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This paper presents an investigation on simultaneous freshwater production and CO2 capture using the flue gases of a 500 MWe coal‐fired power plant. Generally, a fan/cooler is used to reduce the temperature of flue gas before flowing into the absorber column of a CO2 capture unit. It has been replaced with a heat exchanger in this study. Seawater and flue gas were passed through the heat exchanger to raise the temperature of seawater and reduce the temperature of flue gas. The high‐temperature seawater was subsequently fed into a membrane distillation (MD) unit for freshwater production. The cold flue gas was directed to the CO2 capture unit. The heat exchanger and CO2 capture unit were modeled with Aspen Plus software. Whereas MATLAB software was used to develop and solve the MD mathematical model software for freshwater production. The seawater flow rate was varied from 4000 L/min to 7000 L/min in the heat exchanger. As a result, the flue gas (flow rate 781.6 t/h) and the outlet seawater temperatures were reduced from 27.498 to 22.360°C and 73.384 to 52.670°C, respectively. However, higher inlet seawater temperature in the MD unit produced more freshwater. An increase in inlet seawater feed temperature in the MD unit from 52.670 to 73.384°C increased the freshwater production from 211,956.5 to 299,244 L/day. Furthermore, the CO2 capture process has been analyzed by varying the methyldiethanolamine (MDEA) and piperazine (PZ) concentrations in weight% (45 and 5, 40 and 10, 35 and 15, and 30 and 20, respectively). It was observed that the energy requirement reduced from 3.55 to 3.26 MJ/kg CO2 by increasing the PZ content from 5 to 20 wt.%. At 15 and 20 wt.% of PZ content in the blended solution of MDEA/PZ, the energy required to regenerate the solvent was 3.31 and 3.26 MJ/kg CO2, respectively. PZ emissions from the absorber were also increased with the raising of PZ content in the blended solution. The energy requirement was not much higher at 15 wt.% than 20 wt.%. Therefore, MDEA/PZ solution (15/35 wt.%) was considered an optimal concentration. The reboiler duty was reduced up to 3.25 MJ/kg CO2 at 15/35 wt.% concentration with stripper pressure of 2.3 bar. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Maritime Autonomous Surface Ships are in the development stage and they play an important role in the upcoming future. Present generation ships are semi-autonomous and controlled by the ship crew. The performance of the ship is predicted using the data collected from the ship with the help of machine learning and deep learning methods. Path planning for an autonomous ship is necessary for estimating the best possible route with minimum travel time and it depends on the weather. However, even during the navigation, there will be changes in weather and it should be predicted in order to reroute the ship. The weather information such as wave height, wave period, seawater temperature, humidity, atmospheric pressure, etc., is collected by ship external sensors, weather stations, buoys, and satellites. This paper investigates the ensemble machine learning approaches and seasonality approach for wave data prediction. The historical meteorological data are collected from six stations near Puerto Rico offshore and Hawaii offshore. We explore ensemble machine learning techniques on the data collected. The collected data are divided into training and testing data and apply machine learning models to predict the test data. The hyperparameter optimization is performed to find the best parameters before fitting on train data, this is essential to find the best results. Multivariate analysis is performed with all the methods and errors are computed to find the best models. [ABSTRACT FROM AUTHOR]

We develop a new data assimilative (DA) approach by combining two parallel frameworks: a parallel DA framework (PDAF) and a flexible model coupling framework (ESMF). The new DA system is built on the ESMF at the top level that drives the PDAF and any combination of Earth system modeling (ESM) components, to allow maximum flexibility and easy implementation of data assimilation for fully coupled ESM applications. We demonstrate the new DA system using a 3D unstructured-grid ocean model as ESM in this paper. The new system is validated using a simple benchmark and applied to a realistic case of Kuroshio simulation around Taiwan. The new system is demonstrated to significantly improve the model skill for temperature, velocity and surface elevation before, during and after typhoon events. The flexibility and ease of implementation make the new system widely applicable for other coupled ESMs. [ABSTRACT FROM AUTHOR]

The July 2021 flood in central Europe was one of the five costliest natural disasters in Europe in the last half century with estimated total damage of EUR 32 billion. This study investigates the complex interactions between meteorological, hydrological, and hydro-morphological processes and mechanisms that led to the exceptional flood. Furthermore, we present our estimates of the impacts in terms of inundation areas, traffic disruptions, and economic losses. The estimation of inundation areas as well as the derived damage assessments were carried out during or directly after the flood, and show the potential of near-real-time forensic disaster analyses for crisis management, emergency personnel on-site, and the provision of relief supplies. The superposition of several factors resulted in widespread extreme precipitation totals and water levels well beyond a 100-year event: slow propagation of the low pressure system Bernd, convection embedded in a mesoscale precipitation field, unusually moist air masses associated with a significant positive anomaly in sea surface temperature over the Baltic Sea, wet soils, and steep terrain. Various hydro-morphodynamic processes as well as changes in valley morphology observed during the event exacerbated the impact of the flood. Relevant effects included, among many others, the occurrence of extreme landscape erosion, rapidly evolving erosion and scour processes in the channel network and urban space, recruitment of debris from the natural and urban landscape, deposition and clogging of bottlenecks in the channel network with eventual collapse. This study is part one of a two-paper series. The second part puts the July 2021 flood into a historical context and into the context of climate change. [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]

In 2014, an unexpected and unusual warm patch of ocean water was discovered in the northeast Pacific Ocean (PO) that moved south, reaching the Mexican coasts; this patch, returning in 2019, was nicknamed "the Blob". This paper aimed to assess the impacts of this phenomenon on the sea surface temperature (SST) and chlorophyll-a (CHLA) levels in the Gulf of California (GC), a high-productivity region. Daily satellite images of SST and CHLA with a spatial resolution of 1 km/pixel were obtained for 2014, 2017, and 2019 from the Moderate Resolution Imaging Spectroradiometer (MODIS). Two disc-shaped areas of around 25 km in diameter were selected in the southern portion of the GC to assess the variability of both parameters quantitatively. An additional site was selected in the PO for comparison and, thus, to better characterize and have a complete vision of these events. The results showed that in the PO, during the periods in which the Blob occurred, the SST values were higher concerning the neutral year (2017), and the levels of CHLA were very low (barely 0.15 mg m-3). Within the GC, the results showed the presence of a strong seasonal variability, with maximum values of SST (>30°C) and the lowest concentrations of CHLA (<2 mg m-3) during the summer, with maximum concentrations of CHLA (~10 mg m-3) observed during the winter months. Contrary to expectations, no dramatic changes in SST and CHLA were observed during the years impacted by the Blob. This apparent absence of negative impacts could be related to different mechanisms in the gulf that "protect" to avoid climate disruptions. The presence of complex geomorphology and hydrodynamic processes at different scales induce mixing and fertilizing of the euphotic layer. Could these factors protect the southern gulf from the negative impacts of the Blob? [ABSTRACT FROM AUTHOR]

In oceanographic study, satellite-based sea surface temperature (SST) retrieval has always been the focus of researchers. This paper investigates several multi-channel SST retrieval algorithms for the thermal infrared band, and evaluates the accuracy of the COCTS/HY-1C SST products. NEAR-GOOS in situ SST data are utilized for validation and improvement, and a three-step matching procedure including geographic location screening, cloud masking, and homogeneity check is conducted to match in situ SST data with satellite SST data. Two improvement schemes, including nonlinear regression and regularization iteration, are proposed to improve the accuracy of the COCTS/HY-1C SST products and the typical application scenarios and the algorithm characteristics of these two schemes are discussed. The standard deviation of residual between retrieved SST and measured SST for these two data improvement algorithms, which are considered as the main indexes for assessment, result in an improvement of 13.245% and 14.096%, respectively. In addition, the generalization ability of the SST models under two data improvement methods is quantitatively compared, and the factors affecting the model accuracy are also carefully evaluated, including the in situ data acquisition method and measurement time (day/night). Finally, future works about SST retrieval with COCTS/HY-1C satellite data are summarized. [ABSTRACT FROM AUTHOR]

