Towards the Use of Radar Winds in Numerical Weather Prediction

Numerical weather prediction (NWP) models provide the basis for weather forecasting by simulating the evolution of the atmospheric state. A good forecast requires that the initial state of the atmosphere is known accurately, and that the NWP model is a realistic representation of the atmosphere. Data assimilation methods are used to produce initial conditions for NWP models. The NWP model background field, typically a short-range forecast, is updated with observations in a statistically optimal way. The objective in this thesis has been to develope methods in order to allow data assimilation of Doppler radar radial wind observations. The work has been carried out in the High Resolution Limited Area Model (HIRLAM) 3-dimensional variational data assimilation framework. Observation modelling is a key element in exploiting indirect observations of the model variables. In the radar radial wind observation modelling, the vertical model wind profile is interpolated to the observation location, and the projection of the model wind vector on the radar pulse path is calculated. The vertical broadening of the radar pulse volume, and the bending of the radar pulse path due to atmospheric conditions are taken into account. Radar radial wind observations are modelled within observation errors which consist of instrumental, modelling, and representativeness errors. Systematic and random modelling errors can be minimized by accurate observation modelling. The impact of the random part of the instrumental and representativeness errors can be decreased by calculating spatial averages from the raw observations. Model experiments indicate that the spatial averaging clearly improves the fit of the radial wind observations to the model in terms of observation minus model background (OmB) standard deviation. Monitoring the quality of the observations is an important aspect, especially when a new observation type is introduced into a data assimilation system. Calculating the bias for radial wind observations in a conventional way can result in zero even in case there are systematic differences in the wind speed and/or direction. A bias estimation method designed for this observation type is introduced in the thesis. Doppler radar radial wind observation modelling, together with the bias estimation method, enables the exploitation of the radial wind observations also for NWP model validation. The one-month model experiments performed with the HIRLAM model versions differing only in a surface stress parameterization detail indicate that the use of radar wind observations in NWP model validation is very beneficial.

Tukien tuotannosta irrottamisen vaikutukset viljan, naudanlihan ja sianlihan tarjontaan Suomessa

This research discusses decoupling CAP (Common Agricultural Policy) support and impacts which may occur on grain cultivation area and supply of beef and pork in Finland. The study presents the definitions and studies on decoupled agricultural subsidies, the development of supply of grain, beef and pork in Finland and changes in leading factors affecting supply between 1970 and 2005. Decoupling agricultural subsidies means that the linkage between subsidies and production levels is disconnected; subsidies do not affect the amount produced. The hypothesis is that decoupling will decrease the amounts produced in agriculture substantially. In the supply research, the econometric models which represent supply of agricultural products are estimated based on the data of prices and amounts produced. With estimated supply models, the impacts of changes in prices and public policies, can be forecasted according to supply of agricultural products. In this study, three regression models describing combined cultivation areas of rye, wheat, oats and barley, and the supply of beef and pork are estimated. Grain cultivation area and supply of beef are estimated based on data from 1970 to 2005 and supply of pork on data from 1995 to 2005. The dependencies in the model are postulated to be linear. The explanatory variables in the grain model were average return per hectare, agricultural subsidies, grain cultivation area in the previous year and the cost of fertilization. The explanatory variables in the beef model were the total return from markets and subsidies and the amount of beef production in the previous year. In the pork model the explanatory variables were the total return, the price of piglet, investment subsidies, trend of increasing productivity and the dummy variable of the last quarter of the year. The R-squared of model of grain cultivation area was 0,81, the model of beef supply 0,77 and the model of pork supply 0,82. Development of grain cultivation area and supply of beef and pork was estimated for 2006 - 2013 with this regression model. In the basic scenario, development of explanatory variables in 2006 - 2013 was postulated to be the same as they used to be in average in 1995 - 2005. After the basic scenario the impacts of decoupling CAP subsidies and domestic subsidies on cultivation area and supply were simulated. According to the results of the decoupling CAP subsidies scenario, grain cultivation area decreases from 1,12 million hectares in 2005 to 1,0 million hectares in 2013 and supply of beef from 88,8 million kilos in 2005 to 67,7 million kilos in 2013. Decoupling domestic and investment subsidies will decrease the supply of pork from 194 million kilos in 2005 to 187 million kilos in 2006. By 2013 the supply of pork grows into 203 million kilos.

