Sea Surface Research Articles

West African Monsoon System’s Responses to Global Ocean-Regional Atmosphere Coupling

Abstract This study explores the added value (AV) of a regional earth system model (ESM) compared to an atmosphere-only regional climate model (RCM) in simulating West African Monsoon (WAM) rainfall. The primary goals are to foster discussions on the suitability of coupled RCMs for WAM projections and deepen our understanding of ocean-atmosphere coupling’s influence on the WAM system. The study employs results from dynamical downscaling of the ERA-Interim reanalysis and Max Plank Institute ESM (MPI-ESM-LR) by two RCMs, REMO (atmosphere-only) and ROM (REMO coupled with Max Planck Institute Ocean Model; MPIOM), at ∼25-km horizontal resolution. Results show that in regions distant from coupling domain boundaries such as West Africa (WA), constraint conditions from ERA-Interim are more beneficial than coupling effects. REMO, reliant on oceanic sea surface temperatures (SSTs) from observations and influenced by ERA-Interim, is biased under coupling conditions, although coupling offers potential advantages in representing heat and mass fluxes. Contrastingly, as intended, coupling improves SSTs-monsoon fluxes’ relationships under ESM-forced conditions. In this latter case, coupling features a dipole-like spatial structure of AV, improving precipitation over the Guinean coast but degrading precipitation over half of the Sahel. Our extensive examination of physical processes and mechanisms underpinning the WAM system supports the plausibility of AV. Additionally, we found that the monsoonal dynamics over the ocean respond to convective activity, with the Sahara-Sahel surface temperature gradient serving as the maintenance mechanism. While further efforts are needed to enhance the coupled RCM, we advocate for its use in the context of WAM rainfall forecasts and projections.

Characterizing the internal wave wakes and synthetic aperture radar image features of underwater moving objects

In this study, a refined and improved theoretical model was proposed for calculating the synthetic aperture radar (SAR) images of internal wave wakes. This model was based on an equivalent source model of internal wave wakes and the velocity-bunching principle. Wake field, scattering field, and SAR image characteristics were systematically calculated for multiple scenarios. The model described the transfer and solution processes by inputting the background flow field temperature and salinity profiles to map the radar image intensity distribution. The physical mechanisms of the internal wave wake generation and its capture by SAR were comprehensively explained. The effects of various parameters on the internal wave wake SAR images were analyzed comprehensively. The SAR image features containing internal wave wakes were determined based on the gray-level co-occurrence matrix and image power spectrum, which revealed that the maximum surface current induced by the internal wave modes of the same amplitude was considerably larger than that induced by surface-wave mode. When traveling far from the water surface, the rate of change in the total scattering coefficient because of the Bragg effect was approximately 20 times that of the slope effect. In SAR images, the recognizability of wakes depends primarily on the maximum intensity rather than the average disturbance on the sea surface. Therefore, SAR images exhibit considerable differences during downwind radar observations, with the most prominent contrast differences occurring at the maximum spreading angle of wake scattering and 1500 m behind underwater objects. In the image power spectrum, the frequency range of the first modal internal waves was approximately 10–30 Hz, whereas the higher-order modal internal waves had frequencies lower than 10 Hz. Furthermore, the frequency range of the surface-wave mode was larger than that of internal-wave modes, approximately 50–60 Hz.

