This thesis focuses on the main processes in positive ground flashes and the distant lightning environment for both positive and negative ground flashes. It presents the characteristics of the preliminary breakdown pulses (PBPs), the characteristics of the electric field pulses observed during leader propagation, and the characteristics of the electric fields produced by the first and the subsequent return strokes. It also features the observations of distant positive and negative ground flashes at distances up to 1000 km. The results were based on electric field measurements conducted remotely during summer thunderstorms in Sweden in 2014. We found that the majority of the positive ground flashes were preceded by PBPs. Some were preceded by more than one PBP train, and the parameter values for the subsequent PBP trains were found to be smaller than the values for the first PBP train. Three types of PBPs were also identified. The results suggest that the PBPs in positive ground flashes during summer thunderstorms in Sweden are weak, and the inverted dipole charge cloud configuration is consistent with our observation. A small percentage of these positive ground flashes were observed to be preceded by pronounced leader pulses. The presence of these pulses suggests that the leaders propagate in a stepped manner. We inferred that these pulses were due to the upward-connecting negative leader since their characteristics were similar to those of a negative stepped leader. On the basis of the leader pulses’ time of initiation and the average speed of the leader, we estimated the distance travelled by the leader. One case of positive return stroke preceded by negative leader pulses was also observed, and the occurrence of these pulses was the first in positive ground flashes to be reported. The majority of these positive ground flashes were found to be single-stroke. Comparison between the first and the subsequent return strokes showed that the average durations of the subsequent stroke parameters were smaller than that of the first strokes. The distances reported by the lightning location system suggest that the subsequent strokes probably created new terminations to ground. Two possible reasons were given to explain the reason for the shorter duration of the subsequent return strokes parameters compared to the first strokes. Finally, observations of distant positive and negative ground flashes showed that the electric field waveforms have a typical shape, like a distorted ‘W’ (or distorted ‘M’ for negative ground flashes) followed by small oscillations. These small oscillations were more pronounced in negative ground flashes, especially at a greater distance. The heights of the ionospheric reflections estimated for both ground flashes were found to likely correspond to a D-layer of the ionosphere. Two possible reasons were suggested for the small oscillations observed in the waveforms.

