Sea Surface Wind Speed Research Articles

Investigation of dynamic wind speed impacts on radiative transmittance and reflectance in the ocean-sea fog system

Frequent fog and dynamic wind speeds in the ocean significantly impact the radiation transmittance and reflectance on the sea surface, substantially challenging remote sensing and target detection in marine environments. Establishing a model to study the radiative transfer more accurately in ocean-sea fog systems under dynamic wind speed conditions is crucial. Here, a multichannel Monte Carlo (Mc-MC) model is introduced to investigate radiative transfer in ocean-fog systems, which is more realistic and has greater potential than the traditional MC (Tra-MC) approach. Addressing the challenges of dynamic wind speed, this paper introduces two specialized dynamic wind speed models. One prioritized the accurate simulation of changing sea surface wind speeds, and we investigated the transmittance and reflectance of six regions in the Pacific and Atlantic Oceans under this model. The other is proposed for investigating the effect of dynamic wind speed on radiative transfer. The experimental results indicate that an increase in the wind speed dynamic factor accelerates the rate of wind speed changes, thereby intensifying the instability of the radiative transfer transmittance and reflectance. In addition, the light around both the 1 µm and 2 µm wavelengths exhibit high transmittance, but the light surrounding 1 µm has relatively weaker stability compared to that surrounding 2 µm. These investigations provide valuable insights for infrared remote sensing, target detection, and the development of light sources suitable for marine applications.

Analysis of Diurnal Sea Surface Temperature Variability in the Tropical Indian Ocean

Based on the 30-year global hourly sea surface temperature (SST) dataset (MLSST) produced by the National Marine Environmental Forecasting Center, Ministry of Natural Resources of China, we analyzed the variability of diurnal sea surface temperature amplitude (DSST) of the tropical Indian Ocean at multiple time scales, as well as its influencing factors. The results show that the DSST in the Arabian Sea, Bay of Bengal, and equatorial Indian Ocean exhibits a bimodal seasonal variation with a semi-annual cycle, while the DSST in the southern Indian Ocean shows an annual cycle. The seasonal variation of DSST is mainly influenced by factors such as sea surface wind speed, shortwave solar radiation, and precipitation. The DSST in the equatorial Indian Ocean is generally higher during El Niño years compared to La Niña years. At the intraseasonal scale, the large standard deviation of DSST in boreal winter is mainly distributed in the southern hemisphere, while the large standard deviation of DSST in boreal summer shifts northward. The intraseasonal variation amplitude of DSST in boreal winter of the tropical Indian Ocean is greater than that in boreal summer. The DSST in the tropical Indian Ocean exhibits significant variation characteristics at multi-time scales. This study provides reference for numerical simulation of air-sea interaction patterns in the tropical Indian Ocean, as well as improvement of short-term climate prediction.

Effects of meteo-oceanographic conditions on the weathering processes of oil spills in northeastern Brazil

This paper presents the graphical results of the Lagrangian-model and the weathering processes associated with oil spills in the tropical South Atlantic, taking into account the meteorological and oceanographic conditions of the study region. The scenarios were created in the Brazilian-NE waters adjacent, with simulation times of 670 h, and densities of 35, 25, and 15API with volume of 1590 m3 were considered. The main results showed that the meteo-oceanographic characteristics of the study region influence the trajectories and weathering processes in the oil spill. The trajectories varied for each launch point and reached the continent severely in January and October. The associated weathering processes showed higher rates in September and lower rates in April, indicative of the influence of phenomena such as Intertropical Tropical Convergence Zone and warm pool in the South Atlantic region. Sea surface temperature and wind speed are key factors that correlate positively with these months.

