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In the context of rapidly rising sea levels over the north Indian Ocean, the decadal variations play significant role and predicting them is of utmost important to the society. The present study evaluates the quality of all the available retrospective decadal sea level predictions from the state-of-the-art climate models of the Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6). The models are skilful in predicting the sea level over the tropical Indo-Pacific for the lead year 1 and thereafter the skill persists mainly over the western Indian Ocean regions. Most of the models exhibit significant skill in the Arabian Sea region at higher leads including 2–5 years and 6–9 years. Half of the models display higher sea level prediction skill over the Arabian Sea at lead year 2–5, compared to lead year 1. Taking into account of the close association between the Indian Ocean decadal sea level variations and the decadal climate variability in the Pacific and Atlantic, the skill of models in predicting the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) up to a decade is also assessed in this study. The AMO is better predicted in most of the models up to lead year 9, whereas only few models display skill in predicting the PDO. Skilful representations of strong cross equatorial flow and convergence of southerly winds towards the Arabian Sea region are noted in the CMIP6 predictions, which are responsible for better sea level prediction skill over the Arabian Sea. This study highlights that the better representation of AMO in the models has primarily contributed to the skilful sea level predictions over the Arabian Sea region. [ABSTRACT FROM AUTHOR]

Studies have analyzed U.S. tornado variability and correlated F1–F5 tornado occurrence with various natural climate oscillations and anthropogenic factors. Using a relatively new empirical mode decommission (EMD) method that extracts time-frequency modes adaptively without priori assumptions like traditional time-series analysis methods, this study decomposes U.S. tornado variability during 1954–2022 into intrinsic modes on specific temporal scales. Correlating the intrinsic mode functions (IMFs) of EMD with climate indices found that 1. the U.S. overall tornado count is negatively (positively) correlated with the Atlantic Multidecadal Oscillation (AMO) index (the Southern Oscillation Index (SOI)); 2. the negative (positive) correlation tends to be more prevalent in the western (eastern) U.S.; 3. the increase in weak (F1–F2) and decrease in strong (F3–F5) tornadoes after around 2000, when both the AMO and the Pacific Decadal Oscillation (PDO) shifted phases, are likely related to their secular trends and low-frequency IMFs; and 4. the emerging Dixie Tornado Alley coincides with an amplifying intrinsic mode of the SOI that correlates positively with the eastern U.S. and Dixie Alley tornadoes. The long-term persistence of these climate indices can offer potential guidance for future planning for tornado hazards. [ABSTRACT FROM AUTHOR]

Extracting global sea surface temperature (SST) patterns is essential for understanding climate variability in both regional and global perspective. Traditional methods, limited by assumptions of orthogonality, hinder our ability to fully capture the dynamics of global SST, particularly in the complex Pacific basin. This study introduces dynamic mode decomposition (DMD), a powerful method from fluid dynamics, to extract global SST patterns since 1900. Our analysis shows that DMD successfully captures well‐known patterns like global warming and the Atlantic Multidecadal Oscillation (AMO). More importantly, it reveals three Pacific SST modes that are spatially non‐orthogonal but exhibit distinct characteristics. Spectral analysis shows that these Pacific modes have distinct periodicities: Pacific Multi‐decadal Mode (PMDM, ~50 years), Quasi‐decadal Mode (PQDM, 8–16 years) and Interannual Mode (PIAM, 2–8 years). This highlights DMD's strength in not only capturing known patterns but also separating modes with similar spatial features but unique dynamics. Further analysis reveals significant differences in their impacts on global air temperature. During positive phases, all three modes induce tropical warming, with PIAM exerting the strongest influence and PMDM the weakest. In the Northern Hemisphere, both PQDM and PIAM drive mid‐latitude cooling and high‐latitude warming, with a more pronounced effect from PQDM. PMDM, in contrast, triggers widespread cooling across the Northern extratropics. In the Southern Hemisphere, PMDM's influence on temperature exhibits a distinct latitudinal banding pattern. PIAM and PQDM, on the other hand, exhibit a regionalized impact, primarily concentrated in the Amundsen and Ross Seas, with PQDM's influence extending to the Antarctic continent. [ABSTRACT FROM AUTHOR]

The upper reaches of the Yangtze River Basin (UYRB) are famous for their hydropower generation and water resources in China, relying greatly on precipitation. The UYRB summer precipitation has decreased since the early 2000s and has been exposed to a particularly dry period in the most recent two decades. By analyzing the long‐term variability from the beginning of the 20th Century, we found that the precipitation exhibits a profound periodic interdecadal variation, with a significant cycle of 30–50 years. The interdecadal variability of precipitation is shown to be significantly modulated by both the Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), exerting their impact through related circulation anomalies. Moreover, the periodical nature of the UYRB precipitation variation and its correlation with AMO/PDO suggest that the UYRB might enter a wet period in the forthcoming decade, i.e. rich in hydroelectric resources but a high risk of flood. [ABSTRACT FROM AUTHOR]

After precipitation, reference evapotranspiration (ETO) plays a crucial role in the hydrological cycle as it quantifies water loss. ETO significantly impacts the water balance and holds great importance at the basin level because of the spatial distribution of managing water resources. Large scale teleconnection indices (LSTIs) play a vital role by influencing climatic variables and can be pivotal in determining ETO and its predictive variables. This study aimed to model and forecast annual ETO in Iran's basins by utilizing LSTIs and employing various machine learning models (MLMs) such as least squares support vector machine, generalized regression neural network, multi-linear regression (MLR), and multi-layer perceptron (MLP). Initially, climate data from 122 synoptic stations covering six and 30, main and sub basins were collected, and annual ETO values were computed using the Food and Agriculture Organization 56 (PMF 56) Penman–Monteith equation. The correlations between these values and 37 LSTIs were examined within lead times ranging from 7 to 12 months. Through a stepwise approach, the most influential predictor indices (LSTIs) were selected as input datasets for the MLMs. The findings revealed the significant influence of factors such as carbon dioxide (CO2), Atlantic multidecadal oscillation, Atlantic Meridional Mode, and East Atlantic on annual ETO. Overall, all MLMs performed well in terms of the Scatter Index during both training and testing phases across all sub-basins. Furthermore, the MLP and MLR models displayed superior performance compared to other models in the training and testing evaluations based on various assessment metrics. [ABSTRACT FROM AUTHOR]

Ocean oxygen content is decreasing with global change. A major challenge for modelling future declines in oxygen concentration is our lack of knowledge of the natural variability associated with marine oxygen inventory on interannual and multidecadal timescales. Here, we present 10 annually resolved 200 year-long records of denitrification, a marker of deoxygenation, from a varved sedimentary archive in the North Pacific oxygen minimum zone covering key periods over the last glacial–interglacial cycle. Spectral analyses on these records reveal strong signals at periodicities typical of today's Atlantic multidecadal oscillation. Modern subsurface circulation reanalyses regressed on the positive Atlantic and Pacific Climatic Oscillation indices further confirm that North Atlantic temperature patterns are the main control on the subsurface zonal circulation and therefore the most likely dominant driver of oxygen variability in the tropical Pacific. With currently increasing temperatures in the Northern Hemisphere high latitudes and North Atlantic, we suggest deoxygenation will intensify in the region. This study provides the longest annually resolved records of deoxygenation and productivity in the tropical Pacific and highlights the importance of North Atlantic climate oscillations on Pacific oxygen via its impact on the Pacific equatorial shallow overturning. [ABSTRACT FROM AUTHOR]

The disturbance of marine organism phenology due to climate change and the subsequent effects on recruitment success are still poorly understood, especially in migratory fish species, such as the Atlantic herring (Clupea harengus; Clupeidae). Here we used the commercial catch data from a local fisher over a 50‐year period (1971–2020) to estimate western Baltic spring‐spawning (WBSS) herring mean arrival time Q50 (i.e., the week when 50% of the total fish catches had been made) at their spawning ground within the Kiel Fjord, southwest Baltic Sea, and the duration of the spawning season for each year. The relationship between the seawater temperature in the Kiel Bight and other environmental parameters (such as water salinity, North Atlantic and Atlantic multidecadal oscillations) and Q50 was evaluated using a general linear model to test the hypothesis that fish arrived earlier after warm than cold winters. We also estimated the accumulated thermal time to Q50 during gonadal development to estimate the effects of seawater temperature on the variations of Q50. The results of this study revealed a dramatic decrease in herring catches within the Kiel Fjord since the mid‐1990s, as documented for the whole southwestern Baltic Sea. Warmer winter seawater temperature was the only factor related to an earlier arrival (1 week for one January seawater temperature degree increase) of herring at their spawning ground. The relationship was found for the first time on week 52 of the year prior to spawning and was the strongest (50% of the variability explained) from the fourth week of January (8 weeks before the mean Q50 among the studied years). A thermal constant to Q50 (~316°C day) was found when temperatures were integrated from the 49th week of the year prior to spawning. These results indicate that seawater temperature enhanced the speed of gonadal maturation during the latest phases of gametogenesis, leading to an early fish arrival under warm conditions. The duration of the spawning season was elongated during warmer years, therefore potentially mitigating the effects of trophic mismatch when fish spawn early. The results of this study highlight the altering effects of climate change on the spawning activity of a migratory fish species in the Baltic Sea where fast global changes presage that in other coastal areas worldwide. [ABSTRACT FROM AUTHOR]

