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A new global crop water model was developed to compute blue (irrigation) water requirements and crop evapotranspiration from green (precipitation) water at a spatial resolution of 5 arc minutes by 5 arc minutes for 26 different crop classes. The model is based on soil water balances performed for each crop and each grid cell. For the first time a new global data set was applied consisting of monthly growing areas of irrigated crops and related cropping calendars. Crop water use was computed for irrigated land and the period 1998 – 2002. In this documentation report the data sets used as model input and methods used in the model calculations are described, followed by a presentation of the first results for blue and green water use at the global scale, for countries and specific crops. Additionally the simulated seasonal distribution of water use on irrigated land is presented. The computed model results are compared to census based statistical information on irrigation water use and to results of another crop water model developed at FAO.
A data set of monthly growing areas of 26 irrigated crops (MGAG-I) and related crop calendars (CC-I) was compiled for 402 spatial entities. The selection of the crops consisted of all major food crops including regionally important ones (wheat, rice, maize, barley, rye, millet, sorghum, soybeans, sunflower, potatoes, cassava, sugar cane, sugar beets, oil palm, rapeseed/canola, groundnuts/peanuts, pulses, citrus, date palm, grapes/vine, cocoa, coffee), major water-consuming crops (cotton), and unspecified other crops (other perennial crops, other annual crops, managed grassland). The data set refers to the time period 1998-2002 and has a spatial resolution of 5 arc minutes by 5 arc minutes which is 8 km by 8 km at the equator. This is the first time that a data set of cell-specific irrigated growing areas of irrigated crops with this spatial resolution was created. The data set is consistent to the irrigated area and water use statistics of the AQUASTAT programme of the Food and Agriculture Organization of the United Nations (FAO) (http://www.fao.org/ag/agl/aglw/aquastat/main/index.stm) and the Global Map of Irrigation Areas (GMIA) (http://www.fao.org/ag/agl/aglw/aquastat/irrigationmap/index.stm). At the cell-level it was tried to maximise consistency to the cropland extent and cropland harvested area from the Department of Geography and Earth System Science Program of the McGill University at Montreal, Quebec, Canada and the Center for Sustainability and the Global Environment (SAGE) of the University of Wisconsin at Madison, USA (http://www.geog.mcgill.ca/~nramankutty/ Datasets/Datasets.html and http://geomatics.geog.mcgill.ca/~navin/pub/Data/175crops2000/). The consistency between the grid product and the input data was quantified. MGAG-I and CC-I are fully consistent to each other on entity level. For input data other than CC-I, the consistency of MGAG-I on cell level was calculated. The consistency of MGAG-I with respect to the area equipped for irrigation (AEI) of GMIA and to the cropland extent of SAGE was characterised by the sum of the cell-specific maximum difference between the MGAG-I monthly total irrigated area and the reference area when the latter was exceeded in the grid cell. The consistency of the harvested area contained in MGAG-I with respect to SAGE harvested area was characterised by the crop-specific sum of the cell-specific difference between MGAG-I harvested area and the SAGE harvested area when the latter was exceeded in the grid cell. In all three cases, the sums are the excess areas that should not have been distributed under the assumption that the input data were correct. Globally, this cell-level excess of MGAG-I as compared to AEI is 331,304 ha or only about 0.12 % of the global AEI of 278.9 Mha found in the original grid. The respective cell-level excess of MGAG-I as compared to the SAGE cropland extent is 32.2 Mha, corresponding to about 2.2 % of the total cropland area. The respective cell-level excess of MGAG-I as compared to the SAGE harvested area is 27 % of the irrigated harvested area, or 11.5 % of the AEI. In a further step that will be published later also rainfed areas were compiled in order to form the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000). The data set can be used for global and continental-scale studies on food security and water use. In the future, it will be improved, e.g. with a better spatial resolution of crop calendars and an improved crop distribution algorithm. The MIRCA2000 data set, its full documentation together with future updates will be freely available through the following long-term internet site: http://www.geo.uni-frankfurt.de/ipg/ag/dl/forschung/MIRCA/index.html. The research presented here was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) within the framework of the research project entitled "Consistent assessment of global green, blue and virtual water fluxes in the context of food production: regional stresses and worldwide teleconnections". The authors thank Navin Ramankutty and Chad Monfreda for making available the current SAGE datasets on cropland extent (Ramankutty et al., 2008) and harvested area (Monfreda et al., 2008) prior to their publication.
