Severe Windstorms Research Articles

The Impact of Salvage Logging on Deadwood Decomposition and Forest Regeneration: A Case Study in Tatra National Park, Slovakia

In November 2004, a severe windstorm destroyed large portions of the spruce-dominated forests in the Tatra National Park (northern Slovakia). This study focused on the status of deadwood and its influence on post-disturbance forest regeneration 18 years after the destruction. Since some disturbed areas were salvaged and others were not, we could compare the situations between these two management approaches. Therefore, 40 research sites (20 salvaged and 20 unsalvaged) were analyzed; each contained four satellite plots, i.e., circle-like areas with a radius of 3 m. We measured the diameter of deadwood and its decay status (classes 1–5) and recorded the sizes (stem base diameter and height) as well as species of young trees. Our results showed that while salvage conditions and contact with soil stimulated deadwood decomposition, the diameter of logs was not a significant factor. The highest decay class (3.83) was found in deadwood in salvaged areas and touching the soil, while the lowest decay class (3.10) was found in deadwood in unsalvaged areas and in the case of logs not touching the soil. Although carbon content (based on the percentage of wood mass) did not change with the decay class, wood density decreased sharply with decay, and deadwood moisture increased. We also found that the different post-disturbance management strategies influenced forest regeneration. Significantly higher tree diversity was observed in salvaged sites (5.40 species per plot) compared to unsalvaged sites (3.85 species per plot). At the same time, while sites with logging were predominantly covered by broadleaved species, those without logging were typically dominated by Norway spruce (Picea abies L. Karst). Our findings suggest that although salvage logging reduced the carbon and total water content in deadwood, it can promote tree species diversity. Therefore, the currently prevailing opinion about the exclusively negative effects of salvage logging on the forest environment should be accepted with caution, and local conditions must be considered before making broad judgments.

Severe convective outbreak in Siberia in May 2020: Event analysis and high-resolution simulation

Western Siberia is exposed to extreme wind events caused by severe convective storms. However, our knowledge on such storms in Siberia is still fragmentary compared to other parts of the world primarily due to the lack of weather radar data. These storms cause substantial damage, which signifies the need for comprehensive assessment of their characteristics and predictability even on the basis of existing data. In this paper, we present a case study analysis of a severe weather outbreak that occurred on 25–26 May 2020 in Western Siberia, during a record six-month heatwave that lasted in Siberia from January to June. The outbreak resulted in six fatalities and substantial economic losses. Using various satellite data and damage reports we found that two consecutive mesoscale convective systems (MCSs) developed within the outbreak having an exceptionally long total track about 2000 km and causing large-scale forest damage with a total area of 64.5 km2. Such an exceptionally long path was supported by a strong mid-tropospheric jet, which settled extremely high values of wind shear that fostered the development of the outbreak. To analyze the accuracy of the forecast of the MCS and three associated windstorms on 26 May, we performed a set of simulations with the COSMO and ICON numerical weather prediction models launched with convection-permitting resolution (2.2 km) with different forecast lead times. Both models successfully predicted the most severe windstorm with the <50 km spatial displacement and the <1.5 h time shift, but COSMO generally simulated more strong wind. However, two other windstorms of that day were predicted with lower accuracy. The simulation results revealed a limited sensitivity of the model to variations in initial soil temperature and moisture. Together with the better performance of the forecast with >24 h lead time, this emphasized the predominant role of large-scale dynamics and the minor role of local factors in the outbreak formation and development. In particular, the intrusion of the upper tropospheric high potential vorticity streamer along the blocking periphery induced strong deep convection and determined the severe character of the outbreak. Specifically, the studied outbreak had an exceptional longevity compared to other long-lived windstorms observed in Northern Eurasia at the blocking periphery.

Responses of a soil fungal community to severe windstorm damages in an old silver fir stand.

