Factors controlling the surface energy budget over snow and ice

Polar Regions are an energy sink of the Earth system, as the Sun rays do not reach the Poles for half of the year, and hit them only at very low angles for the other half of the year. In summer, solar radiation is the dominant energy source for the Polar areas, therefore even small changes in the surface albedo strongly affect the surface energy balance and, thus, the speed and amount of snow and ice melting. In winter, the main heat sources for the atmosphere are the cyclones approaching from lower latitudes, and the atmosphere-surface heat transfer takes place through turbulent mixing and longwave radiation, the latter dominated by clouds. The aim of this thesis is to improve the knowledge about the surface and atmospheric processes that control the surface energy budget over snow and ice, with particular focus on albedo during the spring and summer seasons, on horizontal advection of heat, cloud longwave forcing, and turbulent mixing during the winter season. The critical importance of a correct albedo representation in models is illustrated through the analysis of the causes for the errors in the surface and near-surface air temperature produced in a short-range numerical weather forecast by the HIRLAM model. Then, the daily and seasonal variability of snow and ice albedo have been examined by analysing field measurements of albedo, carried out in different environments. On the basis of the data analysis, simple albedo parameterizations have been derived, which can be implemented into thermodynamic sea ice models, as well as numerical weather prediction and climate models. Field measurements of radiation and turbulent fluxes over the Bay of Bothnia (Baltic Sea) also allowed examining the impact of a large albedo change during the melting season on surface energy and ice mass budgets. When high contrasts in surface albedo are present, as in the case of snow covered areas next to open water, the effect of the surface albedo heterogeneity on the downwelling solar irradiance under overcast condition is very significant, although it is usually not accounted for in single column radiative transfer calculations. To account for this effect, an effective albedo parameterization based on three-dimensional Monte Carlo radiative transfer calculations has been developed. To test a potentially relevant application of the effective albedo parameterization, its performance in the ground-based retrieval of cloud optical depth was illustrated. Finally, the factors causing the large variations of the surface and near-surface temperatures over the Central Arctic during winter were examined. The relative importance of cloud radiative forcing, turbulent mixing, and lateral heat advection on the Arctic surface temperature were quantified through the analysis of direct observations from Russian drifting ice stations, with the lateral heat advection calculated from reanalysis products.

Learning Nonlinear Visual Processing from Natural Images

The paradigm of computational vision hypothesizes that any visual function -- such as the recognition of your grandparent -- can be replicated by computational processing of the visual input. What are these computations that the brain performs? What should or could they be? Working on the latter question, this dissertation takes the statistical approach, where the suitable computations are attempted to be learned from the natural visual data itself. In particular, we empirically study the computational processing that emerges from the statistical properties of the visual world and the constraints and objectives specified for the learning process. This thesis consists of an introduction and 7 peer-reviewed publications, where the purpose of the introduction is to illustrate the area of study to a reader who is not familiar with computational vision research. In the scope of the introduction, we will briefly overview the primary challenges to visual processing, as well as recall some of the current opinions on visual processing in the early visual systems of animals. Next, we describe the methodology we have used in our research, and discuss the presented results. We have included some additional remarks, speculations and conclusions to this discussion that were not featured in the original publications. We present the following results in the publications of this thesis. First, we empirically demonstrate that luminance and contrast are strongly dependent in natural images, contradicting previous theories suggesting that luminance and contrast were processed separately in natural systems due to their independence in the visual data. Second, we show that simple cell -like receptive fields of the primary visual cortex can be learned in the nonlinear contrast domain by maximization of independence. Further, we provide first-time reports of the emergence of conjunctive (corner-detecting) and subtractive (opponent orientation) processing due to nonlinear projection pursuit with simple objective functions related to sparseness and response energy optimization. Then, we show that attempting to extract independent components of nonlinear histogram statistics of a biologically plausible representation leads to projection directions that appear to differentiate between visual contexts. Such processing might be applicable for priming, \ie the selection and tuning of later visual processing. We continue by showing that a different kind of thresholded low-frequency priming can be learned and used to make object detection faster with little loss in accuracy. Finally, we show that in a computational object detection setting, nonlinearly gain-controlled visual features of medium complexity can be acquired sequentially as images are encountered and discarded. We present two online algorithms to perform this feature selection, and propose the idea that for artificial systems, some processing mechanisms could be selectable from the environment without optimizing the mechanisms themselves. In summary, this thesis explores learning visual processing on several levels. The learning can be understood as interplay of input data, model structures, learning objectives, and estimation algorithms. The presented work adds to the growing body of evidence showing that statistical methods can be used to acquire intuitively meaningful visual processing mechanisms. The work also presents some predictions and ideas regarding biological visual processing.

