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Land surface processes such as the soil moisture—air temperature coupling influence compound climate anomalies like heatwaves and droughts, yet the spatial and temporal variability of the coupling strength is still understudied. We assess global land exposure to concurrent heat waves and drought since the 1980s. We found that drought significantly shapes the spatial distribution of the risk of heat waves. We show that the portion of global land experiencing drought‐conditioned heat anomalies more than tripled in less than 3 decades. However, using such traditional heat waves indicators, the level of spatial coupling between heat waves and drought seems to decline. Conversely, time‐dependent approaches accounting for the baseline climate change offer a more stable perspective. We conclude that tailoring hazard definitions to specific processes and impacts is crucial. Early warning systems can play a prominent role in mitigating the impacts of global warming to society. Plain Language Summary: Climate change is increasing the risk of simultaneous heatwaves and droughts, which significantly impact ecosystems and society. These events are influenced by soil moisture and air temperature interactions, but the variability of this relationship is not well understood. Using data from observations and forecasts since the 1980s, we analyzed global exposure to these compound events. We found that drought significantly influences where heatwaves occur, with the area experiencing both drought and heatwaves more than tripling in less than 30 years. Traditional methods for detecting temperature anomalies may give misleading results, so we recommend using time‐dependent approaches that account for climate change. These approaches provide a clearer understanding of soil moisture‐air temperature interactions and are better for studying the impacts on adaptable systems. Traditional methods are still useful for assessing impacts on less adaptable ecosystems and some societal sectors. We also highlight the importance of weather forecasts in providing early warnings to help society adapt to global warming. Key Points: Drought significantly influences heatwave locations. The affected global land area tripled in under 30 yearsTime‐dependent approaches better reflect soil moisture‐air temperature interactions amid climate changeWeather forecasts are crucial for early warnings, aiding societal adaptation to global warming [ABSTRACT FROM AUTHOR]

The applicability and accuracy of high‐resolution Real‐Time Meso‐scale Analysis (RTMA) system is assessed over India for the first time. The RTMA is a high‐spatial (2.5 km) and temporal resolution analysis system for near‐surface weather conditions. It is used to simulate near‐surface air temperature over India during the Heatwave (HW) period 12th to 20th April 2023. The verification analysis of temperature using the GLDAS gridded temperature shows reasonable improvement in the analysis from RTMA by capturing regional features compared to first‐guess. The spatial and temporal verification using the IMD station observations also confirms the value addition of RTMA in capturing the locations of recorded highest Tmax and their daily variations. The location‐specific heat stress analysis of RTMA shows high skill over many locations during HW days. Heat stress regions have been accurately brought out in the RTMA. Hence, the RTMA can be used for now‐casting and severe weather monitoring. Plain Language Summary: Heat wave (HW) alert systems require accurate high‐resolution surface weather data for better adaption strategies. Real‐Time Meso‐scale Analysis (RTMA) system configured to generate surface weather parameters at a high‐spatial (2.5 km) and temporal (3 hrs) resolution at National Center for Medium Range Weather Forecasting (NCMRWF) for the very first time in India. We verified its performance in representing the HW conditions and extreme temperatures over the Indian region relative to India Meteorological Department (IMD) observations/Global Land Data Assimilation System (GLDAS) during the HW period of 12th to 20th April 2023. Our results indicate significant improvement in the spatial and temporal variations of daily maximum temperature simulated by RTMA system. We have noted lower absolute mean errors of ∼ 0.02 for the RTMA in predicting the Tmax over the HW affected regions of Bihar, Odisha, West Bengal, and East Uttar Pradesh when compared to the GFS model. These improvements have led to the better identification of the locations of higher heat risk through the computation of the Heat Index and highlight the applicability of RTMA. Overall this study clearly brings out the usability of RTMA final analysis fields for now‐casting and severe weather monitoring. Key Points: It is a first‐of‐its‐kind study to understand the applicability and accuracy of high‐resolution RTMA over India by analyzing heatwaveRTMA temperature analysis shows higher skill over the heatwave regions and locations as compared to the background fields and observationsThe study suggested that the RTMA final analysis fields are highly useable for severe weather monitoring and impact‐based weather forecasts [ABSTRACT FROM AUTHOR]