Skill assessment of seasonal forecasts of ocean variables

There is growing demand for seasonal forecast products for marine applications. The availability of consistent and sufficiently long observational records of ocean variables permits the assessment of the spatial distribution of the skill of ocean variables from seasonal forecasts. Here we use state-of-the-art temporal records of sea surface temperature (SST), sea surface height (SSH) and upper 300m ocean heat content (OHC) to quantify the distribution of skill, up to 2 seasons ahead, of two operational seasonal forecasting systems contributing to the seasonal multi-model of the Copernicus Climate Change Services (C3S). This study presents the spatial distribution of the skill of the seasonal forecast ensemble mean in terms of anomaly correlation and root mean square error and compares it to the persistence and climatological benchmarks. The comparative assessment of the skill among variables sheds light on sources/limits of predictability at seasonal time scales, as well as the nature of model errors. Beyond these standard verification metrics, we also evaluate the ability of the models to represent the observed long-term trends. Results show that long-term trends contribute to the skill of seasonal forecasts. Although the forecasts capture the long-term trends in general, some regional aspects remain challenging. Part of these errors can be attributed to specific aspects of the ocean initialization, but others, such as the overestimation of the warming in the Eastern Pacific are also influenced by model error. Skill gains can be obtained by improving the trend representation in future forecasting systems. In the meantime, a forecast calibration procedure that corrects the linear trends can produce substantial skill gains. The results show that calibrated seasonal forecasts beat both the climatological and persistence benchmark almost at every location for all initial dates and lead times. Results demonstrate the value of the seasonal forecasts for marine applications and highlight the importance of representing the decadal variability and trends in ocean heat content and sea level.

Hydrodynamics of an underwater vehicle near the sea surface

The primary goal of this study is to evaluate the hydrodynamic characteristics and the wave exciting forces on a shallowly submerged vehicle. A thin, rigid plate, which is completely submerged beneath the free surface in waters of finite depth is considered herein. The examined body is similar to an unmanned vehicle which is developed in Cyprus Marine and Maritime Institute for ocean science applications. From the present analysis the phenomenon of negative added mass and rapid variations of the added mass and damping coefficients is verified due to the free surface effect which is explained in terms of near-resonant standing waves above the submerged body.

A 300-year tree-ring δ18O-based precipitation reconstruction for the South American Altiplano highlights decadal hydroclimate teleconnections

Tropical South American climate is influenced by the South American Summer Monsoon and the El Niño Southern Oscillation. However, assessing natural hydroclimate variability in the region is hindered by the scarcity of long-term instrumental records. Here we present a tree-ring δ18O-based precipitation reconstruction for the South American Altiplano for 1700–2013 C.E., derived from Polylepis tarapacana tree rings. This record explains 56% of December–March instrumental precipitation variability in the Altiplano. The tree-ring δ18O chronology shows interannual (2–5 years) and decadal (~11 years) oscillations that are remarkably consistent with periodicities observed in Altiplano precipitation, central tropical Pacific sea surface temperatures, southern-tropical Andean ice core δ18O and tropical Pacific coral δ18O archives. These results demonstrate the value of annual-resolution tree-ring δ18O records to capture hydroclimate teleconnections and generate robust tropical climate reconstructions. This work contributes to a better understanding of global oxygen-isotope patterns, as well as atmospheric and oceanic processes across the tropics.

Evaluating of the accuracy of the DTU22MDT mean dynamic topography model based on the tidal gauge data in Vietnam’s coastal areas

In this study, the accuracy of the latest mean dynamic topography model (MDT), DTU22MDT, is determined based on data collected from 14 tide gauge stations along the coast of Vietnam, from the North to the South. The process of assessing the accuracy of the DTU22MDT model is carried out carefully and precisely, involving determining the model’s height at tide gauge stations, quality checks of the data, and evaluation of the model’s accuracy. The research results indicate that, compared to the local sea surface in Vietnam, the DTU22MDT model has a higher height of approximately 0.7 meters. This model represents the global MDT with the highest accuracy in Vietnam, with a mean square error of about 9.0 cm. This information provides a basis for applying the model in scientific research and practical applications, such as constructing a national height system, planning the economic development of coastal areas, generating specialized maps, designing structures, and other activities in the maritime regions of Vietnam. The method used to evaluate the accuracy of the MDT in this study can be applied to other research areas and to different MDTs.

