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A crucial factor influencing the mass balance of the West Antarctic Ice Sheet is the Amundsen Sea Low (ASL), a climatological low‐pressure region situated off the West Antarctic coast. However, albeit the deepening of the ASL since the 1950s has been attributed to anthropogenic forcing, the multi‐decadal variability of the ASL remains poorly understood, because of a lack of long observations. Here, we apply a newly developed data assimilation method to reconstruct the ASL over 1870–2000. We study the forced and internal variability of the ASL using our new reconstruction in concert with existing large ensembles of climate model simulations. Our findings robustly demonstrate that an atmospheric teleconnection originating from the tropical Indo‐Pacific is the main driver of ASL variability at the multi‐decadal time scale, with resemblance to the Interdecadal Pacific Oscillation. Since the mid‐20th century, anthropogenic forcing has emerged as a dominant contributor to the strengthening of the ASL. Plain Language Summary: Changes in the West Antarctic Ice Sheet mass balance (i.e., the difference between the gain and loss of ice mass) are partly influenced by large‐scale winds, and in particular, a climatological low‐pressure feature located off the West Antarctic coast called the Amundsen Sea Low (ASL). Yet, although the long‐term strengthening of the ASL since the mid‐20th century has been demonstrated to be related to anthropogenic forcing, our understanding of the variability of the ASL on time‐scales of decades is poorly known. In this paper, we therefore investigate the origins of this variability since 1870, and quantify the relative contributions of human‐caused climate changes and natural variability of the climate system. For this purpose, we use several ensembles of model simulations as well as new climate reconstructions that combine paleoclimate records with model simulations using a statistical method. Our results indicate that the multi‐decadal variability of the ASL is strongly driven by tropical variability in the Indo‐Pacific through atmospheric connections between this region and the Amundsen Sea. Our reconstruction, when compared with a large ensemble of model simulations, indicates that since 1950, human‐induced climate forcing has become a dominant driver of long‐term ASL variability, contributing equally to tropical variability. Key Points: The large‐scale atmospheric circulation in West Antarctica exhibits a strong multi‐decadal variability superimposed by a 20th‐century trendThe multi‐decadal variability of this large‐scale atmospheric circulation is strongly governed by the Indo‐Pacific tropical variabilitySince 1950, anthropogenic forcing has emerged as a key driver of the long‐term change of this atmospheric circulation [ABSTRACT FROM AUTHOR]

The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top‐of‐the‐atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all‐sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less‐negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes. Plain Language Summary: The cloud feedback is the process by which cloud property changes in a warming climate can either further enhance warming or damp it. The Arctic is warming faster than the rest of the globe, and one of the largest sources of uncertainty in its climate projections is the cloud feedback. There are two popular methods to calculate the cloud feedback: the Adjusted Cloud Radiative Effect technique, and the Cloud Radiative Kernel technique. In this paper we compare the two methods in a suite of climate models by considering the extent to which changes in Arctic sea ice impact the cloud feedbacks. From this analysis we conclude that the Cloud Radiative Kernel method is less affected by sea ice loss. We then apply the Cloud Radiative Kernel technique to data from the two most recent generations of global climate models to investigate how polar day Arctic cloud feedbacks have changed between these generations. We find that the median value of these Arctic feedbacks is slightly positive in the newest generation of models, a change from slightly negative in the previous generation that is largely fueled by a weakening of the feedback associated with changes in cloud optical depth. Key Points: The Cloud Radiative Kernel method is less sensitive to surface albedo changes than the Adjusted Cloud Radiative Effect techniqueThe Cloud Radiative Kernel method provides poor radiative closure in a suite of global climate modelsThe median shortwave Arctic cloud feedback in recent climate models is slightly positive due to a weakened cloud optical depth feedback [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) significantly impact the hydrological cycle and associated extremes in western continental regions. Recent studies suggest ARs also influence water resources and extremes in continental interiors. AR detection tools indicate that AR conditions are relatively frequent in areas east of the Rocky Mountains. The origin of these ARs, whether from synoptic‐scale waves or mesoscale processes, is unclear. This study uses meteorological composite maps and transects of AR conditions during the four seasons. The analysis reveals that ARs east of the Rockies are associated with long‐wave, baroclinic Rossby waves. This result demonstrates that eastern North American ARs are dynamically similar to their western coastal counterparts, though mechanisms for vertical moisture flux differ between the two. These findings provide a foundation for understanding future climate change and ARs in this region and offer new methods for evaluating climate model simulations. Plain Language Summary: Atmospheric rivers (ARs) are a weather pattern that brings high amounts of atmospheric water and winds in a relatively narrow region. ARs are typically considered a "west coast" phenomenon, largely because the majority of the scientific research on ARs has focused on ARs in western coastal regions: particularly the western United States (US). ARs occur in continental interiors, but there has been some debate about whether these ARs represent the same type of weather as those in western coastal regions. This paper uses two objective methods for identifying ARs and finds times when ARs are present in three locations in the eastern half of the US: Norman, OK, Bloomington, IN, and Washington, DC. Examination of weather conditions during these AR times shows remarkable similarity to conditions associated with west coast ARs. This gives strong evidence that ARs do occur in the eastern half of the US. This result is important because it suggests that ARs may be important for water resources and extreme weather in the eastern half of the US, just as they are in the western US. This result also suggests that ARs may be important for water resources and extremes in other continental interiors. Key Points: Atmospheric rivers (ARs) east of the Rockies are associated with baroclinic wavesWestern coastal ARs and eastern/midwest ARs are dynamically similarSynoptic‐scale uplift, combined with convective instability, provide efficient mechanisms for generating precipitation [ABSTRACT FROM AUTHOR]

As the world's glaciers recede in response to a warming atmosphere, a change in the magnitude and frequency of related hazards is expected. Among the most destructive hazards are glacier lake outburst floods (GLOFs), and their future evolution is concerning for local populations and sustainable development policy. Central to this is a better understanding of triggers. There is a long‐standing assumption that earthquakes are a major GLOF trigger, and seismic activity is consistently included as a key hazard assessment criterion. Here, we provide the first empirical evidence that this assumption is largely incorrect. Focusing on the Tropical Andes, we show that, of 59 earthquakes (1900–2021) the effects of which intersect with known glacier lakes, only one has triggered GLOFs. We argue that, to help develop climate resilient protocols, the focus for future assessments should be on understanding other key GLOF drivers, such as thawing permafrost and underlying structural geology. Plain Language Summary: Climate change is increasing glacier melt in high mountains and increasing the size and number of glacial lakes. Over time, these lakes may drain catastrophically to generate glacier lake outburst floods (GLOFs), which can devastate downstream communities and destroy valuable infrastructure such as roads, bridges, and hydroelectric power facilities. As a result, many risk assessments have been carried out to understand what the triggers of GLOFs might be, in order to better predict their occurrence. One of the main triggers has been assumed to be earthquakes, but this association has not been properly tested. In this paper, we use earthquake and GLOF data from the Peruvian and Bolivian Andes to test this and find that there is little association between earthquakes and GLOFs. We conclude by arguing that focus needs to be on other GLOF triggers, and earthquake activity should be used as a secondary – not primary – indicator in GLOF susceptibility studies. Key Points: Glacier lake outburst floods (GLOFs) are a major risk concern, with earthquakes being commonly considered effective triggers in hazard assessmentsOf 59 earthquakes (1900–2021), the effects of which intersect lakes in the Tropical Andes, only one triggered GLOFsWe suggest that earthquake activity should be used as a secondary – not primary – susceptibility indicator for GLOFs [ABSTRACT FROM AUTHOR]

A mass‐conserving method to downscale precipitation from global climate models (GCMs) using sub‐grid‐scale topography and modeled 700‐mb wind direction is presented. Runoff is simulated using a stand‐alone hydrological model, with this and several other methods as inputs, and compared to runoff simulated using historical observations over the western contiguous United States. Results suggest the mitigation of grid‐scale biases is more critical than downscaling for some regions with large wet biases (e.g., the Great Basin and Upper Colorado). In other regions (e.g., the Pacific Northwest) the new method produces more realistic sub‐grid‐scale variability in runoff compared to unadjusted GCM output and a simpler downscaling method. The presented method also brings the runoff centroid timing closer to that simulated with observations for all subregions examined. Plain Language Summary: Due to limitations in computing power which necessitates coarse spatial resolution, climate models do not include many details on mountains and their impact on precipitation. For this reason, it is difficult to estimate the impact of climate change on the availability of water for human consumption in places like the western United States, where mountain snowpack is an important source of water. This paper presents a way to adjust precipitation estimates from climate models by using some simple statistics about nearby mountains and valleys. The adjusted precipitation is then used in a hydrologic model to calculate the runoff that is simulated with different precipitation inputs. Results show that in most cases, the precipitation adjustment improves estimates of the resultant runoff relative to simulations with observed precipitation. The main exceptions are in very dry areas where the climate model produces far too much precipitation. With further work, the proposed adjustment may be integrated into the climate model itself to make it easier for those managing water resources (e.g., controlling reservoir levels) to use the model output to plan and adapt to climate change. Key Points: A mass‐conserving method for downscaling orographic precipitation improves modeled runoff from the CESM2Considering upwind topography further improves modeled runoff compared to simpler adjustmentsNot tuning to individual model grid points makes this method more generalizable than many existing statistical downscaling methods [ABSTRACT FROM AUTHOR]

In this study, we obtained the first leading mode and principal component 1 (PC1) of North Pacific sea surface temperature (SST). The PC1‐related SST anomalies, located relatively north/south, are referred to as North/South PC1 events. Model outputs, observations, reanalysis datasets and sensitivity experiments show that during the North PC1 events, an enhanced Aleutian low occurs and is located relatively north, favoring anomalous southerlies over western North America. The anomalous southerlies induce a strong warming anomaly over North America via warm advection of the anomalous southerlies and temperature advection of the climatological westerlies over North America. However, the Aleutian low anomaly and corresponding southerly anomaly associated with South PC1 events shift southward, favoring weakened effects of South PC1 events on atmospheric circulations and surface temperatures over North America. The meridional position of PC1 events deserves to be considered in the studies of the PC1 and its related climate changes. Plain Language Summary: Understanding of surface temperature variations is important since it largely affects human and society. This paper categorizes the North Pacific sea surface temperature anomaly events, which are associated with the first leading mode of North Pacific sea surface temperature, into North and South events according to their meridional positions. Using model outputs, observations, reanalysis datasets and sensitivity experiments, we found that the surface temperature anomalies over North America during the North events are quite different from those during the South events. During the North events, an enhanced Aleutian low occurs over high‐latitude North Pacific. The enhanced Aleutian low tends to induce anomalous southerlies over western North America. The anomalous southerlies favor warming anomalies over North America via the warm advection of anomalous southerlies and temperature advection of climatological westerly. However, the Aleutian low anomaly and meridional wind anomaly during the South events shift southward, leading to weakened effects of the South events on atmospheric circulations and surface temperatures over North America. Key Points: North American warming anomaly occurs during North Pacific sea surface temperature anomaly events located northThe warming anomaly is related to an enhanced Aleutian low anomaly located north and climatological westerlyDuring the events located south, North American surface temperature responses are weak due to a southward‐shift Aleutian low anomaly [ABSTRACT FROM AUTHOR]

