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Development of ocean measurement technologies can improve monitoring of the global Ocean Heat Content (OHC) and Heat Storage Rate (HSR) that serve as early-warning indices for climate-critical circulation processes such as the Atlantic Meridional Overturning Circulation and provide real-time OHC assessments for tropical cyclone forecast models. This paper examines the potential of remotely measuring ocean temperature profiles using a simulated Brillouin lidar for calculating ocean HSR. A series of data analysis ('Nature') and Observational Systems Simulation Experiments (OSSEs) were carried out using 26 years (1992–2017) of daily mean temperature and salinity outputs from the ECCOv4r4 ocean circulation model. The focus of this study is to compare various OSSEs carried out to measure the HSR using a simulated Brillouin lidar against the HSR calculated from the ECCOv4r4 model results. Brillouin lidar simulations are used to predict the probability of detecting a return lidar signal under varying sampling strategies. Correlations were calculated for the difference between sampling strategies. These comparisons ignore the measurement errors inherent in a Brillouin lidar. Brillouin lidar technology and instruments are known to contain numerous, instrument-dependent errors and remain an engineering challenge. A significant decrease in the ability to measuring global ocean HSRs is a consequence of measuring ocean temperature from nadir-pointing instruments that can only take measurements along-track. Other sources of errors include the inability to fully profile ocean regions with deep mixed layers, such as the Southern Ocean and North Atlantic, and ocean regions with high light attenuation levels. [ABSTRACT FROM AUTHOR]

Global warming is causing poleward expansion of species ranges. Temperate seas, in particular, are undergoing a process known as 'tropicalisation', i.e., the combination of sea-water warming and establishment of southern species. The Ligurian Sea is one of the coldest sectors of the Mediterranean and has thus been characterized by a dearth of warm-temperate species and a comparative abundance of cold-temperate species. This paper uses a time series of sea surface temperature (SST) and new records of thermophilic fish species to reconsider the biogeography of the Ligurian Sea. SST has risen by about 0.7 °C on average between 1948 and 2023, but two phases may be distinguished: a cool one (ended in the mid-1980s) and a warm one (still ongoing); the latter phase shows alternating periods of rapid warming and comparatively stationary temperature. The arrival of thermophilic species coincided with the periods of rapid warming; some of these species were established in the subsequent stationary periods. Heatwaves and climate-related diseases associated with the periods of rapid warming have caused mass mortalities of autochthonous species. Our knowledge on the biogeography of the Ligurian Sea was established during the cool phase; the present situation, however, calls for re-defining the chorological spectrum of the Ligurian Sea biota. [ABSTRACT FROM AUTHOR]

Recent studies have highlighted the increasingly dominant role of external forcing in driving Atlantic and Pacific Ocean variability during the second half of the 20th century. This paper provides insights into the underlying mechanisms driving interactions between modes of variability over the two basins. We define a set of possible drivers of these interactions and apply causal discovery to reanalysis data, an ensemble of pacemaker simulations where the observed El Niño Southern Oscillation (ENSO) is prescribed, and a pre-industrial control simulation. We also utilize large ensemble means of historical simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to quantify the effect of external forcing and improve the understanding of its impact. By conducting a causal analysis of the historical time series, a regime switch is identified in the interactions between major modes of Atlantic and Pacific climate variability. Causal networks derived from pacemaker simulations support this finding and further demonstrate that the effect of external forcing could favor an Atlantic-driven regime between 1985 and 2014 where warming tropical North Atlantic sea surface temperatures induce a La Niña-like cooling in the equatorial Pacific during the following season through a strengthening of the Pacific Walker Circulation. This negative sign effect was not detected when the historical external forcing signal is removed in the pacemaker ensemble. The analysis of the pre-industrial control run further supports the notion that the Atlantic and Pacific modes of natural climate variability exert contrasting impacts on each other even in the absence of external forcing. We show that causal discovery can quantify previously unknown connections and thus provides important potential to contribute to a deeper understanding of the mechanisms driving changes in regional and global climate variability. [ABSTRACT FROM AUTHOR]

The SSS (sea surface salinity) is an important factor affecting global climate changes, sea dynamic environments, global water cycles, marine ecological environments, and ocean carbon cycles. Satellite remote sensing is a practical way to observe SSS from space, and the key to retrieving SSS satellite products is to establish an accurate sea surface brightness temperature forward model. However, the calculation results of different forward models, which are composed of different relative permittivity models and SSR (sea surface roughness) brightness temperature increment models, are different, and the impact of this calculation difference has exceeded the accuracy requirement of the SSS inversion, and the existing SSR brightness temperature increment models, which primarily include empirical models and theoretical models, cannot match all the relative permittivity models. In order to address this problem, this paper proposes a universal DNN (deep neural network) model architecture and corresponding training scheme, and provides different SSR brightness temperature increment models for different relative permittivity models utilizing DNN based on offshore experiment data, and compares them with the existing models. The results show that the DNN models perform significantly better than the existing models, and that their calculation accuracy is close to the detection accuracy of a radiometer. Therefore, this study effectively solves the problem of SSR brightness temperature correction under different relative permittivity models, and provides a theoretical support for high-precision SSS inversion research. [ABSTRACT FROM AUTHOR]

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

Simple Summary: This paper analyzed the different relationships between earlywood and latewood as well as total tree-ring growth and the climate factors and reconstructed 106 years of May–June mean temperature (TMJ) in the Tongbai Mountains based on the earlywood width chronology of Pinus taiwanensis Hayata. It also analyzed the linkages to the Indian and Pacific Oceans. This paper found that earlywood width chronology has better response to the climate factors than latewood width and total tree-ring width. This study also found that the main limiting factors that restrained radial growth of Pinus taiwanensis Hayata in the Tongbai Mountains were May–June mean temperature and mean maximum temperature. The reconstructed TMJ series have a better reliability and are significantly negatively correlated with sea surface temperature (SST) over the tropical Western Pacific Ocean and Indian Ocean and are significantly positively correlated with SST over the subtropical Pacific Ocean. Finally, the periodic fluctuations of TMJ in the Tongbai Mountains might be related to the quasi-biennial interannual oscillation of SST over the Indo-Pacific equatorial region (QBO). The results of this study are significant for further understanding and exploring forest growth and climate change in the climatic transition zone. The Tongbai Mountains are an ecologically sensitive region to climate change, where there lies a climatic transitional zone from a subtropical to a warm–temperate monsoon climate. The northern boundary of Pinus taiwanensis Hayata is here; thus, climate information is well recorded in its tree rings. Based on developed earlywood width (EWW), latewood width (LWW) and total ring width (RW) chronologies (time period: 1887–2014 year) of Pinus taiwanensis Hayata in the Tongbai Mountains in central China, this paper analyzed characteristics of these chronologies and correlations between these chronologies and climate factors. The correlation results showed that earlywood width chronology contains more climate information than latewood width chronology and total ring width chronology, and mean temperature and mean maximum temperature in May–June were the main limiting factors for radial growth of Pinus taiwanensis Hayata. The highest significant value in all correlation analyses is −0.669 (p < 0.05) between earlywood width chronology and May–June mean temperature (TMJ) in the pre-mutation period (1958–2005) based on mutating in 2006. Thus, this paper reconstructed May–June mean temperature using earlywood width chronology from 1901 to 2005 (reliable period of earlywood width chronology is 1901–2014). The reconstructed May–June mean temperature experienced eight warmer periods and eight colder periods and also showed 2–3a cycle change over the past 105 years. The spatial correlation showed that the reconstructed series was representative of the May–June mean temperature variation in central and eastern China and significant positive/negative correlation with the sea surface temperature (SST) of the subtropical Pacific Ocean and the tropical Western Pacific Ocean and Indian Ocean from the previous October to the current June. This also indicated that May–June mean temperature periodic fluctuations might be related to the quasi-biennial oscillation (QBO) in the tropical Western Pacific Ocean and Indian Ocean. The results of this study have extended and supplemented the meteorological records of the Tongbai Mountains and have a guiding significance for forest tending and management in this area. [ABSTRACT FROM AUTHOR]

