Blended Wind Field Research Articles

Effect of Tropical Cyclone Wind Forcing on Improving Upper Ocean Simulation: An Idealized Study

We examined how wind forcing affects the upper ocean response under idealized tropical cyclone (TC) conditions. In this study, we constructed three parameterized wind fields with varying spatial and temporal resolutions for TCs of different intensities and translation speeds. The simulated surface and subsurface temperatures were cooler and deeper when using the blended wind fields owing to their higher wind speeds compared to those from coarse–resolution wind fields. Additionally, TC–induced currents were significantly stronger on the right side of the TC track, with notable differences in current velocities. Similar to the increase in ocean currents, the simulated turbulent kinetic energy driven by the blended winds is significantly higher than that simulated by the coarse-resolution wind fields. These findings suggest that using high-quality wind fields to drive ocean models can enhance the accuracy of the upper ocean response to TCs. The sensitivity of the upper ocean responses to wind forcing depends on the TC’s intensity and translation speed. Stronger and slower-moving TCs induce greater vertical shear and enhanced mixing. Therefore, accurate wind stress as a surface boundary condition is crucial for numerical ocean models.

Impact of Satellite Wind on Improving Simulation of the Upper Ocean Response to Tropical Cyclones

Accurate modeling of the ocean response to tropical cyclones (TCs) requires high-quality wind fields to force ocean models. In this study, blended wind fields are generated using multi-source satellite data and the Climate Forecast System Reanalysis (CFSR) wind data. We utilize the hybrid wind fields to drive the Regional Ocean Modeling System (ROMS) for simulating oceanic dynamic and thermodynamic parameters. The model’s simulated ocean surface and sub-surface temperatures, as well as current speeds, are generally consistent with satellite and in situ observations collected during TC Winston and Freddy. The results are significantly better than those simulated by ROMS using wind forcing from CFSR alone. These results suggest that incorporating satellite wind data into the atmospheric forcing has the potential to enhance vertical mixing and improve simulations of the upper ocean response to TCs.

Improvements in wind field hindcast for storm surge predictions in the Bay of Bengal: A case study for the tropical cyclone Varadah

Forecasting the storm surges is crucial to prevent the enormous devastation of coastal ecosystems, habitats, and economic losses. Further, estimating ocean wave parameters in tropical areas is difficult due to the complexity of wind fields associated with tropical cyclones (TCs). Usually, parametric and global model wind fields are the two primary sources to acquire wind and pressure fields to estimate the storm surges. The parametric models usually depict a better wind field near the cyclone center. Unlike the parametric models, the wind fields from global models have better accuracy in the areas far away from the eye of the cyclone. Owing to this inconsistency, a blended wind field approach has been introduced. However, there are no consensus on selecting parametric and background wind models due to the lack of a rigorous assessment of different wind models in the Bay of Bengal (BoB) region. Hence, in this study, five well-known parametric wind models, namely, Jelesnianski (SLOSH), rankine vortex (RV), Willoughby (WL06), Holland (HL80), and generalized asymmetric holland model (GAHM); and, two global wind models, namely, european center for medium-rangeweather forecasts (ECMWF), and weather research forecast (WRF) models were investigated with the available predictions and measurements in BoB. After investigating the best wind model in this region, a detailed analysis was carried out for the TC Varadah in the BoB region. Further, this study provides insight into the deviations in the resulting simulated surge, wave characteristics, and inundation induced by the different atmospheric forcing wind models. The results reveal that a blended wind model based on GAHM and WRF can better simulate the background wind field and the internal structure of the cyclone for the BoB region.

Assessment of combined wind and wave energy in the tropical cyclone affected region:An application in China seas

Marine renewable energy resources are important for clean energy development. Research on the combined assessment of wind and wave resources, especially in tropical cyclone (TC) affected area is still rare. This study is to assess the potential combined wind and wave energy in the coastal waters of China, where TCs frequently occurred. The study utilizes the blended wind field with a parametric TC model based on the ECMWF reanalysis wind data from 1979 to 2013 for assessing potential wind energy, and the waves generated by the same wind data using the FVCOM-SWAVE model for assessing wave energy. The combined wind and wave energy density and annual power generation are analyzed. The potential energy from wind and waves at 15 nearshore locations along China east coasts are estimated. The results show that the frequency and intensity of TCs have a considerable impact on the distribution of density and stability of wind and wave energy, especially in the southeastern coastal areas of China. Suggestions of site selection of co-located wind and wave farm in the coastal waters of China are given. The research outcome provides a useful guidance for the selection of potential sites and design of wind and wave energy converters along the China coasts.

