Browsing by study line "Meteorologia"
Now showing items 1-20 of 44
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(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.
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(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.
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(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.
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(2021)Carbon monoxide (CO) is a chemically reactive trace gas in the atmosphere, indirectly affecting radiative balance. The oxidation of CO with hydroxyl radical (OH) is the large sink of atmospheric CO. The reactions of CO and OH decrease the atmospheric capacity to oxidize atmospheric methane (CH4), hence indirectly extends the lifetime of CH4 in the atmosphere. In addition, CO oxidation increases the abundance of tropospheric ozone (O3). CH4 and O3 are both very strong greenhouse gases, and it has been estimated that the cumulative indirect radiative forcing of CO can be even more significant than the third most powerful greenhouse gas, nitrous oxide. This study studied CO fluxes in four different ecosystems: a boreal forest, a boreal fen, a cropland in the boreal region, and a sisal plantation in the semi-arid tropical zone. All the ecosystems were CO sources during the growing season from May to August, and ecosystems showed strong seasonal variation. Fluxes had a regular diurnal cycle, peaking at noon and zero flux or small uptake at night. The main drivers for the CO emissions were radiation and air temperature. The strong correlation between radiation and CO flux proved that photodegradation was an important process in biogenic CO emissions. Radiation and air temperature were used in a simple linear regression model to estimate the biogenic CO emissions in the study sites. The model was trained for Hyytiälä data in 2016, tested for the rest of the data from Hyytiälä in 2015 and 2017 and other sites. The chamber measurements showed that soils were CO sinks and CO emissions were mainly from vegetation. Generally, in many upscaling models of CO, soil consumption is considered significantly larger than photodegradation. This study showed that many terrestrial ecosystems can be sources of CO, even though there are generally considered as a sink of CO. There is a need for ecosystem-scale flux measurements in other ecosystems and latitudes to understand better the global CO budget.
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(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.
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(2024)Diurnal temperature range (DTR), defined as the difference between daily maximum and minimum temperatures, is an important variable in ecosystem dynamics. Human-induced climate change, which has increased mean temperatures worldwide, has been noted to cause global changes in DTR. In this thesis, the changes in daily maximum and minimum temperatures, as well as diurnal temperature range, were studied between the climatological periods of 1961–1990 and 1991–2020 from twenty weather observation stations in Finland. Student’s t-test was utilized to assess the statistical significance of the differences between period mean values. The results show that daily maximum and minimum temperatures have risen significantly across Finland in all seasons. The differences between 1961–1990 and 1991–2020 mean values were +1.26 °C and +1.51 °C for daily maximum and minimum temperatures, respectively. Both daily maximum and minimum temperatures have risen most notably in winter (DJF), with daily extreme temperatures increasing asymmetrically. The increase in temperatures was more pronounced for daily minimum temperatures, rising by approximately 3 °C in winter, nearly one degree more than daily maximum temperatures during the same season. Annually averaged diurnal temperature range has generally decreased in Finland from 1961–1990 to 1991–2020. The decrease in DTR was statistically significant in the northern part of Finland, and overall, the country experienced a statistically significant decrease of −0.25 °C. The decreases in annual mean DTR exhibited a latitudinal pattern, with the largest decrease observed in northern Finland and smallest in southern Finland. The majority of the decrease in DTR occurred during winter across the country, whereas changes in the other seasons were smaller and varied in direction. A decrease in DTR in Finland has been reported by other studies, although the results in this thesis (−0.09 °C/decade trend) are larger in amplitude compared to other estimates. The decrease in winter DTR was attempted to be explained by changes in air mass advection, which substantially influences diurnal temperature range in addition to influencing day-to-day variations in temperature. It was concluded that changes in air mass advection have substantially influenced the changes in winter DTR, but they may not necessarily explain all of the observed changes. Cloud cover changes were examined using ERA5 reanalysis data, but these changes were judged to be unimportant for the decrease in winter DTR. However, asymmetrical cloud cover changes in the other seasons could have potentially contributed to the differing direction of DTR change observed in spring, summer and autumn across the country.
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(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.
