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Dust particles suspended in the dusty Martian atmosphere are prone to being charged. In this paper, we investigate the effect of the net charges carried by dust particles on the radiative properties of Martian dust. We find that net charges carried by dust particles significantly alter the extinction properties and single scattering albedo of dust at thermal infrared radiation band, which results in an enhancement of the infrared heating rate, up to 6.36%. We show that the discrepancy between the atmospheric temperature predicted by the Mars Atmosphere Model and the one detected during the Mars rover landing is reduced to within 11% when the effect of the net charges carried by the dust is considered. Therefore, it is essential to consider the effect of the net charges carried by dust particles for an accurate characterization of the atmospheric temperature. Plain Language Summary: Dust suspended in the atmosphere has long been considered as an important factor in altering Mars atmospheric temperature. The suspended Martian dust particles can scatter and absorb solar radiation and thermal infrared radiation, and their heating effect on the atmosphere is significant. The variation of the size and opacity of Martian dust with altitude affecting the interaction of dust particles with solar visible and infrared radiation has been extensively studied. However, the dust suspended in the Martian atmosphere are prone to being charged, and the effect of the net charges carried by the dust on the radiation effect has been neglected in existing studies. Therefore, we investigate the effect of the net charges carried by dust particles on the radiative properties of Martian dust. We find that the net charge carried by dust particles leads to a significant enhancement of the heating rate. In addition, the atmospheric temperature predicted by the atmospheric model is much closer to the one measured during the Mars rover landing when the effect of the net charge carried by the dust is considered. Key Points: Radiation properties of Martian dust change drastically when these particles are chargedThe net charges carried by dust contribute significantly to the Martian atmosphere heating rateThe difference between the observed and model‐predicted atmospheric temperatures is reduced when the effect of dust charging is considered [ABSTRACT FROM AUTHOR]

The ability of satellite instruments to accurately observe long‐term changes in atmospheric temperature depends on many factors including the absolute accuracy of the measurement, the stability of the calibration of the instrument, the stability of the satellite orbit, and the stability of the numerical algorithm that produces the temperature data. We present an example of algorithm instability recently discovered in the temperature data set from the SABER instrument on the NASA TIMED satellite. The instability resulted in derived temperatures that were substantially colder than anticipated from mid‐December 2019 to mid‐2022. This algorithm‐induced change in temperature over 1 to 2 years corresponded to the expected temperature change over several decades from increasing anthropogenic CO2. This paper highlights the importance of algorithm stability in developing Geospace Data Records (GDRs) for Earth's mesosphere and lower thermosphere. A corrected version (Version 2.08) of the temperatures from SABER is described. Plain Language Summary: Instruments on Earth orbiting satellites offer the opportunity to detect long‐term changes in atmospheric temperature. Many factors may affect the ability to identify actual long‐term changes in the temperature and to distinguish these from changes in the instrument or from unintended changes in the algorithm that produces the temperature data from the instrument observations. SABER is an instrument on a NASA satellite that has been observing temperatures from 15 to 110 km (10–68 miles) in altitude for over 20 years. An "instability" in the scientific algorithm used to derive temperature from the instrument observations was recently discovered, beginning in late 2019. An unintended change was made in a parameter central to the derivation of temperature from SABER measurements. The consequence was that the atmospheric temperatures between 85 and 110 km (51–68 miles) from 2020 onward were several degrees colder than they would have been without the unintended change. This has been corrected and an updated version of the SABER temperatures and all other SABER data products, called Version 2.08, is now publicly available. Key Points: The concept of Geospace Data Records (GDRs) and their relevance to accurate detection of long‐term change is introducedAlgorithm instability in a GDR of the 20‐year record of SABER temperatures between 85 and 110 km is described and correctedThe field of Geospace Climate is emerging as a frontier with scientific and economic relevance. Accurate GDRs are essential to both [ABSTRACT FROM AUTHOR]

The annular structure of Antarctic oscillation (AAO) is a research hotpot, but its asymmetry receives less attention. In this paper, the self‐organizing map method is employed to cluster the AAO patterns into symmetric and asymmetric modes in austral autumn. The asymmetry is mainly reflected in the Pacific‐Atlantic sector, and the AAO evolves toward asymmetric positive polarity, with the most pronounced asymmetry in May. Originating from near Australia, the asymmetry indicates a zonal wave train in the Pacific‐Atlantic sector. Both modeled and observed results demonstrate that the sea surface temperature anomaly in the equatorial western Pacific stimulates a local meridional circulation anomaly and induces anomalous Rossby wave sources near Australia subsequently. An anomalous wave train propagating toward the Antarctic Peninsula is formed, and the associated geopotential anomaly enhances the asymmetry of AAO. Asymmetric AAO is conducive to the Antarctic dipole, which modulates the air temperature and sea ice anomalies around Antarctica. Plain Language Summary: The zonal symmetry of the Antarctic oscillation (AAO; also named southern annular mode) is well known to researchers, while the zonal asymmetry has received less attention. We use a clustering method to cluster the AAO modes in austral autumn into symmetric modes and asymmetric modes. The asymmetry of AAO is mainly reflected in the Pacific‐Atlantic sector. The results show that the AAO mode evolves to a positive asymmetric mode, and the asymmetry is most obvious in May. Both simulations and observations suggest that this asymmetry stems from sea surface temperature anomaly in the equatorial western Pacific that stimulates an anomalous local meridional circulation near Australia, and in turn triggers an anomalous wave train propagating toward the Antarctic Peninsula. The associated geopotential anomalies enhance the asymmetry of AAO. The asymmetric AAO favors the Antarctic dipole, regulating the air temperature and sea ice anomalies around Antarctica. Key Points: Via a cluster method, we obtained the zonal asymmetric Antarctic oscillation (AAO) mode, and analyzed its trend and preferred monthThe source of its asymmetry is from the sea surface temperature anomaly in the tropical western PacificThe asymmetric AAO mode has a vital influence on the Antarctic dipole [ABSTRACT FROM AUTHOR]

This study investigates how El Niño‐Southern Oscillation (ENSO) modulates winter cold anomalies over central Eurasia (CE) using reanalysis data during 1950–2019. It is found that ENSO can significantly influence winter air temperature over CE mainly through modulating the strength and location of the cyclonic anomaly of Ural blocking (UB) or long‐lived UB events. A strong (weak) cyclonic anomaly of UB on the southeastern (eastern) side of the Ural Mountains tends to occur over midlatitude (high‐latitude) Eurasia during La Niña (El Niño) winters. Such anomalous circulation leads to a strong (weak) cold anomaly over CE, especially over East Asia, due to enhanced (weakened) cold air advection toward the CE during La Niña (El Niño). The UB‐related cyclonic anomaly in the midlatitude (high latitude) side of Eurasia is shown to be related to weakened (enhanced) eastward extension of strong westerly winds over midlatitude Eurasia during La Niña (El Niño) winters. Plain Language Summary: Observations show that in recent decades a strong cold anomaly appears over Eurasia, especially over central Eurasia (CE). This cold anomaly shows notable variations on interannual, decadal and interdecadal timescales. However, what factors lead to its interannual variations is not well understood. Here we show that El Niño‐Southern Oscillation (ENSO) events can influence Eurasian winter air temperature by modulating the strength and location of the cyclonic anomaly of Ural blocking (UB) or the frequency of long‐lived UB events. A La Niña (El Niño) favors a strong (weak) cyclonic anomaly circulation located in the southeastern (eastern) side of the Ural Mountains in the midlatitudes (high latitudes), which leads to a strong (weak) cold anomaly over CE especially in the low latitude Eurasia (i.e., East Asia) through enhanced (weakened) cold air advection. These new results help us understand the physical cause of the interannual variability of the Eurasian cold anomaly modulated by ENSO. Key Points: This paper examines the causal relationship between the Ural blocking (UB) and Eurasian cold anomaly during the La Niña phase in winterEl Niño‐Southern Oscillation plays an important role in the interannual variability of winter cold anomaly over the EurasiaThe UB leads to stronger cold anomaly over the Eurasian during the La Niña than El Niño [ABSTRACT FROM AUTHOR]

Limiting excess atmospheric ammonia (NH3) is one of the great challenges for humanity in the 21st century but can only be achieved with adequate monitoring means in place. Here, we report the first NH3 measurements from the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the Chinese FY‐4A satellite. The instrument scans almost all of Asia 10 times per day. We show that GIIRS′ unprecedented temporal sampling can be exploited to measure diurnal and nocturnal variations of NH3 and demonstrate this on two case studies over Punjab and the North China Plain. Day–night variations are found to be almost absent in winter, but can reach a factor 2–3 in the warmer months. These case studies are very promising given the future landscape of geostationary sounders, but also show that improved knowledge on lower tropospheric air temperatures and the vertical profile of NH3 is key to better exploit their measurements. Plain Language Summary: To reduce the worldwide concentrations of ammonia (NH3) in the air is one of the great challenges for humanity in the 21st century, but this can only be achieved with stringent policies in place, and with the support of accurate and frequent measurements. In this paper, we report the first ammonia measurements from the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the Chinese FY‐4A satellite. The satellite is positioned above Indonesia and measures almost all of Asia 10 times per day. We show that GIIRS' measurements can be used to measure ammonia both during day and night. We look into more detail at two locations, over Punjab (Pakistan) and the North China Plain. Day‐night variations are found to be almost absent in the colder months, but can reach a factor 2–3 in the warmer months. These case studies are very promising given the future landscape of geostationary sounders, but demonstrate also that improved knowledge on the air temperature at the surface and the behavior of ammonia at higher altitudes will result in more accurate ammonia measurements. Key Points: We report the first observations of atmospheric NH3 from the geostationary satellite FY‐4A GIIRS over AsiaThe potential of GIIRS to reveal the diurnal and nocturnal variations of NH3 total columns is demonstrated over two sitesTo better exploit geostationary data, improved temperature profiles and knowledge on the vertical NH3 distribution is needed [ABSTRACT FROM AUTHOR]

The urbanization impacts on surface air temperature (SAT) change in the Guangdong‐Hong Kong‐Macau region (GHMR) from 1979 to 2018 are examined using homogeneous surface observations, reanalysis, and remote sensing. Results show that the warming due to urbanization tends to be smaller or insignificant as the spatial scale increases. The urbanization contribution to the local warming can reach as high as 50% in the center of each metropolis, remains high (~25%) in the Greater Bay Area (GBA), and decreases to about 10% in the whole GHMR. The warming in GHMR is nearly uniform throughout the day, and therefore, the observed trend of the diurnal temperature range (DTR) is not statistically significant. However, the urbanization contribution exhibits distinct seasonal variations, large in summer and autumn while smaller in winter and spring. Plain Language Summary: The Guangdong‐Hong Kong‐Macau region (GHMR), especially the Greater Bay Area (GBA), is a region typical of China's economic development and rapid urbanization. To precisely assess how much the urbanization contributes to the regional warming, we comprehensively evaluate the urbanization warming and its uncertainties in GHMR by using more careful processed and assessed data (observations, reanalysis, and remote sensing) and different analysis methods. The results show that the warming due to urbanization tends to be smaller as the spatial scale increases: The contribution to the local warming can reach as high as 50% in the metropolis, remains high (~25%) in GBA, and decreases to about 10% in GHMR. In addition, this paper systematically discusses the uncertainty in urbanization contribution detection, which was often neglected in the past detection. Based on the significance tests, urbanization warming is nearly uniform throughout the day, while it exhibits distinct seasonal variation. Our study also has important implications for understanding the influences of human activities on regional climate change for other regions experiencing rapid urbanization processes. Key Points: The contribution of urbanization to regional warming is robust in homogenized SAT data and ERA5 reanalysis using different methodsThe spatial scale dependence of urbanization warming is investigated; the contribution of urbanization warming decreases when the scale increasesUrbanization contribution exhibits distinct seasonal variation based on the uncertainty assessment [ABSTRACT FROM AUTHOR]

