Cyclonic Wind Research Articles

Study of the Effect of an Environmentally Friendly Flood Risk Reduction Approach on the Oman Coastlines during the Gonu Tropical Cyclone (Case Study: The Coastline of Sur)

Tropical cyclones may be destructive in the coastal region, such as the Gonu tropical cyclone, which affected the Arabian Peninsula and parts of southern Iran in 2007. In this study, a coupled MIKE 21/3 HD/SW (hydrodynamic/spectral wave) model was used to simulate the inland flooding inside the Sur port during the Gonu tropical cyclone. The MIKE 21 Cyclone Wind Generation (CWG) tool was utilized to generate the cyclone’s wind and pressure field. The required input data were obtained from the International Best Track Archive for Climate Stewardship (IBTrACS) and imported into the CWG tool. In this study, the wind and pressure fields were compared between the analytical vortex model and European Centre for Medium-Range Weather Forecasts (ECMWF) data during the Gonu cyclone passage. Moreover, by developing a new model, artificial Mangroves’ effect on inland flooding was investigated. The results show that, contrary to the ECMWF data, the analytical vortex models well captured the storm event’s wind and pressure field. Furthermore, the flood hazard is calculated based on the inundation depth, flow velocity, and area’s vulnerability. The flood hazard map shows that 5% of the coast is at high-risk, 49% is at medium-risk, and 46% is at low-risk class in the Sur port. By applying Mangroves as flood risk reduction, the high-risk area is almost completely removed. However, medium and low-risk zones increase by 50% and 50%, respectively. This information could be helpful in disaster risk reduction and coastal management in the future.

Scrambling and Reorientation of Classical Atmospheric Boundary Layer Turbulence in Hurricane Winds

AbstractThe societal, economic, and ecosystem consequences of hurricanes are projected to increase with ocean warming. Although wind gusts can be highly destructive in these extreme events, current knowledge on hurricane turbulence structures is limited due to insufficient measurement sampling data and the low resolution (1–5 km) of weather models. To bridge this knowledge gap, we propose and validate a numerical approach based on a novel theoretical framework that enables us to simulate hurricane boundary layer (BL) at ≈25 m resolution. Our high‐resolution simulations revealed an intermediate layer in the hurricane BL in which the streamwise‐elongated coherent turbulence structures that typically populate the BL flows are broken into smaller eddies. The distinctive structure of turbulence in cyclonic winds also alters internal BL dynamics during hurricane landfalls by reorienting the roll vortices. We demonstrate that the centrifugal forces in hurricanes cause scrambling and reorientation of the elongated conventional atmospheric BL streaks.

Bio-Physical Changes in the Gulf of Mexico During the 2018 Hurricane Michael

We investigate the impacts of one of the strongest recorded hurricanes to have hit the Florida Panhandle, Hurricane Michael (2018), on the upper ocean using a suite of satellite data, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> profiles, and outputs from the HYbrid Coordinate Ocean Model (HYCOM). Strong, low-level cyclonic winds associated with the hurricane generated strong Ekman suction that propagated ahead of the hurricane and caused changes in the surface and subsurface ocean. Following the passage of Hurricane Michael, a 3 °C drop in sea surface temperature (SST) was accompanied with a 4–5 mg <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{-3}$ </tex-math></inline-formula> increase in chlorophyll-a concentration. In the subsurface, a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 15$ </tex-math></inline-formula> m mixed layer deepening preceded upward displacements of the isotherms and cooling of the mixed layer. The impact of hurricane conditions on sea surface salinity (SSS) was localized and influenced by competing processes, with upwelling of salty subsurface water increasing SSS and enhanced precipitation decreasing SSS. During the peak of the hurricane, the impact of upwelling was greater than that of enhanced precipitation and, thus, SSS increased. Further away from the upwelling centers, hurricane-influenced precipitation, and river runoff freshened SSS.

