Severe cold-water bleaching of a deep-water reef underscores future challenges for Mesophotic Coral Ecosystems

Elevated sea surface temperatures are causing an increase in coral bleaching events worldwide, and represent an existential threat to coral reefs. Early studies of Mesophotic Coral Ecosystems (MCEs) highlighted their potential as thermal refuges for shallow-water coral species in the face of predicted 21st century warming. However, recent genetic evidence implies that limited ecological connectivity between shallow- and deep-water coral communities inhibits their effectiveness as refugia; instead MCEs host distinct endemic communities that are ecologically significant in and of themselves. In either scenario, understanding the response of MCEs to climate change is critical given their ecological significance and widespread global distribution. Such an understanding has so far eluded the community, however, because of the challenges associated with long-term field monitoring, the stochastic nature of climatic events that drive bleaching, and the paucity of deep-water observations. Here we document the first observed cold-water bleaching of a mesophotic coral reef at Clipperton Atoll, a remote Eastern Tropical Pacific (ETP) atoll with high coral cover and a well-developed MCE. The severe bleaching (>70 % partially or fully bleached coral cover at 32 m depth) was driven by an anomalously shallow thermocline, and highlights a significant and previously unreported challenge for MCEs. Prompted by these observations, we compiled published cold-water bleaching events for the ETP, and demonstrate that the timing of past cold-water bleaching events in the ETP coincides with decadal oscillations in mean zonal wind strength and thermocline depth. The latter observation suggests any future intensification of easterly winds in the Pacific could be a significant concern for its MCEs. Our observations, in combination with recent reports of warm-water bleaching of Red Sea and Indian Ocean MCEs, highlight that 21st century MCEs in the Eastern Pacific face a two-pronged challenge: warm-water bleaching from above, and cold-water bleaching from below.

Unraveling the role of the western North Pacific circulation anomaly in modulating Indian summer monsoon rainfall variability beyond ENSO

The Indian summer monsoon (ISM) rainfall interannual variability is known to be strongly linked to the El-Niño-Southern Oscillation (ENSO). This linear relationship is the primary factor in controlling the interannual variation in ISM precipitation. However, there are many outlier cases, and such deviations pose significant challenges in seasonal prediction over this region. Here we show that such challenges can be attributed to anomalous atmospheric pressure patterns in the Western North Pacific (WNP) region. The anticyclonic circulation anomaly over WNP region causes the easterly wind toward the Indian subcontinent, leading to positive precipitation anomalies with stronger low-level moist convergence, while the cyclonic circulation decreases ISM precipitation. The linear baroclinic model simulation results further support that the WNP circulation pattern can serve as an independent factor for forecasting precipitation over India. The WNP circulation anomaly play the crucial role generating ISM precipitation particularly for July and September. Our study suggests that the role of the WNP circulation anomaly should be carefully considered as the secondary prevailing mechanism on the subseasonal timescale during the boreal summer in addition to the ENSO signal.

A climate change signal in the tropical Pacific emerges from decadal variability

The eastern tropical Pacific has defied the global warming trend. There has been a debate about whether this observed trend is forced or natural (i.e., the Interdecadal Pacific Oscillation; IPO) and this study shows that there are two patterns, one that oscillates along with the IPO, and one that is emerging since the mid-1950s, herein called the Pacific Climate Change (PCC) pattern. Here we show these have distinctive and distinguishable atmosphere-ocean signatures. While the IPO features a meridionally broad wedge-shaped SST pattern, the PCC pattern is marked by a narrow equatorial cooling band. These different SST patterns are related to distinct wind-driven ocean dynamical processes. We further show that the recent trends during the satellite era are a combination of IPO and PCC. Our findings set a path to distinguish climate change signals from internal variability through the underlying dynamics of each.

Exploring Drivers of Historic Mercury Trends in Beluga Whales Using an Ecosystem Modeling Approach

While mercury occurs naturally in the environment, human activity has significantly disturbed its biogeochemical cycle. Inorganic mercury entering aquatic systems can be transformed into methylmercury, a strong neurotoxicant that builds up in organisms and affects ecosystem and public health. In the Arctic, top predators such as beluga whales, an ecologically and culturally significant species for many Inuit communities, can contain high concentrations of methylmercury. Historical mercury concentrations in beluga in the western Canadian Arctic's Beaufort Sea cannot be explained by mercury emission trends alone; in addition, they could potentially be driven by climate change impacts, such as rising temperatures and sea ice melt. These changes can affect mercury bioaccumulation through different pathways, including ecological and mercury transport processes. In this study, we explore key drivers of mercury bioaccumulation in the Beaufort Sea beluga population using Ecopath with Ecosim, an ecosystem modeling approach, and scenarios of environmental change informed by Western Science and Inuvialuit Knowledge. Comparing the effect of historical sea ice cover, sea surface temperature, and freshwater discharge time series, modeling suggests that the timing of historical increases and decreases in beluga methylmercury concentrations can be better explained by the resulting changes to ecosystem productivity rather than by those to mercury inputs and that all three environmental drivers could partially explain the decrease in mercury concentrations in beluga after the mid-1990s. This work highlights the value of multiple knowledge systems and exploratory modeling methods in understanding environmental change and contaminant cycling. Future work building on this research could inform climate change adaptation efforts and inform management decisions in the region.

Multiscale mushy layer model for Arctic marginal ice zone dynamics

Perhaps the most dynamic component of the Arctic sea ice cover is the marginal ice zone (MIZ), the transitional region between dense pack ice to the north and open ocean to the south. It widens by a factor of four while seasonally migrating more than 1600 km poleward in the Bering-Chukchi Sea sector, impacting climate dynamics, ecological processes, and human accessibility to the Arctic. Here we showcase a transformative mathematical modeling approach to understanding changes in MIZ location and width, focusing on their seasonal cycles as observed by satellites. We view the MIZ as a liquid-solid phase transition region, or mushy zone, on the scale of the Arctic Ocean. Invoking the physics of phase changes, the MIZ is modeled as a dynamic, multiscale composite material layer; this model captures 96% of the annual cycle of MIZ location and 78% of the annual cycle of MIZ width. Temperature in the upper ocean is described by a nonlinear heat equation with effective parameters obtained using homogenization theory for a random medium of ice floes in a sea water host. Observations and simulations together indicate that MIZ location closely tracks the below-ice 273 K isotherm while the width of the MIZ follows vertical heat flux convergence, but with a three-week lag.

