Maximum Significant Wave Height Research Articles

Response of Shallow-Water Temperature and Significant Wave Height to Sequential Tropical Cyclones in the Northeast Beibu Gulf

Using shallow-water buoy observations, reanalysis data, and numerical models, this study analyzes the variations in sea temperature and significant wave height (SWH) caused by two sequential tropical cyclones (TCs) ‘Lionrock’ and ‘Kompasu’ in October 2021 in the northeast Beibu Gulf, South China Sea. The results show that the sea surface temperature (SST) cooling of the nearshore waters was larger than the offshore water in the basin of the gulf, with the cooling amplitude and rate decreasing and the cooling time lagging behind wind increasing from coast to offshore. The near-surface temperature at the buoy station had a maximum decrease of 2.8 °C after ‘Lionrock’, and the decrease increased slightly to 3 °C after the stronger wind of ‘Kompasu’. The total decrease of 4.6 °C indicates that the sequential TCs had a superimposed effect on the cooling of the Beibu Gulf. The heat budget analysis revealed that the sea surface heat loss and the Ekman pumping rate in the nearshore waters during ‘Kompasu’ (−535 W/m2 and 5.8 × 10−4 m/s, respectively) were significantly higher than that (−418 W/m2 and 4 × 10−4 m/s) during ‘Lionrock’. On the other hand, the SST cooling (−1.2 °C) during the second TC is smaller than (−1.6 °C) the first weaker TC in the gulf basin, probably due to the deepening of the mixed layer. During the observation period, the waves in the Beibu Gulf were predominantly wind-driven. The maximum SWHs reached 1.58 m and 2.3 m at the bouy station near shore during the two TCs, and the SWH variation was highly correlated to the wind variation with a correlation of 0.95. The SWH increases from the nearshore to offshore waters during the TCs. The SAWN and ARCIRC coupled model results suggest that wave variations in the Beibu Gulf are primarily influenced by water depth, bottom friction, and whitecapping. Two days after the TCs, sea surface cooling and high waves appeared again due to a cold air event.

Analysis of Wave Characteristics near Wangdeungdo through Southwest Sea Wave Hindcasting

Wave conditions are crucial for offshore wind farm design, particularly in determining structural loads and layout. However, there is limited wave hindcasting research for the Wangdeungdo Island area, a potential offshore wind site. This study used the MIKE21 model for a year-long wave hindcast around Wangdeungdo in 2021. Validation showed high reproducibility for significant wave heights with RMSE values of 0.177 and 0.225 and Pearson correlations of 0.971 and 0.970 at Sangwangdeungdo and Buan buoys. Subsequent analysis of the wave characteristics near Wangdeungdo indicated significant seasonal variations and differences in maximum significant wave heights across locations, which are expected to significantly impact the design loads for offshore wind structures.

Spatial trend analysis of significant wave heights in the Kara Sea

Over the past decades, the extent of sea ice in the Arctic, including the Kara Sea, has been diminishing. This phenomenon has a direct impact on wind waves as the increased expansion of ice-free water influences wave height. Furthermore, alterations in the ice cover also lead to modifications in atmospheric circulation, necessitating a concurrent analysis of wind and waves to refine the understanding of their interrelationships. In this study, wave modeling data were employed using the WAVEWATCH III model and NCEP/CFSR/CFSv2 reanalyzes. Calculations were performed on a non-structural computational grid. The grid covers the Barents and Kara Seas, as well as the entire northern part of the Atlantic Ocean. The spatial resolution varies from ~ 700 m for the coastal zone of the Kara Sea, to ~ 20 km in the open part of the Kara Sea, covering the period from January 1, 1979 to December 31, 2021. Subsequently, average significant wave heights (SWH), maximum SWH, and the 95th percentile of SWH were computed for each grid node on both monthly and yearly basis. The annual values were analyzed for trends and their significance. Calculations were conducted for both the entire period and ice-free period. Positive trends in annual mean values were observed throughout the sea, with the maximum trend occurring near the boundary with the Barents Sea, barely exceeding 0.2 m/10 years. The northern and northeastern parts of the sea were characterized by significant positive trends of the maximum SWH values. Maximum trend values for the 95th percentile of SWH were also evident in the northern part of the Kara Sea. For the ice-free period, maximum trend values were notable for both the annual mean and the 95th percentile of SWH in the northern part of the sea (maximum trend values are approximately 0.25 m/10 years and 0.5 m/10 years, respectively). Significant positive trends in the annual mean SWH were characteristic of the southern part of the sea, while the largest and significant trends for maximum wave heights were observed in the northeast. The assessment of the contribution of wind and ice regimes to the variability of wind waves remains a subject of discussion.