The formation of dense water in the Aegean Sea is important as it affects the deep circulation and the hydrography of the Eastern Mediterranean Sea. In this study, the variability of dense water formation is investigated in relation to forcing mechanisms from 1947 to 2023 in the subbasins of the Aegean Sea, utilising in situ observations from various sources, which have been analysed in combination with satellite altimetry and reanalyses products. The analysis reveals that the Aegean Sea has been in a state of increased dense water formation since 2017 due to the combination of increased surface buoyancy loss and reduced Black Sea water inflow. Extremely high salinity has been recorded in the intermediate layers of the Aegean Sea since 2019. The anticyclonic circulation of the North Ionian gyre during 2017 and 2018 probably also contributed to the rapid transport of highly saline waters in the intermediate and, through dense water formation, the deep layers of the Aegean Sea in 2019. Until 2022, the dense waters formed during the peak of the Eastern Mediterranean Transient still occupied the bottom layers of some deep subbasins of the North and South Aegean; however, the 29.4   k g   m − 3 isopycnal in the North Aegean and the 29.3   k g   m − 3 isopycnal in the Southeastern Aegean have gradually deepened by 800 m, permitting the waters forming in the last ten years in the Aegean Sea to settle at ever greater depths. Temperature controls the density variability of the Cretan intermediate water up to the decadal time scale. Increased data availability since 2010 was sufficient to clarify that intrusions of dense water from the North–Central Aegean Sea contributed to the erosion of the Eastern Mediterranean transitional waters in the South Aegean Sea after 2017, as well as to raising the intermediate water masses of the South Aegean to shallower depths. The erosion of the transitional Mediterranean waters in the South Aegean Sea between 1947 and 1955 and 1973 and 1980 coincided with increased dense water formation in the North–Central Aegean Sea. During the peak of the Eastern Mediterranean Transient, the North Ionian circulation, the Black Sea water inflow, the Atlantic Multidecadal Oscillation, and the surface buoyancy fluxes favoured dense water formation in the Aegean Sea. [ABSTRACT FROM AUTHOR]

The Arabian Sea, notably the Sea of Oman, has exhibited a gradual warming trend since the twentieth century, expected to persist in the future, necessitating a climatological assessment for potential environmental disaster mitigation. This study conducts a comprehensive analysis using satellite-derived data on sea surface temperature (SST), Chlorophyll-a (Chl-a), sea level anomaly (SLA), and wind stress curl (WSC) to understand the region's climate dynamics. Phytoplankton (Chlorophyll-a) in the Sea of Oman plays a vital role in the ocean ecosystem, serving as primary producers and oxygen suppliers by fixing atmospheric carbon dioxide. Over the past four decade, the average Chl-a in the Sea of Oman was 3.06 mg/m3, with elevated levels (> 5.5 mg/m3) observed along coastal regions, peaking in summer and declining in winter. Over four decades, SST has risen by 0.658 °C on average, with the highest gradient magnitude observed along the coast. SLA has steadily increased exceeding 0.722 cm over the entire period (1993–2021). WSC shows seasonal variations, with high values (> 1 N/m2) in July and August and slightly lower values in winter. Furthermore, significant correlations between ocean variables and major climatic oscillations such as the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), El Nino-3.4 (Nino3.4), and the Dipole Mode Index (DMI) are identified, highlighting the intricate interplay shaping the Arabian Sea's ecosystem and providing critical insights for effective environmental management strategies. Implement integrated monitoring and adaptive management strategies to mitigate the impacts of climate variability on the Sea of Oman marine ecosystem. [ABSTRACT FROM AUTHOR]

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Sea level rise is challenging for coastal communities and land management decision makers. Understanding the patterns of regional variations at different temporal and spatial scales is key to implement adaptation plans that mitigate the local impacts of sea level rise. In this study, in situ observations from 14 tide gauges were complemented with satellite altimetry data to assess seasonality, multidecadal variability and long‐term trends in mean sea level around the Western Iberian Coast (WIC) and the Portuguese archipelagos (Azores and Madeira). Results show varying spatial seasonal patterns between regions, with minimum (maximum) sea level observed in April (September) at the islands and minimum (maximum) observed in July (November) at the WIC. The influence of coastal upwelling on the seasonal mean sea level variations was detected over mainland. Although the influence of atmospheric patterns was observed on sea level inter‐annual variability, the Atlantic Multidecadal Oscillation (AMO) showed a greater correlation with the sea level inter‐decadal patterns. Finally, the trend analysis confirmed widespread sea level rise along the mainland and around the islands, which has intensified in recent decades. The regions of La Coruña and Cascais showed trends that were similar to the global average sea level rise since 1993, but the mainland regional average pointed to lower rates of rise (2.00 ± 0.06 mm/year). This work reinforces the need for long‐term monitoring networks of sea level, ensuring the vertical stability of instruments and platforms. The implementation of regional adaptation plans to sea level rise is deeply dependent on high quality information. Plain Language Summary: Sea level is rising worldwide, and coastal communities are starting to have to deal with the effects of such change. However, the rate of sea level rise changes geographically and with time, so it is important to understand regional sea level variations, as it is what local communities directly experience. Important knowledge gaps remained regarding sea level variability along the Western Iberian Coast (WIC) and the Portuguese Islands. To overcome these, 14 long time series of sea level observations were used along with satellite data to study: (a) seasonal variations; (b) inter‐decadal patterns; and (c) long‐term trends in mean sea level across these regions. Different seasonal patterns were obtained: minimum and maximum sea level was reached 2/3‐month later at the WIC than along the islands. The influence of coastal upwelling on the seasonality over the WIC was confirmed. The multidecadal variation in ocean temperature had a strong influence on the inter‐annual variation in sea level. Lastly, sea level has been rising in almost all locations, but the WIC average rate was lower than the global average. This study highlights the need to monitor instrument stability and measurement quality as this will guarantee the implementation of effective regional adaptation plans. Key Points: Western Iberian Coast and islands with differences in phase and amplitude of the mean seasonal cycle, in part due to upwellingMultidecadal variation in ocean temperature with the strongest influence on the inter‐annual variation in sea level over the regionMainland regional average trend of 2.00 ± 0.06 mm/year lower than the global rise observed over the past 30 years [ABSTRACT FROM AUTHOR]

Abstract After precipitation, reference evapotranspiration (ETO) plays a crucial role in the hydrological cycle as it quantifies water loss. ETO significantly impacts the water balance and holds great importance at the basin level because of the spatial distribution of managing water resources. Large scale teleconnection indices (LSTIs) play a vital role by influencing climatic variables and can be pivotal in determining ETO and its predictive variables. This study aimed to model and forecast annual ETO in Iran’s basins by utilizing LSTIs and employing various machine learning models (MLMs) such as least squares support vector machine, generalized regression neural network, multi-linear regression (MLR), and multi-layer perceptron (MLP). Initially, climate data from 122 synoptic stations covering six and 30, main and sub basins were collected, and annual ETO values were computed using the Food and Agriculture Organization 56 (PMF 56) Penman–Monteith equation. The correlations between these values and 37 LSTIs were examined within lead times ranging from 7 to 12 months. Through a stepwise approach, the most influential predictor indices (LSTIs) were selected as input datasets for the MLMs. The findings revealed the significant influence of factors such as carbon dioxide (CO2), Atlantic multidecadal oscillation, Atlantic Meridional Mode, and East Atlantic on annual ETO. Overall, all MLMs performed well in terms of the Scatter Index during both training and testing phases across all sub-basins. Furthermore, the MLP and MLR models displayed superior performance compared to other models in the training and testing evaluations based on various assessment metrics.

