Regional Wind Research Articles

New Zealand Country Report 2021

This paper summarises the activities that have taken place in wind engineering in New Zealand since 2012 when the previous APEC-WW took place in Hanoi, Vietnam. Since that date there have been considerable activities in wind engineering in New Zealand, ranging from an increase in government funding for wind hazard research, an analysis of historical wind data throughout New Zealand which has been used to update the regional wind speeds and directional multipliers for the 2021 version of the wind loading standard, and the construction of a large boundary layer wind tunnel with a computer-controlled three dimensional traversing rig at the University of Auckland that has allowed extensive wind tunnel investigations to be carried out. In addition, this period has seen a strong link to Chinese universities develop through CSC-funded research students that have come to study in New Zealand. Finally, the very successful 9th Asia-Pacific Conference on Wind Engineering (APEC-WW) was held at the University of Auckland in December 2017.

Effect of Land Use/Cover Change on Soil Wind Erosion in the Yellow River Basin since the 1990s

“Ecological conservation and high-quality development of the Yellow River Basin” is one of the fundamental national strategies related to national food security and ecological security in China. Evaluating the impact of land use/cover change (LUCC) on soil erosion is valuable to improving regional ecological environments and sustainable development. This study focused on the Yellow River Basin and used remote sensing data, the soil wind erosion modulus (SWEM) calculated with the revised wind erosion equation (RWEQ), to analyze the impact of regional scale LUCC from 1990 to 2018 on soil wind erosion. The main conclusions are as follows: (1) The total area of cultivated land, grass land, and unused land decreased, with a total reduction of 11,038.86 km²; total areas of forest land and built-up areas increased, increased by 2746.61 and 8356.77 km2, respectively, with differences within the region in these LUCC trends at different periods. From 1990 to 2000, the area of cultivated land increased by 1958.36 km2 and built-up land area increased by 1331.90 km2. The areas of forestland, grass land, water area, and unused land decreased. From 2000 to 2010, the area of cultivated land and grass land decreased by 4553.77 and 2351.39 km², respectively, whereas the areas of forestland and built-up land significantly increased. From 2010 to 2018, the area of cultivated land and grass land continued to decrease, and the area of built-up land continued to increase. (2) Since the 1990s, the SWEM has generally declined (Slope1990–2018 = −0.38 t/(ha·a)). Total amount of wind erosion in 2018 decreased by more than 50% compared with the amount in 1990. During this period, the intensity of wind erosion first increased and then decreased. In terms of the SWEM, 90.63% of the study area showed a decrease. (3) From 1990 to 2018, LUCC reduced the total amount of soil wind erosion by 15.57 million tons. From 1990 to 2000, the conversion of grass land/forest land to cultivated land and the expansion of desert resulted in a significant increase in soil wind erosion. From 2000 to 2018, the amount of soil wind erosion decreased at a rate of about 1.22 million tons/year, and the total amount of soil wind erosion decreased by 17.8921 million tons. During this period, the contribution rate of ecological programs (e.g., conversion of cultivated land to forest land and grass land, ecological engineering construction projects, etc.) to reduction of regional soil wind erosion was 59.13%, indicating that ecological programs have a positive role in reducing soil wind erosion intensity. The sustainable development of the ecological environment of the Yellow River Basin should be continued through strengthening ecological restoration and protection, to further consolidate gains made in this fragile ecosystem. This study provides scientific and technological support and relevant policy recommendations for the sustainable development of the Yellow River ecosystem under global change.

Global forestation and deforestation affect remote climate via adjusted atmosphere and ocean circulation

Forests can store large amounts of carbon and provide essential ecosystem services. Massive tree planting is thus sometimes portrayed as a panacea to mitigate climate change and related impacts. Recent controversies about the potential benefits and drawbacks of forestation have centered on the carbon storage potential of forests and the local or global thermodynamic impacts. Here we discuss how global-scale forestation and deforestation change the Earth’s energy balance, thereby affect the global atmospheric circulation and even have profound effects on the ocean circulation. We perform multicentury coupled climate model simulations in which preindustrial vegetation cover is either completely forested or deforested and carbon dioxide mixing ratio is kept constant. We show that global-scale forestation leads to a weakening and poleward shift of the Northern mid-latitude circulation, slows-down the Atlantic meridional overturning circulation, and affects the strength of the Hadley cell, whereas deforestation leads to reversed changes. Consequently, both land surface changes substantially affect regional precipitation, temperature, clouds, and surface wind patterns across the globe. The design process of large-scale forestation projects thus needs to take into account global circulation adjustments and their influence on remote climate.

