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Belrhaba, T.; Hakkou, M.; Rey, T.; Aangri, A.; Krien, Y.; Elmostafa, Z.; Leone, F., and Benmohammadi, A., 2024. Shoreline change and climatic variability along the Moulay Bousselham coast (Moroccan Atlantic). Journal of Coastal Research, 40(5), 860–874. Charlotte (North Carolina), ISSN 0749-0208. Sandy coasts in Morocco are increasingly threatened by erosion. It is thus crucial to investigate the extent and causes of shoreline change to propose mitigation strategies to stakeholders. This study investigates the long-term shoreline dynamics of Moulay Bousselham (1949–2016) and its relationship with climate variability indices, namely the North Atlantic Oscillation, East Atlantic Oscillation, and West Europe Pressure Anomaly (WEPA). The analysis, which employs geospatial techniques and the Digital Shoreline Analysis System, reveals significant temporal and spatial variability in shoreline changes characterized by phases of erosion and accretion. The study identifies distinct periods of retreat and growth, highlighting the complex nature of coastal dynamics. The correlation analysis between wave parameters and climatic indices emphasizes the influential role of the WEPA index in controlling winter oceanic phenomena. The winter of 2013/14, marked by the highest WEPA, corresponds to the most energetic conditions in at least 70 years, underscoring the index's significance in understanding local climate variability. While acknowledging methodological challenges and uncertainties inherent in shoreline displacement calculations, the study establishes a noteworthy correlation between the WEPA index and shoreline dynamics. This research contributes valuable insights into the intricate interactions between climate variability and coastal evolution, emphasizing the need for refined methodologies and a comprehensive understanding of factors influencing shoreline changes. [ABSTRACT FROM AUTHOR]

Arctic sea ice has undergone a significant decline in the Barents–Kara Sea (BKS) since the late 1990s. Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated by tropical sea temperature changes (mainly referring to La Niña events). The occurrence of multi-year La Niña (MYLA) events has increased significantly in recent decades, and their impact on Arctic sea ice needs to be further explored. In this study, we investigate the relationship between sea-ice variation and different atmospheric diagnostics during MYLA and other La Niña (OTLA) years. The decline in BKS sea ice during MYLA winters is significantly stronger than that during OTLA years. This is because MYLA events tend to be accompanied by a warm Arctic–cold continent pattern with a barotropic high pressure blocked over the Urals region. Consequently, more frequent northward atmospheric rivers intrude into the BKS, intensifying longwave radiation downward to the underlying surface and melting the BKS sea ice. However, in the early winter of OTLA years, a negative North Atlantic Oscillation presents in the high latitudes of the Northern Hemisphere, which obstructs the atmospheric rivers to the south of Iceland. We infer that such a different response of BKS sea-ice decline to different La Niña events is related to stratospheric processes. Considering the rapid climate changes in the past, more frequent MYLA events may account for the substantial Arctic sea-ice loss in recent decades. [ABSTRACT FROM AUTHOR]

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]

Long-lasting La Niña events (including double-year and triple-year La Niña events) have become more frequent in recent years. How the multi-year La Niña events affect tropical cyclone (TC) activities in the western North Pacific (WNP) and whether they differ from single-year La Niña events are unknown. Here we show that TCs are more active over the far-WNP (FWNP, 110°–150°E), leading to marked high risks at China coasts during the second decaying summer of double-year La Niña events. The anomalous TC activities are directly related to the enhanced cyclonic anomaly over the FWNP, possibly a result of large-scale remote forcing initiated by the tropical North Atlantic (TNA) cooling. The persistent TNA cooling from the decaying winter to summer of double-year La Niña events drives westerlies over the Indo-western Pacific through Kelvin waves, which induce the cooling over the north Indian Ocean via the wind-evaporation-sea surface temperature effect, favoring the asymmetric heat distribution pattern and stimulating an anomalous vertical circulation over the eastern Indian Ocean to FWNP. The cooling over the north Indian Ocean also excites Gill responses, magnifying the TNA-induced westerlies and boosting the anomalous vertical circulation, and thus gives rise to the strong cyclonic circulation anomaly over the FWNP in summer. We suggest that the key point of the process is the strong TNA cooling related to the persistent negative Pacific-North American pattern (PNA) and positive North Atlantic Oscillation (NAO) while double-year La Niña events decay, distinct from the rapid decline of PNA and NAO during single-year La Niña events. The work provides a unique perspective on understanding TC activities over the WNP related to the El Niño-Southern Oscillation. [ABSTRACT FROM AUTHOR]

Flash droughts (FDs) are distinguished by a rapid development associated with strong precipitation deficits and/or increases in atmospheric evaporative demand in the short‐term, but little is known about the atmospheric conditions underlying these events. In this study, we analyse for the first time the atmospheric dynamics involved in the development of FDs in Spain over the period 1961–2018. FDs are related to large‐scale atmospheric circulation patterns affecting the region, in particular with the positive phase of the North Atlantic Oscillation (NAO). The NAO is the main atmospheric driver of FDs in winter and autumn, and it is essential in explaining FD development in spring. We also found that FDs are typically linked to strong positive anomalies in 500 hPa geopotential height and sea level pressure over the region during the weeks prior to the onset. At the synoptic scale, the most common weather types (WTs) recorded during the development of FDs are Anticyclonic Western (ANT_W_AD), East (E_AD) and Northeast (NE_AD) advection, and Anticyclonic (ANTICYC). In particular, ANTICYC WT is the main atmospheric driver of FDs in summer. Ridging conditions occur frequently during FDs in all seasons, being the most important factor controlling FD development in spring. Likewise, we noted that some of the FDs recorded in summer are related to and/or exacerbated by Saharan air intrusions associated with pronounced ridges. The results of this research have important implications for the understanding, monitoring and prediction of FDs in Spain, providing a detailed assessment of the main atmospheric dynamics involved in FD triggering at different spatial scales. [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) and North Atlantic tripole sea surface temperature (SST_tri) are important modes in the atmosphere and ocean over the North Atlantic, respectively. The link between the two is well‐known. However, this link weakened during 1980–2001, which is particularly pronounced in late winter and was not detected in early winter. This phenomenon has not been well revealed. The role of NAO in the above correlation changes was discussed. In late winter, a significant eastward shift (up to 20° longitude) of NAO south center during 1980–2001 was observed in both observation and CMIP6, accompanied by the eastward expansion of NAO north center. Spatial shift of the NAO forced the region of strong air‐sea interactions to shift and resulting in the collapse of NAO‐related SST_tri. These findings deepen our understanding of the NAO on the subseasonal scale. Plain Language Summary: A significant correlation between the North Atlantic Oscillation (NAO) and the North Atlantic tripole sea surface temperature (SST_tri) is widely recognized. However, this study found that the correlation between the two was significantly weakened in late winter during 1980–2001 while no such change was detected in early winter. Therefore, this paper will focus on the late winter and discuss the role of NAO spatial structure in the above correlation changes. When the NAO south center is located over the North Atlantic, both observations and the climate models indicate that the corresponding North Atlantic SST shows a significant tripole pattern. However, during 1980–2001, the NAO south center shift significantly eastward from the North Atlantic toward Western Europe (up to 20° longitude). At the same time, the NAO north center expanded eastward significantly. The eastward shift of the NAO results in the significant eastward shift of the turbulent heat flux and wind stress anomalies. Shift in the region of strong air‐sea interaction led to the collapse of NAO‐related SST_tri. These findings deepen our understanding of the NAO on the subseasonal scale and also provide implications for subseasonal‐seasonal predictions of Eurasian climate extremes. Key Points: The link between NAO and North Atlantic tripole SST weakened obviously during 1980–2001 late winter, which was not detected in early winterThe eastward shift of ∼20° longitude in NAO south center forced the strong air‐sea interactions region to shift in observations and CMIP6NAO's spatial shift in late winter caused the changes in the link between NAO and North Atlantic tripole SST [ABSTRACT FROM AUTHOR]

