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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]

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 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]

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]

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]

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]

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]

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]

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]

As ice sheets grow or decay, the net flux of freshwater into the ocean changes and the bedrock adjusts due to isostatic adjustments, leading to variations in the bottom topography and the oceanic boundaries. This process was particularly intense during the last deglaciation due to the high rates of ice-sheet melting. It is, therefore, necessary to consider transient ocean bathymetry and coastlines when attempting to simulate the last deglaciation with Earth system models (ESMs). However, in most standard ESMs the land-sea mask is fixed throughout simulations because the generation of a new ocean model bathymetry implies several levels of manual corrections, a procedure that is hardly doable very often for long runs. This is one of the main technical problems towards simulating a complete glacial cycle with general circulation models. For the first time, we present a tool allowing for an automatic computation of bathymetry and land-sea mask changes in the Max Planck Institute Earth System Model (MPI-ESM). The algorithms developed in this paper can easily be adapted to any free-surface ocean model that uses the Arakawa-C grid in the horizontal and z -grid in the vertical including partial bottom cells. The strategy applied is described in detail and the algorithms are tested in a long-term simulation demonstrating the reliable behaviour. Our approach guarantees the conservation of mass and tracers at global and regional scales; that is, changes in a single grid point are only propagated regionally. The procedures presented here are an important contribution to the development of a fully coupled ice sheet–solid Earth–climate model system with time-varying topography and will allow for transient simulations of the last deglaciation considering interactive bathymetry and land-sea mask. [ABSTRACT FROM AUTHOR]

The T5 expendable bathythermographs reach the greatest depth within the current XBT family. Since the early 1970s, in several areas they have been providing a significant part of available temperature profiles below 1000 m and therefore represent an important resource for ocean climate study. In this paper we present new results from laboratory tests of Sippican T5 and T5/20 probes and analyses of more than 350 XBT–CTD matched pairs from our own field trials and the World Ocean Database (WOD), and we propose an improved fall rate equation (coefficients: A = 6.720 ± 0.025 m s−1, B = 0.001 60 ± 0.000 15 m s−2, Offset = 1.00 ± 0.65 m). Possible influences of probe physical characteristics and initial launch conditions on the probe motion have also been investigated with launching height and probe weight being identified as important factors. Analyses also confirm that fall speed and pure temperature error increase with water temperature, as previously reported for other XBT types. The uncertainties in depth and temperature measurements are then calculated. Finally, a new correction for a global T5 dataset is proposed, with an update of the currently available schemes. [ABSTRACT FROM AUTHOR]

Miura, H.; Ito, Y., and Suenaga, Y., 2018. Construction of Climate Change-Adapted Seaweed Beds on the Japanese Coast. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 391–395. Coconut Creek (Florida), ISSN 0749-0208. Japanese coastal seaweed beds are experiencing a long-term decline in area coverage in a phenomenon called isoyake, which has massively impacted the fisheries industry. Therefore, research has been performed on seaweed bed restoration. Consequent measures have been implemented along with the promulgation of relevant technology. Meanwhile, increasing seawater temperatures and other environmental changes associated with climate change, which is one of the causes of isoyake, are spreading globally and have become increasingly severe in recent years. With respect to methods of coping with the effects of climate change, the Intergovernmental Panel on Climate Change's Fifth Assessment Report (2014) calls for "adaptation" to effects that have already occurred and unavoidable medium- and long-term effects. In this context, this paper discusses the present state of and future forecasts for seaweed beds on the Japanese coast, and it then considers the future trends of climate change-adapted seaweed bed construction. [ABSTRACT FROM AUTHOR]