This paper discusses the nature of the low-frequency seismo-acoustic waves generated by submarine earthquakes in the ocean. In a finite-depth homogeneous ocean over a semi-infinite solid crust, the derivation of the acoustic equations shows that waves propagate as modes. The waves propagating with the speed of sound in water (T waves) are preceded by waves with frequencies below the Airy phase. Furthermore, the group speeds of these modes are sensitive to the environmental setting. As a test, we applied the spectral finite-element code SPECFEM2D in a simplified configuration with an ocean layer overlaying a solid crust, and a seismic source below a Gaussian seamount surrounded by a flat seafloor. The simulations confirm that the generated T waves and their precursors follow the theoretical dispersion curves. A more realistic environment with a seismically-layered crust and a sound-speed profile in the ocean is then used to predict the expected acoustic modes. Although noisy, recordings by ocean bottom seismometers from the southwest Indian Ocean show T waves preceded by ultra-low frequency waves, which display two modes comparable to the theoretical ones. They are in good agreement for mode 1, whereas, for mode 0, a slight offset in frequency has yet to be explained. [ABSTRACT FROM AUTHOR]

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the most significant increasing areas for summer precipitation extremes in China. In this paper, the number of very heavy precipitation days (R20day) is selected as a representative variable to explore the probable causes of abnormal changes in summer precipitation extremes in recent decades by using the gridded 0.25° × 0.25° observation dataset of CN05.1, NCEP/NCAR Reanalysis 1 with a horizontal resolution of 2.5° × 2.5° and NOAA Extended Reconstructed Sea Surface Temperature (ERSST) V5 with a horizontal resolution of 2.0° × 2.0°. The onset of the South China Sea summer monsoon was early (late), and the R20day in summer was more (less) on both interannual and interdecadal scales. In recent decades, the East Asian summer monsoon and the western North Pacific monsoon weakened, and the R20day in the GBA increased. When the Eurasian teleconnection pattern is in the positive (negative) phase, positive (negative) height anomalies occur in Mongolia and North Central China, and negative (positive) height anomalies occur in South China, which enhances (weakens) vertical upward movements and the south wind anomaly in the lower troposphere in South China, resulting in strong (weak) humidity and more (less) R20day in the GBA. The influences of the Silk Road teleconnection pattern, East Asia/Pacific teleconnection pattern, North Pacific decadal oscillation and western Pacific warm pool strength on R20day are only significant on an interdecadal scale. The North Pacific gyre oscillation has significant effects on the interdecadal change and weakly significant effects on the interannual variation of R20day in the GBA. On an interannual scale, the south-north oscillation of sea surface temperature in the North Pacific and Indian Ocean dipole plays a significant role. [ABSTRACT FROM AUTHOR]

This paper concerns the effects of hygrothermal ageing on the tensile behaviour of assymetric helicoidally stacked carbon fibre reinforced plastic (CFRP) composites. MR70 12P carbon fibre epoxy prepreg sheets were manufactured into laminated composites comprising constant inter-ply pitch angles ranging from 0 ° to 30 ° . The composites were tested in tension (according to BS ISO 527-5:2009) as either dry unaged specimens or following hygrothermal ageing in seawater at the constant temperatures of 40 ° C and 60 ° C for 2000 h. Both tensile modulus and tensile strength are found to be detrimentally affected by hygrothermal ageing, and the extent to which ageing affects these properties is a function of the inter-ply pitch angle. Higher hygrothermal ageing temperatures are found to decrease the tensile modulus and strength ratios of asymmetric helicoidally stacked composites when compared against UD composites subjected to the same conditions and the strength and stiffness ratios of all composites when compared against unaged equivalents. Significantly, therefore, we show that the degradation of helicoidal composite properties under hygrothermal conditions, in general, occurs more rapidly than it does in UD composites, and thus the long-term use of helicoidal composites in immersed environments should take into account these differences. A second order relationship is observed for the mechanical properties of the composites when plotted against their inter-ply helicoidal pitch angles. As such, a mixtures model was modified to incorporate the observed effects of laminate inter-ply pitch angle and used to predict the tensile modulus of unaged composites. The predictions are within one standard deviation of the experimental arithmetic mean; however, the model can only be used for dry helicoidal composites, as ageing alters the microstructures in an irregular manner between the different sample sets. The development of this mixture model is useful as it provides a justifiably simple route to predicting the properties of dry helicoidal structures, albeit within the bounds of specific interply-pitch angles. Finite element analyses (Hashin failure) elucidate the plies that are most likely responsible for composite failure. The validity of these numerical predictions is evidenced by observing primary fracture paths in the composites. Finally, hygrothermal ageing is found to enable greater in-plane (mode III) twisting of individual laminates under loading, with certain laminate angles being more prone to twisting than others. [ABSTRACT FROM AUTHOR]

Anticyclonic mesoscale eddies are often observed in the Balearic Sea (BS) toward the end of summer and autumn. In some years, these eddies become strong and persistent, modifying the local water mass properties. In this study, we analyze two of the most significant recent long‐lived anticyclonic eddies, occurring in 2010 and 2017, using data from a high‐resolution circulation model, altimetry and satellite‐borne sea surface temperature observations. These eddies lasted around 2 and 4 months, respectively, with a radius varying between 40 and 75 km. The generation and intensification mechanisms of these long‐lived anticyclonic eddies are studied by means of (a) energy conversion terms associated with eddy‐mean flow interaction and (b) model sensitivity tests. Results show that these eddies were formed and intensified through mixed barotropic and baroclinic instabilities. The former are produced under the action of intense northwesterly (NW) winds. The latter are related to the existence of an intense summer thermal front between the BS and the Gulf of Lion, and to northward inflows of relatively lower salinity waters. Both the wind events and the presence of the thermal front are necessary for the formation of the eddies. The intensification process varied between both events. While in 2010 it was driven by significant salinity gradients produced by northwards inflows, in 2017 it was produced by additional intense NW winds. Both long‐lived anticyclonic eddies created long‐lasting surface temperature anomalies up to 2.5°C, which have characteristics of local marine heatwaves. Plain Language Summary: Eddies are closed circular currents present in the oceans. They are important phenomena due to their capacity to isolate water masses, retain floating particles and modify ocean circulation. In the Western Mediterranean Sea there is a recognized area of anticyclonic eddy presence between Barcelona and the Balearic Islands, especially during late summer. Specifically, in 2010 and 2017 two such eddies were identified with lifetimes of 2 and 4 months, respectively. In this paper, we investigate why these eddies were so long and persistent in comparison with other years. Results confirm that these eddies are generated as a result of northwesterly (NW) winds events blowing over an area with two water masses of different temperature. In 2010, low salinity northward water inflows sustained this eddy during two months, while in 2017 the eddy remained active for a period of four months under the influence of additional intense NW winds. Both eddies created long‐lasting surface temperature anomalies, in particular in 2017, the sea surface temperature within the eddy influence area was 2.5°C warmer in comparison to other years. Key Points: Northwesterly (NW) wind events and the existence of the Pyrenees thermal front are both necessary for the formation of strong long‐lived Balearic Sea eddiesEddy intensification was driven by salinity gradients in 2010 and by additional NW wind events in 2017Both events created long‐lasting surface temperature anomalies that have the characteristics of local marine heatwaves [ABSTRACT FROM AUTHOR]

