Observational constraints on the effective climate sensitivity from the historical period

The observed warming in the atmosphere and ocean can be used to estimate the climate sensitivity linked to present-day feedbacks, which is referred to as the effective climate sensitivity (Shist ). However, such an estimate is affected by uncertainty in the radiative forcing, particularly aerosols, over the historical period. Here, we make use of detection and attribution techniques to derive the surface air temperature and ocean warming that can be attributed directly to greenhouse gas increases. These serve as inputs to a simple energy budget to infer the likelihood of Shist in response to observed greenhouse gases increases over two time periods (1862–2012 and 1955–2012). The benefit of using greenhouse gas attributable quantities is that they are not subject to uncertainties in the aerosol forcing (other than uncertainty in the attribution to greenhouse gas versus aerosol forcing not captured by the multi-model aerosol response pattern). The resulting effective climate sensitivity estimate, Shist , ranges from 1.3 °C to 3.1 °C (5%–95% range) over the full instrumental period (1862–2012) for our best estimate, and gets slightly wider when considering further uncertainties. This estimate increases to 1.7 °C–4.6 °C if using the shorter period (1955–2012). We also evaluate the climate model simulated surface air temperature and ocean heat content increase in response to greenhouse gas forcing over the same periods, and compare them with the observationally-constrained values. We find that that the ocean warming simulated in greenhouse gas only simulations in models considered here is consistent with that attributed to greenhouse gas increases from observations, while one model simulates more greenhouse gas-induced surface air warming than observed. However, other models with sensitivity outside our range show greenhouse gas warming that is consistent with that attributed in observations, emphasising that feedbacks during the historical period may differ from the feedbacks at CO2 doubling and from those at true equilibrium

Robust increase in population exposure to heat stress with increasing global warming

This is the final version. Available on open access from IOP Publishing via the DOI in this recordData availability statement: No new data were created or analysed in this study.Extreme heat, particularly if combined with humidity, poses a severe risk to human health. To estimate future global risk of extreme heat with humidity on health, we calculate indicators of heat stress that have been commonly used: The Heat Index, the Wet-Bulb Globe Temperature and the Wet-Bulb Temperature, from the latest Climate Model Intercomparison Project (CMIP6) projections. We analyse how and where different levels of heat stress hazards will change, from severe to deadly, and how results are sensitive to the choice of the index used. We evaluate this risk at country-level and use population and GDP | PPP growth scenario to estimate the vulnerability of each nation. Consistent with previous studies, we find that South and East Asia, and the Middle-East, are highly exposed to heat stress hazards, and that this exposure increases by 20%-60% with global mean temperature change from 1.5 to 3 âC. However, we also find substantial increases in heat health risk for some vulnerable countries with less adaptive capacity, such as West Africa, and Central and South America. For these regions, about 20 to more than 50% of the population could be exposed to severe heat stress each year on average, independent of the index used. For global warming of 3â, European countries and the USA will also be exposed several times per year to conditions with daily mean heat stress level equal to the maximum heat stress of the 2003 heat wave.Natural Environment Research Council (NERC

Factors Contributing to Record-Breaking Heat Waves over the Great Plains during the 1930s Dust Bowl

Record-breaking summer heat waves were experienced across the contiguous United States during the decade-long “Dust Bowl” drought in the 1930s. Using high-quality daily temperature observations, the Dust Bowl heat wave characteristics are assessed with metrics that describe variations in heat wave activity and intensity. Despite the sparser station coverage in the early record, there is robust evidence for the emergence of exceptional heat waves across the central Great Plains, the most extreme of which were preconditioned by anomalously dry springs. This is consistent with the entire twentieth-century record: summer heat waves over the Great Plains develop on average ~15–20 days earlier after anomalously dry springs, compared to summers following wet springs. Heat waves following dry springs are also significantly longer and hotter, indicative of the importance of land surface feedbacks in heat wave intensification. A distinctive anomalous continental-wide circulation pattern accompanied exceptional heat waves in the Great Plains, including those of the Dust Bowl decade. An anomalous broad surface pressure ridge straddling an upper-level blocking anticyclone over the western United States forced substantial subsidence and adiabatic warming over the Great Plains, and triggered anomalous southward warm advection over southern regions. This prolonged and amplified the heat waves over the central United States, which in turn gradually spread westward following heat wave emergence. The results imply that exceptional heat waves are preconditioned, triggered, and strengthened across the Great Plains through a combination of spring drought, upper-level continental-wide anticyclonic flow, and warm advection from the north

The 2021 western North America heat wave among the most extreme events ever recorded globally

This is the final version. Available on open access from the American Association for the Advancement of Science via the DOI in this recordData and materials availability: ERA5 dataset is available from the Copernicus Climate Change Service (C3S) Climate Data Store. JRA55 dataset is available from the JRA project webpage. CanESM5 data are available from CMIP6 search interface, https://esgf-node.llnl.gov/search/cmip6/. GHCNd station data are available from NOAA Climate Data Online. The code used to generate the figures in this paper and the Supplementary Materials is available from https://zenodo.org/record/6325508 or https://github.com/BrisClim, and this can be used to rapidly assess the extremeness of heat waves relative to other events globally. All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.In June 2021, western North America experienced a record-breaking heat wave outside the distribution of previously observed temperatures. While it is clear that the event was extreme, it is not obvious whether other areas in the world have also experienced events so far outside their natural variability. Using a novel assessment of heat extremes, we investigate how extreme this event was in the global context. Characterizing the relative intensity of an event as the number of standard deviations from the mean, the western North America heat wave is remarkable, coming in at over four standard deviations. Throughout the globe, where we have reliable data, only five other heat waves were found to be more extreme since 1960. We find that in both reanalyses and climate projections, the statistical distribution of extremes increases through time, in line with the distribution mean shift due to climate change. Regions that, by chance, have not had a recent extreme heat wave may be less prepared for potentially imminent events.Natural Environment Research Council (NERC

