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During SPURT (Spurenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region) we performed measurements of a wide range of trace gases with different lifetimes and sink/source characteristics in the northern hemispheric upper troposphere (UT) and lowermost stratosphere (LMS). A large number of in-situ instruments were deployed on board a Learjet 35A, flying at altitudes up to 13.7 km, at times reaching to nearly 380 K potential temperature. Eight measurement campaigns (consisting of a total of 36 flights), distributed over all seasons and typically covering latitudes between 35° N and 75° N in the European longitude sector (10° W–20° E), were performed. Here we present an overview of the project, describing the instrumentation, the encountered meteorological situations during the campaigns and the data set available from SPURT. Measurements were obtained for N2O, CH4, CO, CO2, CFC12, H2, SF6, NO, NOy, O3 and H2O. We illustrate the strength of this new data set by showing mean distributions of the mixing ratios of selected trace gases, using a potential temperature – equivalent latitude coordinate system. The observations reveal that the LMS is most stratospheric in character during spring, with the highest mixing ratios of O3 and NOy and the lowest mixing ratios of N2O and SF6. The lowest mixing ratios of NOy and O3 are observed during autumn, together with the highest mixing ratios of N2O and SF6 indicating a strong tropospheric influence. For H2O, however, the maximum concentrations in the LMS are found during summer, suggesting unique (temperature- and convection-controlled) conditions for this molecule during transport across the tropopause. The SPURT data set is presently the most accurate and complete data set for many trace species in the LMS, and its main value is the simultaneous measurement of a suite of trace gases having different lifetimes and physical-chemical histories. It is thus very well suited for studies of atmospheric transport, for model validation, and for investigations of seasonal changes in the UT/LMS, as demonstrated in accompanying and elsewhere published studies.
During several balloon flights inside the Arctic polar vortex in early 2003, unusual trace gas distributions were observed, which indicate a strong influence of mesospheric air in the stratosphere. The tuneable diode laser (TDL) instrument SPIRALE (Spectroscopie InFrarouge par Absorption de Lasers Embarqués) measured unusually high CO values (up to 600 ppb) on 27 January at about 30 km altitude. The cryosampler BONBON sampled air masses with very high molecular Hydrogen, extremely low SF6 and enhanced CO values on 6 March at about 25 km altitude. Finally, the MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) Fourier Transform Infra-Red (FTIR) spectrometer showed NOy values which are significantly higher than NOy* (the NOy derived from a correlation between N2O and NOy under undisturbed conditions), on 21 and 22 March in a layer centred at 22 km altitude. Thus, the mesospheric air seems to have been present in a layer descending from about 30 km in late January to 25 km altitude in early March and about 22 km altitude on 20 March. We present corroborating evidence from a model study using the KASIMA (KArlsruhe Simulation model of the Middle Atmosphere) model that also shows a layer of mesospheric air, which descended into the stratosphere in November and early December 2002, before the minor warming which occurred in late December 2002 lead to a descent of upper stratospheric air, cutting of a layer in which mesospheric air is present. This layer then descended inside the vortex over the course of the winter. The same feature is found in trajectory calculations, based on a large number of trajectories started in the vicinity of the observations on 6 March. Based on the difference between the mean age derived from SF6 (which has an irreversible mesospheric loss) and from CO2 (whose mesospheric loss is much smaller and reversible) we estimate that the fraction of mesospheric air in the layer observed on 6 March, must have been somewhere between 35% and 100%.
A new version of a digital global map of irrigation areas was developed by combining irrigation statistics for 10 825 sub-national statistical units and geo-spatial information on the location and extent of irrigation schemes. The map shows the percentage of each 5 arc minute by 5 arc minute cell that was equipped for irrigation around the year 2000. It is thus an important data set for global studies related to water and land use. This paper describes the data set and the mapping methodology and gives, for the first time, an estimate of the map quality at the scale of countries, world regions and the globe. Two indicators of map quality were developed for this purpose, and the map was compared to irrigated areas as derived from two remote sensing based global land cover inventories.