Based on 130 climate signal indexes provided by National Climate Center of China, this paper established a decision tree diagnostic prediction model for Spring Kuroshio Sea Surface Temperature (SST) from 1961 to 2015 (65 years) by using Chi-Squared Automatic Interaction Detector (CHAID) algorithm in data mining and obtained five rule sets to determine whether Spring Kuroshio SST is high or not. Considering the data of the 44 years from 1961 to 2004 as the training set of the model and the other years as the test set, the training accuracy of the model can reach to 95.45% and the test accuracy can reach to 81.82%. Three types of Spring Kuroshio SST are different in intensity and distribution. The results show that the prediction model of Spring Kuroshio SST based on CHAID algorithm has a high prediction accuracy, with the reasonable and effective model and the well-thought-out decision rules. Moreover, based on the results of decision classification, the SST anomalies correspond to different distribution characteristics of summer daily precipitation anomalies in eastern China, which can provide a new idea and method for climate prediction of regional summer precipitation. [ABSTRACT FROM AUTHOR]

Machine learning methods have now become an optional technique in Earth science research, and such data-driven solutions have also made tremendous progress in weather forecasting and climate prediction in recent years. Since climate data are typically time series, the neural network layers, which can identify the intrinsic connections between the points of the sequence and features in two-dimensional data, perform particularly well for climate prediction. The North Atlantic Oscillation (NAO) is a prominent atmospherical mode in the northern hemisphere, with the frequency change characteristic of sea level pressure (SLP) in the North Atlantic sector. One of the reasons why NAO prediction is still challenging is that NAO is also proven to be influenced by other climate circulations, the most significant of which is the interaction between El Niño-Southern Oscillation (ENSO) and NAO. Therefore, sea surface temperature (SST) in the Pacific Ocean used to characterize ENSO is also one of the factors that contribute to the evolution of NAO and can be used as an input factor to predict the NAO. In this paper, the seasonal lag correlation between ENSO and NAO is explored and analyzed. The interaction has been considered in both short-term forecasting and midterm prediction of the NAO variability. The monthly NAO index (NAOI) fluctuation is predicted using the Niño indices based on the RF-Var model, and the accuracy achieves 68% when the lead time is about three months. In addition, integrating multiple physical variables directly related to the NAO and Pacific SST, the short-term NAO forecasting is conducted using a multi-channel neural network named AccNet with trajectory gated recursive unit (TrajGRU) layer. AccNet has the ability to identify the mechanism of the high-frequency variation in several days, and the NAO variability is indicated by SLP. The loss function of AccNet is set to anomaly correlation coefficient (ACC), which is the indicator that verifies spatial correlation in geoscience. Forecasting extreme events of NAO between 2010 and 2021, AccNet presents higher flexibility compared against other structures that can capture spatial-temporal features. [ABSTRACT FROM AUTHOR]

Ocean temperature monitoring is of great significance to marine fishing, aquaculture, and marine operations. Traditional electric sensors lack the potential to multiplex several sensors, and may suffer from electromagnetic interference. Meanwhile, fiber Bragg grating-based sensors have the advantages of high sensitivity, possibility for large-scale multiplexing, and immunity to electromagnetic interference. In this paper, we propose a Fabry–Pérot (FP) interferometer based on the draw tower grating array and combine it with the phase measurement method for demonstration and testing. In the sensor system, two adjacent fiber Bragg gratings (FBGs) are used as mirrors and an optical fiber connects them, forming a sensor unit. The signal was detected through the compensation of the optical path difference via two-arm path differences in an unbalanced interferometer. The sensor is calibrated in the range of 36.00–36.50 °C, and back to 36.00 °C, in steps of 0.10 °C. A thermocouple (DW1222) is used as a reference. Experimental testing demonstrates that under the thermal loop, the temperature and phase can be approximated as a linear relationship, the Pearson square correlation coefficient is 0.9996, and the temperature sensitivity is −9846 rad/°C. To prove that our experimental device can achieve a higher temperature resolution, we measured the background noise of the system. The experimental results indicate that the order of magnitude of our system temperature resolution can reach 10−5 °C. Thus, we believe that the sensor system is promising for the application of ocean temperature detection, and owing to the ultraweak reflection characteristics of the FBG, this method provides the possibility for large-scale multiplexing of the system. [ABSTRACT FROM AUTHOR]

The distribution of chlorophyll-a (Chl-a) in the Yangtze River Mouth area was analyzed using a new Chl-a inversion model (PMS-C) based on the relationship between in situ Chl-a and GF-4 PMS band combinations. Combining GF-4 PMS with HY-C CZI, this paper revealed that: (1) Chl-a concentration in Yangtze River Mouth was in the range of 2–6 µg/L, being higher in the west than in the east. The high Chl-a area was mainly distributed near the mouth of the Yangtze River and the Chl-a value was in the range of 3.7 µg/L to 5.9 µg/L. Chl-a concentration is higher in spring and summer than in autumn and winter, with a Chl-a concentration difference of 1–2 µg/L. Chl-a downstream of islands and bridges increased by 0.5–1.7 µg/L compared with upstream. (2) Short-term (within 3 h) changes of Chl-a concentration were effectively detected. In summer and autumn, Chl-a obtained at 13:30 in the noon was generally lower than Chl-a obtained at around 10:30 in the morning and it decreased by nearly 0.1–4 μg/L within three hours on the same day. In winter, the concentration of Chl-a decreased in the range of 0–1.9 μg/L. Generally, within three hours, Chl-a in the downstream of the island decreased significantly from 5 μg/L to about 3.8 μg/L, and Chl-a downstream of piers decreased from 3.7 μg/L to about 3 μg/L. (3) Environmental factors including seawater temperature, illumination, and nutrients, as well as dynamic factors such as wind and tidal current can induce Chl-a change in the Yangtze River Mouth. Short-term change of Chl-a concentration is closely related to the specific hydrodynamic conditions, nutrients, and lighting conditions. [ABSTRACT FROM AUTHOR]

Cooperative transmission is a promising solution for reliable communication in underwater acoustic sensor networks. To fully exploit the benefits of cooperative system, efficient management of relay resources is required. However, the challenging working conditions, including imprecise channel information, limited observation feedback and dynamic underwater environment, call for an adaptive relay selection strategy for improving system capacity performance. In this paper, we present an innovative Partial Expert-based Reinforcement Adversarial Learning (PER-AL) strategy that unifies expert assisted learning and self-adjusting learning in a integral adversarial multi-armed bandit framework. The user constantly interacts with the environment and optimizes the relay decision by analyzing all gathered observation rewards, rather than relying on prior channel information. By introducing a novel expert learning mechanism into the initial learning stage, expert generator and expert learner are proposed to control the performance of experts and provide optimal expert advice to reinforce the initial relay learning for efficiency. With the deepening learning, the relay quality is then evaluated by analyzing the historical observable rewards directly through a Exp3 policy without engaging complexity too much. The proposed algorithm could automatically adapt to the underwater conditions and detect the optimal relay within a short time, significantly improving system capacity without jeopardizing the adversarial regret guarantee. Finally, extensive simulation results demonstrated the superior of PER-AL algorithm compared with recent existing CSI-based and CSI-free solution benchmarks. Particularly, PER-AL algorithm has a 28.3% improvement of the total network capacity and achieves a 44.5% decrease of implementation time. [ABSTRACT FROM AUTHOR]