SPATIAL-TEMPORAL DISTRIBUTION OF NARROW-BARRED SPANISH MACKEREL (Scomberomorus commerson) FISHING GROUNDS IN RIAU ARCHIPELAGO WATERS, INDONESIA

Narrow-barred Spanish mackerel (Scomberomorus commerson) is an exportable fish captured by gillnet fishing fleets from Bintan Regency. The fleets are operated in the Riau Archipelago waters but information on their activities is limited. Such information is important to the institution the Agency for Marine and Fisheries Affairs of Archipelagic Riau Province for ensuring the sustainability of the fisheries from both economic and biological perspectives. This study aims to determine the spatial-temporal distributions of the mackerel fishing grounds along the year with reference to the capture data, sea surface temperatures, chlorophyll-a concentrations, and salinities in the last 4 months of 2022. This study analyzed data from a fish export company, the PSDKP office at Tanjungpinang, Bintan, interviews of fishers affiliated with 44 fishing boat samples, and satellite-based marine data. Analysis on the monthly fishing productivity and optimum marine conditions for the mackerels were carried out to determine prospects of five recognized fishing grounds. Besides Lingga Islands, the fishing grounds are highly prospective from August to November. The longest fishing seasons are expected around Bangka Island (11 months). The spatial and temporal patterns show that the north-south-north shifts in fishing grounds that are associated with regional climates, i.e., monsoon winds.

Evolution of 3-D chlorophyll in the northwestern Pacific Ocean using a Gaussian-activation deep neural network model

Insufficient studies in characterizing vertical structure of Chlorophyll-a (Chl-a) in the ocean critically limit better understanding about marine ecosystem based on global climate change. In this study, we developed a Gaussian-activation deep neural network (Gaussian-DNN) model to assess vertical Chl-a structure in the upper ocean at high spatial resolution. Our Gaussian-DNN model used the input variables including satellite data of sea surface Chl-a and in-situ vertical physics profiles (temperature and salinity) in the northwestern Pacific Ocean (NWPO). After validation test based on two independent datasets of BGC-Argo and ship measurement, we applied the Gaussian-DNN model to reconstruct temporal evolution of 3-D Chl-a structure in the NWPO. Our modelling results successfully explain over 80% of the Chl-a vertical profiles in the NWPO at a horizontal resolution of 1° × 1° and 1 m vertical resolution within upper 300 meters during 2004 to 2022. Moreover, according to our modelling results, the Subsurface Chlorophyll Maxima (SCMs) and total Chl-a within 0-300 m depths were extracted and presented seasonal variability overlapping longer-time trends of spatial discrepancies all over the NWPO. In addition, our sensitivity testing suggested that sea-water temperatures predominantly control 3-D structures of the Chl-a in the tropical NWPO, while salinity played a key role in the temperate gyre of the NWPO. Here, our development of the Gaussian-DNN model may also be applied to craft long term, 3-D Chl-a products in the global ocean.

Analysis of the Multi-Dimensional Characteristics of City Weather Forecast Page Views and the Spatiotemporal Characteristics of Meteorological Disaster Warnings in China

In order to provide insights into how various page views are influenced by public engagement with weather information and to shed light on the patterns of warning issuance across different seasons and regions, this study analyzes the multi-dimensional characteristics of city weather forecast page views and the spatiotemporal characteristics of early warning information in China, from 1 March 2020 to 31 August 2023. This is achieved by utilizing the daily page views of city weather forecasts and meteorological warning data, comparing the public’s attention to weather during holidays versus regular days, assessing the public’s attention to weather under different meteorological warning levels, and performing statistical analysis of the spatiotemporal scale of meteorological disasters. Our analysis shows that compared to weekends and holidays, the public pays more attention to the weather on weekdays, and the difference between weekdays and national statutory holidays is more significant. Due to the widespread impact of heat waves, typhoons, severe convective weather, and geological disasters caused by heavy rainfall, public awareness and participation in flood season weather forecasting have significantly increased. Under red alerts, flash floods, typhoons, and geological risks are the primary concerns. Orange alerts predominantly feature flash floods, rainstorms, typhoons, snowstorms, and cold waves, while sandstorms attract the most attention during yellow alerts. Droughts, however, receive relatively less attention regardless of the warning level. Seasonal patterns in the issuance of meteorological warnings reveal a peak in summer, particularly with typhoons and rainstorms being the main concerns in July, followed by high temperatures and additional typhoon warnings in August. Heavy sea surface wind warnings exhibit a strong seasonal trend, with the majority issued during the winter months. Regionally, southern China experiences the highest frequency of severe convection weather warnings, with provinces such as Jiangxi, Guangxi, and Hunan being the most affected.

