# Browsing by Subject "Master's Programme in Atmospheric Sciences"

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Now showing items 1-20 of 48
• (Helsingin yliopisto, 2022)
Air ions can play an important role in new particle formation (NPF) process and consequently influence the atmospheric aerosols, which affect climate and air quality as potential cloud condensation nuclei. However, the air ions and their role in NPF have not been comprehensively investigated yet, especially in polluted area. To explore the air ions in polluted environment, we compared the air ions at SORPES site, a suburban site in polluted eastern China, with those at SMEAR II, a well-studied boreal forest site in Finland, based on the air ion number size distribution (0.8-42 nm) measured with Neutral Cluster and Air Ion Spectrometer (NAIS) during 7 June 2019 to 31 August 2020. Air ions were size classified into three size ranges: cluster (0.8-2 nm), intermediate (2-7 nm), and large (7-20 nm). Median concentration of cluster ions at SORPES (217 cm−3) was about 6 times lower than that at SMEAR II (1268 cm−3) due to the high CS and pre-existing particle loading in polluted area, whereas the median large ion concentration at SORPES (197 cm−3) was about 3 times higher than that of SMEAR II (67 cm−3). Seasonal variations of ion concentration differed with ion sizes and ion polarity at two sites. High concentration of cluster ions was observed in the evening in the spring and autumn at SMEAR II, while the cluster ion concentration remained at a high level all day in the same seasons. The NPF events occurred more frequently at SORPES site (SMEAR II 16% ; SORPES: 39%), and the highest values of NPF frequency at both sites were in spring ((SMEAR II: spring: 43%; SORPES: spring: 56%). During the noon time on NPF event day, the concentration of intermediate ions were 8-14 times higher than same ours on non-event days, indicating that can be used as an indicator for NPF in SMEAR II and SORPES. The median formation rate of 1.5 nm at SMEAR II were higher then that at SORPES, while higher formation rate of 3 nm ions were observed at SORPES. At 3 nm, the formation rate of charged particles was only 11% and 1.6% of the total rate at SMEAR II and SORPES respectively, which supports the current view that neutral ways dominate the new particle process in continental boundary. However, higher ratio between charged and total formation rate of 3 nm particle at SMEAR II indicates ion-induced nucleation can have a bigger contribution to NPF in clear area in comparison to polluted area. Higher median GR of 3-7 nm (SMEAR II: 3.1 nm h−1; SORPES: 3.7 nm h−1) and 7-20 nm (SMEAR II: 5.5 nm h−1; SORPES: 6.9 nm h−1) ions at SORPES were found in comparison to SMEAR II, suggesting the higher availability of condensing vapors at SORPES. This study presented a comprehensive comparison of air ions in completely different environments, and highlighted the need for long-term ion measurements to improve the understanding of air ions and their role in NPF in polluted area like eastern China
• (Helsingin yliopisto, 2021)
The Arctic Ocean is known to be inhabited with energetic mesoscale eddies commonly detected in depths from 200 m to 1200 m. Due to their high energetics and ability to transfer momentum, heat, salt and biochemical properties for long distances from their origin, eddies may considerably affect the structure of a water column in the Arctic Ocean. This study investigated an anticyclonic eddy event detected at one of the mooring stations deployed under the Nansen and Amundsen Basins Observational System project. The mooring located at the deep part of the continental slope of the Laptev Sea and conducted autonomous measurements during the years 2013–2015. The conductivity-temperature-depth, as well as current measurements from the Acoustic Doppler Current Profiler in the upper ocean (24–82 m) and from the McLane Moored Profiler in the intermediate layer (88–760 m), were examined. Spectral analysis of the currents and calculation of the eddy available potential energy were performed. This study revealed a mesoscale eddy with the core centred deeper than 750 m drifted past the mooring for 2 months. Its horizontal length scale was ∼128 km. The water properties typical for the Fram Strait Branch of the Atlantic water carried by the subsurface boundary current were trapped in the eddy. This study suggests that the eddy was originated from the baroclinic instability of the front between the Fram Strait Branch and the Barents Sea Branch of the Atlantic water flow.
• (Helsingin yliopisto, 2022)
Research in radar technology requires readily accessible data from weather systems of varying properties. Lack of real-world data can delay or stop progress in development. Simulation aids this problem by providing data on demand. In this publication we present a new weather radar signal simulator. The algorithm produces raw time series data for a radar signal using physically based methodology with statistical techniques incorporated for computational efficiency. From a set of user-defined scatterer characteristics and radar system parameters, the simulator solves the radar range equation for individual, representative precipitation targets in a virtual weather cell. The model addresses the question of balancing utility and performance in simulating signal that contains all the essential weather information. For our applications, we focus on target velocity measurements. Signal is created with respect to the changing position of targets, leading to a discernable Doppler shift in frequency. We also show the operation of our simulator in generating signal using multiple pulse transmission schemes. First, we establish the theoretical basis for our algorithm. Then we demonstrate the simulator's capability for use in experimentation of advanced digital signal processing techniques and data acquisition, focusing on target motion. Finally, we discuss possible future developments of the simulator and their importance in application.