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(2023)In this thesis I have examined wind gust cases in Finland that have occurred during the summer season between 2010 and 2021. The main goal of the thesis was to find convective wind gust cases of non-tornadic origin, also known as damaging straight-line winds, and find out whether the gust on the surface could have been, in theory, solely caused by the slow advection of strong upper-level winds to the surface or whether another factor, such as a strong downdraft, must have played a role in the creation of the gust. Convective wind gusts occur in Finland every summer, but despite this, the amount of research on them and the damage they can cause has been relatively small in the past compared to gusts caused by extratropical cyclones, for example. To find suitable wind gust cases, weather data from the Finnish Meteorological Institute (FMI) was downloaded. After scanning through the data to find cases, which were suspected of being convective origin, ERA5 reanalysis data developed by the European Centre for Medium-Range Weather Forecasts (ECMWF) was downloaded from the locations and times of the gusts’ occurrence. Also chosen for further examination, for comparison purposes, were wind gust cases suspected of being caused by extratropical cyclones. The FMI wind gust speed and wind speed data was visualized in line charts, while the ERA5 data values of wind speed, equivalent potential temperature and relative humidity were tabulated and visualized in vertical cross sections. The visualization was done with the help of Python’s matplotlib.pyplot library and the MetPy toolbox. The results indicated that the differences between gust cases caused by convection and gust cases caused by extratropical cyclones can be clearly seen from the reanalysis data. As for the convective cases themselves, the data indicated that in several of them the gust could have been caused by the slow advection of strong upper-level winds to the surface on its own, in theory at least. However, in the majority of the cases the data indicated that the gust was likely the result of a strong downdraft or possibly by a combination of a downdraft and advection. Besides this, the values of the examined parameters and their visualization revealed that damaging straight-line winds can occur under various conditions in Finland.
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(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.
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Effect of forest management on carbon and energy budgets on mineral soil, in pine forests in Finland (2024)Topic of this Master's thesis was to study how different forest management practises can influence the climate change mitigation potential of Finnish pine forests. Study was carried out with a land ecosystem model JSBACH-FOM. Topic was analyzed by comparing the changes in the carbon budget, surface albedo and the water balance over a 45 year period under different management scenarios. Harvest scenarios used were ecology oriented, balanced and profit oriented harvest. In the ecology oriented harvest scenario mainly old pines are harvested, while in the profit oriented scenario harvests are directed towards younger pines preventing them from reaching old ages. Balanced harvest scenario is between the two. Model was also run under two future climate scenarios, RCP 4.5 and RCP 8.5 in order to determine if the scale of climate change affects results of different harvest scenarios. Profit oriented harvesting results in both the largest positive and largest negative impacts in comparison to if forest was left unmanaged. Ecologically oriented is the opposite, and balanced is in between. No significant differences were found between the climate scenarios in any of the modelled variables.
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(2023)In order to reliably quantify the impact of cities to the climate change, carbon dioxide (CO2) fluxes from urban areas need to be accurately estimated. Currently, eddy covariance (EC) measurements of net ecosystem exchange (NEE) are among the most used methods for CO2 balance assessment at ecosystem scale. They cannot, however, directly separate gross primary production (GPP) from different sources of CO2 , but instead different tracers and methods need to be used for the separation. In this thesis, urban carbonyl sulfide (COS) fluxes are reported and used as a tracer for biogenic CO2 uptake. For estimating GPP, a leaf-relative uptake (LRU) of CO2 and COS during photo- synthesis has to be calculated. Three different methods for ecosystem scale LRU estimations are compared in order to find which performs the best at assessing urban GPP from EC measurements. LRUNEE method is based on averaging LRU obtained directly from an equation using EC measurements of CO2 and COS. LRUP AR uses parameterisation of photosynthetically available radiation (PAR) to estimate LRU, and LRUCAP uses additional environmental parameters and information of soil water content (SWC), water vapour pressure deficit (VPD) and PAR. EC measurements were conducted at SMEAR III station (ICOS ecosystem associate site) in Helsinki during summer 2022 using a quantum cascade laser gas analyser. Mole fractions of COS, CO2, CO, and water vapour were collected with 10 Hz frequency, together with three-dimensional wind speed measurements. 30-min fluxes were calculated and used for estimating LRU and GPP with the three methods above. Source area of the station was divided into urban, street, and vegetation sectors. To compare different LRU methods, EC measured GPP from vegetation sector was used because it had the smallest anthropogenic emissions. CO and COS fluxes were compared to estimate co-emissions from fuel combustion. Median COS flux of −25.5 pmol m−2 s−1 was measured, indicating a biogenic CO2 uptake in the study area. For simplicity, soil related COS fluxes were neglected. LRUPAR performed the best at estimating GPP, giving an average CO2 uptake of 13.9 μmol m−2 s−1 for the vegetation sector. Furthermore, peak median anthropogenic emissions of 9.1 μmol m−2 s−1 were deduced with LRUPAR, which agrees with earlier research. However, due to problems with instrumentation the data collection period was so short that distinction between LRUPAR and LRUCAP was not unambiguous. Clear is that setting a constant value for LRU leads to significant underestimation of GPP, and a misunderstanding of its behaviour in heterogeneous urban landscape. Further development of COS based GPP estimation should include a more careful instrumentation and revision of the parameterisation of LRUCAP method.