Abstract: A decadal climate prediction system named as IAP‐DecPreS was constructed in the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, based on a fully coupled model FGOALS‐s2 and a newly developed initialization scheme, referred to as EnOI‐IAU. In this paper, we introduce the design of the EnOI‐IAU scheme, assess the accuracies of initialization integrations using the EnOI‐IAU and preliminarily evaluate hindcast skill of the IAP‐DecPreS. The EnOI‐IAU scheme integrates two conventional assimilation approaches, ensemble optimal interpolation (EnOI) and incremental analysis update (IAU). The EnOI and IAU were applied to calculate analysis increments and incorporate them into the model, respectively. Three continuous initialization (INIT) runs were conducted for the period of 1950–2015, in which observational sea surface temperature (SST) from the HadISST1.1 and subsurface ocean temperature profiles from the EN4.1.1 data set were assimilated. Then nine‐member 10 year long hindcast runs initiated from the INIT runs were conducted for each year in the period of 1960–2005. The accuracies of the INIT runs are evaluated from the following three aspects: upper 700 m ocean temperature, temporal evolution of SST anomalies, and dominant interdecadal variability modes, Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). Finally, preliminary evaluation of the ensemble mean of the hindcast runs suggests that the IAP‐DecPreS has skill in the prediction of the PDO‐related SST anomalies in the midlatitude North Pacific and AMO‐related SST anomalies in the tropical North Atlantic. [ABSTRACT FROM AUTHOR]

This paper introduces and applies a new method to consistently estimate internal climate variability for all models within a multimodel ensemble. The method regresses each model's estimate of internal variability from the preindustrial control simulation on the variability derived from a model's ensemble simulations, thus providing practical evidence of the quasi-ergodic assumption. The method allows one to test in a multimodel consensus view how the internal variability of a variable changes for different forcing scenarios. Applying the method to the CMIP5 model ensemble shows that the internal variability of global-mean surface air temperature remains largely unchanged for historical simulations and might decrease for future simulations with a large CO2 forcing. Regionally, the projected changes reveal likely increases in temperature variability in the tropics, subtropics, and polar regions, and extremely likely decreases in midlatitudes. Applying the method to sea ice volume and area shows that their respective internal variability likely or extremely likely decreases proportionally to their mean state, except for Arctic sea ice area, which shows no consistent change across models. For the evaluation of CMIP5 simulations of Arctic and Antarctic sea ice, the method confirms that internal variability can explain most of the models' deviation from observed trends but often not the models' deviation from the observed mean states. The new method benefits from a large number of models and long preindustrial control simulations, but it requires only a small number of ensemble simulations. The method allows for consistent consideration of internal variability in multimodel studies and thus fosters understanding of the role of internal variability in a changing climate. [ABSTRACT FROM AUTHOR]

In a comment on a 2017 paper by Cheung et al., Kravtsov states that the results of Cheung et al. are invalidated by errors in the method used to estimate internal variability in historical surface temperatures, which involves using the ensemble mean of simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to estimate the forced signal. Kravtsov claims that differences between the forced signals in the individual models and as defined by the multimodel ensemble mean lead to errors in the assessment of internal variability in both model simulations and the instrumental record. Kravtsov proposes a different method, which instead uses CMIP5 models with at least four realizations to define the forced component. Here, it is shown that the conclusions of Cheung et al. are valid regardless of whether the method of Cheung et al. or that of Kravtsov is applied. Furthermore, many of the points raised by Kravtsov are discussed in Cheung et al., and the disagreements of Kravtsov appear to be mainly due to a misunderstanding of the aims of Cheung et al. [ABSTRACT FROM AUTHOR]

