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Midlatitude Europe (ME) emerges as a prominent heatwave hotspot with rapid increases in summer surface air temperature and heatwave days since 1979, surpassing the global land averages by approximately 2.6 and 2.3 times, respectively. The circulation analogs‐based dynamic adjustment reveals that approximately 38% and 35% of these trends result from shifts in zonal dipolar circulation patterns over the North Atlantic (NA) and Europe, crucial for the enhanced warming compared to the global land average. The circulation changes are associated with warming sea surface temperatures in the NA. This warming pattern resembles the Atlantic Multidecadal Variability and is predominantly induced by greenhouse gases. Moreover, the stronger air temperature response in ME to decreased aerosols amplifies warming, contributing to the rapid increase in heatwave frequency. These findings highlight a prominent influence of anthropogenic forcings on the swift surge of European heatwaves compared to global land, with a potential implication for adaptation strategies and risk management. Plain Language Summary: Midlatitude Europe is experiencing a significant increase in heatwaves, with summer temperatures and heatwave occurrences rising much faster than the global land averages since 1979. One of the key contributors to this rapid warming is the changes in zonal dipolar circulation patterns over the NA and Europe, which are linked to the warm sea surface temperatures in the NA. This warming pattern, resembling the Atlantic Multidecadal Variability, is largely caused by greenhouse gases and additionally influenced by reduced aerosols and natural forcing. Furthermore, the stronger response of air temperatures in midlatitude Europe to decreased aerosol emissions intensifies summer warming, contributing to a rapid increase in heatwave days. These findings highlight the significant impact of anthropogenic forcings on the observed surge of heatwaves in Europe compared to global land, with an important implication for developing strategies to adapt to these changing climate conditions and managing the associated risks. Key Points: Midlatitude Europe exhibits more rapid increases in summer heatwave frequency than the global land averages in recent decadesAtmospheric circulation changes contributing about one third of the observed warming trend, further intensify the rapid increases in summer heatwave frequencyLocal air temperature response to reduced aerosol emissions contributes about half of the enhanced warming compared to the global land average [ABSTRACT FROM AUTHOR]

Under global warming, heatwaves (HWs) are exerting increasing impacts on human life. In order to explore the thermal sensation of HWs under the combined influence of air temperature, humidity, radiation and wind speed, this study utilized the hourly Universal Thermal Climate Index (UTCI) data from the ECMWF Reanalysis v5 (ERA5) to define daytime, night‐time and compound HWs, and then comparatively analysed their occurrences in China during 1981–2020. Results revealed that daytime HWs affect the majority of regions in China with the exception of the Tibetan Plateau, while both night‐time and compound HWs mainly strike the Yangtze River Basin and the Guangdong–Guangxi region in southeastern China. Additionally, it is noteworthy that a substantial portion of regions experiencing night‐time HWs also encounter compound HWs. The frequency and intensity of all three types of HWs show increasing trends generally in regions where HWs occur. The spatial coverage of HWs grows at rates of 8.05%/10a, 2.11%/10a and 1.62%/10a for the daytime, night‐time and compound types, respectively. For each summer month, the spatial coverage of daytime HWs notably surpasses that of night‐time and compound HWs. Further classifying HWs with intensity, it is found that the spatial coverage of both moderate and severe HW events exhibits discernible rising trends across all three types of HWs. Furthermore, regions with higher HW frequencies are more likely to experience severe HWs as well as record‐breaking ones. Additionally, the spatial coverage of daytime, night‐time and compound record‐breaking HWs is expanding. [ABSTRACT FROM AUTHOR]

Antarctic warm extremes impact the cryosphere, with very warm extremes driving surface melt on ice shelves. Here, we analyze temperatures exceeding the 90th percentile and the associated circulation patterns and radiation anomalies. ERA5 reanalysis data show positive geopotential height anomalies related to the occurrence of warm extremes. The highest temperature during warm extremes appears on the western periphery of high‐pressure systems, consistent with anticyclonic advection. Temperature anomalies during warm extremes are strongest in winter due to the transport of warm and moist air and a strong meridional temperature gradient. In summer, the weak meridional gradients of top‐of‐atmosphere downward solar radiation flux and surface air temperature contribute to weak temperature anomalies. Warm extremes are associated with positive longwave radiation anomalies in all seasons, but with negative shortwave radiation anomalies at the surface except during polar night. These relationships are verified by station observations. Our results confirm that Antarctic warm extremes are mostly driven by meridional advection of warm air, and suggest that these warm air masses are predominantly moist and cloudy. Plain Language Summary: Changes in Antarctic climate will alter the amount of water stored in the kilometer‐thick Antarctic ice cover, and thereby global sea level. So far, only some regions of the continent have experienced substantial warming under climate change, while others remain largely unaffected. In this study, we analyze the relatively warmest Antarctic temperatures in each place and season. We find that these warm extremes depart more strongly from seasonal mean temperatures in winter than in summer. Warm extremes are often a consequence of warmer air being transported from further North and coincide with moist, probably cloudy air that emits more infrared radiation to the surface than dry, cold air. Key Points: Warm extremes accompanied by high‐pressure systems are driven by advectionWinter experiences strongest temperature anomalies during warm extremesLongwave radiation anomalies during warm extremes are positive and contribute to warm extremes, shortwave radiation anomalies are negative [ABSTRACT FROM AUTHOR]

Extracting global sea surface temperature (SST) patterns is essential for understanding climate variability in both regional and global perspective. Traditional methods, limited by assumptions of orthogonality, hinder our ability to fully capture the dynamics of global SST, particularly in the complex Pacific basin. This study introduces dynamic mode decomposition (DMD), a powerful method from fluid dynamics, to extract global SST patterns since 1900. Our analysis shows that DMD successfully captures well‐known patterns like global warming and the Atlantic Multidecadal Oscillation (AMO). More importantly, it reveals three Pacific SST modes that are spatially non‐orthogonal but exhibit distinct characteristics. Spectral analysis shows that these Pacific modes have distinct periodicities: Pacific Multi‐decadal Mode (PMDM, ~50 years), Quasi‐decadal Mode (PQDM, 8–16 years) and Interannual Mode (PIAM, 2–8 years). This highlights DMD's strength in not only capturing known patterns but also separating modes with similar spatial features but unique dynamics. Further analysis reveals significant differences in their impacts on global air temperature. During positive phases, all three modes induce tropical warming, with PIAM exerting the strongest influence and PMDM the weakest. In the Northern Hemisphere, both PQDM and PIAM drive mid‐latitude cooling and high‐latitude warming, with a more pronounced effect from PQDM. PMDM, in contrast, triggers widespread cooling across the Northern extratropics. In the Southern Hemisphere, PMDM's influence on temperature exhibits a distinct latitudinal banding pattern. PIAM and PQDM, on the other hand, exhibit a regionalized impact, primarily concentrated in the Amundsen and Ross Seas, with PQDM's influence extending to the Antarctic continent. [ABSTRACT FROM AUTHOR]

The winter hydrological period is in transition across the Canadian subarctic, as climate warming is shifting precipitation regimes, thawing permafrost, and altering active layer dynamics, and thus increasing the overall amount, and variability, of winter streamflow. Effects of these changes are poorly understood on the Taiga Shield, which comprises ~20% of North America's permafrost‐covered area, and is characterized by a unique 'fill‐and‐spill' hydrology whereby runoff generation requires the exceedance of lake basin storage thresholds. Here, we assessed lake hydrostatic levels and used trail camera images of icings, which are sheet‐like masses of layered ice that are common manifestations of wintertime flow on the Taiga Shield, to understand landscape controls on winter water movement in this region. We further used paired geochemical measurements to explore how source water characteristics affect icing chemistry, and the degree to which icings may modify the chemical composition of active winter flow. We undertake this work over 2 years, and across watersheds of different sizes and lake basin characteristics. We show that icing growth is driven by hydroclimatic controls that include fill‐and‐spill hydrologic constraints and winter air temperatures, and that pre‐freshet pulses of water flow are common within this landscape. Across winters with variable antecedent precipitation levels, a larger catchment was able to support icing growth via continued runoff generation, while small catchments were not. Icings were often chemically dilute compared with source waters, indicating that solute exclusion may actively enrich geochemical concentrations in flowing water. Across icings, chemical variation appeared related to source water type (groundwater versus lake; lake size) and apparent redox conditions. These results highlight that streamwater hydrology and biogeochemistry can be dynamic during the understudied winter period, and illustrate that icings may alter the composition of wintertime flow as it moves through fluvial networks. [ABSTRACT FROM AUTHOR]

Surface anticyclones connected to the ridge of an upper‐tropospheric Rossby wave are the main dynamical drivers of mid‐latitude summer heatwaves. It is, however, unclear to what extent an anomalously low zonal phase speed of the wave in the upper troposphere is necessary for persistent temperature extremes at the surface. Here, we use spectral decomposition to separate fast and slow synoptic‐scale waves. A composite analysis of ERA5 reanalysis data reveals that, while in some regions heatwaves become more frequent during episodes of weak or no phase propagation, temperature extremes in other regions are commonly associated with more rapidly eastward propagating Rossby waves. Reflected in the mean heatwave duration as well, this relationship is possibly linked to a longitudinal phase preference of slow and fast waves or a meridional storm track shift. These findings open up new questions about the influence of mid‐latitude dynamics on temperature extremes. Plain Language Summary: High pressure systems tend to be associated with mid‐latitude summer heatwaves, defined as multiple consecutive hot days. The persistence of heatwaves raises the question whether the associated high pressure system has to be anomalously persistent as well to cause a heatwave. Using a combination of observational data and atmospheric model output that is commonly regarded as ground truth for prediction purposes we find that this is not the case. By re‐distributing the location of on‐average high air pressure, some regions experience an increased heatwave frequency even if the atmospheric circulation is less persistent than usual. Understanding the link between persistent surface temperature extremes and the atmospheric circulation is important for the prediction and projection of extreme events in a warming climate. Key Points: Phase speed of synoptic‐scale waves is crucial for where, but less important for whether heatwaves occurA longitudinal phase preference of slow and fast waves is reflected in the mean heatwave durationChanges in phase speed are linked to a meridional storm track shift [ABSTRACT FROM AUTHOR]