Surface Thermal Structure and Variability of Upwelling Shadows in the Gulf of Arauco, Chile

AbstractThe upwelling shadow in the Gulf of Arauco (GA) is studied using 15 years of daily satellite images of Sea Surface Temperature (SST) from Geostationary Operational Environmental Satellites (GOES), as well as heat flux and wind data from the ERA5 reanalysis product. An Upwelling Shadow Index (USI) is developed based on the SST differences between the GA and the region off Punta Lavapie (PL) farther offshore, characterized by active upwelling. USI values greater than 0.91°C and SST differences less than 1.1°C, correspond to an upwelling shadow event. These cases occurred 10.29% of the time and were more frequent in spring/summer during events of upwelling‐favorable winds with strong cyclonic wind stress curl, interspersed with wind relaxations. Multiple correlations between USI and wind stress curl and solar radiation showed an r2 = 40%–80% for some summer months. Most events persisted for only 1 day (53%), whereas 34% of upwelling shadow events lasted between 2 and 4 days and 9% of events were longer than 4 days. Water residence times as long as 15 days were observed in the GA during upwelling shadow events. During southerly wind relaxation (less than 2 days), cold surface waters flowing north from PL curved onshore and entered the GA from the north, weakening the thermal gradient between PL and GA and the upwelling shadow. Long periods of wind relaxation (at least 1 week) resulted in the dissipation of the thermal gradient due to the warming of offshore waters.

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.

Assessment of tropical cyclone wave models for engineering applications

Tropical Cyclone (TC) wind and wave models are used to quantify meteorological and oceanographic conditions in the application of offshore engineering design criteria. In regions such as the North West Shelf of Australia, a statistically sound 'risk of failure' design assessment can require historical records far longer than are typically available, even with meteorological datasets of several decades length. To address this mismatch between design requirements and observational history, synthetic tropical cyclone wind and wave datasets can be developed to mimic long records with the objective of estimating extreme event average recurrence intervals of 10,000 years. Modelling large numbers of TC storms in practice requires a trade-off between time (computational efficiency) and accuracy (model skill). The development of the synthetic dataset in this study draws the balance by combining computationally efficient parametric models, and computationally intensive fully dynamic models, with different model grid resolutions. This paper outlines performance differences between the various model approaches and make recommendations for engineering.

Simulating synthetic tropical cyclone tracks for statistically reliable wind and pressure estimations

Abstract. The design of coastal protection measures and the quantification of coastal risks at locations affected by tropical cyclones (TCs) are often based solely on the analysis of historical cyclone tracks. Due to data scarcity and the random nature of TCs, the assumption that a hypothetical TC could hit a neighboring area with equal likelihood to past events can potentially lead to over- and/or underestimations of extremes and associated risks. The simulation of numerous synthetic TC tracks based on (historical) data can overcome this limitation. In this paper, a new method for the generation of synthetic TC tracks is proposed. The method has been implemented in the highly flexible open-source Tropical Cyclone Wind Statistical Estimation Tool (TCWiSE). TCWiSE uses an empirical track model based on Markov chains and can simulate thousands of synthetic TC tracks and wind fields in any oceanic basin based on any (historical) data source. Moreover, the tool can be used to determine the wind extremes, and the output can be used for the reliable assessment of coastal hazards. Validation results for the Gulf of Mexico show that TC patterns and extreme wind speeds are well reproduced by TCWiSE.

Potential Role of Irreversible Moist Processes in Modulating Tropical Cyclone Surface Wind Structure