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(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.
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(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.
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(2022)Tässä tutkielmassa tarkastellaan horisontaalisten gravitaatiovaihteluiden vaikutusta ilmakehän perusyhtälöihin sekä yksinkertaisen ilmakehämallin tuloksiin erilaisissa simulaatioissa. Työn motivointina oli tutkia putoamiskiihtyvyyden vaikutusta mallinnustarkkuuteen, koska se on yksi monista säänennustus- ja ilmastosimulaatioihin liittyvistä epätarkkuustekijöistä. Ilmakehän perusyhtälöt johdettiin aluksi uudelleen huomioimalla gravitaation vaihtelu vaakasuunnassa. Tämän jälkeen vastaavat yhtälömuutokset tehtiin SPEEDY-mallin lähdekoodiin, ja mallin avulla tehtiin simulaatioita gravitaatiovaihteluiden vaikutusten selvittämiseksi. Jotta tulosten analysointi olisi mahdollisimman helppoa, käytettiin simulaatioissa paljon yksinkertaistuksia. Näistä merkittävin oli mallimaapallon korvaaminen vesiplaneetalla. Yhtälömuutosten oikeellisuus mallissa verifioitiin yhden aika-askeleen kokeilla, minkä jälkeen muokatuille perusyhtälöille tehtiin suuruusluokka-analyysi. Analyysin perusteella gravitaatiovaihteluista aiheutuvat lisätermit olivat pääosin yhdestä kahteen kertaluokkaa yhtälöiden muita termejä pienempiä. Lopuksi tehtiin kymmenen vuoden simulaatioita, joissa tarkasteltiin niin sanotun normaaligravitaatiojakauman vaikutuksia mallin tuloksiin. Näissä kokeissa havaittiin, että meteorologisten suureiden anomaliat olivat pääosin maltillisia, mutta eivät merkityksettömän pieniä. Esimerkiksi tuulikentässä havaitut muutokset olivat suurimmillaan noin 2 m/s, kun taas lämpötila-anomaliat jäivät globaalisti alle puoleen asteeseen. Meridionaalisen kiertoliikkeen anomaliassa havaittiin puolestaan selkeä antisymmetria pallonpuoliskojen välillä: intertrooppinen konvergenssivyöhyke siirtyi päiväntasaajalta leveyspiirin 10°S tienoille, kun taas leveyspiirillä 5°N nousuliike heikkeni. Lisäksi länsituulet hidastuivat pohjoisen pallonpuoliskon keskileveysasteilla, mutta voimistuivat eteläisellä pallonpuoliskolla. Tulosten perusteella aiheen tutkimista kannattaa jatkaa myös tulevaisuudessa.
