Explore the vast range of titles available.

Global warming drives changes in Earth’s cloud cover, which, in turn, may amplify or dampen climate change. This “cloud feedback” is the single most important cause of uncertainty in Equilibrium Climate Sensitivity (ECS)—the equilibrium global warming following a doubling of atmospheric carbon dioxide. Using data from Earth observations and climate model simulations, we here develop a statistical learning analysis of how clouds respond to changes in the environment. We show that global cloud feedback is dominated by the sensitivity of clouds to surface temperature and tropospheric stability. Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 ± 0.35 W·m−2·K−1 (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K. We thus anticipate that our approach will enable tighter constraints on climate change projections, including its manifold socioeconomic and ecological impacts.

Standard climate projections represent future volcanic eruptions by a constant forcing inferred from 1850 to 2014 volcanic forcing. Using the latest ice‐core and satellite records to design stochastic eruption scenarios, we show that there is a 95% probability that explosive eruptions could emit more sulfur dioxide (SO2) into the stratosphere over 2015–2100 than current standard climate projections (i.e., ScenarioMIP). Our simulations using the UK Earth System Model with interactive stratospheric aerosols show that for a median future eruption scenario, the 2015–2100 average global‐mean stratospheric aerosol optical depth (SAOD) is double that used in ScenarioMIP, with small‐magnitude eruptions (<3 Tg of SO2) contributing 50% to SAOD perturbations. We show that volcanic effects on large‐scale climate indicators, including global surface temperature, sea level and sea ice extent, are underestimated in ScenarioMIP because current climate projections do not fully account for the recurrent frequency of volcanic eruptions of different magnitudes. Plain Language Summary Climate projections are the simulations of Earth's climate in the future using complex climate models. Standard climate projections, as in Intergovernmental Panel on Climate Change Sixth Assessment Report, assume that explosive volcanic activity over 2015–2100 are of the same level as the 1850–2014 period. Using the latest ice‐core and satellite records, we find that explosive eruptions could emit more sulfur dioxide into the upper atmosphere for the period of 2015–2100 than standard climate projections. Our climate model simulations show that the impacts of volcanic eruptions on climate, including global surface temperature, sea level and sea ice extent, are underestimated because current climate projections do not fully account for the recurrent frequency of volcanic eruptions. We also find that small‐magnitude eruptions occur frequently and can contribute a significant effect on future climate. Key Points There is a 95% chance that the time‐averaged 2015–2100 volcanic SO2 flux from explosive eruptions exceeds the time‐averaged 1850–2014 flux Standard climate projections very likely underestimate the 2015–2100 stratospheric aerosol optical depth and volcanic climate effects Small‐magnitude eruptions (<3 Tg SO2) contribute 30%–50% of the volcanic climate effects in a median future eruption scenario

As global temperatures continue to rise, the impact of heatwaves becomes increasingly striking. The increasing frequency and intensity of these events underscore the critical need to understand regional‐scale mechanisms and feedback, exacerbating or mitigating heatwave magnitude. Here, we use an ensemble of convection‐permitting regional climate models (CPRCMs) to elucidate future heatwave changes at fine spatial scales. We explore whether the recently highlighted drier/warmer signal introduced by CPRCMs improves summer temperature extremes representation and if it modulates future heatwave changes compared to convection‐parameterizing regional climate models (RCMs). In historical runs, CPRCMs show a more realistic representation of summer maximum temperature especially on a ground‐station‐based evaluation. CPRCMs project substantially drier conditions than RCMs. This is associated with a modulation of heatwave temperature changes which show diversified spatial patterns, magnitudes, and signs. CPRCMs ensemble shows an overall reduction in heatwave metrics future changes inter‐model spread compared to the RCMs ensemble. Plain Language Summary Heatwaves are progressively having a bigger impact on communities and ecosystems. The growing frequency and intensity of these events highlight the need to understand regional mechanisms and feedback that can either worsen or mitigate increasing heatwave trends. We use an ensemble of very high‐resolution regional climate models (CPRCMs, ∼3 km) to explore changes in heatwaves at fine spatial scales. We investigate if the drier and warmer conditions characterizing CPRCMs improve the accuracy of summer temperature extremes and how they affect future heatwave patterns compared to lower‐resolution regional climate models (RCMs). In historical simulations, CPRCMs provide a more accurate representation of summer maximum temperatures, especially on a station‐based evaluation. CPRCMs predict drier conditions than RCMs. This dryness affects heatwave temperature changes according to varied spatial patterns, magnitudes, and trends. Overall, the CPRCMs ensemble shows less uncertainty in predicted heatwave changes compared to the RCMs ensemble. Key Points CPRCMs improve summer season maximum temperature representation, especially on a ground‐station‐based evaluation CPRCMs amplify heatwave maximum temperature changes over the Alps and the northern GAR, combined with the strongest projected drying CPRCMs ensemble reduces heatwave metrics change signal inter‐model spread except for the dry spell length