Recent climate and environment over the Tibetan Plateau (TP) have undergone significant changes, dominated by variations in the Westerlies and the Indian summer monsoon. However, long‐term shifts in atmospheric circulation during the transitional seasons are still lacking. Here we investigate the modern distribution of Tsuga pollen over the central‐western TP and confirm it as an indicator of variable atmospheric circulation in spring. By combining our Tsuga record from Taro Co with existing records in the Tsuga pollen source area, we suggest that a potential particle transport pathway from the southern slope of the Himalayas to the interior of the plateau appeared in the spring of the late Holocene. Our results show that the springtime atmospheric circulation over the southwestern TP during the early and late Holocene is closely related to the substantial remnants of ice sheets at northern high latitudes and the frequency of El Niño events, respectively. Plain Language Summary: The spring climate over the Tibetan Plateau (TP) is undergoing significant changes that yield profound impacts on environmental changes such as variations in vegetation phenology and alpine treeline. Knowledge of long‐term variations in atmospheric circulation during spring can improve the understanding of current climatic and environmental change and the projection of future variability. In this paper, we use an exotic pollen grain, which can be transported long distances in the air, as an indicator to trace the variability of spring atmospheric circulation over the TP. The results indicate that the spring meridional atmospheric circulation from the southern slope of the TP to its interior has been enhanced in the last four thousand years, which is mainly influenced by the frequency of El Niño events. Key Points: Spring atmospheric circulation change over the southwestern Tibetan Plateau (TP) during Holocene is reconstructedMeridional atmospheric circulation in spring over the southwestern TP is strengthened in the late HoloceneHigh‐(low‐) latitude forcing mainly influence the variations in spring atmospheric circulation during the early (late) Holocene [ABSTRACT FROM AUTHOR]

Since the early 1990s the Pacific Walker circulation shows a multi‐decadal strengthening, which contradicts future model projections. Whether this trend, evident in many climate indices especially before the 2015 El Niño, reflects the coupled ocean‐atmosphere response to global warming or the negative phase of the Pacific Decadal Oscillation (PDO) remains debated. Here we show that sea surface temperature trends during 1980–2020 are dominated by three signals: a spatially uniform warming trend, a negative PDO pattern, and a Northern Hemisphere‐Indo‐West Pacific warming pattern. The latter pattern, which closely resembles the transient ocean thermostat‐like response to global warming emerging in a subset of CMIP6 models, shows cooling in the central‐eastern equatorial Pacific but warming in the western Pacific and tropical Indian Ocean. Together with the PDO, this pattern drives the Walker circulation strengthening in the equatorial band. Historical simulations appear to underestimate this pattern, contributing to the models' inability to replicate the Walker cell strengthening. Plain Language Summary: This paper investigates the observed changes in the tropical Pacific during the satellite era, including the recent decadal strengthening of the atmospheric zonal circulation—the Walker cell. We aim to understand the extent to which these changes represent a forced response to rising CO2 concentrations versus natural variability. We apply an approach in which we decompose the observed sea surface temperature trends into three components—a pattern associated with the Pacific Decadal Oscillation, which is part of natural variability, a uniform warming pattern, and a residual pattern. This residual pattern shows a remarkable resemblance to a forced ocean thermostat‐like transient response generated in some of the climate models, characterized by equatorial Pacific (EP) cooling, and a broad warming of the Northern Hemisphere, and the Indian Ocean and West Pacific. These results challenge studies arguing that the recent strengthening of the Pacific Walker cell can be explained simply by multi‐decadal natural variability in the tropics. Furthermore, the inability of climate models at large to fully capture this forced pattern with historical forcing puts into focus the reliability of future projections of climate change in the tropical Pacific, specifically the timing of emergence of the eastern EP warming. Key Points: A multi‐decadal strengthening of the Pacific Walker cell is observed in a wide range of indices, especially after 1990A Northern Hemisphere ‐ Indo West Pacific warming sea surface temperature pattern, which differs from the Pacific Decadal Oscillation, is evident since 1980This pattern resembles a forced response to abrupt CO2 forcing, emerging in a subset of climate models, and contributes to the Walker circulation strenthening [ABSTRACT FROM AUTHOR]

Despite lower‐than‐average total precipitation in the western states of the U.S., the 2021 "precipitation roller coaster" defined as large precipitation swings has pointed to a strong hydroclimatic intensity (HYINT). Here we examine the 2021 HYINT using an index—a product of the average precipitation intensity (INT) and dry spell length (DSL). HYINT exhibited an extremely high value in the western U.S. in 2021. INT and DSL contribute differently to the 2021 HYINT, with large spatial variability. Overall, the 2021 extreme HYINT in central California and Utah is tied more to large INT, than to DSL. Meanwhile, the historical trends in INT and DSL may have contributed to the extreme 2021 HYINT event. The fraction of attributable risk framework reveals that the 2021 extreme HYINT is more likely to occur with anthropogenic forcing (e.g., 7.3 times more likely for HYINT exceeding 1.3) than natural forcing alone. Plain Language Summary: The western U.S. is a hotspot for studying climate change impacts on the hydrological cycle. Despite lower‐than‐average total precipitation in 2021, the contrasting dryness and wetness in the western U.S. has been widely reported as a "precipitation roller coaster." In this paper we quantified the "precipitation roller coaster" using an index (hydroclimatic intensity [HYINT])—a product of average precipitation intensity during wet days and dry spell length (DSL). The study found that the 2021 extreme HYINT event was largely attributable to the combined impacts of precipitation intensity and DSL in California and Utah, with precipitation intensity playing a more important role. In contrast, the 2021 precipitation event in other western states exhibited divergent contributions from precipitation intensity and DSL. The southwestern U.S. has been identified as a hotspot for increasing HYINT, which is tied more to the increasing DSL than the precipitation intensity. The trends in DSL and precipitation intensity may have played a key role in driving the 2021 extreme HYINT event. Using climate model experiments with and without anthropogenic forcing, an extreme HYINT event in the western U.S. is more likely to occur with anthropogenic forcing. Key Points: Hydroclimatic intensity (HYINT) exhibited extremely high values in parts of the western U.S. in 2021, mainly caused by average precipitation intensityHYINT shows a significant rising trend in most of the southwestern U.S. mainly tied to a rising dry spell length trendThe extreme HYINT event is more likely to occur under anthropogenic forcing than natural forcing alone [ABSTRACT FROM AUTHOR]

Due to climate change, global oceanic dissolved oxygen (DO) has been decreasing, and oxygen minimum zones (OMZs) have been expanding. Here, we estimate the annual global and regional OMZ areas using geostatistical regression combined with Monte Carlo. From 1960 to 2019, annual global OMZ20 (DO < 20 μmol/kg) and OMZ60 (DO < 60 μmol/kg) areas cover 5%–14% and 15%–32% of the global ocean, respectively. The global and most regional OMZ areas after the late 2000s were all significantly larger than those in previous years. Most oceanic regions likely experienced significant expansions in OMZ areas, especially the North Pacific. However, the equatorial Pacific with the largest OMZ area showed insignificant horizontal expansion. The expanding OMZ areas of most oceans responded more quickly and effectively to the surrounding sea temperatures than to the sea surface temperatures. Our research highlights the need for marine resource management to account for the challenges from OMZs. Plain Language Summary: Expanding oxygen minimum zones (OMZs, low dissolved oxygen [DO] zones) in the open ocean have been the topic of intense interest. However, annual OMZ areas, trends in OMZ areas, and causes of OMZ expansions remain unclear. Our paper explores the locations and annual areas of global and regional OMZ areas based on observations from 1960 to 2019. Over the last six decades, annual global OMZ20 (DO < 20 μmol/kg) and OMZ60 (DO < 60 μmol/kg) areas cover 5%–14% and 15%–32% of the global ocean, respectively. The global OMZ areas show great interannual variability but remain stably large after the late 2000s. Most oceanic regions have experienced significant OMZ expansion, especially the North Pacific. The equatorial Pacific Ocean has the largest OMZ area, but shows insignificant expansion. Subsurface sea temperatures are more associated with the expanding OMZ areas than sea surface temperatures. Increasing sea temperature would substantially increase OMZ areas by the end of the century for the future societal development pathway (SSP585) scenario. Understanding how OMZs will change over the long‐term due to climate change is beneficial for the protection of marine resources. Key Points: From 1960 to 2019, most oceanic regions experienced significant horizontal expansions in oxygen minimum zone (OMZ) areas, especially the North PacificThe equatorial Pacific has the largest OMZ area but shows an insignificant increasing trendThe OMZ areas of most oceans respond more quickly and effectively to surrounding sea temperatures than to sea surface temperatures [ABSTRACT FROM AUTHOR]

The expansion of Antarctic sea ice since 1979 in the presence of increasing greenhouse gases remains one of the most puzzling features of current climate change. Some studies have proposed that the formation of the ozone hole, via the Southern Annular Mode, might explain that expansion, and a recent paper highlighted a robust causal link between summertime Southern Annular Mode (SAM) anomalies and sea ice anomalies in the subsequent autumn. Here we show that many models are able to capture this relationship between the SAM and sea ice, but also emphasize that the SAM only explains a small fraction of the year‐to‐year variability. Finally, examining multidecadal trends, in models and in observations, we confirm the findings of several previous studies and conclude that the SAM–and thus the ozone hole–are not the primary drivers of the sea ice expansion around Antarctica in recent decades. Plain Language Summary: Unlike its Arctic counterpart, sea ice around Antarctica has been growing since 1979, even as the levels of carbon dioxide in the atmosphere have increased. Given that the ozone hole formed over the South Pole around the same time, one is led to ask whether the ozone hole may be responsible for the growth of Antarctic sea ice (recall that there is no ozone hole over the North Pole). In this study, looking at both models and observations, we show that the ozone hole is capable of affecting the surface winds and these, in turn, can make sea ice expand. However, the magnitude of this effect is small. Also since the ozone hole started healing after the year 2000, while Antarctic sea ice kept expanding, we conclude that ozone depletion is not the main reason for the expansion of Antarctic sea ice in recent decades. Key Points: Many CMIP5 models are able to capture the observed seasonal correlation between summertime Southern Annular Mode (SAM) and Antarctic sea ice extentThe SAM, however, only explains 15 of the year‐to‐year sea ice extent variability in the fall, in both models and observationsSAM trends, and ozone depletion, are not the primary drivers of the observed Antarctic sea ice expansion in the last four decades [ABSTRACT FROM AUTHOR]

We present new climate field reconstructions (CFR) of tropical Pacific ENSO sea surface temperatures (HadISST) for the boreal winter season using a circum‐Pacific tree‐ring network from known El Niño rainfall impact regions. We use two different CFR methods: Point‐by‐Point Regression (PPR) and reduced‐space Orthogonal Spatial Regression (OSR). Both methods produce reconstructions with high validation skill, but OSR is preferred because it has less spatial noise and is more efficient. Only the leading EOF of the SST field (EOF1) can be skillfully reconstructed by either method; EOF2 does not validate. The success of EOF1 reflects its importance for ENSO rainfall impacts over land; the failure with EOF2 is from the lack of these impacts. EOF1 allows for the reconstruction of many ENSO indices, including the ENSO Longitudinal Index (ELI). We also find evidence in our reconstructions for a recent increase in ENSO activity. Plain Language Summary: Earth's climate is strongly affected by how warm the tropical Pacific Ocean "El Niño" region is. This is especially true for the delivery of rainfall over many parts of the globe. Tree growth can thus be strongly affected by El Niño impacts on rainfall. We use this relationship to reconstruct tropical Pacific sea surface temperatures associated with El Niño over most of the past millennium from a network of annual tree‐ring chronologies located in regions known to be impacted by El Niño rainfall. Only the leading mode of variability in Pacific sea surface temperatures associated with El Niño can be reconstructed well, but it reflects most of the long‐term variability of El Niño exceptionally well. The reconstruction extends back to 1500 with exceptional skill and back to 1100 with acceptable skill. We can thus compare recent El Niño variability, perhaps affected by global warming, with what happened over the previous centuries unaffected by human activity. We find evidence for an increase in El Niño activity, and for an overall warming in recent decades. Key Points: Tree‐ring series from ENSO rainfall impact regions reconstruct tropical Pacific SSTs with high degrees of skill back to 1500 CE and 1100 CETwo very different reconstruction methods produce similar results and each can only reconstruct the leading EOF mode of SST variabilityReconstructions extending back 1100 CE indicate a recent increase in El Niño variability, and overall SST warming in the equatorial Pacific [ABSTRACT FROM AUTHOR]

