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METOP GOME-2 - Formaldehyde (HCHO) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational HCHO total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/

METOP GOME-2 - Water Vapour (H2O) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational H2O total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV/VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The total H2O column is retrieved from GOME solar backscattered measurements in the red wavelength region (614-683.2 nm), using the Differential Optical Absorption Spectroscopy (DOAS) method. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/

METOP GOME-2 - Bromine Monoxide (BrO) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational BrO (Bromine monoxide) total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. For more details please refer to https://atmos.eoc.dlr.de/app/missions/gome2

METOP GOME-2 - Cloud Optical Thickness (COT) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks) are used for retrieving the following geophysical cloud properties from GOME and GOME-2 data: cloud fraction (cloud cover), cloud-top pressure (cloud-top height), and cloud optical thickness (cloud-top albedo). OCRA is an optical sensor cloud detection algorithm that uses the PMD devices on GOME / GOME-2 to deliver cloud fractions for GOME / GOME-2 scenes. ROCINN takes the OCRA cloud fraction as input and uses a neural network training scheme to invert GOME / GOME-2 reflectivities in and around the O2-A band. VLIDORT [Spurr (2006)] templates of reflectances based on full polarization scattering of light are used to train the neural network. ROCINN retrieves cloud-top pressure and cloud-top albedo. The cloud optical thickness is computed using libRadtran [Mayer and Kylling (2005)] radiative transfer simulations taking as input the cloud-top albedo retrieved with ROCINN. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/

METOP GOME-2 - Nitrogen Dioxide (NO2) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational NO2 total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The total NO2 column is retrieved from GOME solar back-scattered measurements in the visible wavelength region (425-450 nm), using the Differential Optical Absorption Spectroscopy (DOAS) method. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/

METOP GOME-2 - Ozone (O3) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational ozone total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The new improved DOAS-style (Differential Optical Absorption Spectroscopy) algorithm called GDOAS, was selected as the basis for GDP version 4.0 in the framework of an ESA ITT. GDP 4.x performs a DOAS fit for ozone slant column and effective temperature followed by an iterative AMF / VCD computation using a single wavelength. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/

Untersuchung ueber den Einfluss des Mikroklimas an Bauwerksoberflaechen und dadurch bedingten Feuchtigkeitstransport in anorganischen, poroesen, insbesondere inhomogenen Baustoffen im Hinblick auf Korrosion

Die Bestaendigkeit poroeser Baustoffe, die der Witterung und Atmosphaere sowie anderen korrosiven Einfluessen, wie z.B. bei Stahlbetonbruecken dem Einfluss von Streusalzen, ausgesetzt sind, wird massgebend von der Struktur des Stoffes und der Feuchtigkeitsaufnahme bzw. -abgabe bestimmt. Das Eindringen aggressiver Stoffe haengt nicht nur vom momentanen Feuchtigkeitsgehalt in den Poren des Baustoffs ab, sondern offenbar auch von instationaerem Wassertransport, der durch Aenderungen, vor allem der Feuchtigkeit in der Umgebung der Bauteiloberflaechen hervorgerufen wird. Bei Baustoffen, die hinsichtlich Diffusionswiderstand und thermodynamischem Verhalten aus unterschiedlichen Stoffen aufgebaut sind (Beispiel: Beton, Stahl- und Spannbeton, mit Kunststoffen beschichtete poroese Stoffe), ist eine theoretische Betrachtung dieser Vorgaenge im Mikrogefuege kaum moeglich. Mit der Mikrowellenmesstechnik sollen die Wassergehaltsaenderungen und damit der Wassertransport bei Einwirkung verschiedener Umgebungsbedingungen untersucht werden, um die Ablaeufe bei Korrosionsvorgaengen genauer verstehen bzw. Massnahmen fuer besseren Korrosionsschutz ableiten zu koennen.

Nahrungserwerb der Waldameisen (Gattung Formica) und ihr Einfluss auf die Waldbiozoenose

Nahrungserwerb der Waldameisen in einem Eichenwald im Tages- und Jahresverlauf, Jahresbilanz (Menge, Zusammensetzung, Energiegehalt der Nahrung). Beeinflussung des Nahrungserwerbs durch Umweltfaktoren (Witterung, Nahrungsangebot). Regulation des Nahrungserwerbs durch die Waldameisen selbst. Einfluss der Waldameisen auf den Massenwechsel eines Schadinsekts (Eichenwickler Tortrix viridana L.).

Mikroprozessorgesteuertes Prognosesystem zum Wachstum von Pilzen in Kulturpflanzen zur gezielten Einschraenkung von Fungizidspritzungen

Aus modernsten Mikroprozessorbausteinen wurde ein preiswertes, kompaktes Geraet zur Datenerfassung und Datenspeicherung im Freiland entwickelt, das batteriebetrieben unter mitteleuropaeischen Witterungsbedingungen sehr stoerungsarm mit einer bisherigen Ausfallquote von nur 2 Prozent arbeitet. An das Geraet sind maximal 18 Messfuehler anschliessbar. Die Messwerte werden in waehlbaren Abstaenden in einem Speicherbaustein (Eprom) abgelegt, der am Einsatzort des Geraetes leicht auszuwechseln ist. Die Messdaten koennen mit Hilfe eines einfachen Lesegeraetes in jeden Rechner uebertragen werden. Der frei programmierbare Mikroprozessor des Geraetes kann seinerseits bereits im Feld weitere Aufgaben ausfuehren. Im vorliegenden Fall berechnet er aus den gemessenen Daten fuer die Lufttemperatur, die relative Luftfeuchtigkeit und die Blattbenetzung mit Hilfe von mathematischen Modellen die Entwickung von Schadpilzen in Weizen-, Kartoffel- und Apfelkulturen. So erhaelt der Landwirt ein Warngeraet, das ihm anzeigt, ob eine chemische Bekaempfungsmassnahme gegen den betreffenden Schadpilz erforderlich ist, um wirtschaftlichen Schaden abzuwenden.

Interaktion zwischen den Reitbodeneigenschaften und der biomechanischen Beanspruchung von Pferd und Reiter

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