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.

Multiangular Spectrometry and Optical Properties of Debris Covered Surfaces

Due to the recent development in CCD technology aerial photography is now slowly changing from film to digital cameras. This new aspect in remote sensing allows and requires also new automated analysis methods. Basic research on reflectance properties of natural targets is needed so that computerized processes could be fully utilized. For this reason an instrument was developed at Finnish Geodetic Institute for measurement of multiangular reflectance of small remote sensing targets e.g. forest understorey or asphalt. Finnish Geodetic Institute Field Goniospectrometer (FiGIFiGo) is a portable device that is operated by 1 or 2 persons. It can be reassembled to a new location in 15 minutes and after that a target's multiangular reflectance can be measured in 10 - 30 minutes (with one illumination angle). FiGIFiGo has effective spectral range approximately from 400 nm to 2000 nm. The measurements can be made either outside with sunlight or in laboratory with 1000 W QTH light source. In this thesis FiGIFiGo is introduced and the theoretical basis of such reflectance measurements are discussed. A new method is introduced for extraction of subcomponent proportions from reflectance of a mixture sample, e.g. for retrieving proportion of lingonberry's reflectance in observation of lingonberry-lichen sample. This method was tested by conducting a series of measurements on reflectance properties of artificial samples. The component separation method yielded sound results and brought up interesting aspects in targets' reflectances. The method and the results still need to be verified with further studies, but the preliminary results imply that this method could be a valuable tool in analysis of such mixture samples.

Molecular Modelling of Estrogen-Producing Enzymes CYP450 Aromatase and 17beta-Hydroxysteroid Dehydrogenase Type 1

Breast cancer is the most common cancer in women in the western countries. Approximately two-thirds of breast cancer tumours are hormone dependent, requiring estrogens to grow. Estrogens are formed in the human body via a multistep route starting from cholesterol. The final steps in the biosynthesis include the CYP450 aromatase enzyme, converting the male hormones androgens (preferred substrate androstenedione ASD) into estrogens(estrone E1), and the 17beta-HSD1 enzyme, converting the biologically less active E1 into the active hormone 17beta-hydroxyestradiol E2. E2 is bound to the nuclear estrogen receptors causing a cascade of biochemical reactions leading to cell proliferation in normal tissue, and to tumour growth in cancer tissue. Aromatase and 17beta-HSD1 are expressed in or near the breast tumour, locally providing the tissue with estrogens. One approach in treating hormone dependent breast tumours is to block the local estrogen production by inhibiting these two enzymes. Aromatase inhibitors are already on the market in treating breast cancer, despite the lack of an experimentally solved structure. The structure of 17beta-HSD1, on the other hand, has been solved, but no commercial drugs have emerged from the drug discovery projects reported in the literature. Computer-assisted molecular modelling is an invaluable tool in modern drug design projects. Modelling techniques can be used to generate a model of the target protein and to design novel inhibitors for them even if the target protein structure is unknown. Molecular modelling has applications in predicting the activities of theoretical inhibitors and in finding possible active inhibitors from a compound database. Inhibitor binding at atomic level can also be studied with molecular modelling. To clarify the interactions between the aromatase enzyme and its substrate and inhibitors, we generated a homology model based on a mammalian CYP450 enzyme, rabbit progesterone 21-hydroxylase CYP2C5. The model was carefully validated using molecular dynamics simulations (MDS) with and without the natural substrate ASD. Binding orientation of the inhibitors was based on the hypothesis that the inhibitors coordinate to the heme iron, and were studied using MDS. The inhibitors were dietary phytoestrogens, which have been shown to reduce the risk for breast cancer. To further validate the model, the interactions of a commercial breast cancer drug were studied with MDS and ligand–protein docking. In the case of 17beta-HSD1, a 3D QSAR model was generated on the basis of MDS of an enzyme complex with active inhibitor and ligand–protein docking, employing a compound library synthesised in our laboratory. Furthermore, four pharmacophore hypotheses with and without a bound substrate or an inhibitor were developed and used in screening a commercial database of drug-like compounds. The homology model of aromatase showed stable behaviour in MDS and was capable of explaining most of the results from mutagenesis studies. We were able to identify the active site residues contributing to the inhibitor binding, and explain differences in coordination geometry corresponding to the inhibitory activity. Interactions between the inhibitors and aromatase were in agreement with the mutagenesis studies reported for aromatase. Simulations of 17beta-HSD1 with inhibitors revealed an inhibitor binding mode with hydrogen bond interactions previously not reported, and a hydrophobic pocket capable of accommodating a bulky side chain. Pharmacophore hypothesis generation, followed by virtual screening, was able to identify several compounds that can be used in lead compound generation. The visualisation of the interaction fields from the QSAR model and the pharmacophores provided us with novel ideas for inhibitor development in our drug discovery project.