Global temperatures were exceptionally high in 2023/24. Every month from June 2023 to June 2024 set a new record, and September shattered the previous record by 0.5 $0.5$°C. The 2023 annual average approached 1.5 $1.5$°C above pre‐industrial levels. This results from both long‐term warming and internal variability, with the occurrence of an El Niño episode. However the amplitude of the 2023/24 anomalies was remarkable and surprised the scientific community. Here we analyze the rarity of 2023/24 global temperatures from a climate perspective. We show that a 'normal' year 2023 would have roughly equaled the previous annual record, and that the most extreme events of 2023/24 rank among the most extreme since 1940. Our analysis suggests that the 2023/24 event can be reconciled with the long‐term trend and an intense, but not implausible, peak of internal variability. Plain Language Summary: 2023 was the warmest year on record at global scale, and early 2024 has continued to break records. This remarkable episode has received a great deal of attention from the general public and the scientific community. It is well established that it is linked to the long‐term global warming and the occurrence of an El Niño episode, but some temperature anomalies appeared so high, shattering previous records, that several scientists suggested that global warming may have been underestimated, which would have serious implications for future projections. Here we take a step back from the 2023/24 event, precisely quantify its rarity and compare it with other hot years. Using climate monitoring and extreme event attribution methods, we first show that at the current rate of warming, a 'normal' year 2023 would have equaled the 'old' record of 2016, even without any help of El Niño. We also find that the most extreme events of 2023/24 are among the most extreme of the entire record, but remain comparable with some past events. Our analysis thus suggests that the 2023/24 event is extreme but not incompatible with current estimates of global warming. Key Points: At the current rate of global warming, a normal year 2023 would have equaled the record of 2016, without any help of El NinoThe most extreme anomalies of 2023/24 rank among the most extreme of the entire record since 1940The 2023/24 heat can be reconciled with current estimates of global warming and an extreme but not implausible peak of internal variability [ABSTRACT FROM AUTHOR]

The acidification of coastal waters is distinguished from the open ocean because of much stronger synergistic effects between anthropogenic forcing and local biogeochemical processes. However, ocean acidification research is still rather limited in polar coastal oceans. Here, we present a 16 year (2002–2018) observational dataset in the Chukchi Sea during the rapid sea‐ice melting season to determine the long‐term changes in pH and aragonite saturation state (Ωarag). We found that pH and Ωarag significantly declined in the water column with average rates of −0.0095 ± 0.0027 years−1 and −0.0333 ± 0.0098 years−1, respectively, and are 4–6 times faster than those solely due to increasing atmospheric CO2. We attributed the rapid acidification to the increased dissolved inorganic carbon owing to a combination of ice melt‐induced increased atmospheric CO2 invasion and subsurface remineralization induced by a stronger surface biological production as a result of the increased inflow of the nutrient‐rich Pacific water. Plain Language Summary: Anthropogenic CO2 absorbed by the ocean leads to a lower pH and the calcium carbonate saturation state (Ω) and threatens the marine ecosystems state of healthiness via a process called ocean acidification (OA). The Arctic Ocean is particularly sensitive to OA because more CO2 can be dissolved in cold water. This study used the observations collected over 16 years from 2002 to 2018 to estimate long‐term trends of Ωarag and pH in the Chukchi Sea. The results show that rapid acidification occurred in the water column during the rapid sea‐ice melting season from 2002 to 2018, leading to or approaching aragonite undersaturation. The rapid acidification is attributed to the enhanced increasing concentration of dissolved inorganic carbon. While sea ice melt induced uptake of anthropogenic CO2 partly explains the long‐term acidification, the remainder is due to the increased nutrient‐rich Pacific inflow water which promotes the high biological CO2 utilization in the surface waters but leads to stronger subsurface acidification due to the regenerated CO2. We suggest that the acidity in Chukchi Arctic Shelf waters will increase in the future if the increased inflow of Pacific water continues. Key Points: pH and Ωarag declined significantly from 2002 to 2018 during sea‐ice melting season, 4–6 times greater than air CO2 increases‐induced changesThe enhanced acidification in the Chukchi Sea is mainly driven by increased DIC, owing to atmospheric CO2 uptake and biological activityPWW has been in aragonite undersaturation since 2010; other water masses are expected to encounter Ωarag < 1 in 15 years [ABSTRACT FROM AUTHOR]

Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we find that the magnitude of the cloud‐SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi‐decadal SST variability. A heat‐budget analysis reveals coupling between cloud‐radiative effects, circulation, and SST gradients in driving multi‐decadal variability in the Eastern Pacific. Using this relationship and observed feedback estimates, we find that internal Eastern Pacific SST variability is underestimated in most models. Adjusting for model bias increases the likelihood of generating a cooling trend at least as large as observations in preindustrial control simulations by ∼ ${\sim} $56% on average. If models underestimate climate "noise," as our results suggest, this bias should be accounted for when attributing the relative importance of forced versus unforced changes in the climate. Plain Language Summary: In recent decades, observed sea surface temperatures (SSTs) have cooled in the eastern tropical Pacific and warmed in the western tropical Pacific. Historical simulations using state‐of‐the‐art climate models fail to reproduce this pattern. We find that the feedback between low‐lying clouds and SSTs is related to the magnitude of naturally occurring SST variability in the Southeast Pacific. On average, climate models that have too weak a cloud‐SST feedback in the Southeast Pacific underestimate the likelihood of multi‐decadal cooling in the eastern Pacific in preindustrial simulations. Our results suggest that biases in cloud feedbacks may be causing models to underestimate internal SST variability. Key Points: Multi‐decadal Southeast Pacific sea surface temperature trends are related to the strength of the subtropical cloud feedbackCloud radiative effects amplify multi‐decadal Pacific sea surface temperature trends by impacting circulation and surface energy fluxesCorrecting model biases in cloud feedback raises the likelihood of internally producing Southeast Pacific cooling as large as observations [ABSTRACT FROM AUTHOR]

In December 2022, North America experienced an unprecedented extreme cold event. However, the underlying physical mechanisms of this cold wave, and the extent to which it is driven by internal variability or external forcing, are not fully understood. Using ERA5 reanalysis data and the HadGEM3‐A‐N216 attribution simulations, we identified internal variability as the main cause, contributing −5.14 K to surface air temperature (SAT) anomalies in North America. External forcing slightly mitigated the cold by 0.42 K. An internally generated wave train from the North Pacific, influenced in combination by Pacific‐North American (PNA) and North Pacific Oscillation (NPO) teleconnection patterns, initiated this intense cyclonic event, contributing −2.18 K and −2.12 K to SAT anomalies, respectively. La Niña‐like sea surface temperature anomalies amplified this wave train and resultant cold wave. Additionally, excessive snow cover in the previous November also intensified the December cold anomalies by enhancing surface albedo and reducing solar radiation. Plain Language Summary: In December 2022, North America was hit by an exceptionally severe cold event. Scientists have been trying to understand the reasons behind this cold wave. Using detailed weather data and climate models, researchers found that natural climate variability played a major role, causing temperatures to drop by about 5.14 degrees Celsius. On the other hand, external factors like human‐induced climate change had a minor effect, slightly reducing the severity of the cold by 0.42 degrees Celsius. The study identified an atmospheric wave train pattern, originating from the North Pacific and moving toward North America, which played a crucial role in triggering this extreme weather. Further investigations showed that this wave train was influenced by specific large‐scale weather patterns in the Pacific region, namely the Pacific‐North American (PNA) and North Pacific Oscillation (NPO) patterns, which contributed to the cold temperatures by approximately 2.18 and 2.12 degrees Celsius, respectively. Additionally, colder‐than‐normal sea surface temperatures in the tropical central Pacific, associated with La Niña, strengthened the wave train. Internal thermodynamical processes, such as increased snow cover, also slightly intensified the cold wave by reflecting more sunlight and reducing the amount of solar energy reaching the surface. Key Points: Internal variability triggers 2022 December extreme cold wave in North AmericaPNA and NPO are two key teleconnections responsible for this extreme cold waveSnow cover‐SAT feedback intensifies this extreme cold wave [ABSTRACT FROM AUTHOR]

Climate‐vegetation interaction assessments often focus on vegetation response to concurrent climatic perturbations, seldom on the time‐lag effect of climate. Here we employ global satellite observations, climate data records and CO2 flux measurements to calculate the time‐lag of vegetation response to climate. We analyze the time‐lags of various climate variables under distinct environmental conditions to gain insight into how the long‐term climatic regimes and tree cover influence the time‐lag effects. Our findings reveal that terrestrial ecosystems characterized by arid and cold climates show more concurrent climate‐vegetation interactions than other ecosystems. Whereas areas with higher tree cover and humid ecosystems with both high mean annual temperature and precipitation show substantial time‐lag response of vegetation to climate by up to 6 months. Since the global climate‐vegetation interaction is dominated by time‐lag effects, incorporating these effects is paramount to improve our understanding of vegetation dynamics under a changing climate. Plain Language Summary: When studying how climate affects vegetation, many studies usually focus on immediate plant responses, without considering the long‐term effects of climate. In our study, we used satellite data to look at how plant photosynthesis and growth changed over time in response to concurrent and past climates. We found that in dry and cold areas, plants respond quickly to changes in climate. But in regions with high tree cover and humid climate, plant responses to climate can take up to 6 months. Understanding these delays is crucial for predicting how vegetation will respond as the climate changes around the world. Key Points: Terrestrial ecosystems with higher tree cover respond to climate perturbation more slowly than grasslands and croplandsTemperature consistently has more significant impacts on vegetation in the longer term than VPD and soil moistureArid and cold ecosystems show shorter time‐lag responses of vegetation to climate [ABSTRACT FROM AUTHOR]

Regional hydrological sensitivity (i.e., precipitation change per degree local surface warming) contributes substantially to the uncertainty in future precipitation projections over tropical oceans. Here, we investigate the sensitivity of relative precipitation (P*, precipitation divided by the basin average precipitation) to local sea surface temperature (SST) change by dissecting it into three components, namely the sensitivity of P* to relative SST (SSTrel, SST minus the tropical mean SST) changes, the sensitivity of P* to surface convergence changes, and the sensitivity of surface convergence to SST gradient changes. We show that the relationships between P* and SSTrel, and between P*, surface convergence, and SST gradients are largely constant during climate change. This allows us to constrain regional hydrological sensitivity based on present‐day SST‐precipitation relationships. The sensitivity of surface convergence to SST gradient changes is a main source of uncertainty in regional hydrological sensitivity and is likely underestimated in GCMs. Plain Language Summary: Understanding how precipitation will change over tropical oceans is important because these changes influence the atmospheric circulation, which in turn affects the global climate and weather patterns. Climate models disagree on their projections of precipitation changes over tropical oceans in part due to a lack of understanding on how precipitation should respond to a given amount of local surface warming. We find that the sensitivity of precipitation to future changes in local sea surface temperature (which is commonly referred to as regional hydrological sensitivity) largely depends on the present‐day relationship between precipitation and local sea surface temperature, as well as that between precipitation and the spatial gradient in sea surface temperature, and both relationships are observable and thus can serve as constraints. We find that inter‐model differences in regional hydrological sensitivity result primarily from differences in the response of surface winds to sea surface temperature gradient changes. Key Points: Regional hydrological sensitivity is an important source of uncertainty in rainfall projections over tropical oceansRegional hydrological sensitivity can be constrained by components of rainfall‐temperature relationship that stay constant during warmingUncertainty in regional hydrological sensitivity originates largely from surface convergence sensitivity to temperature gradient changes [ABSTRACT FROM AUTHOR]