Future changes in intense tropical cyclone hazards in the Pearl River Delta region: an air-wave-ocean coupled model study

AbstractThe Pearl River Delta (PRD) region is highly vulnerable to tropical cyclone (TC)-caused coastal hazards due to its long and meandering shoreline and well-developed economy. With global warming expected to continue or worsen in the rest of the twenty-first century, this study examines the TC impact on the PRD coastal regions by reproducing three intense landfalling TCs, namely Vicente (2012), Hato (2017), Mangkhut (2018), using a sophisticated air-wave-ocean coupled model of high spatial resolution (1-km atmosphere and 500-m wave and ocean). The simulations are conducted using present-day reanalysis data and the same TCs occurring in a pseudo-global warming scenario projected for the 2090s. Results indicate that the coupled model accurately reproduces the air-wave-ocean status during the TC episodes. The 2090s thermodynamic status effectively increases the intensity of intense TCs, leading to more severe coastal hazards including gale, rainstorm, and storm surges and waves. On average, the maximum surface wind speed within 50–200 km to the right of the TC center can increase by 4.3 m/s (+22%). The 99th and the 99.9th percentile of accumulated rainfall will increase from 405 to 475 mm (+17.3%), and from 619 to 735 mm (+18.6%), respectively. The maximum significant wave height at the ocean is lifted by an average of 57 cm (+13.8%), and the coastline typically faces a 40–80 cm increase. The maximum storm surges are lifted by 30–80 cm over the open sea but aggravate much higher along the coastline, especially for narrowing estuaries. For Typhoon Vicente (2012), there is more than a 200 cm wave height increase observed both at open sea and along the coastline. In the 2090s context, a combination of mean sea level rise, storm surge, and wave height can reach more than 300 cm increase in total water level at certain hot-spot coastlines, without considering the superposition of spring tides.

Wave climate change analysis based on long time-series buoy data

Using the buoy dataset from 2011 to 2022, the trend of wave climate change was analyzed at DaChen station located in the Taizhou City, Zhejiang Province. The results show a decreasing trend of the maximum significant wave height (Hs). Whereas the wave height is higher than 4 m, the corresponding wave period is in the range of 8-14s. Disastrous waves mainly occur between July and October. The relevant analysis presents the wave characteristics at the DaChen station, which is helpful for protecting the life safety along the coast and providing references for offshore engineering design.

Trends in the surface wind-wave heights in the North Indian Ocean based on 50-year NCEP/NCAR reanalysis wind-wave data