In this paper, we provide a Lagrangian analysis of the anomalies in the moisture transport during two important drought events (1989/1990 and 2003) configured over the Danube River Basin (DRB) region. Firstly, we identified the drought episodes that occurred over the DRB in the period of 1980-2014 through the Standardized Precipitation Evapotranspiration Index (SPEI). SPEI was calculated using monthly Climatic Research Unit (CRU) Time-Series (TS) Version 3.23 precipitation and potential evapotranspiration (PET) datasets with a spatial resolution of 0.5 degrees. The monthly SPEI-1 index was applied to identify the drought episodes and their respective indicators, including duration, severity, and intensity. Two significant drought events were selected: 1989/1990 (presenting dry conditions during October 1989-March 1990) and 2003 (presenting dry conditions during April 2003-September 2003). These events were associated with the two most severe SPEI-1 episodes identified over the DRB during 1980-2014. Then, an analysis of anomalies in the moisture transport was conducted in order to verify possible changes in the moisture supply from the climatological sources for the DRB during these episodes. The moisture transport analysis was performed through a Lagrangian approach, which uses the outputs of the FLEXiblePARTicle dispersion model FLEXPART integrated with one of the reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF): the ECMWF Re-Analysis (ERA)-Interim dataset. The DRB receives moisture from seven different moisture source regions: the North Atlantic Ocean (NATL), North Africa (NAF), the Mediterranean Sea (MED), the Black Sea (BS), the Caspian Sea (CS), the DRB, and Central and Eastern Europe (Rest of Land (RestL)). The analysis of drought events shows that the precipitation and moisture supply from the selected sources weakened mainly during both drought events. Anomalous subsidence and an increased PET also prevailed over the DRB during these SPEI-1 episodes. RestL and MED registered the most intensive reduction in the moisture supply over the DRB during both periods. [ABSTRACT FROM AUTHOR]

This paper compares data from linearized and nonlinear Zebiak-Cane model, as constrained by observed sea surface temperature anomaly (SSTA), in simulating central Pacific (CP) and eastern Pacific (EP) El Ni˜no. The difference between the temperature advections (determined by subtracting those of the linearized model from those of the nonlinear model), referred to here as the nonlinearly induced temperature advection change (NTA), is analyzed. The results demonstrate that the NTA records warming in the central equatorial Pacific during CP El Ni˜no and makes fewer contributions to the structural distinctions of the CP El Ni˜no, whereas it records warming in the eastern equatorial Pacific during EP El Ni˜no, and thus significantly promotes EP El Ni˜no during El Ni˜no-type selection. The NTA for CP and EP El Ni˜no varies in its amplitude, and is smaller in CP El Ni˜no than it is in EP El Ni˜no. These results demonstrate that CP El Ni˜no are weakly modulated by small intensities of NTA, and may be controlled by weak nonlinearity; whereas, EP El Ni˜no are significantly enhanced by large amplitudes of NTA, and are therefore likely to be modulated by relatively strong nonlinearity. These data could explain why CP El Ni˜no are weaker than EP El Ni˜no. Because the NTA for CP and EP El Ni˜no differs in spatial structures and intensities, as well as their roles within different El Ni˜no modes, the diversity of El Ni˜no may be closely related to changes in the nonlinear characteristics of the tropical Pacific. [ABSTRACT FROM AUTHOR]

Surface upward longwave radiation (SULR) is an important component of the surface energy balance and is closely related to land surface temperature and emissivity. The estimation of SULR plays an important role in the study of surface energy circulation and climate change. State-of-the-art methods to estimate SULR, including the physical method and the hybrid method, are conducted without considering directional thermal radiation (DTR), which may induce a large error in the estimation, particularly over sparsely vegetated surfaces. In this paper, we modified the physical temperature–emissivity algorithm by combining a directional emissivity model (FRA97) and a kernel-driven DTR model to estimate the SULR of vegetated surfaces while considering the thermal directionality of the land surface. The most suitable kernel-driven model and an angle combination of the DTR were selected from six kernel-driven models and five angular combinations. The sensitivity of the proposed algorithm to the input parameters was also analyzed. The proposed algorithm was then validated with the Wide-angle infrared Dual-mode line/area Array Scanner (WiDAS) data set and longwave radiation data of automatic meteorological stations from the Heihe Watershed Allied Telemetry Experimental Research experiment. The results showed that the five-angle combination with large-angle intervals performs the best. When the leaf area index (LAI) is less than 1.2, the RossThick-LiSparseR model performs the best; when LAI is larger than 1.2, the RossThick-LiDenseR model is the most accurate. The SULR is not sensitive to surface downward longwave radiation and LAI, is slightly sensitive to leaf and soil emissivity at certain LAIs, and is highly sensitive to DTR, which may greatly affect the accuracy of the estimated SULR. The root-mean-square error (RMSE) and the mean bias error (MBE) of the SULR estimated using the WiDAS data and the proposed algorithm are 5.618 and −1.642 W/m2, respectively, thereby improving the estimation accuracy by as much as 7.479 and 10.511 W/m2 at most in terms of RMSE and MBE, respectively, compared with the results calculated without considering the DTR. [ABSTRACT FROM PUBLISHER]