Subseasonal Variation Characteristics of Low-Cloud Fraction in Southeastern and Northwestern North Pacific

The subseasonal variability of the low-cloud fraction (LCF) over the southeastern North Pacific (SENP) and northwestern North Pacific (NWNP) was studied using satellite observations and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis. It is found that subseasonal variability of the LCF was closely related to variations in the estimated inversion strength (EIS), sea surface wind speed (SSW), sensible heat flux (SHF), sea surface temperature (SST), surface temperature advection (Tadv), relative humidity (RH), surface level pressure (SLP) and surface air temperature (SAT). An increase in the LCF over the SENP is associated with the development of an anomalous anticyclonic circulation, which is located on the west coast of America. The cold advection, together with the subsidence warming associated with the anticyclonic circulation, strengthens the temperature inversion, favoring the development of the LCF. In the NWNP, the maximum LCF anomaly was also correlated with the stable boundary layer. The southerly wind blows airflow over the Kuroshio Extension from the subtropics, which brings warm and moist air. When air flows to the colder sea surface, it is cooled and condensed by the intensified heat exchange. A lead-lag composite analysis indicates that the mechanisms are different between the SENP and the NWNP, possibly due to the different types of low-level clouds over these two regions. In the SENP, the trade cumulus dominates under a strong capping inversion over the subtropics, whereas fog and stratus often occur under a shallow capping inversion in the NWNP. The effects of atmospheric circulation are also discussed.

First assessment of Noise-Equivalent Sigma-Zero in GF3-02 TOPSAR mode with sea surface wind speed retrieval

First assessment of Noise-Equivalent Sigma-Zero in GF3-02 TOPSAR mode with sea surface wind speed retrieval

Characterization of the Cultivable Microbiota Components of Marine Bioaerosols in the North Tropical Atlantic

Microorganisms are key to balancing marine ecosystems and have complex interactions at the ocean–atmosphere interface, affecting global climate and human health. This research investigated the diversity of cultivable bacteria and fungi in marine bioaerosols in the North Tropical Atlantic Ocean. Using the technique of spontaneous sedimentation in selective culture media, samples were collected during oceanographic expeditions. After isolation and purification, microbial strains were identified by phenotypic and genetic analyses. Fungi isolated included Acrophialophora, Aspergillus, Chrysosporium, Cladosporium, Fonsecaea, Mucor, Rhodotorula, Schizophyllum, Stemphylium, Candida, Curvularia, Cystobasidium, Exophiala, Neotestudina, Penicillium, Pestalotiopsis, and Preussia. The bacterial isolates belonged to the Bacillota, Pseudomonadota, Enterobacteriaceae family, Bacillus genus, and Serratia liquefaciens groups. About 40% of bacteria and 42% of fungi were identified as potential human pathogens, suggesting a relationship between human actions and the microbiota present in bioaerosols on the high seas. Sea surface temperature (SST) and wind speed influenced microorganisms. More studies and analyses in different scenarios should be conducted considering environmental and climate variables in order to deepen knowledge and generate information on the subject, so that standards can be established, and quality parameters determined.

Digitizing weather observations from World War II US naval ship logbooks

AbstractThe number and coverage of weather observations over the oceans were considerably reduced during World War II (WW2) due to disruptions to normal trade routes. The observations that do exist for this period are often unavailable to science as they are still only available as paper records or scanned images. We have rescued the detailed hourly weather observations contained in more than 28,000 logbook images of the US Navy Pacific Fleet stationed at Hawai'i during 1941–1945 to produce a dataset of more than 630,000 records. Each record contains the date and time, positional information and several meteorological measurements, totalling more than 3 million individual observations. The data rescue process consisted of a citizen science project asking volunteers to transcribe the observations from the available images, followed by additional quality control processes. This dataset not only contains hourly weather observations of air temperature, sea surface temperature, atmospheric pressure, wind speed and wind direction, mainly in the Pacific Ocean but also includes some observations from the Atlantic and Indian Oceans. The new observations are found to be of good quality by inter‐comparing independent measurements taken on ships travelling in convoy and by comparing with the 20th‐Century Reanalysis. This dataset provides invaluable instrumental weather observations at times and places during WW2, which fill gaps in existing reconstructions.

Can we measure sea surface wind speed with a smartphone?

Can we measure sea surface wind speed with a smartphone?

