Wind energy as renewable energy will be crucial in ensuring future energy supply. Foundation for agood implementation of wind power output in the electrical grid are wind forecasts. Especially windpower ramp forecasting is important for an effective generation of wind power energy by wind parks.Wind power ramps are large changes in wind power output over a relative short amount of time. Thiswork compares two statistical definitions for four Swedish wind parks using 15 years of data from theNew European Wind Atlas data. This model provides, among other variables, the wind speed and direction at for wind power relevant height with a temporal solution of 30 min. Compared to absolutedefinitions, commonly used to define wind power ramps, a statistical definition is beneficial since it considers each site’s climatology. Based on this definition, a random forest classifier identifies wind speedand direction as the most important variables when forecasting wind power ramps. When fine-tuned, therandom forest classifier could become a valuable tool for forecasting wind power ramps.

Polar mesoscale cyclones (PMCs) are low-pressure systems that form in polar regions. Their small size and short lifespan pose challenges for coarse resolution models in capturing PMCs and their associated air-sea mass and energy transfer. To address the influence of resolution on PMCs, a comparison between a higher resolution dataset (CARRA with 2.5 km resolution) and a lower resolution reanalysis dataset (ERA5 with 30km resolution) over a 10-year period in the North Atlantic is conducted by employing an automatic algorithm. The results revealed that CARRA detected a greater number of PMC activities, highlighting the benefits of higher resolution data in reducing uncertainties during tracking. PMCs identified using CARRA exhibited smaller vortex sizes, but higher relative vorticity and faster movement speeds compared to ERA5 results. Notably, the typical vortex diameters derived from ERA5 and CARRA were 80 km and 120 km, respectively. Furthermore, the climatology of PMCs in the North Atlantic is presented. Monthly variations indicated that the majority of PMCs occurred during winter, with only a few cases developing in summer. The spatial distribution exhibits that the highest density of PMCs was observed in the Irminger Sea and the Norwegian Sea. It also shows that the presence of sea ice can influence the PMC density, as a significant number of cases formed near the sea ice edge. The comparison results indicate that the current coarse climate simulation may underestimate the influence of PMCs in the Arctic due to the misrepresentation of them, thus introducing uncertainties in the climate prediction.

This thesis examines the co-occurrence of wintertime low temperature extremes (cold spells) over North America and wet or windy extremes over Europe. Prolonged (≅ 5 days) North American cold spells can be associated with both upstream and downstream anomalous large-scale atmospheric flows, the latter modulating extreme weather occurrences over Europe. The approximate co-occurrence of European wet or windy extremes with North American cold spells is temporally and spatially dependent on the location of cold spells. We identify three broad regional clusters of cold spells:  Central Canada: cold spells are predominantly preceded by Iberian precipitation extremes. Eastern United States: occurrences of both wind and precipitation extremes in Iberia before and after the cold spell. East Canada: cold spells are predominantly followed by wind extremes over the British Isles and Northern Europe. We show that cold spells over these three regions are associated with distinct storm track and jet stream anomalies over the North Atlantic. Iberia experiences a higher number of extratropical cyclones during Central Canada cold spells due to an equatorward displacement of the jet. However, the propagation of extratropical cyclones over Europe is limited due to a Scandinavian block-type configuration over Northern Europe. Eastern United States cold spells show a similar configuration to Central Canada. However, this configuration does not show the Scandinavian block-type feature, resulting in a higher number of extratropical cyclones affecting Iberia and Southern Europe. Eastern Canada cold spells are associated with an extended and accelerated jet over Northern Europe. As a result, the UK, France and Northern Europe experience more intense extratropical cyclones on average, with the accelerated jet resulting in stronger extratropical cyclones throughout the North Atlantic in general. These results evidence the existence of a systematic statistical and dynamical connection between North American cold spells and European wet or windy extremes.

