Pre-industrial Climate Research Articles

Lessons learnt from a real-time attribution and contextualisation trial in a National Meteorological and Hydrological Service

Abstract When a record hot month occurs, timely and credible attribution and contextualisation information can enhance public understanding and future preparedness. This is particularly effective if provided in real time by a National Meteorological and Hydrological Service (NMHS). Many NMHSs are working to integrate research-based attribution methods into their operational services. In this study, researchers and climate service staff collaborated to assess the feasibility of delivering such information swiftly and aligned with standard NMHS data and procedures. The record warm July (winter) temperatures of Tasmania, Australia in 2023 were chosen to illustrate the trial. Rapid results were available three days after the event. Approximately half of the unusual warmth was attributed to climate change, with the likelihood of breaking the previous record at least 17 times higher in the current climate compared to a stationary pre-industrial climate (14% vs. 0.4%). The warming trend became evident in the 1980s, and by 2060, average July temperatures in Tasmania match the record temperature of July 2023 under a high emissions scenario. However, average July minimum temperatures were not well modelled, necessitating the addition of a higher-resolution forecast-based attribution method. In subsequent analysis, almost all the forecast temperature anomaly, and reduced storm activity, was attributable to climate change. Statistical analysis revealed that a weak El Niño partly offset the unusual warmth. To expedite these additional approaches, information drawn from real-time forecasts could be used. Lessons learnt from this trial include technical improvements to align better with NMHS protocols including using consistent datasets and baselines, and refining and automating the method suite. Logistical and communication enhancements included training staff to run the suite, improving communication materials, and developing delivery channels. These learnings provide key considerations for NMHSs as they move towards providing timely and credible climate attribution and contextualisation information as part of their operational services.

Water budget of the Caspian Sea by numerical experiments with ocean circulation model INMIO-CICE in the last glacial maximum and pre-industrial period

We used the hydrodynamic model of the Caspian Sea, INMIO-CICE, to calculate equilibrium river runoff and evaporation from the sea surface over a wide range of sea levels (from –85 to +50 m asl) for different climatic conditions: the Last Glacial Maximum (about 21kyr) and pre-industrial climate (~1850 CE). Data from the climate model INMCM4.8 were used as boundary conditions. It was found that to maintain sea level at 35–50 m asl, corresponding to the maximum values of the Khvalynian transgression, a river runoff of about 400 km3/year was required in the Last Glacial Maximum. In the Last Glacial Maximum evaporation from the sea surface decreased by 105–170 mm (12–22%), and precipitation, according to the INMCM4.8 model, by 50–70 mm (15–30%). This caused the equilibrium runoff to decrease by about 10–20% compared to pre-industrial conditions. Smaller absolute and relative changes correspond to lower sea levels. The maximum decrease in evaporation occurred at 5 m asl.

Suppression of Cold Air Outbreaks over the Interior of North America in a Warmer Climate

Abstract In spite of the mean warming trend over the last few decades and its amplification in the Arctic, some studies have found no robust decline or even a slight increase in wintertime cold air outbreaks over North America. But fossil evidence from warmer paleoclimate periods indicates that the interior of North America never dropped below freezing even in the depths of winter, which implies that the maintenance of cold air outbreaks is unlikely to continue indefinitely with future warming. To identify key mechanisms affecting cold air outbreaks and understand how and why they will change in a warmer climate, we examine the development of North American cold air outbreaks in both a preindustrial and a roughly 8×CO2 scenario using the Community Earth System Model, version 2 (CESM2). We observe a sharp drop-off in the wintertime temperature distribution at the freezing temperature, suppressing below-freezing conditions in the warmer climate and above-freezing conditions in the preindustrial case. The disappearance of Arctic sea ice and loss of the near-surface temperature inversion dramatically decrease the availability of below-freezing air in source regions. Using an air parcel trajectory analysis, we demonstrate a remarkable similarity in both the dynamics and diabatic effects acting on cold air masses in the two climate scenarios. Diabatic temperature evolution along cold air outbreak trajectories is a competition between cooling from longwave radiation and warming from boundary layer mixing. Surprisingly, while both diabatic effects strengthen in the warmer climate, the balance remains the same, with a net cooling of about −6 K over 10 days. Significance Statement We compare a preindustrial climate scenario to a much warmer climate circa the year 2300 under high emissions to understand the physical processes that influence the coldest wintertime temperatures and how they will change with warming. We find that enhanced warming in the Arctic, and particularly over the Arctic Ocean due to the loss of wintertime sea ice, dramatically reduces the availability of cold air to be swept into North America. By tracing these cold air masses as they travel, we also find that they experience the same total amount of cooling in the much warmer climate as they did in the preindustrial climate even though many of the individual heating and cooling processes have gotten stronger.

