Refine
Year of publication
Document Type
- Article (2597)
- Doctoral Thesis (407)
- Postprint (138)
- Other (74)
- Review (51)
- Preprint (17)
- Monograph/Edited Volume (13)
- Conference Proceeding (12)
- Habilitation Thesis (11)
- Master's Thesis (6)
Language
- English (3328) (remove)
Keywords
- climate change (51)
- Holocene (44)
- erosion (27)
- Himalaya (26)
- permafrost (26)
- Climate change (23)
- remote sensing (23)
- Tibetan Plateau (22)
- Earthquake source observations (21)
- Pollen (20)
Institute
- Institut für Geowissenschaften (3328) (remove)
We use a data set of 35 surface pollen samples from lake sediments, moss polsters and top soils on the north- eastern Tibetan Plateau to explore the relationship between modern pollen assemblages and contemporary vegetation patterns. The surface pollen transect spanned four vegetation zones--alpine meadow, steppe, steppe desert and desert-- under different climatic/elevational conditions. Relative representation (R (rel)) values and Principal Components Analysis (PCA) were used to determine the relationships between modern pollen and vegetation and regional climate gradients. The results show that the main vegetation zones along the regional and elevational transects can be distinguished by their modern pollen spectra. Relative to Poaceae, a high representation of Artemisia, Nitraria and Chenopodiaceae was found, while Cyperaceae and Gentiana showed values in the middle range, and Ranunculaceae, Asteraceae, Ephedra and Fabaceae had low relative representation values. PCA results indicate a high correlation between the biogeoclimatic zones and annual precipitation and annual temperature and July temperature. The Artemisia/ Chenopodiaceae ratio and the Artemisia/Cyperaceae ratio are useful tools for qualitative and semi-quantitative palaeoenvironmental reconstruction on the north-eastern Tibetan Plateau. Surface lake sediments are found to have different palynomorph spectra from moss cushion and soil samples, reflecting the larger pollen source area in the contemporary vegetation for lakes.
The Kp index is a measure of the midlatitude global geomagnetic activity and represents short-term magnetic variations driven by solar wind plasma and interplanetary magnetic field. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere and the radiation belts. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast Kp, based their inferences on the recent history of Kp and on solar wind measurements at L1. In this study, we systematically test how different machine learning techniques perform on the task of nowcasting and forecasting Kp for prediction horizons of up to 12 hr. Additionally, we investigate different methods of machine learning and information theory for selecting the optimal inputs to a predictive model. We illustrate how these methods can be applied to select the most important inputs to a predictive model of Kp and to significantly reduce input dimensionality. We compare our best performing models based on a reduced set of optimal inputs with the existing models of Kp, using different test intervals, and show how this selection can affect model performance.
This article offers a reconstruction of the vegetation and climate of the south-western Siberian Baraba forest-steppe area during the last ca. 8000 years. The analysis of palynological data from the sediment core of Lake Bolshie Toroki using quantitative methods has made it possible to reconstruct changes of the dominant types of vegetation and mean July air temperatures. Coniferous forests grew in the vicinity of the lake, and mean July air temperatures were similar to present-day ones between 7.9 and 7.0 kyr BP. The warmest and driest climate occurred at 7.0-5.0 kyr BP. At that time, the region had open steppe landscapes; birch groves began to spread. A cooling trend is seen after 5.5 kyr BP, when forest-steppe began to emerge. Steppe communities started to dominate again after 1.5 kyr BP. Mean July air temperatures lower than now are reconstructed for the period of 1.9-1 kyr BP, and then the temperatures became similar to present-day ones. Comparing the archaeological data on the types of economy of the population which inhabited the Baraba forest-steppe with the data on changes in the natural environment revealed a connection between the gradual transition from hunting and fishing to livestock breeding and the development of forest-steppe landscapes with a decrease in the area covered by forests. The development of the forest-steppe as an ecotonic landscape starting around 5 kyr BP might have contributed to the coexistence of several archaeological cultures with different types of economy on the same territory. (C) 2017 Elsevier Ltd. All rights reserved.
To what extent cities can be made sustainable under the mega-trends of urbanization and climate change remains a matter of unresolved scientific debate. Our inability in answering this question lies partly in the deficient knowledge regarding pivotal humanenvironment interactions. Regarded as the most well documented anthropogenic climate modification, the urban heat island (UHI) effect – the warmth of urban areas relative to the rural hinterland – has raised great public health concerns globally. Worse still, heat waves are being observed and are projected to increase in both frequency and intensity, which further impairs the well-being of urban dwellers. Albeit with a substantial increase in the number of publications on UHI in the recent decades, the diverse urban-rural definitions applied in previous studies have remarkably hampered the general comparability of results achieved. In addition, few studies have attempted to synergize the land use data and thermal remote sensing to systematically assess UHI and its contributing factors.
Given these research gaps, this work presents a general framework to systematically quantify the UHI effect based on an automated algorithm, whereby cities are defined as clusters of maximum spatial continuity on the basis of land use data, with their rural hinterland being defined analogously. By combining land use data with spatially explicit surface skin temperatures from satellites, the surface UHI intensity can be calculated in a consistent and robust manner. This facilitates monitoring, benchmarking, and categorizing UHI intensities for cities across scales. In light of this innovation, the relationship between city size and UHI intensity has been investigated, as well as the contributions of urban form indicators to the UHI intensity.