Flow velocity in rivers has a major impact on residence time of water and thus on high and low water as well as on water quality. For global scale hydrological modeling only very limited information is available for simulating flow velocity. Based on the Manning-Strickler equation, a simple algorithm to model temporally and spatially variable flow velocity was developed with the objective of improving flow routing in the global hydrological model of Water- GAP. An extensive data set of flow velocity measurements in US rivers was used to test and to validate the algorithm before integrating it into WaterGAP. In this test, flow velocity was calculated based on measured discharge and compared to measured velocity. Results show that flow velocity can be modeled satisfactorily at selected river cross sections. It turned out that it is quite sensitive to river roughness, and the results can be optimized by tuning this parameter. After the validation of the approach, the tested flow velocity algorithm has been implemented into the WaterGAP model. A final validation of its effects on the model results is currently performed.
Das Klima, insbesondere der Niederschlag ist einer der wichtigsten natürlichen Gestaltungsfaktoren für die Savannenregion Westafrikas. Morphodynamik, Bodenbildung, Abflußregime sowie Wasserhaushalt werden direkt vom Klima bestimmt. Der Niederschlag ist zudem das begrenzende Element für das Wachstum von Flora und Fauna. Jede Änderung der Niederschlagsmenge hat gravierende Folgen für die Landschaft und seine Bewohner. Die Untersuchung langfristiger klimatischer Veränderungen ist ein Beitrag die Entstehung und den Wandel der Landschaft zu verstehen. Hierdurch können parallele Entwicklungen zwischen Natur- und Kulturraum im langfristigen Zusammenhängen gesehen werden. Ziel ist, das Klima des Tschadseegebietes seit dem Beginn regelmäßiger Aufzeichnung von Klimadaten mit Hilfe verschiedener statistischer Verfahren zu beschreiben. Des weiteren sollen Wechselwirkungen und Zusammenhänge zu externen Faktoren (Globale Zirkulation, Ozeantemperatur, Solarstrahlung,...) aufgezeigt werden.
Le phénomène du cuirassement reste une "curiosité" et une énigme pour le pays de la zone intertropicale. A cause de ses caractéristiques lithologiques et structurales assez particulières de ses roches (roches riches en éléments ferromagnésiens), le Burkina Faso est une véritable zone de prédilection des cuirasses. Malgré l'effort des chercheurs pour élucider le phénomène du cuirassement, force est de reconnaître que de nos jours, certains points d'ombre subsistent toujours; ce qui invite à une analyse plus poussée ... Loin de négliger les problèmes liés à la reconstitution de la génèse de la cuirasse, nous proposons ici une analyse assez originale des cuirasses sur la base des connaissances déjà acquises et de nos multiples observations sur le terrain burkinabé.
Maiduguri, an important city in the Sudano-Sahelian zone of West Africa, experiences both drought and floods. Although droughts are more popular, floods are a seasonal occurrence in parts of the city in the average rainy season. Both hazards exert a heavy toll on their victims. Present response to the hazard problems is characterised by a fire-fighting approach which does little about future occurrence. Much of the perception and response is spiritual and stops short of needed structural and organisational programmes for effective mitigation of hazards. Future occurrences of drought and flood may have more adverse effects as land use in the city becomes more complex and agricultural and water supply system comes to depend heavily on surfacial sources. Future effects will also depend on the socio-economic conditions of the people at risk and the capacity of those who help them. Governments and people need to work together to reduce drought and flood hazards.