Role of the sea surface biofilm in regulating the Earth’s climate

Role of the sea surface biofilm in regulating the Earth’s climate

Revealing trends and persistent cycles of non-autonomous systems with autonomous operator-theoretic techniques

An important problem in modern applied science is to characterize the behavior of systems with complex internal dynamics subjected to external forcings. Many existing approaches rely on ensembles to generate information from the external forcings, making them unsuitable to study natural systems where only a single realization is observed. A prominent example is climate dynamics, where an objective identification of signals in the observational record attributable to natural variability and climate change is crucial for making climate projections for the coming decades. Here, we show that operator-theoretic techniques previously developed to identify slowly decorrelating observables of autonomous dynamical systems provide a powerful means for identifying nonlinear trends and persistent cycles of non-autonomous systems using data from a single trajectory of the system. We apply our framework to real-world examples from climate dynamics: Variability of sea surface temperature over the industrial era and the mid-Pleistocene transition of Quaternary glaciation cycles.

Distinct responses of tropical cyclone activity to spatio-uniform and nonuniform SST warming patterns

Most previous studies have reported a decrease in global tropical cyclone (TC) genesis frequency (TCGF) under anthropogenic warming. However, little attention has been drawn to the influence of sea surface temperature (SST) warming patterns on TCGF changes. Here, we investigate the impacts of three distinct SST warming patterns on global TCGF: uniform SST warming, nonuniform (El Niño-like) SST warming, and a combination of both. Results show that spatio-uniform SST warming has a limited impact on global TCGF, instead redistributing the TC genesis locations. Conversely, nonuniform SST warming significantly suppresses global TCGF. The combined warming produces a similar decrease in TCGF to nonuniform warming albeit with differences in spatial distribution. This indicates the dominant role of nonuniform SST warming in affecting TCGF and highlights the nonlinearity of the process. Further analysis shows that these differences in TCGF primarily stem from the distinct responses of tropical circulations to the three warming patterns.

Passive millimeter wave imaging low altitude detection technology

Passive millimeter wave imaging refers to the passive detection of naturally occurring background millimeter waves. After receiving external millimeter wave thermal radiation signals, the passive millimeter wave detection system will form images based on temperature differences and detect targets. Passive millimeter wave imaging has the advantages of non-radiation, non-contact, perspective imaging, good concealment, small size, and low power consumption. It is widely used in safety inspections, aircraft landing, low visibility navigation, sea surface detection and other fields. Driven by high and new technology, passive millimeter wave imaging low-altitude detection technology is rapidly developing. This paper introduced the basic principle of passive millimeter wave imaging, including the characteristics of millimeter wave radiation and Black-body radiation law, as well as its comparison with ordinary optical radiation. It also described the basic model of current passive millimeter wave imaging low altitude detection technology, explored the shortcomings of this technology and pointed out further work as well.

Interdecadal variations in the interannual relationship between winter tropical Pacific SST and subsequent summer Arctic sea ice in early 2000s