This study primarily focuses on comparing coincident ozone profiles, as well as investigating the relationship between the polar vortex and the changes in the ozone layer above Kiruna, Sweden (67.85N 20.22E) during the Arctic winters 2010/2011 and 2018/2019. The instruments used are the Kiruna Microwave Radiometer (KIMRA); a millimeter wave radiometer that allows continuous observations of the evolution of ozone and other trace gases in the Arctic stratosphere, and the Microwave Limb Sounder (MLS) instrument on board the Aura satellite. The KIMRA and MLS measurements are compared to each other over the periods November 2010 to March 2011, as well as November 2018 to March 2019. Overall, the KIMRA and MLS comparison show good agreement, with KIMRA measuring more O3 in the lower stratosphere (around 50hPa) than MLS both during the daytime and nighttime. The O3 time series of KIMRA and MLS, along with the polar vortex edge based on equivalent latitudes, show minimum ozone concentrations when Kiruna was situated well inside the polar vortex.

SIW, Stratospheric Inferred Winds, is one of the upcoming Swedish research satellites, aiming to study the winds in the middle atmosphere by measuring the Doppler shifts in molecules such as O3 with a limb viewing sub-mm spectrometer. By conducting simulations on the expected observations, the pointing sensitivity requirement of the satellite was investigated to be able to optimise the matching of the wind vectors. The development of SIW is in the early phases and therefore few studies of this topic has been conducted. The Python program AMATERASU (Advanced Model for Atmospheric TeraHertz Radiation Analysis and Simulation) developed by P. Baron has been used to calculate the radiative transfer through the atmosphere with the aim of simulating the satellite observations and the induced pointing errors, both horizontal and vertical. The results indicate that the effects of the horizontal pointing errors are neglectable due to their small contributions to the measurements. If horizontal pointing errors were induced the scan bias could be corrected for in the retrieval to a good degree for all species and the wind. If not corrected for, H2O and O3 were the most affected species and something to take into consideration during further development of the satellite design. The optimisation of the wind vectors showed that the bias of the matching could get decreased by changing the angle between the satellite antennas. / SIW, Stratospheric Inferred Winds, är en av de nästkommande svenska forskningssatelliterna som ämnar att studera vindarna i mellanatmosfären genom att mäta dopplerskift från molekyler så som O3 med en sub-mm spektrometer som skannar atmosfären från sidan. Simuleringar av de förväntade observationerna genomfördes för att bestämma gränsen för känsligheten i pekningen i kravspecifikationen och optimera matchningen av vindvektorerna. Utvecklingen av SIW är fortfarande i ett tidigt stadie och studier kring detta är få. Pythonprogrammet AMATERASU (Advanced Model for Atmospheric TeraHertz Radiation Analysis and Simulation) som är utvecklat av P. Baron har använts för att räkna ut strålningstransfern genom atmosfären och därmed kunna simulera satellitens förväntade observationer och de inducerade pekfelen, både horisontella och vertikala. Resultaten indikerar att effekterna av de horisontella pekfelen är försumbara på grund av deras låga påverkan på mätningarna. Vid vertikala pekfel kunde pekfelet korregeras för i återvinningen i hög grad för alla ämnen och vinden. Om pekfelet inte korregerades för var H2O and O3 de mest påverkade molekylerna och något som måste tas i beaktning under vidare utveckling av satellitdesignen. Optimeringen av vindvektorerna visade att skillnaden för matchningen kan minskas genom att ändra vinkeln mellan satellitantennerna.