The wintertime North Atlantic Oscillation (NAO) and East Atlantic Pattern (EA) are the two leading modes of North Atlantic pressure variability and have a substantial impact on winter weather in Europe. The year‐to‐year contributions to multi‐model seasonal forecast skill in the Copernicus C3S ensemble of seven prediction systems are assessed for the wintertime NAO and EA, and well‐forecast and poorly‐forecast years are identified. Years with high NAO predictability are associated with substantial tropical forcing, generally from the El Niño Southern Oscillation (ENSO), while poor forecasts of the NAO occur when ENSO forcing is weak. Well‐forecast EA winters also generally occurred when there was substantial tropical forcing, although the relationship was less robust than for the NAO. These results support previous findings of the impacts of tropical forcing on the North Atlantic and show this is important from a multi‐model seasonal forecasting perspective. Plain Language Summary: The wintertime North Atlantic Oscillation (NAO) and East Atlantic Pattern (EA) are two important indicators of atmospheric variability in the North Atlantic. They can have a substantial impact on European winter weather. The ability of seasonal forecast models to forecast the NAO and EA varies from year to year. This intermittency of forecast skill is investigated in seven different seasonal forecast systems from the Copernicus C3S database, by focusing on the most well‐forecast and poorly‐forecast years. Years where the NAO is well‐forecast are associated with substantial tropical forcing, generally from the El Niño Southern Oscillation (ENSO), while poor forecasts of the NAO occur when ENSO forcing is weak. Similar but weaker results hold for the EA. These results are valuable for increasing the usability of seasonal forecasts by identifying conditions under which forecasts are more likely to be skillful. Key Points: Seasonal forecast skill of the wintertime North Atlantic Oscillation (NAO) and East Atlantic Pattern (EA) is intermittentWell‐forecast NAO/EA winters generally occur when there is substantial tropical forcing [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]

As nations progress, the impact of climate change on food prices becomes increasingly substantial. While the influence of climate change on the yields of major agricultural products is widely recognized, its specific effect on food prices remains uncertain. This study delves into the impact of the North Atlantic Oscillation (NAO) index, a well-established climate indicator, on global food prices. To accomplish this, a robust bivariate Hurst exponent (robust bHe) is applied. The study employs a sliding windows approach across various time scales to produce a color map of this coefficient, presenting a time-varying version. Furthermore, variable-lag transfer entropy with a sliding windows approach is utilized to discern causal relationships between the NAO index and international food prices. The findings reveal that significant increases in the NAO index are correlated with noteworthy upswings in various international food prices over both short and long-term periods. Additionally, variable-lag transfer entropy confirms the causal role of the NAO index in influencing international food prices. [ABSTRACT FROM AUTHOR]

This letter raises the possibility that ergodicity concerns might have some bearing on the signal‐to‐noise paradox. This is explored by applying the ergodic theorem to the theory behind ensemble weather forecasting and the ensemble mean. Using the ensemble mean as our best forecast of observations amounts to interpreting it as the most likely phase‐space trajectory, which relies on the ergodic theorem. This can fail for ensemble forecasting systems if members are not perfectly exchangeable with each other, the averaging window is too short and/or there are too few members. We argue these failures can occur in cases such as the winter North Atlantic Oscillation (NAO) forecasts due to intransitivity or regime behaviour for regions such as the North Atlantic and Arctic. This behaviour, where different ensemble members may become stuck in different relatively persistent flow states (intransitivity) or multi‐modality (regime behaviour), can in certain situations break the ergodic theorem. The problem of non‐ergodic systems and models in the case of weather forecasting is discussed, as are potential mitigation methods and metrics for ergodicity in ensemble systems. [ABSTRACT FROM AUTHOR]

Millennial-scale climate change is thought to be synchronous throughout the Northern Hemisphere and has been demonstrated to be strongly modulated by longer-term glacial–interglacial and orbital-scale processes. However, processes that modulate the magnitude of millennial-scale variability (MMV) at the glacial–interglacial time scale remain unclear. We present multiproxy evidence showing out-of-phase relationships between the MMV of East Asian and North Atlantic climate proxies at the eccentricity band. During most late Pleistocene glacial intervals, the MMV in North Atlantic SST and East Asian monsoon (EAM) proxies shows a gradual weakening trend from glacial inceptions into glacial maxima, inversely proportional to that of the North Atlantic ice-rafted detritus record. The inverse glacial age trends apply to both summer and winter monsoon proxies across the loess, speleothem, and marine archives, indicating fundamental linkages between MMV records of the North Atlantic and East Asia. We infer that intensified glacial age iceberg discharge is accompanied by weakened Atlantic meridional overturning circulation via changes in freshwater input and water column stability, leading to a reduction in North Atlantic SST and wind anomalies, subsequently propagating dampened millennial-scale variability into the midlatitude East Asian monsoon region via the westerlies. Our results indicate that the impact of North Atlantic iceberg discharge and the associated variability in water column stability at the millennial scale is a primary influence on hydroclimate instability in East Asia. [ABSTRACT FROM AUTHOR]

Quantifying the tendency of flood events to demonstrate clustering in time and space is crucial for flood risk assessments. We analyse the temporal (TC) and spatial (SC) coherence of floods in 554 catchments over Great Britain. TC was assessed using the dispersion-index and Conway-Maxwell-Poisson regression, with both methods applied to aggregation windows of 1–5 years. SC was investigated using the flood susceptibility index. Results show that i) most of the UK peak floods are overdispersed and ii) a positive relationship exists between winter mean North Atlantic Oscillation anomalies and the annual number of peak floods across western Britain. The susceptibility to widespread floods is higher for the southeast parts of Britain and for the Clyde-Forth valleys, and it increases with catchment permeability and with the influence of lakes/reservoirs. These findings are relevant to enhance existing flood hazard estimation methods and, in turn, will lead to more realistic flood risk quantification. [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]

This study introduces an innovative analytical methodology for examining the interconnections among the atmosphere, ocean, and society. The primary area of interest pertains to the North Atlantic Oscillation (NAO), a notable phenomenon characterised by daily to decadal fluctuations in atmospheric conditions over the Northern Hemisphere. The NAO has a prominent impact on winter weather patterns in North America, Europe, and to some extent, Asia. This impact has significant ramifications for civilization, as well as for marine, freshwater, and terrestrial ecosystems, and food chains. Accurate predictions of the surface NAO hold significant importance for society in terms of energy consumption planning and adaptation to severe winter conditions, such as winter wind and snowstorms, which can result in property damage and disruptions to transportation networks. Moreover, it is crucial to improve climate forecasts in order to bolster the resilience of food systems. This would enable producers to quickly respond to expected changes and make the required modifications, such as adjusting their food output or expanding their product range, in order to reduce potential hazards. The forecast centres prioritise and actively research the predictability and variability of the NAO. Nevertheless, it is increasingly evident that conventional analytical methods and prediction models that rely solely on scientific methodologies are inadequate in comprehensively addressing the transdisciplinary dimension of NAO variability. This includes a comprehensive view of research, forecasting, and social ramifications. This study introduces a new framework that combines sophisticated Big Data analytic techniques and forecasting tools using a generalised additive model to investigate the fluctuations of the NAO and the interplay between the ocean and atmosphere. Additionally, it explores innovative approaches to analyze the socio-economic response associated with these phenomena using text mining tools, specifically modern deep learning techniques. The analysis is conducted on an extensive corpora of free text information sourced from media outlets, public companies, government reports, and newspapers. Overall, the result shows that the NAO index has been reproduced well by the Deep-NAO model with a correlation coefficient of 0.74. [ABSTRACT FROM AUTHOR]

Tornado outbreaks (TOs) are highly dangerous meteorological phenomena common in the United States and have limited known relationships with climate variability. Many of the challenges in understanding TOs result from a lack of formal TO quantification (both in definition and impact). Here, we present a TO definition based on a spatially cohesive and distinct region of tornado activity and present a TO intensity index using tornado characteristics within the TO region. In developing this index, we present a support vector regression-based detrending methodology to remove the secular trends within tornado reporting. The resulting TO definition suggests a decline in TO activity of roughly 1 TO per 4–5 years, with a similar decline in TO intensity. In addition, the relationship between this new quantification of TOs and common North American interannual and monthly climate variability indices is explored, namely the El Niño Southern Oscillation, the North Atlantic Oscillation, the Arctic Oscillation, and the Pacific North American Oscillation. In general, the links between these teleconnections and TO frequency and intensity were minimal (and sometimes in opposition when comparing TO frequency and intensity), but interesting patterns emerged that may offer an initial pathway to exploring longer-term TO predictability. [ABSTRACT FROM AUTHOR]

