Ilmatieteen laitos

Recent Submissions

  • Kontu, Anna (Finnish Meteorological Institute, 2018)
    Finnish Meteorological Insitute Contributions 144
    Remote sensing using microwave radiometry is an acknowledged method for monitoring various environmental processes in the cryosphere, atmosphere, soil, vegetation and oceans. Several decades long time series of spaceborne passive microwave observations can be used to detect trends relating to climate change, while present measurements provide information on the current state of the environment. Unlike optical wavelengths, microwaves are mostly insensitive to atmospheric and lighting conditions and are therefore suitable for monitoring seasonal snow in the Arctic. One of the major challenges in the utilization of spaceborne passive microwave observations for snow measurements is the poor spatial resolution of instruments. The interpretation of measurements over heterogeneous areas requires sophisticated microwave emission models relating the measured parameters to physical properties of snow, vegetation and the subnivean layer. Especially the high contrast in the electrical properties of soil and liquid water introduces inaccuracies in the retrieved parameters close to coastlines, lakes and wetlands, if the subnivean water bodies are not accounted for in the algorithm. The first focus point of this thesis is the modelling of brightness temperature of ice- and snow-covered water bodies and their differences from snow-covered forested and open land areas. Methods for modelling the microwave signatures of water bodies and for using that information in the retrieval of snow parameters from passive microwave measurements are presented in this thesis. The second focus point is the effect of snow microstructure on its microwave signature. Even small changes in the size of scattering particles, snow grains, modify the measured brightness temperature notably. The coupling of different modelled and measured snow microstructural parameters with a microwave snow emission model and the application of those parameters in the retrieval of snow parameters from remote sensing data are studied.
  • Gregow, Erik (2018)
    Finnish Meteorological Institute Contributions 142
    Observations have been and are an important part of today's meteorological developments. Surface observations are very useful as they are, providing weather information for a point location. ough they do not give much information, if any, on what happens between the stations across a larger area. With models one can create an analysis of the meteorological situation, i.e. calculate and estimate what happens between these fixed observation points. Remote-sensing data, such as radar and satellite, are being processed and the output is given over a domain as an analysed product of their measurements. For example, radar gives a plot of where the rain is located, i.e. an analysis of the current precipitation. With a series of radar images, a human (subjectively) or a computer objectively) can process this information to estimate where the rain will move and be located within the next few minutes (even hours), i.e. a short forecast also called "nowcast". is applies to some extent also for other observations, such as satellite data (cloud propagation). But for most quantities (such as temperature, wind, etc) it is significantly harder to make such a nowcast, since these are influenced by many other factors and there is no linear development of them. Therefore, there are forecast models that solve physical and dynamic equations, so that one can estimate the future weather for the coming hours and days. A prerequisite for generating a forecast of high quality is to capture the initial weather conditions as best as possible. This is done using observations and they are introduced into the forecast model through different techniques, where the model creates its own analysis as the initial step. There remain problems since forecast models often are affected by physical disagreements, as the dynamic conditions are not in balance. This results in the model having a spin-up effect, where the meteorological quantities are not yet in balance with each other and the resulting weather conditions are not always reliable during the first hours. Hence, a lot of research is spent on how to reduce this spin-up effect and on the use of nowcast models, in order to deliver the best model results for the first few hours of the forecast period. In this dissertation, the research work has been to improve the meteorological analysis, algorithms and functionality, using the Local Analysis and Prediction System (LAPS) model. Different kinds of observations were used and their interdependencies have been studied, in order to combine and merge information from variousinstruments. Primarily focus has been to improve the estimation of precipitation accumulation and meteorological quantities that affect wind energy. The LAPS developments have been used for several end-users and nowcasting applications, and experimentally as initial conditions for forecast modelling. The studies have been concentrated on Finland and nearby sea areas, with the available datasets for this domain. By combining surface-station measurements, radar and lightning information, one can improve the precipitation-amount estimations. The use of lightning data further improves the estimates and gives the advantage of having additional data outside radar coverage, which can potentially be very useful for example over sea areas. In addition, the improved LAPS analyses (cloud-related quantities) and a newly developed model (LOWICE), calculating the electricity production during wintertime (taking into account the icing of wind turbine rotor blades which reduces efficiency), have shown good results.