Long-term average groundwater recharge, which is equivalent to renewable groundwater resources, is the major limiting factor for the sustainable use of groundwater. Compared to surface water resources, groundwater resources are more protected from pollution, and their use is less restricted by seasonal and inter-annual flow variations. To support water management in a globalized world, it is necessary to estimate groundwater recharge at the global scale. Here, we present a best estimate of global-scale long-term average diffuse groundwater recharge (i.e. renewable groundwater resources) that has been calculated by the most recent version of the WaterGAP Global Hydrology Model WGHM (spatial resolution of 0.5° by 0.5°, daily time steps). The estimate was obtained using two state-of-the art global data sets of gridded observed precipitation that we corrected for measurement errors, which also allowed to quantify the uncertainty due to these equally uncertain data sets. The standard WGHM groundwater recharge algorithm was modified for semi-arid and arid regions, based on 15 independent estimates of diffuse groundwater recharge, which lead to an unbiased estimation of groundwater recharge in these regions. WGHM was tuned against observed long-term average river discharge at 1235 gauging stations by adjusting, individually for each basin, the partitioning of precipitation into evapotranspiration and total runoff. We estimate that global groundwater recharge was 12 666 km3/yr for the climate nor20 mal 1961–1990, i.e. 32% of total renewable water resources. In semi-arid and arid regions, mountainous regions, permafrost regions and in the Asian Monsoon region, groundwater recharge accounts for a lower fraction of total runoff, which makes these regions particularly vulnerable to seasonal and inter-annual precipitation variability and water pollution. Average per-capita renewable groundwater resources of countries vary 25 between 8m3/(capita yr) for Egypt to more than 1 million m3/(capita yr) for the Falkland Islands, the global average in the year 2000 being 2091m3/(capita yr). Regarding the uncertainty of estimated groundwater resources due to the two precipitation data sets, deviation from the mean is less than 1% for 50 out of the 165 countries considered, between 1 and 5% for 62, between 5 and 20% for 43 and between 20 and 80% for 10 countries. Deviations at the grid scale can be much larger, ranging between 0 and 186 mm/yr.
his paper investigates the value of observed river discharge data for global-scale hydrological modeling of a number of flow characteristics that are required for assessing water resources, flood risk and habitat alteration of aqueous ecosystems. An improved version of WGHM (WaterGAP Global Hydrology Model) was tuned in a way that simulated and observed long-term average river discharges at each station become equal, using either the 724-station dataset (V1) against which former model versions were tuned or a new dataset (V2) of 1235 stations and often longer time series. WGHM is tuned by adjusting one model parameter (γ) that affects runoff generation from land areas, and, where necessary, by applying one or two correction factors, which correct the total runoff in a sub-basin (areal correction factor) or the discharge at the station (station correction factor). The study results are as follows. (1) Comparing V2 to V1, the global land area covered by tuning basins increases by 5%, while the area where the model can be tuned by only adjusting γ increases by 8% (546 vs. 384 stations). However, the area where a station correction factor (and not only an areal correction factor) has to be applied more than doubles (389 vs. 93 basins), which is a strong drawback as use of a station correction factor makes discharge discontinuous at the gauge and inconsistent with runoff in the basin. (2) The value of additional discharge information for representing the spatial distribution of long-term average discharge (and thus renewable water resources) with WGHM is high, particularly for river basins outside of the V1 tuning area and for basins where the average sub-basin area has decreased by at least 50% in V2 as compared to V1. For these basins, simulated long-term average discharge would differ from the observed one by a factor of, on average, 1.8 and 1.3, respectively, if the additional discharge information were not used for tuning. The value tends to be higher in semi-arid and snow-dominated regions where hydrological models are less reliable than in humid areas. The deviation of the other simulated flow characteristics (e.g. low flow, inter-annual variability and seasonality) from the observed values also decreases significantly, but this is mainly due to the better representation of average discharge but not of variability. (3) The optimal sub-basin size for tuning depends on the modeling purpose. On the one hand, small basins between 9000 and 20 000 km2 show a much stronger improvement in model performance due to tuning than the larger basins, which is related to the lower model performance (with and without tuning), with basins over 60 000 km2 performing best. On the other hand, tuning of small basins decreases model consistency, as almost half of them require a station correction factor.