AbstractThe present study investigates the interdecadal change in the interannual relationship between winter sea surface temperature (SST) in the tropical central‐eastern Pacific and the subsequent summer Arctic sea ice concentration (SIC) and its possible mechanism using 1979–2023 monthly SST and SIC data from Hadley Center and atmospheric reanalysis data from NCEP/NCAR. It is found that the relationship between the winter tropical Pacific SST and the subsequent summer SIC of Beaufort Sea experienced an obvious interdecadal change from a significant negative correlation to a weak and insignificant correlation before and after the early 2000s, respectively. Before the early 2000s, when winter SST warming (cooling) anomalies occurred in the central and eastern tropical Pacific, it could sustain into summer and enhance a Rossby wave propagating from Tropic to high latitude, forming negative (positive) pressure anomalies in the North Pacific. Influenced by such anomalies, it is conducive to maintaining negative (positive) SST anomalies in the North Pacific from winter to subsequent summer. The summer SST cooling (warming) in the North Pacific could form a favourable atmospheric circulation anomaly for less (more) SIC. In contrast, after the early 21st century, the strong SST anomalies in winter over the eastern tropical Pacific would weaken with time and subsequently diminish in spring, leading to the SST anomalies in the North Pacific persist to spring, which can hardly affect summer SIC anomaly in the Beaufort Sea. Therefore, the relationship collapses after the the early 2000s due to the weakened persistence of the eastern tropical Pacific SST anomaly.

Improving the modeled variability estimates of offshore winds in Northern Europe by nudging ASCAT-derived winds

Abstract The paper aims to demonstrate how to enhance the accuracy of offshore wind resource estimation, specifically by incorporating near-surface satellite-derived wind observations into mesoscale models. We utilized the Weather Research and Forecasting (WRF) model and applied observational nudging by integrating ASCAT data over offshore areas to achieve this. We then evaluated the accuracy of the nudged WRF model simulations by comparing them with data from ocean oil platforms, tall masts, and a wind Lidar mounted on a commercial ferry crossing the southern Baltic Sea. Our findings indicate that including satellite-derived ASCAT wind speeds through nudging enhances the correlation and reduces the error of the mesoscale simulations across all validation platforms. Moreover, it consistently outperforms the control and previously published WRF-based wind atlases. Using satellite-derived winds directly in the model simulations also solves the issue of lifting near-surface winds to wind turbine heights, which has been challenging in estimating wind resources at such heights. The comparison of the one-year-long simulations with and without nudging reveals intriguing differences in the sign and magnitude between the Baltic and North Seas, which vary seasonally. The pattern highlights a distinct regional pattern attributed to regional dynamics, sea surface temperature, atmospheric stability, and the number of available ASCAT samples.

Variational Reconstruction and Simulation Experiments of Sea Surface Wind Field for Ocean Data Buoy

Variational Reconstruction and Simulation Experiments of Sea Surface Wind Field for Ocean Data Buoy

Evaluation of the characteristics of Indian summer monsoon simulated by CMIP6 models

AbstractThe present research is aimed at evaluating the climate coupled models with respect to the observational datasets for the investigation of the characteristics of the Indian summer monsoon (ISM). The monthly averaged historical simulations from 12 coupled climate models that participated in Coupled Model Intercomparison Project Phase 6 (CMIP6) are compared with the ground based observational data, satellite and reanalysis datasets for the study period of 1980–2014. This study uses these high‐resolution models to investigate monsoon features, onset and withdrawal dates, primarily focusing on individual model performances rather than highly documented multi‐model mean performance. Performance evaluation of the models suggests that sea surface temperature (SST) simulations by the models are in better agreement for the Arabian Sea than the Bay of Bengal with respect to the ERA5 reanalysis data sets. Further, inter‐model differences amongst the CMIP6 models in estimating the spatial distribution of various monsoon system variables during pre‐monsoon and monsoon seasons are noted which may be attributed to the different model components and varying physics configuration, nonetheless, models like NESM3 and INM‐CN5 are able to reproduce ISM pattern reasonably well. The annual precipitation cycle demonstrates a good agreement between most climate models and IMD data. Evolution of tropospheric temperature gradient (ΔTT) estimated from the CMIP6 models mimics the temporal pattern of the annual rainfall and therefore, is used to estimate the onset and withdrawal dates from CMIP6 models; however, high variability is noted amongst the CMIP6 models in retrieving the onset and withdrawal dates when compared with the IMD observations. Most of the models show a shorter rainy season except NorESM2‐MM. Overall our results suggest that the CMIP6 models can be used for the seasonal mean evaluation of monsoon system parameters and process‐based studies to improve our present understanding of the ISM system.