Cellular Mechanisms of Sleep Homeostasis : Studies on Brain Energy Metabolism and Aging

Sleep is governed by a homeostatic process in which the duration and quality of previous wake regulate the subsequent sleep. Active wakefulness is characterized with high frequency cortical oscillations and depends on stimulating influence of the arousal systems, such as the cholinergic basal forebrain (BF), while cessation of the activity in the arousal systems is required for slow wave sleep (SWS) to occur. The site-specific accumulation of adenosine (a by-product of ATP breakdown) in the BF during prolonged waking /sleep deprivation (SD) is known to induce sleep, thus coupling energy demand to sleep promotion. The adenosine release in the BF is accompanied with increases in extracellular lactate and nitric oxide (NO) levels. This thesis was aimed at further understanding the cellular processes by which the BF is involved in sleep-wake regulation and how these processes are affected by aging. The BF function was studied simultaneously at three levels of organization: 1) locally at a cellular level by measuring energy metabolites 2) globally at a cortical level (the out-put area of the BF) by measuring EEG oscillations and 3) at a behavioral level by studying changes in vigilance states. Study I showed that wake-promoting BF activation, particularly with glutamate receptor agonist N-methyl-D-aspatate (NMDA), increased extracellular adenosine and lactate levels and led to a homeostatic increase in the subsequent sleep. Blocking NMDA activation during SD reduced the high frequency (HF) EEG theta (7-9 Hz) power and attenuated the subsequent sleep. In aging, activation of the BF during SD or experimentally with NMDA (studies III, IV), did not induce lactate or adenosine release and the increases in the HF EEG theta power during SD and SWS during the subsequent sleep were attenuated as compared to the young. These findings implicate that increased or continuous BF activity is important for active wake maintenance during SD as well as for the generation of homeostatic sleep pressure, and that in aging these mechanisms are impaired. Study II found that induction of the inducible NO synthase (iNOS) during SD is accompanied with activation of the AMP-activated protein kinase (AMPK) in the BF. Because decreased cellular energy charge is the most common cause for AMPK activation, this finding implicates that the BF is selectively sensitive to the metabolic demands of SD as increases were not found in the cortex. In aging (study III), iNOS expression and extracellular levels of NO and adenosine were not significantly increased during SD in the BF. Furthermore, infusion of NO donor into the BF did not lead to sleep promotion as it did in the young. These findings indicated that the NO (and adenosine) mediated sleep induction is impaired in aging and that it could at least partly be due to the reduced sensitivity of the BF to sleep-inducing factors. Taken together, these findings show that reduced sleep promotion by the BF contributes to the attenuated homeostatic sleep response in aging.

Sleep deprivation and brain energy metabolism : in vivo studies in rats and humans

