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Zscheischler J.,Max Planck Institute for Biogeochemistry | Zscheischler J.,Max Planck Institute for Intelligent Systems (Tubingen) | Zscheischler J.,ETH Zurich | Reichstein M.,Max Planck Institute for Biogeochemistry | And 5 more authors.
Biogeosciences | Year: 2014

Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented and in the focus of this paper. Specifically, we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive extremes (i.e., statistically unusual increases in carbon uptake rates) and negative extremes (i.e., statistically unusual decreases in carbon uptake rates) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power-law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role for the overall impact of GPP extremes compared to the durations or maximal GPP. An analysis of possible causes across continents indicates that most negative extremes in GPP can be attributed clearly to water scarcity, whereas extreme temperatures play a secondary role. However, for Europe, South America and Oceania we also identify fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent. © Author(s) 2013. Source

Notarnicola C.,Institute for Applied Remote Sensing
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2012

A new change detection algorithm based on a Bayesian approach is developed and tested. The main objective of this approach is to exploit the changes in backscattering signals and relate them to soil moisture variations over agricultural fields under the hypothesis of both constant and variable roughness. The proposed methodology overcomes the limitations of the some change detection methods because it takes into account also possible changes in the radar signal due to roughness variability. The method is trained and tested on two data sets considering both C and L-band backscattering coefficients in relation to soil moisture and roughness measurements. The C-band dataset was acquired over bare soils while the L-band data set was acquired on vegetated fields and was exploited to understand the impact of vegetation in such approach. The results indicate that the approach is able to detect soil moisture changes both for C-and L-band data. In case of L band data, the presence of vegetation seems to determine backscattering dynamics reduction with respect to soil moisture changes. © 2012 IEEE. Source

Mastrogiuseppe M.,University of Rome La Sapienza | Poggiali V.,University of Rome La Sapienza | Hayes A.,Cornell University | Lorenz R.,Johns Hopkins University | And 8 more authors.
Geophysical Research Letters | Year: 2014

We construct the depth profile - the bathymetry - of Titan's large sea Ligeia Mare from Cassini RADAR data collected during the 23 May 2013 (T91) nadir-looking altimetry flyby. We find the greatest depth to be about 160 m and a seabed slope that is gentler toward the northern shore, consistent with previously imaged shoreline morphologies. Low radio signal attenuation through the sea demonstrates that the liquid, for which we determine a loss tangent of 3 ± 1·10-5, is remarkably transparent, requiring a nearly pure methane-ethane composition, and further that microwave absorbing hydrocarbons, nitriles, and suspended particles be limited to less than the order of 0.1% of the liquid volume. Presence of nitrogen in the ethane-methane sea, expected based on its solubility and dominance in the atmosphere, is consistent with the low attenuation, but that of substantial dissolved polar species or suspended scatterers is not. Key Points First direct measurement of the depth of a Titan sea First determination of the nearly pure methane-ethane Ligeia Mare composition Determination of the total volume of Ligeia Mare ©2014. American Geophysical Union. All Rights Reserved. Source

Beer C.,Max Planck Institute for Biogeochemistry | Beer C.,University of Stockholm | Weber U.,Max Planck Institute for Biogeochemistry | Tomelleri E.,Max Planck Institute for Biogeochemistry | And 4 more authors.
Journal of Climate | Year: 2014

Temporal variability of meteorological variables and extreme weather events is projected to increase in many regions of the world during the next century. Artificial experiments using process-oriented terrestrial ecosystem models make it possible to isolate effects of temporal variability from effects of gradual climate change on terrestrial ecosystem functions and the system state. Such factorial experiments require two longterm climate datasets: 1) a control dataset that represents observed and projected climate and 2) a dataset with the same long-term mean as the control dataset but with altered short-term variability. Using a bias correction method, various climate datasets spanning different periods are harmonized and then combined with the control dataset with consistent time series for Europe during 1901-2100. Then, parameters of a distribution transformation function are estimated for individual meteorological variables to derive the second climate dataset, which has similar long-term means but reduced temporal variability. The transformation conserves the number of rainy days within a month and the shape of the daily meteorological data distributions, which is important to ensure that, for example, drought duration does not modify the suitability of localized vegetation type to precipitation regimes. The median absolute difference between daily data of both datasets is 5% to 20%. On average, decadal extreme values are reduced by 2% to 35%. Driving a terrestrial ecosystem model with both climate datasets shows a general higher gross primary production under reduced temporal climate variability. This effect of climate variability on productivity demonstrates the potential of the climate datasets for studying various effects of temporal variability on ecosystem state and functions over large domains. © 2014 American Meteorological Society. Source

Bell R.,University of Vienna | Petschko H.,University of Vienna | Rohrs M.,Institute for Applied Remote Sensing | Dix A.,University of Bamberg
Geografiska Annaler, Series A: Physical Geography | Year: 2012

Landslides occur worldwide and contribute significantly to sediment budgets as well as to landform evolution. Furthermore, they pose hazards and risks to people and their goods. To assess the role of landslides, information on their age or persistence (i.e. the length of time the morphological characteristics of a landslide remain recognizable in the terrain) is essential. In this study, the potential of airborne laser scanning digital terrain models (ALS DTMs) is analysed for estimating landslide age, landslide persistence and human impact. Therefore, landslides in two study areas, Swabian Alb in Germany and Lower Austria in Austria, are mapped from hillshades of ALS DTMs and combined with historical information on landslide occurrence. It is tested whether the modification of the geomorphological features of landslides can be used to assess landslide age. In the Swabian Alb older landslides might show fresher features than younger ones because of different degrees of human impact, natural erosion and different histories of landslide reactivation. Estimated persistence times range between 27 and 320 years but are minimum values only. In Lower Austria four landslides show estimated minimum persistence times between 4 and 28 years. In Lower Austria 27 landslides disappeared in less than 7 years after occurrence mainly because of planation by farmers. The results show no clear trend in landslide persistence, neither regarding landslide magnitude, nor regarding land use. However, it is evident that human impact plays a major role in landslide persistence. © 2012 The authors. Geografiska Annaler: Series A, Physical Geography © 2012 Swedish Society for Anthropology and Geography. Source

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