Potential and real predictive skill of the frequency of extreme rainfall in southeastern South America for the December-February season are evaluated in this paper, finding evidence indicating that mechanisms of climate variability at one time scale contribute to the predictability at another scale; that is, taking into account the interference of different potential sources of predictability at different time scales increases the predictive skill. Part I of this study suggested that a set of daily atmospheric circulation regimes, or weather types, was sensitive to these cross-time scale interferences, conducive to the occurrence of extreme rainfall events in the region, and could be used as a potential predictor. At seasonal scale, a combination of those weather types indeed tends to outperform all the other candidate predictors explored (i.e., sea surface temperature patterns, phases of the Madden-Julian oscillation, and combinations of both). Spatially averaged Kendall's τ improvements of 43% for the potential predictability and 23% for real-time predictions are attained with respect to standard models considering sea surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed based on probability forecasts of seasonal sequences of these weather types. The cross-validated real-time skill of the new probabilistic approach, as measured by the hit score and the Heidke skill score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season but also in how, when, and where those events will probably occur. [ABSTRACT FROM AUTHOR]

Few if any high-resolution (annually resolved) paleoclimate records are available for the Hawaiian Islands prior to ~1850 CE, after which some instrumental records start to become available. This paper shows how atmospheric teleconnection patterns between North America and the northeastern North Pacific (NNP) allow for reconstruction of Hawaiian Islands rainfall using remote proxy information from North America. Based on a newly available precipitation dataset for the state of Hawaii and observed and reconstructed December-February (DJF) sea level pressures (SLPs) in the North Pacific Ocean, the authors make use of a strong relationship between winter SLP variability in the northeast Pacific and corresponding DJF Hawaii rainfall variations to reconstruct and evaluate that season's rainfall over the period 1500-2012 CE. A general drying trend, though with substantial decadal and longer-term variability, is evident, particularly during the last ~160 years. Hawaiian Islands rainfall exhibits strong modulation by El Niño-Southern Oscillation (ENSO), as well as in relation to Pacific decadal oscillation (PDO)-like variability. For significant periods of time, the reconstructed large-scale changes in the North Pacific SLP field described here and by construction the long-term decline in Hawaiian winter rainfall are broadly consistent with long-term changes in tropical Pacific sea surface temperature (SST) based on ENSO reconstructions documented in several other studies, particularly over the last two centuries. Also noted are some rather large multidecadal fluctuations in rainfall (and hence in NNP SLP) in the eighteenth century of undetermined provenance. [ABSTRACT FROM AUTHOR]