AbstractTropical cyclone (TC) wind structure is important for its intensity change and induced damage, but its modulating factors remain to be explored. A heat-engine-based surface wind structure parameter α, reflecting TC’s relative compactness, is introduced and derived based on an entropy budget framework. We found that α is modulated by three key parameters: the thermodynamic efficiency ϵPI in potential intensity theory, the Carnot efficiency ϵC of the system, and the degree of irreversibility αirr of the system. A higher αirr contributes to a larger α and a lower heat engine efficiency. An expression linking TC intensity and compactness also emerges under this framework. Idealized simulations of a typical moist TC (CTL), a dry (DRY) TC, and a moist reversible TC (REV; in which hydrometeors do not fall out) evinced that the significantly higher αirr in CTL, due to irreversible entropy productions from precipitation dissipation, water vapor diffusion, and irreversible phase changes, contributes to its much larger compactness compared to DRY and REV. The study illustrates the importance of irreversible entropy production processes in modulating TC surface wind field. Simple estimate suggests that α will increase due to a hypothesized increased αirr with warming because of increased water content. This indicates that TCs will become more compact in a warmer climate.

The Historic Rainfalls of Hurricanes Harvey and Florence: A Perspective from the Multi-Radar Multi-Sensor System

AbstractHurricane Harvey in 2017 generated one of the most catastrophic rainfall events in United States history. Numerous gauge observations in Texas exceeded 1200 mm, and the record accumulations resulted in 65 direct fatalities from rainfall-induced flooding. This was followed by Hurricane Florence in 2018, where multiple regions in North Carolina received over 750 mm of rainfall. The Multi-Radar Multi-Sensor (MRMS) system provides the unique perspective of applying fully automated seamless radar mosaics and locally gauge-corrected products for these two historical tropical cyclone rainfall events. This study investigates the performance of various MRMS quantitative precipitation estimation (QPE) products as it pertains to rare extreme tropical cyclone rainfall events. Various biases were identified in the radar-only approaches, which were mitigated in a new dual-polarimetric synthetic radar QPE approach. A local gauge correction of radar-derived QPE provided statistical improvements over the radar-only products but introduced consistent underestimation biases attributed to undercatch from tropical cyclone winds. This study then introduces a conceptual methodology to bulk correct for gauge wind undercatch across the numerous gauge networks ingested by the MRMS system. Adjusting the hourly gauge observations for wind undercatch resulted in increased storm-total accumulations for both tropical cyclones that better matched independent gauge observations, yet its application across large network collections highlighted the challenges of applying a singular wind undercatch correction scheme for significant wind events (e.g., tropical cyclones) while recognizing the need for increased metadata on gauge characteristics.

The Response of the Near-Surface Tropical Cyclone Wind Field to Inland Surface Roughness Length and Soil Moisture Content during and after Landfall

AbstractThe sensitivity of the inland wind decay to realistic inland surface roughness lengths and soil moisture contents is evaluated for strong, idealized tropical cyclones (TCs) of category 4 strength making landfall. Results show that the relative sensitivities to roughness and moisture differ throughout the decay process, and are dependent on the strength and size of the vortex. First, within 12 h of landfall, intense winds at the surface decay rapidly in reaction to the sudden change in surface roughness and decreasing enthalpy fluxes. Wind speeds above the boundary layer decay at a slower rate. Differences in soil moisture contents minimally affect intensity during the first 12 h, as the enhancement of latent heat fluxes from high moisture contents is countered by enhanced surface cooling. After TCs decay to tropical storm intensities, weakening slows and the sensitivity of the intensity decay to soil moisture increases. Increased latent heating becomes significant enough to combat surface temperature cooling, resulting in enhanced convection outside of the expanding radius of maximum winds. This supports a slower decay. Additionally, the decay of the radial wind profile by quadrant is highly asymmetric, as the rear and left-of-motion quadrants decay the fastest. Increasing surface roughness accelerates the decay of the strongest winds, while increasing soil moisture slows the decay of the larger TC wind field. Results have implications for inland forecasting of TC winds and understanding the potential for damage.