The globally averaged diurnal temperature range (DTR) has shrunk since the mid‐20th century, and climate models project further shrinking. Observations indicate a slowdown or reversal of this trend in recent decades. Here, we show that DTR has a minimum for average temperatures close to 0°C. Observed DTR shrinks strongly at colder temperature, where warming shifts the average temperature toward the DTR minimum, and expands at warmer temperature, where warming shifts the average temperature away from the DTR minimum. Most, but not all climate models reproduce the minimum DTR close to average temperatures of 0°C and a stronger DTR shrinking at colder temperature. In models that reproduce the DTR minimum, DTR shrinking slows down significantly in recent decades. Models project that the global‐mean DTR will shrink over the 21st century, and models with a DTR minimum close to 0°C project slower shrinking than other models. Plain Language Summary: The diurnal temperature range, that is, the difference between daily maximum and minimum temperatures, affects both human health and plant development. Global data sets have shown a shrinking diurnal temperature range since the 1950s, but a recent study found that the diurnal temperature range had expanded again. In this study, we investigate how the diurnal temperature range behaves at different mean temperatures. We find that the diurnal temperature range is particularly small for temperatures close to the melting point of water (0°C), and larger for both colder and warmer temperatures. Due to the latent heat of freezing/melting, more energy is required to warm the soil from −1 to +1°C than from −3 to −1°C or from 1 to 3°C. The diurnal temperature range shrinks in regions and seasons with negative average temperature, where global warming pushes the average closer to 0°C and expands for warmer temperature. Most, but not all climate models also show a narrow diurnal temperature range near 0°C, shrinking of the temperature range at colder temperature and a slower reduction in the diurnal temperature range in recent decades. Models suggest that the currently observed expansion of the diurnal temperature range is a transient phenomenon. Key Points: The diurnal temperature range (DTR) has a local minimum near average temperatures of 0°CDTR in observations shrinks strongly for average temperatures below 0°C and expands for warmer temperaturesClimate models that reproduce the local DTR minimum near 0°C show a significant slowdown of DTR shrinking in recent decades [ABSTRACT FROM AUTHOR]

As global warming intensifies, the coupling relationship between negative Indian Ocean Dipole (nIOD) and La Niña has substantially changed. However, the characteristics and mechanisms of these changes are not yet fully understood. Here, we find that the impact of La Niña on nIOD has considerably weakened since 1999, with the frequency of nIOD occurrences during La Niña years plummeting to a mere one‐third of the pre‐1999 levels. This is primarily attributed to the early onset of Indian summer monsoon and the decrease in La Niña intensity, while the effect of variations in Bjerknes feedback is relatively minor. Model simulations suggest that the influence of La Niña on nIOD will continue to weaken under future global warming through similar mechanisms as in the observations, increasing the complexity of air‐sea coupling in the Indian Ocean. Plain Language Summary: The negative Indian Ocean Dipole (nIOD) has significant impacts on both local and global climate change. La Niña is a major trigger for nIOD. However, as the globe warms up, the connection between nIOD and La Niña has changed a lot. This study analyze observation and reanalysis data from the 1950s onwards to see how nIOD and La Niña are linked. We find that La Niña has had less impact on nIOD since 1999. This is because the summer monsoon starts earlier, causing changes in wind patterns over the Indian Ocean. La Niña normally brings westerly wind anomalies in the Indian Ocean, but these winds are weakened because of the early monsoon. This makes it harder for nIOD to form. The feedback loop known as the Bjerknes feedback doesn't play a big role in maintaining nIOD. Furthermore, the reduction in La Niña intensity also contribute to weakening the relationship between La Niña and nIOD. Models predict that La Niña's impact on nIOD will continue to weaken under future global warming, increasing the complexity of air‐sea coupling in the Indian Ocean and leading to more challenges in forecasting. Key Points: The relationship between La Niña and negative Indian Ocean Dipole has weakened significantly in this centuryThe spring‐summer easterly anomaly induced by the premature summer monsoon weakens the La Niña‐induced westerly anomalyThe impact of La Niña on negative Indian Ocean Dipole will continue to weaken under future global warming [ABSTRACT FROM AUTHOR]

Horizontal and vertical moisture advection in the lower troposphere of the Arctic under progressing global warming is examined using a large‐scale ensemble model data set. Advection is decomposed into terms related to the basic state of the atmosphere and transient eddies and compared against a non‐warming experiment. During summer, horizontal moisture advection increases mainly by transient eddies advecting moisture from the lower latitudes. During winter, enhanced evaporation due to reduced sea ice becomes a source of moisture diminishing the role of transient eddies moistening the atmosphere. This effect intensifies under extreme global warming, turning the change in total horizontal advection in the lower troposphere negative. Diminished horizontal advection during winter is counteracted by vertical advection accompanied with enhanced evaporation and upper‐level horizontal advection maintaining the increase in column moisture. These results improve our understanding of how the water cycle in the Arctic responds via atmospheric processes under global warming. Plain Language Summary: This study uses a data set with a large number of members to investigate how the atmosphere is moistened in the Arctic (north of 70˚N) under various stages of global warming. The movement of moisture is summarized in terms of horizontal and vertical components of advection, a measure of how the atmosphere is moistened in a given specific humidity gradient and wind, which is decomposed into parts related to the average state of the atmosphere and parts related to high‐frequency phenomena, such as cyclones. It is found that (a) during summer, moisturization of the Arctic is mainly driven by horizontal movement of moisture from a remote source in the lower latitude, (b) during winter, this moisturization due to horizontal movement of moisture is suppressed and is driven more by vertical movement of moisture due to reduction of sea ice and increased evaporation. As global warming progresses, the role or horizontal movement of moisture is taken over by the local process of evaporation and vertical movement of moisture. This research helps us understand how the water cycle in the Arctic changes with severe global warming and improves our knowledge of the atmospheric processes that govern the climate system through various feedbacks. Key Points: Moisture advection in the Arctic under progressing global warming is examined using a large‐scale ensemble model simulation data setMoistening effect of horizontal advection in the lower troposphere is enhanced for summer and diminished for winter under extreme warmingEnhanced horizontal advection in the upper layer and surface evaporation are consistent with increased column moisture during winter [ABSTRACT FROM AUTHOR]

The frequency change of 100‐year flood events is often determined by fitting extreme value distributions to annual maximum discharge from a historical base period. This study demonstrates that this approach may significantly bias the computed flood frequency change. An idealized experiment shows frequency bias exceeding 100% for a 50‐year base period. Further analyses using Monte Carlo simulations, mathematical derivations, and hydrological model outputs reveal that bias magnitude inversely relates to base period length and is weakly influenced by the generalized extreme value distribution's shape parameter. The bias, persisting across different estimation methods, implies floods may exceed local defenses designed based on short historical records more often than expected, even without climate change. We introduce a frequency bias adjustment method, which significantly reduces the projected rise in global flood occurrence. This suggests a substantial part of the earlier projected increase in flood occurrence and impacts is not attributable to climate change. Plain Language Summary: We report a previously overlooked bias in a common method for projecting the frequency of extreme floods, like 100‐year events. This method typically uses a short period of historical data for two primary purposes: first, to define local thresholds for extreme floods, such as 100‐year events, and second, to serve as a base for projecting future changes in flood occurrences. Our study, utilizing random data, demonstrates that this method can lead to inaccurate projections, increasing the number of expected extreme floods in future years and decreasing them in historical baseline years, even when no change is indicated by the data. Additionally, we find that the longer the historical period used, the smaller the bias. By simulating the characteristics of real hydrological model projections with artificial data, we are able to estimate a bias similar to that observed in these projections, and thus propose a simple method for its mitigation. Our findings indicate that previous studies might have overstated the impact of climate change on the projected increase in flood frequency and affected people. Additionally, using short historical records to design flood defenses can lead to more frequent flooding than anticipated, even without climate change. Key Points: Using a short historical period both to define extreme flood thresholds and as a base for future projections leads to significant biasThis bias shows an inverse relationship with the length of the base period and is slightly influenced by certain data characteristicsWe propose a practical adjustment method and suggestions to reduce biases in estimating future flood frequency changes [ABSTRACT FROM AUTHOR]

We show that the winter Beaufort High (BH) index defined by sea level pressure (SLP) has a robust negative trend under the scenarios SSP5‐8.5 and SSP2‐4.5, with a reduction by about 5 hPa and 2 hPa, respectively, by the end of the 21st century. The negative trends in the BH SLP are associated with the changes in the background SLP over the Arctic basin. However, the vorticity of the winter BH tends to intensify under SSP5‐8.5, but shows no robust increase under SSP2‐4.5. The intensification is associated with the enhanced ridge over the Western Arctic. Therefore, it is necessary to take into account the dynamic aspects of the BH, such as vorticity. Based on this assessment, under the most likely emissions scenario, the winter BH is likely to weaken through the 21st century, in terms of SLP, but shows no robust changes in term of vorticity. Plain Language Summary: We used the latest IPCC global climate model outputs to investigate the wintertime changes in the Beaufort High (BH). Under the climate change scenarios, during winter, the sea level pressure (SLP) over the BH region is expected to decrease. The SLP reduction is up to 5 hPa by the end‐of‐the‐century. Thus, the BH seems to become weaker. However, its vorticity tends to increase under SSP5‐8.5, mostly due to the intensification of the ridge over the western North America. Key Points: The Beaufort High (BH) index defined by sea level pressure (SLP) decreases under warming climate scenariosMeanwhile, the BH vorticity tends to intensify due to the change in the ridge over the Western ArcticBesides the SLP, impact studies of the BH on the Arctic Ocean need to consider its dynamics such as vorticity [ABSTRACT FROM AUTHOR]

How forests respond to accelerated climate change will affect the terrestrial carbon cycle. To better understand these responses, more examples are needed to assess how tree growth rates react to abrupt changes in growing‐season temperatures. Here we use a natural experiment in which a glacier's fluctuations exposed a temperate rainforest to changes in summer temperatures of similar magnitude to those predicted to occur by 2050. We hypothesized that the onset of glacier‐accentuated temperature trends would act to increase the variance in stand‐level tree growth rates, a proxy for forest net primary productivity. Instead, dendrochronological records reveal that the growth rates of five, co‐occurring conifer species became less synchronous, and this diversification of species responses acted to reduce the variance and to increase the stability of community‐wide growth rates. These results warrant further inquiry into how climate‐induced changes in tree‐growth diversity may help stabilize future ecosystem services like forest carbon storage. Plain Language Summary: Knowing how ecosystems responded to rapid climate changes in the past can help society prepare for the unprecedented rates of change expected in the future. Here, we take advantage of a natural experiment in which a fluctuating glacier caused a temperate rainforest to experience accentuated climate trends similar to those predicted to occur globally over the coming century. As climate changes became accentuated, tree species that once grew in unison shifted to more diversified growth patterns, which unexpectedly caused less variance and greater stability in community‐wide growth rates. Similar diversified growth responses may become important in stabilizing rates of forest carbon sequestration elsewhere. Key Points: A glacier‐adjacent forest in Southeast Alaska serves as a natural climate change experimentDendrochronology reveals that asynchronous species growth rates enhanced the forest‐wide growth stability during accelerated climate trends [ABSTRACT FROM AUTHOR]

There is ample evidence for ice layers and lenses within glacial firn. The standard model for ice layer formation localizes the refreezing by perching of meltwater on pre‐existing discontinuities. Here we argue that even extreme melting events provide insufficient flux for this mechanism. Using a thermomechanical model we demonstrate a different mechanism of ice layer formation. After a melting event when the drying front catches up with the wetting front and arrests melt percolation, conductive heat loss freezes the remaining melt in place to form an ice layer. This model reproduces the depth of a new ice layer at the Dye‐2 site in Greenland. It provides a deeper insight into the interpretation of firn stratigraphy and past climate variability. It also improves the simulation of firn densification processes, a key source of uncertainty in assessing and attributing ice sheet mass balance based on satellite altimetry and gravimetry data. Plain Language Summary: Firn covers a significant portion of Earth's glaciers and ice sheets. It can store surface meltwater and prevent runoff into the ocean. The widespread presence of ice layers embedded in firn formed by meltwater refreezing may prevent meltwater storage and contribute to sea level rise. However, current models of ice layer formation, originally developed for snow, do not seem to work in firn. This work presents a different mechanism for ice layer formation without invoking pre‐existing ice layers within the firn. Our model shows that the sequencing of ice layers formed by subsequent melting events depends on the overall heat added to the firn. Deeper layers occur in warmer, more porous firn during intense melt events in a warming climate. This insight enhances our understanding of firn layering and can help deduce past climate variations. Our model aids in understanding the density evolution of firn to reduce uncertainties in remote sensing data that determines the ice sheet mass loss and its contribution to global sea‐level rise. Key Points: A new ice layer forms without meltwater perching when freezing localizes after a melt event as heat conduction dominates over advectionDeeper ice layers form in warming climatic conditions whereas denser ice layers form near surface in net‐zero climatic conditionsResults indicate the possibility of deducing past variability in climate from firn stratigraphy and vice versa [ABSTRACT FROM AUTHOR]

