High Wind Events Research Articles

Detection and characterization of aeolian sand strips on the beach using permanent laser scanning

Aeolian sand strips are bedforms that often form on the beach during high wind events. The sand strips can move across the beach resulting in sediment transport, but these sediment fluxes have not yet been quantified. Permanent laser scanning (PLS) provides an opportunity to gather long-term and detailed information about sand strips. Here, we present a method that detects sand strips in PLS reflectance images and extracts their wavelength, orientation, and height. The detection method is used on a month-long hourly dataset of Noordwijk beach, the Netherlands. The average sand strip wavelength (13 m), height (3 cm), and orientation (onshore-oblique) found in this dataset are consistent with previous research. Migration rates are obtained by examining successive images of sand strip patterns. Using the concurrent sand strip height, the sediment transport rate associated with sand strips is estimated. During a single 8-hour event, a total sediment flux of 0.16 m3/m is observed of which 0.07 m3/m in onshore direction. Furthermore, the detection method is shown to be applicable to other beaches by calibrating its thresholds. This opens a new possibility for future research to use PLS to investigate the behavior and sediment transport rates of aeolian sand strips.

Numerical modeling on wave–current flows and bed shear stresses over an algal reef

AbstractCurrents in coastal zones under multiple mechanisms in terms of tides, waves, wind, and high roughness are difficult to model; bed shear stresses under wave–current flows are particularly challenging yet not being well studied. Few studies reported the modeling and validation of the bed shear stress in reef environments. In this paper, we present the first direct assessment of numerical modeling on depth-averaged currents and bed shear stresses over an algal reef using a coupled wave–current model (Delft-3D). The modeled results were validated and compared to the field observed data. The model considers hydrodynamic forcing in terms of tides, waves, wind stresses, and bed friction. Results show that the model generally reproduces the depth-averaged currents and bed shear stresses when considering all the mechanisms. Two numerical cases with and without wind forcing were tested to examine the effects of the winds. We found that the tide is mostly the primary factor driving the current, even in shallow waters within a depth of 3 m; however, the currents are also significantly affected by wind speeds and wind directions during high-wind events. When the wind direction is in the same direction as the tidal current, the current speed increases, suggesting the importance of the wind stress on the coastal currents. In addition, two models were chosen to study the nonlinear enhancement of bed shear stress by waves. We found a significant difference between the two models in predicting the bed shear stresses compared to the observed data. Nonlinear contribution from wave enhances the magnitude of bed shear stresses, which reduces the model error. The results highlight the nonlinear interaction between waves and currents is meaningful in predicting the bed shear stresses during high-wave-orbital motions; improvement of the present wave-current nonlinear interaction model for predicting the bed shear stresses may be needed.

The Importance of Contemporaneous Wind and pCO2 Measurements for Regional Air‐Sea CO2 Flux Estimates

AbstractFew observational platforms are able to sustain direct measurements of all the key variables needed in the bulk calculation of air‐sea carbon dioxide (CO2) exchange, a capability newly established for some Uncrewed Surface Vehicles (USVs). Western boundary currents are particularly challenging observational regions due to strong variability and dangerous sea states but are also known hot spots for CO2 uptake, making air‐sea exchange quantification in this region both difficult and important. Here, we present new observations collected by Saildrone USVs in the Gulf Stream during the winters of 2019 and 2022. We compared Saildrone data across co‐located vehicles and against the Pioneer Array moorings to validate the data quality. We explored how CO2 flux estimates differ when all variables needed to calculate fluxes from the bulk formulas are simultaneously measured on the same platform, relative to the situation where in situ observations must be combined with publicly‐available data products. We systematically replaced variables in the bulk formula with those often used for local and regional flux estimates. The analysis revealed that when using the ERA‐5 reanalysis wind speed in place of in situ observations, the ocean uptake of CO2 is underestimated by 8%; this underestimate grows to 9% if the NOAA Marine Boundary Layer atmospheric CO2 product and ERA‐5 significant wave height are also used in place of in situ observations. Overall our findings point to the importance of collecting contemporaneous observations of wind speed and ocean pCO2 to reduce biases in estimates of regional CO2 flux, especially during high wind events.

