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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]

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 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]

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]

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]

This study presents a methodological advancement in the field of clumped‐isotope (∆47) thermometry, specifically tailored for application to freshwater ostracods. The novel ostracod clumped isotope approach enables quantitative temperature and hydrological reconstruction in lacustrine records. The relationship between ∆47 and the temperature at which ostracod shell mineralized is determined by measuring ∆47 on different species grown under controlled temperatures, ranging from 4 ± 0.8 to 23 ± 0.5ºC. The excellent agreement between the presented ∆47 ostracod data and the monitored temperatures confirms that ∆47 can be applied to ostracod shells and that a vital effect is absent outside the uncertainty of measurements. Results are consistent with the carbonate clumped‐isotope unified calibration (Anderson et al., 2021, https://doi.org/10.1029/2020gl092069), therefore, an ostracod‐specific calibration is not needed. The ostracod clumped‐isotope thermometer represents a powerful tool for terrestrial paleoclimate studies all around the world, as lakes and ostracods are found in all climatic belts. Plain Language Summary: In the framework of global warming, the reconstruction of past climatic conditions is important to understand the future evolution of climate and its impact. Lake sediments can be used as archives to quantify these effects. This study presents a novel paleo‐thermometer based on the application of clumped‐isotope technique (i.e., measurement of the number of 13C–18O bonds in carbonate minerals that depends on the temperature of carbonate precipitation) on carbonatic microcrustacea, named ostracods that commonly live in lakes. By using ostracods that formed their shells at known temperatures, we demonstrate that they can be easily used to reconstruct water temperature and hydrological conditions (precipitation/evaporation). The ostracod clumped‐isotope thermometer represents a powerful tool for terrestrial paleoclimate studies around the world, as lakes and ostracods are located in all climatic belts. Key Points: ∆47—ostracod signal accurately records the shell calcification temperature∆47—ostracod signal is not affected by the so called "vital effect"The unified calibration of Anderson et al. (2021) can be used to convert the ∆47—ostracod signal into accurate temperatures [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]

Accurately representing the ocean carbon cycle in Earth System Models (ESMs) is essential to understanding the oceanic CO2 sink evolution under CO2 emissions and global warming. A key uncertainty arises from the ESM's inability to explicitly represent mesoscale eddies. To address this limitation, we conduct eddy‐resolving experiments of CO2 uptake under global warming in an idealized mid‐latitude ocean model. In comparison with similar experiments at coarser resolution, we show that the CO2 sink is 34% larger in the eddy‐resolving experiments. 80% of the increase stems from a more efficient anthropogenic CO2 uptake due to a stronger Meridional Overturning circulation (MOC). The remainder results from a weaker reduction in CO2 uptake associated to a weaker MOC decline under global warming. Although being only a fraction of the overall response to climate change, these results emphasize the importance of an accurate representation of small‐scale ocean processes to better constrain the CO2 sink. Plain Language Summary: Today, the ocean absorbs ∼25% of the CO2 emissions caused by human activities. This CO2 sink is primarily driven by the increase of CO2 in the atmosphere, but it is also influenced by physical changes in the ocean's properties. Earth System Models are used to project the future of the ocean CO2 sink. Due to limited computational capacity, ESMs need to parameterize flows occurring at scales smaller than ∼100 km, their typical horizontal grid resolution. To overcome the computational limitations, we use an ocean biogeochemical model representing an idealized North Atlantic ocean of reduced dimensions. We conduct simulations of global warming using increasingly finer horizontal resolutions (from ∼100 km to ∼4 km). Our findings demonstrate that the ocean CO2 uptake is highly influenced by resolution. This sensitivity primarily stems from how the overturning circulation's mean state depends on resolution, as well as how it responds to global warming. Although our results capture only a fraction of the overall oceanic response to climate change, they emphasize the significance of accurately representing the role of small‐scale ocean processes to better constrain the future evolution of ocean carbon uptake. Key Points: We conducted idealized ocean simulations under global warming and rising atmospheric CO2 at coarse and eddy‐resolving resolutionsCO2 sink is larger by 34% at eddy resolution, due to larger anthropogenic CO2 uptake combined with weaker climate feedbackThis ensues from the model's overturning circulation sensitivity to resolution in both historical and future state [ABSTRACT FROM AUTHOR]

