Our society needs to continuously perform transports of people and goods toensure that business is kept going. Every disturbance in the transportation ofpeople or goods affects the commerce and may result in economical losses forcompanies and society. Severe traffic accidents cause personal tragedies forpeople involved as well as huge costs for the society. Therefore the roadauthorities continuously try to improve the traffic safety. Traffic safety may beimproved by reduced speeds, crash safe cars, tires with better road grip andimproved road maintenance. The environmental effects from roadmaintenance when spreading de-icing chemicals need to be considered, i.e.how much chemicals should be used to maximize traffic safety and minimizethe environmental effects. Knowledge about the current and upcoming roadcondition can improve the road maintenance and hence improve traffic safety.This thesis deals with sensors and models that give information about the roadcondition.The performance and reliability of existing surface mounted sensors wereexamined by laboratory experiments. Further research involved field studies tocollect data used to develop surface status models based on road weather dataand camera images. Field studies have also been performed to find best usageof non intrusive IR technology.The research presented here showed that no single sensor give enoughinformation by itself to safely describe the road condition. However, the resultsindicated that among the traditional road surface mounted sensors only theactive freezing point sensor gave reliable freezing point results. Furtherresearch aimed to find a model that could classify the road condition indifferent road classes from existing road weather sensor data and road images.The result was a model that accurately could distinguish between the roadconditions dry, wet, snowy and icy. These road conditions are clearly dissimilarand are therefore used as the definition of the road classes used in this thesis.Finally, results from research regarding remote sensing IR technology showedthat it significantly improves knowledge of the road temperature and statuscompared to data from surface mounted sensors. / Vårt samhälle bygger på att det finns effektiva transporter av människor ochvaror för att säkerställa att samhällets funktioner fungerar och att företagenkan genomföra sina affärer. Störningar i transporterna av människor och varorpåverkar handeln och kan leda till ekonomiska förluster för både företag ochvårt samhälle. Allvarliga trafikolyckor orsakar personliga tragedier för deinblandade samt stora kostnader för samhället. Det är med denna bakgrundsom vägmyndigheterna kontinuerligt arbetar med att förbättratrafiksäkerheten. Trafiksäkerheten kan förbättras genom att minskahastigheterna, se till att bilarna blir krocksäkra, krav på däck med bättreväggrepp och ett bättre vägunderhåll. Miljöeffekterna från vinterväghållningdär avisningsmedel sprids på vägarna måste beaktas, d.v.s. hur mycketkemikalier bör användas för att maximera trafiksäkerheten och minimeramiljöpåverkan. Denna avhandling handlar om sensorer och modeller som gerinformation om väglaget. En kunskap om aktuellt och kommande väglag kanförbättra väghållningen och därmed öka trafiksäkerheten.I avhandlingen har prestanda och tillförlitlighet hos befintliga vägmonteradesensorer granskats i laboratorieexperiment. Data från fältstudier har använtsför att utveckla modeller som kan ge information om vägytans status baseratpå meteorologiska mätdata och kamerabilder. Det har också genomförtsfältstudier för att utforska den fördelaktigaste användningen av beröringsfriinfraröd sensorteknik.Den forskning som presenteras här visar att ingen enskild givare ger tillräckliginformation för att säkert beskriva väglaget. Från de traditionella ytmonteradesensorerna drogs slutsatsen att den aktiva fryspunktsgivaren gav de mesttillförlitliga fryspunktsresultaten. Det vidare arbetet handlade om att hitta enmodell som skulle kunna klassificera vägförhållanden i olika vägklassergenom att utnyttja information från befintliga sensorer och kamerabilder.Detta arbete resulterade i en modell som tillförlitligt kan särskilja väglagentorr, våt, snöig och isig. Dessa väglag är väsentligt olika och har därför valtssom väglagsklasser i denna avhandling. Under en säsong genomfördes ävenfältförsök med beröringsfri infraröd mätteknik där det visade sig att denberöringsfria teknologin förbättrar kunskapen om vägbanans temperatur och vägbanans status.