The investigation of the interrelationships among different oceanic and atmospheric circulation patterns is crucial for future climate projections in the current century. This paper presents the transition matrix approach of the stochastic Markov chain process to investigate the state/event based relationship between the new index of the Interdecadal Pacific Oscillation (IPO) named as the IPO Tripole index (TPI) and different sea surface temperature anomalies (SSTA) based El Nino-Southern Oscillation (ENSO) indices such as Niño 1.2, Niño 3, Niño 3.4, Niño 4 and the Multivariate ENSO Index (MEI) for the period of 120 years (1900–2019) respectively. Several Markovian descriptors like state dependency, temporal stationarity, expected number of state visits and entropy are derived from the estimated transition matrix. These descriptors are helpful in establishing the validity of Markov chain method and useful to characterize the dynamical properties of a time series like persistence, randomness and behaviour of cycles. Through the Markov chain analysis and by derived descriptors, this study finds similar self-communication (periodic) pattern between the transition states, resemblance in expected number of visits from one transition state to another, asymmetric and truncated cyclic nature of the data sequence and the existence of randomness in the transition states. Finally, a strong 2-dimensional correlation values endorses the existence of strong relations between selected indices datasets. This analysis approach may be helpful in understanding the role of the IPO and ENSO in modulating future climate variability and to formulate effective predictive models at the climatic state. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the teleconnection of large-scale climatic signals with river flow discharge in northern Iran. To this end, the Garmrud, Alishrud, and Babolrud rivers were selected: their monthly data set during the years 1993–2018 was received from the regional water company of the Mazandaran Province. Climate indices including the Southern Oscillation Index, extreme eastern tropical Pacific sea surface temperature (Niño 1 + 2), Global Mean Temperature Index, North Pacific pattern (NP), Pacific Decadal Oscillation, and North Atlantic Oscillation were investigated. The results of the cross-correlation, and the Spearman's test showed that there is a significant relationship at a 0.01 level between the indices and the river flow discharge. The most correlated indices were the NP and Niño 1 + 2. The NP index was inversely correlated and the Niño 1 + 2 was directly correlated with the rivers' flow variations, and the time lag of these two indices' maximum effectiveness was 2 months and 1 month, respectively. The adaptive neuro-fuzzy inference system and multilayer perceptron (MLP) models were used as the predictor models. The inputs were selected from the time lags of both river discharge and climatic indices. According to the normalized root mean square error (NRMSE) values (0.14–0.22), the predictions are evaluated as having moderate and appropriate qualities. The best performance of all models, R = 0.824 and RMSE = 0.350 CMS, was achieved for the MLP model. The results showed that consideration of the climatic indices as inputs may improve monthly flow predictability by an average of 24.1% (11.4–38.4% among the rivers and models). [ABSTRACT FROM AUTHOR]

In this paper, we first investigate the estimation of the functional single index regression model with missing responses at random for strong mixing time series data. More precisely, the uniform almost complete convergence rate and asymptotic normality of the estimator are obtained respectively under some general conditions. Then, some simulation studies are carried out to show the finite sample performances of the estimator. Finally, a real data analysis about the sea surface temperature is used to illustrate the effectiveness of our methodology. [ABSTRACT FROM AUTHOR]

To improve high-resolution numerical environmental prediction, it is essential to represent ocean–atmosphere interactions properly, which is not the case in current operational regional forecasting systems used in western Europe. The objective of this paper is to present a new forecast-oriented coupled ocean–atmosphere system. This system uses the state-of-the-art numerical models AROME (cy43t2) and NEMO (v3.6) with a horizontal resolution of 2.5 km. The OASIS coupler (OASIS3MCT-4.0), implemented in the SurfEX surface scheme and in NEMO, is used to perform the communications between models. A sensitivity study of this system is carried out using 7 d simulations from 12 to 19 October 2018, characterized by extreme weather events (storms and heavy precipitation) in the area of interest. Comparisons with in situ and L3 satellite observations show that the fully coupled simulation reproduces the spatial and temporal evolution of the sea surface temperature and 10 m wind speed quantitatively well. Sensitivity analysis of ocean–atmosphere coupling shows that the use of an interactive and high-resolution sea surface temperature (SST), in contrast to actual numerical weather prediction (NWP) where SST is constant, modifies the atmospheric circulation and the location of heavy precipitation. Simulated oceanic fields show a large sensitivity to coupling when compared to the operational ocean forecast. The comparison to two distinct forced ocean simulations highlights that this sensitivity is mainly controlled by the change in the atmospheric model used to drive NEMO (AROME vs. IFS operational forecast), and less by the interactive air–sea exchanges. In particular, the oceanic boundary layer depths can vary by more than 40 % locally, between the two ocean-only experiments. This impact is amplified by the interactive coupling and is attributed to positive feedback between sea surface cooling and evaporation. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel method to enhance the accuracy of a real-time ocean forecasting system. The proposed system consists of a real-time restoration system of satellite ocean temperature based on a deep generative inpainting network (GIN) and assimilation of satellite data with the initial fields of the numerical ocean model. The deep learning real-time ocean forecasting system is as fast as conventional forecasting systems, while also showing enhanced performance. Our results showed that the difference in temperature between in situ observation and actual forecasting results was improved by about 0.5 °C in daily average values in the open sea, which suggests that cutting back the temporal gaps between data assimilation and forecasting enhances the accuracy of the forecasting system in the open ocean. The proposed approach can provide more accurate forecasts with an efficient operation time. [ABSTRACT FROM AUTHOR]

Theory indicates that tropical cyclone (TC) intensity should respond to environmental temperature changes near the surface and in the TC outflow layer. While the sensitivity of TC intensity to sea surface temperature is well understood, less is known about the role of upper-level stratification. In this paper, we combine historical data analysis and idealised modelling to explore the extent to which historical low-level warming and upper-level stratification can explain observed trends in the TC intensity distribution. Observations and modelling agree that historical global environmental temperature changes coincide with higher lifetime maximum intensities. Observations suggest the response depends on the TC intensity itself. Hurricane-strength storms have intensified at twice the rate of weaker storms per unit surface and upper-tropospheric warming, and we find faster warming of low-level temperatures in hurricane environments than the tropical mean. Idealised simulations respond in the expected sense to various imposed changes in the near-surface temperature and upper-level stratification representing present-day and end-of-century thermal profiles and agree with TCs operating as heat engines. Removing upper-tropospheric warming or stratospheric cooling from end-of-century experiments results in much smaller changes in potential intensity or realised intensity than between present day and the end of the century. A larger proportional change in thermodynamic disequilibrium compared to thermodynamic efficiency in our simulations suggests that disequilibrium, not efficiency, is responsible for much of the intensity increase from present day to the end of the century. The limited change in efficiency is attributable to nearly constant outflow temperature in the simulated TCs among the experiments. Observed sensitivities are generally larger than modelled sensitivities, suggesting that observed TC intensity change responds to a combination of the temperature change and other environmental factors. [ABSTRACT FROM AUTHOR]

• First high-accuracy prediction of global SST at 0.25° spatial resolution and 2 time scales (daily and monthly) based on deep learning. • Fully consider the spatiotemporal correlations in historical time series by attention mechanism to improve prediction accuracy. • Superior to widely-adopted deep learning models (3D-CNN, ConvLSTM, and LSTM) and numerical model (HYCOM). • Applicable to climate change sensitive area. Sea Surface Temperature (SST) is an essential parameter of the ocean–atmosphere system, so accurately predicting the future SST is of great significance. To address the low prediction accuracy due to insufficient consideration of spatiotemporal correlations in existing machine learning models, this paper proposes an Effective Attention Model (EAM) to achieve daily global SST prediction (predicting the SST of the next 15 days using those of the past 15 days) and monthly global SST prediction (predicting the SST of the next 12 months using those of the past 12 months). The EAM adopts an attention mechanism to avoid information redundancy and improve prediction accuracy. This is the first work to realize high-accuracy global SST prediction with a high spatial resolution of 0.25° on two time scales (daily and monthly) based on deep learning. Experiments show that (1) the prediction results have a consistent global spatiotemporal distribution with the ground truth, with the Root Mean Squared Difference (RMSD) of daily prediction ranging from 0.212 to 0.932 ℃ and the RMSD of monthly prediction ranging from 0.666 to 0.782 ℃. The EAM is superior to the deep learning models (ConvLSTM, 3D-CNN, and LSTM) and the numerical model (HYCOM); (2) Besides global prediction, the EAM also achieves good performance in a climate change sensitive area (Niño 3.4 sea area), with the lowest RMSD of 0.231 ℃. This study may not only benefit the research on climate events (El Niño and La Niña) but also serve to predict other marine disasters (such as heat waves and storms). In the future, the proposed attention module can also be adapted to other prediction scenarios such as meteorology. [ABSTRACT FROM AUTHOR]