Analysis of 50 years of hourly significant wave heights of the Indian Ocean between 30°N and 60°S is carried out and linear trends of mean significant wave heights and maximum significant wave heights are obtained on annual, seasonal and decadal scales. The significant wave heights (SWH) are obtained from a third-generation spectral wind-wave model forced with six-hourly NCEP-NCAR winds over the Indian Ocean. These SWHs are validated with measurements available in the north Indian Ocean and the correlation coefficient is more than 0.87. The climatology obtained from the spectral wind wave model matches well with the climatology reported in the literature using other models and satellite-based datasets. The maximum SWH ranged from 0.25 m to 22.5 m with the max-SWH exceeding 7 m South of 30°S, and greater than 13 m between 45°S-55°S and 50°E-95°E. In the Northern Indian Ocean (NIO), max SWH reached 5.5 m in the central Bay of Bengal and over 8 m in the western Arabian Sea. The annual trend of the mean SWH showed an overall positive trend in the Indian Ocean, except in the west BoB, northwest Arabian Sea, and a part of the central Indian Ocean. The maximum SWH also followed an overall similar positive trend as that of mean SWH albeit with a prominent negative trend in the BoB, southeastern and northwestern Arabian Sea. There was a significant difference in the SWH trend between the seasons both spatially and temporally for all other decades. However, the maximum SWH showed highly varying trends for all the seasons and decades. The variation in the mean SWH decadal trend showed greater variation in the lower latitudes compared to the higher latitudes.

Multi-scenario analysis in the Apulia shoreline: A multi-tiers analytical framework for the combined evaluation and management of coastal erosion and water quality risks

Ongoing climate change is causing threats to coastal areas, according to scenarios of Intergovernmental Panel on Climate Change (IPCC). The coastal areas are becoming highly exposed to erosion as a direct consequence of natural and anthropogenic processes that occur at different spatial-temporal scales. Against this interplay, coastal managers are calling for integrated tools supporting a multi-scenario evaluation of risks arising from natural and anthropogenic stress. A multi-tier analytical framework, exploiting the openly available Earth Observation databases, was developed, allowing the combination of remote sensing, GIS and Bayesian Network to evaluate the probability and uncertainty of coastal erosion risks and connected water quality variation, against ‘what-if’ scenarios, representing different management measures (i.e., Nature-Based Solution) and climate change impacts (e.g., higher incident waves due to increased storminess). Based on the available data for the Municipality of Ugento (Italy), the designed framework was applied over the 2009–2018 timeframe, allowing to capture local-scale shoreline erosion dynamics and driving forces. Results from scenario analysis revealed, to a minor extent, a nexus between oceanographic drivers, shoreline evolution, and water quality changes, with increasing probability of high erosion/accretion and higher turbidity under the simulated rising maximum significant wave height. However, the implementation of Nature-Based Solutions (i.e., circular approach exploiting beached Posidonia oceanica leaves) resulted in significant positive effects, stabilizing the shoreline by reducing high erosion and accretion rates. Despite data constraints, outcomes of the performed assessment could represent valuable information to drive adaptive policy pathways in the context of coastal management along the Ugento shoreline.

Contribution of tropical cyclone induced waves to the mean and extreme wave climatology in the Bay of Bengal

This paper examines the contribution of tropical cyclones (TCs) to the mean wave and the extreme wave climatology in the Bay of Bengal (BoB). To assess the impact of TCs on the wave activity in the BoB, we compare 40-years long WAVEWATCH III (WW3) numerical simulation with a twin experiment, where TC signatures are filtered out from the wind forcing dataset. Our experimental strategy of twin simulations, with and without TCs, allow us to separate the TC-induced waves from the background wave activity and therefore allow us to quantify their contribution. The simulation samples more than 200 TCs in the BoB and is extensively validated against the available buoy observations that measure 39 TCs in the BoB. Results show that TCs contribute up to ∼80 % and ∼40 % to the extreme significant wave height (SWH) climatology defined as the maximum SWH and highest 1 % SWH and up to ∼9 % to the mean SWH climatology during the post-monsoon season with slightly lesser contributions during the pre-monsoon season. This contribution is largest in the northern BoB and along the east coast of India during the post-monsoon season and in the eastern BoB and along the Bangladesh and Myanmar coast during the pre-monsoon season.