Where is the most feasible, economical, and green wind energy? Evidence from high-resolution potential mapping in China

China has ambitious renewable energy development plans after undergoing a rapid development phase for wind power. China's prospects for wind development affect the global decarbonization path. The question of where to deploy turbines of this magnitude to achieve technical feasibility, high economic competitiveness, and high emission reduction has become an urgent issue for China. Due to regional differences in wind resources and economic development, the deployment of wind power in China requires clarity on the likely siting and investment costs. It requires an accurate assessment of the exploitable possibilities of wind energy resources in China, which provides practical solutions for national and regional wind energy development. In this study, a multi-potential assessment was developed to estimate the feasibility and emission reduction contribution of wind power using a combined GIS-based approach and learning curves. It is found that there are large areas of land and ocean available for wind farms in China, especially the desert in the northwest and the coastal area of Fujian province. The technical potential of onshore and offshore wind power is 8650.33 TWh/yr and 11298.9 TWh/yr, respectively. Moreover, 76.06% and 20.69% of onshore and offshore wind, respectively, could be supplied economically. The optimal areas for building onshore wind by 2030 are located in Inner Mongolia, Gansu, and Xinjiang, while the optimal construction area for offshore wind power is mainly the coastal area of Fujian. Wind energy has a large potential to meet China's electricity demand and is set to be more cost-competitive as time passes. The cost of onshore and offshore wind will decrease by 25–53% and 21–46%, respectively, by 2030. Wind development could contribute 7823.73–10723.50 Mt CO2 reduction during 2021–2030, which could help decarbonize China's energy system.

Regional winds over the Iberian Peninsula (Cierzo, Levante and Poniente) from high‐resolution COSMO‐REA6 reanalysis

AbstractCierzo in the Ebro Valley and Levante and Poniente in the Strait of Gibraltar are three of the main winds over the Iberian Peninsula. However, their study is difficult due to the limited amount of observational data and available literature. In addition, current reanalysis products do not usually have sufficient resolution, generally greater than 10 km, to capture the orographic characteristics of these winds. In this study we explore the ability of high‐resolution COSMO‐REA6 reanalysis (6 km, 0.055°) to describe Cierzo, Levante and Poniente using HadISD observational data validation whenever it was possible. A numerical definition according to the characteristics of these winds is proposed through speed and directional range thresholds. Regional winds statistics, annual cycles, wind roses and covered areas are calculated. The results show a reasonable agreement between reanalysis and observations, with an annual average of 95 Cierzo days, and around 80 Levante and Poniente days for the whole period. These windy days typically extend around 21,000 km2 (or 600 reanalysis cells). Both extension and number of days present strong annual cycles and interannual variability. Several weather regimes associated to those regional wind days are obtained, in agreement with other comparable studies. Therefore, the study shows the capability of the high‐resolution COSMO‐REA6 reanalysis to capture and describe regional winds such as Cierzo, Levante and Poniente.

Method to describe the distribution of wind velocity and its application in wind resource evaluation

AbstractA convenient and effective method based on vector analysis was proposed in this paper to quantitatively describe the pattern of the wind speed distribution curve. This method can accurately describe the steepness of the single‐peak curve by using two parameters of concentration degree (CD) and concentration period (CP). Through the analysis of wind speed data in China over the past 40 years, this paper found that regional wind resources with larger CD were poorer, while regional wind resources with larger CP were richer. In addition, there were obvious cubic relationships between the CP and the average wind power density. These two parameters could reflect the richness of wind energy and realize the comparisons of wind resources across time and scales. In comparison with conventional approaches, this method is simpler and avoids fitting process, which has broad promotion prospects in the field of power grids.

Passive Environmental Control at Neighborhood and Block Scales for Conservation of Historic Settlements: The Case Study of Huatzai Village in Wang-An, Taiwan

Climate change has gradually become a great challenge for heritage conservation. This study demonstrated that a hierarchal strategy corresponding to the scale of climate or weather date can be an alternative approach to making heritage conservation more efficient and sustainable. Therefore, the passive environmental control strategies at neighborhood and block scales are developed to effectively connect climate actions, normally at global or city scales, and the traditional preservation methods at building scale. The research results reflect the same conclusion as previous studies in that wind is the key factor affecting degradation mechanisms on heritage assets. Moreover, the adoption of weather data is a critical factor that influences the accuracy of computational fluid dynamics (CFD) simulation results of the detailed regional wind performance, which is supportive for strategy development. According to the simulation results, the study site, Huatzai village, with neighborhood-scale strategy can gain an improvement in overall wind impact. The velocity reduction is more than 70% in the windward areas. The block-scale strategy with the reuse of existing structures can bring 90% velocity reduction for the wake areas and the high-risk zones with strong turbulence.

