A geostatistical extreme-value framework for fast simulation of natural hazard events

This is the final version of the article. Available from the publisher via the DOI in this record.We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student's t-process captures spatial dependence and gives a continuous-space framework for natural hazard event simulations. Efficiency of the simulation method allows many years of data (typically over 10 000) to be obtained at relatively little computational cost. This makes the model viable for forming the hazard module of a catastrophe model. We illustrate the framework by simulating maximum wind gusts for European windstorms, which are found to have realistic marginal and spatial properties, and validate well against wind gust measurements.This work has been kindly funded by the Willis Research Network

State of the Art in the Optimisation of Wind Turbine Performance Using CFD

Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained.</p

Drivers of annual variation in tree growth and forest sensitivity to storm damage in Finland

In this thesis, my aim is to study the drivers of tree growth variation and forest predisposition to storm disturbance in Finland. More specifically, the thesis aims to answer the following research questions: (1) What is the role of tree provenance in the climatic control of radial growth variation in Norway spruce? (2) How do weather conditions outside of growing season affect radial growth variation in Norway spruce and Scots pine? (3) How are forest properties, forest management and abiotic environmental factors connected to the storm damage probability of forest stands and individual trees? (4) Do the same factors affect stand-level damage probability in different storm types: autumn extra-tropical cyclones and summer thunder storms? (5) Is fine-scale topographic information connected to tree-level storm damage probability? The thesis addresses these questions by analyzing extensive empirical data sets. The different climatic drivers of Norway spruce provenances were studied using a tree-ring data from seven Norway spruce provenance experiments in Finland, established already in the 1930s and located in different climatic conditions and containing a large variety of provenances. The effects of non-growing season climatic conditions on tree-growth were studied by comparing tree-ring data from unmanaged forests with variables describing winter conditions and modelled tree frost hardiness levels. Storm damage probability on stand and tree levels was examined with storm damage data sets collected at Finnish National Forest Inventory plots after major storms. A statistical modeling approach was used throughout the thesis, utilizing methods such as generalized mixed effects models and statistical distributions of extreme values. The results revealed provenance differences in radial growth variation in Norway spruce. Provenances differed most in their growth response to winter temperature, as adaptation to low winter temperatures was weaker in Central European than in Northern European provenances. While cold winter temperatures were associated with frost damage and declined radial growth in Central European spruce provenances transferred north, simple temperature variables were not sufficient in studying the responses of trees to conditions outside of the growing season in natural forests. Instead, the results showed signs of reduced growth after events of insufficient frost hardiness levels and winters with high frost sum of snowless days. This indicates that accounting for a complexity of factors, such as frost hardiness of trees, snow cover and soil frost, is needed to understand the implications of weather conditions