Forests are increasingly threatened by climate change and the Anthropocene seems to have favored the emergence and adaptation of pathogens. Robust monitoring methods are required to prevent biodiversity and ecosystems losses, and this imposes the choice of bioindicators of habitat health. Fungal communities are increasingly recognized as fundamental components in nearly all natural and artificial environments, and their ecosystem services have a huge impact in maintaining and restoring the functionality of ecosystems. We coupled metabarcoding and soil analyses to infer the dynamics of a fungal community inhabiting the old silver fir stand in Vallombrosa (Italy), which is known to be afflicted by both Armillaria and Annosum root rot. The forest was affected in 2015, by a windstorm which caused a partial falling and uprooting of trees. The remaining stand, not affected by the windstorm, was used as a comparison to infer the consequences of the ecosystem disturbance. We demonstrated that the abundance of pathogens alone is not able to explain the soil fungal differences shown by the two areas. The fungal community as a whole was equally rich in the two areas, even if a reduction of the core ectomycorrhizal mycobiome was observed in the wind-damaged area, accompanied by the increase of wood saprotrophs and arbuscular mycorrhizas. We hypothesize a reshaping of the fungal community and a potentially ongoing re-generation of its functionalities. Our hypothesis is driven by the evidence that key symbiotic, endophytic, and saprotrophic guilds are still present and diversified in the wind-damaged area, and that dominance of single taxa or biodiversity loss was not observed from a mycological point of view. With the present study, we aim at providing evidence that fungal communities are fundamental for the monitoring and the conservation of threatened forest ecosystems.

Assessment of Extreme Ocean Winds within Intense Wintertime Windstorms over the North Pacific Using SMAP L-Band Radiometer Observations

Here, we examine extreme ocean winds associated with intense wintertime extratropical windstorms over the North Pacific. The study was mainly based on NASA Soil Moisture Active Passive (SMAP) L-band radiometer observations allowing the retrieval of ocean wind speeds up to 70 m/s regardless of precipitation intensity. Additionally, we assessed the ability of atmospheric reanalysis ERA5 and the Climate Forecast System Version 2 (CFSv2) to reproduce high-wind features within severe windstorms, particularly those associated with “explosive” cyclogenesis. The analysis identified 145 windstorm events with hurricane-force (HF) wind zones within the SMAP L-band radiometer swath from 2015 to 2023. These windstorms develop most frequently over two areas: southeast of Kamchatka and south of Alaska, spanning 40–47°N latitudes. Both reanalysis datasets significantly underestimated HF wind speeds compared to SMAP measurements, but CFSv2 tends to reproduce more-intense windstorms than ERA5. Among the notable new findings is that the SMAP data revealed two distinct groups in maximum wind speed distribution, indicating the existence of a separate class of severe windstorm events with a distinct mechanism for extreme wind formation related probably to a Shapiro–Keyser cyclogenesis and the presence of sting jet (SJ) feature. The study highlights the potential of SMAP measurements to study wind extremes and underscores the need for improvements in operational predictive models to better reproduce the formation of SJ windstorms.

Assessing wind damage and potential yield loss in mid-season corn using a geospatial approach

Yield loss due to natural disasters, such as storms with high-speed winds and rainfall, can significantly damage standing corn (Zea mays L.) plants and yield. Using a geospatial approach, the study aimed to estimate green snap wind damage to corn and assess potential yield and economic loss in the Mississippi Delta. Midseason corn (V12–V14) snapping occurred on 8 June 2022. We recorded green snap damage in 13 fields [1.0 to 2.0 hectares (ha−1)] with low (224 kg ha−1) and high (336 kg ha−1) N rates and two different row orientations (north–south and east–west) after the damage. The results indicated no nitrogen rates or row orientation effect on green snap damage. The average yield loss could be ~29.25 kg ha−1, with every 1% increase in green snap wind damage causing significant economic loss to producers. Research methods can help scientists to estimate potential green snap yield loss due to severe winds in the larger fields. Research results can also help estimate potential yield and economic loss to assist producers and other stakeholders in decision-making to prepare for changing weather patterns and unprecedented severe windstorms in the future.