Tropical cyclone damage assessment of distributed infrastructure systems under spatially correlated wind speeds

Probabilistic damage evaluation and loss estimation of spatially distributed infrastructure systems (e.g. an electric power system or a building portfolio) under a scenario tropical cyclone must consider the spatial correlation of cyclone wind speeds to estimate their impact on the built environment statistically. Previous studies have seldom considered the impact of this spatial correlation on damage assessments of distributed civil infrastructure. In this paper, a stochastic field model is developed to capture the uncertainty of cyclone wind speeds and their spatial correlation for the North Atlantic region. A series of recorded wind speed fields of historical cyclone events are examined. The bias values between the recorded wind speeds and computed wind speeds based on a widely used cyclonic wind field model are obtained. The statistics of the wind field bias are estimated using geostatistical tools. The effect of wind speed uncertainty and spatial correlation on performance assessment of distributed infrastructure systems is illustrated using an electric power system, where the metrics of performance are damage ratio, outage ratio and outage cost.

A height-resolving tropical cyclone boundary layer model with vertical advection process

The height-resolving model is thought to be an optimal scheme for modeling the tropical cyclone (TC) wind fields in the boundary layer because it explicitly depicts the wind structures in that layer as TC evolves over time. However, the vertical advection process which exists in TCs has not been well considered in previously proposed parametric TC models. Neglecting this process may cause deviations of the simulated wind field structure in the boundary layer. Herein, a height-resolving boundary layer wind field model incorporating both the vertical advection and vertical diffusion processes is proposed and a semi-analytical solution to the governing equations is developed. The adequacy of this model is evaluated by comparing with the Weather Research and Forecasting model simulations, the Hurricane Research Division’s H*Wind snapshots, GPS dropsonde datasets and ground measurements of several TC events. Results show that the proposed model with vertical advection can reasonably produce the wind fields of TCs, and its advantage lies in the production of a more realistic three-dimensional wind structure in the boundary layer.

The economic impacts of tropical cyclones on a mature destination, Florida, USA

Climatic hazards such as tropical cyclones pose multi-faceted threats to coastal tourism, inflicting physical damage to infrastructure, causing business interruption, and requiring the evacuation of tourists, not to mention the ensuing damage to the destination's image. Using the State of Florida, USA, as a case study, this research integrates GIS-based tropical cyclone wind swath data with industry-level monthly sales data in a cross-county panel to explore the differential impacts of these extreme weather events among inland and coastal destinations. This study uses secondary data collected by from the state of Florida and the US federal government to estimate revenue losses to 6 sectors in Florida's tourism economy due to tropical cyclones between 2008 and 2018. Based on the pooled sample of all counties, mean per county losses were estimated to be approximately $10 million during the month of the storm, $12 million in the first month post-storm, and $7 million in the second month post-storm. Coastal counties had mean estimated losses of approximately $12.5 million in the month of the storm and persistent effects for the following 2 months. Inland counties had estimated losses of approximately $7.5 million in the month of the storm and a positive recovery effect in the fourth ($1.6 million) and fifth ($2.7 million) months post-storm. These results suggest that Florida's coastal counties are most impacted by tropical cyclones in terms of tourism-related losses.

Projected future changes in tropical cyclone-related wave climate in the North Atlantic

Tropical cyclones are a major hazard for numerous countries surrounding the tropical-to-subtropical North Atlantic sub-basin including the Caribbean Sea and Gulf of Mexico. Their intense winds, which can exceed 300 km h−1, can cause serious damage, particularly along coastlines where the combined action of waves, currents and low atmospheric pressure leads to storm surge and coastal flooding. This work presents future projections of North Atlantic tropical cyclone-related wave climate. A new configuration of the ARPEGE-Climat global atmospheric model on a stretched grid reaching ~ 14 km resolution to the north-east of the eastern Caribbean is able to reproduce the distribution of tropical cyclone winds, including Category 5 hurricanes. Historical (1984–2013, 5 members) and future (2051–2080, 5 members) simulations with the IPCC RCP8.5 scenario are used to drive the MFWAM (Meteo-France Wave Action Model) spectral wave model over the Atlantic basin during the hurricane season. An intermediate 50-km resolution grid is used to propagate mid-latitude swells into a higher 10-km resolution grid over the tropical cyclone main development region. Wave model performance is evaluated over the historical period with the ERA5 reanalysis and satellite altimetry data. Future projections exhibit a modest but widespread reduction in seasonal mean wave heights in response to weakening subtropical anticyclone, yet marked increases in tropical cyclone-related wind sea and extreme wave heights within a large region extending from the African coasts to the North American continent.