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

The Earth's oceans serve as vast heat storage reservoirs and the ocean currents, forming a heat transfer zone, act as a buffer for climate change. The oceans play a crucial role in the water cycle, carbon cycle, and nitrogen cycle, interacting with the atmosphere. However, the increasing occurrence of heatwaves in recent years has disrupted the stability of the oceans and affected their function as a global thermostat. This paper examines relevant literature from the Web of Science database spanning from 1996 to 2023. Our analysis reveals the evolving research hotspots regarding the impact of heatwaves on ocean carbon sinks, progressing from "carbon dioxide - carbon emissions - ocean - seawater - organic matter - marine sediment" over the past decades. Keyword frequency and centrality analysis indicate a deepening focus in this field of study. The research areas primarily revolve around climate change, carbon dioxide, ocean variability, the influence of high temperatures on the carbon cycle, the weakening of the ocean carbon sink function, and ocean temperature. This study summarizes research findings on the mechanisms by which high temperature heatwaves affect ocean carbon sinks, alterations in ocean carbon cycle patterns, their impacts on marine ecosystems, and factors influencing seawater temperature and heatwave occurrence. Finally, the paper discusses novel findings in this field and proposes countermeasures to enhance ocean sink capacity amidst the warming trend. • The research hotspots have shifted from "carbon dioxide-carbon emissions-ocean-seawater-organic matter-marine sediment". • The study analyzes mechanisms by which high-temperature heat waves affect ocean carbon sinks and identifies influencing factors. • The research presents novel findings in this area and proposes strategies to enhance the capacity of ocean sinks. [ABSTRACT FROM AUTHOR]

Due to the current situation when we observe numerous climate changes, manifested by rising air and seawater temperatures, there have been observed also, changes in recent years regarding the biology aspects of some fish species from the Romanian Black Sea coast. Trachurus mediterraneus (Steindachner, 1868) - horse mackerel, having economic importance it is necessary to observe its biology in order to develop an appropriate management required by the changes observed at the population level. This paper presents results on temporal variations of total length and weight, age composition, growth parameters and sex ratio of the Mediterranean horse mackerel from the Romanian Black Sea coast. Data were collected from commercial trap net catch and from pelagic trawl expeditions in the period 2018-2020. Significant differences were observed between the length distribution and the stations, with the specification that in 2020 individuals from classes of smaller lengths predominated compared to previous years. [ABSTRACT FROM AUTHOR]

Marine heatwaves are discrete and prolonged periods of anomalously warm seawater temperature which have devastating ecological and socioeconomic impacts. Being part of the center of marine biodiversity and a fisheries-dependent country, the Philippines is vulnerable to the threats of marine heatwaves, but these extreme events remain understudied in the country. It is, therefore, crucial to investigate the development of marine heatwaves and to assess and predict the impacts of these events in the Philippine seas. In this perspective paper, we aim to put forward the research direction for advancing our understanding of marine heatwaves and their impacts in the Philippines. The limited studies on marine heatwaves in the Philippines highlight the need for progress in understanding the spatiotemporal patterns, physical processes, and impacts of marine heatwaves in the country. Advancing our knowledge of marine heatwaves will help us formulate mitigating strategies for ocean warming in fisheries management and marine biodiversity conservation in the Philippines. [ABSTRACT FROM AUTHOR]

This study investigates some of the uncertainties sources associated with the pseudo global warming (PGW) approach which was employed to project future patterns of tropical cyclones (TCs) over the Arabian Sea (AS). First, the climate variables controlling the patterns of tropical cyclones were extracted from reanalysis datasets of ERA5, ERAI, CFSR, and NCEP/NCAR. Then, each dataset was evaluated against long‐term measurements to identify the best‐performing reanalysis dataset. ERA5 showed the best performance for most of the variables. Outputs of 20 CMIP5 global climate models (GCMs) were then evaluated against the ERA5 data resulting in an ensemble of the best performing GCMs. A PGW framework was then used to project the changes in patterns of three significant historical cyclones: Gonu, Phet, and Ashobaa. In doing so, the signals of future climate variables were extracted from the GCMs ensemble to modify the initial and boundary conditions of the WRF model which was previously tuned for reproducing the historical TCs. Different tests were conducted to address the sources of uncertainty in the PGW approach, including the selection of the climate variables contributing to the computation of the signals, the selection of GCMs, and the spatial variation of signals. A considerable sensitivity of the projected track and intensity of TCs to the choice of GCMs was observed, acknowledging the importance of GCMs evaluation before calculating the signals. Moreover, it was found that among all variables, signals of sea surface temperature and air temperature have major effects on the cyclone's track and intensity. Apart from that, when the signals were applied to the domain of the WRF model uniformly, compared to applying spatially varying signals, different tracks and intensities for future TCs were also observed. Overall, the findings of this paper challenge the reliability of the projected changes in TCs patterns obtained from PGW. [ABSTRACT FROM AUTHOR]

• The proposed tropical cyclone model is completely driven by a set of environmental variables. • This model reproduces the spatial and temporal characteristics of observed tropical cyclones. • The model achieves remarkable balance between computational complexity and efficiency. • This model will provide decision-makers with valuable information regarding potential wind-induced hazards. • When future climate data are fed into this model, the impact of climate change on tropical cyclones can be evaluated. This paper presents an environment-driven tropical cyclone (TC) model for the Western North Pacific basin, which comprises a revised Poisson regression genesis model, a tailored beta-advection track model, and a fast intensity model. The TC model reproduces the temporal and spatial distributions of genesis events, the motion pattern of tracks, as well as the intensity evolutions along tracks. Risk analyses for Hong Kong and along the southeast coastline of mainland China demonstrate that this model can simulate extreme TC events with high fidelity. And the Gaussian mixture model outperforms the Frank Copula in approximating the joint distributions of the annual maximum wind speeds and the corresponding wind directions. This model is driven by a set of environmental variables including relative vorticity, relative humidity, sea surface temperature, vertical wind shear, potential intensity, sub mixed layer depth stratification, mixture layer depth and so on. This enables the model to not only reproduce historical records, but also make predictions for future TC behaviors under climate change with combination of global climate models. Besides, the computational efficiency of the TC model is comparable to traditional purely statistical models. The proposed model can also be coupled with other natural hazard models to conduct multi-hazard analysis. [ABSTRACT FROM AUTHOR]

Thar Desert is a rainwater shortage (approximately 500-100 mm/year) in the north-west ofIndia. Formerly available research on radiocarbon chronology, sediment faces, and mineralogy has facilitated to recreate orbital-scale lake beds and differences in liquid column salinity in five separate lacustrine basins in the desert. We measured the hydrological situations with respect to the intensity (i.e. quantity and regional coverage) of the southwest summertime rainy season after the last extreme ice age (LGM). Around LGM and c. 15 cal. ka BP, the eastern basins held freshwater and hyper-salt beach reservoirs, and the western portion had an irregular variable pool. A change from salt-hyper-salt beach ponds to constant deep lakes happened in the eastern boundary at around 15 cal. ka BP as further summertime insolation raised the (sea surface temperature) SST of the Indian Oceanic and improved the summer rainy season in the southwest. During the Pleistocene-Holocene transition, the utmost midsummer sunshine as well as the colder sea surface temperature ofthe Indian Oceanic raised the volume of summertime rainfall and spread the southwestern monsoon across the desert. This research paper included surveys of several households in Thar Desert, as well as emphasis on community meetings, main knowledge interviews, and stakeholder consultations and numerous publications and research papers on climate change and catastrophe related topics. [ABSTRACT FROM AUTHOR]

Surface temperature is one of the first ocean variables investigated. Ocean temperature is a key indicator of global climate change. The anomalies in ocean temperature have caused significant deterioration of marine systems. Existing works on surface temperature anomaly considered a suite of other remote sensing measurements such as wave height, salinity and models such as support vector machine, self-organizing maps and convolutional neural networks. Neural networks are used for predicting the surface temperature. This paper proposes use of long short-term memory, a recurrent neural network method to the estimate sea surface temperature anomalies based on previous year's sea surface temperature anomalies. NOAA OI SST V2 dataset with 40 years of data is used in the experimentation. Auto-regression is used during data preprocessing. The basic LSTM method with 3 blocks of size 2 is enhanced to 50 neurons. This proposed LSTM model has been assessed for performance on time series data, yearly wise and for the entire dataset and found that the model has been able to predict the anomalies with a reasonably good precision. The model produced error of 0.036 indicating that the model is feasible for predicting the temperature anomaly and mean absolute error of 0.14 on the testing data. [ABSTRACT FROM AUTHOR]

The growing impact of climate change on port infrastructure and facilities currently may lead to a rising frequency of such serious natural disasters or accidents as rising sea level, increasing extreme weather, increasing intensity of tropical storms and typhoons, rising wave height surmounting breakwater design levels, heavy rain exceeding quay well drainage capacity, rising ocean temperatures, and deteriorating harbor water quality. The paper aims to apply a risk management matrix approach to vulnerability assessment and identification of desirable adaptation strategies. The data for this investigation is first collected by means of questionnaire survey of experts in shipping companies or port management offices at the Kaohsiung port. Then, a vulnerability analysis of port infrastructure and facilities is carried out under the impact of severe typhoons. Subsequently, adaptation strategies are identified for infrastructure and facilities at the Kaohsiung port to address the adverse impacts of climate change. One intellectual merit of this paper is that ten vulnerability assessment criteria are proposed for addressing the impacts of climate change on port infrastructure and facilities. Second, both ground and access roads in the port area, and drainage facilities in flooding-prone areas are shown to be damaged in the moderate risk areas potentially impacted by typhoons. The third merit is that a set of adaptation strategies has been identified for the moderate risk areas impacted by serious typhoons. • A risk management matrix approach is applied to assess vulnerability and identify desirable adaptation strategies. • 10 vulnerability assessment criteria are given for solving impacts of climate change on port infrastructure and facilities. • Both ground and access roads in the port area and drainage facilities in flooding-prone areas are shown to be damaged. • A set of adaptation strategies has been identified for moderate risk areas impacted by serious typhoons. [ABSTRACT FROM AUTHOR]