The report that follows gives the results of tests to deterrnine the compressive strength of artificial roof supports of various kinds used in the mining of anthracite in Pennsylvania. Some of the types tested also are used in bituminous coal mining in Pennsylvania and other parts of the United States. The report was rendered Bebruary 26, 1913, by the United States Bureau of Mines, then in the Interior Department, to the Pennsylvania State Anthracite Mine Cave Commission and was appended, without discussion, to the general report on mine caving made by that commission under date of March 1, 19 13, to the Governor and Legislature of Pennsylvanin. The commission's reporh remains unpublished. As numerous requests have been made for the test data obtained by the Bureau of Mines at its Pittsburgh Experiment Station in 1912-13 and as the data relate to the strength of artificial supports without reference to particular local places of application, they have permanent value in the designing of mine roof supports. It has therefore been deemed advisable to publish the results of the bureau's tests. In order that the reader may understand the reasons for makig these tests of roof supports and the procedure foIIowed by the Pennsylvania commission, its duties will be briefly described. The commission was created by an act of the Legislature of Pennsylvania, approved March 24, 1911, its members being appointed by the Governor of Pennsylvania under the terms of the act. There had been serious cave-ins of the surface in some of the cities and towns in the anthracite districts of Pennsylvania and particularly in the city of Scranton froin 1909 to 1911, destroying surface buildings, public and private, and seriously endangering life. ....
Im Rahmen des Projektes SPURT (Spurenstofftransport in der Tropopausenregion) als Teil des deutschen Atmosphärenforschungsprogramms AFO 2000 wurden bei 8 Messkampagnen mit insgesamt 36 Flügen innerhalb eines Beobachtungszeitraums von zwei Jahren (Nov. 2001 bis Juli 2003) Spurengasmessungen in dem Breitenbereich zwischen 35°N und 75°N durchgeführt. Für die Messungen der Spurengase N2O, F12, SF6, H2 und CO wurde der vollautomatisierte in-situ GC (Gaschromatograph) GhOST II (Gas Chromatograph for the Observation of Stratospheric Tracers) entwickelt und eingesetzt. Das Ziel dieser Messungen war die Untersuchung der jahreszeitlichen Variabilität der Spurengase in der oberen Troposphäre und untersten Stratosphäre (UT/LMS: Upper Troposphere/Lowermost Stratosphere), um die Transport- und Austauschprozesse in der Tropopausenregion besser zu verstehen. Zur Untersuchung von Transport und Mischung in der UT/LMS wurden die Rückwärtstrajektorien entlang der Flugpfade, die Verteilungen der Tracer N2O, F12, SF6, CO und CO2 (MPI für Chemie in Mainz), die Tracer/Tracer-Korrelationen N2O/F12, N2O/O3 F12/O3 und SF6/O3 und die Verteilungen des aus SF6-Messungen berechnete mittlere Alters der Luft herangezogen. Zusätzlich wurden die simultanen Messungen der beiden Alterstracer CO2 und SF6 genutzt, um die Propagation der Amplitude des troposphärischen CO2-Jahresgangs in die LMS zu bestimmen und daraus mit Hilfe eines empirischen Altersspektrums den Eintrag und die mittlere Transportzeit aus der Troposphäre in die unterste Stratosphäre zu quantifizieren. Grundsätzlich muss die LMS in zwei Bereiche eingeteilt werden – die Übergangsschicht („tropopause following layer“) bis etwa 20-30 K über der potentiellen Temperatur der lokalen Tropopause [Hoor et al., 2004] und die freie LMS oberhalb dieser Schicht. Als wesentliche Unterscheidungsmerkmale beider Bereiche wird die mittlere Transportzeit des Eintrags troposphärischer Luft identifiziert. Aus Trajektorienuntersuchungen und Tracerverteilungen (Kap. 3.4) kann gezeigt werden, dass der Transport in die Übergangsschicht und die Mischungsprozesse in diesem Bereich auf der Zeitskala der mesoskaligen troposphärischen Prozesse ablaufen. Im Gegensatz dazu werden aus der Massenbilanz (Kap. 5.3) mittlere Transportzeiten aus der