The radiative feedback continuum from Snowball Earth to an ice-free hothouse

Paleoclimate records have been used to estimate the modern equilibrium climate sensitivity. However, this requires understanding how the feedbacks governing the climate response vary with the climate itself. Here we warm and cool a state-of-the-art climate model to simulate a continuum of climates ranging from a nearly ice-covered Snowball Earth to a nearly ice-free hothouse. We find that the pre-industrial (PI) climate is near a stability optimum: warming leads to a less-stable (more-sensitive) climate, as does cooling of more than 2K. Physically interpreting the results, we find that the decrease in stability for climates colder than the PI occurs mainly due to the albedo and lapse-rate feedbacks, and the decrease in stability for warmer climates occurs mainly due to the cloud feedback. These results imply that paleoclimate records provide a stronger constraint than has been calculated in previous studies, suggesting a reduction in the uncertainty range of the climate sensitivity.

Land-Use Feedback under Global Warming—A Transition from Radiative to Hydrological Feedback Regime

Abstract This study examines the effects of land-use (LU) change on regional climate, comparing historical and future scenarios using seven climate models from phase 6 of Coupled Model Intercomparison Project–Land Use Model Intercomparison Project experiments. LU changes are evaluated relative to land-use conditions during the preindustrial climate. Using the Community Earth System Model, version 2–Large Ensemble (CESM2-LE) experiment, we distinguish LU impacts from natural climate variability. We assess LU impact locally by comparing the impacts of climate change in neighboring areas with and without LU changes. Further, we conduct CESM2 experiments with and without LU changes to investigate LU-related climate processes. A multimodel analysis reveals a shift in LU-induced climate impacts, from cooling in the past to warming in the future climate across midlatitude regions. For instance, in North America, LU’s effect on air temperature changes from −0.24° ± 0.18°C historically to 0.62° ± 0.27°C in the future during the boreal summer. The CESM2-LE shows a decrease in LU-driven cooling from −0.92° ± 0.09°C in the past to −0.09° ± 0.09°C in future boreal summers in North America. A hydroclimatic perspective linking LU and climate feedback indicates LU changes causing soil moisture drying in the midlatitude regions. This contrasts with hydrology-only views showing wetter soil conditions due to LU changes. Furthermore, global warming causes widespread drying of soil moisture across various regions. Midlatitude regions shift from a historically wet regime to a water-limited transitional regime in the future climate. This results in reduced evapotranspiration, weakening LU-driven cooling in future climate projections. A strong linear relationship exists between soil moisture and evaporative fraction in midlatitudes. Significance Statement Land–atmosphere feedback involving soil moisture can increase local temperature and affect how land-use (LU) change impacts manifest in a warming climate. Conversely, an increased surface reflectance due to LU change can decrease local temperature in the midlatitude regions. Further, the LU change signal is often mixed with the internal climate variability, making it harder to separate. This study uses a novel technique to separate LU change impact from other climate forcing in the latest generation of climate and Earth system models. In the future climate, soil moisture drying lessens the cooling impact. A large-ensemble climate experiment analysis confirms a significant weakening of the LU-driven cooling impact in the midlatitudes. Both LU and climate changes exacerbate soil moisture drying, leading to a shift toward a water-limited system where hydrological feedback becomes more influential than radiative feedback.

