Weather categorization in climate change research: Preliminary results

Summary The results of an objective weather categorization are presented. The 9 meteorological variables recorded daily during winter seasons of 1961–66 at Prague-Clementinum represent the input dataset. The principal component analysis and a few clustering procedures have been evaluated. 5 component solution and the average linkage clustering method were found optimal. The winter days have been grouped, according to their meteorological character, into 14 clusters. The warm categories represent 20% of the time and the cold categories less than 15% of the days. The mean maps of 1000 hPa and 500 hPa are shown for a few selected categories. Clustering techniques applied to long-time instrumental series can provide a better basis for attempting to detect temperature changes which have taken place over a long time span.     

On the Integrability of Limited-Area Numerical Weather Prediction Model ALADIN over Extended Time Periods

This note summarizes results of the first integration of regional numerical weather prediction model ALADIN in a climate mode. The ALADIN model, developed in an international cooperation led by Météo France, is operationally used for weather prediction. The grid step of the model is 12 km; the integration domain covers a major part of Europe. A one-month-long run has been performed with this model on observed boundary conditions (represented by assimilations by the global model ARPEGE). It is demonstrated that no excessive error is generated and accumulated in the model during the integration; hence the model is integrable for extended time periods and may serve a basis for a development towards a regional climate model.     

A GCM Simulation of Heat Waves, Dry Spells, and Their Relationships to Circulation

Heat waves and dry spells are analyzed (i) at eightstations in south Moravia (Czech Republic), (ii) inthe control ECHAM3 GCM run at the gridpoint closest tothe study area, and (iii) in the ECHAM3 GCM run fordoubled CO₂ concentrations (scenario A) at thesame gridpoint (heat waves only). The GCM outputs arevalidated both against individual station data andareally representative values. In the control run, theheat waves are too long, appear later in the year,peak at higher temperatures and their numbers areunder- (over-) estimated in June and July (in August).The simulated dry spells are too long, and the annualcycle of their occurrence is distorted.Mid-tropospheric circulation, and heat waves and dryspells are linked much less tightly in the controlclimate than in the observed. Since mid-troposphericcirculation is simulated fairly successfully, wesuggest the hypothesis that either the air-masstransformation and local processes are too strong inthe model or the simulated advection is too weak. Inthe scenario A climate, the heat waves become a commonphenomenon: warming of 4.5 °C in summer(difference between scenario A and control climates)induces a five-fold increase in the frequency oftropical days and an immense enhancement of extremityof heat waves. The results of the study underline theneed for (i) a proper validation of the GCM outputbefore a climate impact study is conducted and (ii)translation of large-scale information from GCMs intolocal scales using downscaling and stochasticmodelling techniques in order to reduce GCMs' biases.     

Testing for Trends in Data Unevenly Distributed in Time

Summary  The question discussed in this study is how to calculate linear trends in data that are not distributed evenly in time. This is examined with time series of ten climate elements at a single station, stratified according to a classification based on daily circulation patterns. Trends are calculated in three different ways: (i) from seasonal means, which is a common approach, (ii) from means of individual events, the event being defined as a sequence of days classified as one particular type, preceded and succeeded by another type, and (iii) from individual daily values. The most common method of estimating trend significance, i.e. the t-test of the Pearson correlation coefficient, has been shown to be applicable to seasonal and event-mean trends for all variables. For daily trends, the Monte Carlo test should be used instead. The daily, event-mean and seasonal trends differ from each other considerably for many combinations of climate variable and circulation type. The reason for this difference is identified. Received December 3, 1998 Revised June 21, 1999     

Nanostructure, composition and mechanisms of bivalve shell growth

Freshwater and marine cultured pearls form via identical processes to the shells of bivalves and can therefore serve as models for the biomineralization of bivalve shells in general. Their nanostructure consists of membrane-coated granules (vesicles) which contain amorphous calcium carbonate (ACC) at the beginning of the biomineralization sequence, preceding the crystallization of aragonite and vaterite. In contrast to the commonly accepted view, crystallization of ACC occurs rapidly and within the granular nano-compartments mediated by organic molecules much earlier than platelet formation. The interlamellar organic sheets in nacre that form the platelet structure of nacre themselves form by self-organization after the crystallization process of CaCO₃ is completed and, thus, cannot serve as a nucleation template for aragonite. Pores in the organic sheets are postulated to be a result of this process rather than to represent the pathways for CaCO₃ through pre-existing interlamellar sheets. The amorphous phase has the highest concentrations of Mg (5.8 mol%), Mn (6.6 mol%), S (4.7 mol%) and P (1 mol%) of the three CaCO₃-polymorphs. Mg/Ca and Mn/Ca ratios are found to decrease in the order ACC > vaterite > aragonite, corresponding to decreasing organic content in the different phases. This, as well as an observed enrichment of Mg in the organic-rich growth-banding of the pearls, suggests an at least partially organic speciation of Mg and Mn in bivalves and may be responsible for the observed physiological influence on Mg/Ca and Mn/Ca ratios in bivalves as a proxy for environmental parameters.     

Potential of continental-scale circulation for the determination of local daily surface variables

Summary This study deals with one aspect of statistical downscaling, viz. links between the continental-scale upper-air circulation and surface weather variables on a daily scale. The circulation-to-weather links are expressed in terms of multiple regression between either grid point values or intensities of circulation variability modes and weather elements, including temperature variables, relative humidity, cloudiness, sunshine duration, zonal and meridional wind components, precipitation, and atmospheric pressure. The upper-air circulation influences the surface pressure, temperature and zonal wind most strongly. The relative humidity, cloudiness and sunshine duration appear not to be connected with circulation in winter at all. The low-frequency part of circulation (i.e. processes with periods longer than 10 days) is most efficient in specifying surface weather variables. The circulation-to-weather links manifest considerable intra- and interdecadal variations, posing doubts on the applicability of the downscaling-from-circulation method of constructing climate change scenarios.With 11 Figures