  • Mäkelä, Antti; Laurila, Terhi K.; Haapalainen, Jussi; Halabi, Tuomas (Finnish Meteorological Institute, 2017)
    Raportteja - Rapporter - Reports 2017:8
    Ilmatieteen laitos on koonnut ja julkaissut salamanlaskijoiden havainnot vuosilta 1960–1997. Vuodesta 1998 lähtien kaikki järjestelmälliset maasalamahavainnot perustuvat salamanpaikantimeen, jonka nykyinen malli aloitti toimintansa elokuussa 1997. Se käsitti 2016 kahdeksan anturia, pohjoisin Lokassa. Vuodesta 2002 mukana ovat olleet lisäksi Norjan ja Ruotsin anturit, joiden ansiosta koko Lappi on katettu ja suorituskyky on parantunut myös muualla Suomessa, sekä yksi anturi Virossa (mukaan vuonna 2005) ja kolme anturia Liettuassa (mukaan 2014). Laitteisto paikantaa maasalamoista erikseen jokaisen osaiskun ja ryhmittelee ne kokonaisiksi salamoiksi. Paikannettu salama voi sisältää 1-15 iskua; keskiarvo Suomessa on vajaa kaksi iskua/salama. Tilastoinnin pohjana käytetään salama- eikä iskumääriä, koska salama on ilmastollisesti edustavampi suure. Kesän 2016 aikana paikannettiin Suomen noin 115 000 maasalamaa, joka on hieman alle keskimääräisen (138 000). Suurin osa salamoista esiintyi heinäkuussa (80 000), ja touko-, kesä- ja elokuussa määrät olivat noin puolet keskimääräisestä.
  • von Lerber, Annakaisa (Finnish Meteorological Institute, 2018)
    Finnish Meteorological Institute Contributions 143
    Globally, snow influences Earth and its ecosystems in several ways by having a significant impact on, e.g., climate and weather, Earth radiation balance, hydrology, and societal infrastructures. In mountainous regions and at high latitudes snowfall is vital in providing freshwater resources by accumulating water within the snowpack and releasing the water during the warm summer season. Snowfall also has an impact on transportation services, both in aviation and road maintenance. Remote sensing instrumentation, such as radars and radiometers, provide the needed temporal and spatial coverage for monitoring precipitation globally and on regional scales. In microwave remote sensing, the quantitative precipitation estimation is based on the assumed relations between the electromagnetic and physical properties of hydrometeors. To determine these relations for solid winter precipitation is challenging. Snow particles have an irregular structure, and their properties evolve continuously due to microphysical processes that take place aloft. Hence also the scattering properties, which are dependent on the size, shape, and dielectric permittivity of the hydrometeors, are changing. In this thesis, the microphysical properties of snowfall are studied with ground-based measurements, and the changes in prevailing snow particle characteristics are linked to remote sensing observations. Detailed ground observations from heavily rimed snow particles to openstructured low-density snowflakes are shown to be connected to collocated triple-frequency signatures. As a part of this work, two methods are implemented to retrieve mass estimates for an ensemble of snow particles combining observations of a video-disdrometer and a precipitation gauge. The changes in the retrieved mass-dimensional relations are shown to correspond to microphysical growth processes. The dependence of the C-band weather radar observations on the microphysical properties of snow is investigated and parametrized. The results apply to improve the accuracy of the radar-based snowfall estimation, and the developed methodology also provides uncertainties of the estimates. Furthermore, the created data set is utilized to validate space-borne snowfall measurements. This work demonstrates that the C-band weather radar signal propagating through a low melting layer can significantly be attenuated by the melting snow particles. The expected modeled attenuation is parametrized according to microphysical properties of snow at the top of the melting layer.