Communication systems have an important role to play in managing the safe and efficient operation of the National Airspace System (NAS). The users of the NAS, from the commercial transport aircraft to hobby airplanes can all benefit from the recent advances in digital communication technology especially as the capacity of the analog voice systems is surpassed by the growth in air traffic. One of the benefits of the new digital data links being developed is to allow delivery of real time weather information to the cockpit of aircrafts. Weather information is essential to flight operations and until recently there were only limited voice and text weather reports available to the pilot. With data links, graphical weather in the cockpit is possible and also highly desired by the aviation community. This thesis will develop a decision model and analysis tool for product developers of weather information systems that need to select appropriate data link technology for which to develop their weather information systems. A comparative analysis of the aeronautical communications systems is done with the view of satisfying end-user requirements for weather information and achieving market success. A study of the various data links is conducted to gain an understanding of their performance characteristics and implementation issues. A consumer survey was designed and valuable insight into the requirements and opinions of pilots was gained. The method of Quality Function Deployment (QFD) was employed to find the most important technical characteristics of the data links to satisfy the consumer requirements captured in the survey. The decision model consisting of the QFD and also further technical assessment was implemented in software to allow any scenario of product requirements and data link to be performed. / Master of Science

Covering the Northern part of the Province, Ontario’s low-volume roads provide a link from remote resource areas to markets. Thus, preserving this transportation asset from the two main sources of pavement deterioration, namely traffic loading and the environment is extremely critical to the movement of goods and to the economy. In particular, Northern Ontario’s secondary highways are challenged by a combination of heavy, low frequency traffic loading and a high number of freeze-thaw cycles for which most of these highways have not been structurally designed. Therefore they experience environmental damage and premature traffic-induced deterioration. To cope with this issue, the Ontario Ministry of Transportation places Spring Load Restrictions (SLR) every year during spring-thaw. For economic reasons, the duration of SLRs is usually fixed in advance and is not applied proactively or according to conditions in a particular year. This rigidity in the schedule needs to be addressed, as it can translate into economic losses either when the payload is unnecessarily restricted or when pavement deterioration occurs. While the traditional approaches are usually qualitative and rely on visual observations, engineering judgment and historical records to make SLR decisions, the latest approaches resort to climatic and deflection data to better assess the bearing capacity of the roadway. The main intent of this research was to examine how the use of a predictor for frost formation and thawing could improve the scheduling of load restrictions by tracking the frost-strengthening and thaw-weakening of the pavement structure. Based on field data captured in Northern Ontario, and on a preliminary analysis that found good correlation between frost thickness in the roadway and Road Weather Information Systems (RWIS) variables, more advanced frost and thaw predictors were developed as part of this research and are presented herein. The report outlines how the model was developed, details the calculation algorithms, and proposes an empirical methodology for a systematic site-specific calibration. This research also involved several experimental and numerical tools, including the use of a Portable Falling Weight Deflectometer (PFWD) to estimate pavement strength during spring thaw, and the use of the Mechanistic-Empirical Pavement Design Guide (MEPDG) software to simulate the impact of SLR on the performance of typical Northern Ontario low volume roads.