Real-Time Simulated Storm Surge Predictions during Hurricane Michael (2018)

Abstract Storm surge caused by tropical cyclones can cause overland flooding and lead to loss of life while damaging homes, businesses, and critical infrastructure. In 2018, Hurricane Michael made landfall near Mexico Beach, Florida, on 10 October with peak wind speeds near 71.9 m s−1 (161 mph) and storm surge over 4.5 m NAVD88. During Hurricane Michael, water levels and waves were predicted near–real time using a deterministic, depth-averaged, high-resolution ADCIRC+SWAN model of the northern Gulf of Mexico. The model was forced with an asymmetrical parametric vortex model [generalized asymmetric Holland model (GAHM)] based on Michael’s National Hurricane Center (NHC) forecast track and strength. The authors report errors between simulated and observed water level time series, peak water level, and timing of peak for NHC advisories. Forecasts of water levels were within 0.5 m of observations, and the timing of peak water levels was within 1 h as early as 48 h before Michael’s eventual landfall. We also examined the effect of adding far-field meteorology in our TC vortex model for use in real-time forecasts. In general, we found that including far-field meteorology by blending the TC vortex with a basin-scale NWP product improved water level forecasts. However, we note that divergence between the NHC forecast track and the forecast track of the meteorological model supplying the far-field winds represents a potential limitation to operationalizing a blended wind field surge product. The approaches and data reported herein provide a transparent assessment of water level forecasts during Hurricane Michael and highlight potential future improvements for more accurate predictions.

Hindcasting of tropical cyclone winds and waves

This paper describes a series of hindcast simulations of 17 tropical cyclones over the northwest shelf region of Australia. Tropical cyclone track and vortex details were obtained from the Bureau of Meteorology “Best Track” database. Wind fields were simulated using a dynamic boundary layer model referred to as the Kepert-Wang model. Surface wind and pressure fields were blended with background fields from the ERA-Interim dataset. These blended wind fields were then used as forcing for the WAVEWATCH III wave model to generate wave fields. Several different configurations of wave model source terms were trialled. Wind and wave models were validated against available observations from the Bureau of Meteorology and our industry partner. The mean absolute error for peak significant wave height (Hs) for all configurations was mostly less than 0.90 m, compared to a mean observed peak Hs of 4.8 m, and the bias was less than around 0.41 m. It was found that while in general the ST6 wave model source term physics package with NL3 non-linear interactions performs well overall, there is no single configuration that performs best for all 17 tropical cyclones.

Analysis of Wave Fields under Tropical Cyclones in the South China Sea

Sun, W.; Shao, Z.; Liang, B., and Gao, H., 2020. Analysis of wave fields under tropical cyclones in the South China Sea. In: Zheng, C.W.; Wang, Q.; Zhan, C., and Yang, S.B. (eds.), Air-Sea Interaction and Coastal Environments of the Maritime and Polar Silk Roads. Journal of Coastal Research, Special Issue No. 99, pp. 126–130. Coconut Creek (Florida), ISSN 0749-0208.The study of wave fields under extreme weather conditions, such as tropical cyclones, is becoming increasingly important for ocean engineering. In this work, wave simulation under a tropical cyclone is carried out in the South China Sea (SCS). The SWAN model is driven by the blended wind field. In this model, the wind input term and whitecapping dissipation term are specifically studied to obtain a reliable model result. During tropical cyclones Doksuri and Kai-tak in 2012, the waves are simulated in the SCS, and the simulated significant wave heights are validated by the measured data at buoys B1, B2 and B3. The validation results show that the simulated values match the measured values well. By the simulated significant wave heights, the wave field is analyzed during the tropical cyclone. In the mean and maximal conditions, the wave fields are studied with the tropical cyclone track. The maximal significant wave heights at the buoy locations are associated with the corresponding spatial distribution of significant wave heights in the SCS, which can reflect the effect of the tropical cyclone on the wave at a specified point.

Improved cyclonic wind fields over the Bay of Bengal and their application in storm surge and wave computations

Tropical cyclone induced storm surge and extreme waves pose a significant threat and danger to coastal inhabitants as well cause significant damage to infrastructure. Nevertheless, significant progress has been achieved over the past several years in tropical cyclone modeling, there are however inherent limitations in the quality of real-time wind forecast for near-field and far-field regions surrounding the cyclone eye. The reliability and quality of computed storm surge and extreme wind-waves remains a challenge due to their primary association with the quality of input wind forcing. Parametric wind field models are widely used owing to their simplicity and also in realistically representing the inner core region of cyclones. On the other hand, global atmospheric models have inherent limitations in underestimating the inner core winds, although they produce outer core winds much better as compared to the parametric formulation. In this study a blending technique is proposed which takes advantage of both these wind fields thereby producing a blended wind field using a smoothing algorithm and superposition technique that provides realistic estimates of both inner and outer core winds. Numerical simulations with a coupled wave-hydrodynamic model using both blended and the parametric winds were also verified against in situ data. The study reveals that simulations using blended winds performed better and has practical relevance to real-time operational forecasts.