• (Helsingin yliopisto, 2021)
Atmospheric aerosol particles absorb and scatter solar radiation, directly altering the Earth’s radiation budget. These particles also have a complex role in weather and climate by changing cloud physical properties such as reflectivity by acting as cloud condensation nuclei or ice nuclei. Aerosol particles in the boundary layer are important because they pose a negative impact on air quality and human health. In addition, elevated aerosol from volcanic dust or desert dust present an imminent threat to aviation safety. To improve our understanding of the role of aerosol in influencing climate and the capability to detect volcanic ash, a ground-based network of Halo Doppler lidars at a wavelength of 1565 nm is used to collect data of atmospheric vertical profiles across Finland. By comparing the theoretical values of depolarization ratio of liquid clouds with the observed values, bleed through of each lidar is detected and corrected to improve data quality. The background noise levels of these lidars are also collected to assess their stability and durability. A robust classification algorithm is created to extract aerosol depolarization ratios from the data to calculate overall statistics. This study finds that bleed through is at 0.017 ± 0.0072 for the Uto-32 lidar and 0.0121 ± 0.0071 for the Uto-32XR lidar. By examining the time series of background noise level, these instruments are also found to be stable and durable. The results from the classification algorithm show that it successfully classified aerosol, cloud, and precipitation even on days with high turbulence. Depolarization ratios of aerosol across all the sites are extracted and their means are found to be at 0.055 ± 0.076 in Uto, 0.076 ± 0.090 in Hyytiala, 0.076 ± 0.071 in Vehmasmaki and 0.041 ± 0.089 in Sodankyla. These mean depolarization ratios are found to vary by season and location. They peak during summer, when pollen is abundant, but they remain at the lowest in the winter. As Sodankylä is located in the Artic, it has aerosols with lower depolarization ratio than other sites in most years. This study found that in summer, aerosol depolarization ratio is positively correlated with relative humidity and negatively correlated with height. No conclusion was drawn as to what processes play a more important role in these correlations. This study offers an overview of depolarization ratio for aerosol at a wavelength of 1565 nm, which is not commonly reported in literature. This opens a new possibility of using Doppler lidars for aerosol measurements to support air quality and the safety of aviation. Further research can be done test the capability of depolarization ratio at this wavelength to differentiate elevated aerosol such as dust, pollution, volcanic ash from boundary layer aerosol.
• (Helsingin yliopisto, 2019)
Tämä työ tarkastelee kylmää jaksoa Pohjois-Euroopassa ja erityisesti Lapissa 1.1.2017 – 6.1.2017. Tarkastelujaksolla Sodankylässä mitattiin yli neljäkymmentä astetta pakkasta, jonka Euroopan keskipitkien ennusteiden keskuksen säämalli IFS ennusti pintalämpötilan yli kymmenen astetta liian korkeaksi. Kylmä jakso ylettyi aina Bulgariaan ja Kreikaan asti antaen viitteitä laajemmasta säähäiriöstä. Näistä lähtökohdista lähdin tutkimaan, mikäli lämpötilan yliennustuksen syy olisi laajemman synoptisen skaalan häiriön epätarkka ennustaminen. Työssä visualisoin IFS:n paine ja lämpötilakenttiä Euroopan keskuksen metview alustalla ja vertaan niitä synoptiseen analyysiin sekä pinta- ja luotaushavaintoihin Sodankylästä. Käytän pohjana Euroopan keskuksen omaa raporttia poikkeuksellisesta sääilmiöistä, joka kuitenkin keskittyy enemmän Kaakkois-Euroopan poikkeukselliseen kylmyyteen ja voimakkaisiin lumisateisiin. Työssä havaitaan, että IFS ennusti synoptisen skaalan matalapainejärjestelmien ja muiden säähäiriöiden synnyn ja liikkeet tarkastelujaksolla varsin hyvin. Syy pintalämpötilan yliennustamiseen ei arvioni mukaan johdu virtaustilanteen väärästä ennustamisesta, vaan mallin tavasta käsitellä pintalämpötilaa. Erittäin stabiileissa olosuhteissa oletukset, joiden perusteella mallin pintalämpötila lasketaan, eivät tuota järkevää tulosta. Luotauksista havaitaan, että Sodankylässä vallitsi voimakas pintainversio, jota malli ei kykene täysin mallintamaan johtuen tavasta, jolla se käsittelee pinnan ja alimman mallitason välistä kerrosta. Ennustettu lämpötila poikkeaa toteutuneesta kuitenkin niin voimakkaasti, että inversion mallintamiseen liittyvät ongelmat eivät välttämättä ole ainoa virhelähde. Lopuksi tarkastelen lyhyesti raportteja mallin ongelmista ennustaa pintalämpötilaa Suomen talviolosuhteisssa, sekä miten Euroopan keskipitkien säähavaintojen keskus on itse käsitellyt ongelmaa. Globaalimallina IFS on kalibroitu tuottamaan keskimäärin osuvin ennuste koko planeetalla, ja on tärkeä tietää ne rajatapaukset, joissa sen oletukset eivät ole päteviä.