This paper introduces the Flexible Global Ocean‐Atmosphere‐Land System Model: Grid‐Point Version 3 (FGOALS‐g3) and evaluates its basic performance based on some of its participation in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) experiments. Our results show that many significant improvements have been achieved by FGOALS‐g3 in terms of climatological mean states, variabilities, and long‐term trends. For example, FGOALS‐g3 has a small (−0.015°C/100 yr) climate drift in 700‐yr preindustrial control (piControl) runs and smaller biases in climatological mean variables, such as the land/sea surface temperatures (SSTs) and seasonal soil moisture cycle, compared with its previous version FGOALS‐g2 during the historical period. The characteristics of climate variabilities, for example, Madden‐Julian oscillation (MJO) eastward/westward propagation ratios, spatial patterns of interannual variability of tropical SST anomalies, and relationship between the East Asian Summer Monsoon and El Niño–Southern Oscillation (ENSO), are well captured by FGOALS‐g3. In particular, the cooling trend of globally averaged surface temperature during 1940–1970, which is a challenge for most CMIP3 and CMIP5 models, is well reproduced by FGOALS‐g3 in historical runs. In addition to the external forcing factors recommended by CMIP6, anthropogenic groundwater forcing from 1965 to 2014 was incorporated into the FGOALS‐g3 historical runs. Plain Language Summary: The sixth phase of the Coupled Model Intercomparison Project (CMIP6) is a crucial support for the sixth Assessment Report of Intergovernmental Panel on Climate Change (IPCC AR6) and will also provide important foundation for research in climate change in the next few years. This paper gives the description of FGOALS‐g3 model, its experiment configures, and the experiments conducted according to the experimental design of CMIP6 and evaluates the preliminary performance of model simulation. This work offers references to CMIP6 data users and provides enormous output data sets for assessing and understanding climate change. Key Points: This paper describes FGOALS‐g3 and its experiment design for CMIP6Historical, preindustrial, and scenario simulations are evaluatedClimate drift is small in preindustrial simulation, and mean climate and climate variabilities at different temporal scales are realistic in historical runs [ABSTRACT FROM AUTHOR]

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

Evidence from previous climate model simulations has suggested a potentially low efficacy of contrails to force global mean surface temperature changes. In this paper, a climate model with a state-of-the-art contrail cirrus representation is used for fixed sea surface temperature simulations in order to determine the effective radiative forcing (ERF) from contrail cirrus. ERF is expected to be a good metric for intercomparing the quantitative importance of different contributions to surface temperature and climate impact. Substantial upscaling of aviation density is necessary to ensure statistically significant results from our simulations. The contrail cirrus ERF is found to be less than 50% of the respective instantaneous or stratosphere adjusted radiative forcings, with a best estimate of roughly 35%. The reduction of ERF is much more substantial for contrail cirrus than it is for a CO2 increase when both stratosphere adjusted forcings are of similar magnitude. Analysis of all rapid radiative adjustments contributing to the ERF indicates that the reduction is mainly induced by a compensating effect of natural clouds that provide a negative feedback. Compared to the CO2 reference case, a less positive combined water vapor and lapse rate adjustment also contributes to a more distinct reduction of contrail cirrus ERF, but not as much as the natural cloud adjustment. Based on the experience gained in this paper, respective contrail cirrus simulations with interactive ocean will be performed as the next step toward establishing contrail cirrus efficacy. ERF results of contrail cirrus from other climate models equipped with suitable parameterizations are regarded as highly desirable. [ABSTRACT FROM AUTHOR]

The data obtained during the recent decades indicate large-scale climatic changes in the Arctic Ocean, especially in the Siberian shelf seas. The impact of shrinking of the Arctic ice cover on marine net primary production (PP) was mostly studied using satellite-derived estimates of chlorophyll-a (Chl a), sea surface temperature, and sea ice concentrations, as well as various modeling approaches. However, no data are available on the quantitative relations between phytoplankton production and heterotrophic bacterioplankton activity in the broadest and shallowest shelf of the World Ocean - the East Siberian Arctic seas (ESAS). In this paper we present a full set of in situ measurements of main PP and microbial heterotrophy characteristics required for better understanding and further validation of the satellite and modeling approaches. In September–October 2011, during the 57th cruise of RV Akademik M.A. Lavrent'ev , PP, bacterioplankton abundance (BA) and bacterioplankton production (BP), as well the rates of dark CO 2 assimilation (DCA) were determined in the Chukchi, East Siberian, and Laptev seas and in the Gulf of Anadyr of the Bering Sea (a total of 26 stations) by in situ measurements using radiolabeled bicarbonate. All three important production indicators exhibited significant variance within the studied water areas of the Arctic (РР from 0.98 to 54.7 μg C L−1 day−1), (ВР from 1.1 to 17.1 μg C L−1 day−1), and (DCA from 0.23 to 8.7 μg C L−1 day−1). The state of phyto- and bacterioplankton was determined by analysis of the BP/PP and DCA/PP ratios. Active photosynthesis with efficient incorporation of inorganic carbon into the biomass was observed in the Chukchi Sea coastal eastern waters and in the Gulf of Anadyr. On the contrary, the phytoplankton primary production was extremely low in oligotrophic basins of the East Siberian and Laptev seas, while the activity of heterotrophic bacterioplankton consuming organic matter of phytoplankton origin was relatively high. The data of direct measurements can be used for further adjustment of the indirect assessments of production obtained by satellite observations. Glossary East Siberian Arctic seas (ESAS), net primary production (PP), bacterioplankton abundance (BA), bacterial biomass (BB), bacterial production (BP), Arctic Ocean PP (AO-PP), organic matter (OM), dissolved organic matter (DOM), colored dissolved organic matter (CDOM), light CO 2 assimilation (LCA), dark (heterotrophic + chemotrophic) CO 2 assimilation (DCA), production indicators of the surface water layer (PP surf , DCA surf , BP surf), estimated production indicators for the entire depth of the sea (PP int , DCA int , BP int ; mg C m−2 day−1). [Display omitted] • The Arctic seas are characterized by high heterogeneity of phyto- and bacterioplankton activity. • In the Chukchi and Bering seas, autotrophic production is higher than heterotrophic. • In the East Siberian and Laptev Seas, heterotrophic production is similar and higher than autotrophic. • The balance of autotrophic and heterotrophic plankton activity determines the direction of CO 2 flow. [ABSTRACT FROM AUTHOR]

Climate modelling and palaeotemperature reconstructions derived from several proxies (TEX 86 , δ18O) suggest that the Late Cretaceous was one of the warmest intervals in Earth history. The greenhouse climate reached its acme near the Cenomanian-Turonian boundary (CTB) interval with sea surface temperatures over 35 °C in low and mid- palaeolatitudes, coinciding with the highest sea level stands of the Phanerozoic. Following this warming phase, a general cooling trend punctuated by short-term hot snaps characterized the rest of the Cretaceous. Palaeotemperature and palaeoenvironmental changes are well documented in deep-water carbonate deposits based on variations in geochemical proxies and distribution patterns of macro- and microfauna. However, such climatic and environmental fluctuations severely impacted carbonate platforms, sedimentary environments that are particularly sensitive to external perturbations. Palaeontological data show major changes within the main carbonate platform producers (rudists and benthic foraminifera) during the early Late Cretaceous. Both groups experienced major taxonomic turnovers at the CTB, followed by a further re-radiation in the middle/late Turonian. The lack of detailed palaeoclimatic reconstructions in shallow water carbonate succession hampers the possibility to investigate a possible causal relationship between temperature changes and faunal evolution. In this paper, we report integrated geochemical, sedimentological, and palaeontological data from the Adriatic Carbonate Platform (Friuli, north-east Italy). Benthic foraminifera biostratigraphy and isotope stratigraphy (δ13C and 87Sr/86Sr) were used to precisely constrain the stratigraphy of the late Cenomanian-middle Turonian interval. δ18O analysis on both well-preserved rudist shells and bulk rock samples enabled the construction of high-resolution palaeotemperature curves. The resulting temperature trends are comparable with those from the deep-water record across the late Cenomanian-Turonian interval. The warmest phase was in the Early Turonian with sea surface palaeotemperatures as high as 41–45 °C recorded in rudist shells. Data show temperature fluctuation from the late Cenomanian to the Early Turonian with a magnitude >7 °C. Benthic foraminifera and rudist evolution responded to these palaeotemperature fluctuations, and their decline in the late Cenomanian and full recovery in the Turonian suggest a strong link with temperature changes. • Reconstructed temperatures from carbonate platforms during the Cenomanian -Turonian interval are missing • High resolution paleotemperatures reconstruction and biota evolution (rudists and benthic foraminifera) from Friuli Carbonate Platform is presented • Paleotemperatures estimated using δ18O analyses on bulk rock and well preserved bivalve samples (rudists and Chondrodonta) • δ18O analyses in bivalve shells suggest warmest Temperatures °>40°C in the Early Turonian • Rudists and benthic foraminifera distribution/abundance strongly modulated by temperature changes [ABSTRACT FROM AUTHOR]