Evaluation of numerical wave model for typhoon wave simulation in South China Sea

The simulating waves nearshore (SWAN) model has typically been designed for wave simulations in near-shore regions. In this study, the model's applicability to the simulation of typhoon waves in the South China Sea (SCS) was evaluated. A blended wind field, consisting of an interior domain based on Fujita's model and an exterior domain based on Takahashi's model, was used as the driving wind field. The waves driven by Typhoon Kai-tak over the SCS that occurred in 2012 were selected for the numerical simulation research. Sensitivity analyses of time step, grid resolution, and angle resolution were performed in order to obtain optimal model settings. Through sensitivity analyses, it can be found that the time step has a large influence on the results, while grid resolution and angle resolution have a little effect on the results.

Blended wind fields for wave modeling of tropical cyclones in the South China Sea and East China Sea

Accurate tropical cyclone (TC) wind fields are crucial for modeling TC waves. Usually, reanalysis wind data, such as the ERA-Interim dataset, and parametric TC models, such as the Holland model, are widely used to generate TC wind fields. In the present work, 29 tropical cyclones (TCs) in the South China Sea (SCS) and East China Sea (ECS) of 4 years (2011–2014) are analyzed at 10 buoy locations. Among them, 9 TCs are selected as study cases due to buoys experience their whole processes of the TC passing. For the 9 selected TCs, data of the ERA-Interim and Holland model are compared with observation data of 10 buoys in the SCS and ECS. Results show that the ERA-Interim largely under-predicts wind speeds near the TC center, where the Holland model performs generally well. However, the Holland model fails to reproduce wind speeds in outer-region of the TC. After analyzing character of two sets of data, applicable ranges for the ERA-Interim and Holland model are identified with critical boundary limits, which are associated with the TC size. A formula for blended TC wind fields combining two datasets is proposed, which shows good capacity of the TC wind simulation. Then, the blended wind model is applied in TC wave simulations in the SCS and ECS, and shows a better performance than both the ERA-Interim and the Holland model. Thus, the proposed blending formula can be used to generate more accurate TC wind fields which are required in TC wave hindcasts.

Wave Hindcast Experiments Using Wam Cycle 4.5.3 - Validation with In situ Measurements in the North Indian Ocean

In this investigation, the execution of the wave model WAM Cycle 4.5.3 was evaluated; based on the forcings by two distinct wind fields namely ERA-40 and QuikSCAT-NCEP Blended winds in the North Indian Ocean. Using the past analysed winds (hindcasting) and with boundary conditions generated from 1° x 1° global runs the wave model have been implemented for the North Indian Ocean from 50°E to 100°E and 0°N to 30°N. The model simulated parameters namely significant wave height (Hs), mean wave periods (Tc), mean wave direction, swell wave height (Hsw), swell wave period (Tsw) and swell wave directions are presented. Further, the predicted waves are compared against in-situ wave measurements. The simulated wave parameters obtained as outputs from numerical simulations such as Hs and Tc; collocated in space and time have been compared with buoy measurements in the Arabian Sea and Bay of Bengal with the aid of statistical error indicators. Comparison between the predicted and observed wave parameters are very encouraging, excepting the higher model estimates of significant wave height and the disagreement in lower wave heights at few buoy locations. Further, the sensitivity of the model to two different wind fields was analyzed and it is noted that the blended winds could accurately reproduce Hs and Tc at the buoy locations. The present study suggests that, WAM Cycle 4.5.3 model predictions are quite reliable for the Indian seas using the analysed wind fields such as ERA-40 and QuikSCAT/NCEP Blended wind fields. However, the performance of wave model was best when blended winds were used. Despite several limitations, the results reveal that the performance of third generation wave model is promising and the correlation and deviation of simulated and measured waves are critically inspected.