Översvämningar till följd av skyfall har blivit allt vanligare och förväntas att öka i takt med klimatförändringarna. Översvämningar kan ställa till stora skador för ett samhälle, framförallt när de samhällsviktiga verksamheterna blir drabbade. För att undvika att detta sker bör samhället vara byggt för att tåla stora volymer vatten som faller vid ett skyfall. Ett steg för att nå dit är att göra en skyfallskartering där flödesvägar, vattenvolymer och översvämningens utbredning tas fram genom hydraulisk modellering. Utifrån skyfallskarteringen kan sårbara områden upptäckas och förebyggande åtgärder kan utföras för att minska översvämningens negativa påverkan. Akademiska sjukhuset i Uppsala är en samhällsviktig verksamhet och har tidigare haft problem med översvämningar. I den här studien har en skyfallskartering utförts på Akademiska sjukhusets område för att ta reda på översvämningens utbredning vid ett skyfall och vilka åtgärder som lämpar sig för att förhindra översvämningar. Skyfallskarteringen utfördes i det tvådimensionella (2D) hydrauliska modelleringsprogrammet MIKE 21 Flow Model. Eftersom en skyfallskartering baseras på många generaliseringar finns det vissa osäkerheter kring valet av parametrar. Därför har även en känslighetsanalys utförts kring valet av regntyp (Chicago Design Storm (CDS) jämfört med ett blockregn), regnets varaktighet, grönytornas avrinningskoefficient och markens infiltrationshastighet. Indata till modellen baserades på olika kartdata som bearbetades i GIS-programmet ArcMap. Flera olika regn med varierande återkomsttid simulerades. Resultaten visade att det blir översvämning inne på sjukhusområdet vid ett 100-årsregn som förvärras när återkomsttiden ökar. Åtgärdsanalysen utfördes genom att lägga in förändringar i höjdmodellen för att se hur det påverkar översvämningens utbredning. Analysen visade att åtgärder som jordvallar och höjdsättning av marken kan tillämpas på området för att minska översvämningsrisken. Resultatet från känslighetsanalysen visade att ett CDS-regn ger större översvämningskonsekvenser i modelleringen än om ett blockregn av samma återkomsttid och varaktighet används. Känslighetsanalysen av varaktigheterna visade att en lång varaktighet kan leda till låga flödestoppar som inte representerar ett skyfall väl. En avrinningskoefficient på 0,4 beskriver infiltrationen i området väl och när en större avrinningskoefficient används tenderar översvämningen att bli större på grönytorna. Till sist visade resultatet att infiltrationshastigheten är en känslig parameter som bör väljas efter mer noggrann analys av marken i modelleringsområdet. / Flooding as a cause of cloudbursts have become more common and is expected to increase with climate change. Floods can cause substantial damage to a society, especially when the critical societal functions are affected. To avoid this the city should be built to tolerate large volumes of water from cloudbursts. As a step on the way to accomplish this, a cloudburst mapping could be made where flow paths, water volumes and the extent of the flooding are studied through hydraulic modelling. Through the cloudburst mapping, vulnerable areas can be spotted, and flood prevention measures can be taken to lessen the extent of the floods negative impact. Uppsala University Hospital serves a critical societal function and has previously had problems with flooding. In this project a cloudburst mapping has been made in the two dimensinoal (2D) hydraulic modelling program, MIKE 21. This was done to find out the extent of a flood caused by a cloudburst event and what measures that can be taken to prevent floods. A cloudburst mapping is based off many generalized assumptions and there are some uncertainties when selecting the parameters. Because of this, a sensitivity analysis was performed on the selection of rain-type (Chicago Design Storm (CDS) vs. block-rain), rain duration, the runoff coefficient and the soil's infiltration capacity. The inputs of the model were based off different geographic data and then constructed in the GIS-program ArcMap. Several different rain events with varying duration and return periods were simulated. The results showed that there is considerable flooding in the area after a rain with a 100-year return period and it gets worse when the return period increases. The flood prevention analysis was made by editing the terrain to mimic flood prevention measures and study how the extent of the flood responds to the edits. The analysis showed that measures like soil barriers and changes in elevation were effective in lessening the risk of flooding. The results from the sensitivity analysis showed that a CDS-rain causes a more significant flooding compared to a block-rain of the same return period and duration. The sensitivity analysis of the rain duration proved that a long duration can lead to flat flow curves that doesn't resemble a flow curve from a cloudburst event. A runoff coefficient of 0.4 describes the infiltration in the area well and with a larger coefficient the flooding on greenery tend to grow. Lastly, the infiltration capacity proved to be a sensitive parameter that needs to be selected carefully, preferably after a thorough soil analysis.

Results are presented from the 2021 test run of active fire detection using the Visual Infrared Imaging Radiometer Suite (VIIRS) instrument, that is currently onboard the polar satellites Suomi-NPP and NOAA-20. The test is performed by the Swedish Civil Contingencies Agency and the Swedish Meteorological and Hydrological Institute, in cooperation with local fire departments in Sweden. The aim of this report was to study the impact of clouds on the ability of active fire detection, as well as to identify objects that potentially can cause commission errors in the VIIRS 375 m active fire algorithm (false positive notifications). Also, the study aimed to investigate what may cause omission errors in the algorithm, and to show to what extent the detections can be used to represent the true time development of the wildfire front and burned area. Using a cloudmask and a cloudtype classification product from Nowcasting Satellite Application Facilities (NWC SAF), the impact of clouds was anlalyzed by comparing the cloud data with the obtained fire notifications from the satellites. Active fires and newly burned areas were also studied using Sentinel-2 imagery, specifically the False Color Urban and the Short Wave Infrared (SWIR) RGB composites, as well as images from the 842 nm band, making use of the relatively high spatial resolution as well as the spectral signatures of fire and newly burned vegetation. Detection of active fires occurred in both cloud free and completely cloud covered conditions. How-ever, roughly 70% of the detected vegetation fire pixels were obtained in conditions with 20% clouds or less. / I rapporten presenteras resultat från 2021 års test av satellitdetektering av skogs- och vegetationsbränder, ett test som genomförs av MSB och SMHI i samverkan med kommunala räddningstjänster. De två satelliter som ingår i testet (Suomi-NPP och NOAA-20) går i polära omloppsbanor och är utrustade med instrumentet Visible Infrared Imaging Radiometer Suite (VIIRS). Detta projekt syftade till att undersöka hur molnighet påverkar möjligheten till detektion med satellit, vilka objekt som potentiellt kan ge upphov till falska detektioner samt vad som kan orsaka uteblivna satellitdetektioner. Ytterligare ett mål med rapporten var att genom fallstudier av större bränder undersöka i vilken utsträckning satellitdetektionerna kan användas för att representera brandfrontens utveckling med tiden och brandens faktiska utbredning. Vid studierna av molnighet analyserades en molnmask och en molnklassificeringsprodukt från Nowcasting Satellite Application Facilities (NWC SAF). I utvärderingen användes även data från Sentinel-2 för att studera pågående bränder och avbränd yta, som syns tydligt i RGB-kompositerna False Color Urban och Short Wave Infrared (SWIR) och i 842 nm-bandet, tack vare den relativt höga bildupplösningen och den nyligen avbrända ytans spektralsignatur. Brand detekterades i både molnfria och helt molntäckta förhållanden. Drygt 70 % av detektionerna vid vegetationsbrand kom emellertid i förhållanden med 20 % moln eller mindre.