Windstorm disturbance sets off plant species invasion, microbiota shift, and soilborne pathogens spread in an urban Mediterranean forest

We investigated the effects of a severe windstorm on vegetation, soil chemistry, understory microclimate, and soil microbiota in a Mediterranean holm oak forest. Plant species composition remained almost unchanged in the undisturbed area, whereas highly diverse plant communities were found in the disturbed area (e.g. gap area). Specifically, 11 invasive plant species were detected in 2015, but four years after, five disappeared and another five decreased, with only Ailanthus altissima increasing. Soil in disturbed areas has higher pH, Na, P, K, Ca, Cu, and Mn, but lower total limestone, organic carbon, total nitrogen, Mg, Fe, and standing litter compared to undisturbed areas. Disturbed areas had higher light availability at the ground and large variations in soil and air temperature and air relative humidity compared to undisturbed areas. The storm disturbance increased soil bacterial and fungal species richness and diversity. Moreover, the microbial co-occurrence network in the undisturbed area was more heterogeneous and complex, while modularity and number of positive correlations were higher in the disturbed area, which suggests that the structural composition of microbial communities and their co-occurrence patterns have been altered by windstorm disturbance. In the gaps, soil microbial community composition indicated a shift toward an opportunistic microbiota dominated by fast-growing but less competitive species. In addition, we found a large increase in putative plant pathogens but a decrease in simbiotrophic and ectomycorrhizal fungi in the gaps. The present work demonstrate the multiple effects of storm damage on the above- and belowground structure and diversity of forest ecosystems.

Rescuing historical weather observations improves quantification of severe windstorm risks

Abstract. Billions of historical climatological observations remain unavailable to science as they exist only on paper, stored in numerous archives around the world. The conversion of these data from paper to digital could transform our understanding of historical climate variations, including extreme weather events. Here we demonstrate how the rescue of such paper observations has improved our understanding of a severe windstorm that occurred in February 1903 and its significant impacts. By assimilating newly rescued atmospheric pressure observations, the storm is now credibly represented in an improved reanalysis of the event. In some locations this storm produced stronger winds than any event during the modern period (1950–2015) and it is in the top-4 storms for strongest winds anywhere over land in England and Wales. As a result, estimates of risk from severe storms, based on modern period data, may need to be revised. Examining the atmospheric structure of the storm suggests that it is a classic Shapiro–Keyser-type cyclone with “sting-jet” precursors and associated extreme winds at locations and times of known significant damage. Comparison with both independent observations and qualitative information, such as photographs and written accounts, provides additional evidence of the credibility of the atmospheric reconstruction, including sub-daily rainfall variations. Simulations of the storm surge resulting from this storm show a large coastal surge of around 2.5 m, comparing favourably with newly rescued tide gauge observations and adding to our confidence in the reconstruction. Combining historical rescued weather observations with modern reanalysis techniques has allowed us to plausibly reconstruct a severe windstorm and associated storm surge from more than 100 years ago, establishing an invaluable end-to-end tool to improve assessments of risks from extreme weather.

Large-scale circulation patterns and their influence on European winter windstorm predictions

Severe winter windstorms are amongst the most damaging weather events for Europe and show significant interannual variability. While surface variables (temperature, precipitation) have been successfully predicted for some time now, predictability of severe windstorms caused by extra-tropical cyclones remains less well explored. This study investigates windstorm prediction skill of the UK Met Office Global Seasonal Forecast System Version 5 (GloSea5) for the Northeast-Atlantic and European region. Based on an objective Lagrangian tracking of severe, damage relevant windstorms, three storm parameters are analysed: windstorm frequency and two intensity measures. Firstly, skill based on direct tracking of simulated windstorms is diagnosed. Significant positive skill for storm frequency and intensity is found over an extended area at the downstream end of the storm track, i.e., from the UK to southern Scandinavia. The skill for frequency agrees well with previous studies for older model versions, while the results of event-based intensity are novel. Receiver Operating Characteristic Curves for three smaller regions reveal significant skill for high and low storm activity seasons. Second, skill of windstorm characteristics based on their multi-linear regressions to three dominant large-scale circulation patterns [i.e., the North Atlantic Oscillation (NAO), the Scandinavian Pattern (SCA), and the East-Atlantic Pattern (EA)] are analysed. Although these large-scale patterns explain up to 80% of the interannual variance of windstorm frequency and up to 60% for intensity, the forecast skill for the respectively linear-regressed windstorms do not show systematically higher skill than the direct tracking approach. The signal-to-noise ratio of windstorm characteristics (frequency, intensity) is also quantified, confirming that the signal-to-noise paradox extends to windstorm predictions.

