Search Results (34)

One of the manifests of air-sea interactions is the change in sea level due to meteorological forcing through wind stress and atmospheric pressure. When meteorological conditions conducive to water level increase coincide with high tides during spring tides, the sea level may rise higher than expected and pose a flood risk to coastal low-lying areas. In Hong Kong, specifically when the northeast monsoon coincides with the higher spring tides in late autumn and winter, and sometimes even compounded by the storm surge brought by late-season tropical cyclones (TCs), the result may be coastal flooding or sea inundation. Aiming at forecasting such sea level anomalies on the scale of hours and days with local tide gauges using a flexible and computationally efficient method, this study adapts a data-driven method based on empirical orthogonal functions (EOF) regression of non-uniformly lagged regional wind field from ECMWF Reanalysis v5 (ERA5) to capture the effects from synoptic weather evolution patterns, excluding the effect of TCs. Local atmospheric pressure and winds are also included in the predictors of the regression model. Verification results show good performance in general. Hindcast using ECMWF forecasts as input reveals that the reduction of mean absolute error (MAE) by adding the anomaly forecast to the existing predicted astronomical tide was as high as 30% in February on average over the whole range of water levels, as well as that compared against the Delft3D forecast in a strong northeast monsoon case. The EOF method generally outperformed the persistence method in forecasting water level anomaly for a lead time of more than 6 h. The performance was even better particularly for high water levels, making it suitable to serve as a forecast reference tool for providing high water level alerts to relevant emergency response agencies to tackle the risk of coastal inundation in non-TC situations and an estimate of the anomaly contribution from the northeast monsoon under its combined effect with TC. The model is capable of improving water level forecasts up to a week ahead, despite the general decreasing model performance with increasing lead time due to less accurate input from model forecasts at a longer range. Some cases show that the model successfully predicted both positive and negative anomalies with a magnitude similar to observations up to 5 to 7 days in advance. Full article

The maximum wind speed radius of a strong typhoon making landfall is an important factor influencing the numerical forecasting of storm surges. A method for inverting the maximum wind speed radius of typhoons based on wave buoys data was designed to significantly reduce the error in 24 h storm surge forecasting in this paper, and an operation scheme was proposed to enhance the storm surge numerical forecasting system based on this method. Hangzhou Bay and the Yangtze River Estuary, which have been frequently impacted by typhoons over the past five years, were selected as the research area. Common schemes for the maximum wind speed radius were analyzed, and five ladder schemes (10, 15, 20, 25, and 30 km) were established for wave and storm surge numerical model verification of Typhoon Muifa in 2022. Based on a comparison of the wave hindcast results and wave buoys observation data, the wave hindcast result of the commonly used scheme (30 km) was significantly greater than that of the observation data, and the optimal scheme (15 km) closest to the observation data could be determined during the 48 h warning period. Moreover, it was difficult to identify the optimal scheme during the 48 h warning period based on the storm surge hindcast results. A 24 h storm surge numerical forecasting test was performed with the commonly used scheme (30 km) and the optimal scheme (15 km). The results showed that the root mean square error (RMSE) of the optimal scheme (15 km) was 34% lower than that of the commonly used scheme (30 km), while the maximum storm surge error was also reduced from 47.7% for the commonly adopted scheme (30 km) to 11.8% for the optimal scheme (15 km). The maximum storm surges under the optimal scheme (15 km) along Hangzhou Bay and the Yangtze River Estuary ranged from 1.9 to 2.2 m, which were closer to the observation data, and the maximum storm surge under the commonly used scheme (30 km) was 0.8~1.2 m greater than that under the optimal scheme (15 km). Full article