Observations of the solar wind-magnetosphere-ionosphere coupling

In this thesis, the solar wind-magnetosphere-ionosphere coupling is studied observationally, with the main focus on the ionospheric currents in the auroral region. The thesis consists of five research articles and an introductory part that summarises the most important results reached in the articles and places them in a wider context within the field of space physics. Ionospheric measurements are provided by the International Monitor for Auroral Geomagnetic Effects (IMAGE) magnetometer network, by the low-orbit CHAllenging Minisatellite Payload (CHAMP) satellite, by the European Incoherent SCATter (EISCAT) radar, and by the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) satellite. Magnetospheric observations, on the other hand, are acquired from the four spacecraft of the Cluster mission, and solar wind observations from the Advanced Composition Explorer (ACE) and Wind spacecraft. Within the framework of this study, a new method for determining the ionospheric currents from low-orbit satellite-based magnetic field data is developed. In contrast to previous techniques, all three current density components can be determined on a matching spatial scale, and the validity of the necessary one-dimensionality approximation, and thus, the quality of the results, can be estimated directly from the data. The new method is applied to derive an empirical model for estimating the Hall-to-Pedersen conductance ratio from ground-based magnetic field data, and to investigate the statistical dependence of the large-scale ionospheric currents on solar wind and geomagnetic parameters. Equations describing the amount of field-aligned current in the auroral region, as well as the location of the auroral electrojets, as a function of these parameters are derived. Moreover, the mesoscale (10-1000 km) ionospheric equivalent currents related to two magnetotail plasma sheet phenomena, bursty bulk flows and flux ropes, are studied. Based on the analysis of 22 events, the typical equivalent current pattern related to bursty bulk flows is established. For the flux ropes, on the other hand, only two conjugate events are found. As the equivalent current patterns during these two events are not similar, it is suggested that the ionospheric signatures of a flux rope depend on the orientation and the length of the structure, but analysis of additional events is required to determine the possible ionospheric connection of flux ropes.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Feasibility of assimilating ASCAT surface winds into a Limited Area Model

Sea-surface wind observations of previous generation scatterometers have been successfully assimilated into Numerical Weather Prediction (NWP) models. Impact studies conducted with these assimilation implementations have shown a distinct improvement to model analysis and forecast accuracies. The Advanced Scatterometer (ASCAT), flown on Metop-A, offers an improved sea-surface wind accuracy and better data coverage when compared to the previous generation scatterometers. Five individual case studies are carried out. The effect of including ASCAT data into High Resolution Limited Area Model (HIRLAM) assimilation system (4D-Var) is tested to be neutral-positive for situations with general flow direction from the Atlantic Ocean. For northerly flow regimes the effect is negative. This is later discussed to be caused by problems involving modeling northern flows, and also due to the lack of a suitable verification method. Suggestions and an example of an improved verification method is presented later on. A closer examination of a polar low evolution is also shown. It is found that the ASCAT assimilation scheme improves forecast of the initial evolution of the polar low, but the model advects the strong low pressure centre too fast eastward. Finally, the flaws of the implementation are found small and implementing the ASCAT assimilation scheme into the operational HIRLAM suite is feasible, but longer time period validation is still required.

Wind drift of snowfall between the radar volume and ground

This study evaluates how the advection of precipitation, or wind drift, between the radar volume and ground affects radar measurements of precipitation. Normally precipitation is assumed to fall vertically to the ground from the contributing volume, and thus the radar measurement represents the geographical location immediately below. In this study radar measurements are corrected using hydrometeor trajectories calculated from measured and forecasted winds, and the effect of trajectory-correction on the radar measurements is evaluated. Wind drift statistics for Finland are compiled using sounding data from two weather stations spanning two years. For each sounding, the hydrometeor phase at ground level is estimated and drift distance calculated using different originating level heights. This way the drift statistics are constructed as a function of range from radar and elevation angle. On average, wind drift of 1 km was exceeded at approximately 60 km distance, while drift of 10 km was exceeded at 100 km distance. Trajectories were calculated using model winds in order to produce a trajectory-corrected ground field from radar PPI images. It was found that at the upwind side from the radar the effective measuring area was reduced as some trajectories exited the radar volume scan. In the downwind side areas near the edge of the radar measuring area experience improved precipitation detection. The effect of trajectory-correction is most prominent in instant measurements and diminishes when accumulating over longer time periods. Furthermore, measurements of intensive and small scale precipitation patterns benefit most from wind drift correction. The contribution of wind drift on the uncertainty of estimated Ze (S) - relationship was studied by simulating the effect of different error sources to the uncertainty in the relationship coefficients a and b. The overall uncertainty was assumed to consist of systematic errors of both the radar and the gauge, as well as errors by turbulence at the gauge orifice and by wind drift of precipitation. The focus of the analysis is error associated with wind drift, which was determined by describing the spatial structure of the reflectivity field using spatial autocovariance (or variogram). This spatial structure was then used with calculated drift distances to estimate the variance in radar measurement produced by precipitation drift, relative to the other error sources. It was found that error by wind drift was of similar magnitude with error by turbulence at gauge orifice at all ranges from radar, with systematic errors of the instruments being a minor issue. The correction method presented in the study could be used in radar nowcasting products to improve the estimation of visibility and local precipitation intensities. The method however only considers pure snow, and for operational purposes some improvements are desirable, such as melting layer detection, VPR correction and taking solid state hydrometeor type into account, which would improve the estimation of vertical velocities of the hydrometeors.

