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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/

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Bautzen, Germany from 1985 – 2023

The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.

Gravity Recovery and Climate Experiment (GRACE-C)

Sentinel-5P TROPOMI - Aerosol Optical Depth (AOD), Level 3 - Global

Aerosol optical depth (AOD) as derived from TROPOMI observations. AOD describes the attenuation of the transmitted radiant power by the absence of aerosols. Attenuation can be caused by absorption and/or scattering. AOD is the primary parameter to evaluate the impact of aerosols on weather and climate. Daily AOD observations are binned onto a regular latitude-longitude grid. The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product is created in the scope of the project INPULS. It develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.

Schwerpunktprogramm (SPP) 1294: Bereich Infrastruktur - Atmospheric and Earth system research with the 'High Altitude and Long Range Research Aircraft' (HALO), CIRRUS-HL – Die HALO Mission zu Zirren in hohen Breiten Umbrella Proposal HALO2020 - CIRRUS-HL

Die Mission CIRRUS-HL – Zirren in hohen Breiten nutzt das Forschungsflugzeug HALO gemeinsam mit Modellen und Satelliten, um die Nukleation, den Lebenszyklus und die Klimawirkung von Eiswolken in hohen Breiten, einer Region mit massiven anthropogenen Klimaänderungen, genauer zu bestimmen. InhaltSchnellste und massivste anthropogen verursachte Änderungen der Erdoberflächentemperatur finden in hohen Breiten statt. Hier führen Eiswolken im Winter zu einem großen positiven Strahlungsantrieb. Direkte Messungen der mikrophysikalischen Eigenschaften von Eiswolken und ihrer Variabilität sind jedoch unvollständig und Eisanzahlkonzentrationen werden in Klimamodellen nicht adäquat repräsentiert, dies schränkt die Aussagekraft von Klimamodellen in hohen Breiten deutlich ein. Die Messkampagne CIRRUS-HL, in den letzten 6 Jahren die einzige HALO Messkampagne mit in situ Wolken-Instrumentierung nutzt neuere Wolkensonden gemeinsam mit umfangreichen Spurengas-, Aerosol- und Strahlungs-Messungen um die Nukleation, den Lebenszyklus und die Klimawirkung von Eiswolken in hohen Breiten genauer zu bestimmen. Die Flugzeugmessungen werden begleitet von Messaktivitäten von Bodenstationen und Satelliten, und liefern Daten für Prozessmodelle und die Evaluierung von globalen Klimamodellen. Die CIRRUS-HL Mission ist eingebunden in einen internationalen Verbund an Messaktivitäten in der Arktis und besitzt als Alleinstellungsmerkmal einen Fokus auf Eiswolken. Von Oktober bis Dezember 2020 werden in Nordeuropa und Kanada 20 Flüge mit dem Forschungsflugzeug HALO, stationiert in Oberpfaffenhofen und Keflavik, Island, durchgeführt, um die Eigenschaften von Eiswolken genau zu vermessen, die sich in verschiedenen dynamischen Regimes wie zum Beispiel Frontensystemen oder orographisch induzierten Hebungen von Luftmassen gebildet haben. Eigenschaften von Zirren, die sich entweder unterhalb von 238 K in situ homogen oder heterogen gebildet haben, oder die ihren Ursprung in einer flüssigen oder Mischphasen-Wolke bei Temperaturen oberhalb von 238 K haben werden differenziert. Die CIRRUS-HL Mission liefert 1.) einen neuen Datensatz der mikrophysikalischen Eigenschaften von Eiswolken in hohen Breiten zur Verbesserung des Prozessverständnisses der Eisnukleation und zum Vergleich mit Satellitenbeobachtungen und Klimamodellen, 2.) neue Einblicke in den Transport von Aerosolen in hohe Breiten und ihre Prozessierung in Mischphasen- und Eiswolken und 3.) umfassende Beobachtungen von Strahlungseigenschaften von Eiswolken in hohen Breiten im Frühwinter. Der umfangreiche Datensatz zu Eiswolken dient dazu, das Verständnis der Rolle von arktischen Zirren im Klimasystem zu erhöhen.

METOP GOME-2 - Tropospheric Ozone (Trop-O3) - Tropical

GOME (Global Ozone Monitoring Experiment) stands for a family of satellite instruments named after the first GOME (https://wdc.dlr.de/sensors/gome/) instrument on ERS-2 launched in April 1995. Currently two GOME-2 instruments are operative on Metop-A and B (https://wdc.dlr.de/sensors/gome2/). The tropical tropospheric ozone is retrieved with convective cloud differential method (Valks et al., 2014 http://www.atmos-meas-tech.net/7/2513/2014/amt-7-2513-2014.html). The tropospheric column is retrieved by subtracting the stratospheric ozone column from the total column. The stratospheric ozone column is estimated as the column above high reaching convective clouds.