Climate change will impact western USA water supplies by shifting precipitation from snow to rain and driving snowmelt earlier in the season. However, changes at the regional-to-mountain scale is still a major topic of interest. This study addresses the impacts of climate change on mountain snowpack by assessing historical and projected variable-resolution (VR) climate simulations in the community earth system model (VR-CESM) forced by prescribed sea-surface temperatures along with widely used regional downscaling techniques, the coupled model intercomparison projects phase 5 bias corrected and statistically downscaled (CMIP5-BCSD) and the North American regional climate change assessment program (NARCCAP). The multi-model RCP8.5 scenario analysis of winter season SWE for western USA mountains indicates by 2040-2065 mean SWE could decrease −19% (NARCCAP) to −38% (VR-CESM), with an ensemble median change of −27%. Contrary to CMIP5-BCSD and NARCCAP, VR-CESM highlights a more pessimistic outcome for western USA mountain snowpack in latter-parts of the 21st century. This is related to temperature changes altering the snow-albedo feedback, snowpack storage, and precipitation phase, but may indicate that VR-CESM resolves more physically consistent elevational effects lacking in statistically downscaled datasets and teleconnections that are not captured in limited area models. Overall, VR-CESM projects by 2075–2100 that average western USA mountain snowfall decreases by −30%, snow cover by −44%, SWE by −69%, and average surface temperature increase of +5.0 ∘C. This places pressure on western USA states to preemptively invest in climate adaptation measures such as alternative water storage, water use efficiency, and reassess reservoir storage operations.

A novel sub‐sampling method has been used to isolate the dynamic effects of the response of the North Atlantic Oscillation (NAO) and the Siberian High (SH) from the total response to projected Arctic sea‐ice loss under 2°C global warming above preindustrial levels in very large initial‐condition ensemble climate simulations. Thermodynamic effects of Arctic warming are more prominent in Europe while dynamic effects are more prominent in Asia/East Asia. This explains less‐severe cold extremes in Europe but more‐severe cold extremes in Asia/East Asia. For Northern Eurasia, dynamic effects overwhelm the effect of increased moisture from a warming Arctic, leading to an overall decrease in precipitation. We show that the response scales linearly with the dynamic response. However, caution is needed when interpreting inter‐model differences in the response because of internal variability, which can largely explain the inter‐model spread in the NAO and SH response in the Polar Amplification Model Intercomparison Project. Plain Language Summary The projected loss of Arctic sea‐ice under 2°C global warming will cause large warming in the Arctic region and climate and weather anomalies outside the Arctic. The warming in the Arctic will mean warmer airmasses coming from the Arctic and also more moisture from the open Arctic Ocean. Furthermore, it will also change atmospheric circulation. These effects together will determine the impacts of Arctic warming. In this study, we introduce a novel sub‐sampling method to isolate atmospheric circulation change in response to the Arctic warming. The method involves selecting members of simulations from the experiment with future Arctic sea‐ice conditions, the average of which is equal to the average of the members of simulations in the experiment with present‐day Arctic sea‐ice conditions. We found that atmospheric circulation change in European regions is relatively weak so that warming effects will dominate the climate and weather response there. On the other hand, atmospheric circulation change will dominate the climate and weather response in East Eurasia. We also found that stronger atmospheric circulation changes will generally increase the response to the Arctic warming. We suggest caution when assessing whether different responses in different models can be interpreted as true differences in model physics. Key Points A novel sub‐sampling method is introduced to isolate the role of dynamics in the response to projected Arctic sea‐ice loss A dynamical Siberian High response dominates the temperature response over East Eurasia while that of the North Atlantic Oscillation is weak Inter‐model differences in Polar Amplification Model Intercomparison Project likely contain a large fraction of internal variability due to the unconstrained dynamic effects