Heat released from soil organic carbon (SOC) decomposition (referred to as microbial heat hereafter) could alter the soil's thermal and hydrological conditions, subsequently modulate SOC decomposition and its feedback with climate. While understanding this feedback is crucial for shaping policy to achieve specific climate goal, it has not been comprehensively assessed. This study employs the ORCHIDEE‐MICT model to investigate the effects of microbial heat, referred to as heating effect, focusing on their impacts on SOC accumulation, soil temperature and net primary productivity (NPP), as well as implication on land‐climate feedback under two CO2 emissions scenarios (RCP2.6 and RCP8.5). The findings reveal that the microbial heat decreases soil carbon stock, predominantly in upper layers, and elevates soil temperatures, especially in deeper layers. This results in a marginal reduction in global SOC stocks due to accelerated SOC decomposition. Altered seasonal cycles of SOC decomposition and soil temperature are simulated, with the most significant temperature increase per unit of microbial heat (0.31 K J−1) occurring at around 273.15 K (median value of all grid cells where air temperature is around 273.15 K). The heating effect leads to the earlier loss of permafrost area under RCP8.5 and hinders its restoration under RCP2.6 after peak warming. Although elevated soil temperature under climate warming aligns with expectation, the anticipated accelerated SOC decomposition and large amplifying feedback on climate warming were not observed, mainly because of reduced modeled initial SOC stock and limited NPP with heating effect. These underscores the multifaceted impacts of microbial heat. Comprehensive understanding of these effects would be vital for devising effective climate change mitigation strategies in a warming world. [ABSTRACT FROM AUTHOR]

The Gulf of St. Lawrence has been nearly free of sea ice in the winter six times in its recorded history, four of which have occurred since 2010. This study examines the inter‐annual variability of sea ice cover characteristics (1969–2024) and winter mixed layer heat content (1996–2024), their sensitivity to fall oceanic conditions (since fall of 1995) and to winter air temperatures. The study finds no relationship between fall oceanic conditions with either the first occurrence of sea ice, maximum seasonal estimated volume or winter mixed layer heat content. However, it shows that the first occurrence of sea ice in the northwestern Gulf is related to the timing of sea surface temperature crossing the 1°C threshold with a lag time of 30–37 days, and with air temperature dropping below −2°C with a lag of 37–44 days; longer lags have weak correlations. The seasonal maximum conditions in area or estimated volume can be estimated by the preceding measurements of the same metrics with a lead time of only 29 days for volume and 36 days for area. The average air temperature over the Gulf between December and February or March is highly correlated to seasonal maximum sea ice area and estimated volume, as well as ice season duration. The six nearly ice‐free winters correspond to the warmest December to February (or December to March) average air temperatures over the Gulf. A warming of >1.9°C–2.4°C (DJFM) or >2.2°C–2.9°C (DJF) above the 1991–2020 climatology leads to nearly ice‐free conditions. Plain Language Summary: The first occurrence and seasonal severity of sea ice in the Gulf of St Lawrence are shown to not be related to early fall ocean conditions. Atmospheric conditions prevalent when water temperature approaches the freezing point are drivers of first occurrence and can be used to predict onset of sea ice in the northwest Gulf with about 37–44 days of lead time. Seasonal sea ice severity metrics (duration, maximum area and estimated volume) are shown to be related to winter air temperatures. The seasonal maximum conditions in area or estimated volume can be estimated by the preceding measurements of the same metrics with a lead time of only 29 days for volume and 36 days for area. Six nearly ice‐free winters correspond to the warmest December to February (or December to March) average air temperatures over the Gulf, providing the thresholds required for future climate warming to result in a nearly ice‐free Gulf of St. Lawrence. Key Points: Seasonal maximum sea ice area and first occurrence are predictable with at most 36–44 days of lead time in the Gulf of St LawrenceSeasonal sea ice severity metrics (duration, maximum area and estimated volume) are shown to be related to winter air temperaturesThe only six nearly ice‐free winters correspond to the warmest winter air temperatures over the Gulf [ABSTRACT FROM AUTHOR]

Diagnosing the role of internal variability over recent decades is critically important for both model validation and projections of future warming. Recent research suggests that for 1980–2022 internal variability manifested as Global Cooling and Arctic Warming (i‐GCAW), leading to enhanced Arctic Amplification (AA), and suppressed global warming over this period. Here we show that such an i‐GCAW is rare in CMIP6 large ensembles, but simulations that do produce similar i‐GCAW exhibit a unique and robust internally driven global surface air temperature (SAT) trend pattern. This unique SAT trend pattern features enhanced warming in the Barents and Kara Sea and cooling in the Tropical Eastern Pacific and Southern Ocean. Given that these features are imprinted in the observed record over recent decades, this work suggests that internal variability makes a crucial contribution to the discrepancy between observations and model‐simulated forced SAT trend patterns. Plain Language Summary: When comparing model simulations of Earth's recent warming to real‐world observations, differences may arise from several factors. Two important factors are the model errors in the simulated response to increased greenhouse gases, and natural fluctuations within the climate system that produced discrepancies between observations and models. Thus, quantifying the role of these natural fluctuations is important for the assessment of model‐observation differences. Previous studies have shown that natural climate variability has depressed global warming and enhanced Arctic warming. By compositing the multi‐decadal trend patterns from CMIP6 simulations in which natural variability warms the Arctic but has a global cooling effect, we find that the majority of these model simulations also produce enhanced warming in the Barents and Kara Seas and cooling in the Tropical Eastern Pacific and Southern Ocean due to natural variability. Since these are the exact features imprinted on observed surface temperature changes over 1980–2022, our work suggests that natural variability is an important component of several noteworthy differences between models and observations. Key Points: Internal variability has enhanced Arctic warming but suppressed global warming over 1980–2022This manifestation of internal variability is rare in model simulations but has a robust global surface air temperature (SAT) trend patternThis internal SAT pattern features warming in the Barents and Kara Sea and cooling of the Tropical Eastern Pacific and Southern Ocean [ABSTRACT FROM AUTHOR]

Thermal regimes of aquatic ecosystems are predicted to change as climate warming progresses over the next century, with high‐latitude and high‐elevation regions predicted to be particularly impacted. Here, we have modelled alpine stream water temperatures from air temperature data and used future predicted air temperature trajectories (representative concentration pathway [rcp] 4.5 and 8.5) to predict future water temperatures. Modelled stream water temperatures have been used to calculate cumulative degree days (CDDs) under current and future climate conditions. These calculations show that degree days will accumulate more rapidly under the future climate scenarios, and with a stronger effect for higher CDD values (e.g., rcp 4.5: 18–28 days earlier [CDD = 500]; 42–55 days earlier [CDD = 2000]). Changes to the time to achieve specific CDDs may have profound and unexpected consequences for alpine ecosystems. Our calculations show that while the effect of increased CDDs may be relatively small for organisms that emerge in spring–summer, the effects for organisms emerging in late summer–autumn may be substantial. For these organisms, the air temperatures experienced upon emergence could reach 9°C (rcp 4.5) or 12°C (rcp 8.5) higher than under current climate conditions, likely impacting on the metabolism of adults, the availability of resources, including food and suitable oviposition habitat, and reproductive success. Given that the movement of aquatic fauna to the terrestrial environment represents an important flux of energy and nutrients, differential changes in the time periods to achieve CDDs for aquatic and terrestrial fauna may de‐couple existing predator–prey interactions. [ABSTRACT FROM AUTHOR]

The accurate partitioning of precipitation is important for snowpack and streamflow simulations in mountainous regions. However, most hydrologic models employ a partitioning method based on near‐surface air temperature (Ta) and the sensitivity of hydrologic simulations to the selection of the precipitation partitioning method (PPM) under climate change has been underexplored. To address this, we compared simulations using two PPMs, a conventional Ta‐based scheme and a wet‐bulb temperature (Tw)‐based approach (TA and TW) with the Variable Infiltration Capacity model. Our study focused on the Colorado River Basin (CRB) which is vulnerable to future snowfall and streamflow reductions due to climate warming. Historical simulations demonstrated the improved performance of the TW scheme in simulating snowfall fraction (SF) and snow water equivalent (SWE) in relation to in situ observations and a gridded SWE product. Subsequently, we evaluated the influence of the PPM selection on snowpack and streamflow projections from eight climate models under two emissions scenarios. The ensemble median results revealed more substantial decline in annual SF with the TW scheme as compared to the TA method (−12% vs. −9%) from the historical (1976–2005) to the far future (2066–2095) period, especially at lower elevations. Hydrologic simulations showed that the TA scheme underestimated reductions in SWE and streamflow (Q) under warming as compared to the TW scheme. This finding has important implications on future projections for the CRB and in other mountainous basins where climate warming can shift conditions from snowfall to rainfall. Key Points: The precipitation partitioning method (PPM) impacts the simulation of snowfall and snowpack dynamics in the Colorado River Basin (CRB)The selection of PPM also determines the sensitivity of streamflow projections in the CRB under climate change scenariosSpatial variations in the impact of PPM reveal distinct climate change sensitivities in high and low elevation regions in the CRB [ABSTRACT FROM AUTHOR]

The Arctic sea ice cover has decreased rapidly over the last few decades both in extent and thickness. Here we present multi‐year (2013–2022) observations of sea ice thickness in the northwestern Barents Sea based on Upward Looking Sonar measurements and show that the winter sea ice has become thicker over the last decade. Sea ice thickness from the Pan‐Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) reproduces both the observed variability and recent 10‐year trend and shows that this thickening (0.24 m decade−1) has not been seen since the 1990s. Using PIOMAS we find that the recent increase in sea ice thickness can be explained by increased sea ice freezing as a result of lower temperatures in the ocean and in the atmosphere. The recent thickening is set in the context of a long‐term thinning trend, with PIOMAS showing much thinner ice now than in the 1980s. Plain Language Summary: The Arctic sea ice cover is becoming smaller and thinner due to global warming. We have measured sea ice thickness in the Barents Sea since 2013, and find that the ice thickness has increased since the measurements were initiated, contrary to what we would expect in a warming world. The Arctic sea ice cover can, however, increase for periods typically up to a decade due to natural climate variability. We find that increased sea ice formation due to lower ocean and air temperatures has caused the recent thickening of the ice cover. We also find that the Barents Sea ice thickness has decreased since the 1980s, and despite the recent thickening, the ice cover is much thinner now than it used to be. Key Points: Upward Looking Sonar measurements in the Barents Sea show increased sea ice thickness during the last decadeIn an ice‐ocean reanalysis (PIOMAS) the recent thickening is due to increased ice freezing, associated with lower ocean and air temperaturesThe long‐term thickness trend is negative, meaning that despite recent thickening, ice is now much thinner than in the 1980s [ABSTRACT FROM AUTHOR]