Sleep deprivation leads to increased subsequent sleep length and depth and to deficits in cognitive performance in humans. In animals extreme sleep deprivation is eventually fatal. The cellular and molecular mechanisms causing the symptoms of sleep deprivation are unclear. This thesis was inspired by the hypothesis that during wakefulness brain energy stores would be depleted, and they would be replenished during sleep. The aim of this thesis was to elucidate the energy metabolic processes taking place in the brain during sleep deprivation. Endogenous brain energy metabolite levels were assessed in vivo in rats and in humans in four separate studies (Studies I-IV). In the first part (Study I) the effects of local energy depletion on brain energy metabolism and sleep were studied in rats with the use of in vivo microdialysis combined with high performance liquid chromatography. Energy depletion induced by 2,4-dinitrophenol infusion into the basal forebrain was comparable to the effects of sleep deprivation: both increased extracellular concentrations of adenosine, lactate, and pyruvate, and elevated subsequent sleep. This result supports the hypothesis of a connection between brain energy metabolism and sleep. The second part involved healthy human subjects (Studies II-IV). Study II aimed to assess the feasibility of applying proton magnetic resonance spectroscopy (1H MRS) to study brain lactate levels during cognitive stimulation. Cognitive stimulation induced an increase in lactate levels in the left inferior frontal gyrus, showing that metabolic imaging of neuronal activity related to cognition is possible with 1H MRS. Study III examined the effects of sleep deprivation and aging on the brain lactate response to cognitive stimulation. No physiologic, cognitive stimulation-induced lactate response appeared in the sleep-deprived and in the aging subjects, which can be interpreted as a sign of malfunctioning of brain energy metabolism. This malfunctioning may contribute to the functional impairment of the frontal cortex both during aging and sleep deprivation. Finally (Study IV), 1H MRS major metabolite levels in the occipital cortex were assessed during sleep deprivation and during photic stimulation. N-acetyl-aspartate (NAA/H2O) decreased during sleep deprivation, supporting the hypothesis of sleep deprivation-induced disturbance in brain energy metabolism. Choline containing compounds (Cho/H2O) decreased during sleep deprivation and recovered to alert levels during photic stimulation, pointing towards changes in membrane metabolism, and giving support to earlier observations of altered brain response to stimulation during sleep deprivation. Based on these findings, it can be concluded that sleep deprivation alters brain energy metabolism. However, the effects of sleep deprivation on brain energy metabolism may vary from one brain area to another. Although an effect of sleep deprivation might not in all cases be detectable in the non-stimulated baseline state, a challenge imposed by cognitive or photic stimulation can reveal significant changes. It can be hypothesized that brain energy metabolism during sleep deprivation is more vulnerable than in the alert state. Changes in brain energy metabolism may participate in the homeostatic regulation of sleep and contribute to the deficits in cognitive performance during sleep deprivation.

Urban energy fluxes in Helsinki and their high frequency spectral corrections

Inadvertent climate modification has led to an increase in urban temperatures compared to the surrounding rural area. The main reason for the temperature rise is the altered energy portioning of input net radiation to heat storage and sensible and latent heat fluxes in addition to the anthropogenic heat flux. The heat storage flux and anthropogenic heat flux have not yet been determined for Helsinki and they are not directly measurable. To the contrary, turbulent fluxes of sensible and latent heat in addition to net radiation can be measured, and the anthropogenic heat flux together with the heat storage flux can be solved as a residual. As a result, all inaccuracies in the determination of the energy balance components propagate to the residual term and special attention must be paid to the accurate determination of the components. One cause of error in the turbulent fluxes is the fluctuation attenuation at high frequencies which can be accounted for by high frequency spectral corrections. The aim of this study is twofold: to assess the relevance of high frequency corrections to water vapor fluxes and to assess the temporal variation of the energy fluxes. Turbulent fluxes of sensible and latent heat have been measured at SMEAR III station, Helsinki, since December 2005 using the eddy covariance technique. In addition, net radiation measurements have been ongoing since July 2007. The used calculation methods in this study consist of widely accepted eddy covariance data post processing methods in addition to Fourier and wavelet analysis. The high frequency spectral correction using the traditional transfer function method is highly dependent on relative humidity and has an 11% effect on the latent heat flux. This method is based on an assumption of spectral similarity which is shown not to be valid. A new correction method using wavelet analysis is thus initialized and it seems to account for the high frequency variation deficit. Anyhow, the resulting wavelet correction remains minimal in contrast to the traditional transfer function correction. The energy fluxes exhibit a behavior characteristic for urban environments: the energy input is channeled to sensible heat as latent heat flux is restricted by water availability. The monthly mean residual of the energy balance ranges from 30 Wm-2 in summer to -35 Wm-2 in winter meaning a heat storage to the ground during summer. Furthermore, the anthropogenic heat flux is approximated to be 50 Wm-2 during winter when residential heating is important.