Reconstruction of the seawater carbonate system is essential for an improved understanding of glacial‐interglacial oceanic carbon cycling and climate change. However, continuous high‐resolution ocean carbonate chemistry data are generally lacking for the Plio‐Pleistocene. Here, we present a deep Pacific carbonate ion saturation state (Δ[CO32−]) record spanning the last 5.1 Myr, reconstructed from the size‐normalized shell weight of planktonic foraminifer in the western tropical Pacific. Deep Pacific Δ[CO32−] has been modulated primarily by orbital obliquity since 5.1 Ma, during which it has exhibited in‐phase behavior with the 40‐Kyr obliquity cycle. Significantly, the amplitude of the 40‐Kyr Δ[CO32−] cycles has responded linearly to obliquity forcing throughout the Plio‐Pleistocene, independent of the late Pliocene intensification of Northern Hemisphere glaciation. We speculate that the obliquity signal in the deep Pacific Δ[CO32−] record reflects an ocean‐atmosphere circulation feedback mediated by migration of the Southern Hemisphere Westerlies. Plain Language Summary: The ocean has played an important role in controlling glacial‐to‐interglacial atmospheric pCO2 variation through changes in its carbon inventory. To decipher the patterns and drivers of the oceanic carbon cycle and climate change through glacial cycles, we provide a continuous Plio‐Pleistocene deep Pacific carbonate ion saturation state (Δ[CO32−]) at orbital time scales. The deep PacificΔ[CO32−] has been modulated by orbital forcing since 5.1 Ma, a time interval during which it has exhibited in‐phase behavior with the 40‐Kyr obliquity cycle as well as a linear response of Δ[CO32−] amplitude to obliquity range. We speculate that Plio‐Pleistocene glacial cycles of the deep Pacific carbon storage were linked to variation in Southern Hemisphere upwelling rates yoked to meridional migration of the Westerlies. Key Points: Deep Pacific Δ[CO32−] has been modulated primarily by orbital obliquity since 5.1 Ma40‐Kyr Δ[CO32−] cycles were in‐phase with and responded linearly to 40‐Kyr band obliquity forcingPlio‐Pleistocene glacial cycles of deep Pacific carbon storage were linked to meridional migration of the Southern Hemisphere Westerlies [ABSTRACT FROM AUTHOR]

Probabilities of coastal extreme water levels (EWLs) are increasing as sea levels rise. Using a time‐dependent statistical model on tide gauge data along U.S. and Pacific Basin coastlines, we show that EWL probability distributions also shift on an annual basis from climate forcing and long‐period tidal cycles. In some regions, combined variability (>15 cm) can be as large or larger than the amount of sea level rise (SLR) experienced over the past 30 years and projected over the next 30 years. Considering SLR and variability by 2050 at a location like La Jolla, California suggests a moderate‐level (damaging) flood today with a 50‐year return level (2% annual chance) would occur about 3–4 times a year during an El Nino nearing the peak of the nodal tide cycle. If interannual variability is overlooked, SLR related impacts could be more severe than anticipated based solely upon decadal‐scale projections. Plain Language Summary: Coastal communities are flooding more often due to sea level rise (SLR), but some years are worse than others. We use a statistical model to show how the probabilities of coastal high waters, often referred to as extreme water levels—a combination of above average tides and storm surge—have shifted higher or lower every year with SLR and from changes in the tides and climatic (persistent weather and ocean) patterns. There are many U.S. and Pacific coastal regions where year‐to‐year variability is 15 cm or more, which is as large as the last 30 years of SLR and this pattern is projected to continue over the next 30 years. Considering additional SLR over the next 30 years could help compensate for year‐to‐year variability. Key Points: Probability distributions of coastal extreme water levels shift higher and lower with tide cycles, climatic patterns and sea level rise (SLR)Annual shifts of >15 cm from variability along Pacific coasts exceed SLR over the last 30 years and projected over the next 30 yearsAnnual‐scale variability envelopes are envisioned to assist in decadal‐scale SLR and flood frequency assessments [ABSTRACT FROM AUTHOR]

Continental alkaline magmatism has been suggested to play a significant role in releasing deep mantle carbon into the atmosphere, which can greatly impact the global climate. However, the temporal variations of alkaline magmatism and their potential to modulate climate over geologic time remain poorly constrained. The detrital zircon record is a frequently used proxy for tracking secular variations in particular magmatism. Here, we use a novel machine‐learning technique to discriminate zircon from carbonatites, kimberlites, and other alkaline rocks. A global compilation of detrital zircon yields continental alkaline magmatic flare‐ups between 1,050−850, 650−500, 250−200, and 50−0 Ma. Our estimates indicate relatively elevated contributions of total magmatic carbon outgassing from alkaline magmatism during the aforementioned magmatic flare‐ups. We infer that anomalous alkaline magmatism may influence global warming during specific intervals of geologic time, but when they are not that voluminous or persistent extensive arc magmatism may drive warming conditions. Plain Language Summary: The potential of volcanic CO2 emissions to modulate atmospheric CO2 levels and affect the environment of our planet has been recognized. Some specific volcanic types, such as continental arc volcanism, have been hypothesized to play a dominant role in driving long‐term climate change. Recently, the efficiency of continental alkaline magmatism in releasing carbon from the deep mantle to the atmosphere and its ability to influence Earth's climate is proposed for certain timescales and supported by empirical data. However, the quantitative estimation of the alkaline magmatic activity over geologic time and its general link to the global climate change remains poorly constrained. Here, we assess the alkaline magmatic variations based on the detrital zircon record and a novel machine‐learning model which could discriminate zircon from carbonatites, kimberlites and other related alkaline silicate rocks. The predictive result shows several peaks at 1,050−850, 650−500, 250−200, and 50−0 Ma, which is considered a minimum estimation due to the preservation bias of the detrital zircon record. Our estimates indicate that continental alkaline magmatism may influence global warming during specific intervals of geologic time such as the early Paleozoic and early Mesozoic. Key Points: Frequency of magmatic events can be assessed by a machine‐learning analysis of zirconContinental alkaline magmatism peaked between 1,050−850, 650−500, 250−200, and 50−0 MaAnomalous alkaline magmatism may contribute to global warming at certain times [ABSTRACT FROM AUTHOR]

Today, volcanic sulfur emissions into the atmosphere are measured spectroscopically from the ground, air and space. For eruptions prior to the satellite era, two main sulfur proxies are used, the rock and ice core records, as illustrated by Peccia et al. (2023, https://doi.org/10.1029/2023gl103334). The first approach is based on calculations of the sulfur content of the magma, while the second uses traces of sulfur deposited in ice. Both approaches have their limitations. For glaciochemistry, the volcano responsible for a sulfur anomaly is often unknown and the atmospheric pathway by which the sulfur reached the ice uncertain. The petrologic method relies, too, on uncertain estimates of eruption size and a number of geochemical assumptions that are hard to verify. A deeper knowledge of processes occurring both within magma bodies prior to eruption, and within volcanic plumes in the atmosphere is needed to further our understanding of the impacts of volcanism on climate. Plain Language Summary: Volcanic emissions of sulfur gases during large eruptions can change the global climate. Today, advanced spectroscopic tools allow us to measure sulfur from the ground, air and space. But to understand the impacts of volcanic activity on climate back through history we need to estimate volcanic sulfur releases in other ways. Clues can be found in the pumice deposits found around a volcano and, perhaps more surprisingly, in the ice caps of the polar regions, which receive the eventual fallout from large eruptions. Both approaches have limitations that are addressed in a recent work by Peccia et al. (2023, https://doi.org/10.1029/2023gl103334) and that are at the focus of our commentary. Key Points: The impact of volcanic activity on climate remains difficult to quantify for eruptions prior to the instrumental eraThe petrological and glaciochemical methods each provide answers, but are still fraught with large uncertaintiesWe need to further our understanding of the physicochemical processes occurring both within magma reservoirs and volcanic plumes [ABSTRACT FROM AUTHOR]

Global climate models (GCMs) are unable to produce detailed runoff conditions at the basin scale. Assumptions are commonly made that dynamical downscaling can resolve this issue. However, given the large magnitude of the biases in downscaled GCMs, it is unclear whether such projections are credible. Here, we use an ensemble of dynamically downscaled GCMs to evaluate this question in the Sierra‐Cascade mountain range of the western US. Future projections across this region are characterized by earlier seasonal shifts in peak flow, but with substantial inter‐model uncertainty (−25 ± 34.75 days, 95% confidence interval (CI)). We apply the emergent constraint (EC) method for the first time to dynamically downscaled projections, leading to a 39% (−28.25 ± 20.75 days, 95% CI) uncertainty reduction in future peak flow timing. While the constrained results can differ from bias corrected projections, the EC is based on GCM biases in historical peak flow timing and has a strong physical underpinning. Plain Language Summary: Global climate models (GCMs) provide information on projected changes. However, their resolution is too coarse to assess future land surface changes at the regional scale. Dynamical downscaling resolves this issue, by refining the representation of hydroclimate conditions at a higher‐resolution. However, GCMs have unique historical biases that remain despite dynamical downscaling. Typically these GCM biases are ignored, resulting in assessments at the regional scale with large uncertainty. Here, we use an approach, called emergent constraint (EC), to reduce the uncertainty in projected changes in the timing of high flow conditions across the Sierra Nevada and Cascade region of the western United States. While this approach was introduced nearly two decades ago with coarse‐resolution GCM data, this is the first time the EC approach has been used at the regional scale with dynamical downscaling. From our analysis, we find high flow events are likely to occur earlier in the future for the Sierra‐Cascade region. This conclusion contains substantial uncertainty without the use of the EC approach. While this study focuses on the timing of high flows, it opens the door to a variety of follow‐on studies, seeking to produce more robust projections of hydroclimate change across the western US. Key Points: For the first time, an emergent constraint (EC) is used to reduce uncertainty in hydroclimate projections from a dynamically downscaled ensembleWe show that snowmelt‐driven basins in the western United States are very likely to experience earlier peak flows in the futureWith EC, uncertainty in future peak flow timing is reduced by roughly 39%; however, bias corrected results can differ [ABSTRACT FROM AUTHOR]

Probabilistic projections from the UK Climate Projections 2018 are presented for four global warming levels (GWLs) at 1.5, 2, 3, and 4°C above the 1850–1900 baseline. Our results show how uncertainties associated with climate models and four representative concentration pathways (RCP) emission scenarios translate to UK regional scale changes in maximum temperature and precipitation, with data also available for minimum and mean temperatures, humidity and surface net downward shortwave radiation flux. We compare weighting the likelihood of RCPs based on (hypothetical) policy decisions, against our baseline assumption that each RCP is equally likely. Differences between weighted and unweighted GWL distributions are small, particularly in relation to the full breadth of uncertainties that are incorporated into the probabilistic projections. Finally we quantify the relative importance of scenario, model and internal variability on regional projected GWLs and show that uncertainty associated with an uncertain climate response to forcings dominates at all GWLs. Plain Language Summary: Global warming levels define the global averaged increase in temperature since the pre‐industrial period. This study looks at what the regional climate in the UK could be like in the future. We estimate how temperature and precipitation in the UK might change under four different global warming levels (GWLs) (1.5, 2, 3, and 4°C above pre‐industrial times). We account for a wide range of outcomes from both climate models and future emissions scenarios. Assuming that the range of future emissions scenarios are equally likely, the center of the ranges of years that we could reach GWLs of 1.5, 2, 3, and 4°C are 2032, 2050, 2072, and 2078 respectively. The largest influence of future climate on these range estimates comes from our understanding of how the Earth actually responds to changes in greenhouse gases. Even if we knew the exact quantity of greenhouse gas emissions we would emit in the future, we still wouldn't be able to predict the exact changes in UK climate with perfect accuracy because our understanding of the regional climate response to these emissions requires further investigation. Key Points: Probabilistic climate projections from the UK are presented for four global warming levels (GWLs) across four representative concentration pathways (RCP)We show how uncertainty associated with climate models and future emission scenarios translate to UK regional scale changesUncertainty associated with an uncertain climate response to forcings dominates at all GWLs [ABSTRACT FROM AUTHOR]