Climatic oscillations affect fish population dynamics, ecological processes, and fishing operations in maritime habitats. This study examined how climatic oscillations affect catch rates for striped, blue, and silver marlins in the Atlantic Ocean. These oscillations are regarded as the primary factor influencing the abundance and accessibility of specific resources utilized by fishers. Logbook data were obtained from Taiwanese large-scale fishing vessels for climatic oscillations during the period 2005–2016. The results indicated that the effect of the Subtropical Indian Ocean Dipole on marlin catch rates did not have a lag, whereas those of the North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation, and Indian Ocean Dipole had various lags. Pearson's correlation analysis was conducted to examine the correlations between atmospheric oscillation indices and marlin catch rates, and wavelet analysis was employed to describe the influences of the most relevant lags. The results indicated that annual atmospheric fluctuations and their lags affected the abundance and catchability of striped, blue, and silver marlins in the study region. This, in turn, may affect the presence of these species in the market and lead to fluctuations in their prices in accordance with supply and demand. Overall, understanding the effects of climatic oscillations on fish species are essential for policymakers and coastal communities seeking to manage marine resources, predict changes in marine ecosystems, and establish appropriate methods for controlling the effects of climate variability. [ABSTRACT FROM AUTHOR]

Previous research has explored the impact of the Interdecadal Pacific Oscillation (IPO) and Atlantic Multidecadal Oscillation (AMO) on Antarctic surface air temperature (SAT) variability. However, a notable gap remains in our comprehension concerning the response of Antarctic SAT to the four phase combinations of IPO and AMO. In this study, we unveil unique patterns of Antarctic SAT anomalies during four distinct sub-periods based on the phases of IPO and AMO. Notably, Antarctic SAT anomalies exhibit a considerable seasonality, with the most pronounced (weakest) anomalies occurring during the austral winter (summer), a phenomenon consistent across all four sub-periods. These different anomalous SST patterns trigger varying convective rainfall patterns, consequently initiating distinct wavetrains that propagate into the Southern Ocean. These different wavetrains, in turn, induce variations in sea level pressure and surface wind fields, resulting in different Antarctic SAT anomalies primarily through mechanisms related to horizontal thermal advection and downward longwave radiation. Plain language summary: Understanding the variability in Antarctic surface air temperature (SAT) is crucial for unraveling the complex dynamics of the polar climate system and its broader implications for global climate patterns. Fewer studies highlighted the impacts of the four combinations of the phases of IPO and AMO on Antarctic SAT anomalies. In this study, we uncover distinct patterns of Antarctic SAT anomalies during four different periods based on the phases of IPO and AMO. We note that Antarctic SAT anomalies exhibit a considerable seasonality, with the most pronounced (weakest) anomalies occurring during the austral winter (summer), consistently across all four periods. The anomalous SST patterns during different periods trigger distinct wavetrains that propagate into the Southern Ocean, inducing variations in sea level pressure, surface wind fields, and Antarctic SAT anomalies. These findings bear substantial implications for the prediction of Antarctic seasonal SAT variations on interdecadal timescales. Key points: Antarctic SAT anomalies exhibit a considerable seasonality during the four combinations of the phases of the IPO and AMO. These different SST anomalies during the combinations trigger distinct wavetrains that propagate into the Southern Ocean. Different wavetrains induce anomalous sea level pressure and surface wind fields and Antarctic SAT through thermal advection and radiation. [ABSTRACT FROM AUTHOR]

Snow is particularly impacted by climate change and therefore there is an urgent need to understand the temporal and spatial variability of depth of snowfall (HN) trends. However, the analysis of historical HN observations on large‐scale areas is often impeded by lack of continuous long‐term time series availability. This study investigates HN trends using observed time series spanning the period 1920–2020 from 46 sites in the Alps at different elevations. To discern patterns and variations in HN over the years, our analysis focuses also on key parameters such as precipitation (P), mean air temperature (TMEAN), and large‐scale synoptic descriptors, that is, the North Atlantic Oscillation (NAO), Arctic Oscillation (AO) and Atlantic Multidecadal Oscillation (AMO) indices. Our findings reveal that in the last 100 years and below 2000 m a.s.l., despite a slight increase in winter precipitation, there was a decrease in HN over the Alps, especially for southern and low‐elevation sites. The South‐West and South‐East regions experienced an average loss of 4.9 and 3.8%/decade, respectively. A smaller relative loss was found in the Northern region (2.3%/decade). The negative HN trends can be mainly explained by an increase of TMEAN by 0.15°C/decade. Most of the decrease in HN occurred mainly between 1980 and 2020, as a result of a more pronounced increase in TMEAN. This is also confirmed by the change of the running correlation between HN and TMEAN, NAO, AO over time, which until 1980 were not correlated at all, while the correlation increased in later years. This suggests that in more recent years favourable combinations of temperature, precipitation, and atmospheric pattern have become more crucial for snowfall to occur. On the other hand, no correlation was found with the AMO index. [ABSTRACT FROM AUTHOR]

This study investigates the long-term temporal patterns of sea level changes by analyzing monthly tide gauge data from 1950 to 2022 (42 to 72 years) along the European coastline and monthly altimetry data from 1992 to 2024 in the surrounding European seas. The primary focus is on signals with periods longer than 5 years. The application of wavelet-based approaches and multiresolution analysis has enabled the isolation of signals with periods of approximately 8 and 16 years. However, the latter has only been observed in tide gauge data, as the altimetry time series is not sufficiently long. The same analysis was applied to the North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation (AMO) indices, which enabled the detection of the same signals. The reported multiyear signals of sea level are correlated with NAO and AMO indices, particularly during the period spanning from 1975 to 2010. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs), especially intense TCs, pose serious threats to life and property particularly in the affected coastal regions. Understanding the factors determining the TC intensification rate (IR) remains a great challenge. This study identifies the dominant factors responsible for the observed significant increase in TC IR over the western North Pacific in recent decades using the energetically based dynamical system model of TC intensification. It is found that the environmental dynamical efficiency mainly contributed by vertical wind shear and upper‐level divergence is responsible for the long‐term changes in TC IR during the strong TC stage, but it played a secondary role in the long‐term changes in IR during the weak TC stage. The latter were primarily contributed by the maximum potential intensity, which is primarily determined by sea surface temperature. Results also strongly suggest that global warming is the primary driver of the long‐term changes in TC IR. Plain Language Summary: Tropical cyclone (TC) intensification is closely associated with the extent of damage caused by these storms. The TC intensification rate (IR) over the western North Pacific (WNP), particularly in tropical regions, has shown a significant increasing trend in recent decades. This study employs an energetically based dynamical system model of TC intensification to quantitatively unveil factors driving the long‐term changes in TC IR over the WNP. Results show that the thermodynamic and dynamic factors exhibit different effects at different stages of TCs. The maximum potential intensity is found to be the most important factor contributing to the long‐term changes in TC IR at the weak TC stage, while the environmental dynamical efficiency, mainly governed by vertical wind shear and upper‐level divergence, plays the predominant role at the strong TC stage. Although the long‐term changes in TC IR over the WNP result from a combination of global warming and internal climate variabilities, global warming is the primary driver of the long‐term changes in TC IR based on quantitative analysis. The Atlantic Multidecadal Oscillation exhibits a secondary influence, while the Pacific Decadal Oscillation contributes little. These results can help enhance forecasting capabilities and future projections of TC activities. Key Points: The environmental dynamical efficiency dominantly controls the long‐term changes in TC intensification rate during the strong TC stageDuring the weak TC stage, the long‐term changes in intensification rate are primarily driven by the maximum potential intensityGlobal warming is the primary driver of the long‐term changes in TC intensification rate [ABSTRACT FROM AUTHOR]

Summer Arctic sea ice is declining rapidly but with superimposed variability on multiple time scales that introduces large uncertainties in projections of future sea ice loss. To better understand what drives at least part of this variability, we show how a simple linear model can link dominant modes of climate variability to low-frequency regional Arctic sea ice concentration (SIC) anomalies. Focusing on September, we find skillful projections from global climate models (GCMs) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) at lead times of 4–20 years, with up to 60% of observed low-frequency variability explained at a 5-yr lead time. The dominant driver of low-frequency SIC variability is the interdecadal Pacific oscillation (IPO) which is positively correlated with SIC anomalies in all regions up to a lead time of 15 years but with large uncertainty between GCMs and internal variability realization. The Niño-3.4 index and Atlantic multidecadal oscillation have better agreement between GCMs of being positively and negatively related, respectively, with low-frequency SIC anomalies for at least 10-yr lead times. The large variations between GCMs and between members within large ensembles indicate the diverse simulation of teleconnections between the tropics and Arctic sea ice and the dependence on the initial climate state. Further, the influence of the Niño-3.4 index was found to be sensitive to the background climate. Our results suggest that, based on the 2022 phases of dominant climate variability modes, enhanced loss of sea ice area across the Arctic is likely during the next decade. Significance Statement: The purpose of this study is to better understand the drivers of low-frequency variability of Arctic sea ice. Teasing out the complicated relationships within the climate system takes a large number of examples. Here, we use 42 of the latest generation of global climate models to construct a simple linear model based on dominant named climate features to predict regional low-frequency sea ice anomalies at a lead time of 2–20 years. In 2022, these modes of variability happen to be in the phases most conducive to low Arctic sea ice concentration anomalies. Given the context of the longer-term trend of sea ice loss due to global warming, our results suggest accelerated Arctic sea ice loss in the next decade. [ABSTRACT FROM AUTHOR]