Les débuts de l’exploitation du fer de gisement sont encore mal connus en Afrique en général et au Burkina Faso en particulier. Pourtant, pendant la colonisation française, plusieurs auteurs ont dit leur émerveillement en découvrant l’industrie métallurgique de certains peuples des pays du Burkina Faso, celle des Moose, Bwaba et Sénoufo par exemple. Selon ces auteurs, les peuples ci-dessus ont développé des technologies qui leur assuraient une bonne production de fer métal. Pour en savoir plus, nous conduisons depuis 1983 un programme sur la métallurgie du fer au Burkina Faso. L’accent a été particulièrement mis sur les aspects relatifs à la métallurgie lourde du fer. C’est pourquoi l’étude des anciennes mines présente pour nous un intérêt très spécial. Notre propos ici est de rapporter rapidement certaines informations rassemblées concernant le site et la situation des mines, les modes d’extraction, les types de minerai et les questions relatives à l’appropriation et aux conditions d’exploitation de ces mines.
Aus der Notwendigkeit heraus, "nachhaltig die Funktionen des Bodens zu sichern" (§1 BBodSchG), und damit auch Bodenschutz vorsorgend in Planungsprozesse zu integrieren, wurde ein neues Bodenschutzkonzept entwickelt. Es basiert auf einer differenzierten, aber gleichzeitig nachvollziehbaren Bodenbewertung. Das Problem bei der Bodenbewertung ist, dass etwas bewertet werden soll, für das - je nach Fragestellung - immer wieder neue Ziele definiert werden müssen. Deshalb liegt der Bodenbewertung ein Zielsystem zu Grunde, das Schutzziele klar festlegt und mit Hilfe dessen die Bodenbewertung nachvollziehbar wird. Für das Bodenschutzkonzept werden aus der Vielzahl möglicher Kriterien wichtige vorgestellt, aus denen die - bezogen auf dieses Zielsystem - wesentlichen ausgewählt werden können. Um aussagekräftige Daten für diese Kriterien zu erhalten stützt sich die Bodenbewertung auf bodenkundliche sowie landschaftsgenetisch-geomorphologische Zusammenhänge. Die eigentliche Bewertung erfolgt dann in drei Schritten: zuerst eine Einzelbewertung, dann zusammengefasst nach den Bodenfunktionen Lebensraumfunktion, Regelungsfunktion, Informationsfunktion, dem Eigenwert des Bodens (Schutzwürdigkeit) sowie der Empfindlichkeit und Gefährdung (Schutzbedürftigkeit). Im dritten Schritt werden diese Bewertungen dann zu einer gewichteten, verbal-argumentativen Gesamtbewertung der Schutzwürdigkeit und Schutzbedürftigkeit zusammengefasst. Mit Hilfe des Bewertungsverfahrens werden auch Zielkonflikte zwischen den unterschiedlichen Schutzgütern offengelegt. Schutzmaßnahmen ergeben sich dann stringent aus den vorher im Zielsystem gesetzten Prämissen, d.h., Ziele und Maßnahmen sind begründbar gewählt, stehen in einem ökologischen Gesamtzusammenhang und lassen sich sehr gut nachvollziehen. Das hier vorgestellte, neue Bodenschutzkonzept ist für verschiedene Planungsebenen geeignet. Es ist in unterschiedlichen Naturräumen anwendbar, kann verschiedene Schutzziele mit Hilfe des Zielsystems bestimmen und so z.B. die Naturraumvielfalt in einem Gebiet ebenso berücksichtigen wie die Meinungsvielfalt, was unter vorsorgendem Bodenschutz zu verstehen sei.
We present simulations with the Chemical Lagrangian Model of the Stratosphere (CLaMS) for the Arctic winter 2002/2003. We integrated a Lagrangian denitrification scheme into the three-dimensional version of CLaMS that calculates the growth and sedimentation of nitric acid trihydrate (NAT) particles along individual particle trajectories. From those, we derive the HNO3 downward flux resulting from different particle nucleation assumptions. The simulation results show a clear vertical redistribution of total inorganic nitrogen (NOy), with a maximum vortex average permanent NOy removal of over 5 ppb in late December between 500 and 550 K and a corresponding increase of NOy of over 2 ppb below about 450 K. The simulated vertical redistribution of NOy is compared with balloon observations by MkIV and in-situ observations from the high altitude aircraft Geophysica. Assuming a globally uniform NAT particle nucleation rate of 3.4·10−6 cm−3 h−1 in the model, the observed denitrification is well reproduced. In the investigated winter 2002/2003, the denitrification has only moderate impact (<=10%) on the simulated vortex average ozone loss of about 1.1 ppm near the 460 K level. At higher altitudes, above 600 K potential temperature, the simulations show significant ozone depletion through NOx-catalytic cycles due to the unusual early exposure of vortex air to sunlight.