Identified for the first time in Norway, windblown yellowish-brown dust in Folldal, east-central southern Norway, fulfils physical and geochemical criteria for sensu stricto loess, including a high carbonate content. Two extant and one relict marl pond located on low-carbonate rocks are investigated. An allochthonous origin for the marl ponds is suggested and explained by the deposition of suspended clastic carbonate as loess by aeolian processes. The scattered geographical distribution of loess and the need for a calcareous source area suggest a W-SW provenance from a relict valley sandur/existing flood plain in upper Grimsdalen. The mean grain size (~22.4 µm) of the aeolian silt is in the finer range of average loess, explained by the up to 25–30 km long transport and approximately 250–300 m airborne uphill move from the suggested source area to the marl ponds. Based on age-depth modelling using 9 AMS radiocarbon dates, loess deposition occurred from ca. 10,390 to 9780 cal. yr BP (610 years). Two prominent periods of loess accumulation occurred from ca. 10,390 to 10,190 (200 years) and ca. 10,020–9950 (70 years) cal. yr BP. Loess deposition results from W-SW wintertime winds in a dry to semi-arid climate. In southern Norway, W-SW winds in winter are associated with a positive mode of the North Atlantic Oscillation (NAO). From source to deposition, the response time to erode, transport and accumulate loess is suggested to be seasonal to 1 year. An immediate increase in organic production followed loess deposition as early initiation of a warmer and wetter Holocene climatic optimum. [ABSTRACT FROM AUTHOR]

Analysis of low river flows provides important information for effective management of water resources in a region. Despite the critical importance of understanding low flow dynamics, there is a gap in the literature regarding the use of non-stationary models to analyze low flow data under climate change in Turkey. In this research, low flow series from 80 measuring stations in Turkey are investigated by employing both stationary and non-stationary models based on the Generalized Additive Models for Location, Scale and Shape (GAMLSS). For constructing non-stationary models, 31 explanatory variables consisting of time, precipitation, temperature and atmospheric oscillation indices were used to model the parameters of the chosen distributions. The results show that stationary models are more successful at 7 stations, while non-stationary models are more successful at 73 stations. Comparisons between non-stationary models showed that for most stations, the best performing models were non-stationary models with annual precipitation as covariates. In addition, successful results were obtained when Western Mediterranean Oscillation and North Atlantic Oscillation indices were used as explanatory variables. Additionally, this study investigated 20 and 50-year return levels by fitting the non-stationary frequency distribution models for low flows over historical and projection periods under SSP2-4.5 and SSP5-8.5 climate scenarios. GAMLSS incorporated annual total precipitation, which is the most effective explanatory variable for low flows, as a covariate, and thus changes in low flows were analyzed. The results show that decreases are expected in low flows, except for the stations in the upper Euphrates basin compared to the historical period. [ABSTRACT FROM AUTHOR]

The Jenkinson‐Collison Weather Typing (JC‐WT) method uses sea‐level pressure gradients to create 27 types based on the geostrophic flow and vorticity around any extratropical target location. Typically, JC‐WTs are applied over specific locations or limited domains, thus hampering the understanding of the impact of large‐scale mechanisms on regional climate. This study explores the links between regional climate variability, as represented by the JC‐WTs, and large‐scale phenomena, to describe the synoptic‐scale variability in the North Atlantic‐European region and evaluate the JC‐WT methodology. Large‐scale circulation is here characterized by major atmospheric low‐frequency modes, namely the North Atlantic Oscillation, the East Atlantic and the Scandinavian teleconnection indices, and by atmospheric blockings. Results show that JC‐WTs coherently capture the spatial and temporal variability of the large‐scale modes and yields a characteristic response to blocking events. Overall, our results underpin the exploratory potential of this method for the analysis of the near‐surface circulation. These findings endorse the use of JC‐WTs and support the reliability and utility of the JC‐WT classification for process‐based model assessments and model selection, a crucial task for climate impact studies. [ABSTRACT FROM AUTHOR]

The coupled nature of the ocean–atmosphere system frequently makes understanding the direction of causality difficult in ocean–atmosphere interactions. This study presents a method to decompose turbulent surface heat fluxes into a component which is directly forced by atmospheric circulation and a residual which is assumed to be primarily "ocean-forced." This method is applied to the North Atlantic in a 500-yr preindustrial control run using the Met Office's HadGEM3-GC3.1-MM model. The method shows that atmospheric circulation dominates interannual to decadal heat flux variability in the Labrador Sea, in contrast to the Gulf Stream where the ocean primarily drives the variability. An empirical orthogonal function analysis identifies several residual heat flux modes associated with variations in ocean circulation. The first of these modes is characterized by the ocean warming the atmosphere along the Gulf Stream and North Atlantic Current and the second by a dipole of cooling in the western subtropical North Atlantic and warming in the subpolar North Atlantic. Lead–lag regression analysis suggests that atmospheric circulation anomalies in prior years partly drive the ocean heat flux modes; however, there is no significant atmospheric circulation response in years following the peaks of the modes. Overall, the heat flux dynamical decomposition method provides a useful way to separate the effects of the ocean and atmosphere on heat flux and could be applied to other ocean basins and to either models or reanalysis datasets. Significance Statement: Variability of the ocean affects atmospheric circulation and provides a source of long-term predictability for surface weather. However, the atmosphere also affects the ocean. This makes the separation of cause and effect in such atmosphere–ocean interactions difficult. This paper introduces a method to separate "turbulent heat fluxes," the primary means by which the atmosphere and ocean influence one another, into a component driven by atmospheric variability and a component which is primarily related to ocean variability. The method is tested by applying it to a climate model simulation and is able to identify regions in which the exchange of heat between the ocean and atmosphere is dominated by atmospheric variability and regions which are dominated by the ocean. [ABSTRACT FROM AUTHOR]

Greenland ice core records feature Dansgaard–Oeschger (D‐O) events, which are abrupt warming episodes followed by gradual cooling during ice age climate. The three climate models used in this study (CCSM4, MPI‐ESM, and HadCM3) show spontaneous self‐sustained D‐O‐like oscillations (albeit with differences in amplitude, duration, and shape) in a remarkably similar, narrow window of carbon dioxide (CO2) concentration, roughly 185–230 ppm. This range matches atmospheric CO2 during Marine Isotopic Stage 3 (MIS 3: between 27.8 and 59.4 thousand of years BP, hereafter ka), a period when D‐O events were most frequent. Insights from the three climate models point to North Atlantic (NA) sea‐ice coverage as a key ingredient behind D‐O type oscillations, which acts as a "tipping element." Other climate state properties such as Mean Atlantic Meridional Overturning Circulation strength, global mean temperature and salinity gradient in the Atlantic Ocean do not determine whether D‐O type behavior can occur in all three models. Plain Language Summary: Dansgaard‐Oeschger (D‐O) events are sudden periods of warming followed by slow cooling during ice ages, as observed in Greenland's ice core records. The study used three different climate models to analyze these events, and all models showed similar behavior within a specific range of atmospheric carbon dioxide (CO2) concentrations. This range of CO2 concentrations aligns well with the levels found during the latter half of the last ice age when D‐O events were most frequent. The study found that when CO2 levels are outside this specific range, the climate models settle into one of two stable states, either warm with high CO2 levels or cold with low CO2 levels. These states are stable until CO2 levels reach a certain "tipping point"‐ below around 185–195 ppm for the cold state and above around 217–230 ppm for the warm state. This study suggests that North Atlantic sea ice coverage is a crucial property essential for D‐O like behavior to develop in complex climate models. Key Points: Three complex climate models show internal unforced oscillations at glacial levels of atmospheric carbon dioxide concentrationNorth Atlantic (NA) sea‐ice coverage plays a crucial role behind Dansgaard–Oeschger type behavior in all three modelsThe three models reproduce oscillations in a similar range of NA sea ice coverage [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) has an important local and remote influence on global climate through the distribution and transport of heat and moisture. As a result of climate forcing, significant changes occur in the SSTs, which result in many natural disasters such as supercharged storms, higher wind speeds, heavier precipitation and flooding. This study investigates the spatiotemporal changes and underlying atmospheric mechanisms of the Black Sea (BLS) surface temperature. For this purpose, National Oceanicand Atmospheric Administration (NOAA) high‐resolution SST data (0.25°), which were verified with buoy observations, were used for the period 1982–2021. To investigate the circulation impacts, the relationship between North Atlantic Oscillation and East Atlantic/West Russia (EA/WR) phases and SSTs of the western BLS (WBLS) and eastern BLS (EBLS) was analysed. According to the results, SST values increased from 1.64°C (in winter) to 2.52°C (in summer) during the 40‐year period. Significant SST increases are shown in the EBLS during the summer and fall months. Statistically significant negative correlations (p < 0.05) were found between EA/WR and winter (r = −0.57) and summer (r = −0.56) SSTs in the EBLS. During winter, surface high located in the eastern Anatolia causes southerly winds, which blows from the terrestrial areas to the EBLS and result in above‐normal SST values. During summer (under negative EA/WR phases), the Azores high‐pressure centre extends to the Balkan Peninsula and WBLS and as a consequence, a significant amount of moisture associated with high sea surface temperature (>27°C, above‐normal 2.0°C) develops low‐level moisture convergence. Proper synoptic conditions, strong instability conditions between the surface and upper levels, and orographic forcing enable the occurrence of convective cloud cells. The movement of these cells to the northeastern part of Turkiye by strong northwesterly winds causes extreme precipitation and associated flash‐flood events in a limited area where land–sea interaction occurs (i.e., Artvin, Rize and Hopa provinces of Turkiye). [ABSTRACT FROM AUTHOR]