To evaluate future changes in the climate system, the outputs from coarse‐resolution global climate models (GCMs) need to be downscaled to a finer scale, making them more directly applicable for impact assessment. Here we focus on examining the projected changes of three key climate variables (precipitation, air temperature, and wet bulb temperature) across Arizona (south‐western United States). We use daily outputs from GCMs from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and bias correct and downscale them to a 4‐km resolution. Through leave‐one‐out cross‐validation, we compare various bias correction methods and identify that the empirical quantile mapping approach performs the best regardless of the climate variable. Then, we analyse the projected bias‐corrected outputs for two future periods (Mid‐of‐Century: 2015–2048; End‐of‐Century: 2067–2100) with respect to the 1981–2014 period, under four shared socioeconomic pathway scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5). Our results show that Arizona's climate is projected to become overall warmer and wetter, more so towards the end of this century and for higher emission scenarios. Additionally, our findings project an increase in wet bulb temperature and cooling degree days, implying the ongoing warming climate's potential impacts on public health and the economy. These results provide a baseline understanding of climate change impacts in the state and highlight the projected changes in the future in response to the climate scenarios. [ABSTRACT FROM AUTHOR]

Under global warming, the summer surface air temperature (SAT) change signal in the northern mid‐latitudes is generally the most significant, while the SAT change in North China (NC) shows distinct local characteristics. Using simulations from the Coupled Model Intercomparison Project Phase 6 and observation from Berkeley Earth Surface Temperature, this study reveals an unusually weak signal of summer SAT change in NC since the 1960s. This uniquely weak signal can be attributed to the small net contribution of external forcings, mainly from anthropogenic greenhouse gases (GHG) and aerosols (AA). Compared to other land regions in the same latitudinal band, the GHG‐induced warming was weaker and AA‐induced cooling was stronger in NC, resulting in the weakest SAT change signal and thus the lowest signal‐to‐noise ratio. This weaker GHG‐induced warming plays a more important role in the SAT change difference between NC and other land regions in the same latitudinal zone. Under different emission scenarios in the future, the signal‐to‐noise ratio in NC will become as large as those in the other land regions in the same latitudinal band and the northern hemisphere, which is partly due to the smaller relative differences in the SAT change signal between NC and the other two regions. The projections of SAT change indicate that climate change in NC will probably become more violent and vulnerable. [ABSTRACT FROM AUTHOR]

An increase in winter air temperature can amplify snowmelt and sublimation in mountain regions with implications to water resources and ecological systems. Winter Warm Spells (WWS) are defined as a winter period (December to February, DJF) of at least 3 consecutive days with daily maximum temperature anomaly above the 90th percentile (using a moving‐average of 15 days between 2001 and 2013). We calculate WWS for every 4‐km grid cell within an atmospheric model over western North America to characterize WWS and analyze snow ablation and their changes in a warmer climate. We find that days with ablation during WWS represent a small fraction of winter days (0.6 days), however, 49% of total winter ablation (33.4 mm/DJF) occurs during WWS. Greater extreme ablation rates (99th percentile) occur 18% more frequently during WWS than during non‐WWS days. Ablation rates during WWS in humid regions are larger (9 mm d−1) than in dry regions (7 mm d−1) in a warmer climate, which can be explained by differences in the energy balance and the snowpack's cold content. We find that warmer (0.8°C), longer (1.8 days) and more frequent (3.7 more events) WWS increase total winter ablation (on average 109% or 18 mm/DJF) in a warmer climate. Winter melt during WWS in warm and humid places is expected to increase about 3 times more than in the cold and dry region. This study provides a comprehensive description of WWS and their impact on snowpack dynamics, which is relevant to reservoir operations and water security. Plain Language Summary: Extreme maximum winter temperatures (Winter Warm Spells, WWS) can affect the snow in winter by increasing snowmelt, with consequences for mountain water supplies. In this study we quantify snowpack response to WWS in the mountains of western North America and its sensitivity to a warmer future climate using numerical models, observations, and statistical tools. We find that 49% of snow lost in winter happens during WWS, despite having only 0.6 days with WWS per winter. Across the mountains, the humid climatic regions are more affected by WWS than arid regions. We show that snowpack ablation during WWS will increase in a warmer climate, which will put more stress on reservoir and water security planning. Key Points: Winter Warm Spells account for 49% of snowpack winter ablation (16.5 mm), despite only representing 0.6 days on averageHistorical Winter Warm Spells increase in frequency (3.7 more events), duration (1.8 days) and magnitude (0.8°C) in a warmer climateWinter snow ablation driven by melt (93.6%) is expected to increase in a warmer climate (147%), especially in humid regions [ABSTRACT FROM AUTHOR]

Humid heatwaves, characterized by high temperature and humidity combinations, challenge tropical societies. Extreme wet‐bulb temperatures (TW) over tropical land are coupled to the warmest sea surface temperatures by atmospheric convection and wave dynamics. Here, we harness this coupling for seasonal forecasts of the annual maximum of daily maximum TW (TWmax). We develop a multiple linear regression model that explains 80% of variance in tropical mean TWmax and significant regional TWmax variances. The model considers warming trends and El Niño and Southern Oscillation indices. Looking ahead, the strong‐to‐very‐strong El Niño at the end of 2023, with an Oceanic Niño Index of ∼2.0, suggests a 2024 tropical land mean TWmax of 26.2°C (25.9–26.4°C), and a 68% chance (24%–94%) of breaking existing records. This method also predicts regional TWmax in specific areas. Plain Language Summary: The heat and humidity in the tropics can be particularly challenging for people to stay comfortable and healthy. This combination of heat and moisture is described using a measure called the wet‐bulb temperature (TW). We found that these extremely humid and hot conditions on land can be predicted about 5 months in advance using a physics‐based statistical model. The forecast is possible because the peak of El Niño comes before the peak in the warmest sea surface temperatures, which affects the maximum TW on land. This prediction can help tropical societies to better prepare for extreme heat. Key Points: Tropical wet‐bulb temperatures (TW) peak around 5 months after El Niño wintersA multiple linear regression model considering the El Niño‐Southern Oscillation index and the long‐term warming trend effectively explains TWmax variabilityOur model quantifies the likelihood of strong El Niño and human‐induced warming pushing TWmax to record‐breaking levels [ABSTRACT FROM AUTHOR]

The Arctic is notable as a region where the greatest rate of increase in precipitation associated with global warming is anticipated. The Arctic precipitation simulated by the Coupled Model Intercomparison Project Phase 6 models showed a strong increasing trend since the 1980s. We found that the forcing factor of the trend is a combination of the continued strengthening of greenhouse gas forcing and the leveling off of aerosol forcing dominated in earlier periods. From an energetic perspective, we found that the increased atmospheric radiative cooling and reduced sensible heat transport from lower latitudes contributed equally to the recent increase in Arctic precipitation. The combination of these two energetic factors suggests a doubling of the Arctic amplification factor for precipitation relative to that for temperature. Future Arctic precipitation will change in proportion to the temperature change, and the fractional contributions of the energetic factors will remain stable across various scenarios. Plain Language Summary: The Arctic region is inherently a low‐precipitation area. However, because of global warming, precipitation is expected to increase substantially in the Arctic region compared with the global average when viewed as a percentage change from the original precipitation. This severely affects climate change in the Arctic environment. The latest climate model simulations show that there has been a rapid increase in precipitation in the Arctic region in recent decades. The driving factors behind the rapid increase are the effects of the accelerating growth of greenhouse gas concentrations, which were previously suppressed by the increasing anthropogenic aerosol emissions before the 1980s. Based on the heat budget of the atmosphere, we identified important factors contributing to these precipitation changes. These include enhanced radiative cooling (responding locally to increased air temperature) and reduced heat transport from lower latitudes due to greater temperature increases at higher latitudes. Future precipitation will change in proportion to the temperature change while maintaining consistent fractional contributions across different scenarios. Key Points: Trends in Arctic precipitation in the recent and future decades are examined from multimodel simulationsThe recent rapid increase is driven by accelerating greenhouse gas concentrations and plateauing growth in anthropogenic aerosol emissionsIncreased radiative cooling and reduced poleward sensible heat transport equally contributed to the Arctic precipitation changes [ABSTRACT FROM AUTHOR]

Aim: Squamate fitness is affected by body temperature, which in turn is influenced by environmental temperatures and, in many species, by exposure to solar radiation. The biophysical drivers of body temperature have been widely studied, but we lack an integrative synthesis of actual body temperatures experienced in the field, and their relationships to environmental temperatures, across phylogeny, behaviour and climate. Location: Global (25 countries on six continents). Taxa: Squamates (210 species, representing 25 families). Methods: We measured the body temperatures of 20,231 individuals of squamates in the field while they were active. We examined how body temperatures vary with substrate and air temperatures across taxa, climates and behaviours (basking and diel activity). Results: Heliothermic lizards had the highest body temperatures. Their body temperatures were the most weakly correlated with substrate and air temperatures. Body temperatures of non‐heliothermic diurnal lizards were similar to heliotherms in relation to air temperature, but similar to nocturnal species in relation to substrate temperatures. The correlation of body temperature with air and substrate temperatures was stronger in diurnal snakes and non‐heliothermic lizards than in heliotherms. Body‐substrate and body‐air temperature correlations varied with mean annual temperatures in all diurnal squamates, especially in heliotherms. Thermal relations vary with behaviour (heliothermy, nocturnality) in cold climates but converge towards the same relation in warm climates. Non‐heliotherms and nocturnal species body temperatures are better explained by substrate temperature than by air temperature. Body temperature distributions become left‐skewed in warmer‐bodied species, especially in colder climates. Main Conclusions: Squamate body temperatures, their frequency distributions and their relation to environmental temperature, are globally influenced by behavioural and climatic factors. For all temperatures and climates, heliothermic species' body temperatures are consistently higher and more stable than in other species, but in regions with warmer climate these differences become less pronounced. A comparable variation was found in non‐heliotherms, but in not nocturnal species whose body temperatures were similar to air and substrate irrespective of the macroclimatic context. [ABSTRACT FROM AUTHOR]

This article explores the thermal acclimation of ecosystem processes to climate warming, with a focus on plant phenology and photosynthesis. The study finds that plant phenology responses to warming level off over time, suggesting acclimation to higher temperatures. The article also discusses the thermal optimality and acclimation of ecosystem carbon cycling, indicating that previous interpretations may have overestimated the positive feedbacks between climate change and the carbon cycle. The rates of response to warming may vary among different life forms, with herbaceous species potentially adapting more rapidly than woody plants. The study suggests that other limiting factors, such as soil water and nutrient availability, may become more important and constrain phenological responses to rising temperatures over longer periods. Overall, the findings suggest that shifts in plant phenology and ecosystem processes may be less significant than anticipated as climate warming continues. The article emphasizes the need for further research, particularly whole-ecosystem field experiments that include both above- and belowground warming, to better understand thermal acclimation and its effects on different organisms and ecological processes. These experiments could provide insights into the pace and factors influencing acclimation, as well as the long-term effects on species composition and soil conditions. The results could also help improve models and reduce uncertainties in predicting the response of terrestrial ecosystems to warming. [Extracted from the article]