Open Cycle - Ocean Thermal Energy Conversion (OC-OTEC) is one of the most important renewable energy sources that generate electricity and fresh water from seawater utilizing the temperature gradient between the warm surface seawater and the cold deep seawater. This paper aims to develop non-linear data-driven model-based adaptive Feedback Control (FBC) schemes for the OC-OTEC process to track the output power and a dynamic Feed-Forward Control (FFC) scheme to reject the effects of temperature disturbance on power caused by climate variations in OC-OTEC. The experiments are conducted on a laboratory-scale OC-OTEC experimental setup at the National Institute of Ocean Technology, Chennai. Firstly, linear data-driven models are developed using system identification techniques. Based on the developed models, gain scheduling-based adaptive control schemes are developed: Proportional Integral (PI) control and Model Predictive Control (MPC). Secondly, the closed-loop performances of the developed FBC schemes are analysed under servo and regulatory operations. Furthermore, it is observed from the sensitivity analysis results that the temperature disturbance highly influences output over the manipulated variable. Hence, a dynamic FFC scheme is implemented to reject known disturbance of 1 °C variation in temperature gradient from 18 °C to 19 °C due to Sea Surface Temperature (SST) changes in temperature gradient. The results show that the proposed MPC-based FBC-FF scheme effectively enhances the tracking and disturbance rejection performance compared to the PI-based FBC-FF control scheme with a minimum Integral Square Error (ISE) of 3.055 and Control Effort (CE) of 7.505. This experimental data-based, data-driven modelling and adaptive control research provides a new direction for automating OC-OTEC. Further, these studies will help to develop a rugged and automated upscaling OC-OTEC plant control system with proposed feasible control schemes. [ABSTRACT FROM AUTHOR]

Comparative estimation of long-term trends in the variability of the largest Atlantic upwellings (Canary and Benguela) has been carried out in this paper. Satellite data on the sea surface temperature and three surface wind datasets prepared by different scientific groups have been used. The difference in the calculated absolute vertical velocities due to alongshore wind drift and horizontal wind-field nonuniformity reach tens of percent. All time series demonstrate the common tendency for the intensification of the upwellings from the 1980s to the early 1990s. This confirms published materials concerning the intensification of Canary and Benguela upwellings under global warming. However, since the late 1990s, the intensification of the upwellings has nearly ceased. This proves the highly important role of the natural interdecadal climate variations in the variability of intensity of generation of upwellings during the period of regular satellite measurements. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) is an important geophysical parameter that is essential for studying global climate change. Although sea surface temperature can currently be obtained through a variety of sensors (MODIS, AVHRR, AMSR-E, AMSR2, WindSat, in situ sensors), the temperature values obtained by different sensors come from different ocean depths and different observation times, so different temperature products lack consistency. In addition, different thermal infrared temperature products have many invalid values due to the influence of clouds, and passive microwave temperature products have very low resolutions. These factors greatly limit the applications of ocean temperature products in practice. To overcome these shortcomings, this paper first took MODIS SST products as a reference benchmark and constructed a temperature depth and observation time correction model to correct the influences of the different sampling depths and observation times obtained by different sensors. Then, we built a reconstructed spatial model to overcome the effects of clouds, rainfall, and land interference that makes full use of the complementarities and advantages of SST data from different sensors. We applied these two models to generate a unique global 0.041 ∘ gridded monthly SST product covering the years 2002–2019. In this dataset, approximately 25 % of the invalid pixels in the original MODIS monthly images were effectively removed, and the accuracies of these reconstructed pixels were improved by more than 0.65 ∘ C compared to the accuracies of the original pixels. The accuracy assessments indicate that the reconstructed dataset exhibits significant improvements and can be used for mesoscale ocean phenomenon analyses. The product will be of great use in research related to global change, disaster prevention, and mitigation and is available at 10.5281/zenodo.4419804 (Cao et al., 2021a). [ABSTRACT FROM AUTHOR]

Global warming is the average temperature of the earth's surface which has increased over the past century by about 0.6 °C. This rising temperature may vary precipitation patterns, more frequent droughts, rise in sea level and intense storms and can be termed as climate change. To understand uneven precipitation pattern for monsoon dominated region like India, there is a need to study cloud processes at high resolution with the help of cloud microphysical properties. Ocean is the major and primary source of cloud whereas local water bodies and re-evaporated water over land could be secondary source. Paper focuses over ocean (Arabian Sea) as well as over land (central India) to know the effect of global warming on cloud microphysical properties such as cloud effective radius and cloud liquid water content. Warming signal in terms of rise in sea surface temperature (0.1 °C/decade) as well as rise in surface air temperature (0.05 °C/decade) are observed over Arabian Sea and central India respectively. Satellite data show an increasing (0.5 µm/decade) trend in cloud effective radius over Arabian Sea, whereas it decreases (− 0.1 µm/decade) over central India. Increasing trend in temperature and cloud properties is may be due to warming signal. Aerosol concentration over ocean and land further helped to understand cloud processes with cloud microphysical properties. Paper will focus on the effect of warming signal in cloud properties over Arabian Sea and central India. This type of high resolution study may help to understand cloud processes which in turn may help to understand precipitation patterns. [ABSTRACT FROM AUTHOR]

The topical issue includes 22 papers on different aspects of meteorology and climatology of the Mediterranean and Black Seas. The papers are grouped into three categories, based on scale analysis of processes, and whether the study is dominantly related to the atmospheric or oceanic phenomenon. The category “Storms, Extremes and Mesoscale Processes” encompasses seven papers, ranging from observation and modelling data analysis of extreme atmospheric (severe winds, hailstorms, waterspout, cyclones) and oceanic (meteotsunamis, surface waves) events, occurring locally, but being connected to wider patterns and processes. The six papers in category “Atmospheric Climate, Variability and Climate Change” contain analyses of long-term observations and climate projection outputs, but also assess atmosphere-ocean-land interactions and cycles, that are important in a climate perspective. The category “Ocean Climate and Variability” includes nine papers, which map ocean processes (sea level variability, circulation, sea surface temperatures, vertical thermal structure, water masses and dense water formation) on a climate timescale, both, in the Mediterranean and Black Sea sub-basins, or taking them as a whole. [ABSTRACT FROM AUTHOR]

There is a large discrepancy between studies on how the Indian Ocean Dipole (IOD) is defined. Indeed, the definition of historical events varies substantially, resulting in conflicting classifications, hampering hydroclimatic impact assessment of this phenomenon. Therefore, this paper aims to compare the various methods that have previously been adopted to define IOD events and demonstrate an alternative method that specifically captures different "flavours" of IOD. It is shown that the choice of sea surface temperature (SST) data set and climatological baseline has significant impact on the resulting classification of IOD events. Furthermore, not all events display the traditional dipole signature pattern of warming/cooling occurring at opposite poles. Rather, some events could be considered "pseudo dipoles," whereby the SST anomalies in the two poles are not of opposite sign. Importantly, the different types of IOD (i.e., "pseudo and true") are associated with varying impacts on rainfall for surrounding regions. To overcome these issues, this study treats Indian Ocean SST anomalies as a continuum of a finite maximum number of statistically distinguishable patterns using a neural network‐based cluster analysis. Ten individual SST patterns were identified with distinct rainfall teleconnections. In particular, four strong IOD patterns (two positive and two negative) were identified, alongside three pseudo dipoles representing anomalously warm conditions across the entire Indian Ocean Basin, with a SST gradient towards the east (i.e., a pseudo negative dipole) or west (i.e., a pseudo positive dipole). The occurrence of each of the 10 self‐organizing mapping (SOM) patterns is shown to be variable over the past 130 years, with some types more common during certain phases of the El Niño/Southern Oscillation or during the first (or second) half of the 20th century. The implications of these findings are particularly significant for attribution studies, development of proxy climate reconstructions, climate model evaluation and future climate change assessment. The Indian Ocean Dipole (IOD) is known to impact hydroclimate across many Indian Ocean rim counties. However, there is a growing body of research that confirms the IOD is a complex phenomenon with multiple variants, which cannot be captured by a simple index such as the dipole mode index (DMI). This paper uses a novel technique (SOM) to identify 10 individual flavours of the IOD with distinct rainfall teleconnections. Figure shows 10 different Indian Ocean SST "types" derived using SOM. Note that numbers in brackets show the number of occurrences of each type. [ABSTRACT FROM AUTHOR]