Observational analyses demonstrate that the Ural persistent positive height anomaly event (PAE) experienced a decadal increase around the year 2000, exhibiting a southward displacement afterward. These decadal variations are related to a large-scale circulation shift over the Eurasian Continent. The effects of underlying sea ice and sea surface temperature (SST) anomalies on the Ural PAE and the related atmospheric circulation were explored by Atmospheric Model Intercomparison Project (AMIP) experiments from the Coupled Model Intercomparison Project Phase 6 and by sensitivity experiments using the Atmospheric General Circulation Model (AGCM). The AMIP experiment results suggest that the underlying sea ice and SST anomalies play important roles. The individual contributions of sea ice loss in the Barents-Kara Seas and the SST anomalies linked to the phase transition of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) are further investigated by AGCM sensitivity experiments isolating the respective forcings. The sea ice decline in Barents-Kara Seas triggers an atmospheric wave train over the Eurasian mid-to-high latitudes with positive anomalies over the Urals, favoring the occurrence of Ural PAEs. The shift in the PDO to its negative phase triggers a wave train propagating downstream from the North Pacific. One positive anomaly lobe of the wave train is located over the Ural Mountains and increases the PAE there. The negative-to-positive transition of the AMO phase since the late-1990s causes positive 500-hPa height anomalies south of the Ural Mountains, which promote a southward shift of Ural PAE. [ABSTRACT FROM AUTHOR]

The North China Plain, a crucial region for winter wheat cultivation, exhibits yield deeply affected by the variability of winter precipitation. This study examines the interdecadal variation in the relationship between the North Pacific Oscillation (NPO) and winter precipitation in the North China Plain (WPNC). Utilizing the East Asian winter monsoon (EAWM) as an intermediary, we have observed an interdecadal variation in the relationship between WPNC and NPO after the late‐1990s. Before 1994, the relationship between NPO and EAWM/WPNC both exhibited a significant positive correlation, while after 1998, their correlation decreased and became insignificant. This interdecadal variation can be attributed to the eastward shift of the winter NPO's location after the late‐1990s. Our investigation found that the eastward shift of the NPO's location is closely linked to the phase transition of the Atlantic Multidecadal Oscillation (AMO) phase after the late‐1990s. The warm sea surface temperatures (SST) over the North Atlantic cause ascending motion, and the outflows induce a compensatory anticyclonic circulation over the North Pacific. The easterlies anomaly on the south side of the anticyclone weakens climatological westerlies, increasing SST and upper‐level air temperatures in the North Pacific through the wind–evaporation–SST–longwave radiation effect. The resulting warmer air strengthens the atmospheric temperature gradient, enhancing the vertical integration of baroclinic energy conversion and shifting the NPO eastward, reducing its correlation with WPNC. [ABSTRACT FROM AUTHOR]

The diverse climates, distribution of snow and glaciers, and geographic locations directly affect the runoff response to climate change in the upper basins of the Third Pole. At present, a comprehensive analysis of runoff variations and their distinct responses to climate change in the westerlies- and monsoon-dominated upper basins is still lacking. This study comprehensively analyzed annual runoff variations in westerlies-dominated basins (the upper basins of the Aksu (UAKS), Syr Darya (USRD), Yarkant (UYK), Hotan (UHT), Amu Darya (UAMD), and Indus (UI)) and monsoon-dominated basins (the upper basins of the Yangtze (UYA), Yellow (UYE), Lancang (ULC), Nujiang (UNJ), and Yarlung Zangbo (UYZ)) of the Third Pole from 1961 to 2015. Using multi-source meteorological data and large-scale circulation factors, this study investigated the divergent responses of runoff in the upper basins to climate change, and explored the large-scale circulation mechanisms underlying runoff variations in these upper basins. The results showed that: (1) The annual runoff in the majority of upper basins (except for the UYE and UYZ) exhibited an increasing trend, and the annual runoff in the UAKS, UYK, and UI showed a significant increasing trend from 1961 to 2015. The annual runoff in the upper basins of the Third Pole changed abruptly from decreasing to increasing between the 1980s and 2000s, with the exception of the UYE. (2) The runoff in the monsoon-dominated upper basins has been controlled primarily by changes in precipitation over the past 55 years. In contrast, the runoff in the westerlies-dominated upper basins exhibited three distinct long-term responses to climate change: temperature-dominated (UYK and UHT), precipitation-dominated (USRD and UAMD), and the combined influence of precipitation and temperature (UAKS and UI). Since the 1960s, the sensitivity of runoff to warm season temperature changes in the most westerlies-dominated upper basins has decreased, while the response of runoff to precipitation changes has intensified. (3) The study revealed the connection between large-scale circulation, climate, and runoff in the upper basins of the Third Pole. The Atlantic Multidecadal Oscillation, the Westerly Index, and the El Niño-Southern Oscillation predominantly impact the precipitation or temperature in the upper basins of the Third Pole, which in turn affect the runoff variations in the upper basins dominated by either the westerlies or the monsoon. This study will be a valuable scientific reference for water resource management and climate change adaptation for both the westerlies- and monsoon-dominated upper basins in the Third Pole. [ABSTRACT FROM AUTHOR]

The Southern Ocean connects the Pacific, Atlantic, and Indian Oceans, serving as a key hub for the global overturning circulation. The climate of the Southern Ocean is closely linked to the low-latitude equatorial Pacific, as well as the highlatitude regions of the North Atlantic, making it an important component of the global climate system. Due to the interactions of various processes such as atmospheric, oceanic, and ice cover, the Southern Ocean exhibits a complex and variable sea surface temperature structure. Satellite observations indicate that since 1980, the sea surface temperature of the Southern Ocean has been cooling, contrary to the global warming trend. However, due to the relatively short length of satellite observations, the specific mechanisms are not yet clear. Here, we used the EOF method to analyze sea surface temperature data since 1870 (HadISST1 and ERSSTV5), with three main separated modes explaining over 70% of the sea temperature variability. Among them, the first mode shows widespread positive sea surface temperature anomalies in the Southern Ocean, with a time series change consistent with global temperature anomalies, representing a mode of global warming. The second mode corresponds to the Atlantic Multidecadal Oscillation (AMO) but with a lag of approximately 4 years. The third mode is consistent with the variability of the El Niño-Southern Oscillation (ENSO). Furthermore, our study indicates that despite the ongoing global warming since 1980, the negative phase of AMO and positive phase of ENSO may counteract the effects of global warming, leading to an overall cooling trend in the sea surface temperature of the Southern Ocean. [ABSTRACT FROM AUTHOR]

The role of chaos in the climate system has been dismissed as high dimensional turbulence and noise, with minimal impact on long-term climate change. However theory and experiment show that chaotic systems can be reduced or "controlled" from high to low dimensionality by periodic forcings and internal feedbacks. High dimensional chaos is somewhat featureless. Conversely low dimensional borderline chaos generates pattern such as oscillation, and is more widespread in climate than is generally recognised. Thus, oceanic oscillations such as the Pacific Decadal and Atlantic Multidecadal Oscillations are generated by dimensionality reduction under the effect of known feedbacks. Annual periodic forcing entrains the El Niño Southern Oscillation. Numerous oceanic and Arctic centered climate oscillations have recently been observed to exhibit delayed synchrony in the manner of a "stadium wave". Here, three studied systems with chaotic-nonlinear dynamics (physico-chemical and biological) are reviewed which show dimensionality reduction as a source of emergent pattern. This alongside mathematical studies of chaotic Lorenz models whose trajectories escape under controlling influences from chaotic to non-chaotic phase space regions – incurring a dimensional haircut in the process. Control of chaos by external and internal influences results in lowered phase-space dimensionality with emergent dissipative structure. Dimensionality reduction is proposed as a source of natural climate change. Thus the effect of astrophysical periodic forcing and oceanic and other feedbacks in climate is not so much to generate chaos as to lower dimensionality in a chaotic system, engendering the export of entropy and emergent regular spatiotemporal pattern. [ABSTRACT FROM AUTHOR]

The Pacific Decadal Oscillation (PDO), the dominant pattern of sea surface temperature anomalies in the North Pacific basin, is an important low-frequency climate phenomenon. Leveraging data spanning from 1871 to 2010, we employed machine learning models to predict the PDO based on variations in several climatic indices: the Niño3.4, North Pacific index (NPI), sea surface height (SSH), and thermocline depth over the Kuroshio–Oyashio Extension (KOE) region (SSH_KOE and Ther_KOE), as well as the Arctic Oscillation (AO) and Atlantic Multi-decadal Oscillation (AMO). A comparative analysis of the temporal and spatial performance of six machine learning models was conducted, revealing that the Gated Recurrent Unit model demonstrated superior predictive capabilities compared to its counterparts, through the temporal and spatial analysis. To better understand the inner workings of the machine learning models, SHapley Additive exPlanations (SHAP) was adopted to present the drivers behind the model's predictions and dynamics for modeling the PDO. Our findings indicated that the Niño3.4, North Pacific index, and SSH_KOE were the three most pivotal features in predicting the PDO. Furthermore, our analysis also revealed that the Niño3.4, AMO, and Ther_KOE indices were positively associated with the PDO, whereas the NPI, SSH_KOE, and AO indices exhibited negative correlations. [ABSTRACT FROM AUTHOR]