Covering the Northern part of the Province, Ontario’s low-volume roads provide a link from remote resource areas to markets. Thus, preserving this transportation asset from the two main sources of pavement deterioration, namely traffic loading and the environment is extremely critical to the movement of goods and to the economy. In particular, Northern Ontario’s secondary highways are challenged by a combination of heavy, low frequency traffic loading and a high number of freeze-thaw cycles for which most of these highways have not been structurally designed. Therefore they experience environmental damage and premature traffic-induced deterioration. To cope with this issue, the Ontario Ministry of Transportation places Spring Load Restrictions (SLR) every year during spring-thaw. For economic reasons, the duration of SLRs is usually fixed in advance and is not applied proactively or according to conditions in a particular year. This rigidity in the schedule needs to be addressed, as it can translate into economic losses either when the payload is unnecessarily restricted or when pavement deterioration occurs. While the traditional approaches are usually qualitative and rely on visual observations, engineering judgment and historical records to make SLR decisions, the latest approaches resort to climatic and deflection data to better assess the bearing capacity of the roadway. The main intent of this research was to examine how the use of a predictor for frost formation and thawing could improve the scheduling of load restrictions by tracking the frost-strengthening and thaw-weakening of the pavement structure. Based on field data captured in Northern Ontario, and on a preliminary analysis that found good correlation between frost thickness in the roadway and Road Weather Information Systems (RWIS) variables, more advanced frost and thaw predictors were developed as part of this research and are presented herein. The report outlines how the model was developed, details the calculation algorithms, and proposes an empirical methodology for a systematic site-specific calibration. This research also involved several experimental and numerical tools, including the use of a Portable Falling Weight Deflectometer (PFWD) to estimate pavement strength during spring thaw, and the use of the Mechanistic-Empirical Pavement Design Guide (MEPDG) software to simulate the impact of SLR on the performance of typical Northern Ontario low volume roads.

Trafikverket, the agency in charge of state road maintenance in Sweden, have a number of so-called Road Weather Information Systems (RWIS). The main purpose of the stations is to provide winter road maintenance workers with information to decide when roads need to be plowed and/or salted. Each RWIS have a number of sensors which make road weather-related measurements every 30 minutes. One of the sensors is dug into the road which can cause traffic disturbances and be costly for Trafikverket. Other RWIS sensors fail occasionally. This project aims at modelling a set of RWIS sensors using supervised machine learning algorithms. The sensors that are of interest to model are: Optic Eye, Track Ice Road Sensor (TIRS) and DST111. Optic Eye measures precipitation type and precipitation amount. Both TIRS and DST111 measure road surface temperature. The difference between TIRS and DST111 is that the former is dug into the road, and DST111 measures road surface temperature from a distance via infrared laser. Any supervised learning algorithm trained to model a given measurement made by a sensor, may only train on measurements made by the other sensors as input features. Measurements made by TIRS may not be used as input in modelling other sensors, since it is desired to see if TIRS can be removed. The following input features may also be used for training: road friction, road surface condition and timestamp. Scikit-learn was used as machine learning software in this project. An experimental approach was chosen to achieve the project results: A pre-determined set of supervised algorithms were compared using different amount of top relevant input features and different hyperparameter settings. Prior to achieving the results, a data preparation process was conducted. Observations with suspected or definitive errors were removed in this process. During the data preparation process, the timestamp feature was transformed into two new features: month and hour. The results in this project show that precipitation type was best modelled using Classification And Regression Tree (CART) on Scikit-learn default settings, achieving a performance score of Macro-F1test = 0.46 and accuracy = 0.84 using road surface condition, road friction, DST111 road surface temperature, hour and month as input features. Precipitation amount was best modelled using k-Nearest Neighbor (kNN); with k = 64 and road friction used as the only input feature, a performance score of MSEtest = 0.31 was attained. TIRS road surface temperature was best modelled with Multi-Layer Perceptron (MLP) using 64 hidden nodes and DST111 road surface temperature, road surface condition, road friction, month, hour and precipitation type as input features, with which a performance score of MSEtest = 0.88 was achieved. DST111 road surface temperature was best modelled using Random forest on Scikit-learn default settings with road surface condition, road friction, month, precipitation type and hour as input features, achieving a performance score of MSEtest = 10.16.

This master thesis emphasizes the importance of aviation meteorological data for flight planning and for making inflight strategic decisions. It describes conventional ways of obtaining meteorological data before and during the flight. It provides the overview of alternative ways of acquiring weather related information. The master thesis compares how hazardous meteorological phenomena - thunderstorms, turbulence and icing - are displayed within the described commercial products.