Seasonal hindcasts have previously been demonstrated to show multi‐decadal variability in skill across the twentieth century in indices describing El‐Niño Southern Oscillation (ENSO), which drives global seasonal predictability. Here, we analyze the skill of predicting ENSO events' magnitude and spatial pattern, in the CSF‐20C coupled seasonal hindcasts in 1901–2010. We find minima in the skill of predicting the first (in 1930–1950) and second (in 1940–1960) principal components of sea‐surface temperature (SST) in the tropical Pacific. This minimum is also present in the spatial correlation of SSTs, in 1930–1960. The skill reduction is explained by lower ENSO magnitude and variance in 1930–1960, as well as decreased SST persistence. The SST skill minima project onto surface winds, leading to worse predictions in coupled hindcasts compared to hindcasts using prescribed SSTs. Questions remain about the offset between the first and second principal components' skill minima, and how the skill minima impact the extra‐tropics. Plain Language Summary: Seasonal forecasts use slowly changing elements of the climate system to predict average weather and climate several months ahead, and have applications across the energy, agriculture, and insurance industries. The most important signal is El‐Niño Southern Oscillation (ENSO), an ocean temperature pattern in the tropical Pacific which varies between warm and cold phases every 2–7 years. ENSO's specific pattern, including how warm/cold it is compared to normal, and where heating/cooling is concentrated, influences global weather. Seasonal forecasting models are tested by running 'reforecasts': comparing a 'forecast' of the past with observations. In this study, we investigate how skilfully reforecasts from a state‐of‐the‐art seasonal forecasting model reproduce observations, for sea‐surface temperatures in the tropical Pacific (where ENSO occurs). We analyze reforecast skill in every Northern Hemisphere winter from 1901 to 2010 and find periods of high skill at the start and end of the century, with reduced skill in 1930–1960. This was likely caused by a reduction in the size of ENSO events, and decreased sea‐surface temperature memory. This reduction in ocean skill leads to lower skill for surface‐level winds. These results are important for understanding whether season‐ahead predictability changes over decades/centuries, and how climate change might impact this predictability. Key Points: The skill of predicting the spatial pattern of ENSO events in coupled seasonal hindcasts is low in 1930–1960, compared to before and afterThe skill minimum is attributable to lower ENSO variability and decreased SST persistence in the mid‐century periodDecreased skill in the SST spatial pattern is linked to decreased surface wind skill in coupled hindcasts (vs. atmosphere‐only hindcasts) [ABSTRACT FROM AUTHOR]

The atmospheric large‐scale environment determines the occurrence of local extreme precipitation, and it is unclear how climate change affects this relationship. Here we investigate the present‐day relationship between large‐scale circulation types (CTs) and daily precipitation extremes over Scandinavia and its future change. A 50‐member EC‐Earth3 large ensemble is used to assess future changes against internal variability. We show that CTs are related to extreme precipitation over the entire domain. The intensity of extreme daily precipitation increases in all seasons in the future climate, generally following the strength of warming in the six different future scenarios considered. However, no significant future change is found in the relationship between extreme precipitation and the CTs in any season or scenario. The results have important implications for applications that rely on the stability of this relationship, such as statistical and event‐based dynamical downscaling of future weather and climate predictions and long‐term climate projections. Plain Language Summary: The occurrence of local devastating extreme precipitation events is influenced by the large‐scale flow of the atmosphere, that is, high‐ or low‐pressure systems and winds from different directions. Understanding this connection helps us to predict precipitation extremes using more readily available information about the large‐scale flow. However, it is not known if the relationship that we observe in the present climate will hold under future climate conditions. Here we study the present‐day relationship between the large‐scale flow and local precipitation events over Scandinavia and analyze how it will change toward the end of the 21st century. We find that extreme precipitation events become more intense over entire Scandinavia in the future climate, but their connection to the large‐scale environment remains unchanged. Key Points: Large‐scale circulation types (CTs) can be used as precursors of local extreme precipitation events over ScandinaviaThe intensity of extreme precipitation events over Scandinavia increases with the warming strength in the future climateThe relationship between extreme precipitation and CTs remains unchanged over Scandinavia in the future climate [ABSTRACT FROM AUTHOR]

The ocean's organic carbon export is a key control on atmospheric pCO2 and stimulating this export could potentially mitigate climate change. We use a data‐constrained model to calculate the sensitivity of atmospheric pCO2 to local changes in export using an adjoint approach. A perpetual enhancement of the biological pump's export by 0.1 PgC/yr could achieve a roughly 1% reduction in pCO2 at average sensitivity. The sensitivity varies roughly 5‐fold across different ocean regions and is proportional to the difference between the mean sequestration time τseq of regenerated carbon and the response time τpre of performed carbon, which is the reduction in the preformed carbon inventory per unit increase in local export production. Air‐sea CO2 disequilibrium modulates the geographic pattern of τpre, causing particularly high sensitivities (2–3 times the global mean) in the Antarctic Divergence region of the Southern Ocean. Plain Language Summary: Atmospheric CO2 levels could be reduced by stimulating plankton in the ocean to produce more organic carbon that then sinks to depth (is exported) at a higher rate. The resulting carbon deficit in surface waters drives atmospheric carbon into the ocean. The efficacy of this process depends on how long the exported carbon stays isolated from the surface and how quickly the surface deficit can be filled. Here we investigate how sensitive atmospheric CO2 levels are to a given enhancement in carbon export and where such enhancements would be most effective. We show that the sensitivity is determined by the difference between the time for which exported carbon stays sequestered at depth and the time with which the rest of the carbon in the ocean responds to the additional export rate. High sequestration times are found where the organic carbon is exported into old deep waters, while fast response times are found where it is easy for gas exchange to inject carbon into the ocean and where the additionally exported carbon is less likely to resurface and escape into the atmosphere. These factors result in the Southern Ocean and the tropics having greatest sensitivity. Key Points: pCO2 sensitivity to carbon export perturbations is governed by sequestration time, preformed response time, and atmospheric turnover timeHigh sensitivity occurs in the tropics and Southern Ocean where sequestration time is long and preformed response time is shortThe preformed response time is modulated by air‐sea CO2 disequilibrium and shortest in the Atlantic and Southern Ocean [ABSTRACT FROM AUTHOR]

Surface, aircraft, and satellite measurements indicate pervasive early cold season (Augut–September) CO2 emissions across Arctic regions, consistent with increased ecosystem metabolism in plants and soils. A key remaining question is whether cold season sources will become large enough to permanently shift the Arctic into a net carbon source. Polar orbiting GHG satellites provide robust estimation of regional carbon budgets but lack sufficient spatial coverage and repeat frequency to track sink‐to‐source transitions in the early cold season. Mission concepts such as the Arctic Observing Mission (AOM) advocate for flying imaging spectrometers in highly elliptical orbits (HEO) over the Arctic to address sampling limitations. We perform retrieval and flux inversion simulation experiments using the AURORA mission concept, leveraging a Panchromatic imaging Fourier Transform Spectrometer (PanFTS) in HEO. Our simulations demonstrate the potential benefits of increased CO2 sampling for detecting emissions during the early cold season. Plain Language Summary: The Arctic is warming rapidly, leading to an acceleration of carbon exchange across tundra and boreal ecosystems. These changing flows of carbon can be difficult to detect using traditional observing systems. We propose that measurement systems which observe Arctic ecosystems continuously from a quasi‐GEO orbit can more accurately detect these important changes, such that unexpected and dangerous feedbacks to climate warming can be monitored and accounted for. Key Points: The Arctic Fourier Transform Spectrometer Investigation (AURORA) mission concept addresses GHG sampling limitations in the ArcticAURORA uses a highly elliptical orbit (HEO) to increase repeat frequency, and a panchromatic iFTS for SWIR O2 and CO2 bands (0.7–2.5 μm)Simulation experiments show potential benefits of increased sampling frequency for grid scale detection of early cold season CO2 emissions [ABSTRACT FROM AUTHOR]

Previous modeling studies indicate that even though marine cloud brightening under a susceptibility‐based strategy is effective in reducing the global average surface temperature, it triggers a La Niña‐like sea‐surface temperature response with cooling mostly confined within lower latitudes. Here we explore a different cloud seeding strategy involving seeding of regions with low susceptibility, primarily over the ocean in midlatitudes during the winter. Simulations with the Community Earth System Model, version 2 reveal that because the regional forcing is weaker and more widespread, cooling is more evenly distributed over the globe. This new strategy also does not result in the La Niña‐like state seen in the other strategies. Plain Language Summary: Most previous marine cloud brightening (MCB) simulations have focused on the regions more likely to induce strong cooling. A common response in these simulations across different climate models is a La Niña‐like sea surface temperature pattern which could disrupt the El Niño Southern Oscillation. We explored simulations in which MCB is deployed over the least susceptible regions rather than the most susceptible. This new seeding strategy cools the globe more evenly and no longer triggers a La Niña‐like response. Key Points: We explore the idea of deploying marine cloud brightening (MCB) over broader regions with low susceptibility to cloud seedingThis approach induces fairly uniform cooling over the globe unlike MCB that targets the most susceptible regionsThis new seeding strategy has fewer climatic side effects and does not trigger a La Niña‐like response [ABSTRACT FROM AUTHOR]

The El Niño–Southern Oscillation (ENSO) teleconnection to Europe is projected to strengthen under global warming in most climate model simulations. However, given the current difference between recent observations and historical model simulations of tropical Pacific sea surface temperature trends, with models simulating an El Niño‐like warming in recent decades which is in disagreement with observations, it is important to understand the relative contributions of changes to the teleconnection forcing and background state to the overall teleconnection change. Using idealized climate model experiments, we show that both the eastward shift of El Niño precipitation and background state changes make contributions to the overall teleconnection change. These results suggest that the ENSO–Europe teleconnection can be expected to strengthen under global warming, even if ENSO precipitation anomalies do not shift eastwards as currently projected. However, the magnitude of the strengthening may depend on how much of an eastward shift does occur. Plain Language Summary: El Niño–Southern Oscillation (ENSO) can influence the weather and climate in Europe, and this connection is expected to become stronger under global warming according to most climate models. However, there is a difference between recent observations of sea surface temperatures in the Pacific Ocean and what climate models simulate. These differences could have important implications for future projections of ENSO's impact on Europe. To understand how likely the projected future strengthening of this link is, we looked at how two factors contribute to this connection change: (a) changes in rainfall associated with El Niño in the tropical Pacific and (b) overall changes in global climate elsewhere. Using a simplified climate model, we found that both these factors play a role in making the connection between El Niño and Europe stronger. This suggests that even if the specific patterns of El Niño rainfall don't change as projected, the link between El Niño and Europe will still get stronger due to global warming. However, how much stronger it gets might depend on the actual changes in El Niño rainfall, so it's important to figure out why there's a difference between observations and the model projections of Pacific Ocean temperature trends. Key Points: The El Niño–Southern Oscillation teleconnection to Europe is projected to strengthen under global warmingThis change is driven by an eastward shift of El Niño precipitation anomalies in the tropical Pacific and background state changes globallyBackground state changes have a greater impact on European circulation than precipitation changes, particularly over central‐eastern Europe [ABSTRACT FROM AUTHOR]