Resolution Dependence of Extreme Wind Speed Projections in the Great Lakes Region

Abstract The effect of anthropogenic climate change on extreme near-surface wind speeds is uncertain. Observed trends are weak and difficult to disentangle from internal variability, and model projections disagree on the sign and magnitude of trends. Standard coarse-resolution climate models represent the fine structures of relevant physical phenomena such as extratropical cyclones (ETCs), upper-level jet streaks, surface energy fluxes, and land surface variability less skillfully than their high-resolution counterparts. Here, we use simulations with the NCAR Community Earth System Model with both uniform (110 km) resolution and the variable-resolution configuration (VR-CESM-SONT, from 110 to 7 km) to study the effect of refined spatial resolution on projections of extreme strong and weak wind speeds in the Great Lakes region under end-of-century RCP8.5 forcing. The variable-resolution configuration projects strengthening of strong-wind events in the refined region with the opposite occurring in the uniform-resolution simulation. The two configurations provide consistent changes to synoptic-scale circulations associated with high-wind events. However, only the variable-resolution configuration projects weaker static stability, enhanced turbulent vertical mixing, and consequentially enhanced surface wind speeds because boundary layer dynamics are better captured in the refined region. Both models project increased frequency of extreme weak winds, though only VR-CESM-SONT resolves the cold-season inversions and summertime high temperatures associated with stagnant wind events. The identifiable mechanism of the changes to strong winds in VR-CESM-SONT provides confidence in its projections and demonstrates the value of enhanced spatial resolution for the study of extreme winds under climate change. Significance Statement In this study, we compare climate change projections of high and low extreme wind speeds in the Great Lakes region between a standard coarse-resolution simulation and a high-resolution simulation performed using the same climate model. The fine-resolution simulation projects strengthening high wind speeds, opposite to the coarse-resolution simulation. Both project increasing frequency of extreme weak winds, but the human-health-related impacts of stagnant winds are only captured at fine resolution. The changes in the coarse-resolution simulation are explained by changes to large-scale circulation, while the fine-resolution changes are linked to local processes the coarse model does not resolve. This helps explain the diverging projections of strong winds and gives greater credibility to the fine-resolution simulation.

Storms facilitate airborne DNA from leaf fragments outside the main tree pollen season

Bioaerosols are useful indicators of plant phenology and can demonstrate the impacts of climate change on both local and regional scales (e.g. pollen monitoring/flowering phenology). Analysing bioaerosols with eDNA approaches are becoming more popular to quantify the diversity of airborne plant environmental DNA (eDNA) and flowering season of plants and trees. Leaf abscission from broadleaved trees and other perennial species can also indicate the status of plant health in response to climate. This happens primarily during autumn in response to seasonal growth conditions and environmental factors, such as changing photoperiod and reduced temperatures. During this period biological material is released in larger quantities to the environment. Here, rural bioaerosol composition during late summer and autumn was captured by MiSEQ sequencing of the rRNA internal transcribed spacer 2 (ITS2) region, a common marker for taxonomic variation. Meteorological parameters were recorded from a proximal weather station. The composition of atmospheric taxa demonstrated that deciduous tree DNA forms part of the bioaerosol community during autumn and, for several common broadleaved tree species, atmospheric DNA abundance correlated to high wind events. This suggests that both flowering and autumn storms cause bioaerosols from deciduous trees that can be detected with eDNA approaches. This is an aspect that must be considered when eDNA methods are used to analyse either pollen or other fragments from trees.