Analyzing changes in macro-level drivers of country-specific emissions : The role of consumption, technology and trade

Industrial ecology is an important field of sustainability science. It can be applied to study environmental problems in a policy relevant manner. Industrial ecology uses ecosystem analogy; it aims at closing the loop of materials and substances and at the same time reducing resource consumption and environmental emissions. Emissions from human activities are related to human interference in material cycles. Carbon (C), nitrogen (N) and phosphorus (P) are essential elements for all living organisms, but in excess have negative environmental impacts, such as climate change (CO2, CH4 N2O), acidification (NOx) and eutrophication (N, P). Several indirect macro-level drivers affect emissions change. Population and affluence (GDP/capita) often act as upward drivers for emissions. Technology, as emissions per service used, and consumption, as economic intensity of use, may act as drivers resulting in a reduction in emissions. In addition, the development of country-specific emissions is affected by international trade. The aim of this study was to analyse changes in emissions as affected by macro-level drivers in different European case studies. ImPACT decomposition analysis (IPAT identity) was applied as a method in papers I III. The macro-level perspective was applied to evaluate CO2 emission reduction targets (paper II) and the sharing of greenhouse gas emission reduction targets (paper IV) in the European Union (EU27) up to the year 2020. Data for the study were mainly gathered from official statistics. In all cases, the results were discussed from an environmental policy perspective. The development of nitrogen oxide (NOx) emissions was analysed in the Finnish energy sector during a long time period, 1950 2003 (paper I). Finnish emissions of NOx began to decrease in the 1980s as the progress in technology in terms of NOx/energy curbed the impact of the growth in affluence and population. Carbon dioxide (CO2) emissions related to energy use during 1993 2004 (paper II) were analysed by country and region within the European Union. Considering energy-based CO2 emissions in the European Union, dematerialization and decarbonisation did occur, but not sufficiently to offset population growth and the rapidly increasing affluence during 1993 2004. The development of nitrogen and phosphorus load from aquaculture in relation to salmonid consumption in Finland during 1980 2007 was examined, including international trade in the analysis (paper III). A regional environmental issue, eutrophication of the Baltic Sea, and a marginal, yet locally important source of nutrients was used as a case. Nutrient emissions from Finnish aquaculture decreased from the 1990s onwards: although population, affluence and salmonid consumption steadily increased, aquaculture technology improved and the relative share of imported salmonids increased. According to the sustainability challenge in industrial ecology, the environmental impact of the growing population size and affluence should be compensated by improvements in technology (emissions/service used) and with dematerialisation. In the studied cases, the emission intensity of energy production could be lowered for NOx by cleaning the exhaust gases. Reorganization of the structure of energy production as well as technological innovations will be essential in lowering the emissions of both CO2 and NOx. Regarding the intensity of energy use, making the combustion of fuels more efficient and reducing energy use are essential. In reducing nutrient emissions from Finnish aquaculture to the Baltic Sea (paper III) through technology, limits of biological and physical properties of cultured fish, among others, will eventually be faced. Regarding consumption, salmonids are preferred to many other protein sources. Regarding trade, increasing the proportion of imports will outsource the impacts. Besides improving technology and dematerialization, other viewpoints may also be needed. Reducing the total amount of nutrients cycling in energy systems and eventually contributing to NOx emissions needs to be emphasized. Considering aquaculture emissions, nutrient cycles can be partly closed through using local fish as feed replacing imported feed. In particular, the reduction of CO2 emissions in the future is a very challenging task when considering the necessary rates of dematerialisation and decarbonisation (paper II). Climate change mitigation may have to focus on other greenhouse gases than CO2 and on the potential role of biomass as a carbon sink, among others. The global population is growing and scaling up the environmental impact. Population issues and growing affluence must be considered when discussing emission reductions. Climate policy has only very recently had an influence on emissions, and strong actions are now called for climate change mitigation. Environmental policies in general must cover all the regions related to production and impacts in order to avoid outsourcing of emissions and leakage effects. The macro-level drivers affecting changes in emissions can be identified with the ImPACT framework. Statistics for generally known macro-indicators are currently relatively well available for different countries, and the method is transparent. In the papers included in this study, a similar method was successfully applied in different types of case studies. Using transparent macro-level figures and a simple top-down approach are also appropriate in evaluating and setting international emission reduction targets, as demonstrated in papers II and IV. The projected rates of population and affluence growth are especially worth consideration in setting targets. However, sensitivities in calculations must be carefully acknowledged. In the basic form of the ImPACT model, the economic intensity of consumption and emission intensity of use are included. In seeking to examine consumption but also international trade in more detail, imports were included in paper III. This example demonstrates well how outsourcing of production influences domestic emissions. Country-specific production-based emissions have often been used in similar decomposition analyses. Nevertheless, trade-related issues must not be ignored.