We used the Meteorological Research Institute Earth System Model to investigate land precipitation and net primary production (NPP, proxy for agricultural production here) in terms of food and water security. In the preindustrial state, the largest decrease in Southeast Asian precipitation (> 20%) occurs along with the largest El Niño and positive phase of the Atlantic multidecadal oscillation, consistent with the 1876-78 Great Drought, leading to the largest decrease in NPP (~ 20%); >2 standard deviations, extreme dryness and crop failure. In relatively arid regions (e.g., India and northeastern Brazil), the largest decreases in precipitation and NPP reach ≥ 50%, particularly 80 ~ 90% in Deccan, India. In the 21st century warming projection (Shared Socioeconomic Pathways 5-8.5, the largest CO2 emission scenario), the interannual variability of precipitation and NPP in Monsoon Asia increase under the influence of enhanced El Niño-Southern Oscillation. Although the increased precipitation variability indicates more frequent severer droughts than in the preindustrial state, this severity does not influence NPP so much: the increased NPP variability is negligible compared to the significant increase in normal NPP by CO2 fertilization effect, which indicates usually rich harvests. Compared to a recent severe crop failure (− 25% in Japan in 1993), the simulated preindustrial drought-induced NPP decreases of ≥ 50% in parts of low latitudes are extraordinarily large enough to correspond to devastating crop failures. The model indicates that great famines before the 20th century were natural in origin, and that manmade factors, such as harsh taxes and hoarding and export of grain, made the famines more devastating. [ABSTRACT FROM AUTHOR]

Disentangling community responses to multiple stressors in a warming context is one of the most challenging tasks ecologists face. Taking advantage of a long‐term (1989–2017) and intensive fish monitoring survey (N = ~900K from 804 seines‐day), we present a comprehensive analysis on the dynamics of coastal fish communities in Jamaica Bay, New York, by addressing multiple dimensions of community change that although closely related are rarely considered in a single work. Specifically, we tested hypotheses about changes in composition, composition variability and community functional attributes, and the role of environmental drivers acting at different temporal scales. Our analyses suggest two decoupled community dynamics triggered by two different extreme events. First, the 1999 Atlantic Multidecadal Oscillation phase switch caused an abrupt shift from a single‐species dominance to intermittent co‐dominance, with species preferring higher temperatures, a shift that has persisted in time but that may be cyclical at a multidecadal scale. Second, the 2012 heat wave promoted an abrupt collapse of rare and cold‐water species, and the sudden arrival of warmer‐water species in a portion of the community that was already increasingly variable due to long‐term warming. Functionally, the entire community subtly shifted toward species with faster turnover and lower trophic levels. Our work sheds light on the complex responses of biological communities to warming in terms of the impacts on composition, its temporal variability, and its functional dimension, by disentangling the interplay of long‐term environmental trends such as warming, multidecadal cycles, and extreme events on different portions (i.e., dominant and rare thermal species) of the community. [ABSTRACT FROM AUTHOR]

In recent years, there has been intense debate in the literature as to whether the Atlantic Multidecadal Oscillation (AMO) is a genuine representation of natural climate variability or is substantially driven by external factors. Here, we perform an analysis of the influence of external (natural and anthropogenic) forcings on the AMO behaviour by means of a linear Granger causality analysis and by a nonlinear extension of this method. Our results show that natural forcings do not have any causal role on AMO in both linear and nonlinear analyses. Instead, a certain influence of anthropogenic forcing is found in a linear framework. [ABSTRACT FROM AUTHOR]

The rainfall regime is a critical factor in the Yucatan Peninsula, as the spatial and multiannual variability of rainfall is a major concern, particularly for crops. Variability in the rainy season was examined considering the onset and demise of the annual rainy season, the total rain volume, the rainfall season duration and the intense precipitation events recorded in meteorological stations (1978–2020). We analysed individual time series and calculated the long‐term trend. Additionally, we explored the relationship between each summer rainfall characteristic and several oceanographic indices using multivariate techniques. We also developed a Trans‐Isthmic Index from the relationship between the El Niño–Southern Oscillation and the Atlantic Multidecadal Oscillation. This index allows for determining the effect of the overall influence of the ocean on climate. The timeseries analysis revealed a high interannual variability and long‐term positive trends concerning the duration of the rainy season with earlier onset and later demise, and the total rainfall volume and also a positive trend for the occurrence of heavy precipitation suggesting a shift in intra‐annual patterns. Spatially, the analysis revealed clusters of stations with a similar variation, probably related to the AMO, NIÑO3.4 or TII indices. The spatial pattern was confirmed by analysing CHIRPS gridded precipitation data. Our results show that wetter conditions are associated with lower temperatures in the equatorial Pacific and warmer conditions in the Atlantic. [ABSTRACT FROM AUTHOR]

The interdecadal variability of tropical cyclone precipitation (TCP) over the western North Pacific (WNP) has not been thoroughly explored in previous studies. Here, we show that the TCP variations are modulated by both the Atlantic Multidecadal Oscillation (AMO) and Interdecadal Pacific Oscillation (IPO) as evidenced by reanalysis data and model experiments. A clustering analysis of tropical cyclone tracks shows that the AMO dominates a dipole pattern of TCP anomalies in the South China Sea and along the coastal eastern China. Meanwhile, the IPO dominates TCP over the southeastern WNP. Further analyses show that the AMO, particularly its extratropical component, affects TCP over the WNP by triggering an eastward‐propagating Rossby‐wave train, resulting in a pair of anomalous gyres over the WNP. Contrastly, the IPO modulates TCP by stimulating tropical circulation anomalies via the tropical pathway. These findings shed light on improving near‐term TCP forecast and its regional influence on East Asia. Plain Language Summary: Tropical cyclone precipitation (TCP) is a topic of great concern owing to its destructive nature. Here, we find that TCP over the western North Pacific (WNP) exhibits significantly interdecadal variability and regional characteristics, a departure from the previous studies focusing on the entire WNP. The Atlantic Multidecadal Oscillation (AMO) mainly causes a dipole response of decadal changes in TCP over the South China Sea and coastal eastern China. Moreover, the AMO primarily affects TCP over the sub‐regional WNP through the extra‐tropical pathway by exciting a Rossby wave train. On the other hand, the Interdecadal Pacific Oscillation (IPO) predominantly affects TCP over the southeastern part of the WNP through the tropical pathway, inducing significant circulation anomalies over the tropical WNP. These findings offer valuable insights for future research and forecasting of TCP. Key Points: The Atlantic Multidecadal Oscillation (AMO) contributes to the dipole pattern of interdecadal tropical cyclone precipitation (TCP) anomalies over the South China Sea and coastal eastern ChinaThe AMO affects TCP by triggering a westerly jet‐guided Rossby‐wave train via the extra‐tropical pathwayThe Interdecadal Pacific Oscillation dominates the TCP anomalies over the southeastern part of western North Pacific by modulating tropical circulation anomalies [ABSTRACT FROM AUTHOR]

The Atlantic Multidecadal Oscillation (AMO) has garnered attention for its important role in shaping surface air temperature (SAT) patterns over Eurasia. While Eurasian winter SAT was traditionally attributed to changes in large-scale atmospheric circulations associated with the AMO, a careful examination of the latest unforced CMIP6 simulations in this study unveils a significant contribution of the AMO's thermodynamic effects. Specifically, the heat released from the North Atlantic Ocean and transported to northern Eurasia through westerlies takes precedence over the effect of dynamic Rossby waves, resulting in warm (cold) phases during positive (negative) AMO cycles, along with increased (decreased) warm extremes and reduced (enhanced) cold extremes. This study contributes to an improved understanding of the dominating mechanism of the AMO's impact on Eurasian SAT. [ABSTRACT FROM AUTHOR]