To improve the water production capacity of solar still (SS), realize the theoretical prediction of the enhanced SS performance, and enrich the theoretical research basis of the desalination technology of SS, this paper sets up three kinds of enhancement measures, namely, rock, corrugated plate and membrane distillation, tests the enhanced water production effect, and reveals the enhanced operation mechanism. At the same time, a performance prediction model of rock enhanced was established based on the body-centered cubic stacking rock technology, and the influence of rock parameters on the distillation effect was studied. The study found that the water production increment of the three enhancement measures was concentrated in the rising period of the water production of the SS, and the total water production was 6.38 %, 12.30 % and 11.63 % higher than that of the traditional basin SS, respectively. The rock or corrugated plate enhances the distillation effect by elevating the seawater temperature and its temperature difference with the cover plate, and the membrane distillation increases the total water production through the additional water production of the membrane. Moreover, the constructed model can effectively predict the characteristics of rock enhanced SS. The increase in the rock layer thickness and the decrease in the rock particle size and material heat capacity both enhance the total daily water production, but the effect of rock particle size and material is weak. Although the increase of thickness increases the water production obviously, it aggravates the fluctuation of water production. • The operation laws and the water yield of three enhanced solar stills were tested. • A prediction model based on the body-centered cubic rockfill technique was built. • The new model can effectively predict the performance of the rock-enhanced still. • Effect of rock layer thickness, grain size and material on water yield was studied. • Daily water yield was increased by 2.86 % after optimized configuration of parameters. [ABSTRACT FROM AUTHOR]

• Proposed a method utilizing an optical resonant cavity to measure seawater temperature and salinity, characterized by high resolution and stability. • Achieved precise measurement and feedback of the resonance frequency of the Fabry-Perot cavity through frequency-locking techniques. • Utilized the Fabry-Perot resonant cavity to enhance the resolution of ocean salinity measurements. The research on the ocean has entered a new stage: we are not only satisfied with understanding the surface of the ocean, but also eager to comprehend its deeper laws. This appeal requires sensors to be able to observe the physical parameters of the ocean (temperature, salinity, etc.) in a more precise manner, and the resolution of the sensor is one of the core factors. This paper presents a method for high-resolution measurements of ocean temperature and salinity. By using our carefully designed Fabry-Perot optical resonator, we have achieved a very high resolution. Through experiments, we have verified the resolution performance of the sensor across the full range. When the temperature is 40 °C, the highest temperature resolution is 1.15 × 10−4 °C, and when the salinity is 8.86 PSU, the highest salinity resolution is 1.49 × 10−4 PSU. [ABSTRACT FROM AUTHOR]

Physical model testing is a crucial step in the validation process of floating offshore wind concepts that can be used to contribute to the worldwide decarbonization objectives. It is also important to understand the coupled performance of all the sub-systems that conform to a floating wind concept: wind turbines, mooring systems or floating platform hydrodynamic responses. Few experimental tests had been conducted, and no real-time hybrid modelling had been performed in these tests. In this paper, an open-source experimental dataset is presented, and the dynamics of a concrete spar-based floating concept withstanding the IEA 15-MW Reference Wind Turbine are investigated. An experiment on a 1:55 scale concrete-based spar (WindCrete) at IHCantabria's ocean basin was developed by means of the hardware-in-the-loop technique under the COREWIND EU-H2020 project. The available data consist of the hydrodynamic characterizations and seakeeping tests with a total of 57 available datasets. The proper behaviour of the WindCrete platform and the designed mooring system is confirmed by the maximum motion values and accelerations below the established acceptance criteria defined. Moreover, this test program identifies the importance of the wind loads over the dynamic performance of the concept. • Floating offshore wind platform dynamics. • On the importance of coupled tests over FOWT performance analysis. • Real-time Hybrid modelling of FOWT. [ABSTRACT FROM AUTHOR]

There is an increasing need to provide real-time datasets for climate monitoring and applications. However, the current data products from all international groups have at least a month delay for data release. One reason for this delay is the long computing time of the global reconstruction algorithm (so-called mapping approach). To tackle this issue, this paper proposes a multi-level parallel computing model to improve the efficiency of data construction by parallelization of computation, reducing code branch prediction, optimizing data spatial locality, cache utilization, and other measures. This model has been applied to a mapping approach proposed by the Institute of Atmospheric Physics (IAP), one of the world's most widely used data products in the ocean and climate field. Compared with the traditional serial construction of MATLAB-based scheme on a single node, the speed of the construction after parallel optimizations is speeded up by ∼4.7 times. A large-scale parallel experiment of a long-term (∼1000 months) gridded dataset utilizing over 16,000 processor cores proves the model's scalability, improving ∼1200 times. In summary, this new model represents another example of the application of high-performance computing in oceanography and climatology. • A new practice of the application of high-performance computation in oceanography and climatology. • The multi-level parallel acceleration model proposed is applied in EnOI-DE, one of the most widely used mapping methods. • Gridded dataset' s construction efficiency improved ∼4.7× for a single month, and ∼1204.9× for the long time-series. [ABSTRACT FROM AUTHOR]

In a 2008 paper, using satellite-derived wind speed estimates from tropical cyclones over the 25-yr period 1981-2006, we showed the strongest tropical cyclones getting stronger. We related the increasing intensity to rising ocean temperatures consistent with theory. Oceans have continued to warm since that paper was published, so the intensity of the strongest cyclones should have continued upward as well. Here I show that this is the case, with increases in the upper-quantile intensities of global tropical cyclones amounting to between 3.5% and 4.5% in the period 2007-19 relative to the earlier base period (1981-2006). All basins individually show upward intensity trends for at least one upper quantile considered, with the North Atlantic and western North Pacific basins showing the steepest and most consistent trends across the quantiles. [ABSTRACT FROM AUTHOR]

Highlights • An analytical model is proposed to calculate the sea surface emissivity based on the measured data. • The error caused by various coupling factors which are difficult to measure are avoided in the paper. • A more realistic radiation model of sea surface is established. Abstract Sea surface infrared emissivity is an important parameter in oceanic remote sensing and it is difficult to measure directly. An analytical model is proposed to calculate the sea surface emissivity based on the infrared radiation theory. Emphasis is placed on the infrared radiative transfer equation deduced from the theoretical analysis of sea surface emissivity. The spectral emissivity, reflectivity, and atmospheric path radiance are then calculated based on an experimental measurement of the sea surface temperature, the spectral radiance of the sky, and the sea surface infrared images at different times. The infrared radiation model of sea surface established in this paper is verified by an example that shows self-consistency by putting the inferred emissivity into a radiative transfer model. The experimental results demonstrate that the sea surface emissivity can be expressed as ε = 0.6457 ± 0.0103 when the detection angle (θ) is 80.0° under a low wind speed. The self- radiation of the sea surface in the 3–5 μm region is ten times as large as the reflected radiation and approximately three to four times greater than the atmospheric path radiance. Comparisons between the calculated values of the Fresnel equations and the experimental results demonstrate the feasibility of the analytical model proposed in this paper. [ABSTRACT FROM AUTHOR]