WAVE ANALYSIS FOR THE DEVELOPMENT OF THIEN NGA - HAI AU OIL FIELD

This study utilizes the SWAN model to simulate wave data, subsequently comparing it with ERA5 and CMEMS wave reanalysis datasets. Our analysis demonstrates that the SWAN-simulated wave data are more consistent with observations compared to ERA5 and CMEMS reanalyzed wave data. The predominant wave directions are Northeast and Southwest, with occurrence frequencies of 43.87% and 24.24%, and maximum significant wave heights of 7.72 m and 3.28 m, respectively. Significant wave heights for 50 and 100 year return periods are 8.17 m and 8.53 m in the NE direction, 3.44 m and 3.56 m in the SW direction, 3.78 m and 3.84 m during the Southwest monsoon, 10.09 m and 10.45 m during the Northeast monsoon, and 12.8 m and 13.6 m during storms, respectively. These results are instrumental for the structural design of the Thien Nga - Hai Au oil field in the Southern region of the East Sea Viet Nam.

FUTURE PREDICTION OF WIND VELOCITY AND SIGNIFICANT WAVE HEIGHT IN THE COMPLETELY ICE-FREE ARCTIC OCEAN UNDER RCP8.5 SCENARIO

The summer sea ice extent in the Arctic Ocean has decreased by several million square kilometers over the past decades highly likely due to anthropogenic global warming (Walsh, 2014). In the Arctic Ocean, the decrease in sea ice increases the open water area (and period), which potentially leads to the development of more energetic wave conditions (Wang et al., 2015). In the summertime Arctic Ocean, the maximum wind speed and the maximum significant wave height have been on a long-term upward trend as the sea ice extent has decreased (Waseda et al., 2018). In addition, changes in wind speed will contribute significantly to changes in the wave height in the future Arctic Ocean (Khon et al., 2014). Thus, it is becoming more important to study the sea surface wave heights in the Arctic area under possible future scenarios. The aim of this study is (1) to develop a method to assess wind and wave conditions over the Arctic Ocean and (2) to predict them under global warming considering the RCP 8.5 scenario.

Spectral wave energy period and peak period statistics concomitant with maximum significant wave heights

Spectral wave energy period and peak period statistics concomitant with maximum significant wave heights

Investigation on influence of RCP-based climate scenarios on the hydrodynamic and morphodynamic changes during extreme events

The hydrodynamics and morphodynamic changes induced by climate change is a serious threat to a coastal community, in which researches are scanty. This study describes how a tropical cyclone and its associated surge, wave and morphological changes would behave in future with persistently changing Representative Concentration Pathway (RCP)-based climate change scenarios. For the prediction of morphodynamics, to fully capture the tidal effects on waves and vice versa, TELEMAC-2D, TOMAWAC and SISYPHE modules are internally coupled with each other. In this study, we considered three scenarios of RCP (4.5, 6.0 and 8.5) in the Near-Future (2025–2045) and Far-Future (2065–2085). To endorse the efficacy of the model in coupled environment, the predicted wind speed, surface elevation and wave climate for an extreme event is compared with the field conditions. The result shows that, in RCP 6.0 and RCP 8.5 in far future, the effects of climate change in terms of maximum wind speed and maximum significant wave height increased in an order of to 10% to 15% and 9% to 14%, respectively. The effect of climate change scenarios in storm surge and current magnitudes does not follow any particular trend. The bed level changes for future scenarios (RCP 6.0 and RCP 8.5) in the area of assessment is doubled from the Control run. The numerical modeling results from this study conveys fresh visions about the effect of tropical cyclone on environmental parameters, in the present and future climate scenarios.

Wave climate characteristics and effects of tropical cyclones on high wave occurrences in Indonesian waters: Strengthening sea transportation safety management