Chlorine monoxide (ClO) plays a key role in stratospheric ozone loss processes at midlatitudes. We present two balloonborne in situ measurements of ClO conducted in northern hemisphere midlatitudes during the period of the maximum of total inorganic chlorine loading in the atmosphere. Both ClO measurements were conducted on board the TRIPLE balloon payload, launched in November 1996 in Le´on, Spain, and in May 1999 in Aire sur l’Adour, France. For both flights a ClO daylight and night time vertical profile could be derived over an altitude range of approximately 15–31 km. ClO mixing ratios are compared to model simulations performed with the photochemical box model version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). Simulations along 24-h backward trajectories were performed to study the diurnal variation of ClO in the midlatitude lower stratosphere. Model simulations for the flight launched in Aire sur l’Adour 1999 show a good agreement with the ClO measurements. For the flight launched in Le´on 1996, a similar good agreement is found, except at around ~ 650 K potential temperature (~26km altitude). However, a tendency is found that for solar zenith angles greater than 86°–87° the simulated ClO mixing ratios substantially overestimate measured ClO by approximately a factor of 2.5 or more for both flights. Therefore we conclude that no indication can be deduced from the presented ClO measurements that substantial uncertainties exist in midlatitude chlorine chemistry of the stratosphere. An exception is the situation at solar zenith angles greater than 86°–87° where model simulations substantial overestimate ClO observations.
Attribution and detection of anthropogenic climate change using a backpropagation neural network
(2002)
The climate system can be regarded as a dynamic nonlinear system. Thus traditional linear statistical methods are not suited to describe the nonlinearities of this system which renders it necessary to find alternative statistical techniques to model those nonlinear properties. In addition to an earlier paper on this subject (WALTER et al., 1998), the problem of attribution and detection of the observed climate change is addressed here using a nonlinear Backpropagation Neural Network (BPN). In addition to potential anthropogenic influences on climate (CO2-equivalent concentrations, called greenhouse gases, GHG and SO2 emissions) natural influences on surface air temperature (variations of solar activity, volcanism and the El Niño/Southern Oscillation phenomenon) are integrated into the simulations as well. It is shown that the adaptive BPN algorithm captures the dynamics of the climate system, i.e. global and area weighted mean temperature anomalies, to a great extent. However, free parameters of this network architecture have to be optimized in a time consuming trial-and-error process. The simulation quality obtained by the BPN exceeds the results of those from a linear model by far; the simulation quality on the global scale amounts to 84% explained variance. Additionally the results of the nonlinear algorithm are plausible in a physical sense, i.e. amplitude and time structure. Nevertheless they cover a broad range, e.g. the GHG-signal on the global scale ranges from 0.37 K to 1.65 K warming for the time period 1856-1998. However the simulated amplitudes are situated within the discussed range (HOUGHTON et al., 2001). Additionally the combined anthropogenic effect corresponds to the observed increase in temperature for the examined time period. In addition to that, the BPN succeeds with the detection of anthropogenic induced climate change on a high significance level. Therefore the concept of neural networks can be regarded as a suitable nonlinear statistical tool for modeling and diagnosing the climate system.
Vielleicht hätte sich außerhalb der Fachwissenschaft niemand für das Weltklimaproblem interessiert, wären da nicht zwei brisante, miteinander gekoppelte Fakten: Die Menschheit ist hochgradig von der Gunst des Klimas abhängig. Es kann uns daher nicht gleichgültig sein, was mit unserem Klima geschieht. Und: Die Menschheit ist mehr und mehr dazu übergegangen, das Klima auch selbst zu beeinflussen. Daraus erwächst uns allen eine besondere Verantwortung. ...