An overflow of dense cold water from the Faroese Channels across the Wyville Thomson Ridge (WTR) into the Rockall Trough was recorded during the 136th cruise of the RRS James Cook in June 2016. This event happened in the eastern part of the ridge. The remotely operated vehicle ISIS deployed for a collection of coral samples recorded an abrupt drop in temperature at 500‐m depth. Specifically, the water temperature decreased from 8.73 to 6.74 °C and salinity from 35.26 to 35.16. This rapid drop happened over 20 min, with the fastest rate of water temperature decrease of 1.10 °C occurring just over 1 min 50 s. The numerical modeling conducted to reproduce the event has shown that a massive overflow took place in the WTR section, which is close to the Darwin Mounds. The overflow has led to resuspension of bottom sediments; the remotely operated vehicle sampling program in the area of the Darwin Mounds terminated due to low visibility. The numerical experiments have shown that tidally induced overflows over the WTR can occur periodically under spring tidal conditions. The model allowed us to identify two places in the eastern part of the WTR where the tidally driven overflows more realistically can happen. Plain Language Summary: The paper concerns deep water circulation in Northern Atlantic. A rare event of the Faroe‐Shetland Bottom Waters overflow through the Wyville Thomson Ridge to the Darwin Mounds was registered during the 136th cruise of the Royal Research Ship James Cook in June 2016. The overflow was observed in the eastern segment of the Wyville Thomson Ridge. The reason for a spillage of the cold bottom waters from the Faroese Channels over the Wyville Thomson Ridge to the Darwin Mound is discussed in the paper based on the observational data and the results of numerical modeling. The Massachusetts Institute of Technology general circulation model reproduced the baroclinic tidal processes developed in the area. Numerical experiments confirmed a high probability of overflows induced by cross‐channel tidal oscillations during spring tidal conditions. Key Points: Observational evidence of the Faroese Channels Bottom Water into the Darwin Mounds area is reportedThe observed overflow in the eastern part of the Wyville Thomson Ridge is replicated numericallySpring tidal currents across the Faroese Channels are responsible for the overflow [ABSTRACT FROM AUTHOR]

This paper discusses rating calculations of underground power cables when the temperature limit is imposed on a location other than the cable conductor. The issue becomes important for installations where the environmental conditions do not allow excessive heating. An example can be a requirement that the cable surface temperature is such that the drying out of the surrounding soil is avoided. Another example is a requirement imposed on submarine cable installations when the temperature rise caused by cable heating at the specified depth below the sea bottom does not exceed 2 K. Such requirements form rating restrictions in several countries; for example, the Netherlands, Germany, France, and others. This paper proposes new solutions to such problems including calculation of the dynamic ratings. [ABSTRACT FROM PUBLISHER]

This paper presents a summary of several seminal observational and numerical studies on climatology and possible change mechanisms of the outer-core wind structure of a tropical cyclone (TC). This has generally been referred to as size, a term also used in this review despite various definitions being given in the literature. In all the ocean basins where TCs exist, TC size has been found to vary with season, year, decade, latitude and longitude. Such variations are related to the synoptic flow patterns in which the TCs are embedded. Several factors have been identified as responsible for changes in TC size, including: environmental humidity, vortex structure, sea surface temperature and planetary vorticity. Each of these factors can modify the transport of lower tropospheric angular momentum into the TC and cause changes in its size. The paper ends with a discussion of outstanding issues in the study of the outer-core wind structure of a TC. [ABSTRACT FROM AUTHOR]

This paper describes the technical approach to generate homogeneous warm brightness temperature scene binary mask over the earth for the intercalibration of microwave imagers. The objective is to identify homogeneous desert scenes as targets in radiometric intercalibration of multisource multisensor systems such as Global Precipitation Measurement (GPM) constellation. In this paper, a method is developed to generate mask over continental Australia using 10, 18, and 37 GHz vertical and horizontal polarized radiance observations from GPM Microwave Imager data. Major factors considered are diurnal variation, second Stokes parameter, spatial homogeneity, and surface emissivity. Major advantage of this tool is its minimal, almost negligible, dependence on any external ancillary modeled or observed data. [ABSTRACT FROM AUTHOR]

This paper evaluates the calibration quality during the blackbody (BB) warm-up cool-down cycle for thermal emissive bands onboard Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS). This evaluation utilizes data from Aqua MODIS Collection 6 Level-1B products and VIIRS Sensor Data Records in 6-min granule format provided by the NASA Land Science Investigator-led Processing System. Nearly simultaneous hyperspectral measurements from the Aqua Atmospheric Infrared Sounder (AIRS) and the S-NPP Cross-track Infrared Sounder (CrIS) are used as references for MODIS and VIIRS, respectively. Each AIRS footprint of 13.5 km is co-located with multiple MODIS pixels while each CrIS field of view of 14 km is co-located with multiple VIIRS pixels. The corresponding AIRS-simulated MODIS and CrIS-simulated VIIRS radiances are derived by convolutions based on sensor-dependent relative spectral response functions. In this paper, the analysis mainly focuses on the bands that are used in sea surface temperature products. The results show that there is virtually no impact for MODIS bands 22 and 23 and bands 31 and 32 for a BB temperature below 290 K; however, when the BB temperature increases above 290 K, the impact is up to 0.3 K for bands 22 and 23 and 0.05 K for bands 31 and 32, respectively. For VIIRS, BB temperature-dependent drifts are observed in M15 and M16, which can reach 0.15 and 0.1 K, respectively, over the operational BB temperature range and the VIIRS brightness temperature range. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3%). Then, the land surface temperatures from the free-land experiments are used to perform a set of "AMIP-prescribed land" (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments. [ABSTRACT FROM AUTHOR]

The small ocean temperature difference causes the power generation efficiency to not be high while the power generation cost is high; this method has not been commercially applied. Therefore, it is particularly important to find a new thermal cycle to improve the cycle efficiency. In this paper, a new cycle of the ocean temperature difference using a non-azeotropic mixed as working fluid is proposed, and a secondary heat recovery device is added to the solution branch separated by the separator. Theoretical analysis and numerical calculation were used to analyze the relationships between cycle efficiency and working fluid concentration, turbine inlet pressure and cold seawater temperature were obtained. The results show that the maximum cycle efficiency can reach 5.25% by adding a secondary heat recovery device. A 10 kW OTEC experimental system was constructed and analyzed; the system performance was obtained. The efficiency of the experimental system was found to be as high as 3.8%, while the experimental value of the test system was lower than the theoretical calculation value. Finally, the heat transfer coefficients of an evaporator and condenser under these conditions were obtained, which provides basic data and technical support for the engineering application of an OTEC plant. [ABSTRACT FROM AUTHOR]

In this paper, a 1 kW-class Solar-Ocean Thermal Energy Conversion integrated Air-Conditioning (S-OTEC/AC) experimental system, which can provide both electrical energy and cooling energy without any pollution, is constructed for the first time. Based on the experimental data, the system's overall performance was comprehensively evaluated in terms of energy, exergy, economy, and environment (4 E). Furthermore, the performance difference between the system using solar energy (i.e., S-OTEC/AC) and the system without solar energy (i.e., OTEC/AC) was compared. The experimental results revealed that the maximum thermal efficiency of the S-OTEC/AC system could reach 2.10%, which was 1.91 times higher than the OTEC/AC system. For the OTEC/AC and S-OTEC/AC systems, the maximum cold energy utilization efficiency was 4.12% and 10.09%, and the maximum isentropic efficiency was 18.81% and 76.84%, respectively. The minimum payback period for the S-OTEC/AC system was 13.90 years, which was much lower than the 18.40 years of the OTEC/AC system. Additionally, the maximum primary energy saving achieved by the OTEC/AC system was 0.53 kW, while the S-OTEC/AC system reached a higher value of 1.56 kW. From the results, the superiority of the S-OTEC/AC system over the OTEC/AC system was confirmed. This work not only provides data references for the actual operating characteristics of the S-OTEC integrated system, but also provides a new technical way for comprehensive utilization of ocean temperature difference energy. • 1 kW class S-OTEC/AC experimental system was built for the first time. • The first 4 E analysis was used to characterize S-OTEC/AC with experimental data. • The S-OTEC/AC system has a thermal efficiency of up to 2.10%. • The S-OTEC/AC system achieves a cooling energy utilization of 10.09%. • The S-OTEC/AC system is superior to the OTEC/AC system in all aspects. [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]