Making the Climate Malleable? “Weak” and “Strong” Governance Objects and the Transformation of International Climate Politics

Abstract Object-oriented theories have been used to understand how the climate and other entities like “the economy” have been produced as discrete, malleable and politically salient “governance objects.” These have structuring effects not only on policy debates but also on entire polities and the international system. However, a failure to distinguish between different kinds of governance objects has obscured their fundamentally different political implications. This article revises earlier definitions and develops a novel distinction between “weakly” and “strongly” malleable governance objects. The former are governable only in terms of not being perturbed in relation to a baseline condition, while “strongly governable” objects are construed as malleable along multiple dimensions, the telos of governing them no longer a given. The weak/strong distinction is applied to elicit implications of four climate strategies: mitigation, adaptation, and prospective “geoengineering” techniques of carbon dioxide removal and solar radiation modification that would deliberately alter the climate. Increasingly billed as risky but necessary, given the fraught politics of mitigation, geoengineering is shown to potentially transform the climate from weak to more strongly governable object. This could “untether” climate governance from the aim of remaining close to a pre-industrial climate, with a "design approach" to geoengineering adding layers of politicization, potentially increasing the fractiousness of global climate politics. However the analysis also highlights possible new routes to depoliticization of the climate, were it to be retethered—potentially to security imperatives or economic indicators. Analysis of governance objects requires much greater attention to types of malleability and politicization.

The Southern Ocean as the climate's freight train – driving ongoing global warming under zero-emission scenarios with ACCESS-ESM1.5

Abstract. Earth system model experiments presented here explore how the centennial response in the Southern Ocean can drive ongoing global warming even with zero CO2 emissions and declining atmospheric CO2 concentrations. These projections were simulated by the earth system model version of the Australian Community Climate and Earth System Simulator (ACCESS-ESM1.5) and motivated by the Zero Emissions Commitment Model Intercomparison Project (ZECMIP); ACCESS-ESM1.5 simulated ongoing warming in the ZECMIP experiment that switched or branched to zero emissions after 2000 PgC had been emitted. New experiments presented here each simulated 300 years and included intermediate branch points. In each experiment that branched after emitting more than 1000 PgC, the global climate continues to warm. For the experiment that branched after 2000 PgC, or after 3.5 °C of warming from a preindustrial climate, there is 0.37 ± 0.08 °C of extra warming after 50 years of zero emissions, which increases to 0.83 ± 0.08 °C after 200 years. All branches show ongoing Southern Ocean warming. The circulation of the Southern Ocean is modified early in the warming climate, which contributes to changes in the distribution of both physical and biogeochemical subsurface ocean tracers, such as ongoing warming at intermediate depths and a reduction in deep oxygen south of 60° S. A simple slab model emulates the global temperatures of the ACCESS-ESM1.5 experiments demonstrating the response here is primarily due to the slow response of the ocean and the Southern Ocean in particular. Centennial global warming persists when the slab model is forced with CO2 diagnosed from late-branching experiments with other ZECMIP models, confirming the dominant role of ocean physics at these timescales. However, decadal responses changed due to the larger drawdown of CO2 from other models. Slow ongoing warming in the Southern Ocean can be found in ZEC scenarios of most models, though the amplitude and global influence varies.

Event attribution of a midlatitude windstorm using ensemble weather forecasts

The widespread destruction incurred by midlatitude storms every year makes it an imperative to study how storms change with climate. The impact of climate change on midlatitude windstorms, however, is hard to evaluate due to the small signals in variables such as wind speed, as well as the high resolutions required to represent the dynamic processes in the storms. Here, we assess how storm Eunice, which hit the UK in February 2022, was impacted by anthropogenic climate change using the ECMWF ensemble prediction system. This system was demonstrably able to predict the storm, significantly increasing our confidence in its ability to model the key physical processes and their response to climate change. Using modified greenhouse gas concentrations and changed initial conditions for ocean temperatures, we create two counterfactual scenarios of storm Eunice in addition to the forecast for the current climate. We compare the intensity and severity of the storm between the pre-industrial, current, and future climates. Our results robustly indicate that Eunice has become more intense with climate change and similar storms will continue to intensify with further anthropogenic forcing. These results are consistent across forecast lead times, increasing our confidence in them. Analysis of storm composites shows that this process is caused by increased vorticity production through increased humidity in the warm conveyor belt of the storm. This is consistent with previous studies on extreme windstorms. Our approach of combining forecasts at different lead times for event attribution enables combining event specificity and a focus on dynamic changes with the assessment of changing risks from windstorms. Further work is needed to develop methods to adjust the initial conditions of the atmosphere for the use in attribution studies using weather forecasts but we show that this approach is viable for reliable and fast attribution systems.