The Puget Sound Coastal Storm Modeling System (PS-CoSMoS) is a tool designed to dynamically downscale future climate scenarios (i.e., projected changes in wind and pressure fields and temperature) to compute regional water levels, waves, and compound flooding over large geographic areas (100 s of kilometers) at high spatial resolutions (1 m) pertinent to coastal hazard assessments and planning. This research focuses on advancing robust and computationally efficient approaches to resolving the coastal compound flooding components for complex, estuary environments and their application to the Puget Sound region of Washington State (USA) and the greater Salish Sea. The modeling system provides coastal planners with projections of storm hazards and flood exposure for recurring flood events, spanning the annual to 1-percent annual chance of flooding, necessary to manage public safety and the prioritization and cost-efficient protection of critical infrastructure and valued ecosystems. The tool is applied and validated for Whatcom County, Washington, and includes a cross-shore profile model (XBeach) and overland flooding model (SFINCS) and is nested in a regional tide–surge model and wave model. Despite uncertainties in boundary conditions, hindcast simulations performed with the coupled model system accurately identified areas that were flooded during a recent storm in 2018. Flood hazards and risks are expected to increase exponentially as the sea level rises in the study area of 210 km of shoreline. With 1 m of sea-level rise, annual flood extents are projected to increase from 13 to 33 km² (5 and 13% of low-lying Whatcom County) and flood risk (defined in USD) is projected to increase fifteenfold (from 14 to USD 206 million). PS-CoSMoS, like its prior iteration in California (CoSMoS), provides valuable coastal hazard projections to help communities plan for the impacts of sea-level rise and storms. Full article

Super Typhoon Saola (2309) skirted past south-southeast of Hong Kong within 40 km on the night of 1 September 2023, posing a significant storm surge threat to Hong Kong. Given the close proximity of Saola with a peak intensity of about 210 km/h within 300 km of Hong Kong, a close call of the “super typhoon direct-hit” scenario, this case provides valuable insights from a hindcast review of storm surge forecasts and warning operation using the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model, which is the operational storm surge model adopted by the Hong Kong Observatory (HKO). The performance of the HKO’s PRobabilistic Inundation Map Evaluation System (PRIMES) using both statistical and model ensemble approaches was also reviewed in this paper. Saola was a challenging case for operational forecasting of a compact TC structure with changes in storm size and intensity when it came close to Hong Kong. With major observations of storm structure using weather radar and dense automatic weather station, tide gauge and water level gauge networks, the high sensitivity of storm surge forecasts to the storm size parameter and the distance of closest approach was clearly revealed in the case of Saola. Even with a circularly symmetric TC parametric model like SLOSH, the hindcast review results illustrated that the model outputs were reasonably accurate during the closest approach of Saola given an accurate storm size and distance of closest approach were input, and using a highly computationally efficient storm surge model made it possible for the nowcasting of storm surges to handle compact and intense TC direct-hit cases in operational TC forecasting. Taking a nowcasting approach not only helps provide more reliable storm tide forecasts, but also facilitates the formulation of a better warning strategy when making final-call decisions in emergency response actions, based on the more frequent real-time analysis of TC position, intensity and storm size and the more accurate prediction of these parameters. A nowcasting workflow for storm surge operation was proposed in this paper. Full article

The study used the SCHISM ocean model combined with the WWM III wind wave model to quantify the interaction between wind waves and tides in the coastal zone of the Changjiang River Estuary and its adjacent areas. The wave and storm surge during Typhoon Ampil, which made landfall in July 2018 in Shanghai, were simulated by using the Climate Forecast System Version 2 (CFSv2) and Medium-Range Weather Forecasts (ECMWF) latest reanalysis (ERA5) wind dataset from 1 July to 31 July. Model results with CFSv2 forcing show better performance in terms of significant wave height and storm surge than those with ERA5 forcing. To investigate the interactions between waves, water levels, currents, and their combined effects on significant wave and surge variations, six numerical sensitivity experiments were designed according to the different coupling methods between SCHISM and WWMIII. The research shows that in coastal areas with water depths of less than 10 m, waves are affected by water levels and currents. The differences in the effect on significant wave height between wave-tide coupling and one-way coupling with water levels and currents are negligible. Wave setup is an important physical term which cannot be ignored during the variations of storm surge caused by Typhoon Ampil. The contributions of wave set up were concentrated in coastal areas with water depths less than 10 m. The peak wave setup occurred in the Changjiang River Estuary, reaching 0.15 m. In Xiangshan Bay and Sanmen Bay, wave radiation stress makes the proportion of wave setup to the total surge reached more than 30%. The consideration of wave-tide interaction can effectively improve the accuracy of numerical wave and storm surge simulations, which can provide more accurate hindcasts of wave and storm surge variations in the Changjiang River Estuary and its adjacent coastal areas. Full article