Acceleration of the Cosmological Expansion as an Effect of Inhomogeneities

The cosmological observations of light from type Ia supernovae, the cosmic microwave background and the galaxy distribution seem to indicate that the expansion of the universe has accelerated during the latter half of its age. Within standard cosmology, this is ascribed to dark energy, a uniform fluid with large negative pressure that gives rise to repulsive gravity but also entails serious theoretical problems. Understanding the physical origin of the perceived accelerated expansion has been described as one of the greatest challenges in theoretical physics today. In this thesis, we discuss the possibility that, instead of dark energy, the acceleration would be caused by an effect of the nonlinear structure formation on light, ignored in the standard cosmology. A physical interpretation of the effect goes as follows: due to the clustering of the initially smooth matter with time as filaments of opaque galaxies, the regions where the detectable light travels get emptier and emptier relative to the average. As the developing voids begin to expand the faster the lower their matter density becomes, the expansion can then accelerate along our line of sight without local acceleration, potentially obviating the need for the mysterious dark energy. In addition to offering a natural physical interpretation to the acceleration, we have further shown that an inhomogeneous model is able to match the main cosmological observations without dark energy, resulting in a concordant picture of the universe with 90% dark matter, 10% baryonic matter and 15 billion years as the age of the universe. The model also provides a smart solution to the coincidence problem: if induced by the voids, the onset of the perceived acceleration naturally coincides with the formation of the voids. Additional future tests include quantitative predictions for angular deviations and a theoretical derivation of the model to reduce the required phenomenology. A spin-off of the research is a physical classification of the cosmic inhomogeneities according to how they could induce accelerated expansion along our line of sight. We have identified three physically distinct mechanisms: global acceleration due to spatial variations in the expansion rate, faster local expansion rate due to a large local void and biased light propagation through voids that expand faster than the average. A general conclusion is that the physical properties crucial to account for the perceived acceleration are the growth of the inhomogeneities and the inhomogeneities in the expansion rate. The existence of these properties in the real universe is supported by both observational data and theoretical calculations. However, better data and more sophisticated theoretical models are required to vindicate or disprove the conjecture that the inhomogeneities are responsible for the acceleration.