Dependency of the impacts of geoengineering on the stratospheric sulfur injection strategy – Part 2: How changes in the hydrological cycle depend on the injection rate and model used

Abstract. This is the second of two papers in which we study the dependency of the impacts of stratospheric sulfur injections on the model and injection strategy used. Here, aerosol optical properties from simulated stratospheric aerosol injections using two aerosol models (modal scheme M7 and sectional scheme SALSA), as described in Part 1 (Laakso et al., 2022), are implemented consistently into the EC-Earth, MPI-ESM and CESM Earth system models (ESMs) to simulate the climate impacts of different injection rates ranging from 2 to 100 Tg(S) yr−1. Two sets of simulations were run with the three ESMs: (1) regression simulations, in which an abrupt change in CO2 concentration or stratospheric aerosols over pre-industrial conditions was applied to quantify global mean fast temperature-independent climate responses and quasi-linear dependence on temperature, and (2) equilibrium simulations, in which radiative forcing of aerosol injections with various magnitudes compensated for the corresponding radiative forcing of CO2 enhancement to study the dependence of precipitation on the injection magnitude. The latter also allow one to explore the regional climatic responses. Large differences in SALSA- and M7-simulated radiative forcing in Part 1 translated into large differences in the estimated surface temperature and precipitation changes in ESM simulations; for example, an injection rate of 20 Tg(S) yr−1 in CESM using M7-simulated aerosols led to only 2.2 K global mean cooling, while EC-Earth–SALSA combination produced a 5.2 K change. In equilibrium simulations, where aerosol injections were utilized to offset the radiative forcing caused by an atmospheric CO2 concentration of 500 ppm, the decrease in global mean precipitation varied among models, ranging from −0.7 % to −2.4 % compared with the pre-industrial climate. These precipitation changes can be explained by the fast precipitation response due to radiation changes caused by the stratospheric aerosols and CO2, as the global mean fast precipitation response is shown to be negatively correlated with global mean atmospheric absorption. Our study shows that estimating the impact of stratospheric aerosol injection on climate is not straightforward. This is because the simulated capability of the sulfate layer to reflect solar radiation and absorb long-wave radiation is sensitive to the injection rate as well as the aerosol model used to simulate the aerosol field. These findings emphasize the necessity for precise simulation of aerosol microphysics to accurately estimate the climate impacts of stratospheric sulfur intervention. This study also reveals gaps in our understanding and uncertainties that still exist related to these controversial techniques.

Possible role of anthropogenic climate change in the record-breaking 2020 Lake Victoria levels and floods