Stock assessment models overstate sustainability of the world's fisheries

Effective fisheries management requires accurate estimates of stock biomass and trends; yet, assumptions in stock assessment models generate high levels of uncertainty and error. For 230 fisheries worldwide, we contrasted stock biomass estimates at the time of assessment with updated hindcast estimates modeled for the same year in later assessments to evaluate systematic over- or underestimation. For stocks that were overfished, low value, or located in regions with rising temperatures, historical biomass estimates were generally overstated compared with updated assessments. Moreover, rising trends reported for overfished stocks were often inaccurate. With consideration of bias identified retrospectively, 85% more stocks than currently recognized have likely collapsed below 10% of maximum historical biomass. The high uncertainty and bias in modeled stock estimates warrants much greater precaution by managers.

network-based constraint to evaluate climate sensitivity

The 2015 Paris agreement was established to limit Greenhouse gas (GHG) global warming below 1.5°C above preindustrial era values. Knowledge of climate sensitivity to GHG levels is central for formulating effective climate policies, yet its exact value is shroud in uncertainty. Climate sensitivity is quantitatively expressed in terms of Equilibrium Climate Sensitivity (ECS) and Transient Climate Response (TCR), estimating global temperature responses after an abrupt or transient doubling of CO2. Here, we represent the complex and highly-dimensional behavior of modelled climate via low-dimensional emergent networks to evaluate Climate Sensitivity (netCS), by first reconstructing meaningful components describing regional subprocesses, and secondly inferring the causal links between these to construct causal networks. We apply this methodology to Sea Surface Temperature (SST) simulations and investigate two different metrics in order to derive weighted estimates that yield likely ranges of ECS (2.35-4.81°C) and TCR (1.53-2.60°C). These ranges are narrower than the unconstrained distributions and consistent with the ranges of the IPCC AR6 estimates. More importantly, netCS demonstrates that SST patterns (at "fast" timescales) are linked to climate sensitivity; SST patterns over the historical period exclude median sensitivity but not low-sensitivity (ECS < 3.0°C) or very high sensitivity (ECS ≥ 4.5°C) models.

Lapsed El Niño impact on Atlantic and Northwest Pacific tropical cyclone activity in 2023

A typical El Niño event often results in suppressed tropical cyclone (TC) genesis frequency (TCGF) over the North Atlantic (NA) and a distinct northwest-southeast dipole pattern in TCGF anomaly over the western North Pacific (WNP). The 2023 saw a strong El Niño event but surprisingly active NA and suppressed WNP TC activities. Here, we present that these unprecedented deviations were driven by the record-warm NA, a record-breaking negative phase of the Pacific Meridional Mode (PMM), and background global warming. Results from high-resolution global model experiments demonstrate that extraordinary Atlantic warming dominated the increased NA TCGF and contributed equally with the PMM to the suppressed WNP TCGF, overshadowing El Niño's impact. Global warming also contributed to the observed TCGF anomalies. Our findings demonstrate that the typical influence of strong El Niño events on regional TC activity could be markedly altered by other climate modes, highlighting the complexity of TC genesis in a warming world.

Enhanced Atlantic Meridional Mode predictability in a high-resolution prediction system

Accurate prediction of sea surface temperatures (SSTs) in the tropical North Atlantic on multiyear timescales is of paramount importance due to its notable impact on tropical cyclone activity. Recent advances in high-resolution climate predictions have demonstrated substantial improvements in the skill of multiyear SST prediction. This study reveals a notable enhancement in high-resolution tropical North Atlantic SST prediction that stems from a more realistic representation of the Atlantic Meridional Mode and the associated wind-evaporation-SST feedback. The key to this improvement lies in the enhanced surface wind response to changes in cross-equatorial SST gradients, resulting from Intertropical Convergence Zone bias reduction when atmospheric model resolution is increased, which, in turn, amplifies the positive feedback between latent and sensible surface heat fluxes and SST anomalies. These advances in high-resolution climate prediction hold promise for extending tropical cyclone forecasts at multiyear timescales.

An unprecedented fall drought drives Dust Bowl-like losses associated with La Niña events in US wheat production

Unprecedented precipitation deficits in the 2022-2023 growing season across the primary wheat-producing region in the United States caused delays in winter wheat emergence and poor crop growth. Using an integrated approach, we quantitatively unraveled a 37% reduction in wheat production as being attributable to both per-harvested acre yield loss and severe crop abandonment, reminiscent of the Dust Bowl years in the 1930s. We used random forest machine learning and game theory analytics to show that the main driver of yield loss was spring drought, whereas fall drought dominated abandonment rates. Furthermore, results revealed, across the US winter wheat belt, the La Niña phase of the El Niño Southern Oscillation (ENSO), increased abandonment rates compared to the El Niño phase. These findings underscore the necessity of simultaneously addressing crop abandonment and yield decline to stabilize wheat production amid extreme climatic conditions and provide a holistic understanding of global-scale ENSO dynamics on wheat production.

Uncertainties too large to predict tipping times of major Earth system components from historical data

One way to warn of forthcoming critical transitions in Earth system components is using observations to detect declining system stability. It has also been suggested to extrapolate such stability changes into the future and predict tipping times. Here, we argue that the involved uncertainties are too high to robustly predict tipping times. We raise concerns regarding (i) the modeling assumptions underlying any extrapolation of historical results into the future, (ii) the representativeness of individual Earth system component time series, and (iii) the impact of uncertainties and preprocessing of used observational datasets, with focus on nonstationary observational coverage and gap filling. We explore these uncertainties in general and specifically for the example of the Atlantic Meridional Overturning Circulation. We argue that even under the assumption that a given Earth system component has an approaching tipping point, the uncertainties are too large to reliably estimate tipping times by extrapolating historical information.

Highest ocean heat in four centuries places Great Barrier Reef in danger

Mass coral bleaching on the Great Barrier Reef (GBR) in Australia between 2016 and 2024 was driven by high sea surface temperatures (SST)1. The likelihood of temperature-induced bleaching is a key determinant for the future threat status of the GBR2, but the long-term context of recent temperatures in the region is unclear. Here we show that the January-March Coral Sea heat extremes in 2024, 2017 and 2020 (in order of descending mean SST anomalies) were the warmest in 400 years, exceeding the 95th-percentile uncertainty limit of our reconstructed pre-1900 maximum. The 2016, 2004 and 2022 events were the next warmest, exceeding the 90th-percentile limit. Climate model analysis confirms that human influence on the climate system is responsible for the rapid warming in recent decades. This attribution, together with the recent ocean temperature extremes, post-1900 warming trend and observed mass coral bleaching, shows that the existential threat to the GBR ecosystem from anthropogenic climate change is now realized. Without urgent intervention, the iconic GBR is at risk of experiencing temperatures conducive to near-annual coral bleaching3, with negative consequences for biodiversity and ecosystems services. A continuation on the current trajectory would further threaten the ecological function4 and outstanding universal value5 of one of Earth's greatest natural wonders.

Drivers and impact of the 2021 extreme warm event in the tropical Angolan upwelling system

Benguela Niños are extreme warm events that typically occur during the main downwelling season (austral fall) in the tropical Angolan upwelling system when the biological productivity is low. However, the extreme warm event that occurred between April and August 2021 stands out due to its late timing. It occurred and peaked during the main upwelling season in austral winter with sea surface temperature anomalies exceeding 2 °C in the Angola-Benguela area in June 2021. This led to an unprecedented reduction of the net primary production off southern Angola. Both local atmospheric processes and remote influences (via downwelling coastal trapped wave propagations) have contributed to the onset of the extreme warm event in April and its intensification towards the peak phase in June. Moreover, the poleward advection of warm equatorial waters toward the Angola-Benguela area in May 2021 might have contributed to the warming, since the transport of the Angola Current, as estimated from observations, was notably elevated, amounting to 2.1 Sv.