Investigation of Black Carbon characteristics over southern ocean: Contribution of fossil fuel and biomass burning

Black Carbon (BC) is an absorbing aerosol which has significant impact on the Earth - Atmosphere radiation balance and hence on climate. The variation of BC mass concentration and contribution of fossil fuel and biomass burning have been investigated over the Indian ocean sector of the Southern Ocean during austral summer. BC mass was in the range of 300-500ngm-3 between 23.3oS to 24.5oS followed by decrease in BC to 150ngm-3 as moving to higher southern latitudes till 41oS latitude. An increase in BC mass from 250 to 450ngm-3 was found between 41 and 50oS due to trap of air masses by cyclonic wind and transport of aerosols from the southern part of African and eastern Madagascar regions. Higher BC concentration (250-350ngm-3) was observed in the latitude range of 57-60oS which can be attributed to convergence of north-westerly and south-easterly winds. The dominant contributor to BC was fossil fuel, which was > 80% during half of the total observations, while > 20% biomass burning contributed to one fifth of observations. The coastal Antarctic region showed higher BC mass concentration with mixed type of contributions of biomass and fossil fuel. Such accumulation of BC near the Antarctic coast can have a crucial impact on the sea-ice albedo which significantly affect the Antarctic climate system locally and global climate in general.

Long-term variability of Sea Surface Temperature in the Tropical Indian Ocean in relation to climate change and variability

Abstract The long-term change in the sea surface temperature (SST) of the Tropical Indian Ocean (TIO) and the underlying mechanisms are examined in detail by analysing multiple reanalysis datasets and historical simulations of a global climate model. A robust basin-wide warming signal was found in SST, with the highest long-term warming trend (~0.09 ± 0.015 °C decade−1) seen over the north-western and equatorial Indian Ocean regions. The robust warming trend of TIO SST is a dominant warming signal of the global tropical oceans and is largely in phase with similar warming in western Pacific and Atlantic Oceans. The central equatorial Indian Ocean and south TIO regions went through significant warming during recent decades. The weakened cross-equatorial flow and the associated cyclonic winds over the Arabian Sea region have resulted in equatorial westerlies with an enhanced loss of latent heat over the central and eastern equatorial Indian Ocean. The anomalous cyclonic wind stress curl, in turn, caused mixed layer stratifications in the western Indian Ocean. The advective heat transfer from the south-eastern Indian Ocean to the western Indian Ocean and reduced oceanic cooling by vertical processes, overcome the cooling by the net loss of surface heat fluxes, and favor surface warming the TIO.

Multi-Parameter Neural Network for Altimeter Tropical Cyclone Wind Speed Estimation

The ability of satellite altimeter to estimate wind speed in tropical cyclone condition has been investigated. In the extreme condition with higher spatio-temporal variation, the ocean-atmosphere interaction is very complex and makes the existing algorithm become an ill-posed solution. In such condition, the developed algorithm from single frequency backscatter and significant waves height were insufficient. Besides, wind speed estimates become saturated at high regimes and the reflected backscatter was contaminated by rain. Therefore, other simultaneously observed parameters are needed to comprehensively account for this condition and is expected to improve the accuracy of wind speed retrieval. Aside from altimeter instrument, the microwave radiometer onboard Jason-2 concurrently records the brightness temperature and the rain information. To accommodate related multiple parameters for wind speed derivation, the neural network approach is proposed. Its unique advantage is relationship among multi-parameters can be easily established without prior knowledge on their physical attributes. Therefore, this study intended to determine the multi-parameter neural network (MPNN) model in estimating altimeter wind speed during the tropical cyclone condition. The results proved that the MPNN technique has potential in reducing the root mean square error by 30% in comparison between tropical cyclone wind speed estimate by the existing algorithm.