In a rapidly changing Arctic, multiple lines of evidence suggest that bowhead whale migration is changing. To explore these changes further, we used passive acoustic data to examine bowhead whale presence in the western Beaufort Sea (12 years) and Chukchi Plateau (11 years) spanning 2008 to 2022. Departure from the western Beaufort Sea shifted 45 days later over the 12‐year period. Summer presence increased at both sites, suggesting feeding areas within the Chukchi Sea are becoming more favorable. Likewise, findings from the Bering Strait suggest that some whales are remaining north of the Bering Strait for the winter instead of in the Bering Sea. These Pacific Arctic‐wide changes to migration have occurred over only one decade. Questions remain about prey availability in the Chukchi Sea, implications of migratory changes, such as a northward shift in the core overwintering area, and impact to communities south of the Bering Strait. Plain Language Summary: Bowhead whales are an important top predator in the Pacific Arctic. With increasing temperatures and decreasing sea ice, changes are occurring in the migration patterns of this "ecosystem sentinel" throughout the Pacific Arctic. We analyzed passive acoustic data from the western Beaufort Sea and Chukchi Plateau from 2008 to 2022. Whales are delaying their fall departure from the western Beaufort Sea and spending more time in the western Beaufort Sea and Chukchi Plateau, which, along with increased habitat use on the Chukchi Shelf, suggests that conditions there are becoming more favorable for feeding. Combined with previous data from the Bering Strait, which showed that some whales are spending winter in the southern Chukchi Sea rather than in the northern Bering Sea, these findings suggests that changes are occurring over a short period of time throughout the Pacific Arctic. A northward shift could put bowhead whales in the direct path of ships, especially along the western side of the Chukchi Sea, and impact whaling communities south of the Bering Strait. Key Points: Acoustic data reinforce known delay in bowhead fall departure from the western Beaufort Sea and overwintering in the southern Chukchi SeaIncreased presence in the western Beaufort Sea and Chukchi Plateau suggests these regions are becoming more favorable for bowhead feedingWhales are adapting to a rapidly changing Arctic, but changes and emerging threats may impact them and communities south of Bering Strait [ABSTRACT FROM AUTHOR]

The influence of climate feedbacks on regional hydrological changes under warming is poorly understood. Here, a moist energy balance model (MEBM) with a Hadley Cell parameterization is used to isolate the influence of climate feedbacks on changes in zonal‐mean precipitation‐minus‐evaporation (P − E) under greenhouse‐gas forcing. It is shown that cloud feedbacks act to narrow bands of tropical P − E and increase P − E in the deep tropics. The surface‐albedo feedback shifts the location of maximum tropical P − E and increases P − E in the polar regions. The intermodel spread in the P − E changes associated with feedbacks arises mainly from cloud feedbacks, with the lapse‐rate and surface‐albedo feedbacks playing important roles in the polar regions. The P − E change associated with cloud feedback locking in the MEBM is similar to that of a climate model with inactive cloud feedbacks. This work highlights the unique role that climate feedbacks play in causing deviations from the "wet‐gets‐wetter, dry‐gets‐drier" paradigm. Plain Language Summary: Climate feedbacks, which act to amplify or dampen global warming, play an important role in shaping how the climate system responds to changes in greenhouse‐gas concentrations. Here, we use an idealized climate model, which makes a simplified assumption about how energy is transported in the atmosphere, to examine how climate feedbacks influence the patterns of precipitation and evaporation change under global warming. We find that the cloud feedback acts to narrow the band of rainfall on the equator known as the Intertropical Convergence Zone and that the surface‐albedo feedback acts to shift the location of maximum rainfall. We also find that the cloud feedback accounts for most of the uncertainty associated with feedbacks in regional hydrological change under warming. The idealized model with a locked cloud feedback also simulates a change in precipitation and evaporation that is similar to a comprehensive climate model with an inactive cloud feedback. Key Points: A moist energy balance model (MEBM) is used to investigate the influence of climate feedbacks on regional hydrological changes under warmingCloud feedbacks act to narrow and increase tropical P − E and are the dominant source of feedback uncertainty in regional hydrological changesThe MEBM with a locked cloud feedback largely replicates a climate model with an inactive cloud feedback [ABSTRACT FROM AUTHOR]