Because winter maintenance is so costly, Utah Department of Transportation (UDOT) personnel asked researchers at Brigham Young University to determine whether asphalt or concrete pavements require more winter maintenance. Differing thermal properties suggest that, for the same environmental conditions, asphalt and concrete pavements will have different temperature profiles. Climatological data from 22 environmental sensor stations (ESSs) near asphalt roads and nine ESSs near concrete roads were used to 1) determine which pavement type has higher surface temperatures in winter and 2) compare the subsurface temperatures under asphalt and concrete pavements to determine the pavement type below which more freeze-thaw cycles of the underlying soil occur. Twelve continuous months of climatological data, primarily from the 2009 calendar year, were acquired from the road weather information system operated by UDOT, and erroneous data were removed from the data set. To predict pavement surface temperature, a multiple linear regression was performed with input parameters of pavement type, time period, and air temperature. Similarly, a multiple linear regression was performed to predict the number of subsurface freeze-thaw cycles, based on month, latitude, elevation, and pavement type. A finite-difference model was created to model surface temperatures of asphalt and concrete pavements based on air temperature and incoming radiation. The statistical analysis predicting pavement surface temperatures showed that, for near-freezing conditions, asphalt is better in the afternoon, and concrete is better for other times of the day, but that neither pavement type is better, on average. Asphalt and concrete are equally likely to collect snow or ice on their surfaces, and both pavements are expected to require equal amounts of winter maintenance, on average. Finite-difference analysis results confirmed that, for times of low incident radiation (night), concrete reaches higher temperatures than asphalt, and for times of high incident radiation (day), asphalt reaches higher temperatures than concrete. The regression equation predicting the number of subsurface freeze-thaw cycles provided estimates that did not correlate well with measured values. Consequently, an entirely different analysis must be conducted with different input variables. Data that were not available for this research but are likely necessary in estimating the number of freeze-thaw cycles under the pavement include pavement layer thicknesses, layer types, and layer moisture contents.

The aim of this thesis is to investigate the use of weather information from an information science perspective. By using Everyday Life Information Seeking theories and a qualitative method this thesis takes a novel approach on how weather information is used and viewed by the everyday users and meteorologists. Thus the material, based on seven interviews with everyday users and two focus group interviews with meteorologists, manages to convey new aspects on how weather information is used in an everyday setting and how meteorologists view their role as information providers. The analysis show that for everyday users there is a difference in how weather information is used depending on age. While apps on mobile phones are used by both younger and older informants, other media types, such as TV and webpages, tend to be used by either older or younger age groups. The results also show that there are non-traditional sources used for weather information among everyday users, such as non-weather web cameras and social media. The results also show that there is a difference in how meteorological forecasters and researchers view different aspects of weather information. Both groups have an understanding of information as being dependent on how it is presented, though forecast meteorologists express a more nuanced view. The results from this study show that information science can be a vital tool for studying weather information habits. It is the firm belief of the author that using information science could gain new insights for the meteorological community in the future. This is a two-year master thesis in Archive, Library and Museum studies. / Syftet med denna uppsats är att undersöka väderinformation från ett informationsvetenskapligt perspektiv. Genom att använda Everyday Life Information Seeking teorier och en kvalitativ metod ger denna uppsats ett nydanande angreppsätt på hur väderinformation används och ses av vardagsanvändare och meteorologer. Således kan materialet, som baseras på sju intervjuer med vardagsanvändare och två fokusgruppsintervjuer med meteorologer, frambära nya aspekter på hur väderinformation används i vardagen och hur meteorologer ser på sin roll som informationsförmedlare. Analysen visar att det för vardagsanvändare finns en skillnad i hur väderinformation används beroende på åldersgrupp. Medan appar på mobiltelefoner används av både yngre och äldre informanter, så tenderar övriga media typer, som TV och hemsidor, att användas främst av endast en ålderskategori. Vidare visar resultaten på att icketraditionella källor för väderprognoser används av vardaganvändare, så som webkameror och sociala medier. Resultaten visar även på att det finns en skillnad i hur prognosmeteorologer och meteorologiska forskare ser på olika aspekter av väderinformation. Båda grupperna visar på en förståelse för att information är beroende på hur den presenteras, så ger prognosmeteorologer uttryck för en mer nyanserad bild. Resultaten från studien visa på att informationsvetenskap kan vara ett viktigt verktyg för att studera väderinformationsvanor. Författaren menar på att informationsvetenskap skulle kunna ge nya insikter inom det meteorologiska området i framtiden. Detta är en tvåårig masteruppsats inom Arkiv-, Bibliotek- och Museumstudier.