From the onset of melt in early June, corresponding declines in Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) freeboard and surface albedo can be seen over the entire Arctic sea ice cover. In the 2019 summer, area‐averaged freeboard decreased from 34 cm prior to melt to a minimum of 12 cm in August while the area‐averaged albedo decreased from ~0.7 to 0.38 for the same period. Calculations using ICESat‐2 freeboards and modeled ice thickness from Pan‐Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) give area‐averaged snow depths ranging from 17 cm prior to melt to 3 cm in August over seasonal ice and from 34 to 4 cm over multiyear ice. Mean rates of snow ablation (including evaporation) in mid‐June were as high as 2 cm/day, comparable to field records from other years. Increases in freeboard after mid‐August in the high latitude (>80°N) multiyear ice cover, north of the Greenland coast, are likely due to earlier freeze‐up and snow accumulation in these regions with shorter melt seasons. Plain Language Summary: As the air temperature warms with the onset of summer, the Arctic Ocean ice cover undergoes its annual transformation from a highly reflective snow‐covered surface in winter to a darker, more absorbent surface during summer composed of bare ice, melt ponds, and open water. Several weeks after the onset of melt, much of the snow layer disappears as the snow is converted into meltwater. Over the entire ice cover, this loss of the snow layer can be seen in the lowering of surface heights measured by the lidar on NASA's Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2). In this paper, we describe the changes in surface height and the corresponding changes in snow depth from the satellite observations and compare them with existing measurements from field programs, which are limited due to challenging logistics during the summer. We show, for the first time, that we can observe corresponding changes in surface height and reflectivity as well as the different rates of melt in the decay of the snow cover. These results will allow for an improved understanding of the impact of the snow layer on the fate of the ice cover at the end of the summer. Key Points: We provide a first look at the evolution of the summer ice cover in ICESat‐2 sea ice productsObservations show a clear lowering of the freeboard associated with snow melt over the entire Arctic Ocean ice coverArea‐averaged snow depths ranged from 17 cm prior to melt to 3 cm in August over seasonal ice and from 34 to 4 cm over multiyear ice [ABSTRACT FROM AUTHOR]

Increasing atmospheric carbon dioxide (CO2) is the main factor of global warming. Carbon satellites have proven that CO2 concentrations have nonuniform spatio‐temporal distributions. The relationship between unevenly distributed CO2 and global surface air temperature (SAT) is seldom known. The success of complex networks provides an opportunity to address this issue. This paper proposes a multilayer climate network approach to identify the impacts of nonuniform CO2 on SAT. The results show that the probability density function (PDF) of degrees, weighted degrees, and link lengths follows power‐law distributions. A large fraction of strong correlation links resides in proximal distance (smaller than 2,000 km), indicating that CO2 nodes are strongly connected to the surrounding SAT nodes. The enhanced distributions of large positive weights, time delays, and degree patterns are all consistent with the properties of Rossby waves. This framework can be useful for predicting future climate changes and policy‐making for carbon reduction. Plain Language Summary: Carbon dioxide (CO2) is a prominent anthropogenic greenhouse gas in the atmosphere, and the increasing CO2 is the main reason for global climate warming. The CO2 concentration from satellites has revealed that the spatial distribution of CO2 is uneven. In previous studies, the relationship between CO2 and temperature is based on global CO2 concentration mean assumptions. Here, we propose a multilayer climate network approach to identify their relations using satellite data. We find that the PDF of degrees, weighted degrees, and link lengths follows power‐law distributions. The most dominant links, with a geographical distance larger than 2,000 km, are found for distances of 7,000 km, coinciding with the wavelengths of atmospheric Rossby waves. The time delays associated with these distances are in agreement with the group velocity of the atmospheric Rossby waves. Moreover, the pronounced band over 50°S, the dominance in the Southern Hemisphere relative to the Northern Hemisphere, and the similar patterns to transient heat flux are consistent with the properties of Rossby waves. The proposed approach leads to a better understanding of the role played by CO2 in forcing global temperatures and future climate change. Key Points: There are short‐term correlations between global mid‐troposphere CO2 concentrations and global surface air temperatureThe degrees, weighted degrees, and link lengths of CO2 and SAT multilayer climate network are conformed to power‐law distributionsSignificant correlation links of the constructed climate network yield a clear association with Rossby waves [ABSTRACT FROM AUTHOR]

We assess the reliability of an indirect method of inferring the atmospheric response to projected Arctic sea ice loss from CMIP5 simulations, by comparing the response inferred from the indirect method to that explicitly simulated in sea ice perturbation experiments. We find that the indirect approach works well in winter, but has limited utility in the other seasons. We then apply a modified version of the indirect method to 11 CMIP5 models to reveal the robust and non‐robust aspects of the wintertime atmospheric response to projected Arctic sea ice loss. Despite limitations of the indirect method, we identify a robust enhancement of the Siberian High, weakening of the Icelandic Low, weakening of the westerly wind on the poleward flank of the eddy‐driven jet, strengthening of the subtropical jet, and weakening of the stratospheric polar vortex. The surface air temperature response to projected Arctic sea ice loss over mid‐latitude continents is non‐robust across the models. Plain Language Summary: The continued melt of Arctic sea ice will likely affect weather and climate in places far from the Arctic. To better understand the far‐flung implications of sea ice loss, scientists can perform bespoke climate model experiments in which sea ice is reduced, but all other climate drivers are fixed. In our paper, we test the reliability of an indirect method to infer the atmospheric response to sea ice loss, which makes use of a large set of climate model experiments originally performed for other purposes. We find that the indirect approach works well in winter, but not so well in other seasons. We then apply the indirect method to 11 climate models to reveal the robust and non‐robust aspects of the wintertime atmospheric response to projected Arctic sea ice loss—the largest such comparison to date. We found that the models agreed on quite a few aspects of the response, including warming over the Arctic, regional surface pressure changes over Siberia and Iceland, and a slowing of the mid‐latitude jet stream. On the other hand, the models disagreed on whether surface air temperatures over Europe, North America, and East Asia will warm or cool in response to future Arctic sea ice loss. Key Points: Wintertime atmospheric response to projected Arctic sea‐ice loss can be well‐estimated indirectly from CMIP5 simulationsRobust changes across models including stronger Siberian High, weaker Icelandic Low, slower eddy‐driven jet and faster subtropical jetNon‐robust changes in surface air temperature over mid‐latitude continents and sea level pressure over the North Pacific [ABSTRACT FROM AUTHOR]

In July and August 2022, the Yangtze River basin (YRB) experienced its hottest summer since 1961. The SINTEX‐F2 seasonal prediction system initialized in early May predicted the hotter‐than‐normal summer due to its successful prediction of central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the tropical West Pacific‐East Indian Ocean (TWP_EIO). The common SST forcing explains only about 26% to the heatwave strength, while the internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land‐air interaction account for approximately 65%, based on the analysis of 108 ensemble members. These factors have collectively increased the maximum temperature over the YRB through the enhancement and westward expansion of western North Pacific subtropical high. Our findings quantify the relative contributions of external forcing and internal variations to the unprecedented hot event, offering insights into its forming mechanism and potential predictability. Plain Language Summary: A record‐breaking heatwave event occurred in the YRB in July and August 2022, posing significant risks on human health, power supply, and social economic activities. Recognizing the importance of such an event, our study aims to identify key factors influencing its prediction using the SINTEX‐F2 system. The central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the TWP_EIO provide the dominant predictability, but accounts only about 26% of the heatwave strength. However, internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land‐air interaction collectively explain about 65%. Our results suggest the necessity of large‐ensemble prediction in capturing this kind of unprecedented extreme event. Key Points: The SINTEX‐F2 initialized on 2022 early May captures the warmer‐than‐normal air temperatures in Yangtze River basinThe model successfully predicts co‐occurrences of CP La Niña and negative IOD in 2022However, the direct SST forcing contributes only 26% to the 2022 extreme event in Yangtze River basin [ABSTRACT FROM AUTHOR]

North Atlantic midlatitude cyclones are among the most severe weather systems, causing enormous economic damages and threatening human lives. The cyclone is typically characterized by cyclonic convergent surface winds, strong updrafts, and precipitation. However, extreme surface winds are often observed within the cyclone where downdrafts develop. The present study investigates the dynamical and thermodynamical characteristics of the horizontal winds impinging on the cold frontal surface and the associated downdrafts. It is shown that the cyclonic winds into the cold frontal surface are mainly responsible for the downdrafts that transport the high‐altitude horizontal momentum to the surface and cause intense surface winds. About half of the North Atlantic midlatitude cyclones are accompanied by the downdrafts especially in the southern and western parts of the cyclone center. Plain Language Summary: In the midlatitudes, air temperature decreases toward the poles, and cyclone systems typically travel eastward along regions characterized by strong meridional temperature gradients. Over the cyclone‐influencing area, the cyclonic, counterclockwise rotating, wind induces southward cold advection on the western side of the cyclone center. Therefore, during the early phase of the North Atlantic midlatitude cyclone, the generation of the cold front, which has a steep gradient of temperature to the west of the cyclone center, and that is a common feature. Even after the formation of the cold front, the horizontal winds keep impinging on the frontal surface. Then the horizontal winds blocked by the frontal surface and downdrafts are induced. The downdrafts transport the upper‐level intense wind speed to the lower level strengthening the surface winds. Key Points: Surface winds within North Atlantic midlatitude cyclones are strengthened by strong downdrafts and downward momentum transportsDowndrafts can be generated by the horizontal winds impinging on the cold frontal surfaceCyclones tend to accompany the downdrafts more to the south and west of the cyclone center [ABSTRACT FROM AUTHOR]

The climate over Europe is significantly affected by the state of the atmospheric circulation over the North Atlantic, which in turn is influenced by various slowly varying components of the climate system. Linear models are employed to investigate how much of the European winter air temperature variability can directly be predicted from the sea surface temperature. By comparing relations from a statistical model to those from an adjoint to a linearized climate model we evaluate the ability of the lagged maximum covariance analysis to reconstruct the dynamical relation between sea surface temperature (SST) and atmosphere temperature. Applied to specific SST conditions, both approaches allow prediction of a similar and significant fraction of the air temperature variability from SST. For a 1‐month lag, extreme air temperature responses are significant and found to be associated with an omega‐blocking pattern over Scandinavia. Plain Language Summary: A connection between sea surface temperature (SST) and atmospheric circulation anomalies has been established for decades. Certain SST anomalies force changes in the atmospheric circulation and cause over Europe typical weather patterns (dry and cold or wet and warm) after some lag. A relationship between the SST pattern and the associated response can be derived from numerical models or statistical relations and used for forecasting the atmospheric response to SST anomalies. In this paper, we validate this forecasting method with observational data. Key Points: Linear models show that sea surface temperature anomalies may provide significant skill for predicting northern European air temperaturesStatistical methods can provide sufficiently precise estimates of the lagged relation between sea surface and air temperature [ABSTRACT FROM AUTHOR]