Future climate projections suggest a poleward shift of the maximum intensity of tropical cyclones (TCs) over the western North Pacific. However, the global nature of the latitudinal change in TC genesis under global warming remains poorly understood. We show, using large‐ensemble high‐resolution atmospheric model simulations (d4PDF) with four warming scenarios, that the poleward shift is a robust change over the globe, attributable to the weakening of the Hadley circulation. The weakened ascent driven by the upper‐tropospheric warming suppresses the TC genesis within 5°–20° latitudes, whereas the weakened descent enhances the TC genesis in the poleward latitudes. We further estimate the poleward shift of TC genesis to emerge at the 2 K global warming over the Arabian Sea, South Atlantic and Pacific Oceans and at the 4 K warming over the North Pacific. The present results underscore the potential for increasing social and economic risks associated with TCs at higher latitudes. Plain Language Summary: Climate models have projected a decrease in TC genesis frequency in future warming. However, the global nature of the latitudinal change in TC genesis under global warming remains uncertain partly due to insufficient resolution as well as the ensemble size of climate model simulations. We show a global feature of the robust poleward shift of the TC genesis during the active seasons of both hemispheres scaled with the global warming level, which can be attributed to the weakening of the Hadley circulation. The weakened ascending branch of the Hadley circulation, driven by the increased upper tropospheric warming, potentially hinders TC genesis within 5°–20° latitudes. Conversely, the weakened descending branch of the Hadley circulation enhances the likelihood of TC genesis within 20°–35° latitudes. We further estimate that the signal of TC genesis is expected to emerge over high latitudes of the Arabian Sea, South Atlantic and South Pacific Oceans at the 2 K warming and at the 4 K warming over the North Pacific. The present analyses have significant implications not only for assessing the reliability of future TC‐related changes in climate models but also for estimating the increased TC‐related hazards at higher latitudes under global warming. Key Points: We project a global feature of the robust poleward shift of tropical cyclone (TC) genesis during active seasons of both hemispheresMore TC genesis at high latitudes can be attributed to the weakening of the Hadley circulationPoleward shift of TC genesis emerges at 2 K warming over Arabian Sea, South Atlantic and Pacific Oceans and at 4 K warming over North Pacific [ABSTRACT FROM AUTHOR]

The temporal relationship between global glaciations and the Great Oxidation Event (GOE) suggests that climate change played an important role in Earth's oxygenation. The potential role of temperature is captured by the stratigraphic proximity between glacial deposits and sediments containing mass‐independent fractionation of sulfur isotopes (MIF‐S). We use a time‐dependent one‐dimensional photochemical model to investigate whether temperature changes associated with global glaciations can drive oscillations in atmospheric O2 levels and MIF‐S production across the GOE. We find that extreme climate change can cause atmospheric O2 to oscillate between pre (<10−6 times the present atmospheric level, PAL) and post‐GOE (>10−5 PAL) levels. Post‐glacial hot‐moist greenhouse climates lead to post‐GOE O2 levels because the abundant H2O vapor and oxidizing radicals drive the depletion of reduced species. This pattern is generally consistent with the MIF‐S signal observed in the sedimentary record, suggesting a link between global glaciations and O2 oscillations across the GOE. Plain Language Summary: The Great Oxidation Event was the most significant environmental and chemical transformation in Earth's history, marking the first time oxygen accumulated in the atmosphere around 2.4 billion years ago. Oxygen increased from below one millionth (low) to at least one‐thousandth of a percent (intermediate) of the present oxygen concentration during this event. However, measurements of geochemical oxygen proxies suggest that oxygen levels oscillated between low and intermediate levels before stabilizing after this event. The first rise of atmospheric oxygen occurred during a period of extreme climate variability indicated by the presence of glacial rock deposits around this time. In this study, we use a time‐dependent photochemical model to show that extreme temperature changes caused by global glaciations can drive oscillations in atmospheric oxygen levels across the Great Oxidation Event (GOE). Our results can help explain why atmospheric oxygen shows drastic changes across the GOE in a way that is consistent with the geochemical record. Key Points: Across the Great Oxidation Event (GOE), extreme climate change linked to global glaciations can drive oscillations in atmospheric O2 levels and mass‐independent fractionation of sulfur isotopes (MIF‐S) productionGlacial climates and hot‐moist greenhouse climates were likely characterized by pre‐GOE and post‐GOE O2 levels respectivelyTemperature changes associated with global glaciations can help explain the MIF‐S record across the GOE [ABSTRACT FROM AUTHOR]