Assessment of Arctic sea ice simulations in cGENIE model and projections under RCP scenarios

Simulating and predicting Arctic sea ice accurately remains an academic focus due to the complex and unclear mechanisms of Arctic sea ice variability and model biases. Meanwhile, the relevant forecasting and monitoring authorities are searching for models to meet practical needs. Given the previous ideal performance of cGENIE model in other fields and notable features, we evaluated the model's skill in simulating Arctic sea ice using multiple methods and it demonstrates great potential and combined advantages. On this basis, we examined the direct drivers of sea-ice variability and predicted the future spatio-temporal changes of Arctic sea ice using the model under different Representative Concentration Pathways (RCP) scenarios. Further studies also found that Arctic sea ice concentration shows large regional differences under RCP 8.5, while the magnitude of the reduction in Arctic sea ice thickness is generally greater compared to concentration, showing a more uniform consistency of change.

Global expansion of marine protected areas and the redistribution of fishing effort

The expansion of marine protected areas (MPAs) is a core focus of global conservation efforts, with the "30x30" initiative to protect 30% of the ocean by 2030 serving as a prominent example of this trend. We consider a series of proposed MPA network expansions of various sizes, and we forecast the impact this increase in protection would have on global patterns of fishing effort. We do so by building a predictive machine learning model trained on a global dataset of satellite-based fishing vessel monitoring data, current MPA locations, and spatiotemporal environmental, geographic, political, and economic features. We then use this model to predict future fishing effort under various MPA expansion scenarios compared to a business-as-usual counterfactual scenario that includes no new MPAs. The difference between these scenarios represents the predicted change in fishing effort associated with MPA expansion. We find that regardless of the MPA network objectives or size, fishing effort would decrease inside the MPAs, though by much less than 100%. Moreover, we find that the reduction in fishing effort inside MPAs does not simply redistribute outside-rather, fishing effort outside MPAs would also decline. The overall magnitude of the predicted decrease in global fishing effort principally depends on where networks are placed in relation to existing fishing effort. MPA expansion will lead to a global redistribution of fishing effort that should be accounted for in network design, implementation, and impact evaluation.

Past, present and future changes in the annual streamflow of the Lancang-Mekong River and their driving mechanisms

The rapid development of the Greater Mekong Subregion (GMS) makes it essential to understand the major mechanisms controlling the streamflow, especially for the Lancang-Mekong River (abbr. Mekong River). We used instrumental annual streamflow data (1960-2007) from Chiang Saen hydrological station and several gridded hydroclimatic datasets to explore the hydroclimatic evolution of the Mekong River, together with its driving mechanisms. We found that changes in the Mekong streamflow are consistent with precipitation changes, and the Mekong is thus a precipitation-dominated river that is susceptible to the effects of ongoing climate change. The instrumental record of Mekong annual streamflow is closely related to hydroclimatic changes, especially those related to moisture, within the area from the Hengduan Mountains to the Chiang Saen Station. Based on these gridded records, we extended the Mekong annual streamflow record to cover 1891-2021 using nested multiple linear regression fitting. The fitted streamflow explained up to 57.6 % of the instrumental changes and it indicates that the major 2019 drought was not unique over the past century. Despite extremely low precipitation and high temperatures, it is likely that the effects of drought can be mitigated via hydraulic engineering regulation. Climatological analyses showed that the Mekong annual streamflow is driven by the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), which is consistent with observed quasi-interannual cycles of 3-4 years. A multi-model ensemble of CMIP6 revealed that the Mekong annual streamflow will experience an upward trend in the future, accompanied by the more extreme impacts of ENSO and the IOD.

Observational evidence of changing cloud macro-physical properties under warming climate over the Indian summer monsoon region

The cloud responses to global warming are captured in various global climate models with distinct inferences on changes in cloud vertical structure as function of surface warming. However, long term observational evidences are scarce to validate the model outputs. Here, we have studied the changes in radiosonde derived cloud macro-physical properties and their association with other atmospheric variables during the period 2000-2019 in response to warming climate over the Indian summer monsoon region. We have observed a statistically significant increase in the frequency of cloudy days (∼13 % decade-1), high-level clouds (HLCs ∼11 % decade-1) and simultaneous decrease in low-level clouds (LLCs ∼8 % decade-1) over the Indian region during the monsoon season. The multiple linear regression, principle component analyses and further correlation analyses suggest significant associations between cloud vertical structure variations and large-scale climate indicators, such as global warming and El Niño-Southern Oscillation. The vertical extension of the tropospheric column and the upward shift of clouds, attributed to global warming, explain the changes observed in both HLCs and LLCs. These results contribute to a deeper understanding of the dynamic interplay between global climate change and regional cloud dynamics, with implications for weather and climate modeling.

Thermal tolerance as a driver of reef fish community structure at the isolated tropical Mid-Atlantic Ridge Islands

Reef fish communities are shaped by historical and ecological factors, including abiotic and biotic mechanisms at different spatial scales, determining species composition, abundance and biomass. The oceanic islands in the Mid-Atlantic Ridge (St. Peter and St. Paul's Archipelago - SPSPA, Ascension, and St. Helena), exhibiting differences in community structure along a 14-degree latitudinal and a 10 °C thermal gradient. We investigate the influence of sea surface temperature, area, age, isolation and phosphate on reef fish community structures. Reef fish trophic structure varies significantly across the islands, with planktivores and herbivore-detritivores showing the highest abundances in SPSPA and Ascension, while less abundant in St. Helena, aligning with the thermal gradient. Variations in reef fish community structures were predominantly influenced by thermal regimes, corroborating the expansion of species' thermal niche breadth at higher latitudes and lower temperatures. This study highlights that in addition to biogeographic factors, temperature is pivotal on shaping oceanic island reef fish community structure.

Rapid summer Russian Arctic sea-ice loss enhances the risk of recent Eastern Siberian wildfires

In recent decades boreal wildfires have occurred frequently over eastern Siberia, leading to increased emissions of carbon dioxide and pollutants. However, it is unclear what factors have contributed to recent increases in these wildfires. Here, using the data we show that background eastern Siberian Arctic warming (BAW) related to summer Russian Arctic sea-ice decline accounts for ~79% of the increase in summer vapor pressure deficit (VPD) that controls wildfires over eastern Siberia over 2004-2021 with the remaining ~21% related to internal atmospheric variability associated with changes in Siberian blocking events. We further demonstrate that Siberian blocking events are occurring at higher latitudes, are more persistent and have larger zonal scales and slower decay due to smaller meridional potential vorticity gradients caused by stronger BAW under lower sea-ice. These changes lead to more persistent, widespread and intense high-latitude warming and VPD, thus contributing to recent increases in eastern Siberian high-latitude wildfires.