Geological factors affecting on after-use of Finnish cut-over peatlands : with implications on the carbon accumulation

In Finland, peat harvesting sites are utilized down almost to the mineral soil. In this situation the properties of mineral subsoil are likely to have considerable influence on the suitability for the various after-use forms. The aims of this study were to recognize the chemical and physical properties of mineral subsoils possibly limiting the after-use of cut-over peatlands, to define a minimum practice for mineral subsoil studies and to describe the role of different geological areas. The future percentages of the different after-use forms were predicted, which made it possible to predict also carbon accumulation in this future situation. Mineral subsoils of 54 different peat production areas were studied. Their general features and grain size distribution was analysed. Other general items studied were pH, electrical conductivity, organic matter, water soluble nutrients (P, NO3-N, NH4-N, S and Fe) and exchangeable nutrients (Ca, Mg and K). In some cases also other elements were analysed. In an additional case study carbon accumulation effectiveness before the intervention was evaluated on three sites in Oulu area (representing sites typically considered for peat production). Areas with relatively sulphur rich mineral subsoil and pool-forming areas with very fine and compact mineral subsoil together covered approximately 1/5 of all areas. These areas were unsuitable for commercial use. They were recommended for example for mire regeneration. Another approximate 1/5 of the areas included very coarse or very fine sediments. Commercial use of these areas would demand special techniques - like using the remaining peat layer for compensating properties missing from the mineral subsoil. One after-use form was seldom suitable for one whole released peat production area. Three typical distribution patterns (models) of different mineral subsoils within individual peatlands were found. 57 % of studied cut-over peatlands were well suited for forestry. In a conservative calculation 26% of the areas were clearly suitable for agriculture, horticulture or energy crop production. If till without large boulders was included, the percentage of areas suitable to field crop production would be 42 %. 9-14 % of all areas were well suitable for mire regeneration or bird sanctuaries, but all areas were considered possible for mire regeneration with correct techniques. Also another 11 % was recommended for mire regeneration to avoid disturbing the mineral subsoil, so total 20-25 % of the areas would be used for rewetting. High sulphur concentrations and acidity were typical to the areas below the highest shoreline of the ancient Litorina sea and Lake Ladoga Bothnian Bay zone. Also differences related to nutrition were detected. In coarse sediments natural nutrient concentration was clearly higher in Lake Ladoga Bothnian Bay zone and in the areas of Svecokarelian schists and gneisses, than in Granitoid area of central Finland and in Archaean gneiss areas. Based on this study the recommended minimum analysis for after-use planning was for pH, sulphur content and fine material (<0.06 mm) percentage. Nutrition capacity could be analysed using the natural concentrations of calcium, magnesium and potassium. Carbon accumulation scenarios were developed based on the land-use predictions. These scenarios were calculated for areas in peat production and the areas released from peat production (59300 ha + 15 671 ha). Carbon accumulation of the scenarios varied between 0.074 and 0.152 million t C a-1. In the three peatlands considered for peat production the long term carbon accumulation rates varied between 13 and 24 g C m-2 a-1. The natural annual carbon accumulation had been decreasing towards the time of possible intervention.