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(2023)Numerical weather prediction models are the backbone of modern weather forecasting. They discretise and approximate the continuous multi-scale atmosphere into computable chunks. Thus, small-scale and complex processes must be parametrised rather than explicitly calculated. This introduces parameters estimated by empirical methods best fit the observed nature. However, the changes to the parameters are changing the properties of the model itself. This work quantifies the impact parameter optimisation has on ensemble forecasts. OpenEPS allows running automated ensemble forecasts in a scientific setting. Here, it uses the OpenIFS model at T255L91 resolution with a 20 min timestep to create 10-day forecasts, which are initialised every week in the period from 1.12.2016 to 30.11.2017. Four different experiments are devised to study the impact on the forecast. The experiments only differ in the parameter values supplied to OpenIFS, all other boundary conditions are held constant. The parameters for the experiments are obtained using the EPPES optimisation tool with different goals. The first experiment minimises the cost function by supplying knowledge regarding the ensemble initial perturbation. The second experiment takes a set of parameters with a worse cost function value. Experiments three and four replicate experiments one and two with the difference that the ensemble initial perturbations are not provided to EPPES. The quality of an ensemble forecast is quantified with a series of metrics. Root mean squared error, spread, and continuous ranked probability score are used with ERA5 reanalysis data as the reference, while the filter likelihood score is providing a direct comparison with observations. The results are summarised in comprehensive scorecards. This work shows that optimising parameters decreases the root mean square error and continuous ranked probability score of the ensemble forecast. However, if the initial perturbations are included in the optimisation the spread of the ensemble is strongly limited. It also could be shown that this effect is reversed if the parameters are tuned with a worse cost function. Nonetheless, when excluding the initial perturbations from the optimisation process, then a better model can be achieved without sacrificing the ensemble spread.
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Improved Integration of Ground-Based Low-Level Wind Shear Alert Systems Using a Grid-Based Approach (2022)Low-level wind shear is a significant aviation hazard. A sudden reduction in the headwind along an aircraft flight path can induce a loss of lift, from which an aircraft may not be able to recover when it is close to the ground. Airports therefore use low-level wind shear alert systems to monitor wind velocities within the airport terminal area and alert of any detected hazardous wind shear. There exist three ground-based sensor systems capable of independently observing low-level wind shear: a Doppler weather radar-based, a Doppler wind lidar-based, and an anemometer-based system. However, as no single sensor system is capable of all-weather wind shear observations, multiple alert systems are used simultaneously, and observations from each system are integrated to produce one set of integrated wind shear alerts. Algorithms for integrating Doppler weather radar and anemometer wind shear observations were originally developed in the early 1990s. However, the addition of the Doppler wind lidar-based alert system in more recent years warrants updates to the existing radar/anemometer integration algorithms. This thesis presents four different replacement candidates for the original radar/anemometer integration algorithms. A grid-based integration approach, where observations from different sensor systems are mapped onto a common grid and integrated, is found to best accommodate central integration considerations, and is recommended as the replacement to the original radar/anemometer algorithms in operational use. The grid-based approach is discussed in further detail, and a first possible implementation of the algorithm is presented. In addition, ways of validating the algorithm and adopting it for operational use are outlined.
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(2021)Accuracy and general performance of weather radar measurements are of great importance to society due to their use in quantitative precipitation estimation and its role on flood hazard risks prevention, agriculture or urban planning, among others. However, radars normally suffer from systematic errors such as attenuation, misscalibration in Z field or bias in Zdr field, or random errors such as clutter, beam blockage, noise, non-meteorological echoes or non-uniform beam filling, which affect directly the rain rate estimates or any other relevant product to meteorologists. Impact of random errors is reduced by exploiding the polarimetric properties of polarimetric radars by identifying and classifying measurements according to their signature and a classification scheme based on the available polarimetric variables, but systematic errors are more difficult to address as they require a ’’true’’ or reference value in order to be corrected. The reference value can either be absolute or obtained from another radar variable. In reality, an absolute reference value is not feasible because we normally do not know what we are observing with the radar. Therefore, a way of assesing this issue is by elaborating theoretical relations between radar variables based on their consistency when measuring a volume with hydrometeors of known characteristics such as size and concentration. This procedure is known as self-consistency theory and it is a powerful tool for checking radar measurements quality and correcting offsets causing bias, misscalibration or attenuation. The theoretical radar variables themselves can be simulated using available T-Matrix scattering algorithms, that estimate the scattered phase and amplitude for a given distribution of drops of a given size. Information of distribution of drops of a given size, commonly referred as drop size distributions, can be obtained, for instance, from gauge or disdrometer measurements. Once the theoretical relations among radar variables are established, it is possible to check the consistency of, for instance, measured differential reflectivity with respect to differential reflectivity calculated as function of measured reflectivity, assuming the latter has been filtered properly, and any discrepancy between the observed and theoretical differential reflectivity can be thus attributed to offsets in the radar. This work thus presents a methodology for the revision of radar measurements filtering and quality for their improvement by correcting bias and calibration, using theoretical relations between radar variables through self-consistency theory. Furthermore, as the aforementioned issues are easier to track and resolve in the liquid rain regime of precipitation, this work presents a detailed description of methodologies to exclude ice-phased hydrometeors such as the melting layer detection algorithm and its operational implementation along with other complementary filters suggested in the literature. Examples of the melting layer detection and filtering as well as self-consistency curves for radar measurement performance evaluation are also provided.
