University of Potsdam

About: University of Potsdam is a education organization based out in Potsdam, Germany. It is known for research contribution in the topics: Population & Computer science. The organization has 9629 authors who have published 26740 publications receiving 759745 citations. The organization is also known as: Universität Potsdam.

Possible links between long-term geomagnetic variations and whole-mantle convection processes

Abstract: The Earth's internal magnetic field varies on timescales of months to billions of years. The field is generated by convection in the liquid outer core, which in turn is influenced by the heat flowing from the core into the base of the overlying mantle. Much of the magnetic field's variation is thought to be stochastic, but over very long timescales, this variability may be related to changes in heat flow associated with mantle convection processes. Over the past 500 Myr, correlations between palaeomagnetic behaviour and surface processes were particularly striking during the middle to late Mesozoic era, beginning about 180 Myr ago. Simulations of the geodynamo suggest that transitions from periods of rapid polarity reversals to periods of prolonged stability — such as occurred between the Middle Jurassic and Middle Cretaceous periods — may have been triggered by a decrease in core-mantle boundary heat flow either globally or in equatorial regions. This decrease in heat flow could have been linked to reduced mantle-plume-head production at the core-mantle boundary, an episode of true polar wander, or a combination of the two.

On the statistics of urban heat island intensity

Abstract: [1] We perform a systematic study of all cities in Europe to assess the Urban Heat Island (UHI) intensity by means of remotely sensed land surface temperature data. Defining cities as spatial clusters of urban land cover, we investigate the relationships of the UHI intensity, with the cluster size and the temperature of the surroundings. Our results show that in Europe, the UHI intensity in summer has a strong correlation with the cluster size, which can be well fitted by an empirical sigmoid model. Furthermore, we find a novel seasonality of the UHI intensity for individual clusters in the form of hysteresis-like curves. We characterize the shape and identify apparent regional patterns.

Nonlinear Principal Component Analysis: Neural Network Models and Applications

Abstract: 1 Competence Centre for Functional Genomics, Institute for Microbiology, Ernst-Moritz-Arndt-University Greifswald, F.-L.-Jahn-Str. 15, 17487 Greifswald, Germany, Matthias.Scholz@uni-greifswald.de Martin.Fraunholz@uni-greifswald.de 2 Institute for Biochemistry and Biology, University of Potsdam, c/o Max Planck Institute for Molecular Plant Physiology Am Muhlenberg 1, 14424 Potsdam, Germany, Selbig@mpimp-golm.mpg.de

On the influence of density and morphology on the Urban Heat Island intensity

Abstract: The canopy layer urban heat island (UHI) effect, as manifested by elevated near-surface air temperatures in urban areas, exposes urban dwellers to additional heat stress in many cities, specially during heat waves. We simulate the urban climate of various generated cities under the same weather conditions. For mono-centric cities, we propose a linear combination of logarithmic city area and logarithmic gross building volume, which also captures the influence of building density. By studying various city shapes, we generalise and propose a reduced form to estimate UHI intensities based only on the structure of urban sites, as well as their relative distances. We conclude that in addition to the size, the UHI intensity of a city is directly related to the density and an amplifying effect that urban sites have on each other. Our approach can serve as a UHI rule of thumb for the comparison of urban development scenarios. How UHI intensity responds to variations of urban structure is unclear. Here the authors proposed a reduced form approach that is able to estimate UHI intensities based only on the number and location of urban sites as well as their distance.