Normalized insured losses caused by windstorms in Quebec and Ontario, Canada, in the period 2008–2021

Severe windstorms pose threats to people, human-made structures, and the environment. An investigation of insured losses caused by windstorms is a multipurpose study that serves to advance the resilience and sustainability of modern communities. The present study proposes a systematic analysis of insured losses imposed by different types of windstorms in two Canadian provinces, Ontario (ON) and Quebec (QC), during the period 2008–2021. Actual wind damage data from the Canadian insurance market were considered in this study. Our calculations show that ON and QC received half of all wind catastrophes across Canada, and nearly three-quarters of all types of catastrophes in ON and QC were wind-related ones. The total windstorm loss of over CA$5.2 billion was not evenly distributed between QC and ON, but rather had a QC:ON ratio of 1:3.1. We attributed this discrepancy in the inflicted damage between two provinces to the predominantly eastward and northeastward storm trajectories and the higher density of wealth and population in ON. Convective storms were the most devastating wind type comprising nearly 65% and 67% of the total number of events and associated damage, respectively. Finally, tornadoes had the highest average loss per event in two provinces combined. Future prospects and the implication of this research are also discussed.

A Retrospective Satellite Analysis of the June 2012 North American Derecho

The North American Derecho of 29–30 June 2012 exhibits many classic progressive and serial derecho features. It remains one of the highest-impact derecho-producing convective systems (DCS) over CONUS since 2000. This research effort enhances the understanding of the science of operational forecasting of severe windstorms through examples of employing new satellite and ground-based microwave and vertical wind profile data. During the track of the derecho from the upper Midwestern U.S. through the Mid-Atlantic region on 29 June 2012, clear signatures associated with a severe MCS were apparent in polar-orbiting satellite imagery, especially from the EPS METOP-A Microwave Humidity Sounder (MHS), Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager Sounder (SSMIS), and NASA TERRA Moderate Resolution Imaging Spectroradiometer (MODIS). In addition, morning (descending node) and the evening (ascending node) METOP-A Infrared Atmospheric Sounding Interferometer (IASI) soundings are compared to soundings from surface-based Radiometrics Corporation MP-3000 series microwave radiometer profilers (MWRPs) along the track of the derecho system. The co-located IASI and MWRP soundings revealed a pre-convective environment that indicated a favorable volatile tropospheric profile for severe downburst wind generation. An important outcome of this study will be to formulate a functional relationship between satellite-derived parameters and signatures, and severe convective wind occurrence. Furthermore, a comprehensive approach to observational data analysis involves both surface- and satellite-based instrumentation. Because this approach utilizes operational products available to weather service forecasters, it can feasibly be used for monitoring and forecasting local-scale downburst occurrence within derecho systems, as well as larger-scale convective wind intensity associated with the entire DCS.

Soil Type Rather Than Freezing Determines the Size of Soil-Root Plate of Silver Birch (Betula pendula Roth.) in the Eastern Baltic Region

In the Eastern Baltic region, severe windstorms increase both in frequency and magnitude, particularly during the dormancy period, increasing wind damage risks even more for silver birch (Betula pendula Roth.), which is considered to be less vulnerable forest tree species. Tree anchorage, particularly the properties of soil–root plate, determines the type of fatal failures trees experience under extreme wind loads and, subsequently, the potential for timber recovery during salvage logging. The link between soil–root plate properties and fatal failure types was assessed by conducting destructive static pulling tests; trees on freely draining minerals and drained deep peat soils under frozen and non-frozen soil conditions were tested. The size of the root plate did not differ between trees experiencing uprooting or stem breakage but was largely affected by soil type. Frozen soil conditions increased soil–root anchorage (via binding between soil particles) and, hence, the frequency of stem breakage without changing the size of soil–root plate. However, the lack of frozen soil conditions is among the main climatic risks for forestry within the region. The differences in the properties of soil–root plate implies plasticity in adaptation to wind loadings relative to birch, suggesting a potential for managing different types of fatal failure of trees and, subsequently, the share of retrievable timber in cases of salvage logging.