Acute Lymphoblastic Leukemia in Adolescents and Young Adults in Finland

In recent reports, adolescents and young adults (AYA) with acute lymphoblastic leukemia (ALL) have had a better outcome with pediatric treatment than with adult protocols. ALL can be classified into biologic subgroups according to immunophenotype and cytogenetics, with different clinical characteristics and outcome. The proportions of the subgroups are different in children and adults. ALL subtypes in AYA patients are less well characterized. In this study, the treatment and outcome of ALL in AYA patients aged 10-25 years in Finland on pediatric and adult protocols was retrospectively analyzed. In total, 245 patients were included. The proportions of biologic subgroups in different age groups were determined. Patients with initially normal or failed karyotype were examined with oligonucleotide microarray-based comparative genomic hybridization (aCGH). Also deletions and instability of chromosome 9p were screened in ALL patients. In addition, patients with other hematologic malignancies were screened for 9p instability. aCGH data were also used to determine a gene set that classifies AYA patients at diagnosis according to their risk of relapse. Receiver operating characteristic analysis was used to assess the value of the set of genes as prognostic classifiers. The 5-year event-free survival of AYA patients treated with pediatric or adult protocols was 67% and 60% (p=0.30), respectively. White blood cell count larger than 100x109/l was associated with poor prognosis. Patients treated with pediatric protocols and assigned to an intermediate-risk group fared significantly better than those of the pediatric high-risk or adult treatment groups. Deletions of 9p were detected in 46% of AYA ALL patients. The chromosomal region 9p21.3 was always affected, and the CDKN2A gene was always deleted. In about 15% of AYA patients, the 9p21.3 deletion was smaller than 200 kb in size, and therefore, probably undetectable with conventional methods. Deletion of 9p was the most common aberration of AYA ALL patients with initially normal karyotype. Instability of 9p, defined as multiple separate areas of copy number loss or homozygous loss within a larger heterozygous area in 9p, was detected in 19% (n=27) of ALL patients. This abnormality was restricted to ALL; none of the patients with other hematologic malignancies had the aberration. The prognostic model identification procedure resulted in a model of four genes: BAK1, CDKN2B, GSTM1, and MT1F. The copy number profile combinations of these genes differentiated between AYA ALL patients at diagnosis depending on their risk of relapse. Deletions of CDKN2B and BAK1 in combination with amplification of GSTM1 and MT1F were associated with a higher probability of relapse. Unlike all previous studies, we found that the outcome of AYA patients with ALL treated using pediatric or adult therapeutic protocols was comparable. The success of adult ALL therapy emphasizes the benefit of referral of patients to academic centers and adherence to research protocols. 9p deletions and instability are common features of ALL and may act together with oncogene-activating translocations in leukemogenesis. New and more sensitive methods of molecular cytogenetics can reveal previously cryptic genetic aberrations with an important role in leukemic development and prognosis and that may be potential targets of therapy. aCGH also provides a viable approach for model design aiming at evaluation of risk of relapse in ALL.

Associations between personality traits and sleep quality and quantity in young adults