outside of growing season to tree growth. Stand-level damage probability was affected by stand characteristics and previous management operations. On tree-level, damage probability was connected to type of the tree species (conifer or broad-leaved) and tree height as well as recent changes in wind exposure and wood decay in the stand. Storm damage probability in autumn storms and summer thunder storms was affected by similar factors, and the similarities were clearest in the effects of forest management history and topography. However, due to the limitations of the data, the results may have missed subtler differences between the storm types. Topography was associated with storm damage probability on both stand and individual tree level. The results also show that high-resolution topographical information, describing the local topography near the tree, can improve models of tree-level storm damage probability.Väitöskirjassani tutkin puun kasvun vaihteluun sekä metsien myrskytuhoherkkyyteen vaikuttavia tekijöitä. Väitöskirja pyrkii vastaamaan seuraaviin tutkimuskysymyksiin: (1) Miten sääolojen vaikutus puun kasvuun eroaa kuusen eri eurooppalaisilla alkuperillä? (2) Miten kasvukauden ulkopuoliset sääolot vaikuttavat puun paksuuskasvuun kuusella ja männyllä? (3) Miten metsän ominaisuudet, metsänhoito ja ympäristötekijät vaikuttavat myrskytuhon todennäköisyyteen metsikön ja yksittäisen puun tasolla? (4) Vaikuttavatko samat tekijät myrskytuhoherkkyyteen erityyppisissä myrskyissä? (5) Onko pienen mittakaavan topografinen vaihtelu yhteydessä myrskytuhon todennäköisyyteen yksittäisen puun tasolla? Näihin tutkimuskysymyksiin paneudutaan analysoimalla kattavia empiirisiä aineistoja. Eri kuusen alkuperien erilaisia kasvuvasteita sääolojen vaihteluun tutkittiin analysoimalla puulustoaineistoa, joka on kerätty eri puolelle Suomea jo 1930-luvulla istutetuista alkuperäkokeista. Kasvukauden ulkopuolisten sääolojen vaikutuksia tutkittiin vertaamalla luonnontilaisista metsistä kerättyä puulustoaineistoa talviolosuhteita ja puiden mallinnettua kylmänkestävyyttä kuvaaviin muuttujiin. Metsien myrskytuhoja tutkimiseen käytettiin Valtakunnan metsien inventoinnin koealoilta dokumentoitua tuhotietoja voimakkaiden myrskyjen jälkeen. Aineistojen analysoinnissa hyödynnettiin tilastollisen mallintamisen menetelmiä. Tulokset paljastivat eroja kasvunvaihtelussa kuusen alkuperien välillä. Suurimmat erot alkuperien välillä liittyivät talvilämpötiloihin – keskieurooppalaiset alkuperät kasvoivat huonommin kylmien talvien jälkeen, kun taas suomalaiset alkuperät ovat paremmin sopeutuneita kylmään ilmastoon. Myös luonnontilaisten metsien puulustoaineistojen analysointi näytti, että kylmät talvet eivät olleet yhteydessä kasvun heikkenemiseen paikallista alkuperää olevilla puilla. Sen sijaan mahdollisesti riittämätön kylmänkestävyyden taso ja vähälumiset mutta kylmät talvet olivat joissain tapauksissa yhteydessä heikentyneeseen kasvuun. Tämä osoittaa, että pelkkien lämpötilamuutosten huomioiminen ei riitä, kun tutkitaan muuttuvien talviolosuhteiden vaikutuksia metsiin. Myrskytuhon todennäköisyys metsissä liittyi puuston ominaisuuksiin, aiempiin metsänhoitotoimenpiteisiin sekä paikallisiin tuuliolosuhteisiin vaikuttaviin tekijöihin. Tulokset osoittivat samojen tekijöiden vaikuttavan tuhon todennäköisyyteen tutkituissa myrskytyypeissä, eli kesäisissä ukkosmyrskyissä ja voimakkaisiin matalapaineisiin liittyvissä syysmyrskyissä. Etenkin metsänhoitohistorian ja topografian vaikutukset olivat eri myrskytyypeillä samanlaisia. Topografia oli yhteydessä myrskytuhon todennäköisyyteen niin metsikkö- kuin puutasolla. Tulokset osoittivat, että korkearesoluutioisten korkeusmallien avulla voidaan parantaa puutason myrskytuhomalleja