• (Helsingin yliopisto, 2019)
The Arctic is warming faster than any other region on Earth due to climate change. The characteristics of the air masses overlying the Arctic play a key role when assessing the magnitude and implications of global warming in the region, but comprehensive studies of Arctic air mass properties covering long time series of measurements are scarce. The aim of this study is to use such a data set to quantify the key characteristics of Arctic air masses prior to transport to the human-habited Eurasian continent, and the typical conditions leading to Arctic events in Värriö. HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model was employed to calculate backward atmospheric trajectories arriving at SMEAR I (Station for Measuring Ecosystem-Atmosphere Relations) in Värriö for every hour in 1998-2017. An air mass was classified as Arctic if the backward trajectory arriving at Värriö was located north of 78 °N 72 hours before the arrival time. Data from SMEAR I, including meteorological variables and trace gas and aerosol concentrations, were then gathered in order to compare Arctic and non-Arctic air masses. Of all the hours that were analysed, 15.0 % were classified as associated with an Arctic air mass. The typically cyclonic curvature of the trajectories and the median duration of 10 hours per individual Arctic event were hypothesised to be due to Arctic air mass events being linked to passing low pressure systems. Arctic air masses were found to be colder and have lower moisture content in summer, when the difference at surface level was 5.6 °C and 1.7 g m-3 respectively, compared to non-Arctic air masses. In other seasons the differences were less pronounced, but average particle and trace gas concentrations were found to be notably lower for Arctic air masses than for non-Arctic air masses. An exception to this was ozone, which had 24.6 % higher average concentration in Arctic air masses in months between November and February, compared to non-Arctic air masses. The annual median aerosol particle concentration in Arctic air masses was found to be 308 cm-3 and only 129 cm-3 between November and March, on average. During a median year, the value of condensation sink (CS) was on average 65 % smaller in Arctic air masses than in the non-Arctic. The Kola Peninsula industry was observed to increase concentrations of SO2 and aerosol particles, particularly Aitken mode (25-90 nm) particles, of affected air masses. Overall, Arctic air masses were found to have several unique characteristics compared to other air masses arriving at SMEAR I, Värriö. As expected, Arctic air masses are colder and drier than non-Arctic air masses, but the difference is pronounced only in summer months. Other air mass characteristics, especially aerosol particle and trace gas concentration were generally found to be lower, unless the air mass was influenced by the industrial sites in the Kola Peninsula.
• (Helsingin yliopisto, 2020)
This thesis presents the Atmospherically Relevant Chemistry and Aerosol Box Model (ARCA box), which is used for simulating atmospheric chemistry and the time evolution of aerosol particles and the formation of stable molecular clusters. The model can be used for example in solving of the concentrations of atmospheric trace gases formed from some predefined precursors, simulation and design of smog chamber experiments or indoor air quality estimation. The backbone of ARCAs chemical library comes from Master Chemical Mechanism (MCM), extended with Peroxy Radical Autoxidation Mechanism (PRAM), and is further extendable with any new reactions. Molecular clustering is simulated with the Atmospheric Cluster Dynamics Code (ACDC). The particle size distribution is represented with two alternative methods whose size and grid density are fully configurable. The evolution of the particle size distribution due to the condensation of low volatile organic vapours and the Brownian coagulation is simulated using established kinetic and thermodynamic theories. The user interface of ARCA differs considerably from the previous comparable models. The model has a graphical user interface which improves its usability and repeatability of the simulations. The user interface increases the potential of ARCA being used also outside the modelling community, for example in the experimental atmospheric sciences or by authorities.