Global warming is destabilizing the cryosphere, with consequences for glaciers, permafrost, sea ice and lake ice. Polar lakes have short ice‐free seasons, and small changes in ice cover duration have the potential to provoke alterations to ecosystem structure. However, these lakes are understudied, and the consequences for mixing regimes, thermal structures and biogeochemical processes remain unclear. We measured three annual cycles of dissolved oxygen, temperature and specific conductivity in a lake at ∼83°N to investigate limnological processes and their interannual variability. There were sharp interannual contrasts in lake dynamics, with state shifts in mixing, stratification and oxygen regimes due to air temperature variability and meteorological events. We also observed unusual thermal profiles that were associated with solute gradients. These striking differences underscore the sensitivity of high Arctic lakes to interannual variations in meteorological forcing, and their susceptibility to regime shifts in response to ongoing global change. Plain Language Summary: Lakes are biodiversity refuges, climate regulators and providers of ecosystem services. High Arctic lakes experience brief summer ice‐free periods and their annual dynamics remain largely unexplored despite their location in one of the most rapidly warming regions on Earth. In particular, patterns of thermal structure and oxygen dynamics have rarely been measured. We studied three complete annual cycles in a coastal lake less than 100 km south of the northernmost land on Earth. The observed limnological dynamics highlight the potential for rapid regime shifts in polar lakes and underline their sensitivity to interannual differences in environmental conditions. Key Points: Pronounced shifts in lake oxygen and temperature dynamics occur due to interannual air temperature variation and meteorological episodesDivergent annual trajectories in lake structure and functioning highlight the vulnerability of high Arctic lakes to climate change [ABSTRACT FROM AUTHOR]

Question: Ecological indicator values (EIVs) reflect species' optimal conditions on an environmental gradient, such as temperature. Averaged over a community, they are used to quantify thermophilization stemming from climate change, i.e. the reshuffling of communities toward more warm‐adapted species. In forests, understorey plant communities do not keep up with global warming and accumulate a climatic debt. Although the causes are still debated, this thermal lag may be partly explained by forest microclimate buffering. For the first time, we test whether community means of EIVs are able to capture microclimate (here, under forest canopies) temperature across, or also within forests. Location: 157 forest plots across three French deciduous forests covering a large macroclimatic gradient. Methods: To assess whether EIVs can be used to infer the mean and range of microclimate temperature in forests, we measured understorey air temperature for ca. 1 year (10 months) with sensors located 1 m above the ground. We surveyed bryophytes and vascular plants within 400‐m2 plots, and computed floristic temperature from ordinal‐scale EIVs (Ellenberg, Julve) and degree‐scale EIVs (ClimPlant, Bryophytes of Europe Traits) for both temperature and continentality, i.e. temperature annual range. Finally, we fitted linear models to assess whether EIVs could explain the mean and range of microclimate temperature in forests. Results: Vascular plant and bryophyte communities successfully reflected differences in mean annual temperatures across forests but largely failed to do so for microclimate variation within forests. Bryophytes did not perform better than vascular plants to infer microclimate conditions. The annual range of microclimate temperatures was poorly associated with ordinal‐scale EIVs for continentality but was positively correlated with degree‐scale EIVs for annual range within lowland forests, especially for vascular plant communities. Conclusion: Overall, the capabilities of EIVs to infer microclimate was inconsistent. Refined EIVs for temperature are needed to capture forest microclimates experienced by understorey species. [ABSTRACT FROM AUTHOR]

The relative importance of oceanic modes to global surface air temperature (SAT) and terrestrial precipitation during 1934–2020 was investigated using a variety of statistical and dynamical system methods. Through singular spectrum analysis, we present the distribution of decadal (10–20‐year), multidecadal (20–50‐year), and secular (>50‐year) variabilities of global SAT and terrestrial precipitation anomalies. Three sea surface temperature modes were identified by singular value decomposition that affect the low‐frequency variabilities of global SAT and terrestrial precipitation anomalies—namely, global warming (GW), the Interdecadal Pacific Oscillation (IPO), and the Atlantic Multidecadal Oscillation (AMO). The relative importance GW, the IPO, and the AMO in SAT and terrestrial precipitation was obtained through a normalized multivariate information flow analysis. Besides a high information flow percentage (60%) from GW to global SAT, especially over the northern Indian Ocean and tropical West Pacific, information flow from the AMO to the northwestern Pacific was also found. In terms of terrestrial precipitation, a large area with a wet trend was found over Eurasia at mid‐to‐high latitudes, and this trend was especially remarkable in the boreal winter half‐year (November–April), as compared with that in the boreal summer half‐year (May–October). By employing artificial neutral networks with a self‐organized map to cluster the key patterns of vertically integrated water vapour flux, we found that the synoptic circulation related to the wet trend is characterized by westerly flow that transports water vapour from the northeastern Atlantic to Eurasia, which is favourable for precipitation there both in the boreal winter and summer half‐year. [ABSTRACT FROM AUTHOR]

Peatlands are sources of bioaccumulating neurotoxin methylmercury (MeHg) that is linked to adverse health outcomes. Yet, the compounding impacts of climate change and reductions in atmospheric pollutants on mercury (Hg) export from peatlands are highly uncertain. We investigated the response in annual flow‐weighted concentrations (FWC) and yields of total‐Hg (THg) and MeHg to cleaner air and climate change using an unprecedented hydroclimatic (55‐year; streamflow, air temperature, precipitation, and peatland water tables), depositional chemistry (21‐year; Hg and major ions), and streamwater chemistry (∼17‐year; THg, MeHg, major ions, total organic carbon, and pH) data sets from a reference peatland catchment in Minnesota, USA. Over the hydroclimatic record, annual mean air temperature increased by ∼1.8°C, while baseflow and the efficiency that precipitation was converted to runoff (runoff ratio) decreased. Concurrently, precipitation‐based deposition of sulfate and Hg declined, where wet Hg deposition declined by ∼3–4 μg Hg m−2. Despite declines in wet Hg deposition over the study period, the catchment accumulated on average 0.04 ± 0.01 g Hg ha−1 yr−1 based on wet Hg deposition minus THg yield alone. Annual MeHg FWC was positively correlated with mean annual air temperatures (p = 0.03, r = 0.51), runoff ratio (p < 0.0001, r = 0.76), and wet Hg deposition concentration (p < 0.0001, r = 0.79). Decreasing wet Hg deposition and annual runoff ratios counterbalanced increased peatland MeHg production due to higher air temperatures, leading to an overall decline in streamwater MeHg FWC. Streamwater MeHg export may continue to decrease only as long as declines in runoff ratio and wet Hg deposition persistently outpace effects of increased air temperature. Plain Language Summary: Climate change and cleaner air are unequivocally altering the movement of toxic mercury and methylmercury. Using long‐term and broad environmental measurements, a stream fed by a peatland exhibited decreased methylmercury levels that correlated with lower wet mercury deposition concentration and lower net water yields from the catchment (runoff ratio), which offsets potential increases of methylmercury due to elevated air temperatures. As such, methylmercury export from peatland catchments will likely continue to decrease over time if climate change continues to accelerate the reduction of runoff ratios and atmospheric wet mercury deposition further decreases. Adaptation to future climate and environmental changes would greatly benefit from additional and longer‐integrated multidisciplinary data sets. Without such long‐term and integrated measures critical insights, such as those gained from this study, would not be possible. Key Points: Lower streamwater methylmercury concentrations and yields due to compounding effects of climate change and cleaner airLower wet atmospheric mercury deposition and runoff ratios offset higher air temperatures, resulting in lower methylmercury concentrationsHeadwater peatland catchments will continue to be net sinks of total mercury; thus, we may not see a net flushing of anthropogenic mercury [ABSTRACT FROM AUTHOR]

Reproductive systems play an important role in the ecological function of species, but little is known about how climate change, such as global warming, may affect the reproductive systems of microbes. In this study, 116 Phytophthora infestans isolates sampled from five different altitudes along a mountain were evaluated under five temperature regimes to determine the effects of historical and experimental temperature on the reproductive system of the pathogen. Both altitude, a proxy for historical pathogen adaptation to temperature, and temperature used in the experiment affected the sexual reproduction of the pathogen, with experimental temperature, that is, contemporary temperature, playing a role several times more important than historical temperature. Furthermore, the potential of sexual reproduction, measured by the number of oospores quantified, increased with the temperature breadth (i.e., difference between the highest and lowest temperature at which sexual reproduction takes place) of the pathogen and reached the maximum at the experimental temperature of 21°C, which is higher than the annual average temperature in many potato‐producing areas. The results suggest that rising air temperature associated with global warming may increase the potential of sexual reproduction in P. infestans. Given the importance of sexuality in pathogenicity and ecological adaptation of pathogens, these results suggest that global warming may increase the threat of P. infestans to agricultural production and other ecological services and highlight that new epidemiological strategies may need to be implemented for future food security and ecological resilience. [ABSTRACT FROM AUTHOR]

A two‐fold enhancement in the sensitivity of atmospheric CO2 growth rate (CGR) to tropical temperature interannual variability (ΓCGRT$$ {\varGamma}_{\mathrm{CGR}}^T $$) till early 2000s has been reported, which suggests a drought‐induced shift in terrestrial carbon cycle responding temperature fluctuations, thereby accelerating global warming. However, using six decades long atmospheric CO2 observations, we show that ΓCGRT$$ {\varGamma}_{\mathrm{CGR}}^T $$ has significantly declined in the last two decades, to the level during the 1960s. The ΓCGRT$$ {\varGamma}_{\mathrm{CGR}}^T $$ decline begs the question of whether the sensitivity of ecosystem carbon cycle to temperature variations at local scale has largely decreased. With state‐of‐the‐art dynamic global vegetation models, we further find that the recent ΓCGRT$$ {\varGamma}_{\mathrm{CGR}}^T $$ decline is barely attributed to ecosystem carbon cycle response to temperature fluctuations at local scale, which instead results from a decrease in spatial coherence in tropical temperature variability and land use change. Our results suggest that the recently reported loss of rainforest resilience has not shown marked influence on the temperature sensitivity of ecosystem carbon cycle. Nevertheless, the increasing extent of land use change as well as more frequent and intensive drought events are likely to modulate the responses of ecosystem carbon cycle to temperature variations in the future. Therefore, our study highlights the priority to continuously monitor the temperature sensitivity of CGR variability and improve Earth system model representation on land use change, in order to predict the carbon–climate feedback. [ABSTRACT FROM AUTHOR]