Abstract. Heavy rainfall in eastern Africa between late 2019 and mid 2020 caused devastating floods and landslides throughout the region. These rains drove the levels of Lake Victoria to a record-breaking maximum in the second half of May 2020. The combination of high lake levels, consequent shoreline flooding, and flooding of tributary rivers caused hundreds of casualties and damage to housing, agriculture, and infrastructure in the riparian countries of Uganda, Kenya, and Tanzania. Media and government reports linked the heavy precipitation and floods to anthropogenic climate change, but a formal scientific attribution study has not been carried out so far. In this study, we characterize the spatial extent and impacts of the floods in the Lake Victoria basin and then investigate to what extent human-induced climate change influenced the probability and magnitude of the record-breaking lake levels and associated flooding by applying a multi-model extreme event attribution methodology. Using remote-sensing-based flood mapping tools, we find that more than 29 000 people living within a 50 km radius of the lake shorelines were affected by floods between April and July 2020. Precipitation in the basin was the highest recorded in at least 3 decades, causing lake levels to rise by 1.21 m between late 2019 and mid 2020. The flood, defined as a 6-month rise in lake levels as extreme as that observed in the lead-up to May 2020, is estimated to be a 63-year event in the current climate. Based on observations and climate model simulations, the best estimate is that the event has become more likely by a factor of 1.8 in the current climate compared to a pre-industrial climate and that in the absence of anthropogenic climate change an event with the same return period would have led lake levels to rise by 7 cm less than observed. Nonetheless, uncertainties in the attribution statement are relatively large due to large natural variability and include the possibility of no observed attributable change in the probability of the event (probability ratio, 95 % confidence interval 0.8–15.8) or in the magnitude of lake level rise during an event with the same return period (magnitude change, 95 % confidence interval 0–14 cm). In addition to anthropogenic climate change, other possible drivers of the floods and their impacts include human land and water management, the exposure and vulnerability of settlements and economic activities located in flood-prone areas, and modes of climate variability that modulate seasonal precipitation. The attribution statement could be strengthened by using a larger number of climate model simulations, as well as by quantitatively accounting for non-meteorological drivers of the flood and potential unforced modes of climate variability. By disentangling the role of anthropogenic climate change and natural variability in the high-impact 2020 floods in the Lake Victoria basin, this paper contributes to a better understanding of changing hydrometeorological extremes in eastern Africa and the African Great Lakes region.

Impact-induced initiation of Snowball Earth: A model study

During the Neoproterozoic and Paleoproterozoic eras, geological evidence points to several “Snowball Earth” episodes when most of Earth’s surface was covered in ice. These global-scale glaciations represent the most marked climate changes in Earth’s history. We show that the impact winter following an asteroid impact comparable in size to the Chicxulub impact could have led to a runaway ice-albedo feedback and global glaciation. Using a state-of-the-art atmosphere-ocean climate model, we simulate the climate response following an impact for preindustrial, Last Glacial Maximum (LGM), Cretaceous-like, and Neoproterozoic climates. While warm ocean temperatures in the preindustrial and Cretaceous-like climates prevent Snowball initiation, the colder oceans of the LGM and cold Neoproterozoic climate scenarios rapidly form sea ice and demonstrate high sensitivity to the initial condition of the ocean. Given suggestions of a cold pre-Snowball climate, we argue the initiation of Snowball Earth by a large impact is a robust possible mechanism, as previously suggested by others, and conclude by discussing geologic tests.

Climate attribution time series track the evolution of human influence on North Pacific sea surface temperature

We apply climate attribution techniques to sea surface temperature time series from five regional North Pacific ecosystems to track the growth in human influence on ocean temperatures over the past seven decades (1950–2022). Using Bayesian estimates of the Fraction of Attributable Risk (FAR) and Risk Ratio (RR) derived from 23 global climate models, we show that human influence on regional ocean temperatures could first be detected in the 1970s and grew until 2014–2020 temperatures showed overwhelming evidence of human contribution. For the entire North Pacific, FAR and RR values show that temperatures have reached levels that were likely impossible in the preindustrial climate, indicating that the question of attribution is already obsolete at the basin scale. Regional results indicate the strongest evidence for human influence in the northernmost ecosystems (Eastern Bering Sea and Gulf of Alaska), though all regions showed FAR values > 0.98 for at least one year. Extreme regional SST values that were expected every 1000–10 000 years in the preindustrial climate are expected every 5–40 years in the current climate. We use the Gulf of Alaska sockeye salmon fishery to show how attribution time series may be used to contextualize the impacts of human-induced ocean warming on ecosystem services. We link negative warming effects on sockeye fishery catches to increasing human influence on regional temperatures (increasing FAR values), and we find that sockeye salmon migrating to sea in years with the strongest evidence for human effects on temperature (FAR ⩾ 0.98) produce catches 1.4 standard deviations below the long-term log mean. Attribution time series may be helpful indicators for better defining the human role in observed climate change impacts, and may thus help researchers, managers, and stakeholders to better understand and plan for the effects of climate change.