Comparison of reanalyzed, analyzed, satellite-retrieved and NWP modelled winds with buoy data along the Iberian Peninsula coast

Offshore wind data derived from satellite measurements (CCMP, QuikSCAT, NCDC Blended Sea Winds and IFREMER Blended Wind Fields), reanalyses (NCEP-CFSR, ERA-Interim, NASA-MERRA and NCEP-RII), analyses (NCEP-FNL and NCEP-GFS) and WRF modelled offshore winds were compared to in situ measurements, in order to assess which one of these products is the best alternative to in situ offshore measured wind data. Wind speed and direction from these products were compared to measurements collected at five buoys moored along the Iberian Peninsula Atlantic coast.Results show that WRF modelled offshore winds are the best alternative to in situ measured offshore wind data, showing the highest temporal accuracy (the ability in representing the wind speed and direction at a given time instant) and lowest errors in terms of offshore wind power flux estimations. However, offshore wind data taken from CCMP shows the lowest errors in terms of the mean wind speeds and, together with IFREMER-BWF, the best wind temporal accuracy after WRF simulation. Therefore, in general CCMP and IFREMER-BWF can be considered as the best alternatives to WRF high resolution modelled offshore winds, if the latter is not available. Specifically for offshore wind energy resource assessment, NCEP-CFSR reanalysis or NCEP-GFS analysis data can also be used with confidence as an alternative to WRF modelled data, showing better wind power flux estimates than CCMP and IFREMER-BWF.Despite the best performances of WRF high resolution offshore winds, such modelling tasks require considerable computational resources and time to obtain quality results. Therefore, the value of satellite-derived wind data should not be disregarded. These remotely sensed offshore wind measurements should be seriously considered when searching for alternative sources of wind information for ocean areas, in particular for open ocean areas where they have their strength.

Impact of Diurnal Variation of Winds on Coastal Waves off South East Coast of India

The land-sea breeze systems, the most interesting phenomena observed at coastal regions, have significant impact on the costal wave characteristics. Present study also focuses the diurnal variations of winds and its impact on wave parameters like significant wave height and mean wave period off Ennore port located in the south east coast of India The impact of the diurnal variation of winds on complex wave patterns in the coastal regions of Indian Ocean have been addressed earlier also. In the present study an attempt has been made to explore the impact of diurnal variation of winds on coastal waves using numerical model forced with European Centre for Medium Range Weather Forecasts (ECMWF) and National Centre for Environmental Prediction (NCEP) blended wind fields. It has been observed that most of the time, the ECMWF blended wind field reproduces the diurnal variation.

Sea wave modeling with X-band COSMO-SkyMed<sup>©</sup> SAR-derived wind field forcing and applications in coastal vulnerability assessment

Abstract. In this paper, X-band COSMO-SkyMed© synthetic aperture radar (SAR) wind field data are first used to force coastal wind wave modeling for both sea wave numerical simulation and coastal vulnerability assessment purposes. The SAR-based wind field retrieval is accomplished by resolving the SAR-based wind speed and wind direction retrieval problems independently. The sea surface wind speed is retrieved through the azimuth cut-off procedure, and the sea surface wind direction is determined by the multi-resolution analysis of the discrete wavelet transform. The wind wave modeling is based on the third-generation Simulating WAves Nearshore (SWAN) model, which is used for sea wave state estimation in coastal and inland regions. The coastal vulnerability assessment is provided by means of a key parameter, known as impact index, which evaluates the coastal risk due to the inundation of the inshore land. Experiments consist of SWAN numerical simulations run with respect to some relevant wave storms recorded in the southern Tyrrhenian Sea on 2010, with applications in coastal vulnerability assessment along the Sele coastal plain. Experimental results show the benefits of blended wind field products, provided by European Centre for Medium Weather Forecast (ECMWF) model winds and SAR-based wind field estimations, for both wind wave modeling and coastal vulnerability assessment purposes.

Improved near real time surface wind resolution over the Mediterranean Sea

Abstract. Several scientific programs, including the Mediterranean Forecasting System Toward Environmental Predictions (MFSTEP project), request high space and time resolutions of surface wind speed and direction. The purpose of this paper is to focus on surface wind improvements over the global Mediterranean Sea, based on the blending near real time remotely sensed wind observations and ECMWF wind analysis. Ocean surface wind observations are retrieved from QuikSCAT scatterometer and from SSM/I radiometers available at near real time at Météo-France. Using synchronous satellite data, the number of remotely sensed data available for each analysis epoch (00:00 h; 06:00 h; 12:00 h; 18:00 h) is not uniformly distributed as a function of space and time. On average two satellite wind observations are available for each analysis time period. The analysis is performed by optimum interpolation (OI) based on the kriging approach. The needed covariance matrixes are estimated from the satellite wind speed, zonal and meridional component observations. The quality of the 6-hourly resulting blended wind fields on 0.25° grid are investigated trough comparisons with the remotely sensed observations as well as with moored buoy wind averaged wind estimates. The blended wind data and remotely wind observations, occurring within 3 h and 0.25° from the analysis estimates, compare well over the global basin as well as over the sub-basins. The correlation coefficients exceed 0.95 while the rms difference values are less than 0.30 m/s. Using measurements from moored buoys, the high-resolution wind fields are found to have similar accuracy as satellite wind retrievals. Blended wind estimates exhibit better comparisons with buoy moored in open sea than near shore.