Sea turtles are vulnerable to climate change since their reproductive output is influenced by incubating temperatures, with warmer temperatures causing lower hatching success and increased feminization of embryos. Their ability to cope with projected increases in ambient temperatures will depend on their capacity to adapt to shifts in climatic regimes. Here, we assessed the extent to which phenological shifts could mitigate impacts from increases in ambient temperatures (from 1.5 to 3°C in air temperatures and from 1.4 to 2.3°C in sea surface temperatures by 2100 at our sites) on four species of sea turtles, under a "middle of the road" scenario (SSP2‐4.5). Sand temperatures at sea turtle nesting sites are projected to increase from 0.58 to 4.17°C by 2100 and expected shifts in nesting of 26–43 days earlier will not be sufficient to maintain current incubation temperatures at 7 (29%) of our sites, hatching success rates at 10 (42%) of our sites, with current trends in hatchling sex ratio being able to be maintained at half of the sites. We also calculated the phenological shifts that would be required (both backward for an earlier shift in nesting and forward for a later shift) to keep up with present‐day incubation temperatures, hatching success rates, and sex ratios. The required shifts backward in nesting for incubation temperatures ranged from −20 to −191 days, whereas the required shifts forward ranged from +54 to +180 days. However, for half of the sites, no matter the shift the median incubation temperature will always be warmer than the 75th percentile of current ranges. Given that phenological shifts will not be able to ameliorate predicted changes in temperature, hatching success and sex ratio at most sites, turtles may need to use other adaptive responses and/or there is the need to enhance sea turtle resilience to climate warming. [ABSTRACT FROM AUTHOR]

Since 1980, the Arctic surface has warmed four times faster than the global mean. Enhanced Arctic warming relative to the global average warming is referred to as Arctic Amplification (AA). While AA is a robust feature in climate change simulations, models rarely reproduce the observed magnitude of AA, leading to concerns that models may not accurately capture the response of the Arctic to greenhouse gas emissions. Here, we use CMIP6 data to train a machine learning algorithm to quantify the influence of internal variability in surface air temperature trends over both the Arctic and global domains. Application of this machine learning algorithm to observations reveals that internal variability increases the Arctic warming but slows global warming in recent decades, inflating AA since 1980 by 38% relative to the externally forced AA. Accounting for the role of internal variability reconciles the discrepancy between simulated and observed AA. Plain Language Summary: The Arctic has been warming four times as quickly as the global mean since 1980. This so‐called Arctic Amplification (AA) has unprecedented impacts on Arctic environments and livelihoods. AA is robustly simulated by climate models, but simulations rarely reproduce the observed levels of AA for 1980–2022. This may be due to a model misrepresentation of the Arctic's sensitivity to increasing greenhouse gases. Another possibility is that the large, observed value of AA is inflated by natural fluctuations in the climate system. Here, we use machine learning to quantify the contribution of natural fluctuations to observed AA. We show that natural fluctuations have inflated AA by 38%, and thus reconcile model‐observation differences and suggest that the observed large AA over 1980 to present would not persist into the future. Key Points: Internally generated and externally forced temperature trends over the Arctic and globe can be partitioned using machine learning methodsInternal variability has enhanced Arctic warming while damping global warming over 1980‐2022Accounting for internal variability in observations reconciles discrepancies between simulated and observed Arctic Amplification [ABSTRACT FROM AUTHOR]

The unprecedented 2021 June‐July heatwave in Western North America resulted in record‐breaking human‐perceived heat stress across the region, measured by the humidex considering both air temperature and humidity. During extended summer (June‐September), both 95th percentiles of daily maximum humidex (HX95) and air temperature (TX95) have increased over the 1940–2022 period, with even faster intensification in the last two decades (2001–2022). HX95 has increased more than TX95 because of the positive monotonic nonlinear relationship between humidex and air temperature at a given level of relative humidity. The Canadian Earth System Model version 5 (CanESM5) projects a larger increase in human‐perceived heat stress than air temperature across the region under low to high emission scenarios (HX95 increases 4.40–7.04°C and TX95 increases 2.92–4.65°C between 1981–2010 and 2041–2060). Moreover, CanESM5 projects significant increases in the frequency of HX and TX conditions that exceed the levels reached in 2021 under intermediate and high emission scenarios. Plain Language Summary: Using humidex, a measure that combines air temperature and humidity, we assessed the human‐perceived heat stress during the record‐breaking 2021 summer heatwave in Western North America. The 2021 heatwave broke records for both air temperature and humidex, and these two measures have been increasing in the past decades. The heatwave was drier than usual due to high pressure in the atmosphere, clear skies, and more heat warming up the air instead of evaporating water. Humidex will rise more than air temperature under various emission scenarios, making people feel even hotter in the region. The climate model used suggests that humidex values and temperatures that exceed the levels observed in 2021 will happen much more often and be much more intense across the region in the future, with estimates of three to ten times for humidex and two to seven times for air temperature more frequent under intermediate to high emission scenarios by the end of the century. However, the likelihood of extreme humidex in dry conditions, as observed in 2021, will remain low, like historical levels. Key Points: Unprecedented 2021 heatwave in Western North America resulted in record‐breaking human‐perceived heat stress, considering both air temperature and humidityExtreme human‐perceived heat stress increased at a faster rate than extreme air temperature, both showing rapid increases in recent decadesFor events exceeding 2021 level, a larger future increase in extreme human‐perceived heat stress is projected compared to air temperature [ABSTRACT FROM AUTHOR]

During the past few decades, the climate over the entire TP changed obviously with general warming and the decreasing trends in wind speed and air humidity. As an important hydrological process of mass losses on the TP glaciers, especially during the cold period, sublimation may be influenced deeply by the climate changes. Therefore, it is imperative to identify the crucial factors controlling and limiting glacier sublimation and analyze its possible changes in the future. The sublimation on a flat‐topped glacier of TP was found to be more intense in spring (0.41 mm d−1) and autumn (0.34 mm d−1) and weak in winter (0.27 mm d−1) and summer (0.16 mm d−1). At yearly scale, sublimation was most sensitive to the surface temperature, followed by air temperature and humidity, and was relatively insensitive to wind speed. However, the main influencing factor was air humidity during summer, showing a strong inhibition on sublimation. The very low surface temperature was the most crucial variable limiting winter sublimation with the highest sensitivity coefficient than other variables. Current sublimation was also found to be more sensitive to the increasing temperature than the decreased air humidity and wind speed. If the climate trends continue, and the glacier climate has the relatively consistent change trend with that of entire TP, glacier sublimation will be more likely to increase, especially during winter. Plain Language Summary: The climate warming trend in the TP has been found to be more sensitive and accelerated since the end of last century. Our study found that, on the August‐one glacier, the very high air humidity and low surface temperature were the most crucial variables limiting summer and winter sublimation, respectively. The glacier sublimation was significantly more sensitive to the surface and air temperature than air humidity and wind speed at yearly scale. With a general warming and the decreasing trends in wind speed and air humidity over the entire TP, sublimation will be more likely to increase as the temperature rises on this glacier, especially during winter. Key Points: Very high air humidity and low surface temperature were the most crucial variables limiting summer and winter sublimation, respectivelyGlacier sublimation was significantly more sensitive to the surface and air temperature than air humidity and wind speed at yearly scaleUnder climate warming, sublimation will be more likely to increase as the temperature rises on this glacier, especially during winter [ABSTRACT FROM AUTHOR]

Summary: Climate warming advances the onset of tree growth in spring, but above‐ and belowground phenology are not always synchronized. These differences in growth responses may result from differences in root and bud dormancy dynamics, but root dormancy is largely unexplored.We measured dormancy in roots and leaf buds of Fagus sylvatica and Populus nigra by quantifying the warming sum required to initiate above‐ and belowground growth in October, January and February. We furthermore carried out seven experiments, manipulating only the soil and not air temperature before or during tree leaf‐out to evaluate the potential of warmer roots to influence budburst timing using seedlings and adult trees of F. sylvatica and seedlings of Betula pendula.Root dormancy was virtually absent in comparison with the much deeper winter bud dormancy. Roots were able to start growing immediately as soils were warmed during the winter. Interestingly, higher soil temperature advanced budburst across all experiments, with soil temperature possibly accounting for c. 44% of the effect of air temperature in advancing aboveground spring phenology per growing degree hour.Therefore, differences in root and bud dormancy dynamics, together with their interaction, likely explain the nonsynchronized above‐ and belowground plant growth responses to climate warming. [ABSTRACT FROM AUTHOR]

Extreme thermal conditions have been known for a long time as is evidenced by the oldest preserved historical accounts referring to weather. However, direct data, that is, air temperature measurements, which began in Europe in the 17th century, are the only reliable source of information. They provide insight into how climate evolved over the characteristic period of the climate timeline known as the Little Ice Age. This study focuses on extreme climatic phenomena, referred to here as exceptionally cold (EC) and exceptionally warm (EW) months and seasons that occurred in the early instrumental period (until 1830). The research is based on average monthly air temperature values (of different lengths) from five meteorological stations in Europe. The Central England Temperature series (CET) offers the longest series that spans 172 years whereas Padua has the shortest, 57 years. Consequently, the year 1659, which is the start date of the Central England Temperature series, marks the beginning of the study period for the research presented in this article. Thermally anomalous periods are identified based on the standard deviation of the average temperature from the corresponding long‐term average (1831–2020). The highlights of the study include the identification of the pronounced prevalence at all five stations of EC months and seasons when compared to EW months and seasons, especially in Western Europe (CET) during the Maunder Minimum. The study also finds a lack of synchronicity in the timing of the anomalous periods under investigation in the different parts of Europe. [ABSTRACT FROM AUTHOR]

In October 2023, Scotland experienced heavy rainfall and flooding due to an atmospheric river and a quasi-stationary front. This event was unusual and different from previous flood events in Scotland. The flooding caused widespread damage, including landslides, road closures, and loss of crops. The synoptic meteorological situation involved a continuous advection of a humid air mass and a temperature and humidity contrast across the front. It is important to note that extreme precipitation events like this may become more severe in a warmer climate. [Extracted from the article]