• (Helsingin yliopisto, 2022)
Suomen lentosäähavainnot käyvät läpi murrosta kohti automaatiota. Automaattisiin havaintoihin liittyy laatuongelmia, joten syntyi idea tehdä aiheesta laajempi tutkimus. Tutkimusaineistona käytettiin Rovaniemen lentoaseman havainnontekijöiden vuodesta 2011 lähtien täyttämää verifiointitaulukkoa, jossa ideana on kirjata manuaalisen havainnon tekohetkellä ylös automaattijärjestelmän tarjoamat arvot eri sääsuureille. Vertailtavat parametrit ovat näkyvyys, pilven alaraja ja vallitseva sää. Parametrien automaatin ja ihmisen määrittämät arvot ristiintaulukoitiin jokaiselle kolmelle parametrille erikseen. Tulokset eivät antaneet kovin hyvää kuvaa automaattihavaintojen nykyisestä laadusta, sillä kaikkien kolmen parametrin osalta havainnoista löytyi merkittäviä puutteita arvojen tarkkuudessa ja ajantasaisuudessa. Erot tarkaksi oletettuihin ihmishavaintoihin olivat niin suuria, että esiin nousi kysymyksiä lentoturvallisuuteen ja automaattihavaintojen käytön järkevyyteen liittyen. Tulosten pohjalta esitetään ratkaisuksi merkittäviä parannuksia havaintojärjestelmään sekä havaintojen tilapäistä manualisointia parannusprosessin ajaksi. Tutkielmassa käydään varsinaisen tutkimusosion lisäksi läpi Suomen lentosäähavaintojen teoriaa. Tekstissä pureudutaan syvemmin manuaalisen ja automaattisen havaintomenetelmän perusperiaatteisiin sekä esitellään Suomen lentosäähavaintojen historiaa pääpiirteittäin.
• (Helsingin yliopisto, 2021)
• (Helsingin yliopisto, 2020)
Biogenic Volatile Organic Compounds play a major role in the atmosphere by acting as precursors in the formation of secondary organic aerosols and by also affecting the concentration of ozone. The chemical diversity of BVOCs is vast but global emissions are dominated by isoprene and monoterpenes. The emissions of BVOCs from plants are affected by environmental parameters with temperature and light having significant impacts on the emissions. The Downy birch and Norway spruce trees consist of heavy and low volatile compounds but published results are limited up to observing sesquiterpenoid emissions from these two trees. In this study, the Vocus proton-transfer-reaction time-of-flight mass spectrometer is deployed in the field to examine BVOC emissions from Downy birch and Norway spruce trees. With higher mass resolution, shorter time response and lower limits of detection than conventional PTR instruments, the Vocus can effectively measure a broader range of VOCs. For the first time, real-time emissions of diterpenes and 12 different oxygenated compounds were observed from birch and spruce trees. The emission spectrum of birch was dominated by C10H17+, while for spruce C5H9+ contributed the most. The sum emissions of oxygenated compounds contributed significantly to the observed total emissions from both the trees. The emission rates of all compounds varied dramatically throughout the period due to fluctuations in temperature and light. Due to lack of data from spruce, conclusive results for temperature and light response on terpene emissions could not be drawn. For birch, the emission rates were well explained by the temperature and temperature-light algorithms. The terpene emissions modelled using both algorithms correlated similarly with experimental data making it difficult to decisively conclude if the emissions originated from synthesis or pools.
• (Helsingin yliopisto, 2022)
Ilmatieteen laitoksella on otettu käyttöön eri säämallien ennusteita yhdistelevä, niin sanotun konsensusennusteperiaatteen mukainen jälkikäsittelymenetelmä, joka tunnetaan nimellä Blend. Tämä tutkielman tarkoituksena on selvittää Blend-menetelmällä tuotetun tuuliennusteen toimivuutta Suomen merialueilla käyttämällä muutamaa yleiseen käyttöön vakiintunutta sääennusteiden verifiointimenetelmää. Verifiointi on toteutettu vertaamalla Blend-ennusteen tuulennopeusarvoja niin ikään jälkikäsittelyllä tuotettuihin potentiaalituuliarvoihin 25:llä Suomen merialueilla sijaitsevalla havaintoasemalla. Potentiaalituulta on päätetty käyttää alkuperäisten tuulihavaintojen sijasta, koska se parantaa eri sääasemilta tulevien mittaustulosten keskinäistä vertailukelpoisuutta ja näin ollen tekee verifiointituloksista paremmin koko alueelle yleistettäviä. Tulokset osoittavat odotetusti, että merkittävimmät Blend-tuuliennusteen toimivuuteen vaikuttavat tekijät ovat tuulennopeus ja ennustepituus – ennustevirhe kasvaa yleisesti suuremmilla tuulennopeuksilla ja pidemmillä ennustepituuksilla. Myös muilla muuttujilla, kuten vuorokauden- ja vuodenajalla sekä tuulen suunnalla, havaittiin olevan jonkin verran vaikutusta ennustevirheeseen. Useimmissa säätilanteissa Blend-ennusteen voidaan todeta olevan toimivuudeltaan varsin hyvä ja tasalaatuinen. Blend-ennusteen merkittävin ongelma on etenkin suurilla tuulennopeuksilla huomattavan suuri negatiivinen harha (bias), eli ennustetut tuulennopeudet ovat havaintoihin nähden selvästi liian heikkoja. Tästä johtuen Blend ei useimmissa tapauksessa kykene ennustamaan kovimpia tuulia, jotka ovat harvinaisuudestaan huolimatta operatiivisen sääennustamisen kannalta kaikista tärkeimpiä mm. merialueille annettavien tuulivaroitusten vuoksi. Menetelmä on kuitenkin kehityskelpoinen, ja jos ennusteharha pystytään jatkossa minimoimaan laskennassa paremmin, se saattaa kyetä tuottamaan jopa varsinaisia säämalleja parempia tuuliennusteita.