It is well known that the wintertime time‐mean surface wind convergence patterns over the Kuroshio Extension and Gulf Stream show significant imprints of the underlying oceanic fronts. Previous studies have suggested that this collocation results from a time‐mean response to sea level pressure forcing from sea surface temperature gradients. However, more recent work has illustrated this phenomenon is heavily influenced by extratropical cyclones, although exact mechanisms are still debated. The purpose of this study is to introduce a new framework that explicitly distinguishes between two separate components in their contribution to the time‐mean surface wind convergence, that associated with and without atmospheric fronts. It is then argued that this distinction can help better explain the mechanisms driving the Kuroshio Extension and Gulf Stream influence on the atmosphere. Plain Language Summary: This paper presents a new framework for understanding the mean wintertime atmospheric state over the Kuroshio Extension and Gulf Stream regions, in the context of advancing our understanding of how these strong ocean currents can impact on the seasonal atmosphere. In recent years, many studies have attributed the oceanic imprint on the atmosphere in these regions to mechanisms based upon the time‐mean response. However, observational analysis here illustrates that the regional wintertime atmosphere is, in fact, dominated by continuous extratropical storm systems. It is suggested this contribution to the mean atmospheric state can be further decomposed into situations when atmospheric fronts embedded within these storms are and are not present. By studying each of these distinct atmospheric scenarios, it is then argued that the oceanic imprint on the mean wintertime atmospheric state should instead be considered as an accumulation of processes driven by mechanisms acting on a synoptic timescale, not on the timescale of the time‐mean. This framework presents a new paradigm for understanding extratropical frontal‐scale air‐sea interactions and is expected to have an immediate impact on atmospheric, oceanic, and climate communities. Key Points: Average wintertime near‐surface wind convergence over Kuroshio Extension and Gulf Stream is a direct accumulation of a baroclinic waveguideBaroclinic waveguide contribution to time‐mean convergence decomposed into atmospheric frontal and non-frontal scenariosDistinction suggests a new paradigm for understanding mechanisms of ocean‐atmosphere forcing in western boundary current regions [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]

Mg/Ca ratio in stalagmites primarily serves as an indicator of past hydrological conditions rather than temperature variations. Here, we present an Mg/Ca ratio record in a stalagmite from northern China, spanning ice age termination II. A unique finding is that Mg/Ca ratio shows a moderately strong positive correlation with cave air temperature obtained from clumped isotopes data in the same stalagmite. The stable hydrogeochemistry of source water and high temperature sensitivity of Mg partition coefficient plausibly explain this temperature dependence. Furthermore, we establish an Mg/Ca‐temperature calibration for stalagmites from mid‐latitudes, encompassing a temperature range between ∼2 and ∼15°C, where Mg/Ca = 14.221 × e0.073×T (R2 = 0.40). Applying this function to Mg/Ca ratio from similar stalagmites could tentatively provide a quantitative regional temperature record over millennial and centennial timescales. This research highlights Mg/Ca ratio in stalagmites as a potential palaeo‐temperature proxy and introduces, for the first time, a tentative Mg/Ca‐temperature calibration function for speleothems. Plain Language Summary: Stalagmite is one type of speleothems that grow from the floor of caves. The geochemical indexes within stalagmites, such as Mg/Ca ratio, can help us to understand the past climate changes. Here, we conducted a study on a stalagmite from northern China during ice age termination II. Traditionally, Mg/Ca ratios in stalagmites have been used to investigate past hydrological conditions. However, we found that Mg/Ca ratio matches the cave air temperature obtained from clumped isotopes data within the same stalagmite. This correlation was explained by the stable chemistry of the source water and the sensitivity of Mg partition coefficient to temperature. We also developed a tentative formula to calculate past temperature from Mg/Ca ratio in similar speleothems. Key Points: A Chinese stalagmite at termination II shows moderately strong positive correlation between Mg/Ca ratio and clumped isotopes‐temperatureStable drip water hydrogeochemistry and high temperature sensitivity of Mg partition coefficient may explain this temperature dependenceWe tentatively establish, for the first time, an Mg/Ca‐temperature calibration function for speleothems [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]

While previous studies have largely focused on anthropogenic warming characterized by surface air temperature, little is known about the behaviors of human‐perceived temperature (HPT), which describe the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity and/or wind speed. Here we adopted an optimal fingerprinting method to compare seasonal mean HPTs in China with those from simulations conducted with multiple climate models participating in the Coupled Model Intercomparison Project Phase 6. We found clear anthropogenic signals in the observational records of changes in both summer and winter HPTs over the period 1971–2020. Moreover, the anthropogenic greenhouse gas influence was robustly detected, with clear separation from natural and anthropogenic aerosol forcings. The anthropogenic greenhouse gas forcing plays the dominant role (>90%) of human‐perceived warming. Urbanization effects contribute slightly and moderately to the estimated trends in summer and winter HPTs, respectively, in addition to the effects of external forcing. Plain Language Summary: Human influences have been identified in the observed warming quantified by surface air temperature (SAT), but SAT alone is inadequate as a metric for human thermal comfort. Here we focus on human‐perceived temperature (HPT), which describes the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity, and/or wind speed. We isolate anthropogenic impacts on the observed increase in summer and winter HPTs in China during 1971–2020 by comparing observations with state‐of‐the‐art climate models. Results show that the influence of anthropogenic greenhouse gas is detected, with clear separation from other external forcings such as solar and volcanic activities and anthropogenic aerosols. The human‐induced greenhouse gas increases are also found to explain most (>90%) of the observed human‐perceived warming. Along with the effects of large‐scale anthropogenic forcing, urbanization effects also have a slight to moderate influence on the estimated trends in summer and winter HPTs. Our work is an early attempt to provide quantitative evidence for the physiological impacts of anthropogenic global warming and local urbanization on human beings. Key Points: The warming is quantified by human‐perceived temperature that considers the joint effects of temperature, humidity and/or wind speedHuman influence could be robustly detected in both summer and winter human‐perceived warmingThe observed increase in human‐perceived temperature is mostly attributed to anthropogenic greenhouse gas increases [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]

The D/H ratio in water on Mars, Rwater, is 4–6× the Earth ratio, signifying past water loss to space. Recently, measurements have revealed high values of the D/H ratio in hydrogen, Ratomic, in the thermosphere during southern summer. Here, we use a photochemical model to explore the potential drivers of Ratomic, testing three: thermospheric temperatures, excess mesospheric water, and changing insolation. We find that Ratomic can achieve values between 15× the Earth ratio (due to water) and 23× the Earth ratio (due to temperature). The effects arise because H escape is diffusion‐limited, while D escape is energy‐limited. Our results underscore how Ratomic reflects mesospheric dynamics, and the need for concurrent measurements of mesospheric water, thermospheric temperatures, and Ratomic to understand seasonal changes in the martian water cycle and atmospheric loss. Plain Language Summary: The high ratio of deuterium (D) to hydrogen (H) measured in water molecules on Mars indicates that much of Mars' past water has escaped to space. Recent measurements of the D/H ratio in the atoms themselves using data from the MAVEN spacecraft have revealed a ratio as high as 100 times the Earth value. In this work, we use a computational model of the Mars atmosphere to explore whether the large values could be caused by seasonal changes in three atmospheric parameters: the upper atmospheric temperature, the presence of extra water vapor in the middle atmosphere, and the incoming solar radiation. We find that temperature and water vapor have comparable effects, with each leading to an atomic D/H ratio similar to those found by MAVEN observations. We also explain how temperature and water affect the dynamics of H and D in the atmosphere to cause the change in the ratio. Key Points: Seasonal increases in exobase temperature or mesospheric water can enhance the upper atmospheric atomic D/H ratio up to 15–23 times VSMOWThe enhancement occurs due to dynamical differences, leading to similarities in D/H ratio but differences in abundance and escapeConcurrent measurements of temperatures, water vapor, and the D/H ratio will enhance our understanding of atmospheric escape from Mars [ABSTRACT FROM AUTHOR]

We simulated the seasonal temperature evolution in the atmosphere of Antarctica and the Arctic focusing on infrared processes. Contributions by other processes were parametrized and kept fixed throughout the simulations. The model was run for current CO2 and CH4 and for doubled concentrations. For doubling CH4 the warming in Antarctica is restricted to the lowest few hundred meters above the surface while in the Arctic we find a warming in the whole troposphere. We find that the amount of water is the main driver for the differences between both polar regions. When increasing both, CO2 and CH4 from pre‐industrial values to current concentrations, and averaged over the whole troposphere, we find a warming of 0.42 K for the Arctic and a slight cooling of 0.01 K for Antarctica. Our results contribute to the understanding of the lack of warming seen in Antarctica throughout the last decades. Plain Language Summary: In 2015 we have initiated a discussion on a fundamental property of the radiation in the atmosphere over Antarctica: The negative greenhouse effect (Schmithüsen et al., 2015, https://doi.org/10.1002/2015GL066749). A negative greenhouse effect means, the atmosphere emits more radiation to space than it receives from the surface. This results in a cooling somewhere in the Antarctic atmosphere during some months of the year, when increasing CO2. We now simulate how the Antarctic atmospheric temperature responds in all altitude levels to CO2 and CH4 increases, and show this is different from the temperature response in the Arctic. We show for example, that an increase in CH4 cools nearly the whole troposphere, although the response for CH4 is much lower in amplitude than for CO2. We find that the amount of water is the main driver for the differences between both polar regions. Since the amount of water vapor strongly depends on temperature, the colder Antarctic atmosphere responds differently to the Arctic when greenhouse gases increase. Our studies could be one important factor when understanding the lack of warming in Antarctica throughout the last decades. Key Points: We simulate the temperature development in both polar regions in the infrared and find that doubling CO2 and CH4 lead to opposing forcingsThe different amount of water vapor shows to be responsible for the differences in warming/cooling in both polar regionsIn Antarctica doubling CH4 leads to a cooling of almost the whole troposphere, a future increase in H2O could invert this [ABSTRACT FROM AUTHOR]