Is local grid parity affordable in China? Discussion on the regional wind power potential and investment returns under policy uncertainty

In China, achieving grid parity is critical for a low-cost carbon-neutral transition over the next decades. However, it may post investment dilemma in renewable energy, given the significant differences in resource endowment across various regions. In this paper, we quantify the regional wind resource endowment and evaluate the impact of different grid parity scenarios on regional wind power investments, including long-term contracts with fixed prices, free contracts with decreasing prices and the marketisation of the electricity market. The results show that while the wind power investment returns decrease in all regions with the feed-in tariff degression, the regions in west China with less developed economies are more affected. Additionally, the regional wind power investment return significantly and positively correlates with the regional wind power potential, but the degree of correlation decreases with the increase of electricity price uncertainty. Regions with abundant wind power resources, such as Inner Mongolia, Xinjiang and Gansu, cannot guarantee a sufficient return on investment when the uncertainty of electricity prices increases. It is suggested that alternative support schemes (e.g., long-term contract) and safeguard policies should be designed to reduce the uncertainty of electricity prices and offset the investment incentives created by subsidies (especially in western regions).

A statistical analysis of the distribution of convective windstorms and their radar characteristics in Hubei Province, China. Part 2

A statistical analysis of the distribution of convective windstorms and their radar characteristics in Hubei Province, China. Part 2

Short term wind power prediction for regional wind farms based on spatial-temporal characteristic distribution

Accurate regional wind power prediction is of great significance to the wind farm clusters integration and the economic dispatch of the regional power grid. The complex spatiotemporally coupled characteristics between multiple wind farms bring challenges to wind power prediction (WPP) of regional wind farm clusters. In this context, this paper proposes a regional WPP method using spatiotemporally multiple clustering algorithm and hybrid neural network to learn the potential spatial-temporal dependencies of regional wind farms. In which, a long-term daily power curve similarity method is proposed to identify spatially correlative wind power plants in long-term. Furthermore, the spatio-temporal wind farm sub-clusters are dynamically recognized by the similar fluctuation trend of short-term power sequences. On this basis, a spatial-temporal integrated prediction model consisting of the improved convolutional neural network (I–CNN) and the bidirectional long short-term memory (BILSTM) network is established for spatio-temporal sub-cluster based on point clouds distribution. Finally, the effectiveness of the proposed regional wind power forecasting framework is validated by using the Wind Integration National Dataset Toolkit, and the results show that the method improves accuracy effectively.

Non-Gaussian multivariate statistical monitoring of spatio-temporal wind speed frequencies to improve wind power quality in South Korea.

The spatial and temporal variability of renewable energy resources, particularly wind energy, should be statistically evaluated to achieve sustainable economic development to mitigate climate change. In this study, a non-Gaussian multivariate statistical monitoring approach is proposed to investigate the wind speed frequencies across different regions of South Korea. Anemometer data were first collected in 11 different provinces of South Korea with hourly resolution for one year. The best-of-fit for the corresponding distribution function was identified to characterize the behavior of the wind speed frequency at each region among more than 60 candidate functions using the chi-squared test. Furthermore, a non-Gaussian multivariate statistical monitoring method based on the Hotelling T2 chart was developed to spatially and temporally analyze the physical patterns of the wind speed frequencies using the estimated distribution parameters. Then determination rule of cut-in and cut-out speeds of wind turbine was suggested to improve the wind power quality across the regions. The results indicated that Weibull and Gamma distributions are best-of-fit functions of each province in South Korea; the physical patterns of wind including the average wind speed and gale can be identified by distribution parameters. Furthermore, the proposed non-Gaussian multivariate monitoring approach can elucidate the spatial and temporal variability of the regional wind speed frequencies, including the average wind speeds and extreme wind events across South Korea. Based on the statistically identified variability of wind behavior, the wind power quality of wind turbines can be improved by 12% on average by adjusting the cut-in and cut-off speed. Thus, the proposed non-Gaussian multivariate monitoring approach can provide practical guidelines for manufacturers to achieve reliable wind energy generation by considering the spatial and temporal wind behavior.