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(2024)Ilmatieteen laitoksen ylläpitämä Suomen virallisten sademittarien havaintoverkko on harva ja sen laajentaminen vaatisi enemmän resursseja. Kansalaisten sadehavaintojen hyödyntäminen olisi yksi keino laajentaa havaintoverkkoa ja siten muun muassa parantaa sääennusteiden laatua. Tässä tutkielmassa selvitettiin kansalaisten Netatmo-kesäsadehavaintojen käyttökelpoisuutta Suomessa. Vuosien 2019–2022 kesä-, heinä- ja elokuun Netatmo-sadehavaintojen laatua tutkittiin vertailemalla niitä Ilmatieteen laitoksen automaattisadeasemien havaintoihin. Vertailua tehtiin tilastollisten suureiden, keskiarvon, korrelaation ja absoluuttisen keskivirheen, avulla. Ennen varsinaista analyysia pyrittiin rajauksilla selkeyttämään aineistoa sekä poistamaan siitä selvästi virheellisiä Netatmo-sadeasemia ja -havaintoja, kuten yli 150 mm:n tunti- ja yli 200 mm:n vuorokausisademäärät. Pääsääntöisesti Netatmo-sadehavainnot näyttävät tilastollisten suureiden valossa hyviltä, sillä esimerkiksi 75 % Netatmo- ja lähimpien Ilmatieteen laitoksen asemien välisistä vuorokausisateiden korrelaatioista oli vähintään 0.6. Netatmo-havaintojen välinen vaihtelu oli kuitenkin suurempi kuin Ilmatieteen laitoksen asemien havaintojen, mikä kertoo osan Netatmo-havainnoista olevan virheellisiä. Virheitä löytyi useita erilaisia. Yleisesti monien Netatmo-asemien havaittiin aliarvioivan sademäärää, koska keskimäärin Netatmo-asemat olivat mitanneet sateita vajaat 10 % vähemmän kuin niiden vertailuasemat. Lisäksi Netatmo-asemien havainnoissa oli huomattavasti enemmän pieniä 0.1 mm mittauksia kuin Ilmatieteen laitoksen vertailuasemilla eikä osa asemista ollut mitannut mitään 0.1 mm virhemittauksia lukuunottamatta. Jotkut Netatmo-asemat puolestaan mittasivat yksittäin tai jopa jatkuvasti virheellisiä hyvin suuria sademääriä. Osa asemista myös yliarvioi sademäärää, sillä asemien sateet korreloivat hyvin vertailuasemien sateiden kanssa ollen vain paljon suurempia. Toisaalta joidenkin Netatmo-asemien realistiset sadehavainnot oli mitattu eri aikoihin kuin vertailuasemien sateet, joten asemien koordinaatit voivat olla väärät. Välillä taas Netatmo-havaintojen laatu muuttui ajan myötä, sillä kyse on kansalaisten havainnoista. Asemat saattoivat ensin tuottaa hyviä havaintoja ja sitten huonoja tai päinvastoin. Kaikkiaan Netatmo-kesäsadehavainnot vaikuttavat käyttökelpoisilta, koska suurin osa havainnoista on hyviä. Netatmo-asemat myös saavat suuria sateita kiinni hyvin. Lisäksi huonoja havaintoja korrelaation perusteella tuottavat Netatmo-asemat ovat hajallaan eri puolilla Suomea ja hyviä asemia on kaikkialla enemmän. Koska virheellisiä Netatmo-asemia ja -havaintoja on silti varsin paljon, Netatmo-sadehavainnot tarvitsevat kattavaa laadun varmistusta ennen havaintojen hyödyntämistä. Laadun varmistusta voisi tehdä tämän tutkimuksen tavoin vertailemalla havaintoja tilastollisesti Ilmatieteen laitoksen asemien havaintoihin. Lisäksi Netatmo-havaintoja voisi verrata keskenään.