Quantitative methods to pinpoint the origin of atmospheric temperature anomalies (T′) associated with heatwaves are pivotal for the construction of physically plausible synoptic storylines of heatwave formation and their evaluation in models. Here, we combine a Lagrangian T′ decomposition with concepts from moisture tracking techniques to identify where and when the principal physical processes generate T′ and to attribute these sources to synoptic weather systems. Applying this framework to near‐surface and free‐tropospheric T′ associated with the record‐shattering 2021 heatwave in the Pacific Northwest shows that ascending, diabatic air streams in North Pacific cyclones contribute more than 50% of free‐tropospheric T′, whereas near‐surface T′ is mainly produced by local subsidence and diabatic heating with only marginal upstream contributions. Since free‐tropospheric T′ facilitates near‐surface accumulation of locally produced T′ by rendering the atmosphere stable to moist convection, our findings corroborate the notion of top‐down induced heatwave formation fueled by upstream diabatic processes. Plain Language Summary: Heatwaves, characterized by strongly above normal air temperatures, are amongst the most severe weather related threats to human lives and economic activities. Understanding the processes causing heatwaves and evaluating their representation in climate models requires suitable quantitative methods to diagnose the process' contributions to temperature anomalies. While it is well established which physical processes can create positive temperature anomalies, that is, transport of air from climatologically warmer regions, warming of air as it is compressed in sinking motion, and heating, for example, by a hot surface, it remains challenging to diagnose where and when these processes create temperature anomalies. Here, we present a quantitative framework based on the tracking of air parcels that allows us to obtain this kind of information. Applying this method to a recent devastating heatwave in the Pacific Northwest, we show that even though the air at the surface acquired its temperature anomaly mainly by local heating, storms over the North Pacific contributed substantially to warming the air aloft. This anomalously warm air aloft, in turn, was a pre‐requisite for the extreme accumulation of heat near the surface by suppressing the formation of thunderstorms, which would have had a cooling effect. Key Points: Novel diagnostic framework quantifies sources of atmospheric temperature anomalies (T′) generated by principal physical processesUpstream warm conveyor belts (WCBs) contributed >50% of free‐tropospheric T′ and <15% of near‐surface T′ to the 2021 Pacific Northwest (PNW) heatwaveImportance of upstream sources of free‐tropospheric T′ corroborate top‐down induced formation of PNW heatwave fueled by WCBs [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]

Ensemble Forecast Sensitivity to Observation (EFSO) is a technique that can efficiently identify the beneficial/detrimental impacts of every observation in ensemble‐based data assimilation (DA). While EFSO has been successfully employed on atmospheric DA, it has never been applied to ocean or coupled DA due to the lack of a suitable error norm for oceanic variables. This study introduces a new density‐based error norm incorporating sea temperature and salinity forecast errors, making EFSO applicable to ocean DA for the first time. We implemented the oceanic EFSO on the CFSv2‐LETKF and investigated the impact of ocean observations under a weakly coupled DA framework. By removing the detrimental ocean observations detected by EFSO, the CFSv2 forecasts were significantly improved, showing the validation of impact estimation and the great potential of EFSO to be extended as a data selection criterion. Plain Language Summary: This study introduces a new method to efficiently estimate the beneficial/detrimental impacts of each oceanic observation in the air‐sea coupled data assimilation (CDA) by incorporating the forecast errors for sea temperature and salinity with a novel density norm. For the first time, we implemented this approach onto the operational‐like CDA system and examined the impacts of ocean observations on the National Centers for Environmental Prediction CFSv2 forecasts. Our findings demonstrate that assimilating ocean profiles and satellite‐retrieved sea surface temperature products significantly improves the CFSv2 forecasts. Moreover, after excluding the detrimental ocean observations identified by our new method, we observed significant improvements in the CFSv2 forecasts. This result validates the accuracy of impact estimation and underscores its great potential as a data selection criterion in CDA. Key Points: A new oceanic Ensemble Forecast Sensitivity to Observation (EFSO) is proposed and implemented on the CFSv2 to investigate observation impactsThe 24‐hr CFSv2 forecasts of sea temperature, salinity, and 2‐m air temperature were improved by 1.5%, 0.8%, and 0.4%, respectively, after removing detrimental ocean observations detected by EFSOThe improvements in the CFSv2 forecast can last for at least 5 days for the ocean and 3 days for the low‐level atmosphere [ABSTRACT FROM AUTHOR]

Extreme climate events are societally harmful and have increased in frequency and intensity in recent decades. Indices based on temperature and precipitation are a valuable way to quantify climate extremes. Certain indices are defined relative to percentiles, which are dependent on a climatological baseline period. In this study, indices computed using temperature and precipitation from the Modern Era Retrospective Analysis for Research and Applications, Version 2 are calculated using percentiles from three baseline periods: 1981–2010, 1991–2020 and 1981–2020. Updating the baseline period from 1981 to 2010 to 1991–2020 leads to significant changes in the quantification of temperature and precipitation extremes over the United States over 1980–2021. Using the later baseline period indicates more cold extremes, fewer warm extremes, and fewer but more intense precipitation extremes throughout the US, with regional variation. Changing the baseline period can mislead the public and decision makers, potentially undermining the appropriate response to climate‐related health risks. Plain Language Summary: Indices computed using 2‐m air temperature and precipitation are used to represent extreme climate events such as heat waves, cold waves, heavy precipitation, and drought. Some indices are defined relative to percentile‐based thresholds, which are computed using a baseline climatology period. The baseline climatology is typically a thirty‐year period and is updated every ten years. This study examines how updating the baseline climatology period from 1981–2010 to 1991–2020 affects the quantification of climate extremes in the United States over 1980–2021. In general, since the 1991–2020 period is warmer than 1981–2010 throughout the United States, there are fewer warm extremes detected and more cold extremes detected when it is used as the baseline. The differences are most notable in the southwest and northeast United States. The changes in the precipitation indices vary throughout the country, but in certain parts of the southern and central United States, updating the baseline period leads to the detection of fewer but heavier extreme precipitation events. It is important to communicate the choice of baseline climatology period to prevent misinterpretation of the extreme climate indices and the comparison of different studies. Key Points: Updating the baseline period from 1981–2010 to 1991–2020 leads to significant changes in percentile‐based extreme climate indices in the USTemperature indices show generally increased cold extremes and decreased warm extremes across the US when the baseline period is updatedFor precipitation indices, the later baseline period indicates fewer but more intense extreme events in the south and central US [ABSTRACT FROM AUTHOR]

Significant imbalances in terrestrial water storage (TWS) and severe drought have been observed around the world as a consequence of climate changes. Improving our ability to monitor TWS and drought is critical for water‐resource management and water‐deficit estimation. We use continuous seismic ambient noise to monitor temporal evolution of near‐surface seismic velocity, dv/v, in central Oklahoma from 2013 to 2022. The derived dv/v is found to be negatively correlated with gravitational measurements and groundwater depths, showing the impact of groundwater storage on seismic velocities. The hydrological effects involving droughts and recharge of groundwater occur on a multi‐year time scale and dominate the overall derived velocity changes. The thermoelastic response to atmospheric temperature variations occurs primarily on a yearly timescale and dominates the superposed seasonal velocity changes in this study. The occurrences of droughts appear simultaneously with local peaks of dv/v, demonstrating the sensitivity of near‐surface seismic velocities to droughts. Plain Language Summary: Terrestrial water storage (TWS) is fundamental to the well‐being of inhabitants on Earth. However, current approaches to measure TWS variations have limited temporal or spatial resolution. In this study, we use near‐surface seismic velocity variations, dv/v, derived from continuous seismic recordings to monitor changes of TWS in central Oklahoma. A negative correlation between the long‐term trend of dv/v with gravity measurements reflects the impact of groundwater recharge/discharge on near‐surface seismic velocity. In addition, a seasonal cycling of dv/v has similar periodicity to recordings of air temperature, which can be explained by thermo‐elastic strain at the subsurface. Comparisons between dv/v and drought index further show the possibility of using near‐surface seismic velocity as a proxy for monitoring severe drought for local communities. Considering the high temporal sampling and flexible spatial deployment, seismometers may be used to monitor subsurface water distributions. This can be useful for sustainable water management and reliable water‐deficit estimation. Key Points: A long‐term trend of dv/v in Oklahoma correlates well with gravity measurements, which may reflect groundwater recharge and dischargeShort‐term peaks of dv/v agree with the drought index, demonstrating a potential for monitoring meteorological droughtsA seasonal cycle of dv/v in central Oklahoma can be explained by thermo‐elastic strains driven by atmospheric temperature changes [ABSTRACT FROM AUTHOR]

This study investigates Gulf Stream (GS) sea surface temperature (SST) anomalies associated with the extratropical transition (ET) of tropical cyclones (TCs) in the North Atlantic. Composites of western North Atlantic TCs indicate that GS SSTs are warmer, and both large‐ and fine‐scale SST gradients are weaker than average, for TCs that begin the ET process but do not complete it, compared with TCs that do. Further analysis suggests that the associated fine‐scale GS SST gradient anomalies are related to atmospheric processes but not the same as those that are typically associated with the onset of ET. As sensible heat flux gradients and surface diabatic frontogenesis are shown to generally scale with the local SST gradient strength, these results suggest that knowledge of the fine‐scale GS SST gradient in the weeks prior to the arrival of a TC might potentially provide additional information regarding the likelihood of that system completing ET. Plain Language Summary: Tropical cyclones can undergo a process known as extratropical transition as they move toward higher latitudes. The resultant weather systems can cause extensive damage and can be difficult to forecast. This study discusses how knowledge of the Gulf Stream sea surface temperature gradients in the week prior to the passage of a tropical cyclone may provide additional insight into whether that tropical cyclone will complete extratropical transition in the region. In particular, we discuss how fine‐scale sea‐surface temperature gradients can modulate the gradient in heat exchange between the ocean and the atmosphere, and in turn influence how favorable the lower atmosphere is to the development of sharp atmospheric temperature gradients. Key Points: Gulf Stream sea surface temperature anomalies are statistically related to the completion of tropical cyclone extratropical transitionFine‐scale sea surface temperature gradients present do not come from an atmospheric setup conducive to extratropical transition completionThe associated sensible heat flux gradients may potentially influence extratropical transition by impacting frontogenesis in the region [ABSTRACT FROM AUTHOR]

Since climate model studies project a decline of the Atlantic Meridional Overturning Circulation (AMOC) in the 21st century, monitoring AMOC changes remains essential. While AMOC variability is expected to be coherent across latitudes on longer than decadal timescales, connectivity on inter‐annual and seasonal timescales is less clear. Model studies and observational estimates disagree on the regions and timescales of meridional connectivity and AMOC observations at multiple latitudes are needed to study its connectivity. We calculate basin‐wide AMOC volume transports (1993–2018) from measurements of the North Atlantic Changes (NOAC) array at 47°N, combining data from moored instruments with hydrography and satellite altimetry. The mean NOAC AMOC is 17.2 Sv exhibiting no long‐term trend. Both the unfiltered and low‐pass filtered NOAC AMOC show a significant correlation with the RAPID‐MOCHA‐WBTS AMOC at 26°N when the NOAC AMOC leads by about one year. Plain Language Summary: In the North Atlantic Ocean, currents transport heat and salt from the warm subtropical regions to the colder and less saline subpolar regions. This current system is part of the Atlantic Meridional Overturning Circulation (AMOC). This enormous northward heat transport associated with the AMOC impacts regional and global climate. In a warming world, climate models project a reduction of the AMOC, affecting, for example, air temperature and rain patterns over the continents. Continuous observations are required to investigate whether climate models realistically simulate the AMOC and assess the validity of these projections. We calculate the AMOC from moored observations, hydrography, and satellite data at 47°N from 1993 to 2018. In this period, the AMOC at 47°N does not show a trend. The 26°N AMOC lags the 47°N AMOC by about one year, indicating that the AMOC evolution at these two latitudes is connected. Key Points: We present a 25‐year observational Atlantic Meridional Overturning Circulation (AMOC) volume transport record at 47°N with a mean basin‐wide AMOC transport of 17.2 SvThe inter‐annual variability at 47°N is similar to the RAPID AMOC at 26°N, while the monthly variability is much stronger at 47°NThe AMOC time series at 47°N and 26°N show a significant lag correlation when the AMOC at 47°N leads by about one year [ABSTRACT FROM AUTHOR]