The main purpose of this thesis is to examine the mineral dust aerosol transport into the Arctic. Two three-dimensional reanalysis datasets of atmospheric composition, the Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), are analyzed with regard to dust transport into the Arctic. The reanalyses agree on that the largest mass transport of dust into the Arctic occurs across western Russia during spring and early summer, although large dust transport events can occur across other geographical areas during all seasons. In several aspects, the reanalyses show substantial differences. The transport in CAMSRA is considerably smaller, more concentrated and occurs at lower altitudes. Furthermore, the transport in CAMSRA is to a larger extent than MERRA-2 driven by well-defined events of dust transport in space and time. The reanalysis data are compared with surface measurements of dust in the Arctic and dust extinction satellite retrievals from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The comparison indicates that CAMSRA underestimates the dust transport into the Arctic and that MERRA- 2 likely overestimates it. The discrepancy between CAMSRA and MERRA-2 can in part be explained by the assimilation process where too little dust is assimilated in CAMSRA while MERRA-2 overestimates the production of light particles, causing an excessive transport, and the assimilation process further increases the dust concentration in remote areas. Despite the clear differences between the reanalyses, this study provides new insights into the spatio-temporal distribution of the dust transport into the Arctic and the transported mass is estimated to be within the range 1.5–31 Tg yr-1. The thesis also briefly examines the aerosol transport of all five aerosol species carried by the reanalyses, that in addition to dust are black carbon, organic matter, sea-salt and sulfate. The annual aerosol mass transport to the Arctic in CAMSRA and MERRA-2 are 24 Tg and 50 Tg respectively. The reanalyses show substantial differences regarding the proportions of the different aerosol types — emphasizing that it is crucial that the aerosol module manages to simulate the correct aerosol mass fractions, as the assimilation of AOD alone cannot change the proportions between the aerosols.

Surface gravity waves alter the turbulence of the bottom atmosphere and the upper ocean. Accordingly, they can affect momentum flux, heat fluxes, gas exchange and atmospheric mixing. However, in most state-of-the-art Earth System Models (ESMs), surface wave influences are not fully considered or even included. Here, applying surface wave influences into ESMs is investigated from different aspects. Tuning parameterisations for including instantaneous wave influences has difficulties to capture wave influences. Increasing the horizontal resolution of models intensifies storm simulations for both atmosphere-wave coupled (considering the influence of instantaneous wave-induced stress) and stand-alone atmospheric models. However, coupled models are more sensitive to the horizontal resolution than stand-alone atmospheric models. Under high winds, wave states have a big impact on the sea spray generation. Introducing a wave-state-dependent sea spray generation function and Charnock coefficient into a wind stress parameterisation improves the model performance concerning wind speed (intensifies storms). Adding sea spray impact on heat fluxes improves the simulation results of air temperature. Adding sea spray impact both on the wind stress and heat fluxes results in better model performance on wind speed and air temperature while compared to adding only one wave influence. Swell impact on atmospheric turbulence closure schemes should be taken into account through three terms: the atmospheric mixing length scale, the swell-induced momentum flux at the surface, and the profile of swell-induced momentum flux. Introducing the swell impact on the three terms into turbulence closure schemes shows a better performance than introducing only one of the influences. Considering all surface wave impacts on the upper-ocean turbulence (wave breaking, Stokes drift interaction with the Coriolis force, Langmuir circulation, and stirring by non-breaking waves), rather than just one effect, significantly improves model performance. The non-breaking-wave-induced mixing and Langmuir circulation are the most important terms when considering the impact of waves on upper-ocean mixing. Accurate climate simulations from ESMs are very important references for social and biological systems to adapt the climate change. Comparing simulation results with measurements shows that adding surface wave influences improves model performance. Thus, an accurate description of all important wave impact processes should be correctly represented in ESMs, which are important tools to describe climate and weather. Reducing the uncertainties of simulation results from ESMs through introducing surface gravity wave influences is necessary.