Freshwater availability is the litmus test of the ongoing global warming, but local effects in relation to larger scale behaviours are often ambiguous. In this study, 19 indicators derived by historical rainfall and temperature records have been used to reconstruct climatic trends over the Umbria region (central Italy). The scenario emerging from observations of the last 70–100 years consists in increasing air temperatures and decreasing yearly precipitation depths, which are differently distributed over the 12 months with respect to the past. As a second step, the response in terms of freshwater availability has been assessed by analysing runoff and groundwater records. A clear reduction in yearly water volumes flowing through the outlet stations of five pilot basins during the last century (1927–2020) has been found, quantified in a median loss rate of equivalent surface water thickness of −1.62 mm/year. Monthly mean groundwater levels show a slight increasing trend for most of the monitoring stations, but such an analysis has been carried out over a limited and more recent period (2006–2020). Hence, it can be affected by the uncertainty commonly associated to the interpretation of trend analyses referring to short temporal windows. This last critical point is strengthened by an analysis of the runoff volume limited to the period 2006–2020 from which, in contrast with the results provided by the aforementioned long‐term investigation, an increasing trend has been derived. [ABSTRACT FROM AUTHOR]

This study analyzes the long‐term observed changes of mean (Tmean), maximum (Tmax) and minimum (Tmin) air temperatures, relative humidity (RH) and vapour pressure deficit (VPD) at different elevation ranges across Bolivia from 1950 to 2019. The linear trends in air temperature series present a significant increase, with no substantial seasonal or spatial differences. On an annual basis, RH exhibited a non‐significant decrease (−0.08% decade−1), while VPD showed a significant increase (0.01 hPa decade−1) (p < 0.05). Although prior research has suggested that highland elevations experience faster warming than the global average, we have not identified a distinct correlation between elevation gradients and differential warming rates in Bolivia. Future research could investigate elevation‐dependent climate trends by examining seasonal and monthly patterns of climatic variables in relation to topographical gradients in various highland regions. [ABSTRACT FROM AUTHOR]

The observed Eurasian winter surface cooling from the 1990s to the early 2010s, which is contrary to global warming, has been extensively studied. Previous studies revealed that the surface cooling trend has significantly weakened in the past decade. Based on large‐ensemble simulations, this study reveals that the weakening of Eurasian surface cooling is primarily driven by the atmospheric internal variability, which coincides with the weakening of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric cooling. Negative Arctic Oscillation (−AO) and Ural blocking (UB) in combination dominate the intensity of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric cooling. In the future, there is a possibility that the severe Eurasian cooling trend with comparable magnitude to that during 1990–2013 may reemerge accompanied with Arctic mid‐tropospheric warming, in response to the decadal strengthening of −AO and UB. This may occur before the 2050s, when the atmospheric internal variability is able to overwhelm the effects of greenhouse gases. Plain Language Summary: The significant Eurasian surface cooling trend observed in winters from the 1990s to the early 2010s has significantly weakened in the past decade. It coincides with the weakened trends of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric cooling. In a warming world, we suggest that the weakening of Arctic mid‐tropospheric warming and Eurasian mid‐tropospheric and surface cooling are primarily caused by the atmospheric internal variability. The weakened trends of negative Arctic Oscillation (−AO) and Ural blocking (UB) in recent years contribute to the weakened trends of Arctic mid‐tropospheric warming and Eurasian cooling. There is a possibility that the atmospheric internal variability may overwhelm the effects of increasing greenhouse gases (GHG) sometime before the 2050s, though the increasing GHG dominate the long‐term increase of air temperature. Then, the strong negative trend of AO and intensified UB may lead to the reemergence of the severe Eurasian cooling trend before the 2050s. Key Points: The significant Arctic mid‐tropospheric warming and Eurasian cooling observed in winters before the 2010s has weakened in the past decadeThe combined effects of Arctic Oscillation and Ural blocking dominate the intensity of Arctic mid‐tropospheric warming and Eurasian coolingStrong Eurasian cooling may reemerge before the 2050s if the atmospheric internal variability overwhelms the effects of greenhouse gases [ABSTRACT FROM AUTHOR]

The intensification of global warming leads to the increased frequency of extreme temperature events. Many studies have reported on numerous regions facing extreme hot and cold temperatures to some degree. In this study, the daily maximum, minimum and mean near‐surface air temperatures were estimated to explore the detailed spatial trends of extreme temperature events along the Qinghai‐Tibet Plateau Transportation Corridor (QTPTC). Sixteen extreme temperature indices were used to represent extreme temperature events, and the Mann‐Kendall trend test and Sen's slope estimation method were employed to explore the spatiotemporal trends of extreme temperatures along the QTPTC during 1981–2019. The possible factors that affect the trends of extreme temperature events were also discussed, indicating that: (a) There was an exacerbation of extreme hot events, while the prevalence of extreme cold events weakened along the QTPTC. This was in accordance with the trend of global warming. (b) The trends of extreme temperature indices based on daily minimum temperature were stronger than those based on daily maximum temperature in most areas, except for the eastern region. Furthermore, as altitude increased, the amplitude of warming intensified. (c) Unlike the trend in most areas, the intensified warming trend occurred in the low‐altitude areas in the eastern region where there are more human activities and rapid urbanization, and the daily maximum temperature trend was more severe there. The results can provide references for policymakers to formulate corresponding adaptation strategies, addressing the impacts of extreme temperature events on transportation facilities with significant elevation differences. Plain Language Summary: With the intensification of global warming, extreme hot events occur more frequently. The frequent extreme temperature events may induce many natural disasters along the QTPTC. Many studies represent extreme temperature events by calculating the extreme temperature indices based on meteorological stations in situ. Due to the sparse meteorological stations in this region, we have produced a gridded air temperature product for nearly 40 years and conducted extreme indices calculations and trend analysis to obtain the spatiotemporal trends of extreme temperature events. The results indicate the intensification of extreme hot events and the reduction of extreme cold events in the region, and this was in accordance with the trend of global warming. As the altitude increased, the amplitude of warming intensified except the low‐altitude areas. The low‐altitude areas in the east did not follow this pattern, possibly due to more human activities here. It could provide comprehensive references for infrastructure construction, railway operation and the safety of residents along the QTPTC, as well as other transportation projects in mountainous areas. Key Points: Spatial trends of extreme temperature events were detected using the gridded temperature productExtreme hot events generally increase with altitudeThe intensification of extreme hot events in the low‐altitude areas is likely due to human activities and urbanization [ABSTRACT FROM AUTHOR]

The Paris Agreement proposed two global warming levels relative to the preindustrial period, with the ideal objective of 1.5°C warming and an upper boundary of 2.0 °C. However, the years when the temperature will first reach 1.5 or 2.0°C vary in different regions. Therefore, climate extremes and their population exposure are still not clear at regional or global warming levels. This study investigated climate extremes in China at different Chinese and global warming with 16 CMIP6 models under the middle SSP245 scenario. In China, the year when 1.5°C warming is projected to occur is 2020 and 2035 for 2.0°C warming. These values are more than 10 years earlier than the corresponding global warming levels of 2030 and 2049. Population exposure to percentile‐based heat extremes at global 1.5°C warming is projected to greatly increase relative to those when 1.5°C warming occurs in China due to increases in climate extremes, and exposure to absolute heat extreme indices is projected to decrease from Chinese to global 2.0°C warming under the joint impacts of increases in extremes and population decreases. Furthermore, from Chinese to global 1.5°C warming, about 344 million people will experience increased exposure to heat, wet and dry extremes, and around 468 and 371 million people will be affected by increased exposure to heat–wet and heat–dry extremes, respectively. Thus, a more adaptive strategy should be proposed to cope with the future possible natural hazards caused by heat–wet and heat–dry extremes. Plain Language Summary: In general, heat extremes are projected to increase in a warmer climate. However, changes in surface air temperature will vary among different regions at regional and global warming levels which might impact future climate extremes and their population exposure. The heat extremes, heavy precipitation amount and consecutive days with no precipitation, and population exposure to these extremes were investigated at global and Chinese 1.5 or 2.0°C warming levels. The years when 1.5 and 2.0°C warming will occur in China are more than 10 years earlier than those of global warming levels, respectively. About 344 million people will be involved in increased exposure to above three types of extremes moving from Chinese to global 1.5°C warming. Thus, more adaptive strategies should be established to cope with the possible increased risks in the future. Key Points: Warming by 1.5 and 2.0°C will occur more than 10 years earlier in China compared with global warming levelsPopulation exposure to percentile‐based heat extremes in China is projected to greatly increase from Chinese to global 1.5°C warmingAbout 400 million people will experience increased exposure to heat–wet and heat–dry extremes from Chinese to global 1.5°C warming [ABSTRACT FROM AUTHOR]

The response of net ecosystem exchange (NEE) to environmental changes is strongly nonlinear, characterized with threshold behaviors that are not well understood. Here, we investigated the threshold behaviors in the relationship between NEE and surface air temperature based on FLUXNET2015 observations, Community Land Model simulations, and Coupled Model Intercomparison Project Phase 6 (CMIP6) model outputs. An air temperature threshold of 16.4°C, corresponding to the maximum carbon sink (Tsink), was identified for all 205 FLUXNET2015 sites combined. For deciduous broadleaf and mixed forests, wetlands and wheat‐barley croplands, and rice‐maize‐soybean croplands, we identified a carbon‐source threshold (Tsource) of 6.8, 5.0, and 18.0°C, respectively, beyond which the ecosystem becomes less of a carbon source. Five cold climate types mainly encompassing these plant functional types showed a clear carbon‐source Tsource of 12.2°C. Six CMIP6 models project a threshold temperature increase of 1.0–2.8°C by the 2090s, which results primarily from a shift of the optimum temperature for gross primary production. Not accounting for the warming‐induced threshold changes may lead to an estimated time of the average summer air temperature passing Tsink that is earlier by 4.5–6.7 and 6.4–12.2 years at low (15°N–15°S) and high (≥60°S or ≥ 60°N) latitudes, respectively. Plain Language Summary: Net ecosystem exchange (NEE) reflects the ecosystem's role as a carbon source or sink. Previous studies on NEE indicated a temperature threshold for the size of ecosystem carbon sink. It remains unknown whether a similar threshold for carbon source might exist, how the thresholds for both carbon source and sink may vary with climate and ecosystem types, and how they may change with global warming. The present study fills these gaps. Here we extract patterns of temperature thresholds for different climate and ecosystem types, and project a 1.0–2.8°C increase of threshold temperature by the end of the century. This increase has to be properly accounted for when studying the terrestrial carbon‐climate interactions. Key Points: An air temperature threshold of 16.4°C, corresponding to the maximum carbon sink, was identified for all 205 FLUXNET2015 sites combinedDeciduous broadleaf forests, mixed forests, and croplands showed a temperature threshold corresponding to a sudden change of carbon sourceCoupled Model Intercomparison Project Phase 6 models project a 1.0–2.8°C increase of threshold temperature by the end of the century [ABSTRACT FROM AUTHOR]