Compared to stratospheric SO2 injection for climate intervention, alumina particle injection could reduce stratospheric warming and associated adverse impacts. However, heterogeneous chemistry on alumina particles, especially chlorine activation via ClONO2+HCl→surfCl2+HNO3${\\text{ClONO}}_{2}+\\text{HCl}\\stackrel{\\text{surf}}{\\to }{\\text{Cl}}_{2}+{\\text{HNO}}_{3}$ , is poorly constrained under stratospheric conditions, such as low temperature and humidity. This study quantifies the uncertainty in modeling the ozone response to alumina injection. We show that extrapolating the limited experimental data for ClONO2 + HCl to stratospheric conditions leads to uncertainties in heterogeneous reaction rates of almost two orders of magnitude. Implementation of injection of 5 Mt/yr of particles with 240 nm radius in an aerosol‐chemistry‐climate model shows that resulting global total ozone depletions range between negligible and as large as 9%, that is more than twice the loss caused by chlorofluorocarbons, depending on assumptions on the degree of dissociation and interaction of the acids HCl, HNO3, and H2SO4 on the alumina surface. Plain Language Summary Global warming caused by increasing greenhouse gases could be temporarily reduced by introducing aerosol particles into the stratosphere. The most frequently studied approach to climate intervention uses H2SO4‐H2O aerosols, which, however, could result in undesirably strong warming of the stratosphere and significant ozone depletion. This might be improved by injecting solid particles, for example, made of aluminum oxide. However, here we show that the extremely limited availability of experimental studies on heterogeneous chemistry on alumina under the influence of stratospheric concentrations of HCl, HNO3, H2SO4, and H2O leads to large uncertainties in the impact of alumina injection on stratospheric ozone. In order to quantify these uncertainties, we integrated the currently available knowledge about the most important heterogeneous reaction ClONO2+HCl→surfCl2+HNO3${\\text{ClONO}}_{2}+\\text{HCl}\\stackrel{\\text{surf}}{\\to }{\\text{Cl}}_{2}+{\\text{HNO}}_{3}$into an aerosol‐chemistry‐climate model. We conclude that the uncertainty in the resulting heterogeneous reaction rate is more than two orders of magnitude depending on the partitioning of HCl, H2SO4, and HNO3 on the alumina surface. This could lead to global ozone column depletion ranging between almost negligible and up to 9%, which would be more than twice as much as the ozone loss caused by chlorofluorocarbons in the late 1990s. Key Points Heterogeneous chemistry on solid alumina particles is highly uncertain and depends strongly on the partitioning of acids onto the surface The reaction rate of ClONO2 with HCl on alumina particles is uncertain by up to two orders of magnitude under stratospheric conditions Injection of 5 Mt/yr of alumina particles could double global ozone reductions compared to chlorofluorocarbons in the late 1990s

Reliable and highly resolved information about onshore wind energy potential (WEP) is essential for expanding renewable energy to eventually achieve carbon neutrality. In this pilot study, simulated 60 m wind speeds (ws60m) from a km‐scale, convection‐permitting 3.3 km‐resolution ICON‐LAM simulation and often‐used 31 km‐resolution ERA5 reanalysis are evaluated at 18 weather masts. The estimated ICON‐LAM and ERA5 WEPs are then compared using an innovative approach with 1.8 million eligible wind turbine placements over southern Africa. Results show ERA5 underestimates ws60m with a Mean Error (ME) of −1.8 m s−1 (−27%). In contrast, ICON‐LAM shows a ME of −0.1 m s−1 (−1.8%), resulting in a much higher average WEP by 48% compared to ERA5. A combined Global Wind Atlas‐ERA5 product reduces the ws60m underestimation of ERA5 to −0.3 m s−1 (−4.7%), but shows a similar average WEP compared to ERA5 resulting from the WEP spatial heterogeneity. Plain Language Summary Onshore wind energy is expected to play a major role in the global energy transition. However, reliable and highly resolved information on the onshore wind energy potential (WEP) crucial for expansion planning is missing over southern Africa. This study evaluated high resolution 3.3 km ICON‐LAM atmospheric simulations and 31 km ERA5 reanalysis against 60 m wind speed (ws60m) observations and compared the corresponding derived WEPs. The results show that ERA5 underestimates ws60m by 27%, resulting in a 48% lower WEP assessment than ICON‐LAM, whose ws60m simulation results show a very small bias. Underestimation of wind energy yields may hinder further expansion of wind energy, as less economic performance is expected, which underlines the importance of highly resolved weather data. Key Points Simulated ERA5 and km‐scale ICON‐LAM wind speeds are evaluated and corresponding southern Africa wind energy potentials are calculated ERA5 underestimates 60 m wind speed, whereas ICON‐LAM produces lower biases in the wind speed simulations Higher wind energy potentials are revealed from wind speeds simulated by ICON‐LAM compared to ERA5, which is often used for such assessments