Tropical cyclones can cause bad weather and high waves that can endanger maritime activities, especially in the waters of Indonesia, which is a maritime country. Understanding ocean wave climate characteristics and the effect of Tropical Cyclones (TCs) on high wave occurrences is important, particularly to ensure the safety of fisheries activities in Indonesian seas. We aim to do so by focusing on Indonesia's 11 Fisheries Management Areas (IFMAs) using descriptive and inferential statistics. Wind and wave data were taken from the European Center for Medium-Range Weather Forecast (ECMWF), namely ECMWF Reanalysis v5 (ERA5) within the range of 42 years (1979–2020), whereas the TC data were from the International Best Track Archive for Climate Stewardship (IBTrACS). We found that significant wave heights (SWHs) in the inner seas are strongly related to monsoonal wind fields. The maximum SWH occurred in northern Indonesian seas during December–February (DJF), while occurring in southern and inner seas between June–August (JJA). The highest extreme SWH and probability of exceedance (PE) for SWH >2 m were found in IFMAs facing the open ocean, such as Malacca Strait, Western Sumatra waters, Southern Java waters, Natuna Sea, Sulawesi Sea, and Northern Papua waters. We found that TCs activity in adjacent Indonesian waters could increase anomalous SWH occurrences. Positive SWH anomalies ranged from 0.1 to 0.4 m and varied depending on TC location and season. TC that forms in the following areas increase the PE for SWH >2 m: (1) Bay of Bengal: Western Sumatra waters (March–May, MAM) around 20%; (2) Western Pacific Ocean: Northern Papua waters (DJF) around 5%; (3) Northeastern Indian Ocean: Western Sumatra waters (DJF) about 3%; and (4) Western and Northern Australian waters: Southern Java waters (DJF) about 20%. The results of this study can serve as an early assessment for investigating wave climate characteristics and identifying the areas in Indonesian waters that are most susceptible to the impact of TCs, particularly in IFMAs. These findings hold significant value for managers and policy authorities, such as the Ministry of Transportation and the Ministry of Marine Affairs and Fisheries of the Republic of Indonesia. They can utilize this information to develop measures aimed at reducing vulnerabilities among marine resource users, specifically fishers, and improving fishing vessel safety. Additionally, these findings can be utilized to enhance advance warnings and forecasts, enabling marine managers to implement strategies that minimize the impact of extreme events and increase resilience in the face of ocean and coastal disasters.

Influence of Long-Term Wind Variability on the Storm Activity in the Caspian Sea

Wind and wave conditions are limiting factors for economic activity, and it is very important to study the long-term variability of storm activity. The main motivation of this research is to assess the impact of wind variability on the storm activity in the Caspian Sea over the past 42 years. The paper presents the analysis of a number of storms based on the results of wave model WAVEWATCH III and the Peak Over Threshold method. The mean, maximum, and 95th percentile significant wave heights were analyzed by season. The highest waves were in the Middle Caspian Sea in winter. Detailed interannual and seasonal analyses of the number and duration of storm waves were performed for the whole Caspian Sea and its separate regions. Positive significant trends were found in the whole sea. Significant positive trends in the number and duration of storms were found for the North and Middle Caspian. In the South Caspian, the trends were negative and not significant. High correlations were found between the number of storms and events with wind speed > 10–14 m/s and 95th percentile wind speed. Positive trends in the number of storms in the Middle Caspian were caused by positive trends in extreme wind situations.

Wind Waves Web Atlas of the Russian Seas

The main parameters of wind waves in the World Ocean are connected with global climate change. Renewable energy technologies, intensive shipping, fishery, marine infrastructure, and many different human marine activities in the coastal zone and open sea need knowledge about the wind-wave climate. The main motivation of this research is to share various wind wave parameters with high spatial resolution in the coastal zone via a modern cartographic web atlas. The developed atlas contains information on 13 Russian Seas, including the Azov, Black, Baltic, Caspian, White, Barents, Kara, Laptev, East Siberian, Chukchi, Bering Seas, the Sea of Okhotsk, and the Sea of Japan/East Sea. The analysis of wave climate was based on the results of wave modeling by WAVEWATCH III with input NCEP/CFSR wind and ice data. The web atlas was organized using the classic three-tier architecture, which includes a data storage subsystem (database server), a data analysis and publishing subsystem (GIS server), and a web application subsystem that provides a user interface for interacting with data and map services (webserver). The web atlas provides access to the following parameters: mean and maximum significant wave height, wave length and period, wave energy flux, wind speed, and wind power. The developed atlas allows changing the map scale (zoom) for detailed analysis of wave parameters in the coastal zones where the wave model spatial resolution is 300–1000 m.