  • Salmi, Jatta; Laukkanen, Emmi; Latikka, Jenni (Finnish Meteorological Institute, 2017)
    Raportteja - Rapporter - Reports 2017:7
    Tämän työn tavoitteena oli määrittää yksinkertainen menetelmä, jolla voidaan mitoittaa pienille energiantuotantoyksiköille ilmanlaadun kannalta riittävä piipunkorkeus. Työssä arvioitiin päästöjen leviämismallilaskelmien avulla polttoaineteholtaan 1–5 MW kokoisten uusien energiantuotantoyksiköiden ilmanlaatuvaikutuksia ja selvitettiin niille sopivaa piipunkorkeutta. Leviämismallitarkastelut tehtiin erikseen seitsemän eri polttoaineen rikkidioksidi-, typenoksidi- ja hiukkaspäästöille. Polttoaineet olivat turve, puupelletit, kokopuuhake, bioöljy, raskas polttoöljy, kevyt polttoöljy ja maakaasu. Raskaasta polttoöljystä tarkasteltiin erikseen öljyä, joka sisältää 0,1 paino-% rikkiä ja öljyä, joka sisältää 0,2 paino-% rikkiä. Laskelmissa tarkasteltiin erikseen polttoaineteholtaan 1, 3 ja 5 MW kokoisten energiantuotantoyksiköiden päästöjen aiheuttamia ulkoilman pitoisuuksia laitosten ympäristössä. Laskelmissa käytettiin lähtötietoja, jotka parhaiten kuvaavat keskimääräisiä olosuhteita tyypillisissä tämän kokoisissa energiantuotantoyksiköissä. Päästöjen leviämislaskelmat tehtiin Ilmatieteen laitoksella kehitetyllä leviämismallilla UDM-FMI. Tarkastelujen avulla muodostettiin polttoainekohtaiset mitoituskäyrät polttoaineteholtaan 1–5 MW:n uusien energiantuotantoyksiköiden piipunkorkeuksille tasaisessa maastossa. Lisäksi tarkasteltiin erikseen läheisen maastoesteen tai lähirakennuksen vaikutusta syntyviin pitoisuuksiin ja määritettiin esteen vaikutuksesta piipunkorkeuteen tarvittava lisäkorkeus.
  • Nuottokari, Jaakko (Finnish Meteorological Institute, 2017)
    Finnish Meteorological Institute Contributions 137,
    Meteorological information and services supporting the various operations of air transport enable a safe, efficient and cost-effective operating environment for airspace users, air navigation service providers and air traffic management. The continuing pursuit towards an improved quality of observation, forecasting and decision support services is driven by an increasingly weather-sensitive society and growing impacts of hazardous weather events. This thesis provides an overview of the field of aeronautical meteorological research by introducing the organisations involved, global and regional strategies, impacts of weather on air transport, current state of the art in meteorological research and decision support systems serving air transport needs with a view of where the field should evolve next. This thesis is an attempt to highlight key findings and point the reader towards the direction of further research on the given topics. Research supporting air transport operations with the optimal use of weather information is a specialized field where advances are led by the needs of various airspace users. Research institutions for example in the United States have contributed greatly due to the severe weather impacts experienced by the National Airspace System (NAS), the ability of the Federal Aviation Aministration (FAA) and the National Oceanic and Atmospheric Administration (NOAA) to direct long-term funding to solve specific aviation-related research questions. The creation and maintenance of long-lived teams of scientists and engineers working together to produce end-toend solutions that meet the needs of the aviation industry is the key to improving meteorological information to aviation users while university research is typically shorter duration and typical does not result in operational systems. From a global perspective, research is yet to be organised in a way that would contribute to solving aviation issues beyond single research projects and/or programmes. There is a lot more the scientific community could do to develop tailored information to decision support systems used by the aviation sector, but it would require systematic investments and the establishment of research groups focusing on the applied science questions and technology transfer. This thesis provides an overview of recommended decision support system development topics with an outline of potential milestones.