Låga moln definieras av att ha molnbasen från 0 till 2 km ovanför markytan. Molnbildande bygger på att den relativa fuktigheten stiger med höjden tills vattenångan i luften kondenseras. Prognosmodeller för moln bygger på grundläggande termodynamiska och fluiddynamiska ekvationer. Områden delas in i ett rutnät och ekvationerna löses med numeriska metoder. För jämförelse kan mätinstrument samt observationer användas, såsom ceilometrar, radar eller observatörer.  Resultat från fyra olika experiment med prognosmodeller för moln används i detta arbete, som är en litteraturstudie för att undersöka modellers förmåga att simulera låga moln. Olika platser, på global och lokal skala, undersöks. Makroskopiska parametrar såsom molnandel och molnfrekvens är i fokus.  WRF-modellen fungerar bäst med 12 km horisontell upplösning, med en viss överskattning av molnfrekvensen. Modellen CAM5 simulerar molnandel väl men vatteninnehåll och isinnehåll underskattas respektive överskattas. Säsongscykler av låga moln fångas väl av modellerna ECMWF, ARPEGE, RACMO och Met Office, med viss överskattning från samtliga modeller. GFS-modellen överskattar molnandelen långt från ekvatorn med upp mot 80% men underskattar nära ekvatorn med 10–20%. Överskattningar och underskattningar kan bero på faktorer såsom otillräcklig representation av mikrofysik eller möjligtvis felaktiga mätdata. Det denna studie visar är däremot att prognosmodeller på lokal skala kan ge bra simuleringar av makroskopiska parametrar av låga moln. / Cloud types are defined by the height of their bases. Low-level clouds have cloud base heights between 0 and 2 km. They are formed when the relative humidity in the air reaches 100 %, leading to the formation of cloud droplets. Forecast models simulate clouds by integrating thermodynamic and fluid dynamic equations using numerical methods. Instruments and observations, such as ceilometers or observers, are used to assess the accuracy of these simulations.  This study uses four previous works, where forecast models have been used to forecast clouds, to study the accuracy of low-level cloud forecasts. This is done on both local and global scales, focusing on macroscopic characteristics such as cloud fractions and frequencies. The results show that the WRF model works best with a horizontal resolution of 12 km, with slight overestimation of cloud frequencies. The climate model CAM5 simulates cloud fractions well, but liquid- and ice content deviate significantly from measurements. Seasonal cycles are generated well by ECMWF, ARPEGE, RACMO and Met Office Unified Model, with reoccurring overestimations by all models. The GFS model overestimates cloud fractions in higher latitudes by up to 80%, but underestimates near the equator by 10-20%.  Lacking representation of microphysics in the models, or faulty data, can be the causes for deviations in the models. However, this study has shown that forecast models can simulate macroscopic parameters of low-level clouds on a local scale well.

By using climate models based on the Earth’s climate, you can get information about how the climate on exoplanets can look like. ROCKE-3D is a general circulation model based on ModelE2, which is used for simulations of modern and prehistoric Earth’s climate. ROCKE-3D, on the other hand, is used to simulate terrestrial planets both in our solar system and around other stars. The orbital eccentricity affects a planet’s climate, if the eccentricity is high, the planet will be closer to its star certain parts of the year and further away from it for other parts. Because of this, it is interesting to study the eccentricity’s influence on the climate of exoplanets, especially since the boundaries of the habitable zone change. In this report, the climate of an Earth-like planet with varying orbital eccentricity has been investigated using ROCKE-3D. The results show that the annual average temperature increased if the eccentricity increased, even though it was expected to decrease because the planet was further away from its star for longer periods than it was closer. The reason for this was that the ocean dampened the surface temperature drop. The amount of snow and ice was also examined. As eccentricity increased, the ocean ice became thicker and snow accumulated in the northern hemisphere. This can be explained, even though the annual average temperature increased due to the warmer winters, by the fact that the temperature in the summer decreased so much that the snow and ocean ice did not melt away completely and started to accumulate for the years with higher eccentricities.

In many numerical weather prediction models, the presence of lakes is simulated crudely, with their effect being neglected in the resulting simulations. However, it has been shown how lakes effect not only their surrounding climate directly, but have an effect to the overall weather evolution and ecosystem. It is therefore vital to improve existing models to take lakes into account, by coupling with smaller models specificaly compiled for a reas with lakes. There have been several sophisticated models to parameterizelakes in a geographical area, which are, on the other hand, computationally expensive and time consuming. A model built specifically on simple physical assumptions, named FLake, aims to provide a solution that is not heavy computationally, but is accurate enough and contains all the necessary physics surrounding the heat budget and temperature of a given lake. For this project, FLake was tried on a lake close to Uppsala, named Erken, where the validity of the model was tested against data archives from Erken Laboratory’s measurement tower. The resulting simulations were very promising regarding the water temperatures, as well as giving out acceptable results for the surface heat fluxes above the lake and the duration of the ice period, as it was modeled by FLake and compared with ice data archives.