Multi-criteria decision-making optimization model for permeable breakwaters characterization

Permeable breakwaters have always been of interest due to their advantages over the traditional types. This study proposed a stochastic multi-criteria decision-making model to optimize the geometry of permeable breakwaters. A multi-objective optimization algorithm was conducted using the non-dominated sorting genetic algorithm-II (NSGA-II) coupling with the estimations made by a well-known machine learning (ML) model, the multi-layer perceptron neural network (MLP-NN) to achieve the objective. Considering the inherent uncertainties in the wave characteristics using the conditional value-at-risk (CVaR) method, the presented risk-based model could determine optimal tradeoffs between wave transmission, wave reflection, and rockfill materials volume. This CVaR-based multi-objective optimization model was experimentally applied to a permeable breakwater with maximum significant wave heights of 1–3.5 m at confidence levels of 50%, 75%, 90%, and 99% for risk analysis. To rank several alternatives between the Pareto-optimal solutions, a decisive so-called multi-criterion decision-making (MCDM) approach was employed, which coupled the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method and analytical network process (ANP) procedure. Results indicated that the heavier permeable breakwater was the most appropriate for greater wave heights. To this extent, the relative rockfill materials height and width increased to 1.1 from 0.77 and 1.1 from 0.41, respectively, by increasing the specific wave height from 2 to 3.5 m.

Моделирование ветрового волнения в море Лаптевых, Восточно-Сибирском и Чукотском морях

The paper presents an analysis of wind wave parameters in the Laptev, East Siberian and Chukchi seas based on the results of numerical experiments with the WAVEWATCH III wave model for a period from 1979 to 2021. Wave modeling was carried out using an unstructured computational grid with a high resolution (up to 800 m) in the coastal zone. The NCEP/CFSR/CFSv2 reanalysis was used as wind forcing. The maps of the long-term mean values of the wave height, wave length and period were obtained. For the several points in the central part of each sea, the mean annual values of wave heights are calculated and the analysis of interannual variability is carried out. The maximum significant wave height was 5–6 m in the Laptev Sea, 6–7 m in the East Siberian Sea, and 7–7.5 m in the Chukchi Sea. The analysis of interannual variability showed that there is a positive trend in wave height for all seas under consideration. The largest increase in the annual mean wave height is observed in the East Siberian Sea (from 0.4 to 1.4 m in the ice-free period). Keywords: Laptev Sea, Chukchi Sea, East Siberian Sea, wave modeling, Arctic wind waves, WAVEWATCH III