Wenn sich beim Klimagipfel in Den Haag [genauer bei der nun schon 6. Vertragstaatenkonferenz zur Klimaschutzkonvention der Vereinten Nationen] nun wieder die Delegationen aus fast allen Staaten der Welt treffen, um über Klimaschutzmaßnahmen zu beraten, dann schwingt auch immer die Frage mit: Sind solche Maßnahmen wirklich notwendig? Sollen wir nicht einfach warten, bis wir mehr, ja vielleicht alles wissen? ...
Die Zunahme der Konzentration von CO2 und anderen "Treibhausgasen" in der Atmosphäre ist unzweifelhaft, und ebenso unzweifelhaft reagiert das Klima darauf. Christian-Dietrich Schönwiese, Professor für Meteorologische Umweltforschung und Klimatologie an der Universität Frankfurt am Main, sieht dringenden politischen Handlungsbedarf und plädiert gleichzeitig dafür, die Debatte rund um den Klimaschutz zu versachlichen.
Die öffentliche Klimadebatte scheint sich zu verselbständigen. Abgehoben von den Erkenntnissen der Fachwissenschaftler reden die einen von der "Klimakatastrophe", die uns demnächst mit voller Wucht treffen wird, wenn wir nicht sofort alles ganz anders machen; Panik ist ihnen das rechte Mittel, Aufmerksamkeit zu erregen. Die anderen sehen im "Klimaschwindel" einen Vorwand für Forschungsgelder und zusätzliche Steuerbelastung der Wirtschaft; ihre Strategie ist Verwirrung und Verharmlosung. Mit der Fixierung auf solche Extrempositionen werden wir den Herausforderungen der Zukunft sicherlich nicht gerecht. Höchste Zeit für eine Versachlichung und für einen klärenden Beitrag zum Verwirrspiel "Klima".
Temporal changes in the occurrence of extreme events in time series of observed precipitation are investigated. The analysis is based on a European gridded data set and a German station-based data set of recent monthly totals (1896=1899–1995=1998). Two approaches are used. First, values above certain defined thresholds are counted for the first and second halves of the observation period. In the second step time series components, such as trends, are removed to obtain a deeper insight into the causes of the observed changes. As an example, this technique is applied to the time series of the German station Eppenrod. It arises that most of the events concern extreme wet months whose frequency has significantly increased in winter. Whereas on the European scale the other seasons also show this increase, especially in autumn, in Germany an insignificant decrease in the summer and autumn seasons is found. Moreover it is demonstrated that the increase of extreme wet months is reflected in a systematic increase in the variance and the Weibull probability density function parameters, respectively.
Simulation of global temperature variations and signal detection studies using neural networks
(1998)
The concept of neural network models (NNM) is a statistical strategy which can be used if a superposition of any forcing mechanisms leads to any effects and if a sufficient related observational data base is available. In comparison to multiple regression analysis (MRA), the main advantages are that NNM is an appropriate tool also in the case of non-linear cause-effect relations and that interactions of the forcing mechanisms are allowed. In comparison to more sophisticated methods like general circulation models (GCM), the main advantage is that details of the physical background like feedbacks can be unknown. Neural networks learn from observations which reflect feedbacks implicitly. The disadvantage, of course, is that the physical background is neglected. In addition, the results prove to be sensitively dependent from the network architecture like the number of hidden neurons or the initialisation of learning parameters. We used a supervised backpropagation network (BPN) with three neuron layers, an unsupervised Kohonen network (KHN) and a combination of both called counterpropagation network (CPN). These concepts are tested in respect to their ability to simulate the observed global as well as hemispheric mean surface air temperature annual variations 1874 - 1993 if parameter time series of the following forcing mechanisms are incorporated : equivalent CO2 concentrations, tropospheric sulfate aerosol concentrations (both anthropogenic), volcanism, solar activity, and ENSO (all natural). It arises that in this way up to 83% of the observed temperature variance can be explained, significantly more than by MRA. The implication of the North Atlantic Oscillation does not improve these results. On a global average, the greenhouse gas (GHG) signal so far is assessed to be 0.9 - 1.3 K (warming), the sulfate signal 0.2 - 0.4 K (cooling), results which are in close similarity to the GCM findings published in the recent IPCC Report. The related signals of the natural forcing mechanisms considered cover amplitudes of 0.1 - 0.3 K. Our best NNM estimate of the GHG doubling signal amounts to 2.1K, equilibrium, or 1.7 K, transient, respectively.