Simple Summary: Atlantic salmon (Salmo salar) has become a commodity worldwide. The culture of Atlantic salmon is by far the most well-developed branch of marine finfish aquaculture, with this species ranking among the top ten most highly produced in global aquaculture. While Atlantic salmon has been commonly farmed in sea cages located in colder waters (e.g., in Norway, Chile and Tasmania), these regions can experience the negative impacts of heat waves that push seawater temperature above values tolerated by this species. These climate-change-driven shifts in water temperature can be associated with mass mortality events and urgent actions are needed to cope with a changing ocean. This paper reviews the thermal limits of adult Atlantic salmon and lists the negative effects driven by heat stress. We highlight how biotechnology and the genetic diversity of wild populations may help producers to tackle this challenge. Selective breeding programs and other more advanced biotechnological solutions (e.g., gene editing) may play a key role in this quest to produce new strains of Atlantic salmon that more readily tolerate higher water temperatures, without compromising productivity and profitability. Atlantic salmon (Salmo salar) cage farming has traditionally been located at higher latitudes where cold seawater temperatures favor this practice. However, these regions can be impacted by ocean warming and heat waves that push seawater temperature beyond the thermo-tolerance limits of this species. As more mass mortality events are reported every year due to abnormal sea temperatures, the Atlantic salmon cage aquaculture industry acknowledges the need to adapt to a changing ocean. This paper reviews adult Atlantic salmon thermal tolerance limits, as well as the deleterious eco-physiological consequences of heat stress, with emphasis on how it negatively affects sea cage aquaculture production cycles. Biotechnological solutions targeting the phenotypic plasticity of Atlantic salmon and its genetic diversity, particularly that of its southernmost populations at the limit of its natural zoogeographic distribution, are discussed. Some of these solutions include selective breeding programs, which may play a key role in this quest for a more thermo-tolerant strain of Atlantic salmon that may help the cage aquaculture industry to adapt to climate uncertainties more rapidly, without compromising profitability. Omics technologies and precision breeding, along with cryopreservation breakthroughs, are also part of the available toolbox that includes other solutions that can allow cage farmers to continue to produce Atlantic salmon in the warmer waters of the oceans of tomorrow. [ABSTRACT FROM AUTHOR]

The Caribbean Sea and adjacent land areas are highly sensitive to the projected impacts of global climate change. The countries bordering the Caribbean Sea depend heavily on coastal and marine assets as a major source of livelihood support. Rising sea surface temperatures (SSTs) are known to be associated with coral bleaching, ocean acidification, and other phenomena that threaten livelihoods in the region. The paucity of SST systematic observations in both the Caribbean Sea and adjoining Western Atlantic waters is a limiting factor in the projection of future climate change impacts on the region's marine resources. Remote sensing of SST by satellites began only within the last three decades and although the data collected so far might be insufficient to provide conclusive definitions of long-term SST variations in the Caribbean waters, these data along with the output from climate model simulations provide a useful basis for gaining further insights into plausible SST futures under IPCC SRES scenarios. In this paper, we examine the recent SST records from the NESDIS AVHRR satellite data and NOAA Optimum Interpolation (OI) sea surface temperature V2 and provide a comparative analysis of projected SST changes for the Caribbean Sea up to the end of the twenty-first century, under the SRES A2 and B2 scenarios' simulations of the sea surface skin temperatures (SSsT) using the Hadley Centre's regional model, PRECIS. The implications of these projected SST changes for bleaching of coral reefs, one of the region's most valuable marine resource, and for rainfall are also discussed. [ABSTRACT FROM AUTHOR]

This paper investigates the structure and dynamics of the Equatorial Undercurrent (EUC) of the Indian Ocean by analyzing in situ observations and reanalysis data and performing ocean model experiments using an ocean general circulation model and a linear continuously stratified ocean model. The results show that the EUC regularly occurs in each boreal winter and spring, particularly during February and April, consistent with existing studies. The EUC generally has a core depth near the 20°C isotherm and can be present across the equatorial basin. The EUC reappears during summer-fall of most years, with core depth located at different longitudes and depths. In the western basin, the EUC results primarily from equatorial Kelvin and Rossby waves directly forced by equatorial easterly winds. In the central and eastern basin, however, reflected Rossby waves from the eastern boundary play a crucial role. While the first two baroclinic modes make the largest contribution, intermediate modes 3-8 are also important. The summer-fall EUC tends to occur in the western basin but exhibits obvious interannual variability in the eastern basin. During positive Indian Ocean dipole (IOD) years, the eastern basin EUC results largely from Rossby waves reflected from the eastern boundary, with directly forced Kelvin and Rossby waves also having significant contributions. However, the eastern basin EUC disappears during negative IOD and normal years because westerly wind anomalies force a westward pressure gradient force and thus westward subsurface current, which cancels the eastward subsurface flow induced by eastern boundary-reflected Rossby waves. Interannual variability of zonal equatorial wind that drives the EUC variability is dominated by the zonal sea surface temperature (SST) gradients associated with IOD and is much less influenced by equatorial wind associated with Indian monsoon rainfall strength. [ABSTRACT FROM AUTHOR]