Monitoring System for Sea Surface Temperature and Wind Speed in FADs Based on the Internet of Things

Sea Surface Temperature (SST) is the temperature of the water measured at sea level. SST is a crucial marine parameter that influences the weather and climate in Indonesia. The value of sea surface temperature will be very closely related to factors such as the depth of measurement from sea level, the intensity of sunlight received, season, weather, water depth, air circulation, and cloud cover. This study aims to design a prototype tool to measure wind speed and sea surface temperature parameters. The components used are the DS18B20 sensor, JL-FS2 sensor, Arduino Mega 2560, and the SIM900a GSM Module. The system is displayed in real-time via the Thingspeak website, accessed via a PC or smartphone. The DS18B20 sensor, as a sea surface temperature sensor, can measure these parameters by looking at the trend of changing day and night temperatures. The JL-FS2, as a wind speed sensor, has been able to measure wind speed parameters during field tests at FADs.

Evaluation of HY-2C and CFOSAT Satellite Retrieval Offshore Wind Energy Using Weather Research and Forecasting (WRF) Simulations

This study simulated the spatial distribution of wind speeds and wind energy density by using the WRF model, and we used the WRF-simulated results to evaluate the sea surface wind speeds retrieved from the HY-2C and CFOSAT satellite-borne microwave scatterometers over the Yellow Sea region. The main conclusions were as follows: (1) The combination of the MRF boundary layer parameterization scheme, the MM5 near-surface parameterization scheme, and the Global Data Assimilation System (GDAS) initial field demonstrated the best performance in simulating the 10 m wind speed in the Yellow Sea region, with a root-mean-square error (RMSE) of 1.57, bias of 1.24 m/s, and mean absolute percentage error (MAPE) of 17%. (2) The MAPE of the HY-2C inversion data was 9%, while the CFOSAT inversion data had an MAPE of 6%. The sea surface wind speeds derived from the HY-2C and CFOSAT satellite scatterometer inversions demonstrated high accuracy and applicability in this region. (3) The wind speed was found to increase with altitude over the Yellow Sea, with higher wind speeds observed in the southern region compared to the northern region. The wind power density increased with altitude, and the wind power density in the southern area of the Yellow Sea was higher than in the northern region. (4) The CFOSAT satellite inversion products were in good agreement with the WRF simulation results under low wind speed conditions. In contrast, the HY-2C satellite inversion products showed better agreement under moderate wind speed conditions. Under high wind speed conditions, both satellite inversion products exhibited minor deviations, but the HY-2C product had an overall overestimation, while the CFOSAT product remained within the range of −1 to 1 m/s. (6) The wind power density increased with the satellite-inverted 10 m wind speed. When the 10 m wind speed was less than 9 m/s, the wind power density exhibited a roughly cubic trend of increase. However, when the 10 m wind speed exceeded 9 m/s, the wind power density no longer increased with the rise in 10 m wind speed. These findings provide valuable insights into wind energy resources in the Yellow Sea region and demonstrate the effectiveness of satellite scatterometer inversions for wind speed estimation. The results have implications for renewable energy planning and management in the area.

Comprehensive study of algal blooms variation in Jiaozhou Bay based on google earth engine and deep learning

The Jiaozhou Bay ecosystem, a crucial marine ecosystem in China, has been plagued by frequent harmful algal blooms as due to deteriorating water quality and eutrophication. This study analyzed the temporal and spatial changes of harmful algal blooms in Jiaozhou Bay from 2000 to 2022 using the Floating Algae Index (FAI) calculated from MODIS (2000–2022) and Sentinel-2 (2015–2022) satellite image datasets. The calculation results of the image datasets were compared. The frequency of planktonic algal outbreaks was low and constant until 2017, but has increased annually since then. Algae blooms are most common in the summer and primarily concentrated along the bay’s coast, middle, and mouth, with obvious seasonal and spatial distribution characteristics. Several factors influencing algal outbreaks were identified, including sea surface temperature, wind speed, air pressure, dissolved oxygen, nitrogen and phosphorus ratios, chemical oxygen demand, and petroleum pollutants. Algal bloom outbreaks in Jiaozhou Bay are expected to remain high in 2023. The findings provide crucial information for water quality management and future algal outbreak prediction and prevention in Jiaozhou Bay.