In this project, we identified and examined the 50 coldest extreme temperature eventsin North America (CENA) and the 50 warmest extreme temperature events insouthwestern Europe (WEEU) during the winter seasons from 1948 to 2023. For theanalysis, we utilized daily NCEP-NCAR reanalysis data for temperature, sea levelpressure (SLP), and 500hPa geopotential height (Z500). Our main objective was toinvestigate the co-occurrence of CENA-WEEU events. To deepen our understandingof the recurrence of these events and their relationship with large-scale atmosphericpatterns and drivers, we examined the SLP and Z500 for the selected extreme events.The results revealed clear indications of an interconnection between CENA andWEEU. During the CENA, above-normal temperatures were observed over Europe,while negative temperature anomalies affected the eastern USA during the WEEU.This co-occurrence was further supported by the identification of seven CENA-WEEUextremes that occurred almost simultaneously. The findings regarding the large-scaleatmospheric drivers of these extremes align with previous studies. The CENAappears to be driven by an anomalous high ridge over the Gulf of Alaska and anortherly flow over North America, while the WEEU seems to be influenced by astrong, zonal and southerly shifted flow across the North Atlantic, associated with adeep trough over the British Isles and a ridge over the Mediterranean basin. Acommon feature of CENA-WEEU events is the presence of a negative North AtlanticOscillation (NAO)-like atmospheric pattern over the Atlantic Ocean prior to theiroccurrence.Despite the significant similarities between these events, some disparities relatedto the atmospheric flow and the magnitude of temperature anomalies in the twocontinents suggest the need for further investigation to enhance our understanding ofthe co-occurrence of CENA-WEEU events. / I detta projekt identifierades och studerades de 50 kallaste extrematemperaturhändelserna i Nordamerika (CENA) och de 50 varmaste extrematemperaturhändelserna i sydvästra Europa (WEEU) under vintersäsongerna från1948 till 2023. För analysen, användes dagliga NCEP-NCAR återanalys för demeteorologiska variablerna temperatur, tryck (SLP) och 500hPa geopotentialhöjd(Z500). Huvudsyftet med denna studie är att undersöka samförekomsten avCENA-WEEU-händelserna. För att fördjupa vår förståelse för återkommandehändelser och deras förhållande till storskaliga atmosfäriska mönster och drivkrafter,användes SLP och Z500 variablar för de utvalda extrema händelserna.Resultaten visade tydliga tecken på sammankoppling mellan CENA och WEEU.Temperaturer över det normala observerades över Europa under CENA, medannegativa temperaturanomalier påverkade östra USA under WEEU. Samförekomstenstöds ytterligare av identifieringen av sju CENA-WEEU-extremer som inträffadenästan samtidigt. När det gäller de storskaliga atmosfäriska drivfaktorer förextremerna, stämmer resultaten överens med tidigare studier. En starkhögtrycskrygg över Alaskagolfen och ett nordligt flöde över Nordamerika verkar drivaCENA, medan ett ett starkt, zon- och sydligt förskjutet flöde över Nordatlanten,associerat med intensiv cyklonaktivitet över de brittiska öarna och en högtrycksryggöver Medelhavsområdet, verkar vara källan till WEEU. Ett gemensamt drag förCENA-WEEU är förekomsten av ett negativt NAO-liknande atmosfäriskt mönster överAtlanten innan de inträffade.Trots de starka och många likheterna mellan händelserna, tyder vissa skillnaderrelaterade till atmosfärsflödet och extrema temperaturavvikelser på de bådakontinenterna, på behovet av ytterligare undersökningar för att fördjupa vår förståelseav samförekomsten mellan CENA och WEEU.