SSTs in the western Pacific Ocean have tracked closely with CMIP5 simulations despite recent hiatus cooling in the eastern Pacific. This paper quantifies these similarities and associated circulation and precipitation variations using the first global 1900-2012 ENSO-residual empirical orthogonal functions (EOFs) of 35 variables: observed SSTs; 28 CMIP5 SST simulations; Simple Ocean Data Assimilation (SODA) 25-, 70-, and 171-m ocean temperatures and sea surface heights (SSHs); and Twentieth Century Reanalysis, version 2 (20CRv2), surface winds and precipitation. While estimated independently, these leading EOFs across all variables fit together in a meaningful way, and the authors refer to them jointly as the west Pacific warming mode (WPWM). WPWM SST EOFs correspond closely in space and time. Their spatial patterns form a "western V" extending from the Maritime Continent into the extratropical Pacific. Their temporal principal components (PCs) have increased rapidly since 1990; this increase has been primarily due to radiative forcing and not natural decadal variability. WPWM circulation changes appear consistent with a Matsuno-Gill-like atmospheric response associated with an ocean-atmosphere dipole structure contrasting increased (decreased) western (eastern) Pacific precipitation, SSHs, and ocean temperatures. These changes have enhanced the Walker circulation and modulated weather on a global scale. An AGCM experiment and the WPWM of global boreal spring precipitation indicate significant drying across parts of East Africa, the Middle East, the southwestern United States, southern South America, and Asia. Changes in the WPWM have tracked closely with precipitation and the increase in drought frequency over the semiarid and water-insecure areas of East Africa, the Middle East, and southwest Asia. [ABSTRACT FROM AUTHOR]

Using the newly available decade-long Argo data for the period 2004-13, a detailed study is carried out on deriving four-dimensional (4D) modality of sea temperature in the upper ocean with emphasis on its interannual variability in terms of amplitude, phase, and periodicity. Three principal modes with central periodicities at 19.2, 33.8, and 50.3 months have been identified, and their relationship with El Niño-Southern Oscillation (ENSO) is investigated, yielding a number of useful results and conclusions: 1) A striking tick-shaped pipe-like feature of interannual variability maxima, which is named the 'Niño pipe' in this paper, has been revealed within the 10°S-10°N upper Pacific Ocean. 2) The pipe core extends downward from ~50 m at 130°E to ~250 m near the date line before tilting upward to the sea surface at about 275°E, coinciding nicely with the pathway of the Pacific equatorial undercurrent (EUC). 3) The double-peak zonal modality pattern of the Niño pipe in the upper Pacific is echoed in the subsurface Atlantic and Indian Oceans through Walker circulation, while its single-peak meridional modality pattern is mirrored in the subsurface North and South Pacific through Hadley circulation. 4) A coherent three-peak modal structure implies a strong coupling between sea level variability at the surface and sea temperature variability around the thermocline. Accumulating evidence suggests that Rossby/Kelvin wave dynamics in tandem with EUC-based thermocline dynamics are the main mechanisms of the three-mode Niño pipe in ENSO cycles. [ABSTRACT FROM AUTHOR]