Short-term regional wind power forecasting based on spatial–temporal correlation and dynamic clustering model

Short-term regional wind power forecasting (WPF) is essential for enhancing the power grid’s robustness. In the field of regional short-term power forecasting, numerical weather forecasts (NWP) and regional wind-power historical data have been commonly used in power forecasting. In this paper, a regional wind power prediction model based on the spatial and temporal correlation of meteorological resources is proposed to predict the wind power in the next seven days. First, combining variational mode decomposition and Granger causality test (VMD-GCT) to analyze the NWP-related meteorological factors to the wind power components in different bands to obtain the screening of the NWP-related factors. Then, the correlation analysis technique, which uses the physical characteristics of the wind speed time lag in a region, dynamically analyzes the spatial correlation time lag between a wind farm in the region and other wind farms, and uses the DBSCAN (density-based spatial clustering of applications with noise) algorithm to dynamically divide wind power clusters in the wind power forecast cycle, thus laying the foundation for the input data of the prediction model. Finally, the short-term power forecasting in the region is performed by a combined deep learning model. The results show that the proposed method can significantly improve the accuracy and efficiency of the wind power prediction for clusters at different wind speeds. The proposed method is of great significance for the short-term prediction of wind power in a region.

Analysis of Spatial and Temporal Variations of the Near-Surface Wind Regime and Their Influencing Factors in the Badain Jaran Desert, China

Wind regime is one of the main natural factors controlling the evolution and distribution of aeolian sand landforms, and sand drift potential (DP) is usually used to study the capacity of aeolian sand transport. The Badain Jaran Desert (BJD) is located where polar cold air frequently enters China. Based on wind data of eight nearby meteorological stations, this research is intended to explore the temporal variation and spatial distribution features of wind speed and DP using linear regression and cumulative anomaly method, and reveal the relationship between atmospheric circulation and wind speed with correlation analysis. We found that the wind speed and frequency of sand-blowing wind in the BJD decreased significantly during 1971–2016, and the wind speed obviously mutated in 1987. The regional wind speed change was affected by the Asian polar vortex, the northern hemisphere polar vortex and the Tibet Plateau circulation. The wind rose of the annual sand-blowing wind in this region was the “acute bimodal” type. Most of the annual wind directions clustered into the W-NW, and the prevailing wind direction was WNW. During 1971–2016, the annual DP, the resultant drift potential (RDP) and the directional variability (PDP/DP) in the desert showed an obvious downtrend, with a “cliff-like” decline in the 1980s and relative stable fluctuation thereafter. The BJD was under a low-energy wind environment with the acute bimodal wind regime. Wind speed, sand-blowing wind frequency and DP were high in the northeast and low in the southwest.

Application of a Wind Environment Simulation Generation Technology in Urban Planning

With the acceleration of urbanization, cities have shown a development trend of high density, high height, and high intensity, which significantly weakens the airflow in the city, resulting in the accumulation of heat and pollutants, and in the urban environment, the problem is getting worse. Therefore, it is particularly necessary to strengthen urban ventilation in the urban environment. However, in the real urban environment, the building layouts are diverse, the building forms are different, and the interaction of the building wind environment is complex due to the lack of relevant research on the complex building spatial form in the urban mesoscale area on the outdoor pedestrian. The research results are difficult to be applied in actual urban construction, and it is difficult to guide the optimization of the urban wind environment. To solve this problem, this paper adopts the CFD method in a real-scale (1 : 1) urban mesoscale regional wind environment simulation study. On this basis, the influencing factors of the urban pedestrian wind environment are analyzed, and the optimization strategy of the wind environment is proposed, which can provide practical guidance for the planning practice of enhancing urban wind comfort.

Morphological changes and dynamic mechanism of blowouts on fixed dunes in the Otingdag sandy land, China