The paper examines the relationships between ENSO events and tropical cyclones (TCs) in the western North Pacific (WNP) during the ENSO decaying phase of March to July [MAMJJ(1)]. It is shown that WNP TC response is asymmetric to ENSO warm and cold events during MAMJJ(1), associated with the asymmetric patterns of oceanic and atmospheric environmental variables. Eastern Pacific warm events correspond to a westward shift in TC genesis location and a significant decrease of the TC number in the southwest subregion of the WNP, which is consistent with unfavorable atmospheric and oceanic conditions for TC activity during MAMJJ(1). Correspondingly, there is a much less WNP TC number, a shorter TC duration, and a decreased tendency in all three primary TC tracks. During MAMJJ(1) of eastern Pacific cold events, an increased TC activity in the northeast subregion results in an enhanced TC genesis number in the WNP. Central Pacific ENSO events have little effect on WNP TC activity during MAMJJ(1), except that central Pacific warm events are unfavorable for TCs to form in the northwest subregion associated with atmospheric and oceanic conditions. The paper also compares and discusses the TC response to ENSO events during the ENSO developing year of March-July. [ABSTRACT FROM AUTHOR]

Caribbean small island developing states (SIDS) are highly vulnerable to the impacts of climate change. Food security is a key issue in the region, and is related to vulnerability in the natural and human system. This short research paper, which reports on a systematic search of the academic literature and is part of a larger research project on climate change adaptation in Caribbean coastal communities, investigates two central questions: (1) what challenges to food security are Caribbean SIDS facing due to climate change? and (2) what strategies, if any, are being used to adapt to these challenges? We review peer-reviewed articles published after the release of Working Group II's contribution to the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change in 2014, which included a chapter on vulnerability and impacts in small islands (Chapter 29). We find that post AR5 articles confirm that climate change will have a significant effect on agriculture and fisheries in the Caribbean, mainly through changing patterns of weather, air and sea surface temperatures, and water availability. These studies highlight the importance of considering the social dimensions of food security in the region when identifying and implementing adaptation strategies, particularly in the context of achieving the Sustainable Development Goals. These social dimensions include the Caribbean's historical and social context as well as its demographics, which feature varying population densities and poverty rates. They serve to increase vulnerability but are imperative considerations for understanding and minimizing the threat climate change poses to food security in the region. [ABSTRACT FROM AUTHOR]

Understanding how marine taxa will respond to near-future climate changes is one of the main challenges for management of coastal ecosystem services. Ecological studies that investigate relationships between the environment and shell properties of commercially important marine species are commonly restricted to latitudinal gradients or small-scale laboratory experiments. This paper aimed to explore the variations in shell features and growth of the edible bivalve Chamelea gallina from the Holocene sedimentary succession to present-day thanatocoenosis of the Po Plain-Adriatic Sea system (Italy). Comparing the Holocene sub-fossil record to modern thanatocoenoses allowed obtaining an insight of shell variations dynamics on a millennial temporal scale. Five shoreface-related assemblages rich in C. gallina were considered: two from the Middle Holocene, when regional sea surface temperatures were higher than today, representing a possible analogue for the near-future global warming, one from the Late Holocene and two from the present-day. We investigated shell biometry and skeletal properties in relation to the valve length of C. gallina. Juveniles were found to be more porous than adults in all horizons. This suggested that C. gallina promoted an accelerated shell accretion with a higher porosity and lower density at the expense of mechanically fragile shells. A positive correlation between sea surface temperature and both micro-density and bulk density were found, with modern specimens being less dense, likely due to lower aragonite saturation state at lower temperature, which could ultimately increase the energetic costs of shell formation. Since no variation was observed in shell CaCO3 polymorphism (100% aragonite) or in compositional parameters among the analyzed horizons, the observed dynamics in skeletal parameters are likely not driven by a diagenetic recrystallization of the shell mineral phase. This study contributes to understand the response of C. gallina to climate-driven environmental shifts and offers insights for assessing anthropogenic impacts on this economic relevant species. [ABSTRACT FROM AUTHOR]

The massive North Atlantic iceberg discharges of the last glacial period, the so-called Heinrich events (HE), resulted in atmospheric and oceanic responses of the Mediterranean region that remain poorly documented and understood. This paper focuses on the climatic phases termed Heinrich stadials (HS) 4 and 5 generated by the HE 4 and 5 that occurred during a period of similar intermediate global ice volume and greenhouse gas concentrations but with different iceberg discharges and orbital boundary conditions. Our comparison of sea surface temperature and salinity changes with deep water conditions in the Gulf of Lions (planktonic and benthic foraminifera δ18O and δ13C records) and regional pollen-based temperature and precipitation reconstructions in NW Mediterranean for these Heinrich stadials reveal a paradoxical situation. A lower North American iceberg discharge during HS 5 compared to HS 4 is associated with colder and drier conditions in the NW Mediterranean borderlands. During the moderate iceberg discharge of HS 5 a relatively high salinity in the Gulf of Lions lead to stronger Western Mediterranean Deep Water formation and mixing of the surface with the deeper layers. By contrast during HS 4, we suggest that the massive North Atlantic iceberg break-up decreased the salinity of the Gulf of Lions and reduced the wind stress in the Mediterranean, leading to the stratification of the Mediterranean water column and inducing limited upward mixing of cold water, resulting in regional atmospheric warming and wetting compared to HS 5. This work highlights the potential crucial role of local processes in modulating the regional response to a global climate change related with ice-sheet instabilities. [ABSTRACT FROM AUTHOR]

Trend identification analyses in any hydrometeorological data are necessary and critical for predictions and planning in many disciplines such as atmospheric, environmental, and oceanographic sciences; water engineering; global warming; and climate change applications. In the literature, many researches have employed trend analyses by Mann-Kendall (MK) and innovative trend analysis (ITA) methods. Especially in recent years, the ITA method is preferred in trend identification methodological applications, because it can present trend graphs with visual inspection, verbal inferences, and objective quantitative calculations. In this paper, the trends of sea surface temperature (SST) data are identified by the MK and ITA methods on double logarithmic graphs, which provide fractal geometrical appearances with power law features. The SST data trends are evaluated at 22 coastal area stations of Turkey with monthly records from 1969 to 2014. According to the MK trend test, only 6 of the 22 stations had a significant upward trend at 5% significant level and 4 of these stations are in the Mediterranean Sea coastal area. At 10% significance level increasing trend numbers become 14 stations. According to the MK test results, the data records have been grouped into two parts as warming and cooling periods considering the physical conditions of the SST data. On the other hand, the results of ITA application provide average behavioral form according to the mathematical power law equations. [ABSTRACT FROM AUTHOR]