Heliostat Consortium: Gap Analysis on State of the Art in Wind Load Design

Abstract Wind loads are a major driver of heliostat cost. Standardized methods and tools are needed for a more detailed understanding of the static and dynamic loads of a heliostat design. This will enable cost reduction of wind-dependent heliostats to avoid unnecessarily conservative heliostat designs and increase field efficiency and reliability to reduce the risk of component failures due to high-wind events. Gaps related to wind load include lack of site characterization for wind measurements, insufficient critical load cases for heliostat design, insufficient understanding of turbulence impacts on heliostat tracking error, lack of knowledge on wind load under various heliostat array configurations, and underexplored heliostat field wind-load reduction and operating strategies. Recommended pathway forward is to develop wind load and site characterization guidelines for heliostat design and develop heliostat field wind-load models with optical performance impacts.

Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part I: Evaluation of Wind Speeds and Gusts

Abstract Strong wind events cause significant societal damage ranging from loss of property and disruption of commerce to loss of life. Over portions of the United States, the strongest winds occur in the cold season and may be driven by interactions with the terrain (downslope winds, gap flow, and mountain wave activity). In the first part of this two-part series, we evaluate the High-Resolution Rapid Refresh (HRRR) model wind speed and gust forecasts for the 2016–22 winter months over Wyoming and Colorado, an area prone to downslope windstorms and gap flows due to its complex topography. The HRRR model exhibits a positive bias for low wind speeds/gusts and a large negative bias for strong wind speeds/gusts. In general, the model misses many strong wind events, but when it does predict strong winds, there is a high false alarm probability. An analysis of proxies for surface winds is conducted. Specifically, 700- and 850-mb (1 mb = 1 hPa) geopotential height gradients are found to be good proxies for strong wind speeds and gusts at two wind-prone locations in Wyoming. Given the good agreement between low-level height gradients and surface wind speeds yet a strong negative bias for strong wind speeds and gusts, there is a potential shortcoming in the boundary layer physics in the HRRR model with regard to predicting strong winds over complex terrain, which is the focus of the second part of this two-part study. Last, the sites with the largest strong wind speed bias are found to mostly sit on the leeward side of high mountains, suggesting that the HRRR model performs poorly in the prediction of downslope windstorms. Significance Statement We investigate the performance of the High-Resolution Rapid Refresh (HRRR) model with respect to strong wintertime wind speeds and gusts over the complex terrain of Wyoming and Colorado. We show that the overall performance of the HRRR model is low with regard to strong wind speed and wind gust forecasts across the investigated winter seasons, with a large negative bias in predicted strong wind speeds and gusts and a small positive bias for weak wind speeds and gusts. The largest biases are found to be on the leeward side of high mountains, indicating poor prediction of downslope winds. This study also utilizes National Weather Service forecasting metrics to understand their performance with respect to strong wind forecasts, and we find that they provide skill in forecasting these events.

Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part II: Sensitivity of Surface Wind Speeds to Model Resolution and Physics

Abstract Strong wind events can cause severe economic loss and societal impacts. Peak winds over Wyoming and Colorado occur during the wintertime months, and in the first part of this two-part series, it was shown that the High-Resolution Rapid Refresh (HRRR) model displays large negative biases with respect to strong wind events. In this part of the study, we address two questions: 1) does increasing the horizontal resolution improve the representation of strong wind events over this region, and 2) are the biases in HRRR-forecasted winds related to the selected planetary boundary layer (PBL), surface layer (SL), and/or land surface model (LSM) parameterizations? We conduct Weather Research and Forecasting (WRF) Model simulations to address these two main questions. Increasing the horizontal resolution leads to a small improvement in the simulation of strong wind speeds over the complex terrain of Wyoming and Colorado. In general, changes in the PBL, SL, and LSM parameterizations show much larger changes in simulated wind speeds compared to increasing the model resolution alone. Specifically, changing from the Mellor–Yamada–Nakanishi–Niino scheme to the Mellor–Yamada–Janjić PBL and SL schemes results in nearly no change in the r2 values, but there is a decrease in the magnitude of the strong wind speed bias (from −12.52 to −10.16 m s−1). We attribute these differences to differences in the diagnosis of surface wind speeds and mixing in the boundary layer. Further analysis is conducted to determine the value of 1-km forecasts of strong winds compared with wind speed diagnostics commonly used by the National Weather Service. Significance Statement Motivated by prior studies showing low skill in the prediction of strong winds using state-of-the-art weather forecast models, in this study, we aim to investigate two questions: 1) does increasing the horizontal resolution improve the prediction of strong wind events over the complex terrain of Wyoming and Colorado, and 2) are the biases in High-Resolution Rapid Refresh (HRRR) forecasted winds related to the selected planetary boundary layer, surface layer, and/or land surface model parameterizations? We find that increasing the horizontal resolution provides a slight improvement in the prediction of strong winds. Further, considerable improvement in the prediction of strong winds is found for varying boundary layer, surface layer, and land surface parameterizations.