Aspects of Inflationary Models at Low Energy Scales

Cosmological inflation is the dominant paradigm in explaining the origin of structure in the universe. According to the inflationary scenario, there has been a period of nearly exponential expansion in the very early universe, long before the nucleosynthesis. Inflation is commonly considered as a consequence of some scalar field or fields whose energy density starts to dominate the universe. The inflationary expansion converts the quantum fluctuations of the fields into classical perturbations on superhorizon scales and these primordial perturbations are the seeds of the structure in the universe. Moreover, inflation also naturally explains the high degree of homogeneity and spatial flatness of the early universe. The real challenge of the inflationary cosmology lies in trying to establish a connection between the fields driving inflation and theories of particle physics. In this thesis we concentrate on inflationary models at scales well below the Planck scale. The low scale allows us to seek for candidates for the inflationary matter within extensions of the Standard Model but typically also implies fine-tuning problems. We discuss a low scale model where inflation is driven by a flat direction of the Minimally Supersymmetric Standard Model. The relation between the potential along the flat direction and the underlying supergravity model is studied. The low inflationary scale requires an extremely flat potential but we find that in this particular model the associated fine-tuning problems can be solved in a rather natural fashion in a class of supergravity models. For this class of models, the flatness is a consequence of the structure of the supergravity model and is insensitive to the vacuum expectation values of the fields that break supersymmetry. Another low scale model considered in the thesis is the curvaton scenario where the primordial perturbations originate from quantum fluctuations of a curvaton field, which is different from the fields driving inflation. The curvaton gives a negligible contribution to the total energy density during inflation but its perturbations become significant in the post-inflationary epoch. The separation between the fields driving inflation and the fields giving rise to primordial perturbations opens up new possibilities to lower the inflationary scale without introducing fine-tuning problems. The curvaton model typically gives rise to relatively large level of non-gaussian features in the statistics of primordial perturbations. We find that the level of non-gaussian effects is heavily dependent on the form of the curvaton potential. Future observations that provide more accurate information of the non-gaussian statistics can therefore place constraining bounds on the curvaton interactions.

Molecular dynamics studies of nanoparticle impacts

This thesis concerns the dynamics of nanoparticle impacts on solid surfaces. These impacts occur, for instance, in space, where micro- and nanometeoroids hit surfaces of planets, moons, and spacecraft. On Earth, materials are bombarded with nanoparticles in cluster ion beam devices, in order to clean or smooth their surfaces, or to analyse their elemental composition. In both cases, the result depends on the combined effects of countless single impacts. However, the dynamics of single impacts must be understood before the overall effects of nanoparticle radiation can be modelled. In addition to applications, nanoparticle impacts are also important to basic research in the nanoscience field, because the impacts provide an excellent case to test the applicability of atomic-level interaction models to very dynamic conditions. In this thesis, the stopping of nanoparticles in matter is explored using classical molecular dynamics computer simulations. The materials investigated are gold, silicon, and silica. Impacts on silicon through a native oxide layer and formation of complex craters are also simulated. Nanoparticles up to a diameter of 20 nm (315000 atoms) were used as projectiles. The molecular dynamics method and interatomic potentials for silicon and gold are examined in this thesis. It is shown that the displacement cascade expansionmechanism and crater crown formation are very sensitive to the choice of atomic interaction model. However, the best of the current interatomic models can be utilized in nanoparticle impact simulation, if caution is exercised. The stopping of monatomic ions in matter is understood very well nowadays. However, interactions become very complex when several atoms impact on a surface simultaneously and within a short distance, as happens in a nanoparticle impact. A high energy density is deposited in a relatively small volume, which induces ejection of material and formation of a crater. Very high yields of excavated material are observed experimentally. In addition, the yields scale nonlinearly with the cluster size and impact energy at small cluster sizes, whereas in macroscopic hypervelocity impacts, the scaling 2 is linear. The aim of this thesis is to explore the atomistic mechanisms behind the nonlinear scaling at small cluster sizes. It is shown here that the nonlinear scaling of ejected material yield disappears at large impactor sizes because the stopping mechanism of nanoparticles gradually changes to the same mechanism as in macroscopic hypervelocity impacts. The high yields at small impactor size are due to the early escape of energetic atoms from the hot region. In addition, the sputtering yield is shown to depend very much on the spatial initial energy and momentum distributions that the nanoparticle induces in the material in the first phase of the impact. At the later phases, the ejection of material occurs by several mechanisms. The most important mechanism at high energies or at large cluster sizes is atomic cluster ejection from the transient liquid crown that surrounds the crater. The cluster impact dynamics detected in the simulations are in agreement with several recent experimental results. In addition, it is shown that relatively weak impacts can induce modifications on the surface of an amorphous target over a larger area than was previously expected. This is a probable explanation for the formation of the complex crater shapes observed on these surfaces with atomic force microscopy. Clusters that consist of hundreds of thousands of atoms induce long-range modifications in crystalline gold.