The South Pacific region is characterised by steep shelves and fringing coral reef islands. The lack of wide continental shelves that can dissipate waves makes Pacific Island countries vulnerable to large waves that can enhance extreme total water levels triggered by tropical cyclones (TCs). In this study, hindcasts of the waves and storm surge induced by severe TC Harold in 2020 on Tongatapu, Tonga’s capital island, were examined using the state-of-the-art hydrodynamic and wave models ADCIRC and SWAN. The contributions of winds, atmospheric pressure, waves, and wave-radiation-stress-induced setup to extreme total water levels were analysed by running the models separately and two-way coupled. The atmospheric pressure deficit contributed uniformly to the total water levels (~25%), while the wind surge was prominent over the shallow shelf (more than 75%). Wave setup became significant at locations with narrow fringing reefs on the western side (more than 75%). Tides were dominant on the leeward coasts of the island (50–75%). Storm surge obtained from the coupled run without tide was comparable with the observation. The wave contribution to extreme total water levels and inundation was analysed using XBEACH in non-hydrostatic mode. The model (XBEACH) was able to reproduce coastal inundation when compared to the observed satellite imagery after the event on a particular coastal segment severely impacted by coastal flooding induced by TC Harold. The coupled ADCIRC+SWAN underestimated total water levels nearshore on the reef flat and consequently inundation extent as infragravity waves and swash motion are not resolved by these models. The suite of models (ADCIRC+SWAN+XBEACH) used in this study can be used to support the Tonga Meteorological Service Tropical Cyclone Early Warning System. Full article

High-quality wind field data are key to improving the accuracy of storm surge simulations in coastal and estuarine water. These data are also of great significance in studying the dynamic processes in coastal areas and safeguarding human engineering structures. A directional correction method for ECMWF reanalysis wind data was proposed in this paper based on the correlation with the measured wind speed and direction. The results show that the accuracies of wind speed and direction were improved after being modified by the correction method proposed in this paper. The modified wind data were applied to drive the storm surge model of the Yangtze Estuary for typhoon events, which resulted in a significant improvement to the accuracy of hindcasted water levels. The error of the hindcasted highest water levels was reduced by 16–19 cm. Full article

The south coast of Korea is vulnerable to coastal disasters, such as storm surges, high waves, wave overtopping, and coastal flooding caused by typhoons. It is imperative to predict such disastrous events accurately in advance, which requires accurate meteorological forcing for coastal ocean modeling. In this study, to acquire accurate meteorological data as important forcing variables for the prediction of storm surges and waves, we examined the forecast performance and applicability of a next-generation global weather/climate prediction model, the Model for Prediction Across Scales (MPAS). We compared the modeled surface pressure and wind with observations on the south coast of Korea for three typhoons that damaged Korea in 2020—Bavi, Maysak, and Haishen—and investigated the accuracy of these observations with the MPAS prediction. Those meteorological forcing variables were then used in the tightly coupled tide-surge-wave model, Advanced CIRCulation (ADCIRC) and the Simulating Waves Nearshore (SWAN) for the simulation of a typhoon-induced storm surge and wave. We also performed the hindcast of the wave and storm surges using a parametric tropical cyclone model, the best-track-based Generalized Asymmetric Holland Model (GAHM) embedded in ADCIRC+SWAN, to better understand the forecast performance and applicability of MPAS. We compared the forecast results of the typhoon-induced wave and storm surges with their hindcast in terms of the time-series and statistical indices for both significant wave height and storm surge height and found that wave and storm surge prediction forced by MPAS forecast provides a comparable accuracy with the hindcast. Comparable results of MPAS forcing with that of hindcast using best track information are encouraging because ADCIRC+SWAN forced by MPAS forecast with an at most four-day lead time still provides a reasonable prediction of wave and storm surges. Full article