The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) assessed a range of scenarios of future greenhouse-gas emissions without policies to specifically reduce emissions, and concluded that these would lead to an increase in global mean temperatures of between 1.6°C and 6.9°C by the end of the twenty-first century, relative to pre-industrial. While much political attention is focused on the potential for global warming of 2°C relative to pre-industrial, the AR4 projections clearly suggest that much greater levels of warming are possible by the end of the twenty-first century in the absence of mitigation. The centre of the range of AR4-projected global warming was approximately 4°C. The higher end of the projected warming was associated with the higher emissions scenarios and models, which included stronger carbon-cycle feedbacks. The highest emissions scenario considered in the AR4 (scenario A1FI) was not examined with complex general circulation models (GCMs) in the AR4, and similarly the uncertainties in climate—carbon-cycle feedbacks were not included in the main set of GCMs. Consequently, the projections of warming for A1FI and/or with different strengths of carbon-cycle feedbacks are often not included in a wider discussion of the AR4 conclusions. While it is still too early to say whether any particular scenario is being tracked by current emissions, A1FI is considered to be as plausible as other non-mitigation scenarios and cannot be ruled out. (A1FI is a part of the A1 family of scenarios, with 'FI' standing for 'fossil intensive'. This is sometimes erroneously written as A1F1, with number 1 instead of letter I.) This paper presents simulations of climate change with an ensemble of GCMs driven by the A1FI scenario, and also assesses the implications of carbon-cycle feedbacks for the climate-change projections. Using these GCM projections along with simple climate-model projections, including uncertainties in carbon-cycle feedbacks, and also comparing against other model projections from the IPCC, our best estimate is that the A1FI emissions scenario would lead to a warming of 4°C relative to pre-industrial during the 2070s. If carbon-cycle feedbacks are stronger, which appears less likely but still credible, then 4°C warming could be reached by the early 2060s in projections that are consistent with the IPCC's 'likely range'.

There is growing evidence of climate change impacts on northern ecosystems. While most climate change studies base their assessments on air temperature, spatial variation of soil temperature responses have not been fully examined as a metric of climate change. Here we examined spatial variations of soil temperature responses to an ensemble of regional climate model (RCM) projections at multiple depths in upland and riparian zones in the Swedish boreal forest. Modeling showed a stronger influence of air temperature on riparian soil temperature than was simulated for upland soils. The RCM ensemble projected a warming range of 4.7–6.0 °C in riparian and 4.3–5.7 °C in upland soils. However, soils were slightly colder in the riparian zone during winter. While the historical record showed that upland soils are about 0.4 °C warmer than the riparian soils, this may be reversed in the future as model projections showed that on an annual basis, riparian soils might be slightly warmer by 0.2 to 0.4 °C than upland soils. However, upland soils could warm up earlier (April) compared to riparian soils (May).

Canonical understanding based on general circulation models (GCMs) is that the atmospheric circulation response to midlatitude sea‐surface temperature (SST) anomalies is weak compared to the larger influence of tropical SST anomalies. However, the ∼100‐km horizontal resolution of modern GCMs is too coarse to resolve strong updrafts within weather fronts, which could provide a pathway for surface anomalies to be communicated aloft. Here, we investigate the large‐scale atmospheric circulation response to idealized Gulf Stream SST anomalies in Community Atmosphere Model (CAM6) simulations with 14‐km regional grid refinement over the North Atlantic, and compare it to the responses in simulations with 28‐km regional refinement and uniform 111‐km resolution. The highest resolution simulations show a large positive response of the wintertime North Atlantic Oscillation (NAO) to positive SST anomalies in the Gulf Stream, a 0.4‐standard‐deviation anomaly in the seasonal‐mean NAO for 2°C SST anomalies. The lower‐resolution simulations show a weaker response with a different spatial structure. The enhanced large‐scale circulation response results from an increase in resolved vertical motions with resolution and an associated increase in the influence of SST anomalies on transient‐eddy heat and momentum fluxes in the free troposphere. In response to positive SST anomalies, these processes lead to a stronger and less variable North Atlantic jet, as is characteristic of positive NAO anomalies. Our results suggest that the atmosphere responds differently to midlatitude SST anomalies in higher‐resolution models and that regional refinement in key regions offers a potential pathway to improve multi‐year regional climate predictions based on midlatitude SSTs. Plain Language Summary Variations in the ocean surface temperature (SST) influence the atmospheric circulation and thus climate over land. Canonical understanding is that tropical SSTs are more important than SSTs in midlatitudes. However, this understanding is based on climate models that don't resolve processes at scales less than 100 km. Here, we show that by increasing the atmospheric model resolution to resolve features on smaller scales, such as weather fronts, we find a larger atmospheric circulation response to midlatitude SST anomalies in the North Atlantic. North Atlantic SST anomalies can be predicted multiple years in advance, and a larger atmospheric circulation response to these predictable SST anomalies therefore implies increased predictability of climate over the surrounding land regions. Key Points There is a large circulation response to idealized Gulf Stream sea‐surface temperature (SST) anomalies in an atmospheric model with 14‐km regional grid refinement This response is weaker or absent in simulations with 28‐km or coarser resolution, which do not fully resolve mesoscale frontal processes Transient‐eddy fluxes of heat and momentum are modified as fronts pass over warm SSTs, leading to a large‐scale circulation response