• (Helsingin yliopisto, 2020)
Urban areas account for 70% of worldwide energy-related CO2 emissions and play a significant role in the global carbon budget. With the enhanced consumption of fossil fuel and the dramatic change in land use related to urbanization, control and mitigation of CO2 emissions in the urban area is becoming a major concern for urban dwellers and city managers. It is of great importance and demand to estimate the local CO2 emissions in urban areas to assess the effectiveness of mitigation regulation. Surface Urban Energy and Water Balance Scheme (SUEWS) incorporated with a CO2 exchange module provides an advanced method to model total urban CO2 flux and quantify the different local-scale emission sectors involving transportation, human metabolism, buildings and vegetation. Using appropriate input data such as detailed site information and meteorological condition, it can simulate the local or neighbourhood scale CO2 emissions in a specific period, or even under a future scenario. In this study, the SUEWS model is implemented in an urban region, Jätkäsaari, which is an extension of Helsinki city centre, to simulate anthropogenic and biogenic CO2 emissions in the past and future. The construction of this district started in 2009 and was planned to be completed in 2030. Therefore, this region is a good case to investigate the impacts of urban planning on urban CO2 emissions. Based on the urban surface information, meteorological data, and abundant emission parameters, a simulation in this 1650 × 1400 m area with the spatial resolution of 50 × 50 m and the time resolution of an hour was conducted with the aim to get information on the total annual CO2 emissions, and the temporal and spatial variability of CO2 fluxes from different sources and sink in 2008 and 2030. The positive CO2 fluxes indicate the CO2 sources, while the negative indicate the CO2 sinks. In both of the previous and future case, the spatial variation of net CO2 fluxes in Jätkäsaari is dominated by the distribution of traffic and human activities. From April to September, the vegetation acts as the CO2 sink with negative net ecosystem exchange. In 2008, the modelled cumulative CO2 flux is 3.0 kt CO2 year-1, consisting of 1.9 kt CO2 year-1 from metabolism, 1.9 kt CO2 year-1 from traffic, 0.5 kt CO2 year-1 from soil and vegetation respiration, as well as -1.3 kt CO2 year-1 from photosynthesis. In 2030, the total annual CO2 emissions increase to 11.1 kt CO2 year-1 because of the rising traffic volume and amount of inhabitants. Road traffic became the dominant CO2 sources, accounting for 53% of the total emissions. For the diurnal variation, in 2008, the study area remains the CO2 sources with the exception of summertime morning when the net CO2 flux is negative, while in 2030, the net CO2 flux is positive in the whole day.
• (Helsingin yliopisto, 2022)
Small arctic glaciers have in general been consistently neglected with respect to the collection of long time-series observations. Available data is often a product of multiple independent and separate studies, thus gaps in the data sets are common. Numerical modelling provides one solution to alleviate existing gaps in knowledge, while historical observations can be used to assess model accuracy. The Foxfonna ice cap and associated glacier were investigated with the aid of the numerical modelling software, Elmer/Ice. The goal was to reproduce core glaciological characteristics of the entire glacier system from a 3D simulation based on multiple digital elevation models (DEMs) between the years 1961-2021. The methods proved capable of providing additional information on the glaciological characteristics of a small glacier system, such as Foxfonna. Issues primarily arose from the steady state assumption and the difficulty of producing simulations for a dynamically varying glacier system.