Analyzing Windstorm Pattern in Malaysia based on Extracted Twitter Data

Abstract Wind-rain interactions often lead to severe windstorm events and consequently cause damages and fatal destructions. The increase in frequency of recent windstorm events overwhelmed the nation. Thus, efforts in obtaining and recording these events are intensified with the help of current technology. This study aims to analyze the pattern of recent windstorm events by utilizing big data and GIS. In this study, the reported windstorm events in Twitter application were extracted using R-programming. Prior to analyses, the extracted data were screened to remove any outliers found. The extracted data were selected based on the credibility of its sources to ensure the accuracy and quality. These selected data were extracted from trusted users such as Meteorological Department of Malaysia (MMD), Berita Harian, Bernama and others. This study has demonstrated the possibility of Twitter data as an alternative data source in windstorm studies based on its reasonable findings. It is exhibited that there is drastic increased of windstorm events frequency in years 2018-2020, especially in the northern and west-coast regions of Peninsular. The highest frequency was recorded in April (inter-monsoon season) while the lowest is in February and December (northeast monsoon). The increase of frequency in several locations in the Peninsular is very alarming especially in the Klang Valley since this region is highly populated and serves as Malaysia’s important economic zones. Hence, risk control should be considered in this region to reduce the negative impacts as suggested in SDG11 and SDG13.

Wind and fire: Rapid shifts in tree community composition following multiple disturbances in the southern boreal forest

AbstractUnder a warming climate, the southern boreal forest of North America is expected to see a doubling in fire frequency and potential for increased wind disturbance over the next century. Although boreal forests are often considered fire‐adapted, projected increases in disturbance frequency will likely result in novel combinations of disturbances with severities and impacts on community composition outside historic norms. Using a network of repeatedly measured vegetation monitoring plots, we followed changes in tree community composition in areas of the Boundary Waters Canoe Area Wilderness (BWCAW), in Minnesota, USA, experiencing disturbances ranging from severe windstorms or wildfires to areas affected by wind followed by fire or multiple fires within a short period of time. Using nonmetric multidimensional scaling ordination, hierarchical cluster analysis, and permutational analysis of variance, we compared successional pathways across different disturbance types and combinations to test whether multiple disturbances had altered successional pathways or caused greater convergence relative to single disturbances. We found that multiple disturbances often resulted in strong shifts toward wind‐dispersed early‐successional tree species, while single disturbances tended to have multiple successional pathways that favored both late‐ and early‐successional species. All disturbances in our study resulted in significant shifts in composition, but we generally failed to find statistical evidence of changes in community dispersion. Although boreal forests appear to be somewhat resilient to multiple disturbance events, multiple disturbances resulted in post‐disturbance tree communities that were heavily dominated by disturbance‐adapted deciduous trees at the expense of conifers. Our results demonstrate that multiple disturbances are capable of altering successional pathways relative to single disturbance events and that increasingly frequent disturbances are likely to alter boreal forest structure and composition, perhaps leading to a forest region strikingly unlike that of today.

Dead or Alive: Drivers of Wind Mortality Initiate Multiple Disturbance Regime in a Temperate Primeval Mountain Forest

The driving forces of tree mortality following wind disturbances of mountain mixed European temperate forests belongs among issues not comprehensively resolved. Hence, we aimed to elucidate the key factors of tree resistance to historical severe disturbance events in the Boubínský Primeval Forest, one of the oldest forest reserves in the Czech Republic. By using spatially explicit tree census, dendrochronological and soil data, we study spatial and temporal patterns of past disturbances and mathematically compared selected characteristics of neighboring trees that were killed by a severe storm in 2017 and those that remained undisturbed. The tendency of trees toward falling was primarily driven edaphically, limiting severe events non-randomly to previously disturbed sites occupied by hydromorphic soils and promoting the existence of two spatially-separated disturbance regimes. While disturbed trees usually recruited in gaps and experienced only one severe release event, surviving trees characteristically regenerated under the canopy and were repeatedly released. Despite the fact that disturbed trees tended to reach both lower ages and dimensions than survivors, they experienced significantly higher growth rates. Our study indicates that slow growth with several suppression periods emerged as the most effective tree strategy for withstanding severe windstorms, dying of senescence in overaged life stage. Despite the selective impact of the Herwart storm on conifer population, we did not find any difference in species sensitivity for most characteristics studied. We conclude that the presence of such ancient, high-density wood trees contributes significantly to the resistance of an entire stand to severe storms.