Cold‐air outbreaks have significant impacts on human health, energy consumption, agriculture, and overall well‐being. This study aims to evaluate the effectiveness of Subseasonal‐to‐Seasonal (S2S) models in predicting cold conditions over northern Eurasia, defined here as the lower tercile of weekly mean 2‐metre temperature anomalies. To assess the predictability of these events we use ensemble hindcasts from five prediction systems from the S2S database. Our analysis focuses on identifying the conditions under which the models confidently predict cold temperatures with a high (>0.5) probability 3–4 weeks ahead, which potentially can represent windows of forecast opportunity. We compare the group of forecasts that correctly predicted the events to the group that forecasted events that did not occur in practice (false alarms). Most of the confident forecasts of cold spells, both correct and false alarms, have cold anomalies already in the initial conditions, often in conjunction with either a negative phase of the North Atlantic Oscillation, or Scandinavian Blocking. We find that S2S models tend to overpredict cold temperatures, with false alarms occurring more likely when the forecasts are initialized during a weak polar vortex. Furthermore, most of the confident false alarms receive the signal from the stratosphere rather than following internal tropospheric dynamics. False alarms initialized during the weak polar vortex conditions are more common when the vortex is in a recovery stage and, subsequently, the downward ‐propagating signal is short‐lived in the troposphere. The analysis of forecasts during different Madden–Julian Oscillation (MJO) phases shows that nearly half of all confident correct cold‐temperature forecasts are initialized during an active MJO in phases 6–8. On the other hand, most false alarms occur during phase 3, which we suggest is due to the presence of the Scandinavian Blocking regime in the initial conditions for this phase. [ABSTRACT FROM AUTHOR]

The "State of the UK Climate 2023" report provides a comprehensive summary of the UK's weather and climate in 2023, based on observational data from the UK land weather station network. The report highlights that recent decades have been warmer, wetter, and sunnier than the 20th century, with extremes of temperature being more affected than average temperature. In 2023, the UK experienced several significant weather events, including its warmest June on record, a heatwave in September, and heavy rainfall in October. The report also discusses temperature trends, rainfall patterns, sunshine hours, wind patterns, and extreme weather events. It emphasizes the increasing frequency of hot days and decreasing number of frosts, as well as the overall trend of a warming and wetter climate in the UK. The report includes data on phenological events and the North Atlantic Oscillation index, as well as information on data sources, quality control, and uncertainties. Overall, the report provides valuable insights into the UK's climate and weather patterns in 2023 and the broader trends observed in recent decades. [Extracted from the article]

Earlier studies based on censuses of adult birds in spring suggest that the Common Merganser Mergus merganser population in Finland has been rather stable during the last few decades. However, in the beginning of the 1990s, a population increase was followed by a decline. Contrary to the trends detected in breeding populations, wintering populations of the species have increased in Finland and elsewhere in Europe. Along with warming winters, wintering areas have shifted gradually towards northeast. In the present study, a coastal population of the Common Merganser breeding in nest boxes was monitored between 2004 and 2022 in southern Finland. The role of winter weather conditions in population fluctuations and changes was examined. The weather conditions during two preceding winters reflected in the population fluctuations of mergansers. The number of nests in nest boxes increased following increasing winter temperatures in the northeastern end of the wintering area (near the breeding area). The breeding population decreased after warm winters in the southwestern end of the wintering area (far from the breeding area). The present results suggest that established populations decrease after warm winters, because young birds that have not yet bred have shifted to overwinter and breed further eastwards than in general. [ABSTRACT FROM AUTHOR]

The escalating local impacts of climate change are a pressing global concern, particularly in regions vulnerable to global warming, like the Hindu Kush Himalayan region. Bhutan, recognised as one of the world's most climate-vulnerable nations, faces extensive socio-economic damages due to climate change, posing significant recovery challenges. Climate change studies using satellite and hybrid data with Global Climate Models often amplify uncertainty, leading to exaggerated results. So, to understand the climate variability in Bhutan, we analysed historical temperature and precipitation using ground station data. We utilised the Mann–Kendall test and Sen's slope analysis for trend assessment, continuous wavelet transform for periodicity detection, and cross wavelet transform for correlation analysis with atmospheric oscillations. The future climate projections were evaluated based on best-fit bias-corrected Coupled Model Intercomparison Project Phase 6 Global Climate Models data under the various Shared Socio‐Economic Pathways. The historical time series revealed, in general, a decreasing trend in rainfall. The maximum temperature showed a warming trend mostly above the elevation of 1000 m above mean sea level, while the minimum temperature showed a decreasing trend. However, the mean annual temperature and precipitation are expected to increase. The country could warm up from 1.7ºC to 3.3ºC under various Shared Socio‐Economic Pathways. The periodicity analysis of wavelets reveals that most stations showed higher covariance with the Indian Ocean Dipole and Elnino Southern Oscillation, followed by North Atlantic Oscillation, with 9–14 months periodicities. The findings of the past and future climate analysis presented in this study are expected to play a significant role in protecting the beautiful ecosystem of Bhutan as a whole. Additionally, the findings could assist policymakers in formulating adaptation strategies for addressing climate change impacts, enabling them to implement essential measures to transform Bhutan into a climate-resilient country. [ABSTRACT FROM AUTHOR]

Britain's power system has shifted towards a major contribution from wind energy. However, wind is highly variable, and exceptionally low wind events can simultaneously occur with cold conditions, which increase demand. These conditions can pose a threat for the security of energy supply. Here we use bias‐corrected wind supply data and the estimated temperature‐related part of demand to analyse events of potential weather‐related energy shortfall based on the historic meteorological record. We conduct sensitivity studies with varying scenarios of Britain's total wind energy capacity and the temperature sensitivity of national demand. These scenarios are estimates for present‐day conditions as well as potential future changes of the power system. We apply a new methodology to estimate the potential severity of an event for the power system, and analyse the atmospheric conditions associated with the most severe events. We find that events of potentially severe shortfall are relatively rare and short‐lived, and often occur with an atmospheric pattern broadly resembling a negative North Atlantic Oscillation. This broad tendency emerges from a wide range of individual daily weather patterns that cause cold and still conditions. With an increase in wind capacity, it is likely that severe events will become rarer, although the most severe days of the record are relatively insensitive to changes in wind supply and temperature sensitivity of demand under our assumptions. [ABSTRACT FROM AUTHOR]

Canonical understanding based on general circulation models (GCMs) is that the atmospheric circulation response to midlatitude sea‐surface temperature (SST) anomalies is weak compared to the larger influence of tropical SST anomalies. However, the ∼100‐km horizontal resolution of modern GCMs is too coarse to resolve strong updrafts within weather fronts, which could provide a pathway for surface anomalies to be communicated aloft. Here, we investigate the large‐scale atmospheric circulation response to idealized Gulf Stream SST anomalies in Community Atmosphere Model (CAM6) simulations with 14‐km regional grid refinement over the North Atlantic, and compare it to the responses in simulations with 28‐km regional refinement and uniform 111‐km resolution. The highest resolution simulations show a large positive response of the wintertime North Atlantic Oscillation (NAO) to positive SST anomalies in the Gulf Stream, a 0.4‐standard‐deviation anomaly in the seasonal‐mean NAO for 2°C SST anomalies. The lower‐resolution simulations show a weaker response with a different spatial structure. The enhanced large‐scale circulation response results from an increase in resolved vertical motions with resolution and an associated increase in the influence of SST anomalies on transient‐eddy heat and momentum fluxes in the free troposphere. In response to positive SST anomalies, these processes lead to a stronger and less variable North Atlantic jet, as is characteristic of positive NAO anomalies. Our results suggest that the atmosphere responds differently to midlatitude SST anomalies in higher‐resolution models and that regional refinement in key regions offers a potential pathway to improve multi‐year regional climate predictions based on midlatitude SSTs. Plain Language Summary: Variations in the ocean surface temperature (SST) influence the atmospheric circulation and thus climate over land. Canonical understanding is that tropical SSTs are more important than SSTs in midlatitudes. However, this understanding is based on climate models that don't resolve processes at scales less than 100 km. Here, we show that by increasing the atmospheric model resolution to resolve features on smaller scales, such as weather fronts, we find a larger atmospheric circulation response to midlatitude SST anomalies in the North Atlantic. North Atlantic SST anomalies can be predicted multiple years in advance, and a larger atmospheric circulation response to these predictable SST anomalies therefore implies increased predictability of climate over the surrounding land regions. Key Points: There is a large circulation response to idealized Gulf Stream sea‐surface temperature (SST) anomalies in an atmospheric model with 14‐km regional grid refinementThis response is weaker or absent in simulations with 28‐km or coarser resolution, which do not fully resolve mesoscale frontal processesTransient‐eddy fluxes of heat and momentum are modified as fronts pass over warm SSTs, leading to a large‐scale circulation response [ABSTRACT FROM AUTHOR]