North Atlantic Oscillation (NAO) has a significant impact on surrounding winter weather and climate. However, the causes of its occasional reversal between early and late winter remain unclear. This study proposes a mechanism for the mid‐winter reversal of NAO from the perspective of local midlatitude air‐sea interaction. Strong sea surface temperature (SST) tripole events, which are defined by empirical orthogonal function of winter‐mean interannual North Atlantic SST anomalies, are primarily induced by NAO in early winter and peak in January. In late winter, the persistent SST tripole exerts active feedback on atmosphere through diabatic heat and transient eddy forcing. The resulting atmospheric circulation anomalies exhibit an almost reversed NAO pattern in February, which forms a wavetrain originating above the Gulf Stream and propagating to the Middle East and weakens the former SST tripole. Consequently, significant reversals of air temperature anomalies occur in Europe and the Caspian Sea area between February and December. Plain Language Summary: The North Atlantic Oscillation (NAO) is a crucial atmospheric system that significantly impacts the weather and climate of the surrounding regions during winter. However, it often reverses between early and late winter, and the reasons for its mid‐winter reversal remain unclear. The NAO behavior can be influenced by multiple factors, such as atmospheric internal processes, underlying surface, and remote climate system, which makes the issue more complex. This study highlights the role of underlying sea surface temperature anomalies (SSTAs) in the mid‐winter reversal of NAO. The North Atlantic SSTAs are closely associated with the NAO and exhibit a tripole pattern. For strong sea surface temperature (SST) tripole events, the NAO primarily induces the early winter North Atlantic SST tripole. The SSTAs develop in early winter, peak in January, and feedback on the atmospheric circulation in late winter. The atmospheric circulation anomalies exhibit an almost reversed NAO pattern in February, forming a wavetrain that propagates above the Gulf Stream to the Middle East. As a result, during the warm phase of the SST tripole, Europe experiences colder temperatures, and the Caspian Sea experiences warmer temperatures in February than usual, as opposed to the positive NAO's control over warm Europe and cold Caspian Sea in December. Key Points: In early winter, North Atlantic Oscillation (NAO) forces a North Atlantic sea surface temperature (SST) tripole, which persists and tends to induce a nearly reversed NAO pattern in FebruarySST tripole induces a wavetrain over the Gulf Stream to the Middle East via diabatic heating and transient eddy forcing in FebruaryAs a result, there are remarkable reversals of air temperature anomalies in Europe and Caspian Sea area between February and December [ABSTRACT FROM AUTHOR]

Rainfall high on the Greenland Ice Sheet is an emerging phenomenon with consequences for the thermal and structural makeup of the surface layer. We document changes to Greenland's firn column due to a 4‐day cold‐season warm/rain event. Heavy precipitation occurred with a sudden 30°C increase in air temperature, reaching 0°C at 2,000 m elevation. Thermistor strings within the firn layer across a 35 km transect show rapid warming of 6°–23°C reaching depths of 2–10 m. Antecedent conditions governed the magnitude, duration, and depth‐distribution of sensible and latent heat added to the firn column. Heat fluxes from the firn layer required up to 8 weeks to recover to baseline, a significant fraction of the winter period. The amount of liquid water refrozen in the firn column was ∼20%–100% of the prior summer demonstrating the impact of extreme weather events on the ice sheet's evolution and runoff characteristics. Plain Language Summary: Based on measurements from a network of sensors installed on the Greenland Ice Sheet, we document changes in the firn layer (snow in transition to ice) due to a late Autumn extraordinary warm/rain event. After an extended period of cold‐season cooling of the firn, the event caused the firn layer to warm by 6°–23°C, mainly in one day, as rainwater and surface melt penetrated up to 6 m depth and refroze. The water added to the firn layer during this extreme weather event was ∼25%–100% of what was added during the entire previous summer melt season. The unusual timing of water input during the cold‐season likely altered the firn differently than summer input from melt or rain. Our results demonstrate that only a minor increase in the frequency and magnitude of similar rain events has potential for outsized impact on the thermal and density transformation of Greenland's firn layer which has implications for future runoff processes. Key Points: A cold‐season rainstorm on the Greenland Ice Sheet demonstrates outsized impact of extreme weather events on evolution of the firn layerFirn layer temperature quickly increased by up to 23°C, altering heat fluxes and requiring up to 2 months to thermally recoverThe liquid water refrozen within the firn layer was ∼20%–100% of the amount of water refrozen during the previous summer [ABSTRACT FROM AUTHOR]

Radiation energy balance at the top of the atmosphere (TOA) is a critical boundary condition for the Earth climate. It is essential to validate it in the global climate models (GCM) on both global and regional scales. However, the comparison of overall radiation field is known to conceal compensating errors. Here we use a new set of radiative kernels to diagnose the radiation biases caused by different geophysical variables in the GCMs of the Coupled Model Intercomparison Project. We find although clouds remain a primary cause of radiation biases, the radiation biases caused by non‐cloud variables are of comparable magnitudes. Many GCMs have a cold air temperature bias and a moist tropospheric humidity bias, which lead to considerable biases in TOA radiation budget but are compensated by cloud biases. These findings signify the importance of validating the GCM simulations in terms of both the overall and component radiation biases. Plain Language Summary: Radiation energy balance at the top of atmosphere is crucial to the Earth climate system and is routinely examined in climate model validations. Here, we show that seemingly good agreements between model and observation can be due to compensating errors and propose the use of a kernel method for separately identifying component radiation biases due to different geophysical variables, which may afford a more stringent test of climate models. Key Points: Climate models are subject to compensating radiation biases caused by cloud and non‐cloud variablesMany models have a cold temperature bias and a moist tropospheric humidity biasKernel diagnosis of component radiation biases affords a stricter test for climate models [ABSTRACT FROM AUTHOR]

During the last decades, the Baltic Sea has been among the fastest warming seas in the world. The warming is mainly driven by increasing air temperatures but deeper water layers can also be warmed by lateral advection of heat. By analyzing a 159 years long (1850–2008) hindcast simulation of the Baltic Sea, we link the exceptionally strong bottom water warming in the western Baltic Sea to a shift in the seasonality of saltwater inflows from the North Sea to the Baltic Sea. Over the model period, warm summer and early autumn inflows have increased while cold winter inflows have decreased. Sensitivity experiments reveal that these changes were partly driven by a shift in river runoff seasonality. The strong warming could lead to faster oxygen depletion in the affected layers and thus have ecological consequences. Plain Language Summary: The Baltic Sea is home to various marine and freshwater species and an important economic factor for the surrounding countries. Like other seas, the Baltic Sea is getting warmer due to climate change. The water at the surface warms especially fast because it takes up heat from the warming atmosphere. After some time, temperatures also increase in deeper layers. However, some deep parts in the western Baltic Sea are warming even faster than the sea surface. In our study, we investigate if the exceptional warming can be explained by an increase in warm saltwater inflows from the North Sea. Hence, we use a model simulation of the Baltic Sea for over 150 years to compare long time series of warm inflows and the temperatures in the deep layers of the western Baltic Sea. We find a strong correlation. Thus, we can link the exceptional warming in the deep layers of the western Baltic Sea during the last decades to an increase in warm inflows. The warming has ecological consequences since in warmer water, the oxygen is consumed faster and the deep water layers of the Baltic Sea are suffering from low oxygen concentrations. Key Points: Summer and early autumn salt import into the Baltic Sea increased significantly since 1851 compared to the annual salt importSalt import between June and October is highly correlated with the annual sub‐thermocline temperature maximum in the western Baltic SeaThe shift in inflow seasonality was partly caused by seasonal changes in river runoff [ABSTRACT FROM AUTHOR]

East Asian winter weather has altered dramatically in response to progressing climate change. However, analysis of time‐averaged atmospheric fields might obscure climate change signals that could relate to specific types of events. This study aimed to detect climate change signals for various background atmospheric fields by applying classification to daily surface pressure patterns. We found a pronounced trend of increase in surface air temperature over Japan since the 1980s, stronger than the seasonal mean trend, when dominating cold air advection from the Sea of Okhotsk. This cold air was warmed and humidified by the retreat of sea ice in the Sea of Okhotsk. In contrast, the warming trend was mitigated when warm air advection was dominant. These results highlight the importance of daily background atmospheric conditions in amplifying and localizing the impact of regional climate change. Plain Language Summary: Winter weather in East Asia varies greatly depending on the daily surface pressure pattern. Hence, the impact of climate change could appear in different forms according to specific weather conditions. This study aimed to detect long‐term changes in atmospheric fields under various weather conditions. Focusing on the daily surface pressure patterns, analysis of East Asian winters showed substantial historical increase in surface air temperature when northerly cold air outbreaks brought colder air toward Japan, and the warming rate was stronger than the trend of the winter average. The retreat of sea ice in the Sea of Okhotsk, located upwind of Japan, caused this local warming and humidification. In contrast, the warming trend was weaker for days when the pressure pattern brought warmer air toward Japan. This finding indicates that winter days with cold air flowing around Japan have been warming more strongly than warm winter days. Our analysis enables assessment of the impact of global warming on specific weather conditions of interest. Key Points: Historical changes in winter climate in Japan were decomposed based on pressure pattern classificationNortherly winter monsoon has been substantially warmed and humidified around Japan due to sea ice retreat in the upwind seaPressure patterns that cause stronger regional response to climate change were identified [ABSTRACT FROM AUTHOR]

At most latitudes, the seasonal cycle of zonal‐mean surface air temperature is notably asymmetric: the length of the warming season is not equal to the length of the cooling season. The asymmetry varies spatially, with the cooling season being ∼40 days shorter than the warming season in the subtropics and the warming season being ∼100 days shorter than the cooling season at the poles. Furthermore, the asymmetry differs between the Northern Hemisphere and the Southern Hemisphere. Here, we show that these observed features are broadly captured in a simple model for the evolution of temperature forced by realistic insolation. The model suggests that Earth's orbital eccentricity largely determines the hemispheric contrast, and obliquity broadly dictates the meridional structure. Clouds, atmospheric heat flux convergence, and time‐invariant effective surface heat capacity have minimal impacts on seasonal asymmetry. This simple, first‐order picture has been absent from previous discussions of the surface temperature seasonal cycle. Plain Language Summary: Away from the equator, most places on Earth experience a noticeable seasonal cycle in surface air temperature. The seasonal cycle of temperature governs many aspects of human and ecosystem behavior. Observations show that, at most latitudes, the length of the warming season is not equal to the length of the cooling season, that is, the seasonal cycle is asymmetric. For example, at 25°N, the average warming season is 35 days longer than the cooling season. Here, we look at how this asymmetry varies with distance from the equator. We find that the asymmetry can largely be explained as a result of variations in the amount of radiation from the sun that reaches Earth, which are determined by Earth's orbit. Key Points: The seasonal cycle in zonal‐mean surface air temperature is asymmetricThe warming period tends to be shorter than 6 months in high latitudes and longer than 6 months in low latitudesThe asymmetry can largely be explained by variations in top‐of‐atmosphere insolation, dictated by Earth's orbit [ABSTRACT FROM AUTHOR]