  • Tsuruta, Aki (Finnish Meteorological Institute, 2017)
    Finnish Meteorological Institute Contributions 141
    Ensemble Kalman filter (EnKF) is a useful Bayesian inverse modelling method to make inference of the states of interest from observations, especially in non-linear systems with a large number of states to be estimated. This thesis presents an application of EnKF in estimation of global and regional methane budgets, where methane fluxes are inferred from atmospheric methane concentration observations. The modelling system here requires a highly non-linear atmospheric transport model to convert the state space on to the observation space, and an optimization in both spatial and temporal dimensions is desired. Methane is an important greenhouse gas, strongly influenced by anthropogenic activities, whose atmospheric concentration increased more than twice since pre-industrial times. Although its source and sink processes have been studied extensively, the mechanisms behind the increase in the 21st century atmospheric methane concentrations are still not fully understood. In this thesis, contributions of anthropogenic and natural sources to the increase in the atmospheric methane concentrations are studied by estimating the global and regional methane fluxes from anthropogenic and biospheric sources for the 21st century using an EnKF based data assimilation system (CarbonTracker Europe-CH4; CTE-CH4). The model was evaluated using assimilated in situ atmospheric concentration observations and various non-assimilated observations, and the model sensitivity to several setups and inputs was examined to assess the consistency of the model estimates. The key findings of this thesis include: 1) large enough ensemble size, appropriate prior error covariance, and good observation coverage are important to obtain consistent and reliable estimates, 2) CTE-CH4 was able to identify the locations and sources of the emissions that possibly contribute significantly to the increase in the atmospheric concentrations after 2007 (the Tropical and extra Tropical anthropogenic emissions), 3) Europe was found to have an insignificant or negative influence on the increase in the atmospheric CH4 concentrations in the 21st century, 4) CTE-CH4 was able to produce flux estimates that are generally consistent with various observations, but 5) the estimated fluxes are still sensitive to the number of parameters, atmospheric transport and spatial distribution of the prior fluxes.
  • Svensson, Jonas (Finnish Meteorological Institute, 2017)
    Finnish Meteorological Institute Contributions 140
    Snow and ice are essential components of the Earth system, modulating the energy budget by reflecting sunlight back into the atmosphere, and through its importance in the hydrological cycle by being a reservoir for fresh water. Light-absorbing impurities (LAI), such as black carbon (BC) and mineral dust (MD), have a unique role in influencing the reflectance of the cryosphere. Deposition of the anthropogenic and natural LAI constituents onto these bright surfaces initiates powerful albedo feedbacks that will accelerate melt. This is important globally, but especially for regions such as the Arctic and the Himalaya. In this thesis, observations from both ambient and laboratory experiments are presented. The overarching research goal has been to better understand the climatic effect of LAI on snow. More specifically, an emphasis has been placed on exploring the process-level interactions between LAI and snow, which will enable better comprehension of LAI affecting the cryosphere. Key findings in this thesis involves the investigations on the horizontal variability of BC concentrations in the surface snow that indicate a larger variability on the order of meter scale at a pristine Arctic site compared to a polluted site nearby a major urban area. In outdoor experiments, where LAI were used to artificially dope natural snow surfaces, the snow albedo was observed to decrease following LAI deposition. The albedo decrease was on the same order as in situ measurements of LAI and albedo conducted elsewhere. As snow melted during the experiment, the snow density was observed to decrease with increasing LAI concentration, while this effect was not observed in non-melting snow. The water retention capacity in melting snow is likely to be decreased by the presence of LAI. Measurements examining the absorption of BC indicate that BC particles in the snow have less absorbing potential compared to BC particles generated in the laboratory. The LAI content of snow pit investigations from two glaciers in the Sunderdhunga valley, northern India, an area not previously examined for LAI, presented high BC and MD content, affecting the radiative balance of the glacier snow. At different points, MD may be greater than BC in absorbing light at the snow surface. A continued monitoring of LAI in the cryosphere, both on the detailed scale explored here, as well as on the larger modelling perspective is needed in order to understand the overall response of the cryosphere to climate change.