• (Helsingin yliopisto, 2021)
International shipping is globally a major source of atmospheric nitrogen oxides (NOx). It has been widely recognized that these emissions have negative effects on maritime air quality and human health. For a long time, shipping was the least regulated NOx emission source, but now first regulations for ship exhaust NOx emissions started as of January 2021. Shipping emissions must be monitored so the obedience of these regulations can be followed. Different measurement techniques are developed to address the problems related to shipping emission monitoring. The purpose of this thesis is to demonstrate how tropospheric nitrogen dioxide (NO2) concentration measurements by TROPOspheric Monitoring Instrument (TROPOMI) onboard Copernicus Sentinel 5 Precursor (S5P) satellite can be used to characterize signatures of shipping emissions. The capability of TROPOMI to detect busy shipping lanes and port areas was first tested with a large study area of the whole Eastern Mediterranean Sea. Analysis was supported with shipping emission data inventory from the Ship Traffic Assessment Model (STEAM). Results showed elevated NO2 concentrations close to major port areas, especially if the dominant wind direction on the water area was from the continent. These elevated concentrations were most likely a result of both transported urban emissions and shipping emissions. STEAM and TROPOMI grid cell comparison was done over the busiest shipping lane area over the open sea, and the results showed that if the monthly summed shipping emission amount was either small or very large, the signal of shipping emissions was affected by background concentrations. More detailed shipping emission study was done at port Piraeus and the surrounding sea area. There, satellite measurement analysis was done by selecting three smaller study areas for comparison, one over the city of Athens, the second one close to the port Piraeus and the third one over the open sea. Relation between the satellite observations of NO2 and modelled shipping emissions of NOx was obtained in the study area that was over the open sea, the center of the area being 35 km from the coast. The signal of shipping emissions was not detected close to the port, most likely because of the influence of other emission sources. Lastly, spring and summer 2020 were analysed separately in more detail, as they were included in the overall study period of this thesis but the air pollution patterns at that time were affected by the extraordinary COVID-19 pandemic restrictions. The results showed unusually small average NO2 concentrations over the city of Athens during spring 2020. Meteorological observations from that time period did not show anything that could fully explain the decrease. Observations over the sea close to Piraeus showed no clear difference between 2019 and 2020 average concentrations, so the pandemic possibly had only a minor impact on the shipping emissions in the port area.
• (Helsingin yliopisto, 2021)
Cumulonimbus (Cb) clouds form a serious threat to aviation as they can produce severe weather hazards. Therefore, it is important to detect Cb clouds as well as possible. Finnish Meteorological Institute (FMI) provides aeronautical meteorological services in Finland, including METeorological Aerodrome Report (METAR). METAR describes weather at the aerodrome and its vicinity. Significant weather is reported in METARs, and therefore Cb clouds must be included in it. At Helsinki-Vantaa METARs are done manually by human observer. Sometimes Cb detection can be more difficult, for example, when it is dark, and it is also expensive to have human observers working around the clock all year round. Therefore, automation of Cb detection is a topical matter. FMI is applying an algorithm that uses weather radar observations to detect Cb clouds. This thesis studies how well the algorithm can detect Cb clouds compared to manual observations. The dataset used in this thesis contains summer months (June, July and August) from 2016 to 2020. Various verification scores can be calculated to analyse the results. In addition, daytime and night-time differences are calculated as well as different years and months are compared together. The results show that the algorithm is not adequate to replace human observers at Helsinki-Vantaa. However, the algorithm could be improved, for instance, by adding satellite observations to improve detection accuracy.
• (Helsingin yliopisto, 2022)
Utveckling inom masspektrometri har varit en av de drivande faktorerna för de senaste decenniernas framsteg inom förståelsen av atmosfärens kemi. Den data som samlas in med hjälp av masspektrometri är en av de största tillgångarna för fortsatt utveckling av kunskapen inom detta område. Dock är analysen av denna data en långsam och arbetsdryg process, och nya metoder krävs för att göra tillgänglig all den information som finns att utnyttja inom denna data. Den här avhandlingens mål var att utveckla en algoritm för automatisk identifiering av kemiska sammansättningar ur masspektrum med begränsad resolution. Målsättningen för algoritmen är att avsevärt minska på den tid som krävs för analys av masspektrum. Algoritmen fungerar genom att välja sammansättningar som maximerar sannolikheten att observera den data som observerats ($\chi^2$-anpassning) och väljer sedan den mest kostnadseffektiva modellen. Den mest kostnadseffektiva modellen syftar på den modell som nöjaktigt kan förklara data med så få sammansättningar som möjligt. För att identifiera den mest kostnadseffektiva modellen användes en modifierad version av det Bayesiska informationskriteriet. Algoritmens funktionsprinciper vidareutvecklades utgående från resultaten som erhölls från test av algoritmen med syntetisk data. Den slutliga algoritmen testades med data som samlats in i samband med tidigare experiment. Algoritmens resultat jämfördes med resultaten för analysen som gjordes i samband med experimenten. På basen av resultaten fungerar algoritmen. De val algoritmen gör motiveras av data, och motsvarar i de flesta fall de val som en forskare gör vid motsvarande tillfällen. Således kan algoritmen i sin nuvarande form tillämpas för analys av masspektrum, och förväntas kunna förkorta den tid som krävs för att identifiera kemiska sammansättningar ur masspektrum betydligt. Dock identifierades också ett antal utvecklingsområden som förväntas förbättra algoritmens prestation ytterligare.