Titel: “Everybody talks about the weather, but nobody does anything about it.” Författare: Malin Nyberg Institution: Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU Kurs: Turismvetenskap III – Examensarbete, 15 hp. Handledare: Martin Gren, (Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU) Examinator: Stefan Gössling, (Linnéuniversitetet, Fakultetsnämnden för ekonomi och design, Ekonomihögskolan, ELNU) Syfte: Studiens syfte är att undersöka på vilket sätt och varför Öland som turistdestination är sårbar inför vädervariationer ur turismaktörernas perspektiv. Studien avser även att belysa på vilket sätt marknadsföring av Öland och medias rapportering om destinationens väderförhållanden är bidragande krafter till väderkänsligheten. Metodik: I undersökningen har en kvalitativ fallstudie använts som forskningsmetod med en induktiv ansats. Informationsinsamling har skett via semi-strukturerade intervjuer med respondenter från fyra turismverksamheter på Öland. Urvalet av fallstudieområde och respondenter har skett genom ett bekvämlighetsurval med hänsyn till access och karaktär av forskningsområdet. Slutsats: De viktigaste betydelserna av forskningsresultatet har bland annat visat att brist på alternativa turismprodukter innebär en stor sårbarhet för turismaktörernas verksamheter vid ogynnsamma väderförhållanden för de huvudsakliga aktiviteterna Forskningsresultaten har även påvisat att fokus på specifika väderattribut i marknadsföringen av destinationen medverkar till destinationens sårbarhet tillsammans med förväntningar om specifika väderförhållanden bland besökare. / Title: “Everybody talks about the weather, but nobody does anything about it.” Author: Malin Nyberg Institution: School of Business and Economics Course: Tourism Studies III – Bachelors Thesis, 15 credits Supervisor: Martin Gren, (Linnaeus University, School of Business and Economics, ELNU) Examiner: Stefan Gössling, (Linnaeus University, School of Business and Economics, ELNU) Purpose: The study aims to examine how and why Öland as a tourist destination is vulnerable to weather variations from tourism operators’ perspective. The study also aims to shed light on how the marketing of Öland and media coverage of the weather conditions of the destination are contributing forces to weather sensitivity. Methodology: The study was conducted with a qualitative case study research method together with an inductive approach. Information has been collected through semi-structured interviews with respondents from four tourism businesses on Öland. The selection of the case study area and respondents have been through a convenience sample with respect to access and the nature of the research. Conclusion: The most important findings of the research results has shown that the lack of alternative tourism products is a major vulnerability for tourism operators in adverse weather conditions for the main activities. Research results have also shown that the focus of the marketing of the destination on specific weather attributes contributing to the destination vulnerability together with expectations on specific weather conditions among visitors.