  • Päivärinta, Sanna-mari (Finnish Meteorological Institute, 2017)
    Finnish Meteorological Institute Contributions 136
    Odd nitrogen (NOx = N + NO + NO2) in the polar regions is mainly produced in the upper atmosphere through ionization processes by solar extreme ultraviolet radiation, soft X-rays and high energy particles originating from the space. During periods of high geomagnetic activity, normally close to the solar maximum, energetic particle precipitation (EPP) provides an in-situ source of NOx also in the middle atmosphere. Understanding the behaviour of NOx in the middle atmosphere is of great importance due to its capability to act as a catalyst in chemical reaction cycles destroying ozone in the stratosphere. This work considers EPP in the form of solar proton events (SPEs). Atmospheric dynamics play an important role in determining the distributions of long-lived trace gases in the middle atmosphere. The main loss mechanism for NOx is photolysis at the upper stratospheric and mesospheric altitudes, leading to long photochemical lifetime of NOx during the dark polar winter. NOx in the middle atmosphere, also if produced in-situ due to SPEs, is therefore affected by atmospheric dynamics, and transported from the mesosphere-lower hermosphere (MLT) region down to the middle atmosphere. This descent phenomenon can be intensified in the aftermath of sudden stratospheric warmings (SSWs), which are dynamical phenomena able to affect a wide range of altitudes in the Northern polar region atmosphere. The enhanced downward transport of NOx can thus strengthen the NOx-ozone connection in the stratosphere. In this work we used both space born observations from several satellite instruments and a chemistry transport model in the examination of the SSW and SPE caused effects in the stratosphere and mesosphere. The scientific objectives of this work were to find out the individual and combined effects of SSWs and SPEs on the NOx and ozone balance in the Northern middle atmosphere, and assess the relative contributions of dynamics (SSWs) and in-situ production of NOx (SPEs) on ozone in the stratosphere. The results showed dramatic increases in NOx in the middle atmosphere, even by a factor of 50, following both periods of enhanced NOx descent in connection with SSWs and in-situ production of NOx due to SPEs. A clear long-term (order of months) decrease in stratospheric ozone (10-90 %), coinciding with the enhanced amounts of NOx, was evident and affected mostly by dynamics in the upper stratosphere. The results of this work emphasize the importance of in-situ production of NOx (SPEs) on the ozone balance in the upper stratosphere, but also the key role of dynamics (SSWs) in transporting the SPE effect to even lower altitudes and its capability to strengthen the effect.
  • Komppula, Birgitta; Waldén, Jari; Lusa, Kaisa; Kyllönen, Katriina; Saari, Helena; Vestenius, Mika; Salmi, Jatta; Latikka, Jenni (Finnish Meteorological Institute, 2017)
    Raportteja - Rapporter - Reports 2017:6
    Suomen ilmanlaadun seurantaa säätelevät suurelta osin EU:n ilmanlaatua koskevat direktiivit. Ilman epäpuhtauksien pitoisuuksia säädellään sitovien raja-arvojen ja tavoitearvojen avulla. Myös kansalliset ohjearvot ovat edelleen voimassa ja niitä käytetään suunnittelun tukena, mutta niiden merkitys on vähenemässä. Raja-arvoja valvoviksi asemiksi kutsutaan niitä ilmanlaadun mittausasemia, jotka täyttävät ilmanlaatudirektiivien kriteerit ja joiden pitoisuustiedot toimitetaan EU:lle. Rajaarvopitoisuuksia valvovien mittausasemien lisäksi ilmanlaatua seurataan mittausverkoissa laajalti erilaisista paikallisista tarpeista, mikä on ollut aikanaan lähtökohta useimpien ilmanlaatumittausten aloittamiselle. Ilmanlaatua seurataan ensisijaisesti hyvän ilmanlaadun turvaamiseksi paikallisille asukkaille ja ympäristölle. Ilmanlaatua mitataan lisäksi muun muassa yksittäisten päästölähteiden vaikutusten arvioimiseksi, asukkaiden valitusten vuoksi, ympäristölupaehtojen täyttämiseksi sekä jatkuvan ilmanlaadun seurannan tarvetta arvioitaessa. Tämä ohje koskee ilmanlaadun mittaamista osana ilmanlaadun seurantaa. Ohjeessa käsitellään ilmanlaatulainsäädäntöä, mittaustarpeen arviointia, mittausten suunnittelua, tekemistä ja laadunvarmennustoimenpiteitä, laatujärjestelmän sisältöä, raportointia sekä tiedottamista. Ohjeen tarkoituksena on kehittää mittausten laatua, luotettavuutta, edustavuutta ja vertailtavuutta sekä luoda edellytyksiä ilmanlaadun mittaustulosten monipuoliselle hyödyntämiselle. Ilmatieteen laitos päivitti ilmanlaadun mittausohjetta edellisen kerran vuonna 2004 ja nyt mittausohjetta on edelleen laajennettu ja päivitetty ajan tasalle.