In 2023, Antarctic sea‐ice extent (SIE) reached record lows, with winter SIE falling to 2.5Mkm2 below the satellite era average. With this multi‐model study, we investigate the occurrence of anomalies of this magnitude in latest‐generation global climate models. When these anomalies occur, SIE takes decades to recover: this indicates that SIE may transition to a new, lower, state over the next few decades. Under internal variability alone, models are extremely unlikely to simulate these anomalies, with return period >1000 years for most models. The only models with return period <1000 years for these anomalies have likely unrealistically large interannual variability. Based on extreme value theory, the return period is reduced from 2650 years under internal variability to 580 years under a strong climate change forcing scenario. Plain Language Summary: In 2023, the area of winter Antarctic sea ice fell to the lowest measured since satellite records began in late 1978. It is still under debate how far this low can be explained by natural variations, and how much can be explained by climate change. Global climate models are tools used to study past and predict future global change. We show that, without climate change, the latest generation of these models are extremely unlikely to simulate a sea‐ice reduction from the mean as large as observed in winter 2023. Including strong climate change quadruples the chance of such a reduction, but the chance is still very low. When these rare reductions are simulated, sea ice takes around 10 years to recover to a new, lower, area: this indicates that Antarctic sea ice may transition to a new, lower, state over the next few decades. Key Points: The latest generation of global climate models rarely simulate an Antarctic sea‐ice extent anomaly as negative as observed in winter 2023The return period for such an anomaly is 2650 years under internal variability, decreasing to 580 years under strong climate change forcingAfter the anomaly occurs, sea‐ice extent recovers within a decade to a new, lower state [ABSTRACT FROM AUTHOR]

We compare abrupt CO2‐quadrupling (abrupt‐4xCO2) and ‐doubling (abrupt‐2xCO2) simulations across 10 CMIP6 models. Two models (CESM2 and MRI‐ESM2‐0) warm substantially more than twice as much under abrupt‐4xCO2 than abrupt‐2xCO2, which cannot be explained by the non‐logarithmic scaling of CO2 forcing. Using an energy balance model, we show that increased warming rates within these two models are driven by both less‐negative radiative feedbacks and smaller global effective heat capacity under abrupt‐4xCO2. These differences are caused by a decrease in low cloud cover and shallower ocean heat storage, respectively; both are linked to smaller fractional declines in the Atlantic Meridional Overturning Circulation (AMOC) under abrupt‐4xCO2 (relative to abrupt‐2xCO2). On a global scale, higher climate sensitivity under larger forcing can be explained by a feedback‐temperature dependence; however, we find that forcing‐dependent spatial warming patterns due to AMOC decline are an important physical mechanism which reduces warming in a way that is not captured by a global‐mean framework. Plain Language Summary: Climate model simulations with abruptly quadrupled CO2 concentrations are often used to characterize the climate response of global climate models to greenhouse gas forcing and inform predictions of the future. In this study, we ask how relevant CO2‐quadrupling experiments are to more modest warming scenarios by comparing them to CO2‐doubling experiments. It is usually assumed that CO2‐quadrupling will produce about twice as much warming than CO2‐doubling, but this is not the case in some models. Two global climate models in particular warm much more under CO2‐quadrupling than twice the warming under CO2‐doubling. By fitting each climate model to a simpler energy balance model, we find that these two climate models are strongly impacted by the effective heat capacity (which can be impacted by ocean circulation changes) in comparison to other climate models where radiative effects (such as effects from clouds) are more impactful. Changes in the strength of an Atlantic Ocean circulation are important for both radiative effects and heat storage. Therefore, the behavior of our planet at 1.5 or 2 times CO2 cannot necessarily be estimated with quadrupling CO2 experiments. Key Points: Models with disproportionate Atlantic Meridional Overturning Circulation (AMOC) declines under abrupt CO2 doubling experience less warmingAMOC decline modulates transient warming by influencing both low cloud feedbacks and the global effective heat capacityTherefore, abrupt quadrupling of pre‐industrial CO2 simulations do not necessarily capture the behavior of lesser warming scenarios [ABSTRACT FROM AUTHOR]

Fires were historically rare in tropical forests of West and Central Africa, where dense vegetation, rapid decomposition, and high moisture limit available fuels. However, increasing heat and drought combined with forest degradation and fragmentation are making these areas more susceptible to wildfires. We evaluated historical patterns of Moderate Resolution Imaging Spectroradiometer active fires in African tropical forests from 2003 to 2021. Trends were mostly positive, particularly in the northeastern and southern Congo Basin, and were concentrated in areas with high deforestation. Year‐to‐year variation of fires was synchronized with increasing temperature and vapor pressure deficit. There was anomalously high fire activity across the region during the 2015–2016 El Niño. These results contrast with the drier African woodlands and savannas, where fire has been decreasing. Further attention to fires in African tropical forests is needed to understand their global impacts on carbon dynamics and their local implications for biodiversity and human livelihoods. Plain Language Summary: Fires have historically been rare in the moist tropical forests of West and Central Africa. However, these forests are becoming more vulnerable to fire because climate change is causing higher temperatures and drought stress in the tropics. Human activities such as agriculture, logging, and mining also fragment the remaining forests and make them more susceptible to fire. We used measurements of actively burning fires from Earth observing satellites to study how the amount of fire in African tropical forests has changed from 2003 to 2021. There were several areas with strong trends of increasing fire, mainly in the Congo Basin. In contrast, there were almost no locations where fire was decreasing. The increasing fire trends occurred in locations where deforestation was occurring and climate was becoming warmer and drier. During 2015–2016 global weather patterns caused by an exceptionally strong El Niño event were associated with higher‐than‐normal fire activity throughout the tropical forests in West and Central Africa. Increasing fire is a concern because it can release greenhouse gasses into the atmosphere, reduce the amount of carbon stored in the African tropics, degrade habitats for species that live in tropical forests, and decrease the amounts of wood, food, medicine and other resources that forests provide for humans. Key Points: Active fire detections increased from 2003 to 2021 across Central Africa, with positive fire trends concentrated in the Congo BasinFire increased in areas with high deforestation and the trends were synchronized with increasing temperature and vapor pressure deficitThere was higher‐than‐usual fire activity in tropical African forests associated with the exceptionally strong 2015–2016 El Niño event [ABSTRACT FROM AUTHOR]

FY‐3E plays a vital role in the meteorological global earth observing system. Precipitable water vapor (PWV) is an essential parameter for the water cycle and global climate change. Here, we carry out the PWV retrieval using the MERSI‐LL sensor onboard the FY‐3E satellite for the first time. The retrieval accuracy under different cloudage conditions is validated by the extra PWV from ground‐based GNSS and spaceborne occultation. For the results against ground‐based GNSS, the total accuracy shows an RMSE of 2.69–3.36 mm as the clouds increase, and correlation coefficients higher than 0.95. The spatial accuracy distribution indicates that inland stations have higher accuracy than the coast and island stations. As for the results against spaceborne occultation, the verification accuracy varies with the spatial pairing distance, showing poor accuracy in the low latitude area. This study can provide an essential reference for the community to understand the current water vapor inversion performance of MERSI‐LL. Plain Language Summary: Fengyun 3E (FY‐3E), as the world's first civilian early morning (EM) orbit meteorological remote sensing satellite, plays an important role in filling the EM‐orbit gap in the global earth observing system. Precipitable water vapor (PWV) is crucial for understanding the process of water cycle, global climate change, and numerical weather prediction. This study exhibits the first attempt to retrieve PWV using the MERSI‐LL sensor onboard the FY‐3E satellite. The accuracy of the PWV retrieval under different cloud conditions is validated by ground‐based GNSS and spaceborne occultation data. Results from the comparisons with ground‐based GNSS data reveal that RMSE ranges from 2.69 to 3.36 mm as cloud increases, with correlation coefficients higher than 0.95. Furthermore, the spatial distribution of accuracy indicates that inland stations exhibited higher precision than coastal and island stations. The verification accuracy against spaceborne occultation decreases as the spatial pairing distance increases, and the results reveal that poor accuracy occurs in the low latitude area. This study provides crucial insights into the water vapor retrieval of MERSI‐LL, which will be valuable for the scientific community in understanding the current capabilities of this sensor. Key Points: First time to retrieve Precipitable water vapor (PWV) with FY‐3E MERSI‐LL data under all weather conditionsRetrieval accuracy was cross‐validated both with co‐platform occultation and ground GNSSRandom Forest (RF) method with the advantage of high accuracy and stability was applied to retrieve PWV [ABSTRACT FROM AUTHOR]

The expected increase in climate change related methane emissions will result in an increase in middle atmospheric water vapor abundance. This will in turn amplify the brightness of noctilucent clouds (NLC). To examine how NLC will impact the absorption of solar radiation, we utilized both an atmospheric background model and a microphysical model spanning the period from 1950 to 2100. At a latitude of 69 ± 3°N, UV absorption at λ = 126 nm is projected to rise from ∼3% to ∼7%. In specific regions, the absorption may spike to approximately 30% by the year 2100. In the visible spectrum, we observe an absorption increase from 0.0030% in 1950 to 0.020% by 2100. Local absorption reach up to 0.35% by the year 2100. These trends are similar at 79 ± 3°N, but are smaller at 58 ± 3°N. Future average absorptions are comparable to solar cycle fluctuations, but local increases are significantly more pronounced. The ice mass contained in NLC is projected to surge from 677 to 1871 tons between 1950 and 2100. Plain Language Summary: Noctilucent clouds (NLC) consist of water ice particles and appear in the summer season in the upper mesosphere at high/middle latitudes where temperatures are very low. Methane is photochemically converted to water vapor in the middle atmosphere. Therefore, the future increase of methane concentration will lead to an increase in water vapor, and to an enhancement of NLC occurrence and brightness. We apply an atmospheric background model and a microphysical ice particle model to study the associated absorption of solar radiation. At 69°N mean absorptions in the UV will increase from ∼3% to ∼7% from 1950 to 2100, respectively. Locally, the absorption can increase to ∼30% in 2100. In the visible (λ = 532 nm) the corresponding numbers are 0.0030% (1950) to 0.020% (2100), that is, an increase by a factor of ∼7, and local maxima up to 0.35% in 2100. Mean absorptions are comparable to variations throughout a solar cycle, but may locally be much larger. Effects on the photochemistry are therefore expected. The total amount of ice mass bound in NLC also increases with time, namely from 677 tons in 1950 to 1871 tons in 2100. NLC will be easier to observe by naked eye, that is, they will be more frequent and brighter. Key Points: Noctilucent clouds (NLC) are ice clouds in the summer mesopause region at middle and polar latitudesThe expected methane related increase in water vapor at NLC heights will lead to more and larger ice particlesLarger ice particles will lead to an enhanced absorption of solar radiation [ABSTRACT FROM AUTHOR]

El Niño/Southern Oscillation (ENSO) is the main climate mode that drives the interannual variability in climate and consequently vegetation greenness. While widespread green‐up has been reported and examined in tropical America during El Niño, it remains unclear how vegetation in tropical Asia changes during the period. Here, we used four remote sensing‐based leaf area index (LAI) products to investigate changes in vegetation greenness during the 2015/16 El Niño in tropical Asia. We found a strong green‐up during the 2015/16 El Niño in tropical Asia, with its regional average LAI stronger than that of tropical America. The drivers for the green‐up vary across the region, with radiation being the main driver for continental tropical Asia, and temperature and soil water anomalies in the west and east parts of maritime tropical Asia, respectively. These findings provide important insights into the response of tropical Asia's vegetation to extreme climate anomalies. Plain Language Summary: El Niño is a climate pattern that is associated with warm and dry conditions in tropical forest regions. Significant climatic changes during El Niño thus affect vegetation greenness (i.e., growth, size of canopy, amount of leaves). While an increase in vegetation greenness has been reported in tropical America during El Niño, it remains unclear how vegetation in tropical Asia changes during the period. Here, we used satellite data to investigate changes in vegetation greenness during El Niño in 2015–2016 in tropical Asia. We found a strong increase in vegetation greenness in tropical Asia during this period. The cause of this increase in greenness varied across different parts of tropical Asia. In mainland tropical Asia, sunlight was the main driver, while in maritime Southeast Asia, temperature or soil moisture was the main driver. These findings help provide better understanding of how vegetation in tropical Asia responds to extreme climate events like El Niño. Key Points: Tropical Asia experienced strong green‐up during the 2015/16 El Niño, stronger than that of tropical AmericaIn continental tropical Asia, green‐up was mostly driven by anomalously high shortwave radiationIn maritime tropical Asia, green‐up was primarily driven either by anomalously warmer temperatures or drier soil moisture from the west to east [ABSTRACT FROM AUTHOR]