Climate extremes in Svalbard over the last two millennia are linked to atmospheric blocking

Arctic precipitation in the form of rain is forecast to become more prevalent in a warmer world but with seasonal and interannual changes modulated by natural modes of variability. Experiencing rapid hydroclimatic changes in the Arctic, Svalbard serves as an ideal study location due to its exposure to oceanic and atmospheric variability in the North Atlantic region. Here we use climate data from paleoproxies, observations, and a climate model to demonstrate that wet and warm extremes in Svalbard over the last two millennia are linked to the presence of atmospheric blocking regimes over Scandinavia and the Ural mountain region. Rainfall episodes lead to the deposition of coarse sediment particles and high levels of calcium in Linnévatnet, a lake in southwest Svalbard, with the coarsest sediments consistently deposited during atmospheric blocking events. A unique annually resolved sediment record from Linnévatnet confirms that this linkage has been persistent over the past 2000 years. Our record also shows that a millennial-scale decline in Svalbard precipitation ended around the middle of the 19th century, followed by several unprecedented extreme events in recent years. As warming continues and sea ice recedes, future Svalbard floods will become more intense during episodes of Scandinavian and Ural blocking.

Body length changes for Atlantic salmon (Salmo salar) over five decades exhibit weak spatial synchrony over a broad latitudinal gradient

Understanding the factors that drive spatial synchrony among populations or species is important for management and recovery of populations. The range-wide declines in Atlantic salmon (Salmo salar) populations may be the result of broad-scale changes in the marine environment. Salmon undergo rapid growth in the ocean; therefore changing marine conditions may affect body size and fecundity estimates used to evaluate whether stock reference points are met. Using a dataset that spanned five decades, 172,268 individuals, and 19 rivers throughout Eastern Canada, we investigated the occurrence of spatial synchrony in changes in the body size of returning wild adult Atlantic salmon. Body size was then related to conditions in the marine environment (i.e., climate indices, thermal habitat availability, food availability, density-dependence, and fisheries exploitation rates) that may act on all populations during the ocean feeding phase of their life cycle. Body size increased during the 1980s and 1990s for salmon that returned to rivers after one (1SW) or two winters at sea (2SW); however, significant changes were only observed for 1SW and/or 2SW in some mid-latitude and northern rivers (10/13 rivers with 10 of more years of data during these decades) and not in southern rivers (0/2), suggesting weak spatial synchrony across Eastern Canada. For 1SW salmon in nine rivers, body size was longer when fisheries exploitation rates were lower. For 2SW salmon, body size was longer when suitable thermal habitat was more abundant (significant for 3/8 rivers) and the Atlantic Multidecadal Oscillation was higher (i.e., warmer sea surface temperatures; significant for 4/8 rivers). Overall, the weak spatial synchrony and variable effects of covariates on body size across rivers suggest that changes in Atlantic salmon body size may not be solely driven by shared conditions in the marine environment. Regardless, body size changes may have consequences for population management and recovery through the relationship between size and fecundity.

Explainable El Niño predictability from climate mode interactions

The El Niño-Southern Oscillation (ENSO) provides most of the global seasonal climate forecast skill1-3, yet, quantifying the sources of skilful predictions is a long-standing challenge4-7. Different sources of predictability affect ENSO evolution, leading to distinct global effects. Artificial intelligence forecasts offer promising advancements but linking their skill to specific physical processes is not yet possible8-10, limiting our understanding of the dynamics underpinning the advancements. Here we show that an extended nonlinear recharge oscillator (XRO) model shows skilful ENSO forecasts at lead times up to 16-18 months, better than global climate models and comparable to the most skilful artificial intelligence forecasts. The XRO parsimoniously incorporates the core ENSO dynamics and ENSO's seasonally modulated interactions with other modes of variability in the global oceans. The intrinsic enhancement of ENSO's long-range forecast skill is traceable to the initial conditions of other climate modes by means of their memory and interactions with ENSO and is quantifiable in terms of these modes' contributions to ENSO amplitude. Reforecasts using the XRO trained on climate model output show that reduced biases in both model ENSO dynamics and in climate mode interactions can lead to more skilful ENSO forecasts. The XRO framework's holistic treatment of ENSO's global multi-timescale interactions highlights promising targets for improving ENSO simulations and forecasts.

Heatwave attribution based on reliable operational weather forecasts

The 2021 Pacific Northwest heatwave was so extreme as to challenge conventional statistical and climate-model-based approaches to extreme weather attribution. However, state-of-the-art operational weather prediction systems are demonstrably able to simulate the detailed physics of the heatwave. Here, we leverage these systems to show that human influence on the climate made this event at least 8 [2-50] times more likely. At the current rate of global warming, the likelihood of such an event is doubling every 20 [10-50] years. Given the multi-decade lower-bound return-time implied by the length of the historical record, this rate of change in likelihood is highly relevant for decision makers. Further, forecast-based attribution can synthesise the conditional event-specific storyline and unconditional event-class probabilistic approaches to attribution. If developed as a routine service in forecasting centres, it could provide reliable estimates of human influence on extreme weather risk, which is critical to supporting effective adaptation planning.

Emergence of decadal linkage between Western Australian coast and Western-central tropical Pacific

The impact of interbasin linkage on the weather/climate and ecosystems is significantly broader and profounder than that of only appearing in an individual basin. Here, we reveal that a decadal linkage of sea surface temperature (SST) has emerged between western Australian coast and western-central tropical Pacific since 1985, associated with continuous intensification of decadal variabilities (8-16 years). The rapid SST changes in both tropical Indian Ocean and Indo-Pacific warm pool in association to greenhouse gases and volcanoes are emerging factors resulting in enhanced decadal co-variabilities between these two regions since 1985. These SST changes induce enhanced convection variability over the Maritime Continent, leading to stronger easterlies in the western-central tropical Pacific during the warm phase off western Australian coast. The above changes bring about cooling in the western-central tropical Pacific and strengthened Leeuwin Current and anomalous cyclonic wind off western Australian coast, and ultimately resulting in enhanced coupling between these two regions. Our results suggest that enhanced decadal interbasin connections can offer further understanding of decadal changes under future warmer conditions.

Atmosphere teleconnections from abatement of China aerosol emissions exacerbate Northeast Pacific warm blob events

During 2010 to 2020, Northeast Pacific (NEP) sea surface temperature (SST) experienced the warmest decade ever recorded, manifested in several extreme marine heatwaves, referred to as "warm blob" events, which severely affect marine ecosystems and extreme weather along the west coast of North America. While year-to-year internal climate variability has been suggested as a cause of individual events, the causes of the continuous dramatic NEP SST warming remain elusive. Here, we show that other than the greenhouse gas (GHG) forcing, rapid aerosol abatement in China over the period likely plays an important role. Anomalous tropospheric warming induced by declining aerosols in China generated atmospheric teleconnections from East Asia to the NEP, featuring an intensified and southward-shifted Aleutian Low. The associated atmospheric circulation anomaly weakens the climatological westerlies in the NEP and warms the SST there by suppressing the evaporative cooling. The aerosol-induced mean warming of the NEP SST, along with internal climate variability and the GHG-induced warming, made the warm blob events more frequent and intense during 2010 to 2020. As anthropogenic aerosol emissions continue to decrease, there is likely to be an increase in NEP warm blob events, disproportionately large beyond the direct radiative effects.