<p indent="0mm">Blowouts are a major indicator of fixed dune reactivation, and their continuous occurrence and expansion aggravate the process of regional desertification. Therefore, research on the morphological evolution and dynamic processes of blowouts is paramount not only to understanding reactivation processes in stabilized and semistabilized dune fields but also to accurately assessing regional desertification trends. At present, much research has focused on blowouts in coastal dunes and flat grasslands, and little research has focused on the evolution mode of blowouts that have developed on fixed dunes in semiarid inland areas. Moreover, the morphological changes and airflow dynamics of blowouts are usually analyzed separately, and research integrating the two is still insufficient. In this paper, a fixed dune on the southern edge of the Otingdag sandy land was selected as the research object. A high precision real-time kinematic global positioning system (RTK-GPS) and 17 2D ultrasonic anemometers were used to measure the topography and airflow of four blowouts with different morphologies on the fixed dunes, and the multiperiod imaging data and multiyear meteorological data were used to monitor the morphological changes of each type of blowout and the regional meteorological conditions. The goal of this research is to reveal the morphological evolution, erosion-accumulation characteristics and airflow distribution patterns of each type of blowout and to discuss the relationship among the topography of fixed dunes, morphology of various blowouts and airflow variation. The results showed that the length, width and area of each type of blowout continued to increase from 2010 to 2021, and the overall shapes of each type of blowout tend to be oval or trough-shaped. The expansion direction of the blowout shape has a general corresponding relationship with the erosion-accumulation pattern in the deflation basin. The eastern and southeastern edges of the deflation basins are the most severely eroded, and their overall shapes expand from west to east. Relative to the wind direction of the field reference station, the approaching wind direction of the blowouts hardly deflects at the foot of the windward slope of the fixed dune, while it deflects significantly at the middle and top of the fixed dune, and the deflection angle changes with the regional wind direction. Both the blowout shapes and the approaching wind directions determine the airflow pattern within the blowouts. Based on a detailed analysis of both the regional climate and the morphological changes in blowouts, this study considered that the effect of the topography of fixed dunes on regional airflow could be the fundamental reason for the morphological differences in blowouts. The shape of blowouts determines the airflow pattern in the deflation basin, and the change in the wind speed and wind direction in turn affects the erosion-accumulation pattern and finally changes the evolution direction of blowouts. The research results can act as a good supplement for studying blowouts in semiarid inland areas.

Long-term investigation of morphodynamic variations of a tidal inlet by remote sensing: A case study of the Meidani Inlet, Hormozgan, Iran

Barrier-island inlets are among the most common inlets worldwide. The variation of the inlets, different sediment bypassing mechanisms, and lack of data are some issues for using numerical modeling in all cases. Remote sensing techniques are helpful for analytical investigation and making time series of the study area for categorizing the inlets and defining the morphological processes. The current study employs a feasible method for investigating tidal inlets, evaluates the morphodynamic changes, and applies the method to the Meidani Inlet in Iran. In this study, Landsat images from 1972 to 2019 were acquired and corrected to investigate changes in the ebb-tidal delta by employing the shoreline determination method, performing bathymetry in shallow areas, evaluating the extracted profiles in specific locations within the ebb-tidal delta, and comparing the Landsat image series at various times (change detection). In order to illustrate the morphological changes during the study period, a conceptual model was proposed. The conceptual model presents three reiterated actions of the ebb-tidal delta that varied from 15–25 years due to different environmental conditions. Regional waves, tidal, and wind data were analyzed in detail using Landsat image intervals to investigate the effects of factors causing changes and instability in the cyclic morphodynamic behavior of the Meidani Inlet and characterize the region’s environmental behavior pattern. By employing the method mentioned above, preparing a temporal inlet channel profile and sedimentation trend in the ebb-tidal delta, the Meidani Inlet is determined to be a mixed-energy inlet and a possibility of long-term behavior is predicted. Eastward main inlet channel and the whole ebb-tidal delta migration is the strongest possibility based on the remote sensing investigation over the investigated period.

Regional Potential Wind Erosion Simulation Using Different Models in the Agro-Pastoral Ecotone of Northern China.

Wind erosion is crucial for assessing regional ecosystem services and sustainable development. The Agro-Pastoral Ecotone of northern China (APEC) is a typical region undergoing wind erosion and soil degradation. In this study, the National Wind Erosion Survey Model of China, the Integrated Wind Erosion Modeling System, and the regional versions of the Revised Wind Erosion Equation and Wind Erosion Prediction System were used to evaluate the regional potential wind erosion of the APEC during 2000 and 2012. The results showed that the potential wind erosion predicted by National Wind Erosion Survey Model of China (NWESMC), Revised Wind Erosion Equation (RWEQ), Wind Erosion Prediction System (WEPS), and Integrated Wind Erosion Modeling System (IWEMS) were significantly related to the observed wind erosion collected from published literature, but the observed data were generally smaller than the predicted values. The average potential wind erosions were 12.58, 25.87, 52.63, and 58.72 t hm−2 a−1 for NWESMC, RWEQ, WEPS, and IWEMS, respectively, while the spatial pattern and temporal trend of annual potential wind erosion were similar for different wind erosion models. Wind speed, soil moisture, and vegetation coverage were the dominant factors affecting regional wind erosion estimation. These results highlight that it is necessary to comprehensively calibrate and validate the selected wind erosion models. A long-term standard wind erosion monitoring network is urgently required. This study can serve as a useful reference for improving wind erosion models.