Dynamic response of conductors during transmission tower failure under downburst loads

The frequency of thunderstorm-related failures of transmission lines has increased globally as a result of climate change. Downbursts are one of the High Intensity Wind (HIW) events associated with thunderstorms that have a detrimental impact on transmission towers due to their localized and non-stationary nature. When one tower fails, the conductors are subjected to dynamic excitation induced by the movement of the attached points to the towers which increases the tension forces in the conductors. If the adjacent towers are unable to sustain the increased tension forces, a cascade failure of multiple towers along the line is formed. The study aims to identify the conductor response to a tower failure under downburst loads using nonlinear dynamic analysis. The reactions transferred to the adjacent towers due to the tower failure are reported as well. The effect of varying the downburst jet velocity and the failure location within the tower height are investigated. The results show that the conductor response to the dynamic excitation of the tower failure depends on the velocity of the tower movement, the magnitude of the transverse load on the conductors, and the failure location along the tower height. The tension forces in the conductors and the reactions at the adjacent towers increase considerably due to the tower failure that can cause the failure of the adjacent towers.

Heliostat Consortium: Gap Analysis on Wind Load for Achieving a Fully Competitive Heliostat Industry

The Heliostat Consortium (HelioCon) Wind Load Subtask was initiated with the aim of bringing research work pertaining to wind load measurement, characterization, and prediction taking place across several tasks, including Advanced Manufacturing, Components and Controls, and Field Deployment. The cross-cutting wind load subtopic in the HelioCon roadmap report [1] highlighted standardized methods and tools that are needed for a more detailed understanding of the static and dynamic loads on a heliostat. This will enable cost reduction of wind-dependent heliostat components to avoid unnecessarily conservative, overly constrained designs and increase field efficiency/reliability, to reduce the risk of component failures due to high-wind events (>15 m/s). Gaps related to heliostat wind load include site characterization for wind measurements, critical load cases for heliostat design, turbulence impacts on heliostat tracking error, testing of heliostat array configurations, understanding spatial variation of maximum loads across the solar field, and heliostat field layout and operating strategies. The recommended highest-priority pathway as first steps taken by HelioCon to address these gaps are to develop site characterization guidelines for heliostat design and field load measurements.

Dynamic properties of an aeroelastic transmission tower subjected to synoptic and downburst-like outflows

Electrical transmission towers can be vulnerable to high intensity non-synoptic wind events such as downbursts. This paper compares the wind-induced response of a single self-supported transmission tower subjected to experimentally produced downburst outflows and synoptic (i.e., atmospheric boundary layer (ABL)) winds. Wind tunnel tests were carried out on a 1:50 aeroelastic model of the tower. A similar mean wind speed was produced at 1/6th of tower height and tower height in the downburst and synoptic simulations, respectively. Lower drag coefficients were observed under downburst winds in comparison to synoptic winds for the case tested. Lower peak base shear and base moments were subsequently observed in the downburst case. However, the results indicate that the base dynamic response of a self-supported tower can be slightly higher under downburst wind loads in comparison to synoptic winds. Higher dynamic amplification factors (DAF) and deviations from the mean were observed in the base dynamic response to downburst winds in comparison to the synoptic case. This indicates that self-supported towers can be subjected to more wind-induced vibrations under downburst winds with similar peak wind speeds as the synoptic winds.