Spatiotemporal Characterization of Dengue Incidence and Its Correlation to Climate Parameters in Indonesia

Dengue has become a public health concern in Indonesia since it was first found in 1968. This study aims to determine dengue hotspot areas and analyze the spatiotemporal distribution of dengue and its association with dominant climate parameters nationally. Monthly data for dengue and climate observations (i.e., rainfall, relative humidity, average, maximum, and minimum temperature) at the regency/city level were utilized. Dengue hotspot areas were determined through K-means clustering, while Singular Value Decomposition (SVD) determined dominant climate parameters and their spatiotemporal distribution. Results revealed four clusters: Cluster 1 comprised cities with medium to high Incidence Rates (IR) and high Case Densities (CD) in a narrow area. Cluster 2 has a high IR and low CD, and clusters 3 and 4 featured medium and low IR and CD, respectively. SVD analysis indicated that relative humidity and rainfall were the most influential parameters on IR across all clusters. Temporal fluctuations in the first mode of IR and climate parameters were clearly delineated. The spatial distribution of heterogeneous correlation between the first mode of rainfall and relative humidity to IR exhibited higher values, which were predominantly observed in Java, Bali, Nusa Tenggara, the eastern part of Sumatra, the southern part of Kalimantan, and several locations in Sulawesi.

Indian Ocean temperature anomalies predict long-term global dengue trends

Despite identifying El Niño events as a factor in dengue dynamics, predicting the oscillation of global dengue epidemics remains challenging. Here, we investigate climate indicators and worldwide dengue incidence from 1990 to 2019 using climate-driven mechanistic models. We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres. The ability of IOBW to predict dengue incidence likely arises as a result of its effect on local temperature anomalies through teleconnections. These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses.

Human-induced intensified seasonal cycle of sea surface temperature

Changes in the seasonal cycle of sea surface temperature (SST) have far-reaching ecological and societal implications. Previous studies have found an intensified SST seasonal cycle under global warming, but whether such changes have emerged in historical records remains largely unknown. Here, we reveal that the SST seasonal cycle globally has intensified by 3.9 ± 1.6% in recent four decades (1983-2022), with hotspot regions such as the northern subpolar gyres experiencing an intensification of up to 10%. Increased greenhouse gases are the primary driver of this intensification, and decreased anthropogenic aerosols also contribute. These changes in anthropogenic emissions lead to shallower mixed layer depths, reducing the thermal inertia of upper ocean and enhancing the seasonality of SST. In addition, the direct impacts of increased ocean heat uptake and suppressed seasonal amplitude of surface heat flux also contribute in the North Pacific and North Atlantic. The temperature seasonal cycle is intensified not only at the ocean surface, but throughout the mixed layer. The ramifications of this intensified SST seasonal cycle extend to the seasonal variation in upper-ocean oxygenation, a critical factor for most ocean ecosystems.

In situ decrease in rhodolith growth associated with Arctic climate change

Rhodoliths built by crustose coralline algae (CCA) are ecosystem engineers of global importance. In the Arctic photic zone, their three-dimensional growth emulates the habitat complexity of coral reefs but with a far slower growth rate, growing at micrometers per year rather than millimeters. While climate change is known to exert various impacts on the CCA's calcite skeleton, including geochemical and structural alterations, field observations of net growth over decade-long timescales are lacking. Here, we use a temporally explicit model to show that rising ocean temperatures over nearly 100 years were associated with reduced rhodolith growth at different depths in the Arctic. Over the past 90 years, the median growth rate was 85 μm year-1 but each °C increase in summer seawater temperature decreased growth by a mean of 8.9 μm (95% confidence intervals = 1.32-16.60 μm °C-1, p < .05). The decrease was expressed for rhodolith occurrences in 11 and 27 m water depth but not at 46 m, also having the shortest time series (1991-2015). Although increasing temperatures can spur plant growth, we suggest anthropogenic climate change has either exceeded the population thermal optimum for these CCA, or synergistic effects of warming, ocean acidification, and/or increasing turbidity impair rhodolith growth. Rhodoliths built by calcitic CCA are important habitat providers worldwide, so decreased growth would lead to yet another facet of anthropogenic habitat loss.

Existence of typical winter atmospheric circulation patterns leading to high PM2.5 concentration days in East Asia

Understanding the atmospheric circulation patterns responsible for severe air pollution events in East Asia is important because East Asia is one of the most polluted regions in the world, particularly during the boreal winter (December-January-February). Here, by conducting GEOS-Chem simulation with fixed anthropogenic emission sources, we found that there exist three typical atmospheric circulation patterns conducive to leading to high concentrations of particulate matter with a diameter less than or equal to 2.5 μm (PM2.5) in East Asia. These atmospheric circulation patterns are characterized by weakened horizontal winds, which allows PM2.5 to accumulate, and by enhanced relative humidity, which can favor secondary formation of PM2.5. The occurrence of these atmospheric circulation patterns is associated with increased sea ice cover over the Barents Sea and heavy precipitation over the tropical western Indian Ocean. The existence of these atmospheric circulation patterns among typical atmospheric circulation patterns indicates high PM2.5 days in East Asia are unavoidable given current level of anthropogenic emissions in the region. This conclusion indicates that sustained efforts to reduce anthropogenic emission sources in East Asia should be warranted to avoid high PM2.5 days.

The role of the North Atlantic Ocean on the increase in East Asia's spring extreme hot day occurrences across the early 2000s

The occurrence frequency of East Asia's extreme hot day in boreal spring has increased since 1979. Using observational data and a Linear baroclinic model experiment, our study suggests that the occurrence of hot day is mainly due to anomalous high pressure over East Asia associated with a horizontal stationary wave train originating from a positive phase of the North Atlantic Tripole (NAT) sea surface temperature (SST) in spring. The effect of a positive phase of the NAT SST is evident in the 2000s, apparently associated with the linear trend of the North Atlantic SST like a positive phase of the NAT SST. Before 2000s, in contrast, SST forcing in the Indian Ocean and eastern tropical Pacific, which is associated with a negative phase of the NAT SST, may contribute to induce the East Asian hot days through atmospheric teleconnections. This implies that the relationship between a positive phase of the NAT SST and the occurrence of hot days in East Asia has been changed during the 2000s.