The Pearl River Basin is one of the most important agricultural areas and water sources in the subtropical humid region of southern China. Drought events occur frequently in the Pearl River Basin under the background of global climate, especially for the continuous seasonal drought. The temporal and spatial evolution of drought at different time scales is of great significance to allocate the water resources for the agricultural planting structure in the Pearl River Basin. In this study, the daily observation data was selected from 44 meteorological stations in the Pearl River Basin from 1960 to 2020. The precipitation and potential evapotranspiration (ET0) was then calculated by the FAO Penman-Monteith, in order to obtain the standardized precipitation evapotranspiration index (SPEI) at the cross-seasonal drought time scale. Linear tendency estimation was combined with Mann-Kendall mutation test and Morlet wavelet analysis. The temporal and spatial variation of continuous seasonal drought was then analyzed over the past 60 years. The result showed that: 1) The instable precipitation was led to the complex and diverse dry and wet changes. The growth trend of the continuous drought was found in autumn-winter and autumnwinter- spring. This variation was attributed to the decrease of autumn precipitation and the concentration of winter precipitation. The frequency of drought was also higher than that before the 21st century. Specifically, the frequency of continuous drought in autumn-winter-spring increased from 0.15 times/a before 2000 to 0.25 times/a after 2000. And there were many consecutive seasonal drought events from 2000 to 2010. The intensity of drought was mostly light and moderate and the continuous drought coverage area is mainly characterized by local, followed by regional drought. Particularly, the drought from dry to wet and from wet to dry occurred in the continuous drought of autumn-winter-spring in 1962 and 1997, respectively. 2) There were the outstanding interannual and interdecadal variations of SPEI in the continuous drought of autumn-winter and autumn-winter-spring. The main periods of continuous drought were 9 and 23a, respectively, in autumnwinter and autumn-winter-spring. There was a general cycle of 9-14a. According to the short period, there was some influence of atmospheric circulation on the wet and dry variation. The correlation analysis showed that the dry and wet variations in the continuous drought in autumn-winter were affected mainly by the Southern oscillation index (SOI). And the wet and dry changes in the continuous drought of autumn-winter-spring were significantly correlated with North Atlantic oscillation index (NAO), Southern oscillation index (SOI) and Pacific Decadal oscillation index(PDO). The SOI shared the better characterization for the ENSO. As such, the ENSO events were the main influencing factors on the changes of dry and wet in autumn-winter and autumn-winter-spring. 3) 47.7 % and 54.5 % of the stations showed a downward trend under the continuous drought of autumn-winter and autumn-winter-spring, respectively. Therefore, the spatial distribution pattern of the continuous drought autumn-winter and autumn-winter-spring was roughly dry in the east and west, while wet in the middle. There were the large spatial differences in dry and wet changes in different watersheds. There was the high frequency of the continuous drought of autumn-winter and autumn-winter-spring, indicating the trend of dry early. The Youjiang, Zuojiang and Yujiang River Basin were used to share the great changes in dry and wet alternation, indicating the high frequency of drought. But there was the weakening trend of the continuous drought in autumn-winter and autumn-winter-spring in recent years. Much more attention should be paid to the extreme precipitation and flood in the future. There was some increase in the continuous drought of autumn-winter with a high frequency and a weak trend of early drought rate from northeast to southwest in the Dongjiang River Basin. The high occurrence can be found in the continuous seasonal risk. [ABSTRACT FROM AUTHOR]

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The paper represents an attempt to understand the impacts produced by the North Atlantic Oscillation on the ice cover regime of the largest coastal lake in Poland situated in the northern part of the country. The purpose of the study was to estimate the impact of the North Atlantic Oscillation on selected ice cover parameters. The study also attempts to examine other factors that may affect its significant impact on observed changes in the climate. Water temperature data are used to assess temperature conditions in aqueous ecosystems as well as determine the heat absorption capacity of these systems. This allows one to then determine cooling rates in the event of ice cover formation. The data analysis provided in the paper focuses on selected characteristics of ice cover conditions (i.e. dependent variables) including the number of days with ice and maximum ice thickness in relation to NAO index changes (i.e. independent variables) for the reference period 1960/61–2009/10. In addition, the paper divides the studied period into 10-year subperiods in order to capture the weakest and strongest phases of NAO and assess the extent to which they affect the duration of ice cover. A large increase in the mean air temperature (1.8°C) occurred in the years 1960–2010. Trendline analysis indicates that the number of days with ice cover declined by about 60 days and the maximum thickness of ice cover decreased by about 10 cm. Oceanographic research employs satellite image data in order to accurately assess human impact. Therefore, ice cover forecasts generated for consecutive winter seasons may become an important tool in this type of assessment.

This study analyzed the past wave climate of the Black Sea region for the period from 1988 to 2021. The wave field has been simulated using the state-of-the-art, third-generation wave model WAVEWATCH III forced by the ECMWF reanalysis ERA5 winds, with the model resolution being the highest ever applied to the region in a basin-scale climate study. The surface currents provided by the Copernicus Marine Service have been included in the wave model to evaluate wave--current interactions. The wave model results have been validated with respect to satellite and buoy observations, showing that the simulation accurately reproduces the past evolution of the wave field, exceeding 0.9 correlation with respect to satellite data. The inclusion of wave--current interaction has been positively evaluated. Four statistics (significant wave height 5th and 95th percentiles, mean, and maxima) have been used to describe the wave field at seasonal timescale, showing a clear distinction between the Western (rougher sea conditions) and Eastern (calmer sea conditions) sub-basins. Furthermore, the intra-annual wave climate variability has been investigated using a Principal Component Analysis (PCA) and the Mann--Kendall test on significant wave height (SWH). This study represents the first time the PCA is applied to the region, identifying two main modes that highlight distinct features and seasonal trends in the Western and Eastern subbasins. Throughout most seasons, the SWH trend is positive for the Eastern basin and negative for the Western basin. The PCA shows a regime shift with increasing eastward waves and decreasing north and north-eastward waves. Finally, SWH correlation (r) with four Teleconnection indexes (East Atlantic Pattern, Scandinavian Pattern, North Atlantic Oscillation, and East Atlantic/West Russia Pattern) revealed that the strongest r is observed with the Eastern--Atlantic--Western Russia teleconnection, with a peculiar spatial pattern of correlation, and is positive for the northwestern and negative for the southeastern sub-basin. [ABSTRACT FROM AUTHOR]

Air‐sea interaction in late boreal winter is studied over the extratropical North Atlantic (NA) during 1960–2020 by examining the relationship between sea‐surface temperature (SST) and total turbulent heat flux (THF). The two quantities are positively correlated on interannual timescales over the central‐midlatitude and subpolar NA, suggesting the atmosphere on average drives SST and THF variability is independent of SST. On decadal timescales and over the central‐midlatitude NA the correlation is negative, suggesting ocean processes on average drive SST and THF variability is sensitive to SST. The correlation is positive over the subpolar NA. There, interannual and decadal THF variability is governed by the North Atlantic Oscillation (NAO). During the major late 20th and early 21st century SST increase in the subpolar NA diminishing oceanic heat loss associated with a weakening NAO was observed. This study suggests that the atmosphere is more sensitive to SST over the central‐midlatitude than subpolar NA. Plain Language Summary: The relationship between the sea‐surface temperature (SST) and air‐sea heat exchange, is studied over the extratropical North Atlantic (NA) for late boreal winter during 1960–2020. This relationship provides information about the roles of atmospheric and oceanic processes in driving SST variations. We consider two regions, the central‐midlatitude (35°N–50°N) and subpolar (50°N–60°N) NA. Over both regions, the atmosphere tends to drive the variations on the short interannual timescales. On the longer decadal timescales and over the central‐midlatitude NA, oceanic processes tend to drive the SST anomalies that in turn influence the air‐sea heat exchange. Air‐sea heat exchange over the subpolar NA is mostly driven by the North Atlantic Oscillation on interannual and decadal timescales, which is the leading mode of internal atmospheric variability in winter. This study suggests that the atmosphere is more sensitive to SST over the central‐midlatitude than subpolar NA. Key Points: Regional variation in the nature of air‐sea interaction over the extratropical North Atlantic (NA) north of 35°NTimescale dependence in relationship between sea‐surface temperature (SST) and turbulent heat flux over the central‐midlatitude NAThe atmosphere is more sensitive to SST variability over the central‐midlatitude than subpolar NA [ABSTRACT FROM AUTHOR]

