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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/

Hochaufgelöste Satellitenbilder von XCO2 und XCH4, Teilprojekt 2: Simulationen

Einfluss der solaren Flareaktivität auf die Qualität des GPS-Empfangs

Es ist durch neuere Untersuchungen bekannt, das Sekundäreffekte sehr starker solarer Eruptionen (Flares), so genannte 'radio bursts', die Empfangsqualität des 'Global Positioning System' (GPS) negativ beeinflussen. Das vorliegende Langzeitprojekt vergleicht die Flare-Aktivität, repräsentiert durch die permanent zur Verfügung stehenden Röntgenmessungen der NOAA-Satelliten GEOS-11 und -12 (siehe http://www.ut-wetter.fh-wiesbaden.de:8080/space.htm), mit der in Rüsselsheim und Locarno ebenfalls permanent gemessenen Empfangsqualität zweier handelsüblicher GPS-Empfänger. Die Untersuchungsdauer soll den gesamten gerade beginnenden 11-Jahres-Aktivitäts-Zyklus der Sonne umfassen.

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 Top Pressure (CTP) - 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-top pressure for GOME scenes is derived from the cloud-top height provided by ROCINN and an appropriate pressure profile. 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 - 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/

Hochaufgelöste Satellitenbilder von XCO2 und XCH4, Teilprojekt 1: Observationen

Human influences on forests in southern Ethiopia: the case of Shashemane-Munessa-forest

Especially during the last decades, the natural forests of Ethiopia have been heavily disturbed by human activities. Some forests have been totally cleared and converted into fields for agricultural use, other suffered from different influences, such as heavy grazing and selective logging. The ongoing research in the Shashemane-Munessa-study area (Gu 406/8-1,2) showed clearly that, in spite of interdiction and control, forests continue to be cleared and degraded. However, it is not yet sufficiently known, how and why these processes are still going on. Growing population pressure and economic constraints for the people living in and around the forests contribute to the actual situation but allow no final answers to the complex situation. Concerning a sustainable management of the forests there is to no solid basis for recommendations from the socioeconomic and socio-cultural view. Therefore, a comprehensive analysis of the traditional needs and forms of forest use, including all forest products, is necessary. The objective of this project is, to achieve this basis by carrying out intensive field observations, the consultation of aerial photographs, satellite imagery and above all semi-structured interviews with the population in the study area in order to contribute to the recommendations for a sustainable use of the Munessa Shasemane forests.

Schwerpunktprogramm (SPP) 1788: Study of Earth system dynamics with a constellation of potential field missions, Kopplung der solaren und geomagnetischen Aktivität mit der räumlichen Verteilung von Trends in Treibhausgasen in der oberen Atmosphäre

Die Struktur und Zusammensetzung des Thermosphäre-Ionosphäre Systems (T-I) wird stark durch die solare EUV-Strahlung beeinflusst. Die andere wichtige externe Quelle von Variabilität in dieser Atmosphärenregion ist das geomagnetische Feld, das geladene Teilchen in die Atmosphäre leitet wo sie insbesondere um die Pole herum ihre Energie abgeben. Wie neue Daten zeigen, können auch interne Antriebsprozesse sowohl auf kurzen (Tage) als auch langen (Jahre) Zeitskalen die T-I Variabilität dominieren. Eine wesentliche Rolle wird dabei dem langsamen aber kontinuierlichen Anstieg von CO2 in der Mesosphäre und unteren Thermosphäre (MLT) zugeschrieben, der zu verstärkter Strahlungskühlung und damit einhergehender Kontraktion der Atmosphäre führt. Auch andere Treibhausgase können auf kürzeren Zeitskalen die T-I Variabilität stark modulieren, u.a. O3 und NO. Das Hauptziel dieses Projektes ist zu untersuchen, wie die räumliche Verteilung von Langzeittrends in MLT Treibhausgasen mit der T-I Langzeit Variabilität gekoppelt ist. Dabei sollen sowohl bodengebundene als auch Satellitendaten von CO2, O3, NO, H2O sowie Elektronendichten herangezogen werden. Durch Kombination von Daten der Satelliten CHAMP, GRACE, SWARM, COSMIC, GOMOS, ACE-FTS, MLS, SABER, MIPAS, HALOE und AIM soll eine nahezu globale Abdeckung über einen Zeitraum von 2 Sonnenzyklen erreicht werden. Aus diesen Daten soll eine globale Klimatologie erstellt werden als Grundlage für die Ableitung von Langzeittrends und ihrer Korrelation in Zeit, Raum und T-I Parametern, einschließlich der Untersuchung von möglichen zeitlichen Verzögerungen in der Variabilität. Ferner sollen chemische und dynamische Wirkmechanismen der T-I Reaktion auf diese Variabilität identifiziert sowie zum ersten Mal echte Abkühlungs- und Aufheizraten aus der globalen Klimatologie und ihre Korrelationen in der T-I Region berechnet werden. Diese können direkt in allgemeinen Zirkulationsmodellen anstatt der aus Volumenemissionsraten gewonnenen Abkühlraten verwendet werden.

Oberflächentemperaturen von Laubwäldern zur Analyse von Wasser- und Hitzestress

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