Why Does Extreme Precipitation Occur in Borneo During Both El Niño and La Niña Winters?

AbstractExtreme precipitation over the Maritime Continent (MC) is not only vital for local livelihoods, but also influences atmospheric circulation in tropical and extra‐tropical regions. The warm (cold) phase of El Niño‐Southern Oscillation usually leads to dry (wet) condition around the MC in boreal winter. This study unravels that extreme precipitation occurs in Borneo during both El Niño and La Niña winters. Extreme precipitation in Borneo is associated with tripole and dipole anomalous vertical motion pattern, respectively, over the MC‐tropical Pacific in El Niño and La Niña years. A parallel analysis reveals that weak precipitation in Borneo in El Niño and La Niña years occurs with dipole and tripole anomalous vertical motion pattern, respectively, over the MC‐tropical Pacific. The amplitude of the equatorial central‐eastern Pacific sea surface temperature (SST) anomalies may be a factor in the change of anomalous vertical motion pattern over the MC‐tropical Pacific. Further analysis identifies a tendency of extreme precipitation in late December to early−mid January and weak precipitation in February in Borneo. This suggests a critical role of seasonal change in the eastern equatorial Pacific SST in the occurrence of extreme precipitation in Borneo.

Experimental and numerical investigation of shelf flow crossing over a strait

AbstractMotivated by the phenomenon of Scotian Shelf Crossover events, the problem of a shelf flow that is interrupted by a strait is considered. Laboratory experiments in a rotating tank with barotropic and baroclinic flow over flat and sloping shelves confirm that the flow is steered by the bathymetric contours and mainly circumnavigates the gulf. In order to jump across the strait, as suggested by earlier theories, the flow must have unrealistically high Rossby numbers. However, the near bottom friction relaxes the bathymetric constraint and causes the formation of a peculiar jet crossing the strait diagonally. For the dissipation values such that a half of the transport goes around the gulf and half crosses the strait diagonally, the diagonal crossover jet becomes most evident. Numerical solutions for realistic values of the frictional parameter reproduce the results of the laboratory experiments and consideration of the actual Gulf of Maine bathymetry reproduces patterns similar to those observed by drift trajectories and in the satellite derived sea surface temperature fields.

Constrained Iterative Adaptive Algorithm for the Detection and Localization of RFI Sources Based on the SMAP L-Band Microwave Radiometer

The Soil Moisture Active Passive (SMAP) satellite carries an L-band microwave radiometer. This sensor can be used to observe global soil moisture (SM) and sea surface salinity (SSS) within the protected L-band spectrum (1400–1427 MHz). Owing to the complex effects of radio frequency interference (RFI), the SM and SSS data are missing or have low accuracy. In this paper, a constrained iterative adaptive algorithm for the detection, identification, and localization of RFI sources is designed, named MICA-BEID. The algorithm synthesizes antenna temperatures for the third and fourth Stokes parameters before RFI filtering, creating a new polarization parameter called WSPDA, designed to approximate the level of RFI interference on the L-band microwave radiometer. The algorithm then utilizes the WSPDA intensity and distribution density of RFI detection samples to enhance the identification and classification of RFI sources across various intensity levels. By utilizing statistical methods such as the probability density function (PDF) and the cumulative distribution function (CDF), the algorithm dynamically adjusts adaptive parameters, including the RFI detection threshold and the maximum effective radius of RFI sources. Through the application of multiple iterative clustering methods, the algorithm can adaptively detect and identify RFI sources at various satellite orbits and intensity levels. Through extensive comparative analysis with other localization results and known RFI sources, the MICA-BEID algorithm can achieve optimal localization accuracy of approximately 1.2 km. The localization of RFI sources provides important guidance for identifying and turning off illegal RFI sources. Moreover, the localization and long-time-series characteristic analysis of RFI sources that cannot be turned off is of significant value for simulating the spatial distribution characteristics of localized RFI source intensity in local areas.