• (Helsingin yliopisto, 2022)
Tässä työssä on tutkittu Euroopan ja Pohjois-Atlantin talvi-ilmaston muuttumista 30-vuotisjaksojen 1961–1990 ja 1991–2020 välillä. Aineistona on käytetty Euroopan keskipitkien sääennusteiden keskuksen (ECMWF) kehittämää ERA5-uusanalyysidataa, jossa on assimiloitu havaintoja sääennustusmallin tuottamaan alkuarvauskenttään. Karttakuvat on piirretty niin ikään ECMWF:n kehittämällä ohjelmistolla, Metviewillä. Lämpötilan muutoksen pystyleikkauskuvan piirtämiseen on puolestaan käytetty Pythonin numpy- ja matplotlib.pyplot -kirjastoja. Työssä on tarkasteltu ilmanpaineessa, suihkuvirtauksessa, lämpötilassa, pystyliikkeissä, kosteudessa ja sademäärässä tapahtuneita muutoksia. Ennen varsinaisia tuloksia tutkielmassa on selitetty meteorologisiin suureisiin liittyvää fysikaalista teoriaa: miten paine, lämpötila ja tiheys ovat riippuvaisia toisistaan, kuinka geostrofinen tuuli syntyy sekä mitkä tekijät vaikuttavat sateen syntyyn. Kaikissa tarkasteltavissa suureissa on havaittu muutoksia. Lämpötilat ovat nousseet lähes koko Euroopan ja Pohjois-Atlantin alueella: eniten Pohjois-Euroopassa ja Pohjoisella jäämerellä sekä vähemmän Etelä-Euroopassa. Ilmanpaine on noussut Pohjois-Euroopassa ja Pohjois-Atlantin pohjoisosassa sekä laskenut Etelä-Euroopassa ja Pohjois-Atlantin eteläosassa. 250 hPa:n painepinnan Pohjois-Atlantin keskimääräinen suihkuvirtausmaksimi on voimistunut ja liikahtanut hieman pohjoisemmaksi. Sademäärät ja ilman sisältämän vesihöyryn määrä ovat kasvaneet Pohjois-Euroopassa ja pienentyneet Etelä-Euroopassa. Nousu- ja laskuliikkeet ovat monin paikoin voimistuneet. Muutosten tilastollisen merkitsevyyden tutkimiseen on käytetty Studentin kaksisuuntaista t-testiä. Alatroposfäärin lämpötilan muutos on eniten tilastollisesti merkitsevä, mutta muidenkin suureiden muutoksissa tilastollista merkitsevyyttä havaittiin laajalti. Tämä on loogista, sillä lämpötilan muutokset ovat kytköksissä myös muiden suureiden muutoksiin. Aiheesta on tehty myös aiemmin tutkimuksia, joiden tulokset ovat pääosin yhteensopivia tämän työn tulosten kanssa. Ainoastaan 500 hPa:n painepinnan geopotentiaalikorkeuden trendissä oli pientä eroavaisuutta. Tässä tutkielmassa muutosten tilastollinen merkitsevyys oli suurempaa kuin aiemmissa tutkimuksissa.
• (Helsingin yliopisto, 2021)
In atmospheric sciences, measurements provided by remote-sensing instruments are crucial in observing the state of atmosphere. The associated uncertainties are important in nearly all data analyses. Random uncertainties reported by satellite instruments are typically estimated by inversion algorithms (ex-ante). They can be incomplete due to simplified or incomplete modelling of atmospheric processes used in the retrievals, and thus validating random uncertainties is important. However, such validation of uncertainties (or their estimates from statistical analysis afterwards, i.e. ex-post) is not a trivial task, because atmospheric measurements are obtained from the ever-changing atmosphere. This Thesis aims to explore the structure function method – an important approach in spatial statistics – and apply it to total ozone column measurements provided by the nadir-viewing satellite instrument TROPOMI. This method allows us to simultaneously perform validation of reported ex-ante random uncertainties and to explore of local-scale natural variability of atmospheric parameters. Two-dimensional structure functions of total ozone column have been evaluated based on spatial separations in latitudinal and longitudinal directions over selected months and latitude bands. Our results have indicated that the ex-post random uncertainties estimated agree considerably well with the reported ex-ante random uncertainties, which are within 1-2 DU. Discrepancies between them are very small in general. The morphology of ozone natural variability has also been illustrated: ozone variability is minimal in the tropics throughout the year, whereas in middle latitudes and polar regions they attain maxima in local spring and winter. In every scenario, the ozone structure functions are anisotropic with a stronger variability in the latitudinal direction, except at specific seasons in polar regions where isotropic behaviour is observed. Our analysis has demonstrated that the structure function method is a remarkable and promising tool for validating random uncertainties and exploring natural variability. It has a high potential for applications in other remote sensing measurements and atmospheric model data.