The dominant mode of interannual variability in summertime high‐frequency tropospheric temperature fluctuations over Southern Africa is found to be associated with tropical Pacific sea surface temperature variability, in such a manner that El Niño is typically accompanied by enhanced high‐frequency variability. This relationship is established via El Niño's teleconnection that contributes to shifting the midlatitude jetstream and associated baroclinic zone equatorward, into the vicinity of Southern Africa, which enhances the baroclinic conversion of energy from the seasonal‐mean flow to high‐frequency eddies. The enhanced temperature variance, combined with the overall warmer summertime‐mean temperatures induced by El Niño, results in more frequent warm extremes over Southern Africa. Plain Language Summary: When warmer‐than‐normal sea surface temperatures associated with El Niño are observed over the Eastern/Central Tropical Pacific Ocean, day‐to‐day surface temperature variability tends to be enhanced over Southern Africa in summer. This relationship is due to the remote impact of El Niño on the atmospheric circulation in the vicinity of Southern Africa, which favors transfers of energy from the summertime‐mean atmospheric circulation into weather systems responsible for temperature fluctuations on daily timescales. This transfer of energy is directly related to southward and northward displacements of warm and cold air masses, respectively, thereby leading to amplified temperature variations near the surface. Key Points: El Niño accompanies enhanced summertime high‐frequency temperature variability over South AfricaDue to enhanced baroclinic energy conversion concomitant with a northward shift of the jetstream and baroclinic zone toward South AfricaThe enhanced high‐frequency variance coincides with warmer seasonal‐mean temperatures, leading to more frequent warm extremes [ABSTRACT FROM AUTHOR]

Extreme heat is investigated in a series of high‐resolution time‐slice global simulations comparing the current and late‐21st century climates. An increase in climate‐relative extreme heat is found in the region surrounding the Black Sea. Similarities between the synoptic‐scale flows in current and future heat events combined with a decrease in future summer precipitation suggests that the increased future severity stems from strengthened land‐atmosphere feedbacks driven primarily by the changes in precipitation. The resulting intensification of heat events beyond the mean warming driven by climate change could generate significant future heat hazards in vulnerable regions. Given the continental cool bias in the present‐day simulations, the resulting estimates of future extreme heat are likely to be conservative. Plain Language Summary: Increases in extreme heat are a direct consequence of global warming. In some regions, however, the frequency and severity of heat waves can exceed what is expected given the rise in mean temperature alone. We examine this issue using data from a high‐resolution climate model run for 10 simulated summers under current and future (late 21st century) climate conditions. In the future simulations, extreme heat events, relative to the baseline of a much warmer climate, become more frequent and severe in a region surrounding the Black Sea. The weather patterns that lead to heat waves are very similar in the current and future climates. This similarity suggests that land‐atmosphere interactions during atmospheric heat waves amplify these events more in the future. Under warmer baseline conditions, the land dries out more rapidly during a heat event, reducing cooling from evaporation, and thus creating more severe and dangerous heat. Additionally, these model simulations are too cold over land areas, likely weakening the land‐atmosphere interactions so our projections of increased extreme heat are probably conservative. Key Points: Climate‐relative extreme heat events in certain regions are substantially amplified in a set of high‐resolution future climate simulationsThis regional amplification of extreme heat does not depend on changes in flow regimesResults suggest amplified heat may be due to stronger regional/local land surface feedbacks, resulting in faster drying in a warmer climate [ABSTRACT FROM AUTHOR]