Based on the observational and reanalysis datasets, a dipole pattern of the early summer (June) precipitation over the eastern Tibetan Plateau (TP) is identified through empirical orthogonal function. In contrast to previous researches, this paper introduces the May North Atlantic Oscillation (NAO) as a preceding signal and investigates its connection with subsequent early summer precipitation over the eastern TP during 1980–2019, focusing on predictive aspects. Results reveal that the correlation between NAO and primary eastern TP precipitation pattern (Precip_EOF1) has weakened since 2000. During 1980–2000, an equivalent barotropic Silk Road Pattern (SRP) observed across Eurasia triggers southerly wind anomalies over the TP. This, in turn, leads to the northward shift of the water vapor, which favors the ascending motion over the northern TP (NTP) due to water vapor convergence. Additionally, the SRP-related sensible heating also plays a critical role in vertical motion over the eastern TP by enhancing the TP thermal effect. Consequently, these factors contribute to shaping the dipole pattern of eastern TP precipitation. However, the weakened relationship between NAO and Precip_EOF1 during 2001–2019 is attributed to the absence of NAO-related atmospheric circulation over Eurasia. Further analysis suggests that these circulation anomalies arise from the interdecadal variability of the NAO and its phase shift. Moreover, when the influence of sea surface temperature anomalies over the northern North Atlantic is removed, the correlation of Precip_EOF1 with NAO and Atlantic Multidecadal Oscillation (AMO) both become insignificant. This suggests that the NAO-related dipole pattern of eastern TP precipitation is modulated by preceding northern North Atlantic sea surface temperature rather than AMO on the interdecadal timescale. • The relationship between North Atlantic Oscillation (NAO) and Tibetan Plateau (TP) precipitation has weakened since 2000. • The change in NAO-related Silk Road Pattern (SRP) is the dominant reason for the unstable correlation. • The interdecadal variability in TP precipitation is attributed to the NAO phase shift. • This relationship is modulated by northern North Atlantic sea surface temperature on the interdecadal scale. [ABSTRACT FROM AUTHOR]

This paper describes the oceanographic and environmental conditions in the Discovery Islands area of British Columbia that are relevant to inform assessments of the risks to wild salmon populations due to pathogen transfer from salmon farms located in the Discovery Islands. Consequently, this paper mainly focuses on the oceanographic and environmental conditions expected to affect the persistence and dispersal of pathogens in the marine environment. The sources of information used to describe the environmental and oceanographic conditions in the Discovery Islands area include data collected from monitoring and research programs carried out by federal and provincial governments, academic institutions, environmental nongovernmental agencies, and by Atlantic Salmon farming companies. The current state of knowledge and associated knowledge gaps for oceanographic conditions such as water temperature, water salinity, dissolved oxygen and water currents in the Discovery Islands are included. Solar radiation and ultraviolet light as well as biota and suspended solids in the region are also reviewed. The Finite Volume Community Ocean Model (FVCOM) has been applied in the Discovery Islands to simulate the hydrodynamics in areas of aquaculture activities. This paper includes main conclusions from simulations conducted for April and July 2010, comparisons of observations and modelling simulations and representativeness of conditions observed in April and July 2010. Results from the passive particle tracking model used to simulate the trajectories and dispersion of particles in the water column in the Discovery Islands are also included. [ABSTRACT FROM AUTHOR]

This paper describes a new model of the seawater dielectric constant as a function of salinity and temperature at L-band. The model function is developed by fitting the accurate measurement data made at 1.413 GHz to a third-order polynomial. The purpose of this study is to provide an accurate model for earth-observing satellites to retrieve seawater salinities from remote sensing data. In this paper, the development of the model function is introduced along with an analysis of the goodness of fit. The model function is then compared with the model functions of Klein-Swift and Meissner-Wentz. Finally, the comparison is made between the retrieved salinity from the satellite data with the in situ data measured by Argo floats. [ABSTRACT FROM PUBLISHER]

Expendable bathythermographs (XBT) to profile upper-ocean temperatures from vessels in motion have been in use for some 50 years now. Developed originally for navy use, they were soon adapted by oceanographers to map out upper-ocean thermal structure and its space-time variability from both research vessels and merchant marine vessels in regular traffic. These activities continue today. This paper describes a new technology--the Autonomous Expendable Instrument System (AXIS)--that has been developed to provide the capability to deploy XBT probes on a predefined schedule, or adaptively in response to specific events without the presence of an observer on board. AXIS is a completely self-contained system that can hold up to 12 expendable probes [XBTs, XCTDs, expendable sound velocimeter (XSV)] in any combination. A single-board Linux computer keeps track of what probes are available, takes commands from ashore via Iridium satellite on what deployment schedule to follow, and records and forwards the probe data immediately with a time stamp and the GPS position. This paper provides a brief overview of its operation, capabilities, and some examples of how it is improving coverage along two lines in the Atlantic. [ABSTRACT FROM AUTHOR]

This paper analyzes the large positive bias of sea surface temperature (SST) retrievals of selected remotely sensed algorithms recorded during the simultaneous occurrence of upwelling and atmospheric subsidence along the coastal waters of Rio de Janeiro, Brazil. The optimal estimator (OE) for retrieving SST and the multichannel (MCSST) and nonlinear (NLSST) estimators are compared using Advanced Very High Resolution Radiometer-3 data. The in situ SST (SSTbuoy) data set used to validate the remotely sensed SST retrievals was collected from five moored buoys (four in the open sea and one in coastal waters). The principal results of this paper are as follows. First, the sensitivity analyses show that OE is quite susceptible to the first-guess SST rather than to the humidity profiles. Second, the comparison between the SSTOE and 365 cloud-free SSTbuoy measurements in open sea waters presents an root mean squared error (RMSE), bias, and standard deviation (STD) with the intervals of [0.5, 0.6], [−0.51, 0.13], and [0.27, 0.48], respectively. Third, the MCSST, NLSST, and OE SST produce a positive bias that can reach 5 K during simultaneous upwelling and atmospheric subsidence in coastal waters. Such unexpected errors are due to low SST values and water vapor compression in the lower layer of the atmosphere related to a temperature inversion. Fourth, an alternative approach using SSTbuoy obtained on the previous day as a first guess instead of the climatological SST significantly improves the errors (SSTOE–SSTbuoy) by reducing RMSE, bias, and STD by 58% (from 3.30 to 1.39 K), 73% (from 3.00 to 0.80 K), and 19% (from 1.38 to 1.12 K), respectively. [ABSTRACT FROM PUBLISHER]