• (Helsingin yliopisto, 2022)
To evaluate whether CMIP6 models provide good simulation in Arctic sea-ice extent, thickness, and motion, selected 6 CMIP6 models are EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, GFDL-ESM4, MPI-ESM1-2-HR, NORESM2-LM. For CMIP6 models and observations, seasonal cycle and the annual variation from 1979-2014 of sea-ice extent were studied, for sea-ice thickness and sea-ice motion, the Arctic is separated into three regions, geographical distribution, inter-annual variation from 1979-2014, seasonal cycle, and trend were studied. Then student t-test is used to evaluate whether the model output has a significant difference from observation, to select the best model(s). For sea-ice extent, EC-Earth3 is overestimating sea-ice extent, especially in winter, BCC-CSM2-MR model underestimates sea-ice extent, ACCESS-CM2, MPI-ESM1-2-HR, NorESM2-LM models perform the best. For sea-ice thickness, BCC-CSM2-MR underestimates sea-ice thickness, EC-Earth3, ACCESS-CM2, and NORESM2-LM models are overestimating sea-ice thickness. GFDL-ESM4 and MPI-ESM1-2-HR have the best performance at sea-ice thickness simulation. For sea-ice motion, the MPI-ESM1-2-HR model overestimates sea-ice drifting speed all year round, ACCESS-CM2 model tends to overestimate sea-ice drifting speed in summer for region1 and region2, in region3 ACCESS-CM2 model mostly overestimate sea-ice motion except winter months. NorESM2-LM model has the best performance overall, and ACCESS-CM2 has the second-best simulation for region1 and region2. EC-Earth3 also has a satisfactory simulation for sea-ice motion. Models and observation also agree on common results for sea-ice properties: Maximum sea-ice extent occurs in March, and minimum sea-ice extent occurs in September. There's a decreasing trend of sea-ice extent. The Central Arctic and Canadian Archipelago always have the thickest sea ice, followed by the East Siberian Sea, Laptev Sea, and Chukchi Sea, Beaufort Sea. East Greenland Sea, Barents Sea, Buffin Bay, and the Kara Sea always have the thinnest sea ice. There's a decreasing trend for sea-ice thickness according to models, sea-ice is thicker in the Chukchi Sea and the Beaufort Sea than in Laptev and East Siberian seas. Winter sea-ice thickness is higher than in summer, and sea-ice thickness has a more rapid decreasing rate in summer than in winter. Laptev and the East Siberian Sea have the most rapidly sea-ice thinning process. Sea-ice thickness has seasonal cycle that maximum usually occurs in May, and minimum sea-ice thickness happens in October. For sea-ice motion, there's an increasing trend of sea-ice motion, and summer sea-ice motion has faster sea-ice motion than winter, Chukchi Sea, and the Beaufort Sea has faster sea-ice motion than Laptev and the East Siberian Sea. Corresponding with the comparatively faster-thinning in the Laptev and the East Siberian Seas simulated by models, there's also a faster increasing rate in the Laptev and the East Siberian Sea.
• (Helsingin yliopisto, 2019)
Atmospheric aerosols affect the Earth's radiative balance, visibility and human health. Therefore the formation processes and growth of these particles are important and should be studied to understand how human and natural processes affects these processes. One poorly understood and relatively little studied part of aerosols is particulate organic nitrates (pONs). These pONs are mostly formed during nighttime when NOx, mainly emitted from fossil fuel combustion and industrial processes, and volatile organic compounds (VOCs), from both natural and anthropogenic sources, reacts in the atmosphere. The quantification of these pONs is still hard due to instrumental restrictions, although much improvement has happened during recent years. One main reason for these challenges is the difficulty to separate inorganic nitrates from organic nitrates with real-time instruments. During this work, we generated pure pON in well controlled laboratory conditions and sampled it with an Aerosol Mass Spectrometer (AMS), an instrument widely used for measuring the chemical composition of atmospheric aerosols. We used four different pON precursors to generate pON. I investigated the fragmentation patterns of pON detected by the AMS, utilizing the high resolution of the newest model of the AMS. As older versions of the AMS has difficulties to separate nitrate-containing organic fragments due to lower resolution than the AMS I used, I was able to study pON mass spectrum with better resolution than anyone before me. I found mass spectral differences for the different pON precursors, and was able to find unique fragments for some of the pON precursors that possibly can be used as marker fragments.