Co‐occurring hazards present unparalleled challenges to development and disaster recovery. In this study, we investigate the relationship between anomalous heat in the aftermath of tropical cyclones in the eastern Caribbean between 1991 and 2020. We analyze the spatial patterns of anomalous heat index (HI) values for 53 tropical storms and hurricanes using a Lagrangian analysis framework. Furthermore, we analyze temporal patterns of 205 city‐storms pairings. The spatial patterns displayed distinct and statistically significant areas of anomalously warm conditions regardless of the storm intensity classification. Moreover, all 205 city‐storm events had positive HI anomalies following the storms' passage with a maximum of 5°C. The results show that HI anomalies can be high, have a time lag of days, and be observed in locations not directly impacted by the storm. The results have implications for tropical cyclones preparedness, including suggesting that preparedness include informing the public about heat impacts. Plain Language Summary: Two or more extreme events that are coincident in time or that occur in close succession present unparalleled challenges to development and disaster recovery. It is well known that tropical cyclones cause long‐lived damage from strong winds, storm surges, intense rain, and/or flooding. Equally, heat is a main concern for public health. However, heat in the aftermath of tropical cyclones has not been a focus.We analyze 53 tropical storms and hurricanes in the eastern Caribbean between 1991 and 2020 and 205 storm‐city events. The storms' heat index (HI) values are statistically significantly warmer during the storm than average in some regions, regardless of groupings of storms by their strength. The HI values before and after storms passed main cities in 14 Caribbean islands further show that in all 205 cases, warm HI anomalies follow the storms' passage, with values as high as 5°C (9 Fahrenheit). The results show that HI anomalies following tropical cyclones can be high, have maximums that occur several days after the storm's passage, and can be observed in locations that are not directly impacted by the storm. The results suggest tropical cyclone preparedness should include informing the public about heat risk. Key Points: Areas around tropical cyclones have heat index (HI) values significantly warmer than average, a result insensitive to storm strengthPositive HI anomalies occur after the cyclones passage in all storms; the maximum anomalies range from 0.3°C to 5.2°CAnomalous heat can be observed in areas 100s of kilometers away from the central location of the tropical storm [ABSTRACT FROM AUTHOR]

While many studies comparing atmospheric reanalysis and surface observations have focused on the similarity of mean fields, trends, or frequencies of extreme events, very few have assessed how similar surface observations and reanalysis data sets are in terms of their specific identification of extreme temperature event days. Here, we assess the similarity between surface observations and three reanalysis products: ERA5, ERA5‐LAND, and NARR, in terms of the days on which they identify extreme heat and cold events for the period 1979–2016 at 230 locations in the United States and Canada. Cold events have a greater match than heat events. ERA5 has the greatest match percentage with station data across the study region. Match percentage is greatest in midlatitude, continental locations, with poorer performance in coastal areas, and the Arctic. Plain Language Summary: Atmospheric reanalysis products are simulations of the atmosphere that create gridded historical data sets. While many studies have looked at how well these products match surface observations overall, very few have examined how similar they are in identifying extreme weather event days. Here, we explore this similarity using three reanalysis products: ERA5, ERA5‐LAND, and NARR, in terms of the days on which they identify extreme temperature events. We do this for 231 locations in the United States and Canada from 1979–2016, for both extreme heat and cold. Cold events have a greater match than heat events. ERA5 has the greatest match percentage with station data across the study region. Match percentage is greatest in midlatitude, continental locations, with poorer performance in coastal areas, and the Arctic. Key Points: There is much variability in how well reanalysis models match surface observations in terms of extreme temperature eventsExtreme cold events are better simulated than heat eventsThe ERA‐5 is the best reanalysis product for simulating extreme temperature events [ABSTRACT FROM AUTHOR]

Critical transitions of the state variable (temperature) in dynamic climate systems often lead to catastrophic consequence, whereas the effort to reverse the transitions usually lags behind. However, these transitions are characterized by the slowing down of recovery from perturbations, carrying early‐warning signals that can be used to predict system bifurcation. In this study, we employ the conceptual framework of pitchfork bifurcation and analyze the early‐warning signals in temperature time series for critical slowing down prior to both the early 20th century global warming and heat waves. We also investigate the urban signature in these heat waves. The emergence of early‐warning signals before heat waves provides new insights into the underlying mechanisms (e.g., possible feedback via land‐atmosphere interactions). In particular, given the increasing frequency and intensity of heat extremes, the results will facilitate the design of countermeasures to reserve the tipping and restore the resilience of climate systems. Plain Language Summary: Critical transitions have been identified in global and regional climate systems, during which a small perturbation can lead to a qualitative change. They are notoriously difficult to predict and can have potential catastrophic impacts on ecosystems and human society. However, certain characteristics may exist prior to such transitions and can serve as the early‐warning signals to predict critical transitions in climate systems. Here we investigate the early‐warning signals in global warming and regional heat waves based on temperature records. We identify clear early‐warning signals before the early 20th century global warming period and several heat waves during recent years. The early‐warning signals for heat waves are possibly due to the interplay of multiple environmental determinants, such as the drying soil during droughts and the heat accumulated in the atmosphere. Furthermore, we observe differences in the early‐warning signals between urban and rural temperature records. Our study highlights the presence of early‐warning signals days (years) prior to heat waves (abrupt global warming). With the higher frequency and intensity of heat wave events in a warming future, the results can be used to design mitigation and adaptation strategies beforehand to attenuate their negative impacts (such as heat stress) and proactively combat climate change. Key Points: We quantify early‐warning signals in temperature evolution of the early 20th century global warming and heat wave eventsCritical slowing down prior to heat waves is likely due to the interactions of multiple determinantsThe contrast of urban‐rural signature is identified for early‐warning signals of extreme heat waves [ABSTRACT FROM AUTHOR]