The existence of a cool sea surface skin layer in the global ocean during both day and night is generally recognized. However, a warm skin should be present if the total surface net heat flux (Qnet ${Q}_{\mathrm{n}\mathrm{e}\mathrm{t}}$) were to be from the atmosphere into ocean. Saildrone, an advanced uncrewed surface vehicle, has been shown to be able to provide sufficiently accurate sea skin temperature (SSTskin) and subsurface temperature (SSTdepth) data at high latitudes. Using those SST data along with meteorological parameters from a Saildrone deployed in the Arctic in the summer of 2019, some warm skin layers were identified due to the Qnet ${Q}_{\mathrm{n}\mathrm{e}\mathrm{t}}$ gain resulting from the combined effect of positive air‐sea temperature difference, humid surface air and cloudy skies. Furthermore, most warm skins here were found during and shortly after rainfall events. It is essential to incorporate the ability to simulate warm skin layers in the present cool skin models. Plain Language Summary: In most cases, the sea‐surface temperature of the skin of the ocean (SSTskin) is cooler than the temperature at the base of skin layer, which is a layer in which the vertical transport of heat is primarily by molecular conduction rather than turbulent mixing. By analyzing the Saildrone data measured in 2019 summer at the Pacific sector of the Arctic Ocean, some unusual warmer SSTskin signals were revealed and which are shown to be physically reasonable. This finding indicates the near‐surface thermal structure needs to be better understood and further studied. Key Points: Using skin and subsurface ocean temperatures and atmospheric variables from Saildrones to identify warm skin layers at high latitudesWarm skins are mostly present with positive air‐sea temperature difference and humid air under cloudy skiesWarm skin is often associated with the occurrence of rainfall and model schemes for the warm skin necessarily need to be established [ABSTRACT FROM AUTHOR]

The explosive 2022 Tonga submarine volcanic eruption produced a globally propagated atmospheric disturbance. A leading Lamb wave pulse was recorded as a pressure pulse worldwide. A weather‐station network in Japan recorded the pressure pulse together with temperature and wind conditions during the passage of the pulse. Individual temperature and wind records indicate little simultaneous change. However, after alignment of records at the time of pressure pulse arrivals and stacking, clear temperature and wind changes synchronized with the pressure change are evident. Assuming Lamb wave propagation, the synthesized temperature and wind changes from the pressure record show a good match with the observed waveforms. The observed wind speed and pressure change of the Lamb pulse yielded a total energy transported by the pulse of 4.2 × 1016 J. Plain Language Summary: Atmospheric disturbance caused by the violent 2022 Tonga volcanic eruption was recorded by multiple types of sensors on the ground. The leading pressure signals, of about 20 min duration and about 2 hPa amplitude, were observed in a nationwide weather network in Japan as an anomaly that stands out from the background atmospheric pressure trend. Other meteorological sensors such as temperature and wind components were also in operation, but expected changes are on the order of 0.15 K and 0.5 m/s over the 20 min signal duration, too small to be detected in individual records. Using a pressure signal as a time mark for data alignment, we averaged all temperature and wind components parallel to the direction from Tonga toward Japan recorded by the network. Such averaging steps greatly reduced the spatially incoherent background noise and enhanced the signals coherent with the arrival of the pressure pulse. The resultant temperature and wind changes are comparable to the theoretically predicted ones. The measured temporal changes of atmospheric pressure and air flow enable direct estimation of the energy flow transported by the pressure pulse. The estimated total energy transported by the pressure pulse is between (3.8–4.6) × $\times $ 1016 J. Key Points: Stacking nationwide weather network records reveals temporal changes in temperature and wind flow synchronized with the Lamb pressure pulseObserved temporal variations are close to the adiabatic air compression and Lamb wave flow models expected from the pressure pulseAnalysis of observed wind speed and pressure changes reveals that the total energy transported by the Lamb pulse was 4.2 × 1016 J [ABSTRACT FROM AUTHOR]

Establishing the timing of maximum Holocene warmth in the Arctic is critical for understanding global climate system response to external forcing. In Greenland, challenges in obtaining climate records that span the full Holocene have hampered efforts to robustly identify when the Holocene Thermal Maximum occurred. Reconstructing land‐based ice sheet history can fill this gap because these ice sheet regions respond sensitively to summer temperature. We synthesize new and published 10Be and 14C ages from southwest Greenland to map Greenland ice sheet margin positions from 12 to 7 ka and calculate retreat rates from 12 to 0 ka. We found that maximum Greenland ice sheet recession occurred between ~10.4 and 9.1 ka. Our reconstruction suggests that summer air temperatures in southwest Greenland were highest from ~10.4 to 9.1 ka, providing support for an early regional Holocene Thermal Maximum. These results can serve as benchmarks for comparison with ice sheet and climate model simulations. Plain Language Summary: As the climate warms, Arctic temperatures are expected to increase at a faster rate than the rest of the world. Previous research has determined that Arctic temperatures were several degrees Celsius higher than today at some point in the past 12,000 years, and understanding when this warm time occurred might give scientists important insights into Arctic climate conditions in the future. However, in Greenland, the timing of maximum warmth is not well defined because many existing climate reconstructions do not span all of the past 12,000 years. In this paper, we use the retreat rate of the western Greenland ice sheet to determine when the warmest time of the past 12,000 years occurred. This method is advantageous because (1) retreat rates of this part of the Greenland ice sheet are directly related to summer air temperature and (2) the retreat history of the western Greenland ice sheet retreat is well known. We bring together new and previously published data that relates to Greenland ice sheet change to calculate how quickly the ice sheet retreated between 12,000 years ago and the present. Using this information, we determined that the warmest time of the past 12,000 years occurred between about 10,400 and 9,100 years ago, which is several thousand years earlier than some previous estimates. These results can help improve computer simulations that are used to predict future changes in Arctic ice sheet extent, climate, and sea‐level. Key Points: We create a database of southwest Greenland ice sheet extents and retreat rates that can be used to assess ice sheet model performanceThe highest southwest Greenland ice sheet retreat rates occurred between 10,400 and 9,100 years agoOur record supports an early Holocene Thermal Maximum in southwest Greenland [ABSTRACT FROM AUTHOR]

Retrospectively comparing future model projections to observations provides a robust and independent test of model skill. Here we analyze the performance of climate models published between 1970 and 2007 in projecting future global mean surface temperature (GMST) changes. Models are compared to observations based on both the change in GMST over time and the change in GMST over the change in external forcing. The latter approach accounts for mismatches in model forcings, a potential source of error in model projections independent of the accuracy of model physics. We find that climate models published over the past five decades were skillful in predicting subsequent GMST changes, with most models examined showing warming consistent with observations, particularly when mismatches between model‐projected and observationally estimated forcings were taken into account. Plain Language Summary: Climate models provide an important way to understand future changes in the Earth's climate. In this paper we undertake a thorough evaluation of the performance of various climate models published between the early 1970s and the late 2000s. Specifically, we look at how well models project global warming in the years after they were published by comparing them to observed temperature changes. Model projections rely on two things to accurately match observations: accurate modeling of climate physics and accurate assumptions around future emissions of CO2 and other factors affecting the climate. The best physics‐based model will still be inaccurate if it is driven by future changes in emissions that differ from reality. To account for this, we look at how the relationship between temperature and atmospheric CO2 (and other climate drivers) differs between models and observations. We find that climate models published over the past five decades were generally quite accurate in predicting global warming in the years after publication, particularly when accounting for differences between modeled and actual changes in atmospheric CO2 and other climate drivers. This research should help resolve public confusion around the performance of past climate modeling efforts and increases our confidence that models are accurately projecting global warming. Key Points: Evaluation of uninitialized multidecadal climate model future projection performance provides a concrete test of model skillThe quasi‐linear relationship between model/observed forcings and temperature change is used to control for errors in projected forcingModel simulations published between 1970 and 2007 were skillful in projecting future global mean surface warming [ABSTRACT FROM AUTHOR]

The response of the Euro‐Atlantic wintertime circulation to climate change is deeply uncertain. The Atlantic jet is caught in a "tug‐of‐war" between rapid warming trends in both the tropics and the Arctic leading to debate over the changing "waviness" of the jet, which is subject to strong non‐linearity and internal variability. From the complementary perspective of weather regimes, there is considerable uncertainty in how atmospheric blocking will alter under climate change. By applying the hybrid approach of geopotential‐jet regimes to 6th phase of the coupled model inter‐comparison project projections, we show that the centers of action of anticyclonic regimes hardly alter even under severe warming. Instead, regimes are expected to become less persistent, with zonal flow conditions becoming more prevalent, although models disagree on the details of regime changes. Finally, we show the regime response can be captured qualitatively in a simple Lorenz‐like model, emphasizing the conceptual link between observed regimes and those in basic mathematical systems. Plain Language Summary: The impact of climate change on European weather can be broken into two components: a thermodynamic part relating to increasing air temperature and humidity, and a dynamic part relating to changes in the atmospheric circulation such as the direction and strength of prevailing winds. While the thermodynamic part is relatively well understood, the dynamic part is very uncertain and this is a major problem in constraining European climate projections. Looking at the winter season, we study the dynamic response of CMIP6 models under climate change using so‐called "regimes," and show that the types of prevailing circulation are not predicted to change strongly. However the regimes are projected to be less long lived. We also show that these features can be well captured in a simple 5 equation model of regime dynamics, providing a potentially useful tool for understanding regime systems in more detail. Key Points: The spatial structure of anticyclonic circulations over Europe are projected to stay the same under climate changeThe persistence of anticyclonic circulations are in general expected to decrease, although there is considerable inter‐model variabilityWe show that these qualitative features of the atmospheric response can be reproduced in a simple forced regime model [ABSTRACT FROM AUTHOR]

Mountain glaciers are highly sensitive to climate change. However, the extent to which glaciers capture regional to hemisphere‐scale atmospheric processes remains uncertain, hindering paleoclimatic interpretations derived from moraine‐based glacier reconstructions. Here, we evaluate how mid‐latitude glacier systems monitor climate by comparing climate reanalysis products with glacier annual equilibrium line altitude (ELA) elevations from the antipodal Southern Alps of New Zealand and European Alps. We find significant regional and hemispheric correlations between glacier annual ELA and summer tropospheric temperatures. Annual ELA also exhibit positive correlations with the latitude of the westerly jets in both hemispheres. These results indicate that westerly wind‐belt latitude modulates the proportion of cold versus warm air masses influencing these glacier systems. These results highlight the sensitivity of mid‐latitude glaciers to atmospheric temperatures and circulation, with implications for interpreting moraine‐based paleoclimate reconstructions. Combined impacts of ongoing tropospheric warming and poleward‐shifting westerlies will likely accelerate recession of mid‐latitude glaciers. Plain Language Summary: Mountain glaciers respond to climate change by gaining mass when the climate cools and losing mass when the climate warms. However, the extent to which these glacial fluctuations are reflective of local, regional, and hemispheric climate variations is less clear, hindering climatic interpretation of paleo‐glacier reconstructions developed from glacial landforms. This study evaluates the climatic footprint monitored by antipodal mid‐latitude glacier populations by comparing gridded reconstructions of global temperature and wind changes with glacier annual snowline elevations in the Southern Alps of New Zealand and annual equilibrium line altitude elevations in the European Alps. Our results indicate that (a) these glacier systems co‐vary with atmospheric temperatures on regional and even hemispheric scales throughout all levels of the troposphere, and (b) the latitudes of the westerly wind belts are important for regulating the proportion of cold versus warm air masses influencing glacier mass‐balance. Altogether, our results indicate that mid‐latitude mountain glacier fluctuations reflect temperature changes integrated over large regions of the atmosphere. With ongoing climate change, the combination of global atmospheric warming and poleward‐shifting westerlies is likely to accelerate recession of mid‐latitude glaciers in both hemispheres. Key Points: Mid‐latitude glacier annual equilibrium line altitude corresponds to broad regions of atmospheric temperatureMid‐latitude glacier annual equilibrium line altitude is sensitive to latitudinal shifts of the mid‐latitude westerliesThe influence of the westerlies on glaciers has important implications for interpreting past and predicting future climate change [ABSTRACT FROM AUTHOR]