The role of internal variability in generating an apparent link between autumn Barents‐Kara sea (BKS) ice and the winter North Atlantic Oscillation (NAO) has been intensely debated. In particular, the robustness and causality of the link has been questioned by showing that BKS‐NAO correlations exhibit nonstationarity in both reanalysis and climate model simulations. We show that the lack of ice observations means nonstationarity cannot be confidently assessed using reanalysis prior to 1961. Model simulations are used to corroborate an argument that forced nonstationarity could result from ice edge changes due to global warming. Consequently, the observed change in BKS‐NAO correlations since 1960 might not be purely a result of internal variability and may also reflect that the ice edge has moved. The change could also reflect the availability of more accurate ice observations. We discuss potential implications for analysis based on coupled climate models, which exhibit large ice edge biases. Plain Language Summary: Does the amount of ice in the Barents‐Kara Sea influence European air pressure or are the patterns we see caused by random changes in the weather? In climate models and in estimates of the atmosphere's history these patterns change depending on which years we look at. This has been interpreted as evidence that the patterns are random. However, there are very few measurements of ice in this region before 1961, so we argue that looking at these years is not helpful. Since 1961, where we have more measurements, the winter sea ice edge has been moving Northwards because of global warming. When the ice in a particular region disappears, it changes the expected relationship with the atmosphere because heat can now quickly leave the ocean. We therefore hypothesize that some of the changes seen in the patterns may therefore not be random, but a result of ice edge changes. We also observe that different climate models put the ice edge in different places, and the same hypothesis therefore implies that models might not get potential ice‐air pressure relationships in specific regions correct. Key Points: A lack of observations means that ice‐NAO links cannot be confidently assessed with reanalysis prior to 1961Nonstationarity since 1961 may reflect forced changes to the ice edge, due to the dependence of heatflux anomalies on ice edge variabilityThe magnitude of this potential forced nonstationarity in the real world is currently unclear [ABSTRACT FROM AUTHOR]

A too‐weak eddy feedback in models has been proposed to explain the signal‐to‐noise paradox in seasonal‐to‐decadal forecasts of the winter Northern Hemisphere. We show that the "eddy feedback parameter" (EFP) used in previous studies is sensitive to sampling and multidecadal variability. When these uncertainties are accounted for, the EFP diagnosed from CMIP6 historical simulations generally falls within the reanalysis uncertainty. We find the EFP is not independent of the sampled North Atlantic Oscillation (NAO). Within the same dataset, a sample containing larger NAO variability will show a larger EFP, suggesting that the link between eddy feedbacks and the signal‐to‐noise paradox could be due to sampling effects with the EFP. An alternative measure of eddy feedback, the barotropic energy generation rate, is less sensitive to sampling errors and delineates CMIP6 models that have weak, strong, or unbiased eddy feedbacks, but shows little relation to NAO variability. Plain Language Summary: Model forecasts on seasonal‐to‐decadal timescales have recently been shown to have significant skill in predicting the North Atlantic Oscillation (NAO, a large‐scale pattern of variability). However, these forecasts are undermined by signal‐to‐noise ratios that are lower than expected given the skill, meaning the models are underconfident. This problem is known as the "signal‐to‐noise paradox". Previous work has shown that models underestimate the strength of feedback from atmospheric eddies onto the midlatitude circulation, but models with a stronger eddy feedback suffer less from the signal‐to‐noise paradox. However, we find that the "eddy feedback parameter" (EFP) used in these studies exhibits large sampling uncertainty that has not previously been taken into account. When accounting for this sampling uncertainty, the EFP in models is generally consistent with reanalysis data. Furthermore, across samples, the EFP correlates with the variability of the NAO, meaning they are not independent, which makes the EFP problematic for understanding the causes of the signal‐to‐noise paradox. Samples with larger NAO variability are diagnosed with a larger EFP, even within the same dataset. An alternative measure of eddy feedback is less sensitive to sampling and better identifies models which have weak, strong, or unbiased eddy feedbacks. Key Points: The "eddy feedback parameter" is a highly non‐stationary quantity, making reanalysis and model comparisons problematic on short time periodsSampling uncertainty in the eddy feedback parameter from reanalysis data is comparable to the intermodel spreadBarotropic energy generation rate is a more stable quantity, but does not explain model spread in North Atlantic climate variability [ABSTRACT FROM AUTHOR]

A continuous decrease in aerosols over the Western North Atlantic Ocean (WNAO) on a decadal timescale provides a long‐term benchmark to evaluate how various natural and anthropogenic processes affect the manifestation of aerosol‐cloud interactions in this region. Furthermore, the WNAO serves as a natural laboratory with diverse aerosol sources, marine boundary layer clouds more variable than those in marine stratocumulus deck regions, and unique flow regimes established by the Gulf Stream and the semi‐permanent Bermuda High. We investigate how satellite‐retrieved macrophysical and microphysical properties of low clouds and the surface shortwave irradiance changed from 2003 to 2020, in tandem with this aerosol decrease. The decadal changes in large‐scale meteorology related to the North Atlantic Oscillation (NAO) are also examined. We find a reduction in low‐cloud optical thickness, accompanied by fewer and larger cloud droplets, yet observe no significant changes in low‐cloud fraction and liquid water path. Despite the reduction in low‐cloud optical thickness together with aerosol decrease, a corresponding increase in the trends of surface shortwave irradiance, also known as surface brightening, is lacking. This absence of brightening is potentially related to concomitant changes found in large‐scale meteorology associated with NAO—Bermuda High strengthening, sea surface warming, and atmospheric moistening— as well as an increase in high‐level cloud fraction that can counteract the surface brightening. Ultimately, our findings suggest that spatial patterns of decadal meteorological variability introduce complexities in the surface cloud radiative effect over the WNAO, thereby complicating the isolation and examination of aerosol‐cloud interactions. Plain Language Summary: Over recent decades, the Western North Atlantic Ocean has experienced a steady decrease in aerosols—tiny particles in the air. This situation offers a chance to study how natural phenomena and human activities influence cloud‐aerosol interactions. The area is known for its diverse aerosol sources, complex cloud types, and distinct oceanic and atmospheric flow patterns influenced by the Gulf Stream and Bermuda High. By analyzing satellite data from 2003 to 2020, we investigated how low‐lying clouds and sunlight penetration have changed in response to fewer aerosols, and how the North Atlantic Oscillation (NAO) affects weather patterns. Our findings show that while low‐lying clouds have become more transparent with fewer, larger droplets, their coverage and juiciness have not changed significantly. Contrary to expectations, these changes have not lead to an increase in sunlight reaching the Earth's surface, a phenomenon known as "surface brightening." This could be due to NAO‐related warmer sea surfaces, increased moisture, and more high‐level clouds, which might obscure any brightening. Our study shows that weather shifts in the Western North Atlantic Ocean add complexity to understanding how clouds influence sunlight, challenging the study of aerosol‐cloud interactions. Key Points: In tandem with the continuous decrease in aerosol, low‐cloud droplets became fewer and larger over the western North AtlanticDespite concurrent changes in aerosol and low‐cloud optical properties, surface shortwave irradiance lacked reciprocal significant trendsMeteorological fields—temperature and humidity—correlated with the North Atlantic Oscillation had changed, exhibiting tripolar patterns [ABSTRACT FROM AUTHOR]

The extreme cooling of the Tibetan Plateau (TP) during the boreal winter typically poses threats to the local environment and people's safety, and it is usually attributed to internal climate variability. Here we demonstrate that the five recent large tropical volcanic eruptions since 1880 have caused an average extreme cooling of up to −0.80 K on the TP in observations during the first boreal winter following the eruptions. This cooling effect is much larger than the global average terrestrial cooling of −0.30 K after the eruptions. The multi-model ensemble mean (MME) of the Atmospheric Model Intercomparison Project (AMIP) runs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), in which realistic sea surface temperatures (SST) were specified, can simulate an extreme TP cooling response of up to −0.79 K, which is much larger than the direct aerosol cooling of −0.36 K simulated by the historical runs. The positive North Atlantic Oscillation (NAO) anomaly during the post-eruption winter after the eruptions plays a key role in amplifying the TP cooling through atmospheric teleconnection, which overwhelms the warming response associated with the frequently occurring El Niños. The results from this study provide a perspective on the potential contribution of volcanic activity or stratospheric sulfur injection scenarios to specific TP cooling. [ABSTRACT FROM AUTHOR]