Land‐atmosphere feedbacks, in particular the response of land evaporation to vapor pressure deficit (VPD) or the dryness of the air, remain poorly understood. Here we investigate the VPD response by analysis of a large database of eddy covariance flux observations and simulations using a conceptual model of the atmospheric boundary layer. Data analysis reveals that under high VPD and corresponding high temperatures, forest in particular reduces evaporation and emits more sensible heat. In contrast, grass increases evaporation and emits less sensible heat. Simulations show that this VPD feedback can induce significant temperature increases over forest of up to 2 K during heat wave conditions. It is inferred from the simulations that the effect of the VPD feedback corresponds to an apparent soil moisture depletion of more than 50%. This suggests that previous studies may have incorrectly attributed the effects of atmospheric aridity on temperature to soil dryness. Key Points: Diverging surface energy balance response to atmospheric aridity is found over grassland and forestHigh vapor pressure deficit enhances simulated heat wave temperatures over forest by up to 2KVapor pressure deficit effect on temperature is similar to effect of severe soil moisture drought [ABSTRACT FROM AUTHOR]

The frequency and severity of heatwaves is expected to increase as the global climate warms. We apply crossing theory for the first time to determine heatwave properties solely from the distribution of daily observations without time‐correlation information. We use Central England Temperature time series to quantify how the simple increased occurrence of higher temperatures makes heatwaves (consecutive summer days with temperatures exceeding a threshold) more frequent and intense. We find an overall twofold to threefold increase in heatwave activity since the late 1800's. Week‐long heatwaves that on average return every 5 years were typically below ∼28 °C and now typically exceed it. Our analysis takes as inputs average user‐specific heat wave properties. Its output pinpoints the range of temperatures for which changes in the distribution must be well resolved statistically in order to track how these heatwave properties are changing. This provides a quantitative benchmark for models used for the attribution of heat waves. Plain Language Summary: As the climate changes, we can expect to see changes in the frequency and severity of heatwaves. Heatwaves are defined here as successive days during which the surface temperature is above a threshold value. A heatwave threshold value that is important for planning will vary depending on circumstances or geographical location, for the United Kingdom we consider the building overheating threshold of 28 °C, but higher thresholds may be relevant in more equatorial regions. The Central England Temperature time series is one of the longest continuous records of daily surface temperature measurements and we use this data to estimate how U.K. heatwaves have changed from 1878 to the present. We find an overall twofold to threefold increase in heatwave activity since the late 1800's. Week‐long heatwaves that occur on average every 5 years were typically below about 28 °C but now typically exceed it. Our analysis relies solely on the observations and does not involve large‐scale numerical models. It provides a quantitative verification for models that are used to attribute heatwave activity. Key Points: First application of crossing theory to determine heatwave properties solely from the distribution of daily observations without time‐correlation informationA twofold to threefold increase in heatwave activity since the late 1800s is found in the Central England Temperature recordObservational, model‐independent, generic analysis gives a new and independent check for global climate model heatwave results [ABSTRACT FROM AUTHOR]