Showcasing the fishery ecosystem trajectory framework, this study seeks to understand the complex interplay between environmental, socioeconomic, and management factors in a large marine ecosystem as they relate to the status, structure, and function of living marine resources over time. Utilizing this framework, a historical accounting of a fishery ecosystem’s shifting stable states can be developed to describe the evolution of resources and identify apparent temporal controls. To that end, approximately three decades of data, spanning 1986–2013, were drawn from the 2017 ecosystem status report for the United States’ Gulf of Mexico (GoM) and used here as a case study. Analyses revealed a capricious system with ten unique fishery regime states over the 28- year period. The fishery ecosystem trajectory was broadly characterized by gradual and persistent changes, likely fueled by exploitation trends. However, a mid-1990s paradigm shift in the dynamics controlling the system-wide organization of resources resulted in an apparent recovery trajectory before leading to continued differentiation relative to its 1986 baseline configuration. This “Humpty Dumpty” ecosystem trajectory signifies permanent alterations akin to the nursery rhyme protagonist’s unrecoverable fall. Anthropogenic factors identified as influential to resource organization included artificial reef prevalence and recreational fishing pressure, while regional effects of the Atlantic Multidecadal Oscillation’s warm phase transition after 1995 and rising sea surface temperatures in the GoM were also deemed notable. Conspicuously, the paradigm shift timing was coincident with effective implementation of annual catch limits due to the 1996 Sustainable Fisheries Act, highlighting the importance of the robust regulatory environment in this region. While these results describe the GoM fishery ecosystem’s vulnerability to shifting environmental and socioeconomic conditions, they also underscore its resources’ resilience, likely rooted in their complexity and diversity, to the rapidly evolving pressures observed throughout the study period. This work emphasizes the necessity of cautious, adaptive management strategies for large marine ecosystems, particularly in the face of climate-related uncertainties and species’ differential responses. It provides insight into the GoM fishery ecosystem’s dynamics and illustrates a transferable approach for informing ecosystem-based management strategies, sustainable practices, and decision making focused on preserving ecologically, economically, and culturally vital marine resources. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The evaluation and monitoring of drought, a complex disaster, are essential issues for the planning of agricultural activities and the operation and management of water resources. In this study, the meteorological drought of the Black Sea region in northern Turkey is evaluated with the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) methods at 3-, 6-, and 12-month time scales. Meteorological parameters obtained between 1965 and 2019 from 28 meteorological observation stations are used to analyze the drought. Drought-wet period percentages, percentages of occurrence of drought classes, critical period, and negative peak index values are investigated. As a result of the study, it is observed that the percentage of drought occurrence at all time scales is higher than 50% at two stations in the study region, which received precipitation above the average of Turkey. The sum of the extreme drought (ED) and severe drought (SD) values throughout the region is approximately 15% for the whole area. There is a high correlation coefficient, 97.8, 97.6, and 97.3 for the 3-, 6-, and 12-month time scales, respectively, between the SPI and RDIst methods in the evaluation of meteorological drought in the Black Sea region, which is generally a rainy region. It is determined that with the increase in the time scale, the percentage of ED occurrence increased and the risk level of the region around RDI and 17089 station is the highest. It has been determined that the correlation between oscillation indices and meteorological drought indices for the Black Sea region is almost non-existent. The highest correlation value between the oscillation and meteorological drought indices in the region is obtained with the Atlantic Multidecadal Oscillation (AMO). [ABSTRACT FROM AUTHOR]

As a feature of global warming, climate change has been a severe issue in the 21st century. A more comprehensive reconstruction is necessary in the climate assessment process, considering the heterogeneity of climate change scenarios across various meteorological elements and seasons. To better comprehend the change in minimum temperature in winter in the Jinsha River Basin (China), we built a standard tree-ring chronology from Picea likiangensis var. balfouri and reconstructed the regional mean minimum temperature of the winter half-years from 1606 to 2016. This reconstruction provides a comprehensive overview of the changes in winter temperature over multiple centuries. During the last 411 years, the regional climate has undergone seven warm periods and six cold periods. The reconstructed temperature sensitively captures the climate warming that emerged at the end of the 20th century. Surprisingly, during 1650–1750, the lowest winter temperature within the research area was about 0.44 °C higher than that in the 20th century, which differs significantly from the concept of the "cooler" Little Ice Age during this period. This result is validated by the temperature results reconstructed from other tree-ring data from nearby areas, confirming the credibility of the reconstruction. The Ensemble Empirical Mode Decomposition method (EEMD) was adopted to decompose the reconstructed sequence into oscillations of different frequency domains. The decomposition results indicate that the temperature variations in this region exhibit significant periodic changes with quasi-3a, quasi-7a, 15.5-16.8a, 29.4-32.9a, and quasi-82a cycles. Factors like El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and solar activity, along with Atlantic Multidecadal Oscillation (AMO), may be important driving forces. To reconstruct this climate, this study integrates the results of three machine learning algorithms and traditional linear regression methods. This novel reconstruction method can provide valuable insights for related research endeavors. Furthermore, other global climate change scenarios can be explored through additional proxy reconstructions. [ABSTRACT FROM AUTHOR]

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Abstract The upper reaches of the Yangtze River Basin (UYRB) are famous for their hydropower generation and water resources in China, relying greatly on precipitation. The UYRB summer precipitation has decreased since the early 2000s and has been exposed to a particularly dry period in the most recent two decades. By analyzing the long‐term variability from the beginning of the 20th Century, we found that the precipitation exhibits a profound periodic interdecadal variation, with a significant cycle of 30–50 years. The interdecadal variability of precipitation is shown to be significantly modulated by both the Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), exerting their impact through related circulation anomalies. Moreover, the periodical nature of the UYRB precipitation variation and its correlation with AMO/PDO suggest that the UYRB might enter a wet period in the forthcoming decade, i.e. rich in hydroelectric resources but a high risk of flood.

Regional weather and climate are generally impacted by global climatic phenomenon′s. Understanding the impact of global climate phenomenon′s on an atmospheric branch of the hydrological cycle is crucial to make advances in skillful precipitation forecast. The present study adopts a multiscale approach based on wavelets for unravelling the linkages between teleconnections and atmospheric moisture transport over homogeneous regions of Indian sub-continent. We investigated linkages between atmospheric moisture transport quantified as monthly integrated water vapor transport (IVT) during 1951–2022 over selected homogeneous regions and eight large scale climate oscillations using wavelet and global wavelet coherence. Our results indicate significant heterogeneity in linkages across different regions and across multiple timescales. In particular, the Indian Ocean Dipole (IOD) influence monthly IVT at intra-annual to inter-annual scale over all regions. The El Niño–Southern Oscillation (ENSO) have strong connection to monthly IVT at inter-annual scale whereas over west central region both IOD and ENSO strongly influence IVT at inter-decadal scale. While the Atlantic Multi-Decadal Oscillation and Pacific Decadal Oscillation have an impact on IVT in the north-east and southern regions, the Arctic Oscillation and North Atlantic oscillation have a strong inter-annual connection to IVT, majorly in the northwest and hilly regions. Overall, the methodology offers an effective approach for capturing the dynamics of atmospheric moisture transport in time–frequency space and provide a practical reference for prediction of atmospheric moisture transport linked precipitation over different regions of Indian subcontinent. [ABSTRACT FROM AUTHOR]

Extreme events, such as droughts, are influenced by climate variability modes such as El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multi‐decadal oscillation (AMO) and Equatorial Indian Ocean Oscillation (EQUINOO). Due to the significant interdependency among the climatic indices at various frequencies, a time‐frequency framework is necessary to better understand the teleconnection. The present study evaluates the association between climate variability modes and drought index in India using different variants of wavelet analysis such as wavelet coherence analysis (WCA), partial wavelet coherence analysis (PWCA), multiple wavelet coherence analysis (MWCA) and wavelet reconstruction methods. In this study, four major climatic indices (ENSO, PDO, AMO, EQUINOO) and the drought index, standard precipitation index (SPI), at four different monthly time periods (1, 3, 6 and 12) are considered. The results from the WCA analysis highlight significant teleconnection spectra for ENSO, PDO and EQUINOO at 2–8, 8–16 and 16–32 year time‐frequency bands. Further, PWCA results reveal significant interdependency in the teleconnection of ENSO and PDO at all the scales, while ENSO and EQUINOO are found to be independent modes of interannual drought variability in India. Finally, MWCA results show that the combination of EQUINOO and ENSO better explains the interannual variability of droughts in Northwest and Central northeast India. The results of this study will help improve drought prediction and early warning systems in India, by selection of appropriate climatic oscillations for different regions in India. [ABSTRACT FROM AUTHOR]

This study used observed rainfall, ERA5 reanalysis, and CMIP6 model datasets to investigate the interdecadal variation and underlying mechanism of persistent heavy rainfall (PHR) over the Huaihe River Basin (HRB) in China during July–August, and to examine the role of the Atlantic Multidecadal Oscillation (AMO) in modulating such rainfall. The results indicate that PHR over the HRB exhibited a marked interdecadal variation. The interdecadal increase in PHR was found attributable primarily to interdecadal enhancement of ascending motion, which might have been due to external forcing by the AMO. The AMO can trigger upper-tropospheric mid–high-latitude Rossby wave trains that can lead to an upper-tropospheric anticyclone and a lower-tropospheric cyclone configuration over the HRB. Increased warm advection and greater transport of water vapor from lower latitudes, caused by enhanced southerlies in the middle–lower troposphere over the HRB, can also lead to enhanced ascending motion over the HRB. Meanwhile, an anomalous cyclone over northeastern China triggered by AMO can transport cold air from higher latitudes to the HRB, boosting convection and promoting the development and duration of PHR. By affecting sea surface temperature in the western North Pacific Ocean, the AMO can also indirectly cause a meridional teleconnection pattern in the lower troposphere, which increases the transport of water vapor to the HRB. Numerical model experiments can reproduce both the interdecadal variations in PHR and the mechanisms of the influence of the AMO on PHR, providing a reliable foundation for understanding and forecasting PHR over the HRB. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau vortices (TPVs) are mesoscale weather systems active at the near-surface of the Tibetan Plateau (TP), which are one of the major precipitation-producing systems over the TP and its surrounding areas. TPVs mainly occur in the warm season from May to September. In this paper, we investigated the interdecadal change of TPVs in the warm seasons of 1979–2020 with the six widely used reanalysis datasets. A significant change of the TPVs frequency appears around the mid-1990s, associated with less TPVs during 1979–1995 and more TPVs during 1996–2020, which is constant among the multiple reanalysis datasets. The abrupt change of TPVs is caused by a transition of the Atlantic Multi-decadal Oscillation (AMO) from a cold phase to a warm phase in the mid-1990s. The shift of AMO leads to a silk-road pattern-like wave train and a spatially asymmetric change of tropospheric temperature. It modifies the intensity of the subtropical westerly jet and the TP heating, leading to the interdecadal change of TPV activities. [ABSTRACT FROM AUTHOR]