Intense atmospheric disturbances, which impact directly on the sea surface causing a significant increase in wave height and sometimes strong storm surges, have become increasingly frequent in recent years in the Mediterranean Sea, producing extreme concern in highly populated coastal areas, such as the Gulf of Naples (Western Mediterranean Sea, Central Tyrrhenian Sea). In this work, fifty-six months of wave parameters retrieved by an HF radar network are integrated with numerical outputs to analyze the seasonality of extreme events in the study area and to investigate the performance of HF radars while increasing their distances from the coast. The model employed is the MWM (Mediterranean Wind-Wave Model), providing a wind-wave dataset based on numerical models (the hindcast approach) and implemented in the study area with a 0.03° spatial resolution. The integration and comparison with the MWM dataset, carried out using wave parameters and spectral information, allowed us to analyze the availability and accuracy of HF sampling during the investigated period. The statistical comparisons highlight agreement between the model and the HF radars during episodes of sea storms. The results confirm the potential of HF radar systems as long-term monitoring observation platforms, and allow us to give further indications on the seasonality of sea storms under different meteorological conditions and on their energy content in semi-enclosed coastal areas, such as the Gulf of Naples. Full article

This paper evaluates the contribution of waves to the total predicted storm surges in a Hurricane Irma hindcast, using ADCIRC+SWAN and ADCIRC models. The contribution of waves is quantified by subtracting the water levels hindcasted by ADCIRC from those hindcasted by ADCIRC+SWAN, using OWI meteorological forcing in both models. Databases of water level time series, wave characteristic time series, and high-water marks are used to validate the model performance. Based on the application of our methodology to the coastline around Florida, a peninsula with unique geomorphic characteristics, we find that wave runup has the largest contribution to the total water levels on the south and northeast coasts. Waves increase the surge on the south and northeast coasts, due to large fetch and wave runups. On the west coast, the wave effect is not significant, due to limited fetch. However, significant wave heights become greater as the waves propagate into the deep inner gulf. The continental shelf on Florida’s west coast plays a critical role in decreasing the significant wave height and sheltering the coastal areas from large wave effects. Both models underpredict the high-water marks, but ADCIRC+SWAN reduces the underprediction and improves the parity with the observed data, although the scatter is slightly higher than that of ADCIRC. Full article

On 2 June 2014, at about 13 UTC, a dust storm arrived in Tehran as a severe hazard that caused injures, deaths, failures in power supply, and traffic disruption. Such an extreme event is not considered as common for the Tehran area, which has raised the question of the dust storm’s origin and the need for increasing citizens’ preparedness during such events. The analysis of the observational data and numerical simulations using coupled dust-atmospheric models showed that intensive convective activity occurred over the south and southwest of Tehran, which produced cold downdrafts and, consequently, high-velocity surface winds. Different dust source masks were used as an input for model hindcasts of the event (forecasts of the past event) to show the capability of the numerical models to perform high-quality forecasts in such events and to expand the knowledge on the storm’s formation and progression. In addition to the proven capability of the models, if engaged in operational use to contribute to the establishment of an early warning system for dust storms, another conclusion appeared as a highlight of this research: abandoned agricultural areas south of Tehran were responsible for over 50% of the airborne dust concentration within the dust storm that surged through Tehran. Such a dust source in the numerical simulation produced a PM10 surface dust concentration of several thousand μm/m³, which classifies it as a dust source hot-spot. The produced evidence indivisibly links issues of land degradation, extreme weather, environmental protection, and health and safety. Full article

Sea surface wind plays an essential role in the simulating and predicting ocean phenomena. However, it is difficult to obtain accurate data with uniform spatiotemporal scale. A high-resolution (10 km) sea surface wind hindcast around the Korean Peninsula (KP) is presented using the weather research and forecasting model focusing on wind speed. The hindcast data for 39 years (1979–2017) are obtained by performing a three-dimensional variational analysis data assimilation, using ERA-Interim as initial and boundary conditions. To evaluate the added value of the hindcasts, the ASCAT-L2 satellite-based gridded data (DASCAT) is employed and regarded as “True” during 2008–2017. Hindcast and DASCAT data are verified using buoy observations from 1997–2017. The added value of the hindcast compared to ERA-Interim is evaluated using a modified Brier skill score method and analyzed for seasonality and wind intensity. Hindcast data primarily adds value to the coastal areas of the KP, particularly over the Yellow Sea in the summer, the East Sea in the winter, and the Korean Strait in all seasons. In case of strong winds (10–25 m·s⁻¹), the hindcast performed better in the East Sea area. The estimation of extreme wind speeds is performed based on the added value and 50-year and 100-year return periods are estimated using a Weibull distribution. The results of this study can provide a reference dataset for climate perspective storm surge and wave simulation studies. Full article