This thesis examines the associations between personality traits and sleep quantity and quality in young adults. Additionally the possible effects of birth status on these associations are examined. The data used in this thesis is part of a birth cohort study (Helsinki Study of Very Low Birth Weight Adults). The personality traits are based on the five-factor model of personality. The sleep quantity and quality are based on actigraphy assessments. Four hypothesis were made about the personality and sleep associations: (1) neuroticism is related to a lesser quality of sleep, (2) there will be more significant associations between personality traits and sleep quality than between personality traits and sleep quantity, (3) the Very Low Birth Weight (VLBW) as well as, (4) the Small for Gestational Age (SGA) status will affect the associations. Linear regressions were used to study the associations between personality traits and sleep quality and quantity. Whenever an association was significant, it was tested whether this association was moderated first, by the VLBW and second, by the SGA status of the participant. The results were mostly in line with previous research especially demonstrating the negative association between neuroticism and the quality of sleep and suggesting that vulnerability to stress decreases sleep quality. Also it was found that agreeableness and conscientiousness were associated with better sleep quality and extraversion was associated with lower sleep quantity. In addition SGA status moderated the personality and sleep associations. It is proposed that there are two factors behind the interaction. First, prenatally developing mechanisms have an effect on the development of sleep as well as personality. Second, differences in the postnatal environment, for instance the parenting practices, can account for this finding. Future research could focus especially on what kind of prenatal disturbances SGA infants have in the development of mechanisms related to sleep and personality. Also focusing on the differences in parental interaction might shed more light on the results.

A Model for Creating Strategic Alliances. A Study of Inter-firm Cooperation in the North European ICT Sector

In this study, it is argued that the view on alliance creation presented in the current academic literature is limited, and that using a learning approach helps to explain the dynamic nature of alliance creation. The cases in this study suggest that a wealth of inefficiency elements can be found in alliance creation. These elements can further be divided into categories, which help explain the dynamics of alliance creation. The categories –combined with two models brought forward by the study– suggest that inefficiency can be avoided through learning during the creation process. Some elements are especially central to this argumentation. First, the elements related to the clarity and acceptance of the strategy of the company, the potential lack of an alliance strategy and the elements related to changes in the strategic context. Second, the elements related to the length of the alliance creation processes and the problems a long process entails. It is further suggested that the different inefficiency elements may create a situation, where the alliance creation process is –sequentially and successfully– followed to the end, but where the different inefficiencies create a situation where the results are not aligned with the strategic intent. The proposed solution is to monitor and assess the risk for inefficiency elements during the alliance creation process. The learning, which occurs during the alliance creation process as a result of the monitoring, can then lead to realignments in the process. This study proposes a model to mitigate the risk related to the inefficiencies. The model emphasizes creating an understanding of the other alliance partner’s business, creating a shared vision, using pilot cooperation and building trust within the process. An analytical approach to assessing the benefits of trust is also central in this view. The alliance creation approach suggested by this study, which emphasizes trust and pilot cooperation, is further critically reviewed against contracting as a way to create alliances.

On ion escape from Venus

This doctoral thesis is about the solar wind influence on the atmosphere of the planet Venus. A numerical plasma simulation model was developed for the interaction between Venus and the solar wind to study the erosion of charged particles from the Venus upper atmosphere. The developed model is a hybrid simulation where ions are treated as particles and electrons are modelled as a fluid. The simulation was used to study the solar wind induced ion escape from Venus as observed by the European Space Agency's Venus Express and NASA's Pioneer Venus Orbiter spacecraft. Especially, observations made by the ASPERA-4 particle instrument onboard Venus Express were studied. The thesis consists of an introductory part and four peer-reviewed articles published in scientific journals. In the introduction Venus is presented as one of the terrestrial planets in the Solar System and the main findings of the work are discussed within the wider context of planetary physics. Venus is the closest neighbouring planet to the Earth and the most earthlike planet in its size and mass orbiting the Sun. Whereas the atmosphere of the Earth consists mainly of nitrogen and oxygen, Venus has a hot carbon dioxide atmosphere, which is dominated by the greenhouse effect. Venus has all of its water in the atmosphere, which is only a fraction of the Earth's total water supply. Since planets developed presumably in similar conditions in the young Solar System, why Venus and Earth became so different in many respects? One important feature of Venus is that the planet does not have an intrinsic magnetic field. This makes it possible for the solar wind, a continuous stream of charged particles from the Sun, to flow close to Venus and to pick up ions from the planet's upper atmosphere. The strong intrinsic magnetic field of the Earth dominates the terrestrial magnetosphere and deflects the solar wind flow far away from the atmosphere. The region around Venus where the planet's atmosphere interacts with the solar wind is called the plasma environment or the induced magnetosphere. Main findings of the work include new knowledge about the movement of escaping planetary ions in the Venusian induced magnetosphere. Further, the developed simulation model was used to study how the solar wind conditions affect the ion escape from Venus. Especially, the global three-dimensional structure of the Venusian particle and magnetic environment was studied. The results help to interpret spacecraft observations around the planet. Finally, several remaining questions were identified, which could potentially improve our knowledge of the Venus ion escape and guide the future development of planetary plasma simulations.