Climate Change Perception and Uptake of Climate-Smart Agriculture in Rice Production in Ebonyi State, Nigeria

Rice production in Nigeria is vulnerable to climate risks and rice farmers over time have experienced the risks and their respective impacts on rice farming. Rice farmers have also responded to perceived climate risks with strategies believed to be climate-smart. Farmers’ perception of climate risks is an important first step of determining any action to be taken to counteract the negative effects of climate change on agriculture. Studies on the link between perceived climate risks and farmers’ response strategies are increasing. However, there are limited studies on the determinants of rice farmers’ perception of climate events. The paper therefore examined climate change perception and uptake of climate-smart agriculture in rice production in Ebonyi State, Nigeria using cross-sectional data from 347 rice farmers in an important rice-producing area in Nigeria. Principal component analysis, multivariate probit regression model and descriptive statistics were adopted for data analysis. Perceived climate events include increased rainfall intensity, prolonged dry seasons, frequent floods, rising temperature, severe windstorms, unpredictable rainfall pattern and distribution, late onset rain, and early cessation of rain. Farmers’ socioeconomic, farm and institutional characteristics influenced their perception of climate change. Additionally, rice farmers used a variety of climate-smart practices and technologies to respond to the perceived climate events. Such climate-smart practices include planting improved rice varieties, insurance, planting different crops, livelihood diversification, soil and water conservation techniques, adjusting planting and harvesting dates, irrigation, reliance on climate information and forecasts, planting on the nursery, appropriate application of fertilizer and efficient and effective use of pesticides. These climate-smart agricultural measures were further delineated into five broad packages using principal component analysis. These packages include crop and land management practices, climate-based services and irrigation, livelihood diversification and soil fertility management, efficient and effective use of pesticide and planting on the nursery. High fertilizer costs, lack of access to inputs, insufficient land, insufficient capital, pests and diseases, floods, scorching sun, high labour cost, insufficient climate information, and poor extension services were the barriers to uptake of climate-smart agriculture in rice production. Rice farmers should be supported to implement climate-smart agriculture in rice production in order to achieve the objectives of increased rice productivity and income, food security, climate resilience and mitigation.

Numerical investigation of flow around a square cylinder in accelerated flow

To investigate the flow field evolution and resultant aerodynamic characteristics of a square cylinder during flow acceleration, large-eddy simulations were undertaken to simulate flow with a dimensionless acceleration rate ap of 0.0048. The adopted ap resembles that is likely to be experienced during a severe downburst wind storm. The tested incidence angle α ranges from 0° to 45° and the time-dependent Reynolds number Re [Re = U(t)D/v, where U(t) is the time-dependent inflow velocity and D and v are the cylinder length and the kinematic viscosity, respectively] varies from 0 to 5 × 104 throughout the simulation. Results revealed that the flow around a square cylinder in accelerated flow evolves through three distinct temporal flow phases: namely, Phase I (Ia and Ib) where no vortex shedding (the instantaneous lift force through this period is zero) is observed, Phase II, where periodic vortex shedding and associated lift force oscillations are initiated and enhanced, and Phase III where stable vortex shedding occurs. Phase I can be further broken down into Phase Ia, which is characterized by laminar shear layer separation and the existence of steady recirculation vortices in the near wake region, and Phase Ib (only present at α = 0° and 45°) which is distinguished by the presence of quasi-steady recirculation vortices behind the cylinder. Aside from the variation of flow patterns, the transient lift and drag coefficients and the wind pressure distributions, as well as the spatial evolution of three-dimensional flow structures and pressure distributions, are also elucidated in detail.