Troposphäre in die freie LMS von einigen Wochen bis zu mehreren Monaten abgeleitet. Außerdem konnte nachgewiesen werden, dass der troposphärische Eintrag in der freien LMS fast ausschließlich auf quasihorizontale isentrope Einmischung aus den Tropen über die Transportbarriere des Subtropenjets zurückzuführen ist. Nur im Sommer und Herbst konnte auch oberhalb der Übergangsschicht für einzelne Messungen ein Einfluss aus der extratropischen Troposphäre beobachtet werden. Die in dieser Arbeit untersuchten Tracerverteilungen und -korrelationen (Kap. 4) und die Verteilung des mittleren Alters (Kap.5.2) in der LMS zeigen einen Jahresgang mit einem maximalen troposphärischen Einfluss im Oktober und einem maximalen stratosphärischen Einfluss im April. Diese saisonale Charakteristik in der freien LMS kann durch die saisonalen Änderungen des Verhältnisses von Abwärtstransport aus der Overworld und quasihorizontalem Transport aus den Tropen und durch die mit den jeweiligen Transportprozessen assoziierte mittlere Transportzeiten erklärt werden, die aus Massenbilanzrechnungen bestimmt wurden. Es wird gezeigt, dass der überwiegende Eintrag von troposphärischer Luft in die LMS im Sommer und Herbst stattfindet, wobei im Mittel die kürzesten mittleren Transitzeiten (unter 0.3 Jahre) für den August und die längsten Transitzeiten (über 0.6 Jahre) für den Mai berechnet werden. Aus den Ergebnissen wird gefolgert, dass ein ausgeprägter isentroper Austauschprozess über den Subtropenjet im Sommer bis in den Herbst hinein der dominierende troposphärische Einfluss in der LMS bis in den Mai ist. Der Vergleich zwischen SPURT und anderen in der UT/LMS im Zeitraum von 1992 bis 1998 durchgeführten Messkampagnen zeigt einen systematischen Unterschied in den N2O/O3-Korrelationen. Die Zunahme von O3 relativ zu N2O in der LMS ist um etwa 6.5 ppb O3 pro 1 ppb N2O bzw. etwa 40% größer als die Zunahme bei jahreszeitlich vergleichbaren früheren Kampagnen. Durch eine weitergehende Analyse der Messungen, z.B. durch den Vergleich der N2O-Verteilungen in der LMS bei verschiedenen Messkampagnen, und zusätzlichen Informationen aus Satelliten- und Ballonmessungen wird abgeleitet, dass diese Änderung der N2O/O3-Korrelationen im Wesentlichen auf einen im Zeitraum von SPURT stärkeren quasihorizontalen Transport aus den Tropen in die Extratropen im Bereich des so genannten „tropical controlled transition layer“ [Rosenlof et al., 1997] zwischen 16-21 km (bzw. Θ ≈ 380-450 K) zurückzuführen ist. In Kooperation mit B. Bregman wurden mit dem Chemie-Transport-Modell TM5 des KNMI die Verteilungen von SF6 und CO2 in der Troposphäre und Stratosphäre, unter den Zielsetzungen Evaluation des Modelltransports und Erweiterung des Datensatzes von SPURT auf globalen Maßstab, für den Zeitraum 1.1.2000 bis 31.12.2002 modelliert. Dabei konnte gezeigt werden, dass bei Modellstudien zur Evaluation des Transports mit Hilfe von Alterstracern nicht nur troposphärisch monoton steigende Tracer wie SF6 sondern auch saisonal variable Tracer wie CO2 verwendet werden müssen. Bei dem Vergleich der Modellergebnisse des TM5 mit ER2- und SPURTMessungen zeigt sich, dass das Modell zum jetzigen Zeitpunkt in der Lage ist, das mittlere Alter in der unteren Stratosphäre und die SF6- und CO2-Verteilungen in der LMS qualitativ richtig wiederzugeben. Das mittlere Alter in der unteren Stratosphäre wird um etwa 0.5 bis 1 Jahr in den Tropen über- und in den Extratropen unterschätzt. Die vertikalen Gradienten im Modell für SF6 und CO2 in der LMS sind, insbesondere im Winter und Frühjahr, zu gering. Die Amplitude des CO2-Jahresganges in der oberen Troposphäre und in der LMS wird durch das Modell unterschätzt, während der saisonale Verlauf des Jahresganges richtig wiedergegeben wird. Im Moment wird vermutet, dass eine zu starke isentrope Mischung zwischen Tropen und Extratropen und/oder ein zu geringer Aufwärtstransport in der extratropischen Troposphäre im Sommer und Herbst die Ursachen für die beobachteten Abweichungen zwischen Modell und Messung sind.