Based on outputs of 28 coupled models from the Phase 6 of the Coupled Model Intercomparison Project (CMIP6), we show that the response of the Southeast Asian summer monsoon to the El Niño‐Southern Oscillation (ENSO) during post‐ENSO summer will likely strengthen in a warmer climate, which can be attributed to concurrently weakened sea‐surface temperature anomalies (SSTAs) in the western equatorial Pacific (WEP). The weakened WEP SSTAs are primarily caused by enhanced latent heat damping due to increased surface wind speed anomalies, which are associated with the eastward shift of the El Niño‐induced anomalous Walker circulation due to El Niño‐like sea surface temperature change in the tropical Pacific under global warming. Besides, the climatological zonal ocean currents will slow down due to the weakening of climatological Walker circulation, which also acts to weaken the WEP SSTAs via reducing the advection of anomalous temperature by the mean current. Plain Language Summary: As an important component of the Asian monsoon system, the Southeast Asian summer monsoon (SEASM) is crucial for the livelihoods of billions of people in East Asia, and is closely connected to a climate phenomenon called El Niño‐Southern Oscillation (ENSO). Understanding how the relationship between SEASM and ENSO will change in the future is important for enhancing our knowledge of climate change in East Asia. Outputs of 28 climate models from the Phase 6 of the Coupled Model Intercomparison Project show that ENSO will exert enhanced impacts on the SEASM in a warmer climate. The enhanced influences of ENSO on the monsoon will exacerbate the reduction of rainfall over the western North Pacific during the post‐El Niño summer. We find that such projected changes are mainly caused by weakened warm sea surface temperature (SST) anomalies (SSTAs) in the western equatorial Pacific (WEP). Further analyses indicate that the change in WEP SSTAs can be linked to the El Niño‐like change in climatological SSTs in the tropical Pacific. This study depicts detailed physical processes responsible for the projected changes in ENSO's impacts on the SEASM. Key Points: The effects of the El Niño‐Southern Oscillation on the Southeast Asian summer monsoon will strengthen under global warmingThe enhanced El Niño's impacts result from the weakened warm sea‐surface temperature (SST) anomalies in the western equatorial Pacific (WEP)The weakened WEP SST anomalies are related to the eastward shift of anomalous Walker circulation and the slackened mean zonal ocean currents [ABSTRACT FROM AUTHOR]

Global warming and climate change have increased the frequency and intensity of floods and droughts, limiting economic development and threatening human survival. Therefore, accurate global forecasts well in advance of precipitation are essential to facilitate timely adaptation. Current seasonal forecasts are based mainly on numerical models, but raw forecasts suffer from systematic bias and under/overdispersion problems and cannot be directly used in applications. In addition, bias correction methods for global forecasts need to be further developed. Based on a fusion of ResNet34 and Unet, called Res34‐Unet, deep learning post‐processing is proposed to correct global precipitation forecasts of the North American Multi‐Model Ensemble (NMME). Compared with raw global NMME predictions, post‐processed precipitation predictions can be improved by up to 45%, which is significant at different latitudes. Feature importance analysis shows that precipitation itself, meridional wind, and sea surface temperature are key factors. Plain Language Summary: Under the influence of global warming, extreme events, especially floods and droughts, are becoming more frequent, severely limiting social and economic development and greatly affecting people's lives. Therefore, accurate global forecasts are crucial to help people adaptively respond as soon as possible. Currently, seasonal forecasts are based mainly on numerical models. The North American Multi‐Model Ensemble (NMME) is one of the most advanced multi‐model ensemble systems for intra‐seasonal to interannual global prediction. However, due to deficiencies in numerical weather prediction models and inaccurate initial conditions, raw model predictions still have a large bias compared to observations. Therefore, accurate and efficient post‐processing algorithms are essential. Traditional post‐processing algorithms have some disadvantages such as the assumption of linearity, and spatial and temporal inconsistency. In addition, most post‐processing work has a regional focus, and more research focusing on global post‐processing prediction is needed to reduce global losses from extreme events. With the rapid development of machine learning, artificial intelligence is an effective tool to improve post‐processing. The fusion of ResNet34 and Unet, called Res34‐Unet, is proposed to post‐process global NMME rainfall predictions. Compared with raw NMME predictions, post‐processed predictions can be improved by up to 45%, which is significant at different latitudes. Key Points: Accurate global seasonal precipitation prediction is essential, but the bias of raw model predictions is largeRes34‐Unet post‐processing provides accurate seasonal precipitation prediction and outperforms Unet post‐processingRes34‐Unet post‐processing can improve predictions by up to 45%, which is significant at different latitudes [ABSTRACT FROM AUTHOR]