Recent observations suggest that El Niño–Southern Oscillation (ENSO) impacts basal melting of West Antarctic ice shelves, yet sparse ocean observations limit our understanding of the associated processes. Here we investigate how ENSO events modulate subsurface West Antarctic shelf temperatures using high‐resolution global ocean‐sea ice model simulations. During El Niño, the subsurface shelf warming between 150 m and the shelf bottom can be up to 0.5°C in front of ice shelves. This warming arises from a weaker Amundsen Sea Low (ASL) and weaker coastal easterlies that reduce on‐shelf Ekman transport of cold surface waters, enabling enhanced transport of warm Circumpolar Deep Water (CDW) onto the shelf. A largely opposite response occurs during La Niña, with a stronger ASL and stronger Ekman transport that results in less cross‐shelf CDW transport and cooling in the subsurface. These findings have implications for interpreting basal melting on interannual to decadal time‐scales in West Antarctica. Plain Language Summary: El Niño‐Southern Oscillation (ENSO) is the Earth's dominant year‐to‐year climate variation. The impacts of its two phases, El Niño and La Niña, extend from the tropics to Antarctica through atmospheric waves. Past studies have suggested that West Antarctic ice shelves melt more during El Niño because of warmer ocean waters at the ice shelf bases. However, oceanic changes during El Niño lead to warming on the shelf near the ice which is difficult to isolate. That is because ENSO is only one of many drivers that impact shelf water temperatures. In this work, we simulate isolated ENSO events using an ocean circulation model. We show that during El Niño, the on‐shelf flow of cold surface waters in West Antarctica, driven by coastal easterly winds, is reduced because the winds weaken. To balance out this mass deficit at the surface, more warm CDW flows onto the continental shelf below. During La Niña, we see a largely opposite response. Stronger coastal easterlies increase the on‐shelf flow of cold surface waters and less CDW is flowing onto the shelf. Our results show the link between ENSO and mass loss of the West Antarctic ice shelves and ice sheet. Key Points: Ocean‐sea ice model simulations of El Niño and La Niña events illustrate how they modulate West Antarctic shelf temperaturesEl Niño weakens coastal easterlies, reduces on‐shelf Ekman flow of cold waters, increasing cross‐shelf flow of warm Circumpolar Deep Water (CDW)The La Niña shelf circulation response is largely opposite and reduces cross‐shelf transport of warm CDW [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]

Coastal waters often experience enhanced ocean acidification due to the combined effects of climate change and regional biological and anthropogenic activities. Through reconstructing summertime bottom pH in the northern Gulf of Mexico from 1986 to 2019, we demonstrated that eutrophication‐fueled respiration dominated bottom pH changes on intra‐seasonal and interannual timescales, resulting in recurring acidification coinciding with hypoxia. However, the multi‐decadal acidification trend was principally driven by rising atmospheric CO2 and ocean warming, with more acidified and less buffered hypoxic waters exhibiting a higher rate of pH decline (−0.0023 yr−1) compared to non‐hypoxic waters (−0.014 yr−1). The cumulative effect of climate‐driven decrease in pH baseline is projected to become more significant over time, while the potential eutrophication‐induced seasonal exacerbation of acidification may lessen with decreasing oxygen availability resulting from ocean warming. Mitigating coastal acidification requires both global reduction in CO2 emissions and regional management of riverine nutrient loads. Plain Language Summary: The northern Gulf of Mexico is an ecologically and economically vital coastal system facing acidification threats from both climate change and eutrophication (excess nutrients). The first robust multi‐decadal pH reconstruction from 1986 to 2019 revealed recurring summer bottom acidification in the Gulf's oxygen‐depleted "dead zone." These seasonal acidification and year‐to‐year differences were driven predominantly by respiration intensified by eutrophication. However, over multi‐decadal timescale, rising atmospheric CO2 and ocean warming emerged as the dominant acidification drivers. More severe acidification occurred in the "dead zone" each summer, and these waters were acidifying more rapidly over decades. Looking ahead, climate‐driven pH decline is projected to become more pronounced over time, while potential eutrophication impacts may lessen as warming reduces oxygen availability. Mitigating acidification requires global actions to curb CO2 emissions for slowing long‐term trends, as well as regional nutrient management for restraining seasonal intensification of acidification in nutrient‐rich coastal ecosystems. Key Points: We reconstructed summertime bottom acidification history (1986–2019) in the northern Gulf of Mexico and predicted future trends toward 2100Rising atmospheric CO2 and ocean warming drive decadal decline in pH baseline while eutrophication exacerbates summer acidificationLess buffered hypoxic bottom waters showed a higher decadal acidification rate (−0.0023 yr−1) than non‐hypoxic waters (−0.014 yr−1) [ABSTRACT FROM AUTHOR]

Drought has affected much of the western United States since about the year 2000, including the Upper Colorado River Basin (UCRB). Using a time series of UCRB streamflow derived from a tree‐ring based reconstruction of UCRB streamflow for the years 1 CE through 1905 CE, together with naturalized UCRB streamflow values for 1906 CE through 2021 CE, we identify 51 drought events, including the 2000–2021 drought. Although the recent 2000–2021 drought has been relatively severe, it is not the most severe of the UCRB drought events we identified. Results also indicate that natural variability combined with projected climate warming can result in UCRB drought events that are more severe than any drought since 1 CE. Plain Language Summary: A long and severe drought has affected much of the western United States since about the year 2000 CE, including the Upper Colorado River Basin (UCRB). Comparing this drought to past UCRB droughts (during 1 CE through 2021 CE), we find that the 2000–2021 drought is not the most severe UCRB drought. The results also suggest that natural variability combined with projected climate warming could result in UCRB drought events that are more severe than any drought since 1 CE. Key Points: We identify 51 drought events for the years 1 CE through 2021 CE for the Upper Colorado River Basin (UCRB)Twelve of the 51 UCRB droughts we identify were more severe than the 2000–2021 droughtNatural variability and/or a 1°C temperature increase can trigger UCRB droughts that are more severe than the 2000–2021 drought [ABSTRACT FROM AUTHOR]

As sea ice disappears, the emergence of open ocean deep convection in the Arctic, which would enhance ice loss, has been suggested. Here, using 36 state‐of‐the‐art climate models and up to 50 ensemble members per model, we show that Arctic deep convection is rare under the strongest warming scenario. Only five models have convection by 2100, while 11 have had convection by the middle of the run. For all, the deepest mixed layers are in the eastern Eurasian basin. When that region undergoes a salinification and increasing wind speeds, the models convect; yet most models are freshening. The models that do not convect have the strongest halocline and most stable sea ice, but those that lose their ice earliest ‐because of their strongly warming Atlantic Water‐ do not have a persistent deep convection: it shuts down mid‐century. Halocline and Atlantic Water changes urgently need to be better constrained in models. Plain Language Summary: Both observations and modeling simulations suggest that deep vertical mixing (or deep convection) in winter may become the new normal in the Arctic as sea ice disappears, which further accelerates that disappearance. These simulations are often done using only one model, so here we used all models available that participated in the Climate Model Intercomparison Project Phase 6 (CMIP6), for the strongest warming scenario. We show that after removing those that are already inaccurate in the present, and even with a restrictive threshold, most models have no deep convection in the Arctic, or extremely rarely. Only five still had deep convection by the time the run finishes in 2100. We found that deep convection regions and periods are associated with a saltier, windier surface, while the rest of the Arctic and/or run freshens. The subsurface properties were crucial too: a deep halocline, that is, strongly stratified model, leads to less ice loss and no deep convection. In contrast, models with a shallow halocline and strongly warming Atlantic Water lose their ice and convect earliest, although it does not persist. As water mass properties are poorly represented in CMIP6 models, these need improving to better constrain Arctic deep convection and sea ice projections. Key Points: Oceanic deep convection does not emerge and persist in the Arctic in the majority of Climate Model Intercomparison Project Phase 6 models, despite a drop in the Nordic SeasArctic deep convection occurs only when both surface salinity and winds are increasing, year round, yet most models are fresheningA deep halocline and stable ice cover hinder deep convection, while early ice loss due to warmer Atlantific water can also stop it rapidly [ABSTRACT FROM AUTHOR]

Preparing for climate change requires an understanding of the degree to which global warming has regional implications. Here we document a strong relationship between the magnitude and extent of warming and explain its origin using a simple model based on binomial statistics. Applied to HadCRUT5 instrumental observations, the model shows that 96% of interannual variability in the proportion of regions experiencing anomalous warmth over the last century can be explained on the basis of the magnitude of global mean surface temperature (GMST) anomalies. The model performs similarly well when applied to a variety of unforced and forced model simulations and represents a general thermodynamic link between global and local warming on annual timescales. Our model predicts that, independent of the baseline that is chosen, 95% of the globe is expected to experience above‐average annual temperatures at 0.7°C of GMST warming, and 99% at 1.0°C of warming. Plain Language Summary: Whereas many studies focus on global mean surface temperature (GMST), it is also critical to understand the spatial patterns of this warming in preparing for a warmer world. Using a simple statistical model, we describe a strong relationship between GMST and the spatial extent of above‐average temperature anomalies each year. This relationship is shown to hold across various model simulations and historical temperature data, capturing both annual and decadal trends. We can use our model alongside projections to gain insight into the extent of warming variations. For instance, 1°C GMST warming from a given baseline climate generally corresponds to a world in which 99% of places across the globe will be anomalously warm every year. Key Points: A simple statistical model relates the proportion of Earth's area that is anomalously warm to global mean surface temperature (GMST)The model predicts 96% of the interannual variance in the proportion of anomalous warmth between 1900 and 2021 on the basis of GMST1.0°C of GMST warming corresponds to 99% of the globe being anomalously warm, independent of baseline [ABSTRACT FROM AUTHOR]

Each year, the biological carbon pump (BCP) transports large quantities of carbon from the ocean surface to the interior. The efficiency of this transfer varies geographically, and is a key determinant of the atmosphere‐ocean carbon dioxide balance. Traditionally, the attention has been focused on explaining perceived geographical variations in this transfer efficiency (TE) in an attempt to understand it, an approach that has led to conflicting results. Here we combine observations and modeling to show that the spatial variability in TE can instead be explained by the seasonal variability in carbon flux attenuation. We also show that seasonality can explain the contrast between known global estimates of TE, due to differences in the date and duration of sampling. Our results suggest caution in the mechanistic interpretation of annual‐mean patterns in TE and demonstrates that seasonally and spatially resolved data sets and models might be required to generate accurate evaluations of the BCP. Plain Language Summary: Each year, marine phytoplankton convert carbon dioxide into millions of tonnes of organic carbon with a fraction of it reaching the deep ocean, where it can remain for hundreds of years. The efficiency of this surface‐to‐depth carbon transfer is therefore a key determinant of the atmosphere‐ocean carbon dioxide balance. However, the variability of this transfer efficiency (TE) and its underlying causes are poorly understood, to the extent that different studies report contradicting results. We show that the existence of seasonal variability in the attenuation of sinking carbon particles can explain the observed spatial variability in annual TE and reconcile with the literature. Our findings suggest caution in interpreting results from sparse but time‐varying data sets, highlighting that seasonal variability should be considered when studying the oceanic carbon cycle. Key Points: Spatial variability in carbon transfer efficiency (TE) can be generated solely by the seasonality of flux attenuation informed by observationsSeasonality in flux attenuation can reconcile contrasting TE maps reported in the literatureResolving and understanding seasonality are key for an accurate evaluation of the biological carbon pump under climate change [ABSTRACT FROM AUTHOR]