臺灣被國際視為「自然災害很多，極度高風險的地區」，其中的天然災害，包括颱風。由於臺灣位於颱風路徑要衝，每年飽受颱風的威脅，根據氣象局的統計，從西元1911年至2015年總計有360個颱風侵襲臺灣，平均每年有3到4個，颱風引進的西南氣流或是伴隨而來的強降雨，更經常造成許多脆危地區嚴重災損。 現今科技的進步，預報技術日新月異，讓民眾可提早得知颱風警報，尤其電視新聞中有氣象報告之後，氣象主播提供天氣、颱風動態和影響的解說，更成了民眾日常生活中獲得天氣資訊的主要管道，根據國外文獻調查，觀眾對電視新聞最感興趣就是收看氣象。 螢光幕前負責氣象報告的氣象主播可以說是氣象科學、電視傳播媒體和社會大眾之間的重要橋樑，面對全球極端氣候，災變性氣候頻率增加，有許多天氣的最新動態、科學方面的知識和氣象素養更需要詳盡的解說，氣象主播的重要職責就是做好氣象傳播，提供民眾預警訊息。 西元1978年開始，臺灣出現專業的氣象主播，電視產業從早年的三臺壟斷到現今有線電視蓬勃發展，競爭白熱化的電視新聞生態，氣象報告時間也成了新聞戰場，各臺氣象主播更是搶收視率的重，要利器。氣象新聞相互較勁，每一家電視臺氣象主播使出渾身解數並強調自己的解說最權威，最精準，但民眾怎麼看？氣象主播所播報的訊息對於民眾做好防颱準備真的有幫助嗎？為了收視率，播報颱風動態，氣象主播創造新用語或是誇大形容，強化預警效果，民眾認同度又是如何？面對災變性天氣，氣象主播在風險溝通過程中，怎麼看待自己的定位？ 當網路科技興起之後，電腦或行動裝置日益改變民眾接受訊息的習慣，收看氣象主播播報天氣資訊的觀眾，收視行為是否也會有所轉變？本文將以蘇迪勒颱風災害防救的個案分析角度，一來了解氣象主播在災害防救上發揮怎麼樣的關鍵影響力，同時也希望在氣象主播的主題上做先探性的研究。 / Taiwan has been regarded by international as a high-risk area where suffers a lot of natural disasters such as typhoons. According to the Bureau of Meteorology statistics, from 1911 to 2015, a total amount of 360 typhoons attacked Taiwan, with an average of three to four per year. The southwest air flow introduced by typhoons as well as accompanied heavy rains have contributed serious damage to many areas. Thanks to today’s technology and the rapid advance of forecasting technology, people can access the typhoon information in advance, especially from the TV weather forecast. The weather anchor provides information on weather, typhoon dynamics, and impact with the audience. Watching weather report has become part of many people’s daily routine. According to foreign literature survey, the audience is most interested in weather report when they watch TV news. The weather anchor can be viewed as a person who builds the bridge between meteorological science, broadcast media and the public. Due to extreme weather and climate change and the increased rates of catastrophic natural disasters, the audience gets an urge to learn more about the weather and knowledge related to meteorology. Thus, the major duty of a weather anchor is to provide accurate weather information to help prepare the audience for natural disasters. Since 1978, we have had professional weather anchor in the local broadcast industry. Taiwan’s TV industry has gone from the three television stations (TTV, CTV, and CTS), representing the central government’s monopoly on television broadcasting, to booming cable TV today. TV Weather forecasting has become a battlefield in today’s broadcast industry— every weather anchor is competing for the ratings. Every weather anchor claims that they deliver the most authoritative and accurate weather information. However, what does the audience think of it? Is the information provided by the weather anchor helpful for them when it comes to disaster prevention? For the ratings, most weather anchors create fancy words or rather prone to exaggeration, how does the public respond to it? Facing the extreme weather and climate change, how does a weather anchor identify themselves in the process of weather communication? Today the internet has changed the way people access information. Does it also affect people’s behavior when it comes to watching weather news on TV? In this paper, we aim to focus on what the role a weather anchor plays in disaster prevention using a case study approach. Also, we hope our explorations and insights will contribute to your understanding of the role of a weather anchor.