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(2023)The parameterization of deep convection is simulated poorly over the Central and East Pacific. This could lead to issues in predicting the annual total precipitation in the tropics, such as the existence of a double intertropical convergence zone over the equatorial Pacific. Resolving tropical deep convection instead of parameterization leads to the presence of more linear systems. Observations over Atlantic indicate that shear-perpendicular lines (squall lines) propagate faster than shear- parallel lines, mainly due to their connection with the low-level vertical wind shear (VWS). The study examines the different movement speeds of mesoscale convective systems (MCSs) over the East- and West Pacific to determine whether this could explain the reason why climate models have problems with predicting deep convection. A higher proportion of fast moving MCSs (squall lines) could contribute to the prediction problems in the tropics. The MCS motion is determined by the sum of the mean wind and propagation speed. In squall lines, the MCS motion is mainly influenced by the propagation, which is associated with the low-level VWS. Therefore, the effect of the low-level VWS on the fast- and slow moving MCSs is also investigated. The Global High-Resolution Mesoscale Convective System Database is used, which provides infor- mation about the time, location and movement of MCSs. Additionally, ERA5 wind data is used to obtain the mean wind and VWS. Two specific areas over the northern equatorial Pacific are chosen to compare the different types of MCSs. These areas are over the East Pacific (120°W - 140°W and 5°N - 12°N) and West Pacific (140°E - 160°E and 0°N - 7°N). The movement speed is used to categorize the MCSs into three groups: slow moving MCSs (< 3 m/s), moderate moving MCSs (3 m s−1 − 7 m s−1) and fast moving MCSs (> 7 m/s). The study reveals that the share of the fast moving MCSs is 9.8% over the East Pacific and 13.8% over the West Pacific. This is only a 4 percent point difference between the two areas. Therefore, it is not shown that the fast moving MCSs contribute to the existing issues that models have in predicting the annual total precipitation over the East Pacific. Moreover, approximately 85-90% are categorized as slow- to moderate moving MCSs. Hence, the influence of fast moving MCSs is relatively small when compared to the other types. A difference is seen in the mean wind and VWS over the East Pacific, but do not explain the MCS motion vector. Therefore, the difference between fast- and slow moving MCSs cannot be explained by only the monthly averaged mean wind and low-level VWS over the East Pacific. Over the West Pacific, the mean wind direction and VWS are about the same in direction and speed. Therefore, the difference between fast- and slow moving MCSs is not explained by the low-level VWS over the West Pacific.
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(2024)The purpose of this master's thesis is 1) to determine the meteorological structure and evolution of extra-tropical cyclones that develop in an idealized aqua-planet simulation, which utilizes a newly developed way to represent the large-scale initial state of the atmosphere; and 2) to examine the Lorenz energy cycle of this simulation. The simulation is run with the OpenIFS numerical weather model for 15 days, and the Lorenz energy cycle terms are computed for each time step of the simulation over a volume of the atmosphere, which extends from the 1000-hPa pressure surface to the 200-hPa pressure surface between 30 N and 75 N. The intensity of cyclones is evaluated with the TRACK program. In general, the simulation produces text-book type realistic cyclones whose structures resemble those of the Norwegian cyclone model. Cyclones which form upstream of the firstly developing original cyclone are smaller and less intense than the ones which form downstream of it. The most intense cyclone is the first cyclone which develops downstream of the original cyclone. None of the cyclones undergo their full life-cycle and therefore the simulation could be run for more than 15 days in the future. Over the course of the simulation, the available potential energy of the zonal mean flow decreases due to conversion to eddy available potential energy by a northward meridional heat flux. Vertical heat flux acts to inhibit this energy conversion, but its effect is minor. Eddy available potential energy is converted to eddy kinetic energy by the rising of warm air and the sinking of cold air within the developing cyclones and anticyclones. Eddy kinetic energy is converted to the kinetic energy of the zonal mean flow by momentum fluxes of the zonal wind component. The kinetic energy of the zonal mean flow is converted back to the available potential energy of the mean flow by the mean meridional overturning. In addition, friction dissipates the kinetic energy of the eddies and the zonal mean flow. Overall, the results of this thesis show that Lorenz energy cycle terms can be computed for an idealized aqua-planet simulation and that the computed terms can be used as diagnostics for evaluating the development of extra-tropical cyclones.
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