  • Salminen, Miia (Finnish Meteorological Institute, 2017)
    Finnish Meteorological Institute Contributions 139
    Monitoring of snow cover in northern hemisphere is highly important for climate research and for operational activities, such as those related to hydrology and weather forecasting. The appearance and melting of seasonal snow cover dominate the hydrological and climatic patterns in the boreal and arctic regions. Spatial variability (in particular during the spring and autumn transition months) and long-term trends in global snow cover distribution are strongly interconnected to changes in Earth System (ES). Satellite data based estimates on snow cover extent are utilized e.g. in near-real-time hydrological forecasting, water resource management and to construct long-term Climate Data Records (CDRs) essential for climate research. Information on the quantitative reliability of snow cover monitoring is urgently needed by these different applications as the usefulness of satellite data based results is strongly dependent on the quality of the interpretation. This doctoral dissertation investigates the factors affecting the reliability of snow cover monitoring using optical satellite data and focuses on boreal regions (zone characterized by seasonal snow cover). Based on the analysis of different factors relevant to snow mapping performance, the work introduces a methodology to assess the uncertainty of snow cover extent estimates, focusing on the retrieval of fractional snow cover (within a pixel) during the spring melt period. The results demonstrate that optical remote sensing is well suited for determining snow extent in the melting season and that the characterizing the uncertainty in snow estimates facilitates the improvement of the snow mapping algorithms. The overall message is that using a versatile accuracy analysis it is possible to develop uncertainty estimates for the optical remote sensing of snow cover, which is a considerable advance in remote sensing. The results of this work can also be utilized in the development of other interpretation algorithms. This thesis consists of five articles predominantly dealing with quantitative data analysis, while the summary chapter synthesizes the results mainly in the algorithm accuracy point of view. The first four articles determine the reflectance characteristics essential for the forward and inverse modeling of boreal landscapes (forward model describes the observations as a function of the investigated variable). The effects of snow, snow-free ground and boreal forest canopy on the observed satellite scene reflectance are specified. The effects of all the error components are clarified in the fifth article and a novel experimental method to analyze and quantify the amount of uncertainty is presented. The five articles employ different remote sensing and ground truth data sets measured and/or analyzed for this research, covering the region of Finland and also applied to boreal forest region in northern Europe.
  • Oikkonen, Annu (Finnish Meteorological Institute, 2017)
    Finnish Meteorological Institute Contributions 138
    The state of the sea ice cover results from an interplay between thermodynamics and dynamics. Changes in the ice cover further affect the way in which the ice responds to forcing, both thermodynamic and dynamic. This thesis discusses several aspects of sea ice thermodynamics and dynamics, and their contribution to the evolution of ice pack, and particularly to changes in the Arctic sea ice cover. The main focus is on the ice dynamics in different types of ice zones and under different conditions, which also enables the examination of the impact of thermodynamic forcing on sea ice dynamics. Changes in the Arctic sea ice thickness distribution during the period 1975-2000 are studied in detail, and the contribution of thermodynamics and dynamics as driving forcing is discussed. The results show that the shape of the sea ice thickness distribution has changed: the peak of the distribution has generally narrowed and shifted towards thinner ice. A prevalent feature is the loss of thick, mostly deformed ice, which has had a significant role in the decrease in the mean and modal ice thickness. The results also show a decrease in the seasonal variability of the mean ice thickness, but with strong regional differences. Also, the regional variability of the sea ice thickness has decreased, since the thinning has been the most pronounced in regions which formerly had the