Exploring spatial patterns and environmental risk factors for global maritime accidents: A 20-year analysis

The global shipping industry faces increasingly complex safety challenges due to the rapid growth of international maritime trade. This study develops a novel framework that combines spatial density analysis and machine learning (i.e., extreme gradient boosting model) to investigate the evolutionary patterns of global maritime accidents during 2001–2020 from both spatial and temporal dimensions, and then identifies key environmental risk factors affecting maritime safety. The results show that the number of global maritime accidents exhibits fluctuations between 2001 and 2019, with a significant decrease observed in 2020. Furthermore, the distribution of global maritime accidents shows significant spatial variation over different time periods. Denmark's sea areas have high accident rates between 2001 and 2005, while concentrated accidents are observed in the seas around the United Kingdom, Denmark, and China between 2006 and 2010. From 2011 to 2015, Europe's accident-prone areas increase, but fewer accidents are reported along China's east coast. The Strait of Malacca is also an accident-prone area from 2016 to 2020. In addition, wave height, sea surface temperature, wind speed, water depth, and precipitation are identified as key environmental risk factors affecting maritime safety. These findings can inform strategies and mitigation plans to improve navigational safety in the global shipping industry.

ВОССТАНОВЛЕНИЕ СКОРОСТИ ПРИВОДНОГО ВЕТРА ПО ДАННЫМ МТВЗА-ГЯ

A neural network (NN) algorithm for the sea surface wind speed retrieval from the MTVZA-GYa Russian satellite microwave radiometer measurements is presented. The algorithm is based on the physical modeling of the brightness temperature of microwave radiation in the ocean-atmosphere system using new theoretical geophysical model functions of the dependence of ocean radiation on wind speed. The algorithm is validated by comparing the wind fields retrieved from the MTVZA-GYa data with those obtained from the AMSR2 radiometer (Japan) for different areas of the World Ocean with a difference in measurement time not exceeding five minutes. The validation has shown that the NNs with a number of neurons n from 3 to 8 provide the smallest root-mean-square difference between the AMSR2 and MTVZA-GYa retrieved wind speeds, namely 1.6 m/s. When mapping the wind speed in tropical cyclones, the best fit to the wind fields from the AMSR2 data is obtained using the NN with n = 4.

Relationship between subsurface diurnal warming and wind speed

Observations and numerical simulations show an inverse relationship between sea surface diurnal warming and wind speed. However, the dependence of subsurface diurnal warming on wind speed remains largely unexplored. Here, we investigate the relationship between subsurface diurnal warming and wind speed using field observations, numerical simulations, and theoretical analysis. With increasing wind speed, subsurface diurnal warming decreases at the shallower depths where the daily maximum temperature occurs in the afternoon, while it first increases and then decreases at the deeper depths where the daily maximum temperature moves from afternoon to night, reaching a maximum when the daily maximum temperature occurs at about 18:00 local time (sunset). The relationship is mainly governed by the time-accumulated ocean heat gain from the air-sea heat flux (the difference between time-accumulated shortwave absorption and time-accumulated surface heat loss), which represents the downward heat transfer. Increasing wind speed increases surface heat loss and decreases the timing of the daily maximum temperature (t2h). For the shallower depths, both the decreased t2h and the increased surface heat loss reduce the accumulated ocean heat gain from the air-sea heat flux, i.e., the downward heat transfer, and thus reduce subsurface diurnal warming. For the deeper depths, the decreased t2h with increasing wind speed initially reduces the accumulated surface heat loss (the accumulated shortwave absorption almost the same) when t2h is during the night, causing the increase in subsurface diurnal warming, and subsequently reduces the accumulated net ocean heat gain along with the increased surface heat loss when t2h is during the afternoon, leading to the decrease in subsurface diurnal warming. This study extends our understanding of the dependence of diurnal warming on wind speed.