Downslope Windstorm Forecasting: Easier with a Critical Level, but Still Challenging for High-Resolution Ensembles

Abstract Strong downslope windstorms can cause extensive property damage and extreme wildfire spread, so their accurate prediction is important. Although some early studies suggested high predictability for downslope windstorms, more recent analyses have found limited predictability for such winds. Nevertheless, there is a theoretical basis for expecting higher downslope wind predictability in cases with a mean-state critical level, and this is supported by one previous effort to forecast actual events. To more thoroughly investigate downslope windstorm predictability, we compare archived simulations from the NCAR ensemble, a 10-member mesoscale ensemble run at 3-km horizontal grid spacing over the entire contiguous United States, to observed events at 15 stations in the western United States susceptible to strong downslope winds. We assess predictability in three contexts: the average ensemble spread, which provides an estimate of potential predictability; a forecast evaluation based upon binary-decision criteria, which is representative of operational hazard warnings; and a probabilistic forecast evaluation using the continuous ranked probability score (CRPS), which is a measure of an ensemble’s ability to generate the proper probability distribution for the events under consideration. We do find better predictive skill for the mean-state critical-level regime in comparison to other downslope windstorm–generating mechanisms. Our downslope windstorm warning performance, calculated using binary-decision criteria from the bias-corrected ensemble forecasts, performed slightly worse for no-critical-level events, and slightly better for critical-level events, than National Weather Service high-wind warnings aggregated over all types of high-wind events throughout the United States and annually averaged for each year between 2008 and 2019.

Quantifying spit growth and its hydrodynamic drivers in wind-dominated lake environments

Many sand spits are morphodynamically complex landforms, that are either analysed with complex and expensive computational models or at a conceptual level. Therefore, most case studies on spits in different environments are descriptive. A novel method based on the use of polar coordinates was devised to quantitatively analyse spit morphodynamics in a non-tidal, wind-dominated lake environment, using the Marker Wadden islands in Lake Markermeer, the Netherlands, as a case study. A high-resolution morphological data set allowed for the quantification of sedimentation processes around two spits, in two distinctive depth zones. Spit-platform growth is governed by alongshore currents that transport sediment over the spit-platform into deeper waters; the size of the spit-platform in turn affects the growth of the spit around the mean water level. Insight in this complex interplay of processes is crucial to understand spit behaviour in low-energy lake environments. At the Marker Wadden the submerged spit-platform grows during high energy wind events while the emerged spit part grows under mild to moderate energy conditions. With this new method we can quantitatively explore the role of different wave and flow conditions and predict spit growth direction in non-tidal, wind-dominated environments, beyond the level of conceptual descriptions.

Remotely sensed terrestrial open water evaporation

Terrestrial open water evaporation is difficult to measure both in situ and remotely yet is critical for understanding changes in reservoirs, lakes, and inland seas from human management and climatically altered hydrological cycling. Multiple satellite missions and data systems (e.g., ECOSTRESS, OpenET) now operationally produce evapotranspiration (ET), but the open water evaporation data produced over millions of water bodies are algorithmically produced differently than the main ET data and are often overlooked in evaluation. Here, we evaluated the open water evaporation algorithm, AquaSEBS, used by ECOSTRESS and OpenET against 19 in situ open water evaporation sites from around the world using MODIS and Landsat data, making this one of the largest open water evaporation validations to date. Overall, our remotely sensed open water evaporation retrieval captured some variability and magnitude in the in situ data when controlling for high wind events (instantaneous: r2 = 0.71; bias = 13% of mean; RMSE = 38% of mean). Much of the instantaneous uncertainty was due to high wind events (u > mean daily 7.5 m·s−1) when the open water evaporation process shifts from radiatively-controlled to atmospherically-controlled; not accounting for high wind events decreases instantaneous accuracy significantly (r2 = 0.47; bias = 36% of mean; RMSE = 62% of mean). However, this sensitivity minimizes with temporal integration (e.g., daily RMSE = 1.2–1.5 mm·day−1). To benchmark AquaSEBS, we ran a suite of 11 machine learning models, but found that they did not significantly improve on the process-based formulation of AquaSEBS suggesting that the remaining error is from a combination of the in situ evaporation measurements, forcing data, and/or scaling mismatch; the machine learning models were able to predict error well in and of itself (r2 = 0.74). Our results provide confidence in the remotely sensed open water evaporation data, though not without uncertainty, and a foundation by which current and future missions may build such operational data.