This paper explores the impact of anomalous northward oceanic heat transport on global climate in a slab ocean setting. To that end, the GCM LMDZ5A of the Laboratoire de Météorologie Dynamique is coupled to a slab ocean, with realistic zonal asymmetries and seasonal cycle. Two simulations with different anomalous surface heating are imposed: 1) uniform heating over the North Atlantic basin and 2) concentrated heating in the Gulf Stream region, with a compensating uniform cooling in the Southern Ocean in both cases. The magnitudes of the heating and of the implied northward interhemispheric heat transport are within the range of current natural variability. Both simulations show global effects that are particularly strong in the tropics, with a northward shift of the intertropical convergence zone (ITCZ) toward the heating anomalies. This shift is accompanied by a northward shift of the storm tracks in both hemispheres. From the comparison between the two simulations with different anomalous surface heating in the North Atlantic, it emerges that the global climate response is nearly insensitive to the spatial distribution of the heating. The cloud response acts as a large positive feedback on the oceanic forcing, mainly because of the low-cloud-induced shortwave anomalies in the extratropics. While previous literature has speculated that the extratropical Q flux may impact the tropics by the way of the transient eddy fluxes, it is explicitly demonstrated here. In the midlatitudes, the authors find a systematic northward shift of the jets, as well as of the associated Ferrel cells, storm tracks, and precipitation bands. [ABSTRACT FROM AUTHOR]

Amos, C.L.; Martino, S.; Sutherland, T.F., and Al Rashidi, T., 2015. Sea surface temperature trends in the coastal zone of British Columbia, Canada. Coastal sea surface temperature (SST), measured daily at the British Columbia (BC) Lighthouse network of stations, has been analyzed in this paper. A network of 14 of the 27 stations had (near) continuous data sets. These stations were clustered previously into exposed (northern/outer) and sheltered (southern/inner) sites. SST trends, evaluated between 1973 and 2010, show that the temperature contrast between these clusters is becoming greater: The northern/exposed stations are strongly influenced by interdecadal (Pacific Decadal oscillation [PDO]) and multidecadal oscillations in the north Pacific that are coherent with HadISST1.1 data for the region. There is no statistically significant warming trend for this region. The stations in the Strait of Georgia are much less influenced by the PDO and show a statistically significant mean increase in SST of up to 0.56°C/decade (Anomaly 1). This is higher than the global average and contrasts markedly with the trends from the northern stations. The warming trends of the southern stations are significant at all months of the year but are most evident during summer (July-September). The summertime anomalies in temperature at Active Pass are significantly correlated ( p < 0.001) with the temperature of the Fraser River water. Temperature differences between the Strait of Georgia and the outer shelf (Anomaly 2) are increasing in time; this is particularly evident since 2000. Monthly averaged MODIS satellite data (4×4-km resolution) show that trends in SST at two selected sites in the Strait of Georgia are very similar to the BC Lighthouse measurements and support the spatial extrapolation of the Lighthouse measurements. At present rates of SST rise, the southern coastal waters of BC will be about 3°C warmer by the end of the 21st century. [ABSTRACT FROM AUTHOR]

This paper provides a review of atmospheric circulation and sea surface temperature (SST) conditions that are associated with meteorological drought on the seasonal time scale in the Greater Horn of Africa (the region 10°S-15°N, 30°-52°E). New findings regarding a post-1998 increase in drought frequency during the March-May (MAM) 'long rains' are also reported. The period 1950-2010 is emphasized, although rainfall and SST data from 1901-2010 are used to place the recent long rains decline in a multidecadal context. For the latter case, climate model simulations and isolated basin SST experiments are also utilized. Climatologically, rainfall exhibits a unimodal June-August (JJA) maximum in west-central Ethiopia with a generally bimodal [MAM and October-December (OND) maxima] distribution in locations to the south and east. Emphasis will be on these three seasons. SST anomalies in the tropical Pacific and Indian Oceans show the strongest association with drought during OND in locations having a bimodal annual cycle, with weaker associations during MAM. The influence of the El Niño-Southern Oscillation (ENSO) phenomenon critically depends on its ability to affect SSTs outside the Pacific. Salient features of the anomalous atmospheric circulation during drought events in different locations and seasons are discussed. The post-1998 decline in the long rains is found to be driven strongly (although not necessarily exclusively) by natural multidecadal variability in the tropical Pacific rather than anthropogenic climate change. This conclusion is supported by observational analyses and climate model experiments, which are presented. [ABSTRACT FROM AUTHOR]