High-fidelity prediction of flight trajectories of plate-type debris in boundary layer winds

From reconnaissance surveys, plate-type objects, such as roof shingles and tiles, are known to be among the most common types of debris objects. Therefore, a reliable prediction of their flight trajectories is instrumental for evaluating the vulnerability of building envelopes, especially in the regions with severe windstorms. Despite the development of several quasi-steady models for this purpose, the current literature lacks high-fidelity models to predict the flight pattern and impact velocity of the windborne debris objects separated from the ground and/or buildings. To address this gap, a coupled computational fluid dynamics and rigid body dynamics simulation framework was developed in the current study to capture the flight trajectories of plate-type debris objects in atmospheric boundary layer winds. Upon establishing a fundamental understanding of main flight characteristics, this study was extended to investigate the effects of initial pitch and yaw angles, plate characteristics, mean wind velocity, and release height on the flight of plate-type debris. In addition, a set of models were developed to predict debris travel distance, as well as linear and angular velocities associated with it. This can be directly employed to assess the impact-induced loading demand that building envelopes are expected to resist due to windborne plate-type debris.

Fast restoration of microgrids using online evaluation metrics considering severe windstorms

This paper presents a new online scheme for estimating critical contingencies caused by extreme windstorms aiming at improving the microgrid (MG) resiliency. The proposed scheme benefits from an online and non-model-based index by which the fragility metrics of MGs and the loads are evaluated at each time moving window. Also, four indices based on dynamic evaluation of the network are proposed which two indices correspond to the failure period and the two other are related to the network recovery period. By evaluation of these indices, correction actions aiming at improving the resilience of MG are provided. Finally, the proposed method is assessed in the case of different generation locations and the outage probability of system components. The results evidence that the proposed scheme shows a 15% reduction in the total load failure index and a 7% reduction in the critical load failure index if compared to the base case. It also shows a 23% improvement in the total load recovery in the presence of severe storms.

Detection of Forest Windstorm Damages with Multitemporal SAR Data—A Case Study: Finland

The purpose of this study was to develop methods to localize forest windstorm damages, assess their severity and estimate the total damaged area using space-borne SAR data. The development of the methods is the first step towards an operational system for near-real-time windstorm damage monitoring, with a latency of only a few days after the storm event in the best case. Windstorm detection using SAR data is not trivial, particularly at C-band. It can be expected that a large-area and severe windstorm damage may affect backscatter similar to clear cutting operation, that is, decrease the backscatter intensity, while a small area damage may increase the backscatter of the neighboring area, due to various scattering mechanisms. The remaining debris and temporal variation in the weather conditions and possible freeze–thaw transitions also affect observed backscatter changes. Three candidate windstorm detection methods were suggested, based on the improved k-nn method, multinomial logistic regression and support vector machine classification. The approaches use multitemporal ESA Sentinel-1 C-band SAR data and were evaluated in Southern Finland using wind damage data from the summer 2017, together with 27 Sentinel-1 scenes acquired in 2017 and other geo-referenced data. The stands correctly predicted severity category corresponded to 79% of the number of the stands in the validation data, and already 75% when only one Sentinel-1 scene after the damage was used. Thus, the damaged forests can potentially be localized with proposed tools within less than one week after the storm damage. In this study, the achieved latency was only two days. Our preliminary results also indicate that the damages can be localized even without separate training data.

Resilient distribution network planning under the severe windstorms using a risk-based approach

This paper proposes a risk-based approach for planning resilient radial distribution networks to severe windstorms. The proposed approach is based on the concept of interval analysis, Relative Distance Measure (RDM) interval arithmetic, mixed integer linear programming, and risk analysis. It enables obtaining a number of different resilient network plans taking into account dependence among the following uncertain inputs: maximum wind speed, storm duration and its annual frequency of occurrence, fragility of network components, repair duration, forecasted load and generation from renewable generators. In order to improve the computational efficiency of the proposed approach a hybrid simulated annealing and mixed integer linear programming algorithm is introduced. The best resilient plan is selected by employing the Minimal risk (Minimax) criterion for measuring and managing risk. In this way, the proposed approach provides a decision-maker with a means of determining the resilient network plan that minimizes the risk of significant costs due to severe windstorms.