Using Museum collections to assess the impact of industrialization on mussel (Mytilus edulis) calcification

Mytilus edulis is a commercially and ecologically important species found along the east coast of the United States. Ecologically, M. edulis improves water quality through filtration feeding and provides habitat formation and coastal protection through reef formation. Like many marine calcifiers, ocean warming, and acidification are a growing threat to these organisms-impacting their morphology and function. Museum collections are useful in assessing long-term environmental impacts on organisms in a natural multi-stressor environment, where acclimation and adaptation can be considered. Using the American Museum of Natural History collections ranging from the early 1900s until now, we show that shell porosity changes through time. Shells collected today are significantly more porous than shells collected in the 1960s and, at some sites, than shells collected from the early 1900s. The disparity between porosity changes matches well with the warming that occurred over the last 130 years in the north Atlantic suggesting that warming is causing porosity changes. However, more work is required to discern local environmental impacts and to fully identify porosity drivers. Since, porosity is known to affect structural integrity, porosity increasing through time could have negative consequences for mussel reef structural integrity and hence habitat formation and storm defenses.

Coupled Pacific Rim megadroughts contributed to the fall of the Ming Dynasty's capital in 1644 CE

Historical documents provide evidence for regional droughts preceding the political turmoil and fall of Beijing in 1644 CE, when more than 20 million people died in northern China during the late Ming famine period. However, the role climate and environmental changes may have played in this pivotal event in Chinese history remains unclear. Here, we provide tree-ring evidence of persistent megadroughts from 1576 to 1593 CE and from 1624 to 1643 CE in northern China, which coincided with exceptionally cold summers just before the fall of Beijing. Our analysis reveals that these regional hydroclimatic extremes are part of a series of megadroughts along the Pacific Rim, which not only impacted the ecology and society of monsoonal northern China, but likely also exacerbated external geopolitical and economic pressures. This finding is corroborated by last millennium reanalysis data and numerical climate model simulations revealing internally driven Pacific sea surface temperature variations and the predominance of decadal scale La Niña-like conditions to be responsible for precipitation decreases over northern China, as well as extensive monsoon regions in the Americas. These teleconnection patterns provide a mechanistic explanation for reoccurring drought spells during the late Ming Dynasty and the environmental framework fostering the fall of Beijing in 1644 CE, and the subsequent demise of the Ming Dynasty.

Amundsen Sea Ice Loss Contributes to Australian Wildfires

Wildfires in Australia have attracted extensive attention in recent years, especially for the devastating 2019-2020 fire season. Remote forcing, such as those from tropical oceans, plays an important role in driving the abnormal weather conditions associated with wildfires. However, whether high latitude climate change can impact Australian fires is largely unclear. In this study, we reveal a robust relationship between Antarctic sea ice concentration (SIC), primarily over the Amundsen Sea region, with Australian springtime fire activity, by using reanalysis data sets, AMIP simulation results, and a state-of-the-art climate model simulation. Specifically, a diminished Amundsen SIC leads to the formation of a high-pressure system above Australia as a result of the eastward propagation of Rossby waves. Meanwhile, two strengthened meridional cells originating from the tropic and polar regions also enhance subsiding airflow in Australia, resulting in prolonged arid and high-temperature conditions. This mechanism explains about 28% of the variability of Australian fire weather and contributed more than 40% to the 2019 extreme burning event, especially in the eastern hotspots. These findings contribute to our understanding of polar-low latitude climate teleconnection and have important implications for projecting Australian fires as well as the global environment.

Weakened western Indian Ocean dominance on Antarctic sea ice variability in a changing climate

Patterns of sea surface temperature (SST) anomalies of the Indian Ocean Dipole (IOD) exhibit strong diversity, ranging from being dominated by the western tropical Indian Ocean (WTIO) to the eastern tropical Indian Ocean (ETIO). Whether and how the different types of IOD variability patterns affect the variability of Antarctic sea ice is not known, nor is how the impact may change in a warming climate. Here, we find that the leading mode of austral spring Antarctic sea ice variability is dominated by WTIO SST variability rather than ETIO SST or El Niño-Southern Oscillation. WTIO warm SST anomalies excite a poleward-propagating Rossby wave, inducing a tri-polar anomaly pattern characterized by a decrease in sea ice near the Amundsen Sea but an increase in regions on both sides. Such impact has been weakening in the two decades post-2000, accompanied by weakened WTIO SST variability. Under greenhouse warming, climate models project a decrease in WTIO SST variability, suggesting that the reduced impact on Antarctic sea ice from the IOD will likely to continue, facilitating a fast decline of Antarctic sea ice.

Dominant contribution of atmospheric nonlinearities to ENSO asymmetry and extreme El Niño events

Extreme El Niño events have outsized impacts and strongly contribute to the El Niño Southern Oscillation (ENSO) warm/cold phase asymmetries. There is currently no consensus on the respective importance of oceanic and atmospheric nonlinearities for those asymmetries. Here, we use atmospheric and oceanic general circulation models that reproduce ENSO asymmetries well to quantify the atmospheric nonlinearities contribution. The linear and nonlinear components of the wind stress response to Sea Surface Temperature (SST) anomalies are isolated using ensemble atmospheric experiments, and used to force oceanic experiments. The wind stress-SST nonlinearity is dominated by the deep atmospheric convective response to SST. This wind-stress nonlinearity contributes to ~ 40% of the peak amplitude of extreme El Niño events and ~ 55% of the prolonged eastern Pacific warming they generate until the following summer. This large contribution arises because nonlinearities consistently drive equatorial westerly anomalies, while the larger linear component is made less efficient by easterly anomalies in the western Pacific during fall and winter. Overall, wind-stress nonlinearities fully account for the eastern Pacific positive ENSO skewness. Our findings underscore the pivotal role of atmospheric nonlinearities in shaping extreme El Niño events and, more generally, ENSO asymmetry.

Northeast Pacific warm blobs sustained via extratropical atmospheric teleconnections

Large-scale marine heatwaves in the Northeast Pacific (NEP), identified here and previously as 'warm blobs', have devastating impacts on regional ecosystems. An anomalous atmospheric ridge over the NEP is known to be crucial for maintaining these warm blobs, also causing abnormally cold temperatures over North America during the cold season. Previous studies linked this ridge to teleconnections from tropical sea surface temperature anomalies. However, it was unclear whether teleconnections from the extratropics could also contribute to the ridge. Here we show that planetary wave trains, triggered by increased rainfall and latent heat release over the Mediterranean Sea accompanied by decreased rainfall over the North Atlantic, can transport wave energy to the NEP, guided by the westerly jet, and induce a quasi-barotropic ridge there. Our findings provide insights into extratropical teleconnections sustaining the NEP ridge, offering a source of potential predictability for the warm blobs and temperature fluctuations over North America.

Data-driven dimensionality reduction and causal inference for spatiotemporal climate fields

We propose a data-driven framework to describe spatiotemporal climate variability in terms of a few entities and their causal linkages. Given a high-dimensional climate field, the methodology first reduces its dimensionality into a set of regionally constrained patterns. Causal relations among such patterns are then inferred in the interventional sense through the fluctuation-response formalism. To distinguish between true and spurious responses, we propose an analytical null model for the fluctuation-dissipation relation, therefore allowing us for uncertainty estimation at a given confidence level. We showcase the methodology on the sea surface temperature field from a state-of-the-art climate model. The usefulness of the proposed framework for spatiotemporal climate data is demonstrated in several ways. First, we focus on the correct identification of known causal relations across tropical basins. Second, we show how the methodology allows us to visualize the cumulative response of the whole system to climate variability in a few selected regions. Finally, each pattern is ranked in terms of its causal strength, quantifying its relative ability to influence the system's dynamics. We argue that the methodology allows us to explore and characterize causal relations in spatiotemporal fields in a rigorous and interpretable way.