Abstract: The impact of atmospheric blocking on European heat waves (HWs) and cold spells (CSs) is investigated for present and future conditions . A 50‐member ensemble of the second generation Canadian Earth System Model is used to quantify the role of internal variability in the response to blocking. We find that the present blocking‐extreme temperature link is well represented compared to ERA‐Interim, despite a significant underestimation of blocking frequency in most ensemble members. Our results show a strong correlation of blocking with northern European HWs in summer, spring, and fall. However, we also find a strong anticorrelation between blocking and HW occurrence in southern Europe in all seasons. Blocking increases the CS frequency particularly in southern Europe in fall, winter, and spring but reduces it in summer. For the future we find that blocking will continue to play an important role in the development of both CSs and HWs in all seasons. [ABSTRACT FROM AUTHOR]

Climate simulations of future hot extremes exhibit large uncertainties regarding the magnitude of projected warming. We identify two mechanisms that influence how strongly future heat extremes intensify in climate models. First, the magnitude of extreme temperature increases is determined by changes in preceding seasonal precipitation, connected to amplified warming via soil moisture decreases. Second, there are large differences in how models respond to moisture variability; those with a stronger response under current climate simulate larger future increases in hot extremes. We build on this mechanistic understanding of future uncertainty and develop a novel constraint, the observed precipitation‐hot temperature relationship, focused on the conditions on the actual hottest day, to identify climate models with realistic land‐atmosphere feedbacks on hot extremes. Applying this constraint to the Coupled Model Intercomparison Project Phase 5 ensemble reduces the probability of the largest increases in projected heat extremes, particularly over Europe and North America. Plain Language Summary: Climate model simulations of future hot temperature extremes agree on the regions of strongest warming but disagree on how much temperature will increase. We identify that a large part of the uncertainty is explained by intermodel differences in future precipitation changes, and differences in the model‐specific strength of land‐atmosphere feedbacks. We constrain the future climate model ensemble simulations by using only those models that simulate land‐atmosphere feedbacks more similar to real‐world observations over the past 60 years. This reduces the uncertainty of future changes by reducing the probability of the strongest increases in hot extremes particularly over Europe and North America. Key Points: Regional uncertainty of future heat extremes is controlled by changes in seasonal precipitation and strength of land‐atmosphere feedbacksObserved land‐atmosphere feedbacks help constrain future heat extremes in the CMIP5 ensemble over Europe and North AmericaEmploying this process‐based constraint reduces the probability of the highest increases in temperature extremes within the CMIP5 ensemble [ABSTRACT FROM AUTHOR]

The physical mechanisms by which heat waves in the Brisbane region of Australia develop are elucidated through trajectory and composite analyses. Trajectories are started close to the surface during heat waves and integrated backward. Those trajectories for which the net diabatic heating lies in the uppermost pentile are called strongly diabatic, while those in the lowermost pentile are called weakly diabatic. In the weakly diabatic case, air parcels originate eastward of the continent over the ocean and warm almost entirely by adiabatic compression in an anticyclonic environment. Surprisingly, strongly diabatic heat waves in this region are characterized by an upper‐tropospheric cyclonic anomaly off the southeastern corner of Australia. The air parcels originate far to the southwest of the heat wave, and their temperature increases roughly in equal parts by adiabatic compression as air parcels subside on the rear flank of this cyclonic anomaly and surface sensible heating as air parcels are advected horizontally. Plain Language Summary: Heat waves are the deadliest natural hazard in Australia. Motivated by the projection that the number of extremely hot days in subtropical Australia will increase in a warmer climate, this study aims to develop a comprehensive physical picture of the processes leading to the extreme temperatures. The approach taken is to compare heat waves dominated by land surface‐atmosphere interactions to those that are due to atmospheric dynamical processes using the Brisbane region as a specific example. The key finding is that unlike heat waves in other parts of the world, heat waves are not necessarily associated with a high pressure system but with a low pressure system off the southeastern corner of Australia. Hence, it seems likely that when considering how heat waves might change in the future, not only are the location and intensity of subtropical high pressure systems important but also are the location, intensity, and variability of the midlatitude storm tracks. Key Points: Heat waves around Brisbane can form through adiabatic compression in an anticyclonic environmentHeat waves in the region can also occur in the wake of a midlatitude troughIn this case they form through a combination of adiabatic compression and surface sensible heating [ABSTRACT FROM AUTHOR]