4 results
Search Results
Now showing 1 - 4 of 4
- ItemComparing two years of Saharan dust source activation obtained by regional modelling and satellite observations(München : European Geopyhsical Union, 2013) Tegen, I.; Schepanski, K.; Heinold, B.A regional-scale dust model is used to simulate Saharan dust emissions and atmospheric distributions in the years 2007 and 2008. The model results are compared to dust source activation events compiled from infrared dust index imagery from the geostationary Meteosat Second Generation (MSG) satellite. The observed morning maximum in dust source activation frequencies indicates that the breakdown of nocturnal low level jets is an important mechanism for dust source activation in the Sahara. The comparison shows that the time of the day of the onset of dust emission is delayed in the model compared to the observations. Also, the simulated number of dust emission events associated with nocturnal low level jets in mountainous regions is underestimated in the model. The MSG dust index observations indicate a strong increase in dust source activation frequencies in the year 2008 compared to 2007. The difference between the two years is less pronounced in the model. Observations of dust optical thickness, e.g. at stations of the sunphotometer network AERONET, do not show such increase, in agreement with the model results. This indicates that the number of observed dust activation events is only of limited use for estimating actual dust emission fluxes in the Sahara. The ability to reproduce interannual variability of Saharan dust with models remains an important challenge for understanding the controls of the atmospheric dust load.
- ItemViticulture in the Laetanian Region (Spain) during the Roman Period: Predictive Modelling and Geomatic Analysis(Basel : MDPI AG, 2020) Stubert, Lisa; Oliveras, Antoni Martín i; Märker, Michael; Schernthanner, Harald; Vogel, SebastianGeographic information system (GIS)-based predictive modelling is widely used in archaeology to identify suitable zones for ancient settlement locations and determine underlying factors of their distribution. In this study, we developed predictive models on Roman viticulture in the Laetanian Region (Hispania Citerior-Tarraconensis), using the location of 82 ancient wine-pressing facilities or torcularia as response variables and 15 topographical and 6 socio-economic cost distance datasets as predictor variables. Several predictor variable subsets were selected either by expert knowledge of similar studies or by using a semi-automatization algorithm based on statistical distribution metrics of the input data. The latter aims at simplifying modelling and minimizing the necessity of a priori knowledge. Both approaches predicted the distribution of archeological sites sufficiently well. However, the best prediction performance was obtained by an expert knowledge model utilizing a predictor variable combination based on recommendations on viticulture by Lucius Junius Moderatus Columella, the prominent ancient Roman agronomist. The results indicate that the accessibility of a location and its connectivity to trade routes and distribution centres, determined by terrain steepness, was decisive for the settlement of viticultural facilities. With the knowledge gained, the ancient cultivated area and number of wine-pressing facilities needed for processing the vineyard yields were extrapolated for the entire study region.
- ItemExploring the sensitivity of Northern Hemisphere atmospheric circulation to different surface temperature forcing using a statistical-dynamical atmospheric model(Göttingen : Copernicus GmbH, 2019) Totz, S.; Petri, S.; Lehmann, J.; Peukert, E.; Coumou, D.Climate and weather conditions in the mid-latitudes are strongly driven by the large-scale atmosphere circulation. Observational data indicate that important components of the large-scale circulation have changed in recent decades, including the strength and the width of the Hadley cell, jets, storm tracks and planetary waves. Here, we use a new statistical-dynamical atmosphere model (SDAM) to test the individual sensitivities of the large-scale atmospheric circulation to changes in the zonal temperature gradient, meridional temperature gradient and global-mean temperature. We analyze the Northern Hemisphere Hadley circulation, jet streams, storm tracks and planetary waves by systematically altering the zonal temperature asymmetry, the meridional temperature gradient and the global-mean temperature. Our results show that the strength of the Hadley cell, storm tracks and jet streams depend, in terms of relative changes, almost linearly on both the global-mean temperature and the meridional temperature gradient, whereas the zonal temperature asymmetry has little or no influence. The magnitude of planetary waves is affected by all three temperature components, as expected from theoretical dynamical considerations. The width of the Hadley cell behaves nonlinearly with respect to all three temperature components in the SDAM. Moreover, some of these observed large-scale atmospheric changes are expected from dynamical equations and are therefore an important part of model validation.
- ItemRegression kriging for improving crop height models fusing ultra-sonic sensing with UAV imagery(Basel : MDPI, 2017) Schirrmann, Michael; Hamdorf, André; Giebel, Antje; Gleiniger, Franziska; Pflanz, Michael; Dammer, Karl-HeinzA crop height model (CHM) can be an important element of the decision making process in agriculture, because it relates well with many agronomic parameters, e.g., crop height, plant biomass or crop yield. Today, CHMs can be inexpensively obtained from overlapping imagery captured from unmanned aerial vehicle (UAV) platforms or from proximal sensors attached to ground-based vehicles used for regular management. Both approaches have their limitations and combining them with a data fusion may overcome some of these limitations. Therefore, the objective of this study was to investigate if regression kriging, as a geostatistical data fusion approach, can be used to improve the interpolation of ground-based ultrasonic measurements with UAV imagery as covariate. Regression kriging might be suitable because we have a sparse data set (ultrasound) and an exhaustive data set (UAV) and both data sets have favorable properties for geostatistical analysis. To confirm this, we conducted four missions in two different fields in total, where we collected UAV imagery and ultrasonic data alongside. From the overlapping UAV images, surface models and ortho-images were generated with photogrammetric processing. The maps generated by regression kriging were of much higher detail than the smooth maps generated by ordinary kriging, because regression kriging ensures that for each prediction point information from the UAV, imagery is given. The relationship with crop height, fresh biomass and, to a lesser extent, with crop yield, was stronger using CHMs generated by regression kriging than by ordinary kriging. The use of UAV data from the prior mission was also of benefit and could improve map accuracy and quality. Thus, regression kriging is a flexible approach for the integration of UAV imagery with ground-based sensor data, with benefits for precision agriculture-oriented farmers and agricultural service providers.