The air temperature difference is an essential indicator to measure weather and climate change. The Tibetan Plateau (TP) is a sensitive area to global climate change. The study on its temperature difference variations is of great significance for further understanding the evolution of weather and climate systems, and scientific disaster prevention and mitigation. In this study, the spatio‐temporal evolution characteristics of the temperature difference on daily, monthly, seasonal and annual scales and their possible causes are analysed based on the daily observations at 59 meteorological stations over the TP from 1961 to 2020 and the circulation indexes such as the East Asian summer monsoon, South Asian summer monsoon, midlatitude westerly and TP summer monsoon. The results indicate that the diurnal temperature range (DTR) on the TP tends to decrease from 1961 to 2020. Compared with the situation in the late 20th century, the annual average of the DTR in the eastern TP turns from a nonsignificant increasing trend into a pronounced decreasing trend, while that in the western TP maintains a decreasing trend. This phenomenon is primarily influenced by the minimum and maximum temperature, precipitation and atmospheric circulations. The standardized temperature difference at different temporal scales shows decreasing trends and is distributed in north–south and east–west distribution patterns. The annual temperature range is mainly influenced by the remarkable increase of the minimum temperature, especially in the northern and southeastern TP. Besides, the increases of maximum temperature and precipitation also affect the annual temperature range. In terms of the seasonal temperature range, it is dramatically influenced by different meteorological factors, especially in the northern TP. The monthly temperature range (Mon‐TR) is dramatically influenced by the maximum and minimum temperature in the first and second half years, respectively. Moreover, the circulation systems, such as the midlatitude westerly, South Asian summer monsoon and TP summer monsoon, are the main influencing factors of the temperature difference variations on the TP. The midlatitude westerly have a large influence on Mon‐TR in June and September, and the significantly influenced stations reaches 54.2% and 35.6%. The impact stations of the TP summer monsoon on Mon‐TR is the largest in August, and the significantly influenced stations is 39%. In July, the influenced stations of the TP summer monsoon and South Asian summer monsoon on the Mon‐TR reaches 30.5%–33.9%. The influenced area of the Mon‐TR in June is largest affected by single summer monsoon or westerly index. Previous studies have shown that the warming mechanisms and their influencing factors have changed in the TP since the 21st century. The study results might provide the foundation for a scientific understanding of climate warming on the TP. [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet is a leading contributor to global sea‐level rise because climate warming has enhanced surface meltwater runoff. Melt rates are particularly sensitive to air temperatures due to feedbacks with albedo. The primary melt‐albedo feedback, fluctuation of seasonal snowlines, however, is determined not only by melt but also by antecedent snowfall which could delay the onset of dark glacier ice exposure. Here we investigate the role of snowfall versus air temperatures on ice sheet melt‐albedo feedbacks using satellite remote sensing and atmospheric reanalysis data. We find several lines of evidence that snowline fluctuations are driven primarily by air temperatures and that snowfall is a secondary control. First, standardized linear regressions indicate that the timing of glacier ice exposure is nearly twice as sensitive to air temperatures than antecedent snowfall. Second, in 74% of the ablation zone by area, winter snowfall rates are not significantly correlated with winter air temperatures. This relationship implies that ice sheet melt due to climate warming is unlikely to be compensated by higher snowfall rates in the ablation zone. Third, we find no significant change in snowfall rates in the ablation zone during our 1981–2021 study period. Our findings demonstrate that snowfall is unlikely to reduce future ice sheet melt and that ice sheet meltwater runoff should be accurately predicted by air temperatures. Although given the importance of melt‐albedo feedbacks, ice sheet models that parameterize albedo or are coupled with regional climate models are likely to provide the most accurate projections of mass loss. Plain Language Summary: The Greenland Ice Sheet is currently losing mass because rates of mass loss (mainly due to surface meltwater runoff and iceberg discharge into the ocean) are higher than rates of mass gain (mainly due to snowfall). As the climate warms, rates of mass loss are expected to increase non‐linearly because rising air temperatures darken the surface, leading to more solar energy absorption, and more melting. The main process responsible for surface darkening is the exposure of dark glacier ice due to Greenland's seasonally evolving snowline. The position of the snowline is determined not only by summer melt but also by the thickness of the snowpack that accumulates during winter. In this study, we investigated whether summer melt or snowpack thickness was more important for determining the timing of glacier ice exposure using satellite remote sensing and climate model outputs. We found that the glacier ice exposure is much more sensitive to air temperatures than snowfall and that snowfall did not change in the ablation zone during the 1981–2021 study period. Our findings imply that snowfall is unlikely to reduce ice sheet mass loss and that meltwater runoff from the ice sheet should be accurately predicted by air temperatures. Key Points: We investigate the extent to which antecedent snowfall versus summer air temperatures controls melt‐albedo feedbacksWe find that melt‐albedo feedbacks are primarily driven by air temperatures and that antecedent snowfall is of secondary importanceWe find little evidence that snowfall will compensate enhanced ice sheet melt due to climate warming [ABSTRACT FROM AUTHOR]

This article discusses the reasons for shortening snow cover duration in the Western Sudetes, considering local changes in: air temperature; amount and type of precipitation; sunshine duration and atmospheric circulation leading to changes in the number of days with snow cover and its depth; and its start and end dates. All factors were linked to the exposure and relief of the study area. The analysis was made for the winter seasons (Nov–Apr) 1961/1962–2020/2021. It was found that the primary reasons for the shortening of snow cover duration in the Western Sudetes are: a multi‐year increase in air temperature and sunshine duration; changes in precipitation patterns—a decrease in the proportion of solid precipitation, changes in atmospheric circulation—including an increase in anticyclonic circulation types with sunny weather, especially in April (snow cover disappears in most of the elevation profile of the Sudetes); and less cyclonic weather types. The above factors synergistically affect the lower snow depth, and fewer days with solid precipitation, which promotes its faster spring ablation. In the subsequent 30 years (climatological norms), there is a successive shortening in its duration. On the snow cover start dates, there are no clear trends in the direction and rate of change. On end dates, negative trends are observed, in most cases statistically significant. The rate of change for the end dates of snow cover is about twice as high as the start dates. The rate of decline in snow cover is higher at stations at similar altitudes with northern macro‐exposure than southern. The results correspond with other studies from Europe and the world on the earlier disappearance of snow cover. They confirm the successive global warming and shortening snow cover duration, especially evident in the last few decades. [ABSTRACT FROM AUTHOR]

Phenotypic plasticity might increase fitness if the conditions under which it evolved remain unaltered, but becomes maladaptive if the environment no longer provides reliable cues for subsequent conditions. In seasonal environments, timing of reproduction can respond plastically to spring temperature, maximizing the benefits of a long season while minimizing the exposure to unfavorable cold temperatures. However, if the relationship between early spring temperatures and later conditions changes, the optimal response might change. In geothermally heated ecosystems, the plastic response of flowering time to springtime soil temperature that has evolved in unheated areas is likely to be non-optimal, because soil temperatures are higher and decoupled from air temperatures in heated areas. We therefore expect natural selection to favor a lower plasticity and a delayed flowering in these areas. Using observational data along a natural geothermal warming gradient, we tested the hypothesis that selection on flowering time depends on soil temperature and favors later flowering on warmer soils in the perennial Cerastium fontanum. In both study years, plants growing in warmer soils began flowering earlier than plants growing in colder soils, suggesting that first flowering date (FFD) responds plastically to soil temperature. In one of the two study years, selection favored earlier flowering in colder soils but later flowering in warmer soils, suggesting that the current level of plastic advance of FFD on warmer soils may be maladaptive in some years. Our results illustrate the advantages of using natural experiments, such as geothermal ecosystems, to examine selection in environments that recently have undergone major changes. Such knowledge is essential to understand and predict both ecological and evolutionary responses to climate warming. [ABSTRACT FROM AUTHOR]

Predictions of stream water temperature are an important tool for assessing potential impacts of climate warming on aquatic ecosystems and for prioritizing targeted adaptation and mitigation measures. Since predictions require reliable baseline data, we assessed whether open‐access data can serve as a suitable resource for accurate and reliable water temperature prediction using artificial neural networks (ANNs). For this purpose, we trained and tested ANNs in 16 small (≤1m3s) headwater streams of major types located in Bavaria, Germany. Between four and eight different combinations of input parameters were trained and tested for each stream ANN, based on data availability. These were air temperature (mean, minimum and maximum), day of the year, discharge, water level and sunshine duration per day. We found that the input combination with the highest accuracy (lowest RMSE) was stream‐specific, suggesting that the optimal input combination cannot be generalized across streams. Using a reasonable, but random, input combination resulted in an increase in error (RMSE) of up to >100% compared to the stream‐specific optimal combination. Hence, we conclude that the accuracy of water temperature prediction strongly depends on the availability of open‐access input data. We also found that environmental parameters such as hydrological characteristics and the proportion of land use in the 5 m riparian strip and the entire catchment are important drivers, affecting the accuracy and reliability of ANNs. ANNs' prediction accuracy was strongly negatively related to river length, total catchment area and water level. High proportions of semi‐natural and forested land cover correlated with a higher accuracy, while open‐canopy land use types such as grassland were negatively associated with ANN accuracy. In conclusion, open‐access data were found to be suitable for accurate and reliable predictions of water temperature using ANNs. However, we recommend incorporating stream‐specific environmental information and tailor the combination of input parameters to individual streams in order to obtain optimal results. [ABSTRACT FROM AUTHOR]

The frequency and magnitude of global warming events varies greatly across different regions and countries. The climatic diversity for China and future warming features are projected across 12 climatic zones based on the ensemble of the five well‐performing high‐resolution downscaled climate models for each zone. There are warming patterns for the mean near‐surface air temperature (Tm), maximum near‐surface air temperature (Tmax), minimum near‐surface air temperature (Tmin) as well as heatwave and frost events. Under RCP4.5 and RCP8.5 scenarios, the three indices (i.e., Tm, Tmax and Tmin) countrywide are likely to increase at respective rates of 0.30–0.31 and 0.64–0.67°C·decade−1. The extent of frost event (FE) are projected to decrease at a rate of −1912 and −4442 day·km−2·decade−1 while the extent of heatwave event (HE) increase at a rate of 1116 and 3557 day·km−2·decade−1 under RCP4.5 and RCP8.5 scenarios, respectively. A higher increment in temperatures, a decreasing trend in diurnal temperature range (DTR), frost days and FE are highlighted in the western and northern zones, while these trends are opposite in southern zones. The warming is likely to get faster in the current colder zones (western and northern zones) while heatwave is more intense and severe in Jianghuai, Jianghan, the south Yangzi River, South China and Xinjiang. These potential changes indicate that adaption and mitigation strategies are necessary in response to future warming. [ABSTRACT FROM AUTHOR]