Recent autumn sea ice loss in the eastern Arctic enhanced by summer Asian-Pacific Oscillation

Recent rapid Arctic sea ice loss was documented as combined results from anthropogenic forcing and climate system internal variability. However, the role of internal variability is not well understood. Here, we propose that the Asian-Pacific Oscillation (APO), an intrinsic atmospheric mode featuring out-of-phase variations in upper-tropospheric temperatures between Asia and the North Pacific, is one driver for autumn sea ice variability in the eastern Arctic. The positive summer APO favors warming of the mid-latitude North Atlantic sea surface temperatures. This warming persists to autumn and in turn triggers strong anticyclonic anomalies over the Barents-Kara-Laptev Seas and weak lower-tropospheric cyclonic anomalies over the East Siberian Sea, enhancing moisture transport into the eastern Arctic. Such changes consequently increase lower-tropospheric humidity, downwelling longwave radiation, and surface air temperature in the eastern Arctic, thereby melting sea ice. Hence, a recent tendency of the summer APO towards the positive phase accelerates autumn sea ice loss in the eastern Arctic.

Satellite-based time-series of sea-surface temperature since 1980 for climate applications

A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high degree of independence from in situ measurements. Observations from twenty infrared and two microwave radiometers are used, and are adjusted for their differing times of day of measurement to avoid aliasing and ensure observational stability. A total of 1.5 × 1013 locations are processed, yielding 1.4 × 1012 SST observations deemed to be suitable for climate applications. The corresponding observation density varies from less than 1 km-2 yr-1 in 1980 to over 100 km-2 yr-1 after 2007. Data are provided at their native resolution, averaged on a global 0.05° latitude-longitude grid (single-sensor with gaps), and as a daily, merged, gap-free, SST analysis at 0.05°. The data include the satellite-based SSTs, the corresponding time-and-depth standardised estimates, their standard uncertainty and quality flags. Accuracy, spatial coverage and length of record are all improved relative to a previous version, and the timeseries is routinely extended in time using consistent methods.

Marine heatwaves disrupt ecosystem structure and function via altered food webs and energy flux

The prevalence and intensity of marine heatwaves is increasing globally, disrupting local environmental conditions. The individual and population-level impacts of prolonged heatwaves on marine species have recently been demonstrated, yet whole-ecosystem consequences remain unexplored. We leveraged time series abundance data of 361 taxa, grouped into 86 functional groups, from six long-term surveys, diet information from a new diet database, and previous modeling efforts, to build two food web networks using an extension of the popular Ecopath ecosystem modeling framework, Ecotran. We compare ecosystem models parameterized before and after the onset of recent marine heatwaves to evaluate the cascading effects on ecosystem structure and function in the Northeast Pacific Ocean. While the ecosystem-level contribution (prey) and demand (predators) of most functional groups changed following the heatwaves, gelatinous taxa experienced the largest transformations, underscored by the arrival of northward-expanding pyrosomes. We show altered trophic relationships and energy flux have potentially profound consequences for ecosystem structure and function, and raise concerns for populations of threatened and harvested species.

Atlantic origin of the increasing Asian westerly jet interannual variability

The summer Eurasian westerly jet is reported to become weaker and wavier, thus promoting the frequent weather extremes. However, the primary driver of the changing jet stream remains in debate, mainly due to the regionality and seasonality of the Eurasian jet. Here we report a sharp increase, by approximately 140%, in the interannual variability of the summertime East Asian jet (EAJ) since the end of twentieth century. Such interdecadal change induces considerable changes in the large-scale circulation pattern across Eurasia, and consequently weather and climate extremes including heatwaves, droughts, and Asian monsoonal rainfall regime shifts. The trigger mainly emerges from preceding February North Atlantic seesaw called Scandinavian pattern (contributing to 81.1 ± 2.9% of the enhanced EAJ variability), which harnesses the "cross-seasonal-coupled oceanic-atmospheric bridge" to exert a delayed impact on EAJ and thus aids relevant predictions five months in advance. However, projections from state-of-the-art models with prescribed anthropogenic forcing exhibit no similar circulation changes. This sheds light on that, at the interannual timescale, a substantial portion of recently increasing variability in the East Asian sector of the Eurasian westerly jet arises from unforced natural variability.

Identifying important drivers of East African October to December rainfall season

Monsoon rainfall plays a crucial part in Africa's socio-economic structure and its year-to-year variability has profound implications for agricultural, energy, and other societal sectors. The current study focuses on two of the major climate drivers of the east African rainy season during October-November-December (OND), which is when the season starts for a large portion of east Africa (e.g. Tanzania and Malawi). Such drivers could be different in early austral summer from the rest of the year, due to the relative positioning of the Intertropical convergence zone, which passes through this region - hence regions of east Africa and OND season are the focus here. The two drivers of Monsoon viz. El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are considered: both independently indicate strong connections with monsoon OND rain. Not only is there a strong significant positive correlation in the OND season as a simultaneous relation, but the signal is also there even with the lag of a few months. This has been tested using various data sources, detrending data beforehand, analysing either recent time periods or earlier time periods - covering two decades each, and using regression analyses. To further strengthen the results, a compositing approach is applied that can additionally identify strong rainfall signals to that from years when opposite combinations of ENSO and IOD phases act as confounding factors. Results of precipitation anomaly for OND for compositing, when IOD and ENSO are both negative (positive) in July-August-September(JAS) indicate a deficit (excess) in rainfall in that region. The Walker circulation seems to play a major part via altering ascending to descending branch in two situations, when both drivers are in same phase. In the last near thirty years period, a total of 9 years matched the criteria when both drivers were negative and suggested a deficit in OND rainfall; more recently, that criteria occurred also in 2022 (JAS) and was again associated with a rainfall deficit in OND 2022. Based on this analysis, it is possible to deliver an estimation of cumulative rain in terms of median value, range and distribution, one season in advance, at a point location or average over a region. Some results of compositing are confirmed for longer record (1940-2021) too and further classifications based on threshold of drivers are tested. Rainfall (OND) variability at intra-decadal, decadal and multi-decadal scales are studied by applying the method of centered moving averages of 5-year, 11-year and 21-year respectively. Our results have implications for future planning in optimizing agricultural and energy outputs, mitigating severe consequences and losses associated with droughts and excess rain and will impact the livelihoods of millions of east Africans.