thickest ice cover. The observed changes in the regional ice draft distributions cannot be explained by local warming of the atmosphere, but changes in the ice drift patterns have had an essential impact. These results emphasize the importance of the description of sea ice dynamics in the models. Sea ice dynamics, and especially deformation, strongly affect the evolution of ice volume and properties of ice cover. There has still been a need for better understanding of the highly local and intermittent deformation process, as well as its variability that rises from different types of conditions and regions. Several aspects of these questions are covered in this thesis. With coastal and ship radar images, the study of the length scale dependency of sea ice deformation rate is extended to smaller length scales (from 100 m to 10 km) and time scales (from 10 min to 24 h) than were previously possible. Sea ice deformation rate is shown to exhibit a power law with respect to both length scale and time scale at all the scales covered. Both the overall deformation rate and the length scale dependency of deformation rate are found to depend strongly on the time scale considered. Small scale deformation is studied in different type of ice regions (coastal boundary zone, compact Arctic ice pack and marginal ice zone), and under different weather conditions. One of the key findings is the connection between air temperature and deformation rate: during warm days deformation rates are generally higher than during cold days. The deformation rate is found to respond to changes in air temperature in a time scale of days, which is clearly faster than previously assumed. This response is most likely connected to the effectiveness of the healing process. However, despite of the most effective healing during the coldest winter, the previously damaged areas are found to remain the weak points in the ice cover. This confirms that the deformation history is an important factor in determining how the ice cover responds to dynamic forcing.
  • Huttunen, Jani (Finnish Meteorological Institute, 2017)
    Finnish Meteorological Institute Contributions 135
    Aerosols affect the climate both directly and indirectly. The direct effect comes from their influence on the radiation balance by scattering and absorption of solar radiation, while the indirect effect is based on the ways in which aerosols interact via clouds. Currently the total anthropogenic aerosol forcing includes one of the main uncertainties in the assessment of human induced climate change. The aerosol direct radiative effect (ADRE) can be simulated with either the radiative transfer modelling or estimated with solar radiation and aerosol amount measurements. Both approaches include significant uncertainties and this thesis focuses on the uncertainties on the measurement based estimation of ADRE and the uncertainties therein. The main scientific objectives of this thesis are to seek answers to the following four questions: 1) are the machine learning algorithms better than the a traditional lookup table (LUT) approach in estimating aerosol load (aerosol optical depth, AOD)?; 2) what is the role of water vapor (WVC) variability in the measurementbased regression method used to estimate the surface ADRE?; 3) how well do the radiative transfer codes, typically used in global aerosol models, agree?; 4) what is the impact of typically neglected diurnal aerosol variability in ADRE estimation? The results show that: 1) the machine learning algorithms are able to provide AOD more accurately than the LUT approach for conditions of varying aerosol optical properties, since in the LUT approach the aerosol model (e.g. single scattering albedo, asymmetry factor) needs to be fixed in advance. 2) It was found that covariability of AOD and WVC can have an influence in ADRE estimates, when using groundbased measurements of surface solar radiation and AOD. This has not been taken into account previously, but needs to be considered when these methods are applied. 3) The model intercomparison study, in which the models estimated the radiative fluxes for the same atmospheric states, revealed that there is relatively large diversity between models regarding the results from their radiative transfer modelling. 4) The main conclusion from the study focusing on the impact of systematic diurnal AOD cycles in aerosol direct radiative effect, was that even a notable diurnal change in AOD does not typically affect the 24h-average ADRE significantly.