Dynamic Systems Theory (DST) and spectral analysis are employed to study the tropospheric jet stream and the stratospheric polar vortex. The objective is to investigate the relationship between Rossby wave activity and inverse persistence and dimensionality of geopotential height at 250 hPa and 10 hPa, as these two dynamical indicators are expected to show a characteristic behavior of Rossby wave harmonics. The results show that persistent states exhibit suppressed Rossby wave activity for eastward-propagating Rossby waves, whereas it is increased for the westward counterpart. Positive anomalies of spectral power at positive phase speeds are present for less persistent states. Events with low dimensionality relate to the suppression of most Rossby waves, while an increase in spectral power is present during high dimensional states. The results were more pronounced in the stratosphere compared to the troposphere with different spatial patterns of geopotential height anomalies due to additional factors influencing the location of Rossby waves. Furthermore, Sudden Stratospheric Warmings (SSWs) are connected to a decrease in persistence up to 2 weeks prior, followed by a significant increase in persistence and dimensionality, and reduced integrated spectral power. Strong Polar Vortex events (SPVs) exhibit the opposite behavior with an increase in persistence before and a decrease in persistence and dimensionality, and higher ISP afterward. Additionally, SSWs (SPVs) exhibit a suppression (enhancement) of Rossby wave activity in the stratosphere and to a lesser extent in the troposphere for eastwards traveling waves.

In this thesis, we have evaluated a stochastic Lagrangian model for computing particle deposition rates with prospects to use for atmospheric deposition applications.  The model is one-dimensional and models the particle dynamics in the boundary layers near walls and obstacles by simulating the coherent turbulent structures and Brownian motion governing the wall-normal transport. The deposition model is used with a hybrid deterministic/stochastic particle dispersion model governing the dynamics in the turbulent bulk flow. We used a steady-state RANS k-ϵ turbulence model to simulate the turbulent fluid flow in a neutral atmospheric boundary layer (ABL) using the with inflow boundary conditions by Richards & Hoxey (1993). The turbulence model is solved with the SIMPLE algorithm using the OpenFOAM software. The mean-field characteristic of the turbulent flow in the computational domain is exported and used for the particle model. The particle model is a Lagrangian Langevin-type model, consisting of a system of stochastic differential equations. The particle model was solved using a weakly first order a-stable scheme. We evaluated the deposition model by computing the deposition rate for a range of particle sizes and compared our results with collected experimental wind tunnel data. The numerical experiment was done in a computational domain based on the ABL model by Hargreaves & Wright (2007), a rectangular domain with a logarithmic wind profile. We used a particle source near the inflow boundary with an instantaneously release at the initial time. Results showed disagreement with the experimental data and was only valid for medium sized particles. However, time restrictions led to the analysis being cut short and only a single simulation was conducted. A definite conclusion on the suitability of the method could not be made based solely on this single results. Some uncertainties were identified and discussed for further potential work on the evaluation of the method. However, one conclusion was drawn on the performance of the method. The computational cost was concluded to be too high with the first order particle scheme used and higher order schemes is required for any practical use of the method for atmospheric deposition applications.

Accurate forecasts of wind speed and power production are of great value for wind power producers. In Southwest Iceland, wind power installations are being planned by various entities. This study aims to create optimal wind speed and wind power production forecasts for wind power production in Southwest Iceland by applying statistical post-processing methods to a deterministic HARMONIE-AROME forecast at a single point in space. Three such methods were implemented for a 22 month-long set of forecast-observation samples in 1h resolution: Temporal Smoothing (TS), Observational Distributions on Discrete Intervals (ODDI - a relatively simple classification algorithm) and Quantile Regression Forest (QRF - a relatively complicated Machine Learning Algorithm). Wind power forecasts were derived directly from forecasts of wind speed using an idealized power curve. Four different metrics were given equal weight in the evaluation of the methods: Root Mean Square Error (RMSE), Miss Rate of the 95-percent forecast interval (MR95), Mean Median Forecast Interval Width (MMFIW - a metric to measure the forecast sharpness) and Continuous Ranked Probability Score (CRPS). Of the three methods, TS performed inadequately while ODDI and QRF performed significantly better, and similarly to each other. Both ODDI and QRF predict wind speed and power production slightly more accurately than deterministic AROME in terms of their Root Mean Square Error. In addition to an overall evaluation of all three methods, ODDI and QRF were evaluated conditionally. The results indicate that QRF performs significantly better  than ODDI at forecasting wind speed and wind power at wind speeds above 13 m/s. Else, no strong discrepancies were found between their conditional performance. The results of this study are limited by a relatively scarce data set and correspondingly short time series. The results indicate that applying statistical post-processing methods of varying complexity to deterministic wind speed forecasts is a viable approach to gaining a probabilistic insight into the wind power potential at a given location.