A statistical model for the prediction of wind-speed probabilities in the atmospheric surface layer

Wind fields in the atmospheric surface layer (ASL) are highly three-dimensional and characterized by strong spatial and temporal variability. For various applications such as wind comfort assessments and structural design, an understanding of potentially hazardous wind extremes is important. Statistical models are designed to facilitate conclusions about the occurrence probability of wind speeds based on the knowledge of low-order flow statistics. Being particularly interested in the upper tail regions we show that the statistical behavior of near-surface wind speeds is adequately represented by the Beta distribution. By using the properties of the Beta probability density function in combination with a model for estimating extreme values based on readily available turbulence statistics, it is demonstrated that this novel modelling approach reliably predicts the upper margins of encountered wind speeds. The model’s basic parameter is derived from three substantially different calibrating datasets of flow in the ASL originating from boundary-layer wind-tunnel measurements and direct numerical simulation. Evaluating the model based on independent field observations of near-surface wind speeds showed a high level of agreement between the statistically modelled horizontal wind speeds and measurements. The results show that, based on the knowledge of only a few simple flow statistics (mean wind speed, wind speed fluctuations and integral time scales), the occurrence probability of velocity magnitudes at arbitrary flow locations in the ASL can be estimated with a high degree of confidence

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 – an application to the Italian Seas

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 80's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the &lt;i&gt;r-largest annual maxima&lt;/i&gt; and the &lt;i&gt;peak-over-threshold&lt;/i&gt;. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The &lt;i&gt;r-largest annual maxima&lt;/i&gt; method provides more reliable predictions of the extreme values especially for small return periods (&amp;lt;100 years). Finally, the study statistically proves the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century

Non-stationarity in daily and sub-daily intense rainfall – Part 1: Sydney, Australia

This study was driven by a need to clarify how variations in climate might affect intense rainfall and the potential for flooding. Sub-daily durations are of particular interest for urban applications. Worldwide, few such observation-based studies exist, which is mainly due to limitations in data. While there are still large discrepancies between precipitation data sets from observations and models, both show that there is a tendency for moist regions to become wetter and for dry regions to become drier. However, changes in extreme conditions may show the opposite sign to those in average conditions. Where changes in observed intense precipitation have been studied, this has typically been for daily durations or longer. &lt;br&gt;&lt;br&gt; The purpose of this two-part study is to examine daily and sub-daily rainfall extremes for evidence of non-stationarity. Here the problem was addressed by supplementing one long record (Part 1) by a set of shorter records for a 30-yr concurrent period (Part 2). Variations in frequency and magnitude of rainfall extremes across durations from 6 min to 72 h were assessed using data from sites in the south-east of Australia. For the analyses presented in this paper, a peaks-over-threshold approach was chosen since it allows investigating changes in frequency as well as magnitude. Non-parametric approaches were used to assess changes in frequency, magnitude, and quantile estimates as well as the statistical significance of changes for one station (Sydney Observatory Hill) for the period 1921 to 2005. Deviations from the long-term average vary with season, duration, and threshold. The effects of climate variations are most readily detected for the highest thresholds. Deviations from the long-term average tend to be larger for frequencies than for magnitudes, and changes in frequency and magnitude may have opposite signs. &lt;br&gt;&lt;br&gt; Investigations presented in this paper show that variations in frequency and magnitude of events at daily durations are a poor indicator of changes at sub-daily durations. Studies like the one presented here should be undertaken for other regions to allow the identification of regions with significant increase/decrease in intense rainfall, whether there are common features with regards to duration and season exhibiting most significant changes (which in turn could lead to establishing a theoretical framework), and assist in validation of projections of rainfall extremes

Optimization of Low Reynolds Number Airfoils for Martian Rotor Applications Using an Evolutionary Algorithm

The Mars Helicopter (MH) will be flying on the NASA Mars 2020 rover mission scheduled to launch in July of 2020. Research is being performed at the Jet Propulsion Laboratory (JPL) and NASA Ames Research Center to extend the current capabilities and develop the Mars Science Helicopter (MSH) as the next possible step for Martian rotorcraft. The low atmospheric density and the relatively small-scale rotors result in very low chord-based Reynolds number flows over the rotor airfoils. The low Reynolds number regime results in rapid performance degradation for conventional airfoils due to laminar separation without reattachment. Unconventional airfoil shapes with sharp leading edges are explored and optimized for aerodynamic performance at representative Reynolds-Mach combinations for a concept rotor. Sharp leading edges initiate immediate flow separation, and the occurrence of large-scale vortex shedding is found to contribute to the relative performance increase of the optimized airfoils, compared to conventional airfoil shapes. The oscillations are shown to occur independent from laminar-turbulent transition and therefore result in sustainable performance at lower Reynolds numbers. Comparisons are presented to conventional airfoil shapes and peak lift-to-drag ratio increases between 17% and 41% are observed for similar section lift