First Report of Fishkill Incidence in Bonny-Andoni Coastal Area, Nigeria

Abstract A fish kill is characterised by the death of a large number of fish in a given area within a short period of time. This is an indicator that water quality and ecosystem conditions in general have deteriorated. Remote sensing data from the MODIS instrument on the Aqua and Merra-2 satellites were accessed from 18 to 22 March 2020, a period that spans before and after the fish kill was reported. Analysis of the remote sensing data shows that the fish kill was preceded by strong winds, i.e. major and sustained wind events. The maps of sea surface temperatures prior to the fish kill show that high-temperature water masses flowed from the equator toward the Bonny-Andoni coast. The dates of occurrence of the high-temperature surface water masses and high wind events around the Bonny-Andoni coastal area were consistent with the location and timing of the fish kill, as indicated by community reports. We hypothesise that the low-oxygen, high-temperature surface water masses passing from the equator on the windward side of the coast may have encountered migrating croakers and trapped an entire school of this benthopelagic fish species, causing acute respiratory distress. The results and hypothesis confirm local reports of gasping fish about 2 nautical miles off the Bonny-Andoni coast. This study confirms the relationship between wind patterns, temperature, and fish kills, providing the first empirical account of probable causes. Because fish kills occur episodically and often leave no trace, this report and future analyses of remote sensing data may be the best way to elucidate this event.

Predicting wildfire ignition induced by dynamic conductor swaying under strong winds

During high wind events with dry weather conditions, electric power systems can be the cause of catastrophic wildfires. In particular, conductor-vegetation contact has been recognized as the major ignition cause of utility-related wildfires. There is a urgent need for accurate wildfire risk analysis in support of operational decision making, such as vegetation management or preventive power shutoffs. This work studies the ignition mechanism caused by transmission conductor swaying out to nearby vegetation and resulting in flashover. Specifically, the studied limit state is defined as the conductor encroaching into prescribed minimum vegetation clearance. The stochastic characteristics of the dynamic displacement response of a multi-span transmission line are derived through efficient spectral analysis in the frequency domain. The encroachment probability at a specified location is estimated by solving a classical first-excursion problem. These problems are often addressed using static-equivalent models. However, the results show that the contribution of random wind buffeting to the conductor dynamic displacement is appreciable under turbulent strong winds. Neglecting this random and dynamic component can lead to an erroneous estimation of the risk of ignition. The forecast duration of the strong wind event is an important parameter to determine the risk of ignition. In addition, the encroachment probability is found highly sensitive to vegetation clearance and wind intensity, which highlights the need of high resolution data for these quantities. The proposed methodology offers a potential avenue for accurate and efficient ignition probability prediction, which is an important step in wildfire risk analysis.

Climate change on extreme winds already affects off-shore wind power availability in Europe

Off-shore wind energy in Europe plays a key role in the transition to renewable energy, and its usage is expected to increase in the next few decades. According to the working regimes of a wind turbine, wind energy production can be disrupted by extreme atmospheric events related to low wind speed below the cut-in wind speed and high wind speed above the cut-out wind speed. The purpose of this work is to estimate the behavior of extreme winds on the European panorama, over the period 1950–2020, in order to investigate the large-scale weather regimes related to them and their impact on off-shore wind energy availability. We detected significant changes in the frequency of high and low extreme wind events, proving that climate change or long-term internal climate variability have already affected the off-shore wind power output. Moreover, the analysis of weather regimes showed that high and low extreme wind events can occur simultaneously over Europe. Our results suggest the necessity to implement efficient European energy management policies, to minimize the deficit in wind power supply.