The climate system can be regarded as a dynamic nonlinear system. Thus, traditional linear statistical methods fail to model the nonlinearities of such a system. These nonlinearities render it necessary to find alternative statistical techniques. Since artificial neural network models (NNM) represent such a nonlinear statistical method their use in analyzing the climate system has been studied for a couple of years now. Most authors use the standard Backpropagation Network (BPN) for their investigations, although this specific model architecture carries a certain risk of over-/underfitting. Here we use the so called Cauchy Machine (CM) with an implemented Fast Simulated Annealing schedule (FSA) (Szu, 1986) for the purpose of attributing and detecting anthropogenic climate change instead. Under certain conditions the CM-FSA guarantees to find the global minimum of a yet undefined cost function (Geman and Geman, 1986). In addition to potential anthropogenic influences on climate (greenhouse gases (GHG), sulphur dioxide (SO2)) natural influences on near surface air temperature (variations of solar activity, explosive volcanism and the El Nino = Southern Oscillation phenomenon) serve as model inputs. The simulations are carried out on different spatial scales: global and area weighted averages. In addition, a multiple linear regression analysis serves as a linear reference. It is shown that the adaptive nonlinear CM-FSA algorithm captures the dynamics of the climate system to a great extent. However, free parameters of this specific network architecture have to be optimized subjectively. The quality of the simulations obtained by the CM-FSA algorithm exceeds the results of a multiple linear regression model; the simulation quality on the global scale amounts up to 81% explained variance. Furthermore the combined anthropogenic effect corresponds to the observed increase in temperature Jones et al. (1994), updated by Jones (1999a), for the examined period 1856–1998 on all investigated scales. In accordance to recent findings of physical climate models, the CM-FSA succeeds with the detection of anthropogenic induced climate change on a high significance level. Thus, the CMFSA algorithm can be regarded as a suitable nonlinear statistical tool for modeling and diagnosing the climate system.
Observed global and European spatiotemporal related fields of surface air temperature, mean-sea-level pressure and precipitation are analyzed statistically with respect to their response to external forcing factors such as anthropogenic greenhouse gases, anthropogenic sulfate aerosol, solar variations and explosive volcanism, and known internal climate mechanisms such as the El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). As a first step, a principal component analysis (PCA) is applied to the observed spatiotemporal related fields to obtain spatial patterns with linear independent temporal structure. In a second step, the time series of each of the spatial patterns is subject to a stepwise regression analysis in order to separate it into signals of the external forcing factors and internal climate mechanisms as listed above as well as the residuals. Finally a back-transformation leads to the spatiotemporally related patterns of all these signals being intercompared. Two kinds of significance tests are applied to the anthropogenic signals. First, it is tested whether the anthropogenic signal is significant compared with the complete residual variance including natural variability. This test answers the question whether a significant anthropogenic climate change is visible in the observed data. As a second test the anthropogenic signal is tested with respect to the climate noise component only. This test answers the question whether the anthropogenic signal is significant among others in the observed data. Using both tests, regions can be specified where the anthropogenic influence is visible (second test) and regions where the anthropogenic influence has already significantly changed climate (first test).