Pinatubo erupted during the first decadal survey of ocean biogeochemistry, embedding its climate fingerprint into foundational ocean biogeochemical observations and complicating the interpretation of long‐term biogeochemical change. Here, we quantify the influence of the Pinatubo climate perturbation on externally forced decadal and multi‐decadal changes in key ocean biogeochemical quantities using a large ensemble simulation of the Community Earth System Model designed to isolate the effects of Pinatubo, which cleanly captures the ocean biogeochemical response to the eruption. We find increased uptake of apparent oxygen utilization and preindustrial carbon over 1993–2003. Nearly 100% of the forced response in these quantities are attributable to Pinatubo. The eruption caused enhanced ventilation of the North Atlantic, as evidenced by deep ocean chlorofluorocarbon changes that appear 10–15 years after the eruption. Our results help contextualize observed change and contribute to improved constraints on uncertainty in the global carbon budget and ocean deoxygenation. Plain Language Summary: Oceanographers' understanding of ocean properties comes from research cruises that take scientific measurements in the same locations every ten years. However, the first of these research cruises were deployed just after a large volcanic eruption in 1991 called Pinatubo. The eruption cooled the planet for several years, including the upper ocean. Here, we investigate how this eruption affected ocean properties using two collections of simulations of the Community Earth System Model which is a mathematical representation of the Earth system. The first collection of simulations shows the response to the eruption, while the second collection shows how ocean properties would have changed if there had been no eruption. The difference thus tell us the influence of the eruption on ocean properties. We find an increase of oxygen and preindustrial carbon over 1993–2003 due to Pinatubo, as well as an increase of ventilation of the North Atlantic that appears years after the eruption. Key Points: Using a large ensemble model, we quantify the impact of Pinatubo on observed, externally forced decadal changes in ocean biogeochemistryNearly 100% of forced changes in apparent oxygen utilization and preindustrial carbon over 1993–2003 are attributable to PinatuboImpacts of Pinatubo last several decades, affecting interpretation of anthropogenic changes from physical and biogeochemical observations [ABSTRACT FROM AUTHOR]

Climate variability over the Tropical and North Pacific Ocean (TPO and NPO, respectively) modulates marginal sea variability. The South China Sea (SCS), the largest marginal sea in the western NPO, is an outstanding example of a region that responds quickly to climate change. However, there is considerable uncertainty regarding the response of the deep SCS to large‐scale climate variability. Multivariate empirical orthogonal function analysis revealed three prominent modes of interconnected temperature anomaly fluctuations within the TPO and NPO. These coherent modes highlight the interactive dynamics among climate variations and reveal their modulation mechanisms for previously less explored potential temperature variabilities in the deep SCS. On the atmospheric bridge, external forces modify the upper‐layer Luzon Strait Transport (LST) by adjusting the Ekman transport and Kuroshio intrusion. For the oceanic pathway, climate variations disturb the deep‐layer LST by adjusting the barotropic flows in the upper layer. Plain Language Summary: This study utilizes multivariate empirical orthogonal function analysis to examine long‐term hydrographic observations and identify coherent variations in surface temperature anomalies in the Tropical and North Pacific Ocean. The leading mode displays in‐phase combinations of the East Pacific El Niño and warm Pacific Decadal Oscillation. The second mode displays a Central Pacific El Niño and North Pacific Meridional Mode‐like mode. The third mode resembles a Central Pacific El Niño and Victoria Mode‐like mode. The objective is to comprehend the synergies between the climatic variabilities in the Tropical and North Pacific Ocean, as well as the processes by which the predominant climate variabilities regulate the undocumented potential temperature variabilities in the deep South China Sea. Extrinsic forcings in the Tropical and North Pacific Ocean regulate the interannual–decadal temperature variabilities by modulating the Luzon Strait Transport. On the atmospheric bridge, these extrinsic forcings affect the upper‐layer Luzon Strait Transport by altering the local Ekman transport and Kuroshio intrusion associated with the bifurcation of the North Equatorial Current. On the oceanic pathway, climate variabilities disturb the deep‐layer Luzon Strait Transport by changing the ocean bottom pressure between the two sides of the Luzon Strait. Key Points: Coherent climate variabilities in the Tropical and North Pacific Ocean are obtained through MVEOF analysisPotential temperature observations from the deep South China Sea indicate interannual–decadal variabilityClimate variabilities affect deep temperature variability through the changing atmospheric bridge and oceanic pathway [ABSTRACT FROM AUTHOR]