Teleconnections like the El Niño/Southern Oscillation affect climate and weather conditions across the globe, including conditions that modulate tornado activity. Early studies of teleconnection/tornado activity relationships provided evidence of links between one teleconnection and tornado activity. Later attempts introduced multivariate approaches by analyzing bivariate distributions and integrating multiple teleconnections in statistical models to predict variability in tornado activity. However, little attention has been given to teleconnection interactions and the role of these interactions in modulating tornado activity. Here, we employ a data-driven, multiple logistic regression modelling approach to explore the interactions between the El Niño/Southern Oscillation, North Atlantic Oscillation, Artic Oscillation, and Pacific North American pattern and their ability to predict the odds of an active tornado period in the southeastern United States. We develop models at the annual, seasonal, and monthly scales and, in doing so, illustrate that the teleconnections and teleconnection interactions that best predict the odds of an active tornado period differ across timescales and that the relationships exhibit clear seasonality. We also show climate conditions associated with select interactions, like the ENSO-NAO interaction in spring, that help explain the elevated tornado activity, namely anomalously high near-surface air temperature and humidity steered by an anomalously strong subtropical high. [ABSTRACT FROM AUTHOR]

Ensemble forecasts have been shown to better predict observed Atlantic climate variability than that of their own ensemble members. This phenomenon—termed the signal‐to‐noise paradox—is found to be widespread across models, timescales, and climate variables, and has wide implications. The signal‐to‐noise paradox can be interpreted as forecasts underestimating the amplitude of predictable signals on seasonal‐to‐decadal timescales. The cause of this remains unknown. Here, we examine sea level pressure variability from a very large multi‐model ensemble of uninitialized atmosphere‐only simulations, focusing on boreal winter. To assess signal‐to‐noise errors, the ratio of predictable components (RPC) is examined globally, as well as for regional climate indices: the North Atlantic Oscillation, Arctic Oscillation, Southern Annular Mode, and an Arctic index. Our analyses reveal significant correlations between the multi‐model ensemble‐mean and observations over large portions of the globe, particularly the tropics, North Atlantic, and North Pacific. However, RPC values greater than one are apparent over many extratropical regions and in all four climate indices. Higher‐resolution models produce greater observation‐model correlations and greater RPC values than lower‐resolution models in all four climate indices. We find that signal‐to‐noise errors emerge more clearly at higher resolution, but the amplitudes of predictable signals do not increase with resolution, at least across the range of resolutions considered here. Our results suggest that free‐running atmospheric models underestimate predictable signals in the absence of sea surface temperature biases, implying that signal‐to‐noise errors originate in the atmosphere or in ocean–atmosphere coupling. [ABSTRACT FROM AUTHOR]

A climatology of snow water equivalent (SWE) based on data collected at 240 gauging sites was performed for the Italian Alps over the 1967–2020 period, when Enel routinely conducted snow depth and density measurements with homogeneous methods. Six hydrological sub-regions were investigated spanning from the eastern Alps to the western Alps at altitudes ranging from 1000 to 3000 m a.s.l. Measurements were conducted at fixed dates at the beginning of each month from 1 February to 1 June and on 15 April. To our knowledge, this is the most comprehensive and homogeneous dataset of measured snow depth and density for the Italian Alps. Significant decreasing trends over the years at all fixed dates and elevation classes were identified for both snow depth, equal to -0.12 ± 0.06 m per decade, and snow water equivalent, equal to -51 ± 37 mm per decade, on average in the six macro-basins we selected. The analysis of bulk snow density data showed a temporal evolution along the snow accumulation and melt season, but no altitudinal trends were found. A Moving Average and Running Trend Analysis (MARTA triangles), combined with a Pettitt's test change-point detection, highlighted a decreasing change of snow climatology occurring around the end of the 1980s. The comparison with winter temperature and precipitation data from the HISTALP dataset identified a major role played by temperature on the long-term decrease and changing points of snow depth and SWE with respect to precipitation, mainly responsible for its variability. Correlation with climatic indexes indicates significant negative values of the Pearson correlation coefficient with winter North Atlantic Oscillation (NAO) and positive values with winter Western Mediterranean Oscillation (WeMO) for some areas and elevation classes. Results of this climatology are synthesized in a temporal polynomial model that is useful for climatological studies and water resources management in mountain areas. [ABSTRACT FROM AUTHOR]

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]

The Taklamakan and Gobi Desert (TGD) region has experienced a pronounced increase in summer precipitation, including high-impact extreme events, over recent decades. Despite identifying large-scale circulation changes as a key driver of the wetting trend, understanding the relative contributions of internal variability and external forcings remains limited. Here, we approach this problem by using a hierarchy of numerical simulations, complemented by diverse statistical analysis tools. Our results offer strong evidence that the atmospheric internal variations primarily drive this observed trend. Specifically, recent changes in the North Atlantic Oscillation have redirected the storm track, leading to increased extratropical storms entering TGD and subsequently more precipitation. A clustering analysis further demonstrates that these linkages predominantly operate at the synoptic scale, with larger contributions from large precipitation events. Our analysis highlights the crucial role of internal variability, in addition to anthropogenic forcing, when seeking a comprehensive understanding of future precipitation trends in TGD. The Taklamakan and Gobi Desert region has witnessed a significant rise in summer precipitation in recent decades. This study shows that atmospheric internal variability, rather than external forcings, is the main driver shaping this wetting trend. [ABSTRACT FROM AUTHOR]

The impact of interactive ocean dynamics on internal variations of Atlantic sea surface temperature (SST) is investigated by comparing preindustrial control simulations of a fully coupled atmosphere–ocean–ice model to the same atmosphere–ice model with the ocean replaced by a motionless slab layer (henceforth slab ocean model). Differences in SST variability between the two models are diagnosed by an optimization technique that finds components whose variance differs as much as possible. This technique reveals that Atlantic SST variability differs significantly between the two models. The two components with the most extreme enhancement of SST variance in the slab ocean model resemble the tripole SST pattern associated with the North Atlantic Oscillation (NAO) and the Atlantic multidecadal variability (AMV) pattern. This result supports previous claims that ocean dynamics are not necessary for the AMV, although ocean dynamics lead to slight increases in the memory of both the AMV and the NAO tripole. The component with the most extreme enhancement of SST variance in the fully coupled model resembles the Atlantic Niño pattern, confirming the ability of our technique to isolate physical modes known to require ocean dynamics. The second component with more variance in the fully coupled model is a mode of subpolar SST variability. Both the reemergence of SST anomalies and changes in ocean heat transport lead to increased SST variance and memory in the subpolar Atlantic. Despite large differences in the mean and variability of SST, atmospheric variability is quite similar between the two models, confirming that most atmospheric variability is generated by internal atmospheric dynamics. [ABSTRACT FROM AUTHOR]

Identifying the climate-induced variability in the condition of vegetation is particularly important in the context of recent climate change and plants' impact on the mitigation of climate change. In this paper, we present the coherence and time lags in the spectral response of three individual vegetation types in the European temperate zone to the influencing meteorological factors in the period 2002–2022. Vegetation condition in broadleaved forest, coniferous forest and pastures was measured with monthly anomalies of two spectral indices – normalised difference vegetation index (NDVI) and enhanced vegetation index (EVI). As meteorological elements we used monthly anomalies of temperature (T), precipitation (P), vapour pressure deficit (VPD), evapotranspiration (ETo), and the teleconnection indices North Atlantic Oscillation (NAO) and North Sea Caspian Pattern (NCP). Periodicity in the time series was assessed using the wavelet transform, but no significant intra- or interannual cycles were detected in both vegetation (NDVI and EVI) and meteorological variables. In turn, coherence between NDVI and EVI and meteorological elements was described using the methods of wavelet coherence and Pearson's linear correlation with time lag. In the European temperate zone analysed in this study, NAO produces strong coherence mostly for forests in a circa 1-year band and a weaker coherence in a circa 3-year band. For pastures these interannual patterns are hardly recognisable. The strongest relationships occur between conditions of the vegetation and T and ETo – they show high coherence in both forests and pastures. There is a significant cohesion with the 8–16-month (ca. 1-year) and 20–32-month (ca. 2-year) bands. More time-lagged significant correlations between vegetation indices and T occur for forests than for pastures, suggesting a significant lag in the forests' response to the changes in T. [ABSTRACT FROM AUTHOR]