Landscape and Marine Environmental Factors Jointly Regulate the Intertidal Species Richness and Community Structure in the Islands of South Korea

Most studies on island biogeography have focused on the terrestrial taxa; however, there are few studies on the drivers of diversity and community structure of intertidal organisms on islands. We evaluated the effect of landscape and marine environmental factors on the species richness (SR), functional diversity (FD), and community structure (SES.MFD) of intertidal invertebrates among the overall, inhabited, and uninhabited islands. Using the data on the intertidal organisms from 78 islands in South Korea, we implemented variable selection and piecewise structural equation modeling to determine the causal relationships between the SR, FD, and SES.MFD with four landscapes (i.e., island area, coastline length, distance from the mainland, and structural connectivity) and three marine environment factors (i.e., mean annual sea surface temperature variation, wind speed, and evapotranspiration). The coastline length had a positive effect on the SR and SES.MFD in the overall islands including inhabited and uninhabited islands. The SR and FD were negatively affected by the variation in sea surface temperature. The relative importance of the landscape and marine environmental factors differed between the inhabited and uninhabited islands. That is, the inhabited islands were mainly affected by the coastline length, whereas uninhabited islands were regulated by marine environmental factors. Our results demonstrated that the biotic factors of the island intertidal ecosystems are controlled by the interactions between the biotic and various environmental factors. Moreover, the results emphasize that the water stress on the intertidal organisms due to climate change may lead to a loss of biodiversity and functional clustering.

Joint Retrieval of Sea Surface Rainfall Intensity, Wind Speed, and Wave Height Based on Spaceborne GNSS-R: A Case Study of the Oceans near China

In this paper, a method for joint sea surface rainfall intensity (RI), wind speed, and wave height retrieval based on spaceborne global navigation satellite system reflectometry (GNSS-R) data is proposed, which especially considers the effects between these two parameters. A method of rainfall detection (RD) according to different wind speed ranges is also proposed by mitigating the impact of swell and wind speed. The results, with data collected over the oceans near Southeast Asia, show that the RD method has a detection accuracy of up to 81.74%. The RI retrieval accuracy can reach about 2 mm/h by simultaneously correcting the effects of wind speed and swell. The accuracy of wind speed retrieval is improved by about 5% after removing rainfall interference through RD in advance. After considering the influence of wind speed and eliminating rainfall interference, the retrieval accuracy of significant wave height (SWH) is improved by about 18%. Finally, the deep convolutional neural network (DCNN) model is built to estimate the SWH of the swell. The results show that the retrieval accuracy of the swell height is better than 0.20 m after excluding rainfall interference. The proposed joint retrieval method provides an important reference for the future acquisition of multiple high-precision marine geophysical parameters by spaceborne GNSS-R technology.

Techno-economic assessment of offshore wind energy potential at selected sites in the Gulf of Guinea

Offshore wind power has been found to stand out among the most dynamic renewable energy technologies. With its long coastal line, Nigeria has an overwhelming advantage in developing marine energy resources to relieve the power crisis effectively. This work analyzed and characterized observation data of sea-surface wind speed and direction at 30-minute intervals between 1979 and 2015 at five synoptic offshore stations in the Gulf of Guinea. The seasonal variations in hourly surface wind speed and directions as well as the Weibull distribution of wind speed and wind power at 100 m hub height were examined. The wind shears, capacity factors, and accumulated energy outputs for seven offshore wind turbine types were determined for the selected locations. In addition, the economic analysis of the selected offshore turbines using levelized cost of energy was carried out, while sensitivity analysis of the total levelized cost of energy to key input parameters was further determined. The results revealed large spatial and temporal variations in wind speed and wind power in the Gulf of Guinea. The most viable offshore site for wind energy exploitation was Agbami (the deepest offshore site), while Bonny (the shallow coastal site) had the least. The findings established very good fits (having mean bias (between −0.08 ms−1 and −2.44 ms−1), percentage bias (between −0.47% and −13.98%), correlation coefficients (between 0.97 and 0.98), Chi-square (between 0.2 and 1.2), and root mean square error (between 1.2 ms−1 and 3.1 ms−1)) between Weibull distribution and the actual wind data. The wind turbines with the highest and the lowest wind power densities, capacity factors, and power outputs across the seasons and sites were V236-15.0 MW and Siemens SWT113, respectively. The levelized cost of energy was considered for the deep waters due to the moderately high-capacity factors. The highest values ranged between 101.48 and 137.12 USD/MWh at Sea Eagle with V236-15 MW and V117-4.2 MW, respectively, while the lowest ranged from 52.29 to 69.66 USD/MWh at Agbami with V236-15 MW and Siemens (SWT113), respectively. The exploitation of Nigeria’s offshore wind resources could also be dedicated to producing renewable hydrogen and can serve to meet the country’s ambitious targets set for carbon neutrality by 2060.