The current reconstructions of the Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO) primarily rely on marine sediment proxies. However, the limited resolution of these records makes it difficult to precisely understand the short‐term dynamics of the PDO and AMO, and consequently, their influence on global climate. This study unveils two new Holocene reconstructions of AMO and PDO derived from a large‐scale compilation of speleothem isotope records (δ18Os) from Chinese monsoon region, in which spatial patterns of summer rainfall are generally accepted as good indicators of internal variability. Principal component analysis applied to Chinese δ18Os records identifies the first principal component as representative of Holocene Asian monsoon (AM) variation. This data‐driven approach reveals a significant shift in hydroclimatic conditions after 8.2 ka, potentially providing valuable insights into the underlying forcing mechanisms driving these changes. The remanent components, which show spatial rainfall patterns, are effectively validated through independent records of AMO and PDO derived from the previous paleo‐proxy based reconstructions and model simulations. The present reconstructions suggest a significantly enhanced stability of the AMO and PDO in the middle Holocene, which may explain the concurrent more stable and optimum climate observed in the AM region. These findings also imply that the Holocene AM intensity recorded in Chinese cave records is largely controlled by external forcing, whereas the regionally heterogenous rainfall is regulated by internal variability. The successful attempt on the Holocene AMO and PDO reconstructions indicates an effective isolation between different modes of climate variability from paleoclimate records. Key Points: Different modes of climate variability are isolated from a large‐scale compilation of Chinese speleothem δ18O recordsHolocene high‐resolution Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation variations are reconstructed based on Chinese speleothem δ18O recordsHigh stability of internal variability in the middle Holocene may explain the Holocene climate optimum [ABSTRACT FROM AUTHOR]

Arctic warming has significant environmental and social impacts. Arctic long‐term warming trend is modulated by decadal‐to‐multidecadal variations. Improved understanding of how different external forcings and internal variability affect Arctic surface air temperature (SAT) is crucial for explaining and predicting Arctic climate changes. We analyze multiple observational data sets and large ensembles of climate model simulations to quantify the contributions of specific external forcings and various modes of internal variability to Arctic SAT changes during 1900–2021. We find that the long‐term trend and total variance in Arctic‐mean SAT since 1900 are largely forced responses, including warming due to greenhouse gases and natural forcings and cooling due to anthropogenic aerosols. In contrast, internal variability dominates the early 20th century Arctic warming and mid‐20th century Arctic cooling. Internal variability also explains ∼40% of the recent Arctic warming from 1979 to 2021. Unforced changes in Arctic SAT are largely attributed to two leading modes. The first is pan‐Arctic warming with stronger loading over the Eurasian sector, accounting for 70% of the unforced variance and closely related to the positive phase of the unforced Atlantic Multidecadal Oscillation (AMO). The second mode exhibits relatively weak warming averaged over the entire Arctic with warming over the North American‐Pacific sector and cooling over the Atlantic sector, explaining 10% of the unforced variance and likely caused by the positive phase of the unforced Interdecadal Pacific Oscillation (IPO). The AMO‐related changes dominate the unforced Arctic warming since 1979, while the IPO‐related changes contribute to the decadal SAT changes over the North American‐Pacific Arctic. Plain Language Summary: The Arctic warms much faster than the rest of the world, leading to significant local and remote influences. Warming in the Arctic is not uniform over time, with decadal‐to‐multidecadal variations upon the long‐term trend. The changes in Arctic surface air temperature (SAT) can be attributed to either instrinct variability within the climate system or external forcings including anthropogenic factors such as greenhouse gases emission and natural factors such as volcanic eruptions. Understanding of the relative contributions of internal variability and external forcing to observed changes in Arctic SAT is crucial for improving Arctic climate projections in coming decades. By synthesizing multiple observational data sets and large‐ensemble climate simulations, we find that the Arctic experienced long‐term warming with some periods of slowdown in response to external forcing, which largely explains the overall change since 1900. Internal variability, particularly the multidecadal oscillation in the North Atlantic, dominates the early 20th century warming and mid‐20th century cooling and significantly contributes to the recent rapid warming since 1979. A regression‐based rescaling method removes systematic biases in model‐simulated response (in comparison with observations), ensuring that our results are not influenced by the choice of climate models, as long as they are under the same historical forcing. Key Points: Externally forced Arctic warming dominates the trend and variance in Arctic surface air temperature during 1900–2021Most of the internally generated Arctic temperature changes are related to the unforced Atlantic Multidecadal OscillationInternal variability explains 40% of the Arctic warming from 1979 to 2021, while greenhouse gases and natural forcings account for the rest [ABSTRACT FROM AUTHOR]

Based on long-term observational and reanalysis datasets from 1901 through 2014, this study investigates the characteristics and physical causes of the interdecadal variations in the summer precipitation over the East Asian monsoon boundary zone (EAMBZ), which is a peculiar domain defined from the perspective of the interplay between climatic systems (i.e., mid-latitude westerly and East Asian summer monsoon). Observational evidence reveals that, similarly to previous studies, the EAMBZ precipitation featured prominent interdecadal fluctuations, e.g., with dry summers during the periods preceding 1927, 1939–1945, 1968–1982, and 1998–2010 and wet summers during the periods of 1928–1938, 1946–1967, and 2011 onwards. Further analyses identify that, amongst the major interdecadal oceanic forcings (e.g., Atlantic multidecadal oscillation and Pacific decadal oscillation), the Indian Ocean basin mode (IOBM) is a significant oceanic forcing responsible for the interdecadal variations of the EAMBZ precipitation, playing an independent and critical modulation role. When the cold phase of the IOBM occurs, an anomalous cyclonic circulation is excited around the northeast corner of the tropical Indian Ocean, which further induces a north-low–south-high meridional seesaw pattern over the Northeast China–subtropical western Pacific (SWP) sector. Such seesaw pattern is conducive to the enhanced EAMBZ precipitation by linking favorable environments for the transportation of water vapor from the SWP and the convergence over the EAMBZ at interdecadal timescales. For this reason, a physical–empirical model for the EAMBZ precipitation is developed in terms of the IOBM cooling. Despite the fact that the extreme summer EAMBZ precipitation cannot be captured by this model, it can still well capture its interdecadal fluctuations and reflect their steady relationship. The key physical pathway connecting the IOBM cooling with the interdecadal variations of the summer EAMBZ precipitation is supported by the numerical results based on the large ensemble experiment and the Indian Ocean pacemaker experiment. Our findings may provide new insights into the understanding of the causes of the interdecadal variations in the summer EAMBZ precipitation, which may favor the long-term policy decision-making for the local hydrometeorological planning. [ABSTRACT FROM AUTHOR]

In the summer of 2022, China (especially the Yangtze River Valley, YRV) suffered its strongest heatwave (HW) event since 1961. In this study, we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV, focusing on the city of Shanghai. We found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global warming. During mid-summer of 2022, an enhanced western Pacific subtropical high (WPSH) and anomalous double blockings over the Ural Mountains and Sea of Okhotsk, respectively, were associated with the persistently anomalous high pressure over the YRV, leading to the extreme HW. The Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time scale. Also, the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking pattern. Anomalous warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong WPSH. At the subseasonal time scale, the anomalously frequent phases 2–5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden–Julian Oscillation suppressed the convection over the YRV and also contributed to the HW. Therefore, the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air-sea interaction at multiple time scales. [ABSTRACT FROM AUTHOR]

The Asian monsoon (AM) has direct and profound effects on the livelihoods of residents in South Asia and East Asia. Modern observations have shown multi-decadal alternations of flood and drought periods in these regions, likely influenced by climatic processes such as the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation. However, our understanding of the multi-decadal variability of the AM under different climatic conditions remains uncertain. In this study, we collected an annually laminated and 780-mm stalagmite (sample number: BJ7) from Binjia (BJ) Cave in southwestern China, which is deeply influenced by the Asian monsoon system. Based on this sample, we established 6-year resolution and multi-proxy records for the Asian summer monsoon (ASM) variabilities during the early last termination, spanning from 18.2 to 16.1 ka BP. Measurements of five pairs of uranium and thorium solutions for 230Th dating were conducted using a multi-collector inductively coupled plasma mass spectrometer (MC-ICP- MS), and 374 pairs of stable isotope (δ18O and δ13C) analyses were run on a Kiel Carbonate Device connected with Finnigan MAT-253 at Nanjing Normal University. The chronology for this sample was established by annual layer counting anchored with 230Th dating results. Our BJ7 δ18O record replicates well with other Chinese δ18O records on the general trend, all of which are superimposed by frequent multidecadal-scale fluctuations at approximately 60 years periodicity. Inspection of the 60-year band in BJ7 δ18O and δ13C records and results of the cross-wavelet analysis indicate coherent changes in the ASM and biomass production/karst processes during most of the studied period. In addition, the 60-year band of BJ7 and NGRIP δ18O records are consistent, implying the impacts of the high-latitude North Atlantic or Atlantic Multidecadal Oscillation on the ASM. Our study suggests that the 60-year variability should be an intrinsic feature of the climate system regardless of glacial or interglacial backgrounds. [ABSTRACT FROM AUTHOR]