Recent rapid melting of the summer Greenland ice sheet (GrIS) and its impact on Earth's climate has attracted much attention. In this paper, we establish a connection between the melting of GrIS and the variability of summer sea surface temperature (SST) anomalies over the North Atlantic on interannual to interdecadal time scales through changes in subseasonal Greenland blocking (GB). It is found that the latitude and width of GB are important for the spatial patterns of the GrIS melting. The melting of the GrIS on interdecadal time scales is most prominent for the positive Atlantic multidecadal oscillation phase (AMO+) because the high-latitude GB and its large width, long lifetime, and slow decay are favored. However, the North Atlantic mid-high latitude warm–cold–warm (cold–warm–cold) tripole, referred to as the NAT+ (NAT−) pattern, on interannual time scales tends to strengthen (weaken) the role of AMO+ in the GrIS melting, especially on the northern or northeastern periphery of Greenland, by promoting (inhibiting) high-latitude GB and increasing (decreasing) its width. It is further revealed that AMO+ (NAT+) favors the persistence and width of GB mainly through producing weak summer zonal winds and a small summer meridional potential vorticity gradient (PVy) in the North Atlantic mid-high latitudes at 55°–70°N (55°–65°N) compared to the role of negative AMO (NAT−). The event frequency and zonal width of GB events and their poleward shift are favored by the combination of NAT+ with AMO+. In contrast, the combination of NAT− and AMO+ tends to suppress reduced summer zonal winds and PVy, thus inhibiting the event frequency of GB events and their poleward shift and zonal width. Significance Statement: Rapid melting of the summer Greenland ice sheet (GrIS) has been observed to frequently occur, especially after the year 2000, leading to a rise in sea level and other effects on Earth's climate. The physical cause of the rapid melting of the GrIS is an important area of research. We establish a connection between the summer melting of the GrIS and different sea surface temperature (SST) modes in the North Atlantic via changes in Greenland blocking. Although the positive Atlantic multidecadal oscillation (AMO+) phase favors the overall melting of GrIS, the phase of the North Atlantic tripole (NAT) SST pattern modulates the strength and location of the GrIS melting. The positive NAT phase (NAT+) with a warm–cold–warm tripole structure in the North Atlantic mid-high latitudes and AMO+ combine to result in a strong warm SST anomaly in the high latitudes of the North Atlantic north of 60°N, which promotes the melting of GrIS on the western, northern, and northeastern peripheries of Greenland via high-latitude Greenland blocking with an increased zonal width. The combination of the negative NAT phase (NAT−) with a cold–warm–cold tripole structure and AMO+ tends to suppress this effect. Thus, our results provide a new understanding of why the melting of GrIS shows a strong variability in strength and region. [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]

Sea surface temperature (SST) has important practical value in ocean related fields. Numerical prediction is a common method for forecasting SST at present. However, the forecast results produced by the numerical forecast models often deviate from the actual observation data, so it is necessary to correct the bias of the numerical forecast products. In this paper, an SST correction approach based on the Convolutional Long Short-Term Memory (ConvLSTM) network with multiple attention mechanisms is proposed, which considers the spatio-temporal relations in SST data. The proposed model is appropriate for correcting SST numerical forecast products by using satellite remote sensing data. The approach is tested in the region of the South China Sea and reduces the root mean squared error (RMSE) to 0.35 °C. Experimental results reveal that the proposed approach is significantly better than existing models, including traditional statistical methods, machine learning based methods, and deep learning methods. [ABSTRACT FROM AUTHOR]

The accumulated remote sensing data of altimeters and scatterometers have provided new opportunities for ocean state forecasting and have improved our knowledge of ocean–atmosphere exchanges. Studies on multivariate, multistep, spatiotemporal sequence forecasts of sea level anomalies (SLA) for different modalities, however, remain problematic. In this paper, we present a novel hybrid and multivariate deep neural network, named HMnet3, which can be used for SLA forecasting in the South China Sea (SCS). First, a spatiotemporal sequence forecasting network is trained by an improved convolutional long short-term memory (ConvLSTM) network using a channelwise attention mechanism and multivariate data from 1993 to 2015. Then a time series forecasting network is trained by an improved long short-term memory (LSTM) network, which is realized by ensemble empirical mode decomposition (EEMD). Finally, the two networks are combined by a successive correction method to produce SLA forecasts for lead times of up to 15 days, with a special focus on the open sea and coastal regions of the SCS. During the testing period of 2016–18, the performance of HMnet3 with sea surface temperature anomaly (SSTA), wind speed anomaly (SPDA), and SLA data is much better than those of state-of-the-art dynamic and statistical (ConvLSTM, persistence, and climatology) forecast models. Stricter testbeds for trial simulation experiments with real-time datasets are investigated, where the eddy classification metrics of HMnet3 are favorable for all properties, especially for those of small-scale eddies. [ABSTRACT FROM AUTHOR]

It is widely recognized that the initial ensemble describes the uncertainty of the variables and, thus, affects the performance of ensemble-based assimilation techniques, which is investigated in this paper with experiments using the Community Earth System Model (CESM) and the Data Assimilation Research Testbed (DART) assimilation software. Five perturbation strategies involving adding noises of different patterns and with/without extra integration are compared in the observation system simulation experiments framework, in which the SST is assimilated with the ensemble adjustment Kalman filter method. The comparison results show that for the observed variables (sea surface temperature), the differences in the initial ensemble lead to different rate of convergence in the assimilation, but all experiments reach convergence after three months. However, other variables (sea surface height and sea surface salinity) are more sensitive to the initial ensemble. The analysis of variance results reveal that the white-noise perturbation scheme has the largest RMSE. After excluding the effect of the white noise perturbation scheme, it can be found that the difference in the effect of different initial ensembles on the SSH with only assimilated SST is concentrated in the region of the Antarctic Circumpolar Current, which is related to the spread of the covariance between the SSH and the SST. [ABSTRACT FROM AUTHOR]

This paper presents the analysis of the frequency of lightning strikes associated with thunderstorm and precipitation distributions over smooth oceanic surface relative to that over solid earth surface in the tropical region. Long-term (1998–2014) data retrieved from the Lightning Imaging Sensors (LIS) of the Tropical Rainfall Measuring Mission (TRMM) satellite shows lightning flash counts over Indian landmass found to be 9.1 times more than those over the smooth oceanic surface of the Arabian Sea and the Bay of Bengal. On the other hand, the annual variation of rainfall-to-lightning ratio (RLR) is found to be 0.8 over Indian landmass, whereas it is 10 over the oceanic surfaces. We discuss the convective strength of thunderstorm distributions over land and oceanic regions by examining the relationships of RLR to the Bowen ratio, sea surface temperature (SST), and maximum air temperature over land, maximum updraft speed, and Aerosol Optical Depth (AOD) and cloud ice water content. The RLR shows high positive Pearson's correlations with the Bowen ratio, maximum updraft speed, AOD, and cloud ice water content over land region relative to those measured over the oceanic region. The RLR also shows negative correlations with SST, maximum updraft speed, AOD over the oceanic region. The results are applicable in understanding of the convective characteristics of thunderstorm distributions and lightning flashes over the tropical regions of the world. [ABSTRACT FROM AUTHOR]

In recent years, the East Asian (EA) region experienced escalated cost of damages associated with tropical cyclones (TC) during the mature boreal autumn (i.e., September−October). Questions arise whether such increased TC-associated cost of damages are indicative of increasing activity of TCs in EA, particularly during the mature boreal autumn. Here we show evidence of significantly increasing activity of TCs in EA from 1981 to 2019 that is mainly accompanied by an abrupt regime shift in TC passage frequency since 1998. Such trend and shift are robustly linked to the shift of the Pacific Decadal Oscillation (PDO) to its negative phase in the mid-1990s. Characterized by warm sea surface temperature anomalies in the subtropical North Pacific, a negative PDO phase is related to the weakening of the East Asian subtropical jetstream and the westward displacement of the WNP subtropical high, which initiates a favorable steering environment for increased TC passages into the EA region. Contrasting environmental patterns are associated in a positive PDO phase. Considering the prominence of EA in the global economy, our paper contributes additional insights on long-term tropical cyclone risk reduction and management in the region. [ABSTRACT FROM AUTHOR]