Historical changes in wind-driven ocean circulation drive pattern of Pacific warming

The tropical Pacific warming pattern since the 1950s exhibits two warming centers in the western Pacific (WP) and eastern Pacific (EP), encompassing an equatorial central Pacific (CP) cooling and a hemispheric asymmetry in the subtropical EP. The underlying mechanisms of this warming pattern remain debated. Here, we conduct ocean heat decompositions of two coupled model large ensembles to unfold the role of wind-driven ocean circulation. When wind changes are suppressed, historical radiative forcing induces a subtropical northeastern Pacific warming, thus causing a hemispheric asymmetry that extends toward the tropical WP. The tropical EP warming is instead induced by the cross-equatorial winds associated with the hemispheric asymmetry, and its driving mechanism is southward warm Ekman advection due to the off-equatorial westerly wind anomalies around 5°N, not vertical thermocline adjustment. Climate models fail to capture the observed CP cooling, suggesting an urgent need to better simulate equatorial oceanic processes and thermal structures.

Global vegetation, moisture, thermal and climate interactions intensify compound extreme events

Compound extreme events, encompassing drought, vegetation stress, wildfire severity, and heatwave intensity (CDVWHS), pose significant threats to societal, environmental, and health systems. Understanding the intricate relationships governing CDVWHS evolution and their interaction with climate teleconnections is crucial for effective climate adaptation strategies. This study leverages remote sensing, reanalysis data, and climate models to analyze CDVWHS during historical (1982-2014), near-future (2028-2060), and far-future (2068-2100) periods under two Shared Socioeconomic Pathways (SSP; 245 and 585). Our results show that reduced vegetation health, unfavorable temperature conditions, and low moisture conditions have negligible effects on vegetation density. However, they worsen the intensity of heatwaves and increase the risk of wildfires. Wildfires can persist when thermal conditions are poor despite favorable moisture levels. For example, despite adequate moisture availability, we link the 2012 Siberian wildfire in the Ob basin to anomalous negative thermal conditions and concurrent unfavorable thermal-moisture conditions. In contrast, the Amazon experiences extreme and exceptional drought associated with unfavorable moisture conditions in the same year. A comparative analysis of Siberian and North American fires reveals distinct burned area anomalies due to variations in vegetation density and wildfire fuel. The North American fires have lower positive anomalies in burned areas because of negative anomalous vegetation density, which reduced the amount of wildfire fuel. Furthermore, we examine basin-specific variability in climate teleconnections related to compound CDVWHS, revealing the primary modes of variability and evolution of CDVWHS through climate teleconnection patterns. Moreover, a substantial increase in the magnitude of heatwave severity emerges between the near and far future under SSP 585. This study underscores the urgency for targeted actions to enhance ecosystem resilience and safeguard vulnerable communities from CDVWHS impacts. Identifying CDVWHS hotspots and comprehending their complex relationships with environmental factors are essential for developing effective adaptation strategies in a changing climate.

Ability of a dynamical climate sensitive disease model to reproduce historical Rift Valley Fever outbreaks over Africa

Rift Valley Fever (RVF) is a zoonosis transmitted by Aedes and Culex mosquitoes, and is considered a priority pathogen by the WHO. RVF epidemics mostly occur in Africa and can decimate livestock herds, causing significant economic losses and posing health risks for humans. RVF transmission is associated with the occurrence of El Niño events that cause floods in eastern Africa and favour the emergence of mosquitoes in wetlands. Different risk models have been developed to forecast RVF transmission risk but very few studies have validated models at pan-African scale. This study aims to validate the skill of the Liverpool Rift Valley Fever model (LRVF) in reproducing RVF epidemics over Africa and to explore the relationship between simulated climatic suitability for RVF transmission and large-scale climate modes of variability such as the El Niño Southern Oscillation (ENSO) and the Dipole Mode Index (DMI). Our results show that the LRVF model correctly simulates RVF transmission hotspots and reproduces large epidemics that affected African countries. LRVF was able to correctly reproduce major RVF epidemics in Somalia, Kenya, Zambia and to a lesser extent for Mauritania and Senegal. The positive phases of ENSO and DMI are associated with an increased risk of RVF over the Horn of Africa, with important time lags. Following research activities should focus on the development of predictive modelling systems at different time scales.

Unraveling sub-seasonal precipitation variability in the Middle East via Indian Ocean sea surface temperature

This study examines sub-seasonal precipitation anomalies, challenging to predict yet vital for society and the environment. Focusing on October, we investigate correlations between the Indian Ocean Dipole Mode Index (DMI), West Tropical Indian Ocean Index (WTIO), and Middle Eastern precipitation. We find robust correlations (~ 0.7), up to a two-month lag, demonstrating strong links between these climate indices and rainfall patterns, potentially suggesting sub-seasonal precipitation predictability. Over the past four decades, DMI and WTIO have shown a significant upward trend of ~ 0.4 °C, intensifying their impact on precipitation dynamics. This trend signifies evolving Indian Ocean climate patterns with potential regional consequences and is projected to continue in the twenty-first century. Significant correlations also emerge between DMI, WTIO, and maximum daily precipitation, highlighting their role in extreme rainfall events. Finally, our study attributes most of October's precipitation variability to Indian Ocean sea surface temperature variations. These temperature anomalies influence the Indian Ocean's Walker circulation, affecting water vapor flux to the Middle East and shaping regional precipitation. Our findings underscore the importance of these indices in understanding and predicting Middle East climate variability, revealing intricate ocean-atmosphere interactions.

Environmental drivers of Arctic communities based on metabarcoding of marine sediment eDNA

Our ability to assess biodiversity at relevant spatial and temporal scales for informing management is of increasing importance given this is foundational to identify and mitigate the impacts of global change. Collecting baseline information and tracking ecological changes are particularly important for areas experiencing rapid changes and representing data gaps such as Arctic marine ecosystems. Environmental DNA has the potential to provide such data. We extracted environmental DNA from 90 surface sediment samples to assess eukaryote diversity around Greenland and Svalbard using two separate primer pairs amplifying different sections of the 18S rRNA gene. We detected 27 different phyla and 99 different orders and found that temperature and the change in temperature explained the most variation in the community in a single linear model, while latitude, sea ice cover and change in temperature explained the most variation in the community when assessed by individual non-linear models. We identified potential indicator taxa for Arctic climate change, including a terebellid annelid worm. In conclusion, our study demonstrates that environmental DNA offers a feasible method to assess biodiversity and identifies warming as a key driver of differences in biodiversity across these remote ecosystems.

Last millennium hurricane activity linked to endogenous climate variability

Despite increased Atlantic hurricane risk, projected trends in hurricane frequency in the warming climate are still highly uncertain, mainly due to short instrumental record that limits our understanding of hurricane activity and its relationship to climate. Here we extend the record to the last millennium using two independent estimates: a reconstruction from sedimentary paleohurricane records and a statistical model of hurricane activity using sea surface temperatures (SSTs). We find statistically significant agreement between the two estimates and the late 20th century hurricane frequency is within the range seen over the past millennium. Numerical simulations using a hurricane-permitting climate model suggest that hurricane activity was likely driven by endogenous climate variability and linked to anomalous SSTs of warm Atlantic and cold Pacific. Volcanic eruptions can induce peaks in hurricane activity, but such peaks would likely be too weak to be detected in the proxy record due to large endogenous variability.