The emergence of climate change (CC) is affecting and changing the development of the natural environment, biological species, and human society. In order to better understand the influence of climate change and provide convincing evidence, the need to quantify the impact of climate change is urgent. In this paper, a climate change model is constructed by using a radial basis function (RBF) neural network. To verify the relevance between climate change and extreme weather (EW), the EW model was built using a support vector machine. In the case study of Canada, its level of climate change was calculated as being 0.2241 ("normal"), and it was found that the factors of CO2 emission, average temperature, and sea surface temperature are significant to Canada's climate change. In 2025, the climate level of Canada will become "a little bad" based on the prediction results. Then, the Pearson correlation value is calculated as being 0.571, which confirmed the moderate positive correlation between climate change and extreme weather. This paper provides a strong reference for comprehensively understanding the influences brought about by climate change. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Climate change is one of the biggest and most urgent challenges for the 21st century. Rising average temperatures and ocean levels, altered precipitation patterns and increased occurrence of extreme weather events affect not only the global landscape and ecosystem, but also human health. Multiple environmental factors influence the onset and severity of human diseases and changing climate may have a great impact on these factors. Climate shifts disrupt the quantity and quality of water, increase environmental pollution, change the distribution of pathogens and severely impacts food production – all of which are important regarding public health. This paper focuses on brain health and provides an overview of climate change impacts on risk factors specific to brain diseases and disorders. We also discuss emerging hazards in brain health due to mitigation and adaptation strategies in response to climate changes. • Climate change is one of the biggest and most urgent challenges regarding human health. • Multiple environmental factors affecting human health can be modulated in the changing climate. • The paper provides an overview of climate change impacts on risk factors specific to brain diseases. • Hazards due to mitigation and adaptation strategies in response to climate changes are also discussed. [ABSTRACT FROM AUTHOR]

It is important to consider where, when, and how the evolution of sea surface temperature anomalies (SSTA) plays significant roles in regional or global climate changes. In the comparison of where and when, there is a great challenge in clearly describing how SSTA evolves in space and time. In light of the evolution from generation, through development, and to the dissipation of SSTA, this paper proposes a novel approach to identifying an evolution of SSTA in space and time from a time-series of a raster dataset. This method, called PoAIES, includes three key steps. Firstly, a cluster-based method is enhanced to explore spatiotemporal clusters of SSTA, and each cluster of SSTA at a time snapshot is taken as a snapshot object of SSTA. Secondly, the spatiotemporal topologies of snapshot objects of SSTA at successive time snapshots are used to link snapshot objects of SSTA into an evolution object of SSTA, which is called a process object. Here, a linking threshold is automatically determined according to the overlapped areas of the snapshot objects, and only those snapshot objects that meet the specified linking threshold are linked together into a process object. Thirdly, we use a graph-based model to represent a process object of SSTA. A node represents a snapshot object of SSTA, and an edge represents an evolution between two snapshot objects. Using a number of child nodes from an edge's parent node and a number of parent nodes from the edge's child node, a type of edge (an evolution relationship) is identified, which shows its development, splitting, merging, or splitting/merging. Finally, an experiment on a simulated dataset is used to demonstrate the effectiveness and the advantages of PoAIES, and a real dataset of satellite-SSTA is used to verify the rationality of PoAIES with the help of ENSO's relevant knowledge, which may provide new references for global change research. [ABSTRACT FROM AUTHOR]

This is an update of Sobrino et al.'s paper, published in January 2020, which extends the calculation of the Earth's surface temperature to the period 2003–2019 and uses the new version 2019.0 for the sea surface temperature product MODIS, which is available from 15 January 2020 and replaces version 2014.0. The land surface temperature was estimated from the MCD11C1 product for the same period. The results corroborate the temperature anomalies retrieved from climate models and improve the comparison with global annual air temperatures estimated by the NOAA's National Climatic Data Center (NOAA-NCDC), with a correlation coefficient of 0.96. In addition, a trend of 0.021 ± 0.001 °C/year increase was found for the Earth's surface temperature in this 17-year period. [ABSTRACT FROM AUTHOR]