METOP GOME-2 - Tropospheric 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 operational NO2 tropospheric column products are generated using the algorithm GDP (GOME Data Processor) version 4.x for NO2 [Valks et al. (2011)] 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 using the DOAS method. An additional algorithm is applied to derive the tropospheric NO2 column: after subtracting the estimated stratospheric component from the total column, the tropospheric NO2 column is determined using an air mass factor based on monthly climatological NO2 profiles from the MOZART-2 model. 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/

BodenBewegungsdienst Deutschland (BBD) 2019-2023 L2B Ascending (WMTS)

Die vielfältige Geologie Deutschlands sowie die sich hieraus ergebende Nutzung sind Ursachen für verschiedenste Bodenbewegungen, wie z.B. Bodenkompaktion, Erdrutsche, Grundwasserentnahme, Erdgasförderung, (Alt-)Bergbau- und Kavernenspeicherbetrieb. Die Produkte des BodenBewegungsdienst Deutschland (BBD) basieren auf SAR Daten der Copernicus Sentinel-1 Mission und einer Persistent Scatterer Interferometrie (PSI) Verarbeitung. Das BBD Portal enthält PSI Daten der gesamten Bundesrepublik Deutschland (ca. 360.000 km²). Die PSI Technologie ermöglicht präzise Messungen von Bewegungen der Erdoberfläche im mm Bereich. Die Messpunkte (Persistent Scatterer, PS) entsprechen bereits am Boden vorhandenen Objekten, wie z.B. Gebäuden, Infrastruktur oder natürlichen Objekten, wie Gesteinen und Schuttflächen. Jeder PS wird durch einen über mehrere Jahre gemittelten Geschwindigkeitswert (ausgedrückt in mm/Jahr) und eine Zeitreihe der Verschiebungen charakterisiert. Für jeden PS kann die Zeitreihe der Verschiebungen von der ersten Sentinel-1 Aufnahme bis zur letzten ausgewerteten Sentinel-1 Aufnahme eingesehen werden. Die PS werden nach der mittleren Geschwindigkeit entlang der Sichtlinie der Sentinel-1 Satelliten, Line of Sight (LOS), gemäß der folgenden Konvention im BBD Portal visualisiert: - die grüne Farbe entspricht den PS, deren mittlere Geschwindigkeit sehr gering ist, zwischen -2,0 und +2,0 mm/Jahr, d.h. im Empfindlichkeitsbereich der PSI Technologie; - in den Farben von gelb bis rot werden diejenigen PS mit negativer Bewegungsrate visualisiert, d.h. Bewegungen vom Satelliten weg; - mit den Farben von türkis bis blau werden diejenigen PS mit positiver Bewegungsrate visualisiert, d.h. PS die sich dem Satelliten nähern. Die Präzision der dargestellten PSI Daten liegt in der Größenordnung von typischerweise +- 2 mm/Jahr für die mittlere Geschwindigkeit in LOS.

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Landshut, Germany from 1984 – 2023

The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.

Kostenreduktion und erhöhte Ressourceneffizienz durch neue Versorgungssysteme für Metall-Organische Ausgangsstoffe in der Epitaxie von III-V Hochleistungssolarzellen 2.0

Solarzellen aus III- V Halbleitern erreichen heute weltweit mit über 46 % die höchsten Umwandlungseffizienzen und finden industrielle Anwendung in Satelliten und in Konzentrator- PV Systemen. Als Ausgangsverbindungen werden Trimethylindium und Trimethylgallium als sogenannte 'Metallorganische Quellen' eingesetzt. Diese machen die Hälfte der Epitaxiekosten des Herstellprozesses aus. Zur Reduktion der Epitaxiekosten bietet sich das sogenannte 'Liquid- Indium' als hochreine Indium-Quelle an. Dazu soll ein produktionstauglicher Prozess für die Darstellung von Trimethylindium mittels eines Hochdruckverfahren und die folgende Umsetzung zum Liquid-Indium etabliert werden, was die Aufreinigung auf eine hochreine, epitaxietaugliche Qualität inklusive der analytischen Verfahren beinhaltet. Die Grundlage bieten dabei die Ergebnisse aus dem vorhergegangen KoReMo Projekt. Das Ziel des Teilprojektes für Dockweiler Chemicals stellt die Etablierung dieses großskaligen Produktionsprozesses dar, um bei den Projektpartnern das hochreine Material in der metallorganischen Gasphasenepitaxie einzusetzen.

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