Simulating Meteorological and Water Wave Characteristics of Cyclone Shaheen

The Bay of Bengal and Arabian Sea are annually exposed to severe tropical cyclones, which impose massive infrastructure damages and cause the loss of life in coastal regions. Cyclone Shaheen originally generated in the Bay of Bengal in 2021 and translated a rare east-to-west path toward the Arabian Sea. Although the cyclone’s wind field can be obtained from reanalysis datasets such as ERA5 (fifth generation European Centre for Medium-Range Weather Forecasts), the wind speed cannot be reproduced with realistic details in the regions close to the center of cyclone due to spatial resolution. In this study, to address this problem, the high-resolution advanced Weather Research and Forecasting (WRF) model is used for simulation of Shaheen’s wind field. As a critical part of the study, the sensitivity of the results to the planetary boundary layer (PBL) parameterization in terms of the track, intensity, strength and structure of the cyclone Shaheen is investigated. Five experiments are considered with five PBL schemes: Yonsei University (YSU); Mellor–Yamada–Janjić (MYJ); Mellor–Yamada–Nakanishi–Niino level 2.5 (MYNN); Asymmetric Convective Model version 2 (ACM2); Quasi-Normal Scale Elimination (QNSE). The track, intensity, and strength of the experiments are compared with the wind fields obtained from the Joint Typhoon Warning Centre (JTWC) dataset. The results imply the high dependency of the track, intensity, and strength of the cyclone to the PBL parameterization. Simulated tracks with non-local PBL schemes (YSU and ACM2) outperformed those of the local PBL schemes (MYJ, MYNN, and QNSE), especially during the rapid intensification phase of Shaheen before landfall. The YSU produced highly intensified storm, while the ACM2 results are in better agreement with the JTWC data. The most accurate track was obtained from the ERA5 data; however, this dataset overestimated the spatial size and underestimated the wind speed. The WRF model using either YSU or ACM2 overestimated the wind speed compared to that of the altimeter data. The YSU and ACM2 schemes were able to reproduce the observed increase in wind speed and pressure drop at in situ stations. The wind data from EAR5 and cyclone parametric model were applied to the SWAN model to simulate the wave regime in the Arabian Sea during the time that Shaheen was translating across the region. Janssen formulation for wind input and whitecapping dissipation source terms in combination with both ERA5 and hybrid wind were used and the minimum combined error in the prediction of significant wave height (Hs) and zero up-crossing wave period (Tz) was examined. The maximum significant wave height for hybrid wind is higher than that of ERA5, while the cyclone development was successfully inferred from the wave field of the hybrid data.

Optimal tropical cyclone size parameter for determining storm-induced maximum significant wave height

The maximum significant wave height (Hsmax) induced by a tropical cyclone (TC) can be estimated from an empirical fetch formula using the TC’s size, maximum wind speed, and translation speed, in which larger, stronger, and faster-moving TCs generally have higher the Hsmax. In the formula, the radius of maximum wind (RMW) has been widely used as the TC size parameter under the assumption that Hsmax is mainly generated by strong winds near the RMW. This study investigates whether RMW is the optimal parameter for determining TC-induced Hsmax through extensive wave model simulations for North Atlantic hurricanes from 1988–2017. The correlation analysis between the estimated Hsmax and TC size parameters revealed that the radius of the 34-kt wind speed (R34, r = 0.84–0.95) was much higher than the widely used RMW (r = 0.33–0.58), which suggests that R34 is a more important TC size parameter for determining TC-induced Hsmax than RMW. This result can be explained by the fact that R34 showed a significantly higher correlation (r = 0.96) than RMW (r = 0.31) with cumulative TC wind speeds, which are closely related to Hsmax. These findings also indicate that the TC-induced Hsmax is more affected by the region containing moderately strong winds outside the TC than by the region of maximum wind speed near the RMW. Our paper provides additional insight into the mechanisms by which extreme wave heights, which cause severe damage during TC passage, occur.

Ongoing Development of the Bass Strait GNSS/INS Buoy System for Altimetry Validation in Preparation for SWOT

GNSS equipped buoys remain an important tool in altimetry validation. Progressive advances in altimetry missions require associated development in such validation tools. In this paper, we enhanced an existing buoy approach and gained further understanding of the buoy dynamics based on in situ observations. First, we implemented the capability to separate the ambiguity fixing strategy for different constellations in the processing software TRACK. A comparison between GPS and GNSS solutions suggested up to 3 cm reduction in the root mean square of the buoy minus co-located mooring SSH residuals over the selected sidereal periods. Then, comparison between double differencing and precise point positioning solutions suggested a possible common mode error external to GNSS processing. To assess buoy performance in different ocean conditions and sea states, GNSS and INS observations were used during periods where external forcings (waves, current and wind) were not interacting substantially. For the deployments investigated, no significant relationship was found, noting the maximum significant wave height and current velocity was ~2.3 m and ~0.3 m/s, respectively. In the lead up to the validation required for the SWOT mission, these results place important bounds on the performance of the buoy design under real operating conditions.