The recent development of inexpensive, compact hyperspectral transmissometers broadens the research capabilities of oceanographic applications. These developments have been achieved by incorporating technologies such as micro-spectrometers as detectors as well as light emitting diodes (LEDs) as light sources. In this study, we evaluate the performance of the new commercial LED-based hyperspectral transmissometer VIPER (TriOS GmbH, Rastede, Germany), which combines different LEDs to emulate the visible light spectrum, aiming at the determination of attenuation coefficients in coastal environments. For this purpose, experimental uncertainties related to the instrument stability, the effect of ambient light and derived temperature, and salinity correction factors are analyzed. Our results identify some issues related to the thermal management of the LEDs and the contamination of ambient light. Furthermore, the performance of VIPER is validated against other transmissometers through simultaneous field measurements. It is demonstrated that VIPER provides a compact and cost-effective alternative for beam attenuation measurements in coastal waters, but it requires the consideration of several optimizations.

Coastal zones are increasingly threatened by extreme sea level events, with storm surges being among the most hazardous components, especially in regions prone to tropical cyclones. This study aims to explore the factors influencing the performance of numerical models in simulating storm surges in the tropical Atlantic region. The maxima, durations, and time evolutions of extreme storm surge events are evaluated for four historical hurricanes against tide gauge records. The Advanced Circulation (ADCIRC) and Nucleus for European Modelling of the Ocean (NEMO) ocean models are compared using similar configurations in terms of domain, bathymetry, and spatial resolution. These models are then used to perform sensitivity experiments on oceanic and atmospheric forcings, physical parameterizations of wind stress, and baroclinic/barotropic modes. NEMO and ADCIRC demonstrate similar abilities in simulating storm surges induced by hurricanes. Storm surges simulated with ERA5 atmospheric reanalysis forcing are generally more accurate than those simulated with parametric wind models for the simulated hurricanes. The inclusion of baroclinic processes improves storm surge amplitudes at some coastal locations, such as along the southeastern Florida peninsula (USA). However, experiments exploring different implementations of wind stress and interactions among storm surges, tides, and mean sea level have shown minimal impacts on hurricane-induced storm surges.

The detection and prediction of changes in coastal ecosystems require a better understanding of the complex physical, chemical and biological interactions, which involves that observations should be performed continuously. For this reason, there is an increasing demand for small, simple and cost-effective in situ sensors to analyze complex coastal waters at a broad range of scales. In this context, this study seeks to explore the potential of beam attenuation spectra, c(λ), measured in situ with an advanced-technology optical transmissometer, for assessing temporal and spatial patterns in the complex estuarine waters of Alfacs Bay (NW Mediterranean) as a test site. In particular, the information contained in the spectral beam attenuation coefficient was assessed and linked with different biogeochemical variables. The attenuation at λ = 710 nm was used as a proxy for particle concentration, TSM, whereas a novel parameter was adopted as an optical indicator for chlorophyll a (Chl-a) concentration, based on the local maximum of c(λ) observed at the long-wavelength side of the red band Chl-a absorption peak. In addition, since coloured dissolved organic matter (CDOM) has an important influence on the beam attenuation spectral shape and complementary measurements of particle size distribution were available, the beam attenuation spectral slope was used to analyze the CDOM content. Results were successfully compared with optical and biogeochemical variables from laboratory analysis of collocated water samples, and statistically significant correlations were found between the attenuation proxies and the biogeochemical variables TSM, Chl-a and CDOM. This outcome depicted the potential of high-frequency beam attenuation measurements as a simple, continuous and cost-effective approach for rapid detection of changes and patterns in biogeochemical properties in complex coastal environments.

A deconvolution approach is presented to use spectral light absorption and attenuation data to estimate the concentration of the major nonwater compounds in complex shelf sea waters. The inversion procedure requires knowledge of local material‐specific inherent optical properties (SIOPs) which are determined from natural samples using a bio‐optical model that differentiates between Case I and Case II waters and uses least squares linear regression analysis to provide optimal SIOP values. A synthetic data set is used to demonstrate that the approach is fundamentally consistent and to test the sensitivity to injection of controlled levels of artificial noise into the input data. Self‐consistency of the approach is further demonstrated by application to field data collected in the Ligurian Sea, with chlorophyll (Chl), the nonbiogenic component of total suspended solids (TSS_nd), and colored dissolved organic material (CDOM) retrieved with RMSE of 0.61 mg m⁻³, 0.35 g m⁻³, and 0.02 m⁻¹, respectively. The utility of the approach is finally demonstrated by application to depth profiles of in situ absorption and attenuation data resulting in profiles of optically significant constituents with associated error bar estimates. The advantages of this procedure lie in the simple input requirements, the avoidance of error amplification, full exploitation of the available spectral information from both absorption and attenuation channels, and the reasonably successful retrieval of constituent concentrations in an optically complex shelf sea.

Several studies have been carried out to investigate the correlation between the spectral shape features of the beam attenuation coefficient and the particulate matter characteristics in seawater, but little attention has been paid to the spectral resolution of these measurements. For this reason, the potential of the new hyperspectral transmissometer VIPER (TriOS GmbH), with 1.7 nm spectral resolution, has been evaluated in this study and compared with lower resolution and multispectral based approaches (e.g. ac-9 or ac-s-with 4 nm resolution - from WETLabs Inc.) in order to evaluate whether any additional information about water composition can be retrieved from a spectral shape-based assessment. In this way, this study proposes a statistical-based method - a Hierarchical Cluster Analysis (HCA) using the cosine distance as similarity value - which allows discriminating suspended sediment samples with different particle size distribution (PSD) based on the attenuation spectral shape features. Finally, the effects of both particle size and concentration on the spectral shape have been analyzed separately. The results confirmed that the beam attenuation spectral features are in first-order driven by particle concentration, which means that a prior knowledge of particulate matter concentration is required in order to classify sediment samples according to their particle size. This approach based on hyperspectral attenuation measurements to characterize the PSD has been demonstrated a potential alternative compared to the traditional methods such as Coulter Counter or the particle size analyzer LISST 100X, which are much more expensive and time-consuming approaches.

Tropical cyclones represent one of the major natural hazards for coastal regions worldwide, primarily due to the extreme storm surges they generate. Reliable estimates of storm surge associated with return periods are essential for coastal risk assessment, infrastructure design, and climate adaptation planning. These estimates, however, are highly sensitive to the characteristics of the accuracy of the input forcing and the underlying datasets used for the extreme value analysis, including their temporal length, time resolution and the representation of rare but high-impact events.The goal of this study is to analyze this sensitivity. To this end, several tropical cyclone–induced storm surge datasets are considered for the Caribbean Sea and Gulf of Mexico region, differing in duration, structure, input forcing, and underlying assumptions. The datasets are derived using commonly adopted approaches, including a 32-year (1993–2024) continuous storm surge hindcast forced by ERA5 reanalysis wind and pressure fields, as well as event-based storm surge simulations generated using a parametric Holland wind model for both historical and synthetic tropical cyclones. The historical hurricane dataset is analysed for the full period of available records (1851–2024) and separately for the period overlapping with the ERA5 hindcast (1993–2024), enabling a consistent comparison across datasets. Return level curves obtained from these datasets are compared to evaluate the sensitivity of extreme storm surge estimates to dataset length, input forcing, and the inclusion of synthetic events. The results provide valuable insights into the uncertainties affecting storm surge return period estimates and emphasize the importance of carefully selecting datasets when assessing tropical cyclone–induced coastal hazards.