to express their views about divisive facilities, but the political science literature on the topic has little to say about their electoral effects. To fill the gap, we examine wind turbine construction in the United States between 2003 and 2012. An instrumental variable analysis shows that wind turbine construction generated large electoral benefits for (pro-renewables) Democratic candidates: every megawatt of additional wind power capacity over statewide trend increased the Democratic vote share in U.S. House elections by 0.03 percentage points. This electoral shift has contributed to a pro-environmental shift in congressional roll call voting on the environment. While the result is inconsistent with naive models of retrospective voting, it accords with positive reinforcement theories on how policies endogenously create their political support.
Investor Rewards to Climate Responsibility: Stock-Price Responses to the Opposite Shocks of the 2016 and 2020 U.S. Elections
Stefano Ramelli et al.
Review of Corporate Finance Studies, December 2021, Pages 748–787
Abstract:
Donald Trump’s 2016 election and his nomination of climate skeptic Scott Pruitt to head the Environmental Protection Agency drastically downshifted expectations about U.S. policy toward climate change. Joseph Biden’s 2020 election shifted them dramatically upward. We study firms’ stock-price movements in reaction to these changes. As expected, the 2016 election boosted carbon-intensive firms. Surprisingly, firms with climate-responsible strategies also gained, especially those firms held by long-run investors. Such investors appear to have bet on a “boomerang” in climate policy. Harbingers of a boomerang appeared during Trump’s term. The 2020 election marked its arrival.
Seawalls and Stilts: A Quantitative Macro Study of Climate Adaptation
Stephie Fried
Review of Economic Studies, forthcoming
Abstract:
Can we reduce the damage from climate change by investing in seawalls, stilts, or other forms of adaptation? Focusing on the case of severe storms in the US, I develop a macro heterogeneous-agent model to quantify the interactions between adaptation, federal disaster policy, and climate change. The model departs from the standard climate damage function and incorporates the damage from storms as the realization of idiosyncratic shocks. Using the calibrated model, I infer that adaptation capital comprises approximately one percent of the US capital stock. I find that while the moral hazard effects from disaster aid reduce adaptation in the US economy, federal subsidies for investment in adaptation more than correct for the moral hazard. I introduce climate change into the model as a permanent increase in either or both the severity or probability of storms. Adaptation reduces the damage from this climate change by approximately one third. Finally, I show that modeling the idiosyncratic risk component of climate damage has quantitatively important implications for adaptation and for the welfare cost of climate change.
The effect of rainfall changes on economic production
Maximilian Kotz, Anders Levermann & Leonie Wenz
Nature, 13 January 2022, Pages 223–227
Abstract:
Macro-economic assessments of climate impacts lack an analysis of the distribution of daily rainfall, which can resolve both complex societal impact channels and anthropogenically forced changes. Here, using a global panel of subnational economic output for 1,554 regions worldwide over the past 40 years, we show that economic growth rates are reduced by increases in the number of wet days and in extreme daily rainfall, in addition to responding nonlinearly to the total annual and to the standardized monthly deviations of rainfall. Furthermore, high-income nations and the services and manufacturing sectors are most strongly hindered by both measures of daily rainfall, complementing previous work that emphasized the beneficial effects of additional total annual rainfall in low-income, agriculturally dependent economies. By assessing the distribution of rainfall at multiple timescales and the effects on different sectors, we uncover channels through which climatic conditions can affect the economy. These results suggest that anthropogenic intensification of daily rainfall extremes will have negative global economic consequences that require further assessment by those who wish to evaluate the costs of anthropogenic climate change.
Pricing indirect emissions accelerates low-carbon transition of US light vehicle sector
Paul Wolfram et al.