Free-tropospheric aerosols contribute to large aerosol optical depth at a remote, inland location with insignificant anthropogenic emissions

In-situ measurements of atmospheric aerosols from remote environments marked with negligible human activities are required to reduce the uncertainties associated with natural aerosols in pre-industrial climate forcings (particularly the aerosol-cloud interactions). In this study, we present long-term continuous aerosol measurements, carried out using ground-based and satellite observations, both close to the surface and in the vertical column, over a remote, rural, inland location in southern peninsular India. The near-surface aerosol concentrations were low, in general conformity to the typical pattern expected for a remote location, with the temporal changes being primarily governed by the background meteorology. However, the columnar aerosol optical depth (AOD) was surprisingly high and resembled that of a typical semi-urban continental location, with an yearly mean AOD of 0.47 ± 0.06. Spaceborne lidar observations in conjunction with ground-based radiometer measurements revealed that around 60% of this AOD was contributed by free-tropospheric aerosol layers during summer and monsoon seasons. Airmass back-trajectory analysis along with particle depolarisation ratio profiles indicate that these aerosol layers are mostly associated with long-range transported dust aerosols. Our findings indicate that benign surface concentration of aerosols at a location need not necessarily be sufficient to consider it as an optimal choice for studying background aerosols.

Root zone soil moisture in over 25 % of global land permanently beyond pre-industrial variability as early as 2050 without climate policy

Abstract. Root zone soil moisture is a key variable representing water cycle dynamics that strongly interact with ecohydrological, atmospheric, and biogeochemical processes. Recently, it was proposed as the control variable for the green water planetary boundary, suggesting that widespread and considerable deviations from baseline variability now predispose Earth system functions critical to an agriculture-based civilization to destabilization. However, the global extent and severity of root zone soil moisture changes under future scenarios remain to be scrutinized. Here, we analysed root zone soil moisture departures from the pre-industrial climate variability for a multi-model ensemble of 14 Earth system models (ESMs) in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in four climate scenarios as defined by the shared socioeconomic pathways (SSPs) SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5 between 2021 and 2100. The analyses were done for 43 ice-free climate reference regions used by the Intergovernmental Panel on Climate Change (IPCC). We defined “permanent departures” when a region's soil moisture exits the regional variability envelope of the pre-industrial climate and does not fall back into the range covered by the baseline envelope until 2100. Permanent dry departures (i.e. lower soil moisture than pre-industrial variability) were found to be most pronounced in Central America, southern Africa, the Mediterranean region, and most of South America, whereas permanent wet departures are most pronounced in south-eastern South America, northern Africa, and southern Asia. In the Mediterranean region, dry permanent departure may have already happened according to some models. By 2100, there are dry permanent departures in the Mediterranean in 70 % of the ESMs in SSP1–2.6, the most mitigated situation, and more than 90 % in SSP3–7.0 and SSP5–8.5, the medium–high and worst-case scenarios. North-eastern Africa is projected to experience wet permanent departures in 64 % of the ESMs under SSP1–2.6 and 93 % under SSP5–8.5. The percentage of ice-free land area with departures increases in all SSP scenarios as time goes by. Wet departures are more widespread than dry departures throughout the studied time frame, except in SSP1–2.6. In most regions, the severity of the departures increases with the severity of global warming. In 2050, permanent departures (ensemble median) occur in about 10 % of global ice-free land areas in SSP1–2.6 and in 25 % in SSP3–7.0. By the end of the 21st century, the occurrence of permanent departures in SSP1–2.6 increases to 34 % and, in SSP3–7.0, to 45 %. Our findings underscore the importance of mitigation to avoid further degrading the Earth system functions upheld by soil moisture.