The related atmospheric and oceanic factors are investigated in this analysis to understand the natural attributes responsible for the significant increase of the high temperature extremes (HTEs) on the Tibetan Plateau (TP) in summer. It is found that a stronger-than-normal South Asian high (SAH) and corresponding weaker-than-normal East Asian jet, an anomalous anticyclone and intensified midlevel westerly wind over the TP, and a more extensive, stronger, farther westward- and northward-stretching western Pacific subtropical high motivate more occurrences of HTEs over the TP on the interannual time scale. From 1961 to 2021, these crucial circulation patterns show a significant changing trend favorable for the occurrence of HTEs and thus contribute to its great increase. Further, the significant warmings of sea surface temperature (SST) in the tropical western Indian, northern North Pacific, and western North Atlantic Oceans make great contributions through different air–sea interactive processes as the Matsuno–Gill response, zonal vertical circulation cell, and mid- to high-latitude teleconnection wave train, respectively. Meanwhile, the interdecadal variability plays an important role. A breakpoint at the early twenty-first century is detected in the occurrence of summer HTEs on the TP. Both the crucial circulation patterns and the SST anomalies in the key oceanic regions experienced significant interdecadal transition to favor the occurrence of HTEs. In particular, the Atlantic multidecadal oscillation (AMO) is significantly and positively correlated with the interdecadal variation of summer HTEs on the TP. The zonal teleconnection wave train triggered by AMO forms a stronger-than-normal SAH and strengthened midlevel westerly airflow over the TP, conducive to the increase of summer HTEs on the TP. [ABSTRACT FROM AUTHOR]

Historical meteorological droughts are analysed over the Coordinated Regional Downscaling Experiment‐Central America, Caribbean and Mexico (CORDEX‐CAM) domain during 1981–2010, with particular emphasis on the North American monsoon (NAM) and the mid‐summer drought (MSD) regions. We analyse droughts based on the standardized precipitation index (SPI‐12) and the standardized precipitation‐evapotranspiration index (SPEI‐12) using observations from CRU, CHIRPS, GPCP and ERA5‐Land reanalysis (ERA5), and assess the skill of the regional climate model RegCM4 (version 7) at 25 km resolution driven by ERA‐Interim (Reg‐ERA) and by three global climate models (Reg‐GCMs: Reg‐Had, Reg‐MPI and Reg‐GFDL). Observational data sets show large spatial variations in drought frequency, and both Reg‐ERA and Reg‐GCMs have difficulties simulating it. RegCM4 shows positive precipitation and water balance biases over mountain regions and negative ones over Central America, possibly due to the complex terrain and poor observational data coverage. Despite differences among observations, the trend in droughts, duration and severity show consistent dry hot spots (regions with long‐duration severe droughts) over the western United States, the United States‐Mexico border region, the NAM, the Yucatan Peninsula and northern Central America, with stronger values of SPEI‐12 than SPI‐12, particularly over the subtropical regions. Reg‐ERA and ERA5 show similar spatial patterns and similar positive and negative spatial biases relative to observations. Reg‐ERA and Reg‐Had adequately simulate the spatial patterns of the trend, duration and severity of droughts, with smaller biases in SPI‐12 than SPEI‐12; in contrast, Reg‐MPI and Reg‐GFDL overestimate the trend biases over northwest CAM. Observations, reanalysis, and RegCM4 capture an inverse drought response between the NAM and the MSD regions linked to climate teleconnections; however, a stronger drought signal is observed in the NAM, which appears to be linked to decadal variations from negative to positive phases of the Atlantic Multidecadal Oscillation combined with La Niña conditions (negative El Niño 1+2 phase). [ABSTRACT FROM AUTHOR]

Aquatic ecologists are integrating mixotrophic plankton - here defined as microorganisms with photosynthetic and phagotrophic capacity - into their understanding of marine food webs and biogeochemical cycles. Understanding mixotroph temporal and spatial distributions, as well as the environmental conditions under which they flourish, is imperative to understanding their impact on trophic transfer and biogeochemical cycling. Mixotrophs are hypothesized to outcompete strict photoautotrophs and heterotrophs when either light or nutrients are limiting, but testing this hypothesis has been hindered by the challenge of identifying and quantifying mixotrophs in the field. Using field observations from a multi-decadal northern North Atlantic dataset, we calculated the proportion of organisms that are considered mixotrophs within individual microplankton samples. We also calculated a "trophic index" that represents the relative proportions of photoautotrophs (phytoplankton), mixotrophs, and heterotrophs (microzooplankton) in each sample. We found that the proportion of mixotrophs was positively correlated with temperature, and negatively with either light or inorganic nutrient concentration. This proportion was highest during summertime thermal stratification and nutrient limitation, and lowest during the North Atlantic spring bloom period. Between 1958 and 2015, changes in the proportion of mixotrophs coincided with changes in the Atlantic Multi-decadal Oscillation (AMO), was highest when the AMO was positive, and showed a significant uninterrupted increase in offshore regions from 1992-2015. This study provides an empirical foundation for future experimental, time series, and modeling studies of aquatic mixotrophs. [ABSTRACT FROM AUTHOR]

In recent decades, winter Arctic sea-ice concentration (SIC) has experienced a most prominent decline over Barents-Kara Seas (BKS). However, what regulates the time scale and spatial structure of the SIC variability over the Eurasian Arctic is unclear. Here, we find that the SIC variability over the Eurasian Arctic exhibits two major modes: decadal dipole mode with antiphase variation between the BKS and East Greenland (EG), and interannual monopole mode with in-phase variation between the BKS and EG. This decadal mode mainly results from interdecadal changes in ocean heat transports (OHTs) through Barents Sea Opening (BSO) and EG, lagging the Atlantic Multidecadal Oscillation by 7–16 years. The positive SIC dipole mode with a decrease over the BKS and an increase over the EG is also tied to the negative Arctic Oscillation comprised of Ural blocking and the negative North Atlantic Oscillation (NAO). However, the SIC loss of the interannual monopole mode mainly stems from the positive Arctic dipole comprised of Ural blocking and positive NAO through interannual changes in the BSO OHT and atmospheric moisture or heat transport. We further highlight that interannual atmospheric transports and BSO OHT associated with the Arctic dipole contribute to ~66% and ~34% of the interannual variability of the Eurasian Arctic SIC during 1960-2017, respectively. On decadal timescales, the relative contributions of atmospheric transports associated with Arctic Oscillation and OHT to the Eurasian Arctic SIC variability are ~19% and ~81%, respectively. Especially, the contribution of decadal atmospheric transports is significantly intensified during 2000–2017. [ABSTRACT FROM AUTHOR]

The relative importance of oceanic modes to global surface air temperature (SAT) and terrestrial precipitation during 1934–2020 was investigated using a variety of statistical and dynamical system methods. Through singular spectrum analysis, we present the distribution of decadal (10–20‐year), multidecadal (20–50‐year), and secular (>50‐year) variabilities of global SAT and terrestrial precipitation anomalies. Three sea surface temperature modes were identified by singular value decomposition that affect the low‐frequency variabilities of global SAT and terrestrial precipitation anomalies—namely, global warming (GW), the Interdecadal Pacific Oscillation (IPO), and the Atlantic Multidecadal Oscillation (AMO). The relative importance GW, the IPO, and the AMO in SAT and terrestrial precipitation was obtained through a normalized multivariate information flow analysis. Besides a high information flow percentage (60%) from GW to global SAT, especially over the northern Indian Ocean and tropical West Pacific, information flow from the AMO to the northwestern Pacific was also found. In terms of terrestrial precipitation, a large area with a wet trend was found over Eurasia at mid‐to‐high latitudes, and this trend was especially remarkable in the boreal winter half‐year (November–April), as compared with that in the boreal summer half‐year (May–October). By employing artificial neutral networks with a self‐organized map to cluster the key patterns of vertically integrated water vapour flux, we found that the synoptic circulation related to the wet trend is characterized by westerly flow that transports water vapour from the northeastern Atlantic to Eurasia, which is favourable for precipitation there both in the boreal winter and summer half‐year. [ABSTRACT FROM AUTHOR]