Systematic change in global patterns of streamflow following volcanic eruptions

Following large explosive volcanic eruptions precipitation decreases over much of the globe1–6, particularly in climatologically wet regions4,5. Stratospheric volcanic aerosols reflect sunlight, which reduces evaporation, whilst surface cooling stabilises the atmosphere and reduces its water-holding capacity7. Circulation changes modulate this global precipitation reduction on regional scales1,8–10. Despite the importance of rivers to people, it has been unclear whether volcanism causes detectable changes in streamflow given large natural variability. Here we analyse observational records of streamflow volume for fifty large rivers from around the world which cover between two and 6 major volcanic eruptions in the 20(th) and late 19(th) century. We find statistically significant reductions in flow following eruptions for the Amazon, Congo, Nile, Orange, Ob, Yenisey and Kolyma amongst others. When data from neighbouring rivers are combined - based on the areas where climate models simulate either an increase or a decrease in precipitation following eruptions – a significant (p<0.1) decrease in streamflow following eruptions is detected in northern South American, central African and high-latitude Asian rivers, and on average across wet tropical and subtropical regions. We also detect a significant increase in southern South American and SW North American rivers. This suggests that future volcanic eruptions could substantially affect global water availability

Detection and attribution of human influence on regional precipitation

Understanding how human influence on climate is affecting precipitation around the world is immensely important for defining mitigation policies, and for adaptation planning. Yet despite increasing evidence for the influence of climate change on global patterns of precipitation, and expectations that significant changes in regional precipitation should have already occurred as a result of human influence on climate, compelling evidence of anthropogenic fingerprints on regional precipitation is obscured by observational and modelling uncertainties and is likely to remain so using current methods for years to come. This is in spite of substantial ongoing improvements in models, new reanalyses and a satellite record that spans over thirty years. If we are to quantify how human-induced climate change is affecting the regional water cycle, we need to consider novel ways of identifying the effects of natural and anthropogenic influences on precipitation that take full advantage of our physical expectations

Possible causes of data model discrepancy in the temperature history of the last Millennium

Model simulations and proxy-based reconstructions are the main tools for quantifying pre-instrumental climate variations. For some metrics such as Northern Hemisphere mean temperatures, there is remarkable agreement between models and reconstructions. For other diagnostics, such as the regional response to volcanic eruptions, or hemispheric temperature differences, substantial disagreements between data and models have been reported. Here, we assess the potential sources of these discrepancies by comparing 1000-year hemispheric temperature reconstructions based on real-world paleoclimate proxies with climate-model-based pseudoproxies. These pseudoproxy experiments (PPE) indicate that noise inherent in proxy records and the unequal spatial distribution of proxy data are the key factors in explaining the data-model differences. For example, lower inter-hemispheric correlations in reconstructions can be fully accounted for by these factors in the PPE. Noise and data sampling also partly explain the reduced amplitude of the response to external forcing in reconstructions compared to models. For other metrics, such as inter-hemispheric differences, some, although reduced, discrepancy remains. Our results suggest that improving proxy data quality and spatial coverage is the key factor to increase the quality of future climate reconstructions, while the total number of proxy records and reconstruction methodology play a smaller role

Large differences in regional precipitation change between a first and second 2 K of global warming

For adaptation and mitigation planning, stakeholders need reliable information about regional precipitation changes under different emissions scenarios and for different time periods. A significant amount of current planning effort assumes that each K of global warming produces roughly the same regional climate change. Here using 25 climate models, we compare precipitation responses with three 2 K intervals of global ensemble mean warming: a fast and a slower route to a first 2 K above pre-industrial levels, and the end-of-century difference between high-emission and mitigation scenarios. We show that, although the two routes to a first 2 K give very similar precipitation changes, a second 2 K produces quite a different response. In particular, the balance of physical mechanisms responsible for climate model uncertainty is different for a first and a second 2 K of warming. The results are consistent with a significant influence from nonlinear physical mechanisms, but aerosol and land-use effects may be important regionally

Climate Policy Under Fat-Tailed Risk: An Application of Dice

Uncertainty plays a significant role in evaluating climate policy, and fat-tailed uncertainty may dominate policy advice. Should we make our utmost effort to prevent the arbitrarily large impacts of climate change under deep uncertainty? In order to answer to this question, we propose a new way of investigating the impact of (fat-tailed) uncertainty on optimal climate policy: the curvature of the optimal carbon tax against the uncertainty. We find that the optimal carbon tax increases as the uncertainty about climate sensitivity increases, but it does not accelerate as implied by Weitzman's Dismal Theorem. We find the same result in a wide variety of sensitivity analyses. These results emphasize the importance of balancing the costs of climate change against its benefits, also under deep uncertainty. © 2013 Springer Science+Business Media Dordrecht