Random Forest Approach for Improving Nonconvective High Wind Forecasting across Southeast Wyoming

Abstract High winds are one of the key forecast challenges across southeast Wyoming. The complex mountainous terrain across the region frequently results in strong gap winds in localized areas, as well as more widespread bora and chinook winds in the winter season (October–March). The predictors and general weather patterns that result in strong winds across the region are well understood by local forecasters. However, no single predictor provides notable skill by itself in separating warning-level events from others. Random forest (RF) classifier models were developed to improve upon high wind prediction using a training dataset constructed of archived observations and model parameters from the North American Regional Reanalysis (NARR). Three locations were selected for initial RF model development, including the city of Cheyenne, Wyoming, and two gap regions along Interstate 80 (Arlington) and Interstate 25 (Bordeaux). Verification scores over two winters suggested the RF models were beneficial relative to current operational tools when predicting warning-criteria high wind events. Three case studies of high wind events provide examples of the RF models’ effectiveness to forecast operations over current forecast tools. The first case explores a classic, widespread high wind scenario, which was well anticipated by local forecasters. A more marginal scenario is explored in the second case, which presented greater forecast challenges relating to timing and intensity of the strongest winds. The final case study carefully uses Global Forecast System (GFS) data as input into the RF models, further supporting real-time implementation into forecast operations.

Winds at the Mars 2020 Landing Site. 2. Wind Variability and Turbulence.

Wind speeds measured by the Mars 2020 Perseverance rover in Jezero crater were fitted as a Weibull distribution. InSight wind data acquired in Elysium Planitia were also used to contextualize observations. Jezero winds were found to be much calmer on average than in previous landing sites, despite the intense aeolian activity observed. However, a great influence of turbulence and wave activity was observed in the wind speed variations, thus driving the probability of reaching the highest wind speeds at Jezero, instead of sustained winds driven by local, regional, or large-scale circulation. The power spectral density of wind speed fluctuations follows a power-law, whose slope deviates depending on the time of day from that predicted considering homogeneous and isotropic turbulence. Daytime wave activity is related to convection cells and smaller eddies in the boundary layer, advected over the crater. The signature of convection cells was also found during dust storm conditions, when prevailing winds were consistent with a tidal drive. Nighttime fluctuations were also intense, suggesting strong mechanical turbulence. Convective vortices were usually involved in rapid wind fluctuations and extreme winds, with variations peaking at 9.2 times the background winds. Transient high wind events by vortex-passages, turbulence, and wave activity could be driving aeolian activity at Jezero. We report the detection of a strong dust cloud of 0.75-1.5km in length passing over the rover. The observed aeolian activity had major implications for instrumentation, with the wind sensor suffering damage throughout the mission, probably due to flying debris advected by winds.

Numerical investigation and design of crest-fixed corrugated steel claddings under static wind uplift loading

When crest-fixed corrugated steel roof claddings are subjected to wind uplift loading, local dimpling failures occur prematurely at their screwed connections because of the large stress concentrations around the fastener holes. Once the screwed crests are locally dimpled, high wind events such as storms and cyclones can cause severe fatigue cracking and pull-through failures, leading to the loss of entire corrugated roof cladding. Therefore, the pull-through capacity is an important parameter governing the wind uplift strength of corrugated roof claddings. This paper presents the details of a numerical investigation of the local dimpling behaviour of corrugated claddings under static wind uplift loading. It includes the details of the developed finite element model and validation, an extensive parametric study, and the results including a design equation to determine the pull-through capacity of crest-fixed corrugated cladding.