Warming temperatures and increasing disturbance by wildfire and extreme weather events is driving permafrost change across northern latitudes. The state of permafrost varies widely in space and time, depending on landscape, climate, hydrologic, and ecological factors. Despite its importance, few approaches commonly measure and monitor the changes in deep (>1 m) permafrost conditions with high spatial resolution. Here, we use electrical resistivity tomography surveys along two transects in interior Alaska previously disturbed by wildfire and more recently by warming temperatures and extreme precipitation. Long‐term point observations of permafrost depth, temperature, and water content inform geophysical measurements which, in turn, are used to extrapolate interpretations over larger areas and with high spatial fidelity. We contrast gradual loss of recently formed permafrost driven by warmer temperatures and increased snowfall, with rapid permafrost loss driven by changes in air temperature, snow depth, and extreme summer precipitation in 2014. Plain Language Summary: Permafrost, or ground that remains perennially frozen, is thawing across Arctic and sub‐Arctic regions, driven in part by climate warming, wildfire, and changes in the amount and timing of rain and snow. When permafrost thaws, previously frozen carbon can be released to the atmosphere as greenhouse gases, water flow and storage is altered, and community land use and access are impacted. Permafrost landscapes can be mapped over large areas from satellites or airborne remote sensing methods, but only at the surface with limited information obtained at depth. Measurements of deeper permafrost properties are often limited to point observations. We use geophysical measurements to indirectly map and monitor high spatial resolution changes in permafrost characteristics within the ground. Combined with point observations of soil temperature and moisture content, and thaw depths, geophysical measurements help to extend our ability to measure changing permafrost conditions over time. At two nearby transects in interior Alaska, we document the long‐term trajectory of permafrost thaw following wildfire. Our results show similar yet distinct responses in shallow permafrost recovery and more recent degradation, both gradual and rapid, caused by warming temperatures, increased snowfall, and extreme summer rainfall events. Key Points: Changes in the state of permafrost can be highly variable in both space and timeDisturbance or changes in climate and precipitation influence the long‐and short‐term trajectory of permafrost and seasonally frozen groundGeophysical measurements and monitoring complement direct permafrost observations by providing high resolution information at depth [ABSTRACT FROM AUTHOR]

We assimilate atmospheric temperatures from the Emirates Mars Infrared Spectrometer on board the Emirates Mars Mission (EMM) into the Mars Planetary Climate Model at the start of EMM's early science phase (Mars Year 36 Ls = 57.34–92.90°). Mars data assimilation benefits significantly from EMM's unique near‐hemispheric observations, frequent repeated observations of the same location, and full diurnal cycle coverage. Our analysis verifies well against in‐sample temperature observations, and is 1–3 K warmer than Mars Climate Sounder observations. We identify a warm front in concurrent Emirates eXploration Imager observations by correlating an elongated water ice cloud with temperatures and winds in the analysis; the analysis winds are consistent with its observed motion. We also calculate the full horizontal wind diurnal cycle; the zonal flow is weaker and the meridional circulation is stronger than simulating the same time period using the model alone. Plain Language Summary: The Emirates Mars Mission (EMM) promises advances in our understanding of Mars' atmosphere similar to when geostationary satellites first observed Earth. Data assimilation is a process where we combine observations with an atmospheric simulation. Using it to study Mars will benefit from EMM's observations of the whole of one side of the planet, frequent repeated observations of the same location, and observations of the full day‐night cycle. We combined observations of Mars atmospheric temperatures with our model over 79 Martian days at the start of EMM's main study period. We were able to demonstrate what is possible with EMM that has not been possible before. In particular, we found a long water ice cloud near the north pole in separate visible and ultraviolet images made by EMM. By comparing the motion and structure of this cloud with our results, we found that this "warm front" also appears in our results, and we were able to deduce properties of the front that were not observed. We were also able to deduce how Martian winds change over the course of the day and night, by making use of EMM's temperature observations over the full day‐night period. Key Points: We assimilate atmospheric temperature profiles from Emirates Mars Mission‐Emirates Mars InfraRed Spectrometer (EMM‐EMIRS) over a 79‐sol period in Mars Year 36 shortly before northern summer solsticeEMIRS' near‐hemispheric spatial coverage is used to analyze complete weather systems; we deduce the structure and motion of a warm frontThe horizontal wind diurnal cycle is retrieved by assimilation based on EMM‐EMIRS' extended local time coverage of atmospheric temperatures [ABSTRACT FROM AUTHOR]

This study investigates the relative contributions of internal variability and external forcing to multidecadal variations in the winter (December–February) East Asian averaged surface air temperature (EASAT) since 1880 by analyzing three observational datasets and large ensemble simulations from 12 coupled models. The results indicate that the internal variability plays a dominant role in the EASAT multidecadal variations. Specifically, the Atlantic Multidecadal Oscillation (AMO) affects the EASAT via an atmospheric teleconnection across the Eurasian continent, and the correlation coefficient between internally generated EASAT variation and the AMO index is −0.49. In comparison, the external forcings only modulate the observed EASAT variations due to offsetting effects of the external forcing agents. That is, the multidecadal variations in the greenhouse gas concentrations and anthropogenic/volcanic aerosols make positive and negative contributions, respectively. Our new finding is conducive to EASAT predictions in the following decades due to the predictability of AMO and anthropogenic forcings. Plain Language Summary: Internal variability is one of the most important sources of uncertainty in predicting the East Asian winter temperature in future decades. It is thus essential to address associated reasons for the internally generated East Asian temperature variability. This study tries to separate internal variability from the externally forced climate response for the winter East Asian averaged surface air temperature (EASAT) based on three observational datasets and large ensemble simulations from 12 latest coupled models. We find that the internal variability explains 59% of the total EASAT multidecadal variations, in which the Atlantic Multidecadal Oscillation (AMO) plays a vital role. The external forcings play the secondary role. This means that accurate prediction of the AMO would be helpful for predicting internally generated EASAT variations at the multidecadal scale. Key Points: Internal variability has played a dominant role in the multidecadal variations of winter temperature averaged over East Asia since 1880The Atlantic Multidecadal Oscillation plays a vital role in internally generated East Asian winter temperature variationsChanges in greenhouse gas concentrations and anthropogenic/volcanic aerosols make positive and negative contributions, respectively [ABSTRACT FROM AUTHOR]

Defined as the difference between the daily maximum (Tmax) and minimum surface air temperature (Tmin), the diurnal temperature range (DTR) is critical to local climate, ecosystem, and socio‐economic functioning. This study investigates how DTR responds to the future global warming, using a novel, fine‐resolution convection‐permitting regional climate model. Results demonstrate the asymmetrical impact of global warming, that is, the more substantial warming in Tmin, and the lower in Tmax. This asymmetry results in the DTR reduction of 0.5°K in the mid‐latitude and 0.25°K in the low‐altitude area (under 2°K warming scenario). The increase in daytime cloudiness under warmer climates is likely responsible for the reduction of incoming short‐wave radiation reduction, consequently causing Tmax "underwarming." Study results also suggest that atmospheric instability could play a vital role in the difference in DTR response between the tropical and mid‐latitude areas. Plain Language Summary: Diurnal temperature range, which is defined as the difference between the daily maximum (Tmax) and daily minimum air temperature (Tmin), is a critical factor that modulates local climate, ecosystem, and socio‐economic functioning. This study investigates how global warming impacts diurnal temperature range (DTR) using a high resolution numerical model. Results demonstrate the asymmetrical response to global warming, that is, the more substantial warming is confirmed in Tmin, and the lower in Tmax. This asymmetry results in the DTR reduction of approximately 0.5°K in the mid‐latitude and 0.25°K in the low‐altitude area. A cause of the DTR reduction is the daytime‐cloudiness increase under warmer climates, which reduces short‐wave solar radiation reaching the surface, consequently causing the Tmax "underwarming." Also, the difference in atmospheric instability in the mid‐ and low‐latitude areas explains the difference in the DTR response, that is, more moderate DTR reduction is confirmed in low latitude areas. Key Points: This study demonstrates the reduction of the diurnal temperature range (DTR) under future warmer climatesThe reduction of DTR is primarily attributed to the increase in cloudiness which reducing daytime incoming‐shortwave radiationDifference in intrinsic atmospheric stability between tropical and mid‐latitude areas could explain the distinct responses of DTR [ABSTRACT FROM AUTHOR]

Understanding influence of vegetation on past temperature changes in the Arctic region would help isolate uncertainty and build understanding of its broader climate system, with implications for paleoclimate reconstructions and future climate change. Using an Earth system model EC‐Earth, we conduct a series of simulations to investigate the impact of vegetation‐climate feedback on the Arctic climate during the mid‐Holocene. Results show Arctic greening induced by the warming resulting from stronger orbital forcing, further amplifies the Arctic warming. The increased vegetation contributes 0.33°C of Arctic warming and 0.35 × 106 km2 of Arctic sea ice loss. Increased Arctic vegetation leads to reduced land surface albedo and increased evapotranspiration, both of which cause local warming in spring and summer. The resultant sea ice loss causes warming in the following seasons, with atmospheric circulation anomalies further amplifying the warming. Our results highlight the significant contribution of vegetation‐climate feedback to Arctic climate under natural conditions. Plain Language Summary: Vegetation‐climate feedback is an essential process between the terrestrial biosphere and the atmosphere. Greening of the Arctic can be invoked by increased solar radiation, for example, during the mid‐Holocene (6,000 years ago), or increased greenhouse gas, for example, ongoing global warming. Here we perform simulations of vegetation and climate interactions during the mid‐Holocene and demonstrate the impact of vegetation‐climate feedback on the Arctic climate. We show that compared to the pre‐industrial period (1850 CE), the Arctic region experiences an expansion of vegetation under a warm climate due to increased solar radiation during the mid‐Holocene. The greening leads to reduced land albedo and enhanced evapotranspiration. These changes and resultant sea ice loss, in combination with associated atmospheric circulation changes, further amplify the Arctic warming. These changes alone are responsible for 0.33°C increase in surface air temperature and 0.35 × 106 km2 increase in sea ice loss. Given the facts of observed ongoing Arctic greening in recent decades, our modeling results suggest that the effect of the vegetation‐climate feedback will amplify the future Arctic warming and sea ice loss even more. Key Points: The Earth system model EC‐Earth reproduced the expansion of vegetation in northern high latitudes during the mid‐Holocene compared to the PIThe mid‐Holocene Arctic greening contributes 0.33°C increase in annual Arctic warming and 0.35 × 106 km2 of sea ice lossThe increased evapotranspiration and decreased surface albedo due to the Arctic greening amplify the Arctic warming in the growing season [ABSTRACT FROM AUTHOR]