A forecast-model-based extreme weather event attribution system developed for Aotearoa New Zealand

A largely automated extreme weather event (EWE) attribution system has been developed that uses the Weather Research and Forecast numerical weather prediction model to simulate EWEs under current and pre-industrial climate conditions. The system has been applied to two extreme precipitation events in Aotearoa New Zealand with the goal of quantifying the effect of anthropogenic climate change on the severity of these events. The forecast simulation of the target event under current climate conditions constitutes the first scenario (ALL). We then apply a climate change signal in the form of delta fields in sea-surface temperature, atmospheric temperature and specific humidity, creating a second ‘naturalised’ scenario (NAT) which is designed to represent the weather system in the absence of human interference with the climate system. A third scenario, designed to test for coherence, is generated by applying deltas of opposite sign compared to the naturalised scenario (ALL+). Each scenario comprises a 22-member ensemble which includes one simulation that was not subject to stochastic perturbation. Comparison of the three ensembles shows that: (1) the NAT ensemble develops an extreme event which resembles the observed event, (2) the severity, i.e. maximum intensity and/or the size of area affected by heavy precipitation, changes when naturalising the boundary conditions, (3) the change in severity is consistently represented within the three scenarios and the signal is robust across the different ensemble members, i.e. it is typically shown in most of the 22 ensemble members. Thus, the attribution system presented here can be used to provide information about the influence of anthropogenic climate change on the severity of specific extreme events.

Attribution of 2022 early-spring heatwave in India and Pakistan to climate change: lessons in assessing vulnerability and preparedness in reducing impacts

In March 2022, large parts over the north Indian plains including the breadbasket region, and southern Pakistan began experiencing prolonged heat, which continued into May. The event was exacerbated due to prevailing dry conditions in the region, resulting in devastating consequences for public health and agriculture. Using event attribution methods, we analyse the role of human-induced climate change in altering the chances of such an event. To capture the extent of the impacts, we choose March–April average of daily maximum temperature over the most affected region in India and Pakistan as the variable. In observations, the 2022 event has a return period of ∼1-in-100 years. For each of the climate models, we then calculate the change in probability and intensity of a 1-in-100 year event between the actual and counterfactual worlds for quantifying the role of climate change. We estimate that human-caused climate change made this heatwave about 1 °C hotter and 30 times more likely in the current, 2022 climate, as compared to the 1.2 °C cooler, pre-industrial climate. Under a future global warming of 2 °C above pre-industrial levels, heatwaves like this are expected to become even more common (2–20 times more likely) and hotter (by 0 °C–1.5 °C) compared to now. Stronger and frequent heat waves in the future will impact vulnerable groups as conditions in some regions exceed limits for human survivability. Therefore, mitigation is essential for avoiding loss of lives and livelihood. Heat Action Plans have proved effective to help reduce heat-related mortality in both countries.

How does Mei-yu precipitation respond to climate change?

Mei-yu is an important weather phenomenon in the middle-lower Yangtze River valley (YRV) region. This study investigates the changes in the characteristics of Mei-yu under global warming and the potential reasons based on observation and reanalysis data during 1961-2022. Notable increasing long-term trends are detected in the number of days without rainfall (NDWOR), the intensity of rainfall events, and the frequency and intensity of extreme precipitation events (EPEs) in the YRV region during the Mei-yu period (15 June-10 July) over past decades. The increasing trend in NDWOR is attributed to decreased relative humidity over land surface and a longer time for the air to be replenished with moisture after rainfall events in a warming climate. The increasing trends in the intensity of rainfall events and frequency/intensity of EPEs are attributed to the strengthened transient water vapor convergence and convection in the atmosphere under global warming. Furthermore, the response of Mei-yu to 2°C of global warming with respect to the pre-industrial climate is analysed using CMIP6 models. The results suggest that the NDWOR, intensity of rainfall events and frequency of EPEs will increase in the YRV region during the Mei-yu period under the 2°C warming scenario, which implies a more challenging climate risk management in the future. Overall, the intensity of rainfall events during the Mei-yu period has the most significant response to climate change in observations and projections. The model results have a relatively large uncertainty.