This paper focuses on sea surface temperature (SST) trends due to the importance of temperature difference in climate change impact research. These trends are not only essential for climate, but they are also important for marine ecosystem. Immigration of fish population due to the temperature changes is expected to cause unexpected economical results. For this purpose, both classical Mann–Kendall, (MK) (Mann in Econom: J Econom Soc 13:245–259, 1945; Kendall in Rank Correlation Methods, Charless Griffin, London, 1975) and innovative trend analysis (ITA) (Şen in J Hydrol Eng 17(9):1042–1046, 2012) methodologies are applied for the SST data records. Monthly SST data are considered along the Black, Marmara, Aegean, and Mediterranean coastal areas in Turkey. SST data are categorized into five clusters considering fish life as "hot," "warm-hot," "warm," "cold," and "very cold." According to ITA, SST in all coastal areas tends to increase except for winter season during "very cold" (0–10 °C) temperatures. The temperature changes in both winter and summer seasons are expected to change the marine life, fish population, tourism habit, precipitation regime, and drought feature. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) observations in the North Atlantic since 1870 reveal a region of enhanced warming off the northeastern coast of North America, and a region of cooling to the south of Greenland. It has been hypothesized that these adjacent SST trends are a result of long‐term changes in the buoyancy‐driven ocean circulation—a slowdown of the Atlantic Meridional Overturning Circulation. The impacts of these historical SST trends on the atmosphere are estimated using idealized atmospheric general circulation model experiments in which the global atmosphere is exposed to modern climatological forcing minus the aforementioned regional SST trends. The local response includes a negative North Atlantic Oscillation tendency and southward shift of the wind forcing for the subtropical gyre. Due to planetary wave propagation, the regional SST trends also induce a northward shift of the intertropical convergence zone over the Indian Ocean. Implications for climate feedbacks and projections are discussed. Plain Language Summary: The ocean surface is warming over most of the planet, with a couple of notable exceptions. One is over the North Atlantic Ocean, just south of Greenland, where the temperature of the ocean surface has actually been cooling by about 1°C since 1870. Nearby, extending off the northeastern coastline of North America is a region where the ocean surface has been warming much faster than the global ocean on average—by about 1.5°C since 1870. This side‐by‐side pair of accelerated warming and cooling trends is likely due to a slowdown of the ocean's overturning circulation, which carries large amounts of heat energy from the tropics toward the poles. This paper reveals the effects of those unusual ocean temperature trends in the North Atlantic on the atmospheric circulation using a computer model of the global atmosphere. The model simulations indicate that these ocean temperature trends are causing shifts in the jet stream, changing the way the winds propel the upper ocean currents, and even have impacts quite far away by moving the tropical rain belt northward in the Indian Ocean. Key Points: The impact of historical sea surface temperature trends in the North Atlantic since 1870 is simulated with a global atmospheric modelAdjacent warming and cooling trends in the North Atlantic Ocean induce a negative NAO‐like response and southward‐shifted gyre forcingPropagation of planetary waves away from the North Atlantic induces a northward‐shifted intertropical convergence zone in the Indian Ocean [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) is an important geophysical parameter that is essential for studying global climate change. Although sea surface temperature can currently be obtained through a variety of sensors (MODIS, AVHRR, AMSR-E, AMSR2, Windsat, in situ sensors), the temperature values obtained by different sensors come from different ocean depths and different observation times, so different temperature products lack consistency. In addition, different thermal infrared temperature products have many invalid values due to the influence of clouds, and passive microwave temperature products have very low resolutions. These factors greatly limit the applications of ocean temperature products in practice. To overcome these shortcomings, this paper first took MODIS SST products as a reference benchmark and constructed a temperature depth and observation time correction model to correct the influences of the different sampling depths and observation times obtained by different sensors. Then, we built a reconstructed spatial model to overcome the effects of clouds, rainfall and land interference that makes full use of the complementarities and advantages of SST data from different sensors. We applied these two models to generate a unique global 0.041° gridded monthly SST product covering the years 2002–2019. In this dataset, approximately 25% of the invalid pixels in the original MODIS monthly images were effectively removed, and the accuracies of these reconstructed pixels were improved by more than 0.65°C compared to the accuracies of the original pixels. The accuracy assessments indicate that the reconstructed dataset exhibits significant improvements and can be used for mesoscale ocean phenomenon analyses. The product will be of great use in research related to global change, disaster prevention and mitigation and is available at http://doi.org/10.5281/zenodo.4419804 (Cao et al., 2021). [ABSTRACT FROM AUTHOR]

Integrated atmospheric water vapor transport (IVT) is a determinant of global precipitation. In this paper, using the CERA-20C climate reanalysis dataset, we explore three questions in Northern Hemisphere precipitation for four seasons: 1) What is the covariability between the leading spatiotemporal modes of seasonal sea surface temperature (SST), the seasonal IVT, and the seasonal precipitation for the Northern Hemisphere? 2) How well can the leading spatial modes of seasonal precipitation be reconstructed from the leading modes of IVT and SST for the same season? 3) How well can the leading modes of precipitation for the next season be predicted from the leading modes of the current season's SST and IVT? Wavelet analyses identify covariation in the leading modes of seasonal precipitation and those of IVT and SST in the 2–8-yr band, with the highest amplitude in the March–May (MAM) season, and provide a firm physical explanation for the potential predictability. We find that a subset of the 10 leading principal components of the seasonal IVT and SST fields has significant trends in connections with seasonal precipitation modes, and provides an accurate statistical concurrent reconstruction and one-season-ahead forecast of the leading seasonal precipitation modes, thus providing a pathway to improving the understanding and prediction of precipitation extremes in the context of climate change attribution, seasonal and longer prediction, and climate change scenarios. The same-season reconstruction model can explain 76% of the variance, and the next-season forecast model can explain 58% variance of hemispheric precipitation on average. [ABSTRACT FROM AUTHOR]

The assumption of a stationary global signal linked to El Niño–Southern Oscillation (ENSO) events is often used in paleo-ENSO proxy data interpretation. This paper attempts to investigate whether the assumption is valid during the last glacial maximum (LGM) over the region 60°S–90°N, 60°E−60°W. Using four models within phase 3 of the Paleoclimate Modeling Intercomparison Project framework that well reproduce ENSO-induced variabilities, differences from the preindustrial period to LGM in the ENSO-related sea surface temperature pattern and its impacts are investigated. Compared to the preindustrial period, the ENSO impacts are revealed to weaken and shift eastward during the LGM. According to multimodel medians, ENSO impacts on precipitation and near-surface air temperature are attenuated over most regions of concern, with percentage changes in both parameters averaging −21% for the whole region; the ENSO-induced Pacific–North America (PNA) teleconnection pattern is weakened, manifested by the 41% diminished center over the North Pacific and the almost vanished activity centers over the continent. Spatially, there is a zonal contraction of 13° for the sea surface warming of ENSO, as well as eastward migration over 10° for the ENSO-induced positive precipitation anomaly center over the tropical Pacific and the PNA teleconnection pattern outside the tropics. The aforementioned changes are linked to the altered climatic background during the LGM, which features a 16° eastward shift for the Pacific Walker circulation rising branch and a weakened waveguide in the midlatitudes. The results suggest that the hypothesis of stationary ENSO impacts should be applied cautiously to the past. [ABSTRACT FROM AUTHOR]

This paper focuses on a paleoecological study conducted on planktonic foraminifera from upper Oligocene-lower Miocene deposits of the J-Anomaly Ridge (North Atlantic Ocean). Paleoclimatic studies are crucial to better comprehend how climatic changes occurred in the past and how they might influence global climate in the next few decades. Oceanic currents are the predominant vehicle for heat transport across the globe and therefore organisms living within the water mass can supply much information on paleoceanographic settings. In total, 53 samples from IODP Hole U1406A were selected in the core interval 96-24 CCSF-M to perform statistical analyses (R-mode cluster analysis, principal component analysis) to describe ecogroup distribution and a paleoclimatic curve based on shallow dwelling taxa. The species have been subdivided into three ecogroups referring to recent studies on planktonic foraminiferal paleoecology. The statistical analyses allowed a preliminary screening of the distribution of the foraminiferal assemblages in the biozonal interval of O7-M3. The ecogroup distribution curves revealed the behavior of each group along the section, highlighting the interconnection among the various habitats. Finally, the abundance of the surface taxa was used to trace a paleoclimatic curve (SDPC) describing the superficial water variations. Those results were compared with the Alkenone Sea Surface Temperature (SST) record from IODP Site U1404 and the d18O North Atlantic stack from the literature. This comparison showed a good match among the foraminiferal and geochemical data, allowing the correlation of SDPC and SST minima with well-known glacial events of the North Atlantic Ocean. This study supports the potential of census data of planktonic foraminifera in paleoclimatic studies when geochemical data are not available. [ABSTRACT FROM AUTHOR]

Heat waves (HWs) represent a major danger to society and natural environment. The increasing occurrence of high magnitude and impact HWs has raised concerns worldwide and has attracted an increasing interest on this issue among climatologists over the past decade. In this review the research from 2007-2018 period on HWs definitions, driving mechanisms, present changes, future changes, and impact on human mortality is summarized. By reviewing the recent literature, it was found that whilst the atmospheric dynamic is considered to be the primary driver in HW occurrence, the sea surface temperature (SST) and land surface conditions are also essential driving components. The vastness of HW-definitions raises difficulties in selecting the appropriate methodology to identify heat episodes and to compare results from studies which used different definitions. However, by analyzing a sample of 109 papers, a preference for percentile-based definitions was observed. Therefore, 71.6% of the analyzed articles used only percentilebased definitions to identify HWs. Despite the wide variety of definitions, the analysis of changes in HWs converged to similar results. Thus, the existing recent literature provided extensive evidence of significant increase in HWs characteristics across large regions of the planet. Available scientific literature indicated that HWs have been responsible for a considerable increase in mortality in many regions of the world. In the future HWs are predicted to increase in their main characteristics leading to a greater impact on human mortality. Nevertheless, the implementation of rigorous adaptation measures can mitigate the negative impact on mortality. In conclusion, it was noted that a substantial progress has been done in the HW research, but there are still important gaps in this issue which need to be addressed. [ABSTRACT FROM AUTHOR]