This work delivers manifold contributions to the understanding of the UHI, which have complemented and advanced a number of previous studies. Firstly, a log-linear relationship between surface UHI intensity and city size has been confirmed among the 5,000 European cities. The relationship can be extended to a log-logistic one, when taking a wider range of small-sized cities into account. Secondly, this work reveals a complex interplay between UHI intensity and urban form. City size is found to have the strongest influence on the UHI intensity, followed by the fractality and the anisometry. However, their relative contributions to the surface UHI intensity depict a pronounced regional heterogeneity, indicating the importance of considering spatial patterns of UHI while implementing UHI adaptation measures.
Lastly, this work presents a novel seasonality of the UHI intensity for individual clusters in the form of hysteresis-like curves, implying a phase shift between the time series of UHI intensity and background temperatures. Combining satellite observation and urban boundary layer simulation, the seasonal variations of UHI are assessed from both screen and skin levels. Taking London as an example, this work ascribes the discrepancies between the seasonality observed at different levels mainly to the peculiarities of surface skin temperatures associated with the incoming solar radiation. In addition, the efforts in classifying cities according to their UHI characteristics highlight the important role of regional climates in determining the UHI.
This work serves as one of the first studies conducted to systematically and statistically scrutinize the UHI. The outcomes of this work are of particular relevance for the overall spatial planning and regulation at meso- and macro levels in order to harness the benefits of rapid urbanization, while proactively minimizing its ensuing thermal stress.
This paper assesses the seasonality of the urban heat island (UHI) effect in the Greater London area (United Kingdom). Combining satellite-based observations and urban boundary layer climate modeling with the UrbClim model, the authors are able to address the seasonality of UHI intensity, on the basis of both land surface temperature (LST) and 2-m air temperature, for four individual times of the day (0130, 1030, 1330, and 2230 local time) and the daily means derived from them. An objective of this paper is to investigate whether the UHI intensities that are based on both quantities exhibit a similar hysteresis-like trajectory that is observed for LST when plotting the UHI intensity against the background temperature. The results show that the UrbClim model can satisfactorily reproduce both the observed urban rural LSTs and 2-m air temperatures as well as their differences and the hysteresis in the surface UHI. The hysteresis-like seasonality is largely absent in both the observed and modeled 2-m air temperatures, however. A sensitivity simulation of the UHI intensity to incoming solar radiation suggests that the hysteresis of the LST can mainly be attributed to the seasonal variation in incoming solar radiation.
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.
Urban climate is determined by a variety of factors, whose knowledge can help to attenuate heat stress in the context of ongoing urbanization and climate change. We study the influence of city size and urban form on the Urban Heat Island (UHI) phenomenon in Europe and find a complex interplay between UHI intensity and city size, fractality, and anisometry. Due to correlations among these urban factors, interactions in the multi-linear regression need to be taken into account. We find that among the largest 5,000 cities, the UHI intensity increases with the logarithm of the city size and with the fractal dimension, but decreases with the logarithm of the anisometry. Typically, the size has the strongest influence, followed by the compactness, and the smallest is the influence of the degree to which the cities stretch. Accordingly, from the point of view of UHI alleviation, small, disperse, and stretched cities are preferable. However, such recommendations need to be balanced against e.g. positive agglomeration effects of large cities. Therefore, trade-offs must be made regarding local and global aims.
The Indus Molasse records orogenic sedimentation associated with uplift and erosion of the southern margin of Asia in the course of ongoing India-Eurasia collision. Detailed field investigation clarifies the nature and extent of the depositional contact between this molasse and the underlying basement units. We report the first dataset on detrital zircon U-Pb ages, Hf isotopes and apatite U-Pb ages for the autochthonous molasse in the Indus Suture Zone. A latest Oligocene depositional age is proposed on the basis of the youngest detrital zircon U-Pb age peak and is consistent with published biostratigraphic data. Multiple provenance indicators suggest exclusively northerly derivation with no input from India in the lowermost parts of the section. The results provide constraints on the uplift and erosion history of the Ladakh Range following the initial India-Asia collision.
The Puna Plateau, adjacent Eastern Cordillera and the Sierras Pampeanas of the central Andes are largely characterized by thick-skinned, basement-involved deformation. The Puna Plateau hosts similar to N-S trending bedrock ranges bounded by deep-seated reverse faults and sedimentary basins. We contribute to the understanding of thick-skinned dynamics in the Puna Plateau by constraining regional kinematics of the poorly understood southern Puna Plateau through a multidisciplinary approach. On the southeastern plateau, sandstone modal composition and detrital zircon U-Pb and apatite fission-track data from Cenozoic strata indicate basin accumulation during the late Eocene to early Oligocene (similar to 38-28 Ma). Provenance analysis reveals the existence of a regional-scale basin covering the southern Puna Plateau during late Eocene to early Oligocene time (similar to 38-28 Ma) that was sourced from both the western plateau and the eastern plateau margin and had a depocenter located to the west. Petrographic and detrital zircon U-Pb data reveal erosion of proximal western and eastern sources after 12 Ma, in mid-late Miocene time. This indicates that the regional basin was compartmentalized into small-scale depocenters by the growth of basement-cored ranges continuing into the late Miocene (similar to 12-8 Ma). We suggest that the Cenozoic history of the southern Puna Plateau records the formation of a regional basin that was possibly driven by lithospheric flexure during the late Eocene to early Oligocene, before the growth of distributed basement-cored ranges starting as early as the late Oligocene. (C) 2015 Elsevier B.V. All rights reserved.