Ongoing climate warming has strong moderating control over aquatic processes, such as ice cover duration, length of the growing season, vertical mixing patterns, thermal stratification, and the availability of light and nutrients. These fundamental mechanisms in turn influence the population dynamics of aquatic organisms such as diatoms and chrysophytes.In our study, over 3.5 years with contrasting meteorological conditions, we investigated eutrophic Lake Żabińskie located in northeast Poland. By combining observational data of meteorological conditions, physicochemical variables measured in the water column, and modern sedimentation, we sought to explain the relationships between changes in meteorological conditions, dynamics of total fluxes and the taxonomic composition of diatoms and chrysophyte cysts.Our results show the direct influence of meteorological conditions on physicochemical conditions and their indirect influence on total diatom and chrysophyte cyst fluxes and taxonomic succession. The former refers to the importance of air temperature and wind speed in shaping the mixing regime of Lake Żabińskie, while the latter refers to the nutrient cycling driven by changes in the mixing regime, which in turn influences the formation of biotic signals in the sediment. Our study also revealed that the biotic response to unusual meteorological conditions that occurred in 2020 (i.e., warm winter without ice cover) differed from typical years in terms of the phenology of diatom and chrysophyte cyst blooms. However, this response was not as pronounced as in lakes with lower productivity and can be attributed to the already turbid conditions and high nutrient concentrations, which alter the threshold for noticeable changes to occur. The taxonomic composition of diatoms and chrysophyte cysts also changed in response to changes in meteorological conditions.Complex interactions between physical and chemical conditions masked the direct influences of meteorological conditions on lake biota under eutrophic conditions. Nevertheless, high‐resolution monitoring enabled indirect links to be recognised. Both phenology and turnover in community composition responded to changes in meteorological conditions.These results show how ongoing climate change might affect biota in eutrophic lakes in the future. [ABSTRACT FROM AUTHOR]

Extremely high land surface temperatures affect soil ecological processes, alter land‐atmosphere interactions, and may limit some forms of life. Extreme surface temperature hotspots are presently identified using satellite observations or deduced from complex Earth system models. We introduce a simple, yet physically based analytical approach that incorporates salient land characteristics and atmospheric conditions to globally identify locations of extreme surface temperatures and their upper bounds. We then provide a predictive tool for delineating the spatial extent of land hotspots at the limits to biological adaptability. The model is in good agreement with satellite observations showing that temperature hotspots are associated with high radiation and low wind speed and occur primarily in Middle East and North Africa, with maximum temperatures exceeding 85°C during the study period from 2005 to 2020. We observed an increasing trend in maximum surface temperatures at a rate of 0.17°C/decade. The model allows quantifying how upper bounds of extreme temperatures can increase in a warming climate in the future for which we do not have satellite observations and offers new insights on potential impacts of future warming on limits to plant growth and biological adaptability. Plain Language Summary: While satellite imagery can identify extreme land surface temperatures, land and atmospheric conditions for the onset of maximum land surface temperature (LST) have not yet been globally explored. We developed a physically based analytical model for quantifying the value and spatial extent of maximum LST and provide insights into combinations of land and atmospheric conditions for the onset of such temperature extremes. Results show that extreme LST hotspots occur primarily in the Middle East and North Africa with highest values near 85°C. Importantly, persistence of surface temperatures exceeding 75°C limits vegetation growth and disrupts primary productivity such as in Lut desert in Iran. The study shows that with global warming, regions with prohibitive land surface temperatures will expand. Key Points: Hotspots for high land surface temperatures (LSTs) were globally identified using a physically based analytical approach incorporating land and atmospheric conditionsHigh LSTs primarily occur in Middle East and North Africa with values exceeding 85°CMaximum LSTs rising at a rate of 0.17°C/decade may limit plant growth and biological adaptability in a warming world [ABSTRACT FROM AUTHOR]

The soil freeze-thaw cycle in the permafrost regions has a significant impact on regional surface energy and water balance. Although increasing efforts have been made to understand the responses of spring thawing to climate change, the mechanisms controlling the global interannual variability of the start date of permafrost frozen (SOF) remain unclear. Using long-term SOF from the combinations of multiple satellite microwave sensors between 1979 and 2020, and analytical techniques, including partial correlation, ridge regression, path analysis, and machine learning, we explored the responses of SOF to multiple climate change factors, including warming (surface and air temperature), start date of permafrost thawing (SOT), soil properties (soil temperature and volume of water), and the snow depth water equivalent (SDWE). Overall, climate warming exhibited the maximum control on SOF, but SOT in spring was also an important driver of SOF variability; among the 65.9% significant SOT and SOF correlations, 79.3% were positive, indicating an overall earlier thawing would contribute to an earlier frozen in winter. The machine learning analysis also suggested that apart from warming, SOT ranked as the second most important determinant of SOF. Therefore, we identified the mechanism responsible for the SOT-SOF relationship using the SEM analysis, which revealed that soil temperature change exhibited the maximum effect on this relationship, irrespective of the permafrost type. Finally, we analyzed the temporal changes in these responses using the moving window approach and found increased effect of soil warming on SOF. In conclusion, these results provide important insights into understanding and predicting SOF variations with future climate change. [ABSTRACT FROM AUTHOR]

Tropical overshooting deep convections (ODCs) play a vital role in vertical transport of boundary layer pollutants, especially short‐lived species, to upper troposphere and lower stratosphere, with important implications for stratospheric ozone and climate. We use simulations from a global cloud‐system resolving model, Nonhydrostatic Icosahedral Atmosphere Model (NICAM), to study ODC changes from historical period to the end of the 21st century. NICAM well reproduces Tropical Rainfall Measuring Mission‐satellite observed ODC spatiotemporal patterns. The future occurrences of ODCs with cloud top height above 15.5, 16.9, and 18.4 km scaled by the global temperature increase will increase by 7%/K, 27%/K, and 90%/K, respectively, over ocean where the atmosphere is becoming warmer and wetter. The corresponding changes are −1%/K, 10%/K, and 37%/K over land where the atmosphere will become hotter but drier. Relative to tropical cold point tropopause height, ODCs will only change by 3%/K, with 6%/K over the ocean but −3%/K on land. Plain Language Summary: Tropical overshooting deep convection (ODC) plays an important role in transporting short‐lived chemical species rapidly from troposphere to stratosphere. This study shows that the simulations from a global cloud‐system resolving model, Nonhydrostatic Icosahedral Atmosphere Model (NICAM), can well capture observed spatiotemporal variations of tropical ODCs. The NICAM simulations predict that by the end of the 21st century (2075–2104) versus the historical period (1979–2008) with a global‐mean surface air temperature increase of 2.67 K, ODC occurrences with cloud tops reaching above 15.5, 16.9, and 18.4 km will increase by 14%, 59%, and 189%, respectively. Thus ODCs with higher cloud tops increase by a larger fraction than ODCs with lower cloud tops. The corresponding changes in ODC occurrences over the future warmer (hotter) and wetter (drier) oceanic (terrestrial) environments will be 20% (−2%), 72% (27%), and 240% (98%). Thus ODCs over ocean generally increase at a faster rate than over land. With tropical cold point tropopause height as a reference level, which will increase from 17.2 to 18.1 km, ODCs will increase by only 8% over the tropics, with 15% over ocean but decrease by −8% over land. Key Points: The Nonhydrostatic Icosahedral Atmosphere Model well reproduces observed spatiotemporal distributions of tropical overshooting deep convections (ODCs)Tropical ODC increases with global temperature on ocean (land) by 7%/K (−1%/K) for ODCs above 15.5 km, 27%/K (10%/K) above 16.9 km, and 90%/K (37%/K) above 18.4 kmResponse of tropical ODCs that penetrate the tropical cold point tropopause height to global warming is 3%/K, with 6%/K over the ocean and −3%/K on land [ABSTRACT FROM AUTHOR]

Cold‐season methane (CH4) emissions may be poorly constrained in wetland models. We examined cold‐season CH4 emissions simulated by 16 models participating in the Global Carbon Project model intercomparison and analyzed temporal and spatial patterns in simulation results using prescribed inundation data for 2000–2020. Estimated annual CH4 emissions from northern (>60°N) wetlands averaged 10.0 ± 5.5 Tg CH4 yr−1. While summer CH4 emissions were well simulated compared to in‐situ flux measurement observations, the models underestimated CH4 during September to May relative to annual total (27 ± 9%, compared to 45% in observations) and substantially in the months with subzero air temperatures (5 ± 5%, compared to 27% in observations). Because of winter warming, nevertheless, the contribution of cold‐season emissions was simulated to increase at 0.4 ± 0.8% decade−1. Different parameterizations of processes, for example, freezing–thawing and snow insulation, caused conspicuous variability among models, implying the necessity of model refinement. Plain Language Summary: Wetlands in the northern high latitudes are a major source of methane (CH4) to the atmosphere, mainly during the warm season. Previously, models have assumed that cold‐season CH4 emissions are low, but recent observations suggest high‐latitude wetlands can be substantial sources even in winter. We compared CH4 emissions simulated by 16 state‐of‐the‐art wetland models, participating in a model intercomparison project with a focus on the cold‐season in northern wetlands. The model simulations indicated that nearly one third of annual emissions were simulated to occur from September to May, and CH4 emissions to the atmosphere were not negligible even under freezing air temperatures, although the results differed greatly among the models. However, field studies suggest cold‐season emissions account for an even larger fraction of annual emissions. These results highlight the contribution of cold‐season emissions to the annual CH4 budget, which future climatic warming is expected to affect severely, and they also show that simulations of cold‐season CH4 emissions from wetlands need to be improved. Key Points: Cold‐season methane (CH4) emissions simulated by 16 Global Carbon Project‐CH4 wetland models were analyzedMost models underestimate the cold‐season emissions in comparison with observational dataFurther model improvement by including cold‐season processes is required to reduce the model bias and uncertainty [ABSTRACT FROM AUTHOR]