Joseph, D.; Liya, V.B.; Rojith, G.; Zacharia, P.U., and Grinson, G., 2019. Time series analysis of CMIP5 model and observed sea surface temperature anomaly along Indian coastal zones. In: Jithendran, K.P.; Saraswathy, R.; Balasubramanian, C.P.; Kumaraguru Vasagam, K.P.; Jayasankar, V.; Raghavan, R.; Alavandi, S.V., and Vijayan, K.K. (eds.), BRAQCON 2019: World Brackishwater Aquaculture Conference. Journal of Coastal Research, Special Issue No. 86, pp. 239–247. Coconut Creek (Florida), ISSN 0749-0208. Analysis of the time series Sea Surface Temperature (SST) variations is a key element in understanding the climate change impacts on the phenology, trophodynamics, distribution, and catch of commercial marine fish species. As SST projections are mostly model dependent, the discrepancy in the model and observed values needs to be elucidated so as to derive accurate interpretations and conclusions. In this paper, the decadal and seasonal variations of SST anomaly over the four coastal zones of India were analysed. The selected period of the study is from 1968 to 2017 and the data obtained from the International Comprehensive Ocean Atmosphere Data Sets (ICOADS) and Max Planck Institute Earth System Model (MPI-ESM) was used. The Coupled Model Intercomparison Project 5 (CMIP5) model data were used for comparison with the observed value. The linear trend of observed and modelled values was inferred using the least square method for four seasons. The seasonal variation of SST anomaly of observed data in four coastal zones of India reveals that Northeast zone exhibits the least trend of warming in all seasons, whereas Northwest zone shows the highest trend of warming. SST anomaly of the first decade in all zones exhibited negative values in all seasons, while last decade shows positive value, indicating warming trend. In other decades, no uniform SST trend for all seasons was observed. However, the Northeast zone is exceptional with negative anomaly during all decades. The warming trend was observed in all coasts for both model and observed values. The model and observed SST anomaly follows an almost similar trend, but with noticeable differences in values among both. Owing to the differences in the model and observed values, it could be emphasised that error corrections needs to be applied in futuristic SST projections and related studies of Indian fisheries. [ABSTRACT FROM AUTHOR]

Introduction: The life history of the California sea lion (Zalophus californianus) in the Gulf of California is marked by a series of important events influencing and modifying its population growth, distribution, and evolution. Despite the fact that this population has been studied since the 1950s, research has been rather punctual and fragmentary. Before 2010, there are only a few surveys conducted simultaneously in all rookeries, thus there is no reliable information on key aspects of life cycle, population trend and potential threats. In the present work we conducted a review of California sea lion life history and environmental changes in the Gulf of California thorough a collation of survey data encompassing the last 37 years. Objective: Our aim was focused on identifying short- and long-term processes potentially acting on the population, and hopefully improve knowledge about the population trend and status using different points of view. Methods: We collected and analyzed population survey data from different sources since the 1970s to 2018: published papers, master's and doctoral thesis, in addition to technical reports. The survey data are organized in sections corresponding with crucial population life history events. Results: Considering a long-time period the population size appears to be stable with zero growth. Cyclic interannual fluctuation seem to denote a certain dependence with climatic factors, not directly with El Niño, but with sea surface temperature anomalies that determine prey availability. However, many doubts persist about the incidence of different local environmental factors on gender and age, particularly related with juvenile recruitment and female survival rate. Conclusions: In conclusion, more information is required based on seasonal surveys, life cycle, regional environmental variation. Statistical errors need to be assessed and monitoring methods should be standardized and must be considered to ascertain short- and long-term population and colony spatial-temporal patterns. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to elucidate a potential use of the large samples of seasonal means that hindcasts provide for investigating different aspects of climate variability. This use of hindcasts complements their traditional uses in bias correction, real-time forecast calibration, and prediction skill assessment. For seasonal hindcast data from NCEP CFSv2 we show that a sample size 5208 for each target season is achievable. To demonstrate the utility of the proposed concept, we use this large sample dataset to illustrate how it could be used in documenting spatial variability in various moments of seasonal mean precipitation PDF over the US, and further, quantify nuances in the variations in precipitation PDF at different geographical locations with the amplitude of ENSO SSTs. It is our hope that analysis presented in this paper will accelerate utilization of seasonal hindcast datasets in furthering our understanding of different aspects of climate variability. With the advantage of the large sample size, we demonstrated that the precipitation PDF at the each grid of the CONUS can be represented by gamma distribution for a more concise and effective way to summarize precipitation variability. The availability of the large sample dataset also allowed us to analyze the statistical characteristic of the precipitation responses to the different amplitudes of ENSO SSTs. The results show that for strong warm events, enhancement in precipitation has larger amplitude than decrease in precipitation for cold events in the regions of Southern California and southeastern US. The variation of the precipitation signal over the other sub-regions including the southwestern US, mid-northwest, and mid-east shows more linear relationship with the ENSO SSTs. In response to anomalous ENSO SSTs, although the PDF of December-January-February seasonal mean precipitation anomaly is shifted from its climatological PDF, there is still a large overlap between precipitation PDFs for ENSO and its climatological counterpart. This uncertainty in seasonal mean outcomes of precipitation, therefore, limits the seasonal prediction skill. [ABSTRACT FROM AUTHOR]

The Earth's climate is largely determined by its energy budget. Since the 1960s, satellite remote sensing has been used in estimating these energy budget components at both the top of the atmosphere (TOA) and the surface. Besides the broadband sensors that have been traditionally used for monitoring Earth's Energy Budget (EEB), data from a variety of narrowband sensors aboard both polar-orbiting and geostationary satellites have also been extensively employed to estimate the EEB components. This paper provides a comprehensive review of the satellite missions, state-of-the art estimation algorithms and the satellite products, and also synthesizes current understanding of the EEB and spatio-temporal variations. The TOA components include total solar irradiance, reflected shortwave radiation/planetary albedo, outgoing longwave radiation, and energy imbalance. The surface components include incident solar radiation, shortwave albedo, shortwave net radiation, longwave downward and upwelling radiation, land and sea surface temperature, surface emissivity, all-wave net radiation, and sensible and latent heat fluxes. Some challenges, and outlook such as virtual constellation of different satellite sensors, temporal homogeneity tests of long time-series products, algorithms ensemble, and products intercomparison are also discussed. [ABSTRACT FROM AUTHOR]

Climate change is the result of complex interactions between a wide array of climatic variables. Over a long period of time, climatic patterns can shift, possibly multiple times. Abrupt shifts that occur over a relatively short period of time are known as change points. During these intervals, different climatic variables may undergo dramatic shifts posing serious consequences for many biological and physical systems. In this paper, we discuss a Bayesian algorithm for detecting the location of change points in time series data. In particular, we utilize our method to analyse five different global surface temperature anomaly data sets, as well as temperature records associated with land, ocean, and different zonal bands in an attempt to identify common features of these data sets. Change points in the five global records were detected between 1902–1917, 1936–1945, and 1963–1976, but do these change points also manifest themselves across other parts of the globe? Our analysis indicates that the timing of change points is consistent from one record to the next, but not all change points appear in all records. In particular, there were more change points in the ocean than on land, and also more change points in southern latitudes than in northern latitudes. [ABSTRACT FROM AUTHOR]

Ninety-five percent of climate models contributing to phase 5 of the Coupled Model Intercomparison Project (CMIP5) project early summer [October–December (OND)] rainfall declines over subtropical southern Africa by the end of the century, under all emissions forcing pathways. The intermodel consensus underlies the Intergovernmental Panel on Climate Change (IPCC) assessment that rainfall declines are "likely" and implies that significant climate change adaptation is needed. However, model consensus is not necessarily a good indicator of confidence, especially given that there is an order of magnitude difference in the scale of rainfall decline among models in OND (from <10 mm season−1 to ~100 mm season−1), and that the CMIP5 ensemble systematically overestimates present-day OND precipitation over subtropical southern Africa (in some models by a factor of 2). In this paper we investigate the uncertainty in the OND drying signal by evaluating the climate mechanisms that underlie the diversity in model rainfall projections. Models projecting the highest-magnitude drying simulate the largest increases in tropospheric stability over subtropical southern Africa associated with anomalous upper-level subsidence, reduced evaporation, and amplified surface temperature change. Intermodel differences in rainfall projections are in turn related to the large-scale adjustment of the tropical atmosphere to emissions forcing: models with the strongest relative warming of the northern tropical sea surface temperatures compared to the tropical mean warming simulate the largest rainfall declines. The models with extreme rainfall declines also tend to simulate large present-day biases in rainfall and in atmospheric stability, leading the authors to suggest that projections of high-magnitude drying require further critical attention. [ABSTRACT FROM AUTHOR]

Decadal climate predictability has received considerable scientific interest in recent years, yet the limits and mechanisms for decadal predictability are currently not well known. It is widely accepted that noise due to internal atmospheric dynamics at the air‐sea interface influences predictability. The purpose of this paper is to use the interactive ensemble (IE) coupling strategy to quantify how internal atmospheric noise at the air‐sea interface impacts decadal predictability. The IE technique can significantly reduce internal atmospheric noise and has proven useful in assessing seasonal‐to‐interannual variability and predictability. Here we focus on decadal timescales and apply the nonlinear local Lyapunov exponent method to the Community Climate System Model comparing control simulations with IE simulations. This is the first time the nonlinear local Lyapunov exponent has been applied to the state‐of‐the‐art coupled models. The global patterns of decadal predictability are discussed from the perspective of internal atmospheric noise and ocean dynamics. Key Points: For the first time, the nonlinear local Lyapunov exponent method has been applied to the state‐of‐the‐art coupled climate modelsDepending on region reducing internal atmospheric noise reduces decadal variability but either increases or decreases decadal predictabilityDecadal‐scale subsurface predictability is examined for the North Atlantic region [ABSTRACT FROM AUTHOR]

