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METOP GOME-2 - Sulfur Dioxide (SO2) - Global

Gridded Level 3 SO2 total column densities derived from the Metop/GOME-2-instruments. Volcanoes are the largest soures of SO2 in the atmosphere, depending on the erruption the Sulfurous compounds can be injected into stratosphere but in most cases it stays within the troposphere. Another important source is the coal combustion. Desulfurisation facilities within the power stations have reduced the sulfur emissions around the globe. In the stratosphere sulfur is a key component for building up aerosols, which reflect parts of the solar irradiation. The total SO2 column is retrieved from GOME solar back-scattered measurements in the ultraviolet wavelength region [using the DOAS method]. Depending on the plume SO2 can be a very strong absorber, because of that the ODAS retrieval might have some smaller issues, they can be reduced by choosing different wavelenght ranges depending on the signal. We apply three different fitting windows between 310 and 360nm. For the AMF, we assume a plumeheight of 6 km altitude. 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. Three instruments operate on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in 2006, 2012, and 2018, respectively. GOME-2 measures a range of atmospheric trace constituents, with the emphasis on global ozone distribution. 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 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF).

METOP GOME-2 - Ozone (O3) - Global

Gridded Level 3 ozone column densities derived from the Metop/GOME-2-instruments. In the stratosphere – where the majority of the total O3 amount is located - O3 plays an vital role for the UV protection. In the troposphere O3 is generated by chemical processes caused by natural and anthropogenic emission of NO2 and volatile organic components (VOCs) (e.g. HCHO). Direct exposure to O3 is harmfull for humans and our environment. The total O3 column is retrieved from GOME solar back-scattered measurements in the uv wavelength region 325-335nm [using the DOAS method]. To determine the AMF an iterative process is applied, the assumed profile depends on the latitude, month, but also on the total column. 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. Three instruments operate on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in 2006, 2012, and 2018, respectively. GOME-2 measures a range of atmospheric trace constituents, with the emphasis on global ozone distribution. 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 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF).

Sentinel-5P TROPOMI - Aerosol Single-Scattering Albedo (ASSA), Level 3 - Global

Aerosol single-scattering albedo (ASSA) as derived from TROPOMI observations. ASSA is a measure of how much light is scattered by aerosols compared to how much is absorbed. It is important for understanding the impact of aerosols on climate and radiative forcing. ASSA is unitless; a value of unity implies that extinction is completely due to scattering; conversely, a single-scattering albedo of zero implies that extinction is completely due to absorption. Daily ASSA 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.

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

Gridded Level 3 tropospheric NO2 column densities derived from the Metop/GOME-2-instruments. In the troposphere NO2 is a short-lived atmospheric constituent caused by combustion processes, e.g. fossil fuel consumption or biomass buring or by lightning. NO2 plays an important role in the formation of ozone. The total NO2 column is retrieved from GOME solar back-scattered measurements in the visible wavelength region around 440nm [using the DOAS method]. To derive tropospheric NO2 columns, the estimated stratospheric component is substracted from the total column. In addition, an air mass factor based on monthly climatological NO2 profiles is considered. 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. Three instruments operate on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in 2006, 2012, and 2018, respectively. GOME-2 measures a range of atmospheric trace constituents, with the emphasis on global ozone distribution. 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 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF).

METOP GOME-2 - Formaldehyde (HCHO) - Global

Gridded Level 3 formaldehyde (HCHO) column densities derived from the Metop/GOME