Correction of WindSat sea surface wind speed under rain

To improve the accuracy of sea surface wind speed under rain based on data obtained from the U.S. spaceborne fully polarimetric microwave radiometer (WindSat), a wind speed correction model based on a statistical algorithm is constructed. First, the coupled samples from 2003 to 2014 are considered as the training sample set, and the coupled samples from 2015 to 2020 are used as the test sample set. Then, the WindSat sea surface wind speed under rain correction model is constructed. Results show that the WindSat wind speed data is overestimated severely. The higher the wind speed, the larger the wind speed is overestimated. The experimental results reveal that the WindSat wind speed standard deviation of the test samples is 2.6 m/s. However, the wind speed standard deviation decreases to 2.2 m/s after correction.

Physics-statistics-based hybrid simulation scheme of coupled nonstationary hurricane wind and wave fields for long-span floating bridges

Abstract Long-span bridges with floating towers have recently drawn great attention from the engineering community. Due to their sensitivity to the aerodynamic and hydrodynamic loads during extreme storms, accurate and efficient simulation tools for hurricane winds and waves are needed for improved understanding of the complex dynamics of the fully coupled wind–wave–structure interaction system. Conventional simulation schemes usually generate winds and waves separately, and hence cannot capture the intense wind–wave interactions under hurricanes. In this study, a physics-statistics-based hybrid simulation scheme of nonstationary hurricane wind and wave fields is presented, where the winds and waves are coupled in both large and small scales. To simulate the large-scale winds and waves, a height-resolving hurricane wind model is coupled with a parametric hurricane wave model through a dependence between sea surface roughness and surface wind speed. In the small-scale simulations, the nonstationary wind fluctuations are statistically obtained by a Hilbert-wavelet-based scheme in which the target parameters (e.g. fluctuation intensity) are estimated based on the local sea state, while the nonstationary sea surface elevations are physically acquired by solving the governing equation of the nonlinear wave evolution under the action of winds. The simulation fidelity of the proposed physics-statistics-based hybrid scheme is demonstrated by generating the coupled nonstationary wind and wave fields approaching to a hypothetical long-span bridge with floating towers under a hurricane event.

The monthly average distributions of sea-surface wind speeds and directions in the East Vietnam Sea

This paper analyzes a monthly global gridded sea-surface wind dataset from Jan 1991 to Dec 2020, sourced from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS). The goal is to construct schematic maps depicting the monthly average distributions of sea-surface wind speeds and directions in the East Vietnam Sea. These maps provide a visual representation of the monsoon patterns at different points and areas in the region. The statistical and analytical findings reveal that the East Vietnam Sea is primarily influenced by two types of monsoons: Northeast and Southwest. When one is strong, the other is weak, and vice versa. The Northeast monsoon dominates from September to April of the following year, while the Southwest monsoon is more dominant from May to August. The intensity of the Northeast monsoon is usually greater than that of the Southwest monsoon. These results provide an overview of the monsoon distributions in the East Vietnam Sea, which can assist scientists and managers in proposing policies and measures suitable to the climate environment and wind seasons. These findings also help in the effective exploitation of abundant wind energy resources in coastal Vietnam and the East Vietnam Sea. Furthermore, the results are consistent with previous studies of monsoons in the East Vietnam Sea, indicating that the data source used in this study is reliable and can be utilized as input data for tidal, currents, or oil spread models.