Trends of spring time frost events and phenological dates in Central Europe

Summary ?Over large parts of the Northern Hemisphere’s continents temperature has been increasing during the last century. Particularly minimum temperatures show a more pronounced increase than maximum temperatures. Not only the phenological seasons, but also the potentially plant damaging late frost events are governed by the atmosphere. In case of a rise of minimum temperatures one would expect phenological phases and spring late frost events to occur earlier. In this work the question is elucidated whether plant phenology shifts at a higher or lower rate towards earlier occurrences than potential plant damaging events, like spring late frost events. Frost events based on the last occurrence of daily minimum temperatures below a certain threshold have been moving faster to earlier occurrence dates than phenological phases during the last decades at 50 climate stations in Central Europe. Trend values of frost time series range around −0.2 days/year and of phenological time series are between −0.2 and 0.0 days/year over the period from 1951–1997. ‘Corylus avellana beginning of pollination’ is the only one of the 13 phases considered here with a lower trend value of −0.28 days/year. Early phases are more adapted to below zero temperatures and therefore follow more closely the temperature variability. Later phases seem to have more reason to be concerned about possible late frost events and react more cautiously towards higher spring temperatures and earlier last frost dates. The risk of late frost damage for plants should have been lower during the last decade as compared to the previous decades. Received June 28, 2002; accepted July 18, 2002     

Confidence regions for GPS baselines by Bayesian statistics

 The global positioning system (GPS) model is distinctive in the way that the unknown parameters are not only real-valued, the baseline coordinates, but also integers, the phase ambiguities. The GPS model therefore leads to a mixed integer–real-valued estimation problem. Common solutions are the float solution, which ignores the ambiguities being integers, or the fixed solution, where the ambiguities are estimated as integers and then are fixed. Confidence regions, so-called HPD (highest posterior density) regions, for the GPS baselines are derived by Bayesian statistics. They take care of the integer character of the phase ambiguities but still consider them as unknown parameters. Estimating these confidence regions leads to a numerical integration problem which is solved by Monte Carlo methods. This is computationally expensive so that approximations of the confidence regions are also developed. In an example it is shown that for a high confidence level the confidence region consists of more than one region. Received: 1 February 2001 / Accepted: 18 July 2001     

Strain investigations on calcite marbles using neutron time-of-flight diffraction

In order to describe and explain the effect of bowing of marble facade panels, neutron time-of-flight diffraction was applied to determine residual macro- and microstrain on the calcite mineral phase. The measurements were combined with investigations of the crystallographic preferred orientation (texture) measurements by neutron diffraction, macroscopic measuring of the bowing on marble building stones, as well as microfabric analyses. Three samples were investigated to explain the bowing effect: a fresh broken sample, a good conditioned facade panel and a strongly deformed facade panel. Residual intracrystalline strain was detected in all investigated samples, which differed in the degree of bowing. For the first time, the preferred orientation and the residual strain were found to be related. The results show that different strain magnitudes are reflected by residual strains, which differ significantly in magnitude and direction. Furthermore, different Bragg peak widths have been detected as an indication of microscopic strain. The observed residual strain values in the samples are related with the grain shape and texture properties.     

A generalized model for evaluating area-potential in a mineral exploration program

A generalized model for predicting the potential of geographic areas for mineral exploration is developed using computers and mathematical techniques. A cellular approach is adopted and each area is divided into cells; the data base is transformed into a computer processable form by digitizing data over each cell. Control cells are selected from a control area by two a priori subjective models using multiple linear regression and filtering techniques. These control cells are used to develop weighting factors for computer-transformed variables. The evaluation and prediction of cells are made using an evaluation model, wherein products of weighting factors and corresponding transformed variables are added to give a probability score for each cell. In the example analysis, 7.76% of cells are selected as predicted cells and checked for mining in the cell areas by comparing them with a mining data base. Of the total predicted cells, 38.13% are classified as first-order prospects and the remaining predicted cells are classified into second- and third-order prospects. The success of the prediction and the open structure of the model implies a successful, generalized model with capabilities of evaluating large areas and predicting the potential in any exploration program.Presented at the Third Decennial International Conference on Geophysical and Geochemical Exploration for Minerals and Groundwater, Sept. 27–Oct 1, 1987, Toronto, Canada.