Under the STORMTOOLS initiative, maps of the impact of sea level rise (SLR) (0 to 12 ft), nuisance flooding (1–10 yr), 25, 50, and 100 yr storms, and hindcasts of the four top ranked tropical storms have been developed for the coastal waters of Rhode Island (RI). Estimates of the design elevations, expressed in terms of the Base Flood Elevation (BFE) and thus incorporating surge and associated wave conditions, have also been developed, including the effects of SLR to facilitate structural design. Finally, Coastal Environmental Risk Index (CERI) maps have been developed to estimate the risk to individual structures and infrastructure. CERI employs the BFE maps in concert with damage curves for residential and commercial structures to make estimates of damage to individual structures. All maps are available via an ArcGIS Hub. The objective of this senior design capstone project was to develop STORMTOOLS Design Load maps (SDL) with a goal of estimating the hydrostatic, hydrodynamic, wave, and debris loading, based on ASCE/SEI 7–16 Minimum Design Standards methods, on residential structures in the RI coastal floodplain. The resulting maps display the unitized loads and thus can be scaled for any structure of interest. The goal of the maps is to provide environmental loads that support the design of structures, and reduce the time and cost required in performing the design and the permitting process, while also improving the accuracy and consistency of the designs. SDL maps were generated for all loads, including the effects of SLR for a test case: the Watch Hill/Misquamicut Beach, Westerly, along the southern RI coast. The Autodesk Professional Robot Structural Analysis software, along with SDL loading, was used to evaluate the designs for selected on-grade and pile-elevated residential structures. Damage curves were generated for each and shown to be consistent with the US Army Corps of Engineers empirical damage curves currently used in CERI. Full article

In this paper, a three-dimensional storm surge model was developed based on the Finite Volume Community Ocean Model (FVCOM) by the hindcasts of four typhoon-induced storm surges (Chan-hom, Mireille, Herb, and Winnie). After model validation, a series of sensitivity experiments were conducted to explore the effects of key parameters in the wind and pressure field (forward speed, radius of maximum wind (RMW), inflow angle, and central pressure), typhoon path, wind intensity, and topography on the storm surge and surge asymmetry between sea level rise (positive surge) and fall (negative surge) along the southeastern coast of China (SCC). The model results show that lower central pressure and larger RMW could lead to stronger surge asymmetry. A larger inflow angle results in a stronger surge asymmetry. In addition, the path of Chan-hom is the most dangerous path type for the Zhoushan Archipelago area, and that of Winnie follows next. The model results also indicate that the non-linear interaction between wind field and pressure field tends to weaken the peak surge elevation. The effect of topography on storm surges indicates that the peak surge elevation and its occurrence time, as well as the surge asymmetry, increase with a decreasing slope along the SCC. Full article

A numerical study was conducted to characterize the probability and intensity of storm surge hazards in Canada’s western Arctic. The utility of the European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation (ERA5) dataset to force numerical simulations of storm surges was explored. Fifty historical storm surge events that were captured on a tide gauge near Tuktoyaktuk, Northwest Territories, were simulated using a two-dimensional (depth-averaged) hydrodynamic model accounting for the influence of sea ice on air-sea momentum transfer. The extent of sea ice and the duration of the ice season has been reducing in the Arctic region, which may contribute to increasing risk from storm surge-driven hazards. Comparisons between winter storm events under present-day ice concentrations and future open-water scenarios revealed that the decline in ice cover has potential to result in storm surges that are up to three times higher. The numerical model was also used to hindcast a significant surge event that was not recorded by the tide gauge, but for which driftwood lines along the coast provided insights to the high-water marks. Compared to measurements at proximate meteorological stations, the ERA5 reanalysis dataset provided reasonable estimates of atmospheric pressure but did not accurately capture peak wind speeds during storm surge events. By adjusting the wind drag coefficients to compensate, reasonably accurate predictions of storm surges were attained for most of the simulated events. The extreme value probability distributions (i.e., return periods and values) of the storm surges were significantly altered when events absent from the tide gauge record were included in the frequency analysis, demonstrating the value of non-conventional data sources, such as driftwood line surveys, in supporting coastal hazard assessments in remote regions. Full article