The paper tests if the two La Niña (LN) types can be distinguished from each other using their climate impacts on northeastern Brazil (NEB). To this end, all LN events during the 1901–2010 period followed by a wet or dry rainy season (from February to April) in NEB are classified into two categories: WET‐LN and DRY‐LN. The global and regional anomalous atmospheric circulation patterns and the rainfall anomaly patterns in South America associated with the two cases are analysed. The WET‐LN and DRY‐LN events present, respectively, the eastern Pacific LN and central Pacific LN sea surface temperature (SST) anomaly features in the tropical Pacific. On the other hand, the WET‐LN features an interhemispheric SST dipole pattern in the tropical Atlantic, and the DRY‐LN, colder‐than‐normal surface waters in the tropical South Atlantic (TSA) and equatorial Atlantic during MAM(+1). The two analysed cases show regional differential circulation patterns in all seasons. The anomalous wetness over northern and northwestern South America occurs for the WET‐LN type during JJA(0)–DJF(+1) and for the DRY‐LN type, during DJF(+1)–MAM(+1). The anomalous dryness over SESA is more evident for the WET‐LN during JJA(0) and MAM(+1), and for the DRY‐LN, during SON(0). Anomalous dryness occurs in central and eastern South America noted during JJA(0) and DJF(+1) for both cases analysed. The precipitation anomalies in northern South America during DJF(+1) are stronger and more extensive for the DRY‐LN than for the WET‐LN events due to the action of both the anomalous (double) Walker and Hadley cells for the DRY‐LN, in contrast with the exclusive action of an anomalous Walker cell for the WET‐LN case. Also, a double Walker cell drives the dry–wet dipole between northern South America and NEB during MAM(+1) for the DRY‐LN. Our results might be useful mainly for climate monitoring purposes. The two La Niña (LN) types were distinguished from each other using their climate impacts on northeastern Brazil (NEB) and classified in two categories WET‐LN (LN events followed by a wet rainy season in NEB) and DRY‐LN (LN events followed by a dry rainy season in NEB) that present, respectively, the eastern Pacific LN and central Pacific LN sea surface temperature (SST) anomaly features in the tropical Pacific. The illustration shows the LN‐related SST and precipitation anomaly patterns evolutions associated with the two LN types. [ABSTRACT FROM AUTHOR]

Model‐based sensitivity experiments are a widely used method for studying climate change attributions. In traditional climate sensitivity studies, "climate drift" occurs because of the accumulation of model errors during long‐term integrations, both in "actual" and "hypothetical" states. A more accurate piecewise‐integration method is used to reduce the model errors, dividing the continuous simulation into a series of sequential short‐term simulations. The model fields are updated at the end of each subinterval with analysis data for the "actual" state run, and with the sum of the analysis data and the difference between "hypothetical" and "actual" states for the "hypothetical" state run. This paper conducts sensitivity experiments with the continuous‐integration method and the piecewise‐integration method to evaluate the impacts of the central and eastern Pacific Ocean sea surface temperature anomalies (SSTAs) on the severe drought that occurred in southwestern China (SWC) in the winter of 2009/2010. The results show the following. (a) Model errors produced by the piecewise‐integration method for the actual state simulation are significantly less than those produced by the continuous‐integration method. (b) The intensity of the drought is significantly overestimated in continuous‐integration experiments. However, the drought can be accurately simulated in its spatial distribution and intensity via the piecewise‐integration method. Thus, climate sensitivity to changes in external forcing can be studied with greater credibility. (c) The warm central Pacific Ocean SSTAs may be the main cause of the drought over SWC. Adequate precipitation occurred over SWC when the centre of the SSTAs shifted to the east. (d) Warm SSTAs over the central Pacific Ocean influenced precipitation over SWC by weakening the water vapour transport branch from South China Sea to SWC. With a deficit of water vapour, the pronounced subsidence and warm temperatures were the main dynamic and thermodynamic factors that caused and maintained the drought. Model‐based sensitivity experiment is a method of studying climate change attributions. In traditional climate sensitivity studies, "climate drift" occurs both in "actual" and "hypothetical" states. Therefore, the scientific value of climate sensitivity experiments is questioned. In this study, piecewise‐integration method (shown in the figure) is used to significantly reduce model errors caused by inaccuracies of analysis fields, to improve the accuracies of climate sensitivity simulations and to evaluate the impacts of the Pacific Ocean SSTAs on a drought. [ABSTRACT FROM AUTHOR]

Future sea surface temperature and sea-ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcings for the downscaling of future climate experiments. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly method and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea-ice concentration (SIC) are presented. For SIC, we also propose a new analogue method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiments and some real-case applications using observations. We find that with respect to other previously existing methods, the analogue method is a substantial improvement for the bias correction of future SIC. Consistency between the constructed SST and SIC fields is an important constraint to consider, as is consistency between the prescribed sea-ice concentration and thickness; we show that the latter can be ensured by using a simple parameterisation of sea-ice thickness as a function of instantaneous and annual minimum SIC. [ABSTRACT FROM AUTHOR]

Based on our previous study (Yu et al., Clim Dyn 49:1139-1156, 2017), this paper further investigates the interdecadal change in the relationship between the Kuroshio Extension (KE; 27°-37°N, 140°-158°E) and the East Asian summer monsoon (EASM) in the late 1980s. The summer KE sea surface temperature anomalies (SSTAs) show a significant positive relationship with the EASM over the period 1968-1987 (P1), but a significant negative connection with the EASM between 1991 and 2010 (P2). This interdecadal change in the KE-EASM relationship can be interpreted by considering the difference in the relationships of summer KE SSTAs with the East Asian subtropical westerly jet (EASWJ) and western North Pacific subtropical high (WNPSH) during the two periods. During P1, summertime KE SST warming is significantly related to the strengthened EASWJ and WNPSH, but it has close relationships with the weakened and northward-moving EASWJ and WNPSH during P2. These anomalous EASWJ and WNPSH associated with the summertime KE SST warming in P1 (P2) then favors increased (reduced) rainfall over the Yangtze River Valley that corresponds to a strong (weak) EASM, thereby leading to the significant positive (negative) KE-EASM relationship during this period. This change in the relationships of summer KE SSTAs with the EASWJ and WNPSH may be attributed to the increased KE SST variability associated with an enhanced Pacific Decadal Oscillation (PDO) in summer during P2, which is most probably induced by the stronger North Pacific Oscillation (NPO)-like atmospheric forcing, especially its southern pole (SP), in the preceding spring during this period. The spring NPO-like SP forces the KE SSTAs and PDO more directly during the following summer and can thus have been a better precursor for the following EASM than the full NPO-like dipole after the late 1980s. [ABSTRACT FROM AUTHOR]

This paper compares extreme value statistics of daily maximum 10 m wind speed in winter simulated by the regional climate model COSMO‐CLM at a horizontal resolution of 15 km (C15) with the reanalyses ERA‐Interim and Arctic System reanalysis (ASR version 1 and 2) and with a satellite data set (CCMPv2). Our C15 simulation (1979/1980–2015/2016, November–April) is thereby the longest high‐resolution simulation available for the Arctic. The results show that the extreme wind speeds tend to increase over the ocean with increasing the horizontal model resolution. A horizontal resolution of ≤15 km is required to sufficiently capture all extreme wind characteristics, in particular for the tip jets and barrier winds over the Irminger Sea and in the Denmark Strait, and for the low‐level jets in the Nares Strait. Of almost equal importance are physical parameterizations of surface fluxes and of turbulence. Capturing extreme wind characteristics has a direct effect on climate relevant air–ice–ocean interactions, such as triggering open‐ocean deep convection, polynya dynamics, or on the sea ice and freshwater balance of the Arctic. State‐of‐the‐art global climate models and reanalyses (e.g., ERA‐Interim) underestimate the extreme near‐surface wind speeds in the Arctic and around Greenland. Regional climate models, for example, ASR/WRF or COSMO‐CLM, resolve the mesoscale wind systems that frequently produce extreme winds, which we estimated i.a. as 10‐year return levels (see the figure). Capturing extreme wind characteristics has a direct effect on climate relevant air–ice–ocean interactions, such as triggering open‐ocean deep convection, polynya dynamics, or on the sea ice and freshwater balance of the Arctic. [ABSTRACT FROM AUTHOR]