The thesis is devoted to the study of the Antarctic polar vortex, mainly by analyzing data collected during APE-GAIA (1999) and ASHOE (1994) campaigns and recorded by the ADEOS satellite (1996-1997), and to improvement of the chromato-graphic processing schemes. A general introduction and overview of the campaigns and instruments relevant to the present work are given in Chapters 1 and 2. A relatively large part of the thesis (Chapters 3-5) is on improvement of the analysis of raw chromatographic data recorded during in-flight measurements of the trace gases. A Gaussian non-straight-base-line method, i.e. the Gaussian processing scheme (Chapter 3), is developed for better evaluation of the chromatographic peak size. Furthermore, a statistical cross-correlation method (Chapter 5) based on statistical behaviour of the whole chromatogram series fNchrg recorded, e.g., during a research flight or laboratory calibration, is developed and applied to measure the low-concentration trace gases. As demonstrated for HAGAR's chromatograms (HAGAR - High Altitude Gas Analyzer), the combination of the Gaussian fitting scheme for individual chromatograms and the statistical cross-correlation method for a series of subsequent chromatograms considerably improves and stabilizes quantitative analysis of in-flight chromatographic data. In this case, the detection accuracy of weak and noisy chromatographic signals can be improved by up to 40 %. A particular attention is paid to the in-flight two-standard calibration method. For this method, a special procedure, that allows to evaluate and effectively remove a weak background chromatographic signal associated with residual molecules in the carrier gas N2, is proposed and coded (Chapter 4). The developed approaches and methods are completely automized and, therefore, can be used for processing of in-flight chromatograms of recent and future field campaigns. The main part of the thesis (Chapters 6-8) deals with a two-dimensional quasi-Lagrangian coordinate system ... , based on a long-lived stratospheric trace gas i, and its systematic use for i = N2O in order to describe the structure of a well-developed Antarctic polar vortex, linearization and compactization of the tracer-tracer correlations in the polar vortex core (i.e. the stratospheric dynamics in this area), and the differential ozone losses in the Antarctic polar vortex area. In the coordinate system ... (...-method, Chapter 6), which refers to a well-developed polar vortex, the mixing ratio Âi is the vertical coordinate and ... = .... i is the reference profile in the vortex core) is the meridional coordinate. The quasi-Lagrangian coordinates ... are much more long-lived comparing with the standard quasi-isentropic coordinates, potential temperature ... and equivalent latitude ..e, do not require explicit reference to geographic space, and therefore well-suited for studying the dynamics of the Antarctic polar vortex and the relevant ozone loss processes. By using the introduced coordinate system ... to analyze the well-developed Antarctic vortex investigated in the APE-GAIA campaign, it is shown, in concurrence with the conclusion of A. M. Lee et al. (2001), that the Antarctic vortex area can be described in terms of the well-mixed and well-isolated vortex core, relatively wide vortex boundary region and adjoining surf zone. In this case, the reference profile ... i , which is compact in a well-developed and isolated polar vortex core [J. B. Greenblatt et al. (2002)], can be found by combining airborne (and/or balloon) data with high-altitude satellite measurements. A criterion, which uses the local in-situ measurements of Âi = Âi(£) and attributes the inner vortex edge to a rapid change (±-step) in the meridional pro¯le of the mixing ratio..., is developed in Chapter 6 to determine the (Antarctic) inner vortex edge. In turn, the outer vortex edge of a well-developed Antarctic vortex is proposed to attribute to the position of a local maximum of ...H2O in the polar vortex area. For a well-developed Antarctic vortex, the ...-parametrization of tracer-tracer correlations allows to distinguish the tracer-tracer inter-relationships in the vortex core, vortex boundary region and surf zone (Chapter 7). This is clearly illustrated by analyzing the tracer-tracer relationships Âi ¡ ÂN2O obtained from the in-situ data of the APE-GAIA campaign for i = CFCl3 (CFC-11), CF2Cl2 (CFC-12), CBrClF2 (H-1211) and SF6. The solitary anomalous points in the ...CFC11 ¡ ÂN2O correlation, observed in the Antarctic vortex core during the APE-GAIA and ASHOE campaigns, are interpreted in terms of small-scale localized differential descent. As detailed in Chapter 8, the quasi-Lagrangian coordinate system fÂN2O; ¢ÂN2Og is an effective tool for evaluation of the differential ozone losses in the polar vortex area. With this purpose, a two-parametric reference function ...O3 = F(...), which characterizes the unperturbed O3 distribution in the early winter polar vortex area, is introduced to separate and quantify in terms of the meridional coordinate ...2O the differential ozone losses in the vortex core and vortex boundary region. The method is applied to analyze the ozone depletion in the Antarctic stratosphere during the austral spring 1999 (APE-GAIA campaign). In Chapter 9, the main results of the thesis are summarized.
[Nachruf auf] Carlos Ribeiro
(1883)
L'Astrolabe a Vanikoro
(1829)