  • Hippi, Marjo; Hartonen, Sari; Hirvonen, Mikko (Finnish Meteorological Institute, 2017)
    Raportteja - Rapporter- Reports 3:2017
    Työmatkatapaturmia tapahtuu kävellen talvisin huomattavasti enemmän kuin kesäisin, ja yksittäiset liukkaimmat päivät näkyvät selvinä piikkeinä kuvaajissa, joissa on esitetty päivittäiset liukastumisten kokonaismäärät. Liukastumisonnettomuudet aiheuttavat vuosittain merkittävät taloudelliset kustannukset sairaanhoidon ja sairauspoissaolojen takia. Projektin tavoitteena oli vähentää talvisin ulkona tapahtuvia liukastumisonnettomuuksia informoimalla työnsä puolesta ulkona liikkuvia tulevasta liukkaasta kelistä, jolloin he voisivat varautua liukkauteen esimerkiksi pitävillä kengillä, liukuesteillä tai varaamalla enemmän aikaa matkaan. Kun kerrotaan liukastumistapaturmista ja niiden ehkäisystä, se saa työyhteisön toivottavasti suhtautumaan liukastumistapaturmien riskeihin entistä vakavammin. Projektissa olivat mukana Ilmatieteen laitos, Työterveyslaitos (TTL) ja Posti (entiseltä nimeltään Itella). Vaisalalta ostettiin kaksi DSC111-mittaria projektin käyttöön ja niillä tutkittiin, kuinka hyvin laite määrittää kevyenliikenteen väylien liukkautta. Ilmatieteen laitos kehitti kelivaroitusmallia ja liukastumisvaroituksia loppukäyttäjille. Työterveyslaitos teki liukkaustutkimuksia kehittämällään liukkausmittarilla. Postin työntekijöitä toimi liukkausvaroituspalvelun testikäyttäjinä, ja he tekivät myös omia havaintoja liukkaista paikoista ja päivistä. Projekti kesti vuodesta 2013 vuoteen 2016 kattaen kolme täyttä talvijaksoa. Tavoitteena oli päästä testaamaan Ilmatieteen laitoksen kelivaroitusmallia ja varoituspalvelua useamman talvikauden aikana erilaisten talvikelien vallitessa.
  • Hoilijoki, Sanni (Finnish Meteorological Institute, 2017)
    Finnish Meteorological Institute Contributions 132
    This thesis investigates interactions between solar wind and the magnetosphere of the Earth using two global magnetosphericsimulation models, GUMICS-4 and Vlasiator, which are both developed in Finland. The main topic of the thesis is magnetic reconnection at the dayside magnetopause, its drivers and global effects. Magnetosheath mirror mode waves and their evolution, identification and impacts on the local reconnection rates at the magnetopause are also discussed. This thesis consists of four peer-reviewed papers and an introductory part. GUMICS-4 is a magnetohydrodynamic model solving plasma as a single magnetized fluid. Vlasiator is the world’s first global magnetospheric hybrid-Vlasov simulation model, which solves the motion of ions by describing them as velocity distribution functions, whereas electrons are described as a charge neutralizing fluid. Vlasiator is able to solve ion scale physics in a global scale simulation. However, it is computationally heavy and the global simulations are currently describing Earth’s magnetosphere only in two spatial dimensions, whereas the velocity space is three dimensional. This thesis shows that magnetic reconnection at the dayside magnetopause is controlled by several factors. The impact of dipole tilt angle and sunward component of the interplanetary magnetic field on magnetopause reconnection is investigated with a set of GUMICS-4 simulations. Using Vlasiator simulations, this thesis shows that local reconnection rate is highly variable even during steady solar wind and correlates well with an analytical model for 2D asymmetric reconnection. It is also shown that the local reconnection rate is affected by local variations in the magnetosheath plasma. Fluctuations in the magnetosheath parameters near X-lines are partly generated by mirror mode waves that are observed to grow in the quasi-perpendicular magnetosheath. These results show that that the local reconnection rate at the X-lines is affected not only by the fluctuations in the inflow parameters but also by reconnection at nearby X-lines. Outflow from stronger X-lines pushes against the weaker ones and might ultimately suppress reconnection in the weaker X-lines. Magnetic islands, 2D representations of FTEs, form between X-lines in the Vlasiator simulations. FTEs propagate along the dayside magnetopause driving bow waves in the magnetosheath. The bow waves propagate upstream all the way to the bow shock causing bulges in the shock, from which solar wind particles can reflect back to the solar wind causing local foreshocks. The overall conclusion of this thesis is that the ion scale kinetic physics is important to accurately model the solar wind – magnetosheath – magnetopause interactions. Vlasiator results show a strong scale-coupling between ion and global scales: global scale phenomena have an impact on the local physics and the local phenomena may have unexpected impacts on the global dynamics of the magnetosphere. Neglecting the global scales in local ion scale simulations and vice versa may therefore lead to incomplete description of the solar wind – magnetosphere interactions.