Eco-Catastrophe in The Wind From Nowhere

Ecocriticism constitutes the fictional treatment of environmental problems. Climate Change is one of the biggest threats the world is facing today. There are alarming debates signaling constant fear of the grave consequences that can be triggered by the global warming. Newspapers are literally filled with articles on the topic of climate change. Sea levels are rising like anything and oceans are becoming warmer. The Wind From Nowhere is one of the insightful novels in the contemporary age where Ballard prophesizes the vision of an eco-catastrophe triggered by human induced global warming leaving earth totally unfit for human survival which can turn into reality anytime. The aim of this paper is to explore how Ballard portrays that vision of eco-catastrophe using the metaphor of cyclonic winds which create havoc all over the world. It also illustrates the creepy imageries and undertones of the catastrophic setting presented in the novel, in which people are reduced to beastly mode of survival. Particular emphasis is given on the psychological effects of the altered environment on the characters in the novel. Ballard portrays his characters to be trapped between an old dead world and a terrifying incomprehensible new one.

Contribution of precipitation events with different consecutive days to rainfall change over Asia during ENSO years

The present study investigates the contributions of four types of precipitation events with different consecutive days (1–3-day, 4–7-day, 8–14-day, and over-14 day) of precipitation to April–October rainfall anomalies over Asia and roles of the three factors (intensity, number, duration) in area-mean rainfall anomalies of four types of precipitation events in El Nino and La Nina years. It is found that precipitation tends to be below normal in the entire tropical and extratropical regions except for northeastern Asia and east and west Indochina Peninsula during El Nino years. During La Nina years, precipitation tends to increase in eastern China, India, the south hills of the Himalayas, west Indochina Peninsula-southwest China, and the Maritime Continent, but decreases in northeast China, east Kazakhstan, Afghanistan, and east Indochina Peninsula. The precipitation change at the low latitudinal regions has a larger contribution from the over-14-day events. The number of events is a main factor in changes of precipitation of primary events during El Nino years. The precipitation changes in El Nino and La Nina years are consistent with changes in the activity of cyclonic wind anomalies corresponding to the precipitation events. The intraseasonal wind anomalies leading to the precipitation events in China are preceded by northwestward move of cyclonic systems from the tropical western North Pacific that promotes the start of precipitation in the concerned regions. The present study points to the impacts of intraseasonal wind systems with various lifespans on precipitation changes over Asia in El Nino and La Nina years.

A semi-empirical method for computing storm surges on open coasts during tropical cyclones

A new semi-empirical storm surge prediction (SESSP) method is presented that computes tropical cyclone induced storm surge levels as a function of space and time for various storm and geometry input parameters. It distinguishes between five components that contribute to the total surge: the normal, parallel, radial, Ekman, and inverse barometer surge. The parallel surge (caused by shore-parallel gradients in the wind stress) and radial surge (resulting from wind set-up due to the inflow angle of cyclonic wind fields) have not been adequately reported upon before. The empirical relations are derived using the results of thousands of numerical model simulations in which synthetic storms are simulated at coasts with varying cross-shore topography. Non-linear fitting procedures are used to derive surge response functions (SRFs). The SESSP method reproduces peak surge levels within 10 percent of the values computed by the hydrodynamic model. This study showed variable surge response at different types of coast. On steep coasts, surge is dominated by the inverse barometer effect. Along intermediate and mild sloping coasts, the wind set-up has the greatest contribution to the peak surge. The Ekman surge (caused by the Coriolis effect) typically peaks several hours before landfall and can either have a positive or negative contribution to the peak surge. The radial surge becomes relatively more important on mild-sloping coasts. SESSP's computational efficiency allows for the execution of ensemble forecasts with thousands of synthetic storms along large stretches of coast.