Flood forecasting maps are essential for rapid disaster response and risk management, yet the computational complexity of physically-based simulations hinders their application for efficient high-resolution spatial flood forecasting. To address the problems of high computational cost and long prediction time, this thesis proposes to develop deep learning neural networks based on a flood simulation dataset, and explore their potential use for flood prediction without learning hydrological modelling knowledge from scratch.  A Fully Convolutional Network (FCN), FCN with multiple outputs (Multioutput FCN), UNet, Graph-based model and their Recurrent Neural Network (RNN) variants are trained on a catchment area with twelve rainfall events, and evaluated on two cases of a specific rainfall event both quantitatively and qualitatively. Among them, Convolution-based models (FCN, Multioutput FCN and UNet) are commonly used to solve problems related to spatial data but do not encode the position and orientation of objects, and Graph-based models can capture the structure of the problem but require higher time and space complexity. RNN-based models are effective for modelling time-series data, however, the computation is slow due to its recurrent nature. The results show that Multioutput FCN and the Graph-based model have significant advantages in predicting deep water depths (>50 cm), and the application of recurrent training greatly improves the long-term flood prediction accuracy of the base deep learning models. In addition, the proposed recurrent training FCN model performs the best and can provide flood predictions with high accuracy.

In the event of a radioactive release in an urban environment the consequent response mustbe swift and precise. As soon as first responders have correct information, they can make anaccurate risk assessment. However, if the position, release rate and time of the radioactiverelease is unknown it is hard to know how the pollutant will spread. This thesis aims to testa model which approximates these three unknowns using weather data (wind and rain) as wellas measurement data collected at sensors placed around an urban environment. An atmospheric dispersion model based on an existing Reynolds Averaged Navier-Stokes modelis set up in two geometries of different complexity to create forward mode synthetic depositiondata and adjoint mode concentration fields resulting from a fixed dry deposition velocity andscavenging effect for wet deposition. Variations of time- and space-dependent rainfall is simu-lated. The resulting data is used in an existing optimization model, where a parameter studyis conducted regarding regularization coefficients. This thesis shows that the optimization model accurately estimates position and its approximaterelease rate of a 2D geometry of radioactive releases using a logarithmic optimization approach,and fail to do so using a linear optimization approach. The logarithmic optimization model alsoapproximately estimates position and release rate in a 3D geometry. Regularization parametersshould be within the range of 0.1 and 1.2 depending on rain. More rain requires smallerparameters and will estimate a lower release rate. Time-dependent rainfall is shown to have amajor negative effect on simulation time.iii

Studien undersökte implementeringen och undervisningen av klimat och väder som år 2011 lades till under Fysik 1 i den svenska gymnasieskolan. Undersökningen använde sig av metodkombination som omfattade lärarintervjuer kompletterade med intervju av ett undervisningsråd på Skolverket och med textanalys av kursböcker. Lärarna upplevde en del problem kopplat till vad det nya ämnesområdet skulle innehålla. Oklarheten kring vad området skulle innehålla märktes också i kursböckernas framställning. Intervjupersonerna var överens om att viktiga aspekter inom ämnesområdet var växthuseffekten och global uppvärmning. Växthuseffekten och global uppvärmning hade även en framträdande roll i kursböckernas framställning. Från lärarintervjuerna framkom att lärarna gärna inkluderade Samhällsfrågor med Naturvetenskapligt Innehåll (SNI) i sin undervisning, men i bedömningen av elevernas lärande var det fysikalisk begreppsförståelse som accentuerades. Ämnesöverskridande samarbeten beskrevs av lärarna som önskvärt och förekom ofta. / This study examined the implementation and teaching of climate and weather which was added in the year 2011 under Physics 1 in the Swedish upper secondary school. The study performed a mixed-methods approach consisting of teacher interviews supplemented with an interview with an official at the Swedish National Agency for Education and with text analysis of course books. The teacher’s experienced some problems related to what the new subject area would contain. The uncertainty about what the area would contain was also seen in the course books. The interviewees’ opinion that the important issues in the subject area were the greenhouse effect and global warming were shared among the teachers. The greenhouse effect and global warming also had prominent roles in the course books. From the interviews it was found that teachers were positive to include Socio-Scientific Issues (SSI) into their teaching, but when assessing students learning the concepts of physics were emphasized. Cross-disciplinary cooperation was described by the teachers as desirable and often occurring.