Detecting recurrent weather patterns and understanding the transitions between such regimes are key to advancing our knowledge of the low-frequency variability of the atmosphere and have important implications in terms of weather and climate-related risks. We adopt an analysis pipeline inspired by Markov State Modelling and detect in an unsupervised manner the dominant winter mid-latitude Northern Hemisphere weather patterns in the Atlantic and Pacific sectors. The daily 500 hPa geopotential height fields are first classified in about 200 microstates. The weather dynamics are then represented on the basis of these microstates and the slowest decaying modes are identified from the spectral properties of the transition probability matrix. These modes are defined on the basis of the nonlinear dynamical processes of the system and not as tentative metastable states, as often done in Markov state analysis. When focusing on a shifting longitudinal window of 60∘, we find that the longitude-dependent estimate of the longest relaxation time is smaller where stronger baroclinic activity is found. In the Atlantic and Pacific sectors slow relaxation processes are mainly related to transitions between blocked regimes and zonal flow. We also find strong evidence of a dynamical regime associated with the simultaneous Atlantic-Pacific blocking. When the analysis is performed on a broader geographical region of the Atlantic sector, we discover that the slowest relaxation modes of the system are associated with transitions between dynamical regimes that resemble teleconnection patterns like the North Atlantic Oscillation and weather regimes like the Scandinavian and Greenland blocking, yet have a much stronger dynamical foundation than classical methods based e.g. on EOF analysis. Our method clarifies that, as a result of the lack of a time-scale separation in the atmospheric variability of the mid-latitudes, there is no clear-cut way to represent the atmospheric dynamics in terms of few, well-defined modes of variability. The approach proposed here can be seamlessly applied across different regions of the globe for detecting regional modes of variability, and has a great potential for intercomparing climate models and for assessing the impact of climate change on the low-frequency variability of the atmosphere. [ABSTRACT FROM AUTHOR]

The Little Ice Age (LIA) was a period of most recent glacial advancement and had pronounced cooling effect in the North Atlantic region. Synchronous hydroclimate changes are also reported from the Himalayas, however owing to the heterogeneity within the proxy reconstructions, their relationship with LIA cooling is unclear. Varied topography, huge glacial mass, and multiple moisture sources (both from the Indian Summer Monsoon (ISM) and the Westerlies) makes understanding of the impact of LIA cooling on this region ambiguous. In this study, we review and assess the existing paleoclimatic proxy records for a comprehensive analysis of the regional response of the Western Himalayas to LIA cooling. Using the existing meteorological reanalysis data for back trajectory analysis for the last 20 years, the Western Himalayan region was classified into three different zones based on the relative percentage of moisture-bearing-wind-source contribution. The upper Western Himalayas receive most of the moisture from the Westerlies, both Middle and Lower Western Himalayas receive majority of rainfall from the ISM, with a relatively higher contribution of Westerlies in the Lower Western Himalayas. Comparison of reconstructions using Principal Component Analysis reveal consistent high moisture conditions during the LIA, with increased winter precipitation and decreased summer precipitation coherently in all the records. Spectral analysis of the available proxy records and various climate forcing for LIA cooling show similar dominant frequency, attesting that the LIA cooling drove the hydroclimate changes in the Western Himalayan region. External forcings such as decreased solar activity and increased volcanic activity caused cooling, influenced the Inter Tropical Convergence Zone, and resulted in weaker summer rainfall during the LIA. Synchronous changes in the North Atlantic Oscillations and El Niño–Southern Oscillation records with precipitation records suggest a link between "monsoon breaks" and enhanced Westerly intensity and an intensified winter precipitation in this region. [ABSTRACT FROM AUTHOR]

Rainfall seasonality in Serbia is examined trough the analysis of several indices: seasonality index (SI), individual seasonality index ( SI i) , and replicability index (RI). Based on data from 14 synoptic stations that are well distributed over Serbian territory, spatial distribution of general seasonality index SI ¯ , mean individual seasonality index SI ind ¯ , and RI are analyzed in two subperiods (1961–1990 and 1991–2020). The modified Mann–Kendall test (MMK) and Sen's slope methods are used to investigate the possible trends and its magnitudes in time series of SI i . The values of SI ¯ show that precipitation regime in Serbia is very equitable or equitable with definite wetter season. For the entire Serbian territory, the values of RI are low, indicating that the month of maximum rainfall occurs over large spread of months along the studied periods. The existence of significant negative correlation between RI and longitude is found. Results show a highest influence of the North Atlantic Oscillation and East Atlantic/West Russia pattern on rainfall seasonality in Serbia. [ABSTRACT FROM AUTHOR]

Using a CESM1 control simulation, we conduct a follow-up study to advance our earlier theoretical research on the multicentennial oscillation (MCO) of the Atlantic meridional overturning circulation (AMOC). The modeled AMOC MCO primarily arises from internal oceanic processes in the North Atlantic, potentially representing a North Atlantic Ocean–originated mode of AMOC multicentennial variability (MCV) in reality. Specifically, this AMOC MCO is mainly driven by salinity variation in the subpolar upper North Atlantic, which dominates local density variation. Salinity anomaly in the subpolar upper ocean is enhanced by the well-known positive salinity advection feedback that is realized through anomalous advection in the subtropical to subpolar upper ocean. Meanwhile, mean advection moves salinity anomaly in the subtropical intermediate ocean northward, weakening the subpolar upper salinity anomaly and leading to its phase change. The salinity anomalies have a clear three-dimensional life cycle around the North Atlantic. The mechanism and time scale of the modeled AMOC MCO are consistent with our earlier theoretical studies. In the theoretical model, artificially deactivating either the anomalous or mean advection in the AMOC upper branch prevents it from exhibiting AMOC MCO, underscoring the indispensability of both the anomalous and mean advections in this North Atlantic Ocean–originated AMOC MCO. In our coupled model simulation, the South Atlantic and Southern Oceans do not exhibit variabilities synchronous with the AMOC MCO; the Arctic Ocean's contribution to the subpolar upper salinity anomaly is much weaker than the North Atlantic. Hence, this North Atlantic Ocean–originated AMOC MCO is distinct from the previously proposed Southern Ocean–originated and Arctic Ocean–originated AMOC MCOs. [ABSTRACT FROM AUTHOR]

Of the climate variability patterns that influence the weather in the North Atlantic region in winter, the North Atlantic Oscillation (NAO) is the most dominant. The effects of the NAO span from cold air outbreaks to unseasonably warm conditions and unusual precipitation, with significant impacts on human activities and ecosystems. While a connection between the NAO and antecedent sea surface temperature (SST) conditions has been recognised for decades, the precise causal interaction between the ocean and the atmosphere remains enigmatic. In this study we uncover a robust statistical relationship between North Atlantic SSTs in November and the NAO throughout the subsequent winter in the extended ERA5 reanalysis back to 1940. We apply a well-established causal inference technique called mediation analysis, commonly used in social science and now adopted in climate research. This analysis highlights the roles of low-level baroclinicity, latent heat fluxes, and latent heat release in mediating the effect of November SSTs on the NAO in January and February. It is important to recognise that these mediators are interrelated. Moreover, our analysis reveals bidirectional relationships, where the NAO reciprocally mediates the effects of the November SSTs on these variables. This is evidence of a complex web of feedback mechanisms which collectively contribute to the response of the winter NAO to late autumn/early winter SSTs. [ABSTRACT FROM AUTHOR]

Among the global monsoon systems, the Asian summer monsoon (ASM) reaches the furthest north into eastern Asia and separates it into the monsoon- and westerlies-dominated regions. Paleoclimate studies revealed different hydroclimate patterns between the monsoon- and westerlies-dominated regions at glacial-interglacial and centennial timescales. The monsoon-westerlies boundaries are difficult to be quantified with the instrumental data. Herein, a monsoon-westerlies dipole pattern was identified by empirical orthogonal function (EOF) analysis of the Palmer Drought Severity Index (PDSI) for the 1900–2018 period on interdecadal timescales. This dipole pattern showed significant correlations with variations of the monsoon-related western Pacific sea surface temperature (SST) and the westerlies-related North Atlantic Oscillation (NAO). We then reconstructed the dipole pattern back to 1511 by tree rings, which was consistent with the reconstructed NAO at interdecadal timescale. Our reconstruction revealed long-term changes of monsoon-westerlies boundaries and provided evidence of their linkages with the NAO. Apart from anthropogenic forcing, climate internal variability also play a critical role in modulations of the dipole mode between ASM and westerlies at interdecadal timescale. [ABSTRACT FROM AUTHOR]