Nature Communications, December 2021
Abstract:
Large–scale electric vehicle adoption can greatly reduce emissions from vehicle tailpipes. However, analysts have cautioned that it can come with increased indirect emissions from electricity and battery production that are not commonly regulated by transport policies. We combine integrated energy modeling and life cycle assessment to compare optimal policy scenarios that price emissions at the tailpipe only, versus both tailpipe and indirect emissions. Surprisingly, scenarios that also price indirect emissions exhibit higher, rather than reduced, sales of electric vehicles, while yielding lower cumulative tailpipe and indirect emissions. Expected technological change ensures that emissions from electricity and battery production are more than offset by reduced emissions of gasoline production. Given continued decarbonization of electricity supply, results show that a large–scale adoption of electric vehicles is able to reduce CO2 emissions through more channels than previously expected. Further, carbon pricing of stationary sources will also favor electric vehicles.
Who are the 3 Per Cent? The Connections Among Climate Change Contrarians
Laura Young & Erin Fitz
British Journal of Political Science, forthcoming
Abstract:
Despite 97 per cent of scientists agreeing on anthropogenic global warming, the remaining 3 per cent play a critical role in keeping the debate about climate consensus alive. Analysis of climate change contrarians from multi-signatory documents reveals 3 per cent of signees to be climate experts, while the remaining 97 per cent do not meet expert criteria and are also involved with organizations and industries who make up the climate change countermovement. The data also reveal most contrarians to be aged sixty-five or older. As a result, we explore other factors (for example, collective memories and ideological views) that may have also contributed to expert and non-expert views.
Inequitable patterns of US flood risk in the Anthropocene
Oliver Wing et al.
Nature Climate Change, forthcoming
Abstract:
Current flood risk mapping, relying on historical observations, fails to account for increasing threat under climate change. Incorporating recent developments in inundation modelling, here we show a 26.4% (24.1–29.1%) increase in US flood risk by 2050 due to climate change alone under RCP4.5. Our national depiction of comprehensive and high-resolution flood risk estimates in the United States indicates current average annual losses of US$32.1 billion (US$30.5–33.8 billion) in 2020’s climate, which are borne disproportionately by poorer communities with a proportionally larger White population. The future increase in risk will disproportionately impact Black communities, while remaining concentrated on the Atlantic and Gulf coasts. Furthermore, projected population change (SSP2) could cause flood risk increases that outweigh the impact of climate change fourfold. These results make clear the need for adaptation to flood and emergent climate risks in the United States, with mitigation required to prevent the acceleration of these risks.
Six-fold increase in historical Northern Hemisphere concurrent large heatwaves driven by warming and changing atmospheric circulations
Cassandra Rogers et al.
Journal of Climate, February 2022, Pages 1063–1078
Abstract:
Simultaneous heatwaves affecting multiple regions (referred to as concurrent heatwaves), pose compounding threats to various natural and societal systems, including global food chains, emergency response systems, and reinsurance industries. While anthropogenic climate change is increasing heatwave risks across most regions, the interactions between warming and circulation changes that yield concurrent heatwaves remain understudied. Here, we quantify historical (1979-2019) trends in concurrent heatwaves during the warm-season (May-September, MJJAS) across the Northern Hemisphere mid- to high-latitudes. We find a significant increase of ~46% in the mean spatial extent of concurrent heatwaves, ~17% increase in their maximum intensity, and ~6-fold increase in their frequency. Using Self-Organising Maps, we identify large-scale circulation patterns (300 hPa) associated with specific concurrent heatwave configurations across Northern Hemisphere regions. We show that observed changes in the frequency of specific circulation patterns preferentially increase the risk of concurrent heatwaves across particular regions. Patterns linking concurrent heatwaves across eastern North America, eastern and northern Europe, parts of Asia, and the Barents and Kara Seas, show the largest increases in frequency (~5.9 additional days per decade). We also quantify the relative contributions of circulation pattern changes and warming to overall observed concurrent heatwave day frequency trends. While warming has a predominant and positive influence on increasing concurrent heatwaves, circulation pattern changes have a varying influence and account for up to 0.8 additional concurrent heatwave days per decade. Identifying regions with an elevated risk of concurrent heatwaves and understanding their drivers is indispensable for evaluating projected climate risks on interconnected societal systems and fostering regional preparedness in a changing climate.