Australia experienced record‐breaking wildfires during 2019–2020, which emitted large amounts of carbonaceous aerosols (CAs) to the atmosphere. In this study, we explored the atmospheric dynamics and thermodynamic mechanism of the long‐range transport of CAs during November 2019–February 2020. The results indicate that the emitted CAs had a ternary advective spreading pattern across the Pacific Ocean in the Southern Hemisphere (SH), influenced mainly by the westerlies and anticyclonic systems. Upward vertical motion over the convergence zone and heat released from smoke pyro‐cumulonimbus clouds and strong light absorption of CAs provided strong vertical lift as the predominant injection pathway of the CAs into the stratosphere in the central Pacific Ocean in the SH. The abundant tropospheric CAs induced atmospheric heating (and potentially surface cooling), with increasing air temperature and decreasing of surface temperature. The anomalous thermal structure led to changes in atmospheric circulation, which weakened the upward vertical motion. Plain Language Summary: During the summer of 2019–2020, Australia suffered unprecedented wildfires. These wildfires emitted large amounts of pollutants into the free atmosphere. The pollutants are mainly composed of carbonaceous aerosols (CAs). Under the effects of meteorological conditions, the CAs experienced a long‐range spread expanding from the western Pacific Ocean to the eastern Pacific Ocean even arriving at the Atlantic Ocean. During the transportation, the CAs were accumulated over the central Pacific Ocean under the trapping effect of the anticyclone and then exhibited significant lift owing to upward motion over the convergence zone between westerlies and anticyclone and heat buoyancy released from smoke pyro‐cumulonimbus clouds and strong light absorption of CAs. As a response, the strong absorption of CAs resulted in the warming of the atmosphere and cooling of the surface, which enhanced atmospheric stratification and constrained the development of atmospheric instability. Thus, the upward vertical motion was weakened. Key Points: The westerlies and anticyclonic system dominated the advective spread of carbonaceous aerosols (CAs)The upward vertical motion, heat released from smoke pyro‐cumulonimbus clouds, and strong CAs light absorption contributed to CAs liftThe CAs caused warming of air temperature and cooling of surface temperature, which weakened the upward vertical motion [ABSTRACT FROM AUTHOR]

The diversity of El Niño events is commonly described by two distinct flavors, the Eastern Pacific (EP) and Central Pacific (CP) type. While the remote impacts, that is, teleconnections, of EP and CP events have been studied for different regions individually, a global picture of their structure is still lacking. Here, we use Forman‐Ricci curvature applied on climate networks constructed from surface air temperature data to distinguish regional links from teleconnections. Our results confirm that both El Niño types influence the teleconnection patterns, however, with different spatial manifestations. Our analysis suggests that EP El Niños alter the general circulation which changes the teleconnection structure to primarily tropical teleconnections. In contrast, the teleconnection pattern of CP El Niños show only subtle changes to normal conditions. Moreover, this work identifies the dynamics of the Eastern Pacific as a proxy for the remote impact of both El Niño types. Plain Language Summary: El Niño events, characterized by anomalous sea surface temperatures (SSTs) in the Tropical Pacific, come in two flavors; Eastern Pacific (EP) and Central Pacific (CP) types, depending on the longitudinal location of the strongest SST anomalies. Their remote impacts, known as teleconnections, differ. Although there are many studies investigating teleconnections of EP and CP events for individual target regions, a global analysis of the spatial distribution of their teleconnections is still lacking. In this study, we use the theory of complex networks to study EP and CP El Niño teleconnections. We construct "climate networks" from global surface air temperature data and use the notion of "curvature" of a network link to uncover their spatial organization. We show that the most negatively curved links highlight important teleconnection patterns that differ depending on the El Niño type. EP events change the teleconnection structure to the tropics while CP and Normal year conditions reveal teleconnections to all latitudes. Interestingly, the Central Pacific does not show many teleconnections, even during CP El Niño events which we attribute to the varying location of warm water anomalies in the Central Pacific. The Eastern Pacific changes more consistently allowing identifying remote impacts of both El Niños types. Key Points: Ricci curvature of boreal winter climate networks reveals long‐range teleconnection structureEastern Pacific (EP) El Niños show primarily teleconnections in tropical while Central Pacific El Niños teleconnections on all latitudesThe EP contains robust teleconnections for both El Niño types [ABSTRACT FROM AUTHOR]

Based on statistical analysis using observations and idealized model simulations, previous studies have revealed the potential response of early‐winter atmospheric circulation and temperature anomalies to November Ural blocking (UB) anomalies. Using a large number of coupled simulations, this study found that the response is sensitive to the intensity of November mid‐latitude westerly jet over Eurasia. Stronger‐than‐normal November UB without a significantly weakened westerly jet could not cause significant atmospheric response in early‐winter. By contrast, stronger‐than‐normal November UB with a significantly weakened jet would be followed by a warmer Arctic‐colder Eurasia (WACE) pattern in December. The significantly weakened westerly jet favors stronger upward propagation of planetary waves, which causes stronger weakening and longer persistence of the stratospheric polar vortex. This stratospheric response persists into December and propagates downward into the troposphere interfering with planetary waves (especially wavenumber‐1). The lead‐lag UB‐WACE linkage modulated by mid‐latitude jet may have implications for sub‐seasonal predictability. Plain Language Summary: Observations and idealized model simulations have shown that strong Ural blocking (UB) anomalies in November can induce the "warmer Arctic, colder Eurasia" anomaly in the following December. In this study, a large number of coupled simulations are employed. The results show that the impact of November UB on early‐winter Arctic‐Eurasian temperature is sensitive to the intensity of November mid‐latitude (around 60°N) westerly jet over Eurasia. When November UB anomalies are accompanied by a significantly weakened mid‐latitude westerly jet, early‐winter would experience a warmer Arctic‐colder Eurasia pattern. The significantly weakened westerly wind waveguide is favorable for stronger upward propagation of planetary waves caused by UB anomalies, which leads to persistent atmospheric response in the following December. Key Points: Early‐winter atmospheric response to November Ural blocking (UB) anomalies is sensitive to the background state of westerly jetStrong UB with sufficiently weakened westerly jet in November can induce a warmer Arctic‐colder Eurasia pattern in DecemberThe weakened westerly wind waveguide promotes stronger upward propagation of planetary waves forced by UB anomalies [ABSTRACT FROM AUTHOR]

In this study, we investigate both the changes of tropical cyclone (TC) rainfall hazard in the United States under climate change and the relative importance of the factors that cause the changes. We find that under the SSP5 8.5 scenario, the 100‐year TC rainfall level can increase by up to 320% along the U.S. coastline by the end of this century. The influence of TC rainfall‐producing ability increase is more significant than the influence of TC frequency increase on the increase of the 100‐year TC rainfall level (up to 180% vs. 60% increase). Among the different physical drivers for the increase in storm rainfall‐producing ability, the increase of TC intensity is the leading factor, followed by changes in TC duration and atmospheric temperature. The projected increase of TC rainfall hazard is robust against the uncertainty in the TC frequency projection. Plain Language Summary: Rainfall associated with landfalling tropical cyclones (TC) can cause extreme flooding and landslides, which are hazardous for coastal and inland areas. We project that by the end of the 21st century, TC rainfall hazard in the United States will increase by as much as 320% compared to its current value. The increase in TC rainfall hazard can be caused by two factors: more TCs making impact and TCs becoming more capable of producing rainfall in the future. The increased ability for TCs to produce rainfall is linked to increased TC intensity and duration as well as a warmer and more humid atmosphere in the future. Though uncertainties exist in the projected trend of future TC landfall frequency, TC rainfall hazard is very likely to increase due to the significant increase in TC rainfall‐producing ability. Key Points: U.S. landfalling tropical cyclone (TC) rainfall hazard will increase in the future due to increased TC landfalling frequency and TC rainfall‐producing abilityStorm intensity change is the leading factor for TC rainfall‐producing ability to increaseThe projected increase of TC rainfall hazard is robust against the uncertainty in TC frequency projection [ABSTRACT FROM AUTHOR]

The daily variation of ground‐level ozone (O3), a harmful pollutant, is positively correlated with air temperature (T) in many midlatitude land regions in the summer. The observed temporal regression slope between O3 and T (dO3/dT) is referred to as the "ozone‐climate change penalty" and has been proposed as a way to predict the impact of future climate warming on O3 from observations. Here, we use two chemical transport models to show that the spatial variation of dO3/dT is primarily determined by simultaneous meridional advection of O3 and T. Furthermore, the sign and magnitude of dO3/dT can be approximated by their climatological meridional gradient ratio (O3 gradient divided by T gradient). Consideration of expected changes in the meridional gradients of T and O3 due to climate change indicates that dO3/dT will likely change. Caution is needed when using the observed climate penalty to predict O3 changes. Plain Language Summary: At Earth's surface, ozone is a harmful pollutant. In the summer, we observe higher ozone concentrations on hotter days over land in the midlatitudes. This leads researchers to expect higher ozone concentrations as a result of global warming, based on chemistry that associates higher ozone concentrations with higher temperatures. Here, we show that the relationship between ozone and temperature is largely controlled by the north‐south movement of air which simultaneously transports ozone and heat. Therefore, the background spatial distributions of ozone and temperature determine how ozone and temperature covary. The ozone‐temperature relationship in the future may look different from today, because global warming is not spatially uniform. We advise caution in using observed ozone‐temperature relationship to estimate future ozone changes. Key Points: Transport by meridional advection of O3 and T explains the spatial variation in the daily O3‐T relationshipDaily regression slope dO3/dT can be approximated by the ratio of O3 and T mean meridional gradients when temperature gradients are strongGradient ratio suggests dO3/dT will change with warming, making it questionable to use observed dO3/dT in O3 projections [ABSTRACT FROM AUTHOR]

While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970–2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the "best" CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step‐like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time. Plain Language Summary: The rate of Arctic warming varied in time, while the rate of global warming was nearly constant over the period 1960–2020. This led to a variable Arctic Amplification (AA) defined as a ratio of the Arctic warming trend to mean global warming trend. In addition, the Arctic experienced sudden changes in the rate of warming with step‐like changes in annual mean Arctic Amplification around the years 1986 and 1999. Climate models do not capture the second observed sharp increase of the AA. We suggest that the first AA increase around 1986 is primarily due to external forcing (increasing concentration of carbon dioxide) while the second sharp increase around 1999 is dominated by internal climate variability which current models cannot capture accurately within the time scale of the physical phenomena. Key Points: Annual mean Arctic Amplification (AA) within the period 1970–2020 changed in steep steps around 1986 and 1999. It reached values over 4.0Even those CMIP6 models best at reproducing the AA did not reproduce the second sudden increase near 1999We conjecture that the first AA sharp increase is due to external forcing, while the second is due to internal climate variability [ABSTRACT FROM AUTHOR]