Snow characteristics in Dronning Maud Land, Antarctica

Snow cover is very sensitive to climate change and has a large feedback effect on the climate system due to the high albedo. Snow covers almost all surfaces in Antarctica and small changes in snow properties can mean large changes in absorbed radiation. In the ongoing discussion of climatic change, the mass balance of Antarctica has received increasing focus during recent decades, since its reaction to global warming strongly influences sea-level change. The aim of the present work was to examine the spatial and temporal variations in the physical and chemical characteristics of surface snow and annual accumulation rates in western Dronning Maud Land, Antarctica. The data were collected along a 350-km-long transect from the coast to the plateau during the years 1999-2004 as a part of the Finnish Antarctic Research Programme (FINNARP). The research focused on the most recent annual accumulation in the coastal area. The results show that the distance from the sea, and the moisture source, was the most predominant factor controlling the variations in both physical (conductivity, grain size, oxygen isotope ratio and accumulation) and chemical snow properties. The sea-salt and sulphur-containing components predominated in the coastal region. The local influences of nunataks and topographic highs were also visible on snow. The variations in all measured properties were wide within single sites mostly due to redistribution by winds and sastrugi topography, which reveals the importance of the spatially representative measurements. The mean accumulations occurred on the ice shelf, in the coastal region and on the plateau: 312 ± 28, 215 ± 43 and 92 ± 25 mm w.e., respectively. Depth hoar layers were usually found under the thin ice crust and were associated with a low dielectric constant and high concentrations of nitrate. Taking into account the vast size of the Antarctic ice sheet and its geographic characteristics, it is important to extend investigation of the distribution of surface snow properties and accumulation to provide well-documented data.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

Simulations of dimensionally reduced effective theories of high temperature QCD

Quantum chromodynamics (QCD) is the theory describing interaction between quarks and gluons. At low temperatures, quarks are confined forming hadrons, e.g. protons and neutrons. However, at extremely high temperatures the hadrons break apart and the matter transforms into plasma of individual quarks and gluons. In this theses the quark gluon plasma (QGP) phase of QCD is studied using lattice techniques in the framework of dimensionally reduced effective theories EQCD and MQCD. Two quantities are in particular interest: the pressure (or grand potential) and the quark number susceptibility. At high temperatures the pressure admits a generalised coupling constant expansion, where some coefficients are non-perturbative. We determine the first such contribution of order g^6 by performing lattice simulations in MQCD. This requires high precision lattice calculations, which we perform with different number of colors N_c to obtain N_c-dependence on the coefficient. The quark number susceptibility is studied by performing lattice simulations in EQCD. We measure both flavor singlet (diagonal) and non-singlet (off-diagonal) quark number susceptibilities. The finite chemical potential results are optained using analytic continuation. The diagonal susceptibility approaches the perturbative result above 20T_c$, but below that temperature we observe significant deviations. The results agree well with 4d lattice data down to temperatures 2T_c.