Will Anthropogenic Warming Increase Evapotranspiration? Examining Irrigation Water Demand Implications of Climate Change in California
Pouya Vahmani, Andrew Jones & Dan Li
Earth's Future, January 2022
Abstract:
Climate modeling studies and observations do not fully agree on the implications of anthropogenic warming for evapotranspiration (ET), a major component of the water cycle and driver of irrigation water demand. Here we use California as a testbed to assess the ET impacts of changing atmospheric conditions induced by climate change on irrigated systems. Our analysis of irrigated agricultural and urban regions shows that warmer atmospheric temperatures have minimal implications for ET rates and irrigation water demands−about one percent change per degree Celsius warming (∼1 %°C-1). By explicitly modeling irrigation, we control for the confounding effect of climate-driven soil moisture changes and directly estimate water demand implications. Our attribution analysis of the drivers of ET response to global anthropogenic warming shows that as the atmospheric temperature and vapor pressure deficit depart from the ideal conditions for transpiration, regulation of stomata resistance by stressed vegetation almost completely offsets the expected increase in ET rates that would otherwise result from abiotic processes alone. We further show that anthropogenic warming of the atmosphere has minimal implications for mean relative humidity (<1.7%°C-1) and the surface available energy (<0.2%°C-1), which are critical drivers of ET. This study corroborates the growing evidence that plant physiological changes moderate the degree to which changes in potential ET are realized as actual ET.
Enhanced winter, spring, and summer hydroclimate variability across California from 1940 to 2019
Diana Zamora-Reyes, Bryan Black & Valérie Trouet
International Journal of Climatology, forthcoming
Abstract:
California’s recent hydroclimatic pivots have caused billions of dollars in damages with the potential to become more extreme in the future, even if the mean total precipitation and streamflow do not change. In this study, we compile instrumental precipitation and streamflow records across California to quantify trends in hydroclimatic variability across spatial, temporal, and seasonal domains. We use the 10th and 90th percentiles of the distribution to examine whether any trends in variability are driven primarily by extreme low or high rainfall or streamflow events. Our analysis shows that there is a statistically significant positive trend in precipitation variability that is driven by long-term increases to the 90th percentile through most of California during winter (January–March), which has been steadily increasing since the mid-20th century. In contrast, significant positive streamflow trends are seen in winter, spring (April–June), and summer (July–September) and are driven by changes to both the 10th and 90th percentiles. Moreover, we found that there is a decreasing trend in fall (October–December) hydroclimatic variability, particularly over central California, that is related to declining values in the 90th percentile in both precipitation and streamflow. Our results suggest that California’s hydroclimate has been under a continually heightened state of volatility, leaving the state vulnerable to hydroclimatic extremes and elevated risk of associated compound events (floods, landslides, fires). Thus, water resources managers will need to incorporate this increased volatility into their planning for public and agricultural water supply, while being aware of the higher risks for wildfires and floods as well as the disproportionate and lasting impact on vulnerable ecosystem structures.
Investigating climate tipping points under various emission reduction and carbon capture scenarios with a stochastic climate model
Alexander Mendez & Mohammad Farazmand
Proceedings of the Royal Society: Mathematical, Physical and Engineering Sciences, December 2021
Abstract:
We study the mitigation of climate tipping point transitions using an energy balance model. The evolution of the global mean surface temperature is coupled with the CO2 concentration through the green-house effect. We model the CO2 concentration with a stochastic delay differential equation (SDDE), accounting for various carbon emission and capture scenarios. The resulting coupled system of SDDEs exhibits a tipping point phenomena: if CO2 concentration exceeds a critical threshold (around 478 ppm), the temperature experiences an abrupt increase of about six degrees Celsius. We show that the CO2 concentration exhibits a transient growth which may cause a climate tipping point, even if the concentration decays asymptotically. We derive a rigorous upper bound for the CO2 evolution which quantifies its transient and asymptotic growths, and provides sufficient conditions for evading the climate tipping point. Combining this upper bound with Monte Carlo simulations of the stochastic climate model, we investigate the emission reduction and carbon capture scenarios that would avert the tipping point.