The Effect of Regional Winds on Subtidal Along‐Inlet Currents at Oregon Inlet, NC

AbstractWind influence on tidal inlet hydrodynamics is examined using 40 days of wind, water level, and current observations collected in Spring 2019 at Oregon Inlet, NC, a large (1 km wide, 1–13 m deep) meso‐tidal inlet with complex delta systems. Wind velocities through the inlet (ranging 0–18 m/s) are modulated at subtidal timescales and are well correlated (R = 0.87) to a subtidal component of the water level slope through the inlet. The subtidal wind and water level slope are also well correlated to the subtidal current along the principal flow axis in the main inlet channel (R = 0.92 and 0.96, respectively). In combination with findings from previous studies, these findings suggest that regional winds induce the subtidal water level slope through the inlet by causing opposing setup/setdown to either side of the inlet. A force balance at the inlet demonstrates that the wind‐induced pressure gradient forces the subtidal currents, with wave forcing and local wind shear acting as lower‐order influences. The magnitude of the subtidal current is substantial, exceeding that of the tidal currents 45% of the time. Cumulatively, these findings indicate that regional winds exert a first‐order control on the currents at Oregon Inlet and cause irregular hydrodynamic patterns not well described by the traditional inlet classification scheme. Regional geographic characteristics may contribute to the high level of wind influence at Oregon Inlet, but similar processes are likely to be important to net flow dynamics at other inlets with large, shallow inland water bodies.

A simplified seasonal forecasting strategy, applied to wind and solar power in Europe

We demonstrate levels of skill for forecasts of seasonal-mean wind speed and solar irradiance in Europe, using seasonal forecast systems available from the Copernicus Climate Change Service (C3S). While skill is patchy, there is potential for the development of climate services for the energy sector. Following previous studies, we show that, where there is skill, a simple linear regression-based method using the hindcast and forecast ensemble means provides a straightforward approach for producing calibrated probabilistic seasonal forecasts. This method extends naturally to using a larger-scale feature of the climate, such as the North Atlantic Oscillation, as the climate model predictor, and we show that this provides opportunities to improve the skill in some cases.We further demonstrate that, on seasonal-average and regional (e.g. national) average scales, wind and solar power generation are highly correlated with single climate variables (wind speed and irradiance). The detailed non-linear transformations from meteorological quantities to energy quantities, which are essential for detailed simulation of power system operations, are usually not necessary when forecasting gross wind or solar generation potential at seasonal-mean regional-mean scales.Together, our results demonstrate that where there is skill in seasonal forecasts of wind speed and irradiance, or a correlated larger-scale climate predictor, skilful forecasts of seasonal mean wind and solar power generation can be made based on the climate variable alone, without requiring complex transformations. This greatly simplifies the process of developing a useful seasonal climate service.

The Aeolian Environment in Glen Torridon, Gale Crater, Mars

AbstractThe Mars Science Laboratory (MSL) rover spent a full martian year exploring the phyllosilicate‐bearing Glen Torridon trough on the flank of Aeolis Mons in Gale crater, enabling in‐depth assessment of aeolian processes. MSL encountered erosional and depositional features recording a long aeolian history. The trough has served as a long‐term conduit for sand transport, probably involving many cycles of sand accumulation and deflation. Rock abrasion textures indicate sand‐driving winds blowing W‐SW (opposite of abrasion textures on the Greenheugh Pediment above the trough floor). Indurated megaripple surfaces with 2–5 mm grains contrast with seasonally active ripples having finer maximum grain sizes, indicating more vigorous saltation in the past. Active ripples display a broad continuum of wavelengths, as well as coarser grains at crests than troughs, consistent with origins as impact ripples. Orientations of a wind streak extending from a large ripple field, and sandy wind tails behind obstacles, indicate sand is driven W‐SW in the current era, approximately along the trough axis. Erosion of drill tailings piles was strongly seasonal, enhanced during late spring and early summer (perihelion). Climate modeling suggests W‐SW sand transport can be attributed to seasonal enhancement of nighttime regional winds entering Gale crater from the N, combined with local katabatic winds flowing down the slopes of Aeolis Mons. However, it is unclear whether sand transport at Glen Torridon is primarily from these wind components combining and acting simultaneously, or occurring in serial at different times of night; field evidence supports both possibilities.