Did the Bronze Age deforestation of Europe affect its climate? A regional climate model study using pollen-based land cover reconstructions

Abstract. This paper studies the impact of land use and land cover change (LULCC) on the climate around 2500 years ago (2.5 ka), a period of rapid transitions across the European landscape. One global climate model was used to force two regional climate models (RCMs). The RCMs used two land cover descriptions. The first was from a dynamical vegetation model representing potential land cover, and the second was from a land cover description reconstructed from pollen data by statistical interpolation. The two different land covers enable us to study the impact of land cover on climate conditions. Since the difference in landscape openness between potential and reconstructed land cover is mostly due to LULCC, this can be taken as a measure of early anthropogenic effects on climate. Since the sensitivity to LULCC is dependent on the choice of climate model, we also use two RCMs. The results show that the simulated 2.5 ka climate was warmer than the simulated pre-industrial (PI, 1850 CE) climate. The largest differences are seen in northern Europe, where the 2.5 ka climate is 2–4 ∘C warmer than the PI period. In summer, the difference between the simulated 2.5 ka and PI climates is smaller (0–3 ∘C), with the smallest differences in southern Europe. Differences in seasonal precipitation are mostly within ±10 %. In parts of northern Europe, the 2.5 ka climate is up to 30 % wetter in winter than that of the PI climate. In summer there is a tendency for the 2.5 ka climate to be drier than the PI climate in the Mediterranean region. The results also suggest that LULCC at 2.5 ka impacted the climate in parts of Europe. Simulations including reconstructed LULCC (i.e. those using pollen-derived land cover descriptions) give up to 1 ∘C higher temperature in parts of northern Europe in winter and up to 1.5 ∘C warmer in southern Europe in summer than simulations with potential land cover. Although the results are model dependent, the relatively strong response implies that anthropogenic land cover changes that had occurred during the Neolithic and Bronze Age could have affected the European climate by 2.5 ka.

Last interglacial seasonal hydroclimate in the North Sea–Baltic Sea region

The Last Interglacial (LIG) experienced substantial changes in seasonal insolation compared with the present day, which may have affected the hydrography and water-mass exchange in the North Sea and Baltic Sea region. Here we investigate the effects of solar radiation and greenhouse gas (GHG) forcing on the regional climate by analyzing model simulations of the LIG (127 ka BP), pre-industrial (PI, 1850 CE), and present-day (PD, 1990 CE) climates. We also interpret the reconstructed seasonal bottom water conditions using benthic foraminifera and geochemistry data.Our simulations reveal that during the LIG, the Baltic Sea region (including the Kattegat and the Danish Straits) experienced more saline and colder bottom waters than those in the PD, in agreement with the reconstruction data. This can be attributed to lower GHG levels and enhanced water exchange of cooler, saline North Sea water into the Baltic Sea during the LIG. The thermocline was stronger during the summer months in the LIG, mainly due to the higher sea surface temperature (SST) compared to that of the PD resulting from increased summer insolation.Further, the temperature anomalies (LIG–PD) show significant inverse correlations with the precipitation–minus–evaporation (P–E) at the Baltic Sea entrance. However, the P–E balance appears to have had minimal impact on salinity changes in the North Sea, the Baltic Proper, and the open sea area. Our findings indicate that monthly surface and bottom water salinity anomalies of LIG-PI exhibit strong positive correlations with the North Atlantic Oscillation (NAO) anomalies in the Baltic entrance region. During the LIG, a more positive phase of the NAO index in autumn played a crucial role in wind-driven major inflows and led to more intensive water exchange in the North Sea–Baltic Sea region compared to the late Holocene.

The Hadley circulation in the Pangea era

The Pangea era is an exceptional phase in Earth’s history. It is characterized by its hothouse climate state and the latest supercontinent. Thus, it is expected that atmospheric circulation in the Pangea era was largely different from that of the modern world. Here, we study the Hadley circulation in the Pangea era and compare it with that of the present, by performing climate simulations. Our results show that the annual mean Hadley cells are about 20% and 45% weaker than that in the pre-industrial (PI) climate, and their poleward edges are about 2° wider in latitude. The austral winter cell is weakened by 27% and expanded by 2.6°, while the changes of the boreal winter cell are not significant. One distinctive feature is that the ascending branches of the boreal and austral winter cells shift to 23°S and 18°N, respectively, which are much more poleward than their present locations. Our analyses demonstrate that the weakening and widening of the Hadley circulation is due to increasing tropical and subtropical static stability, and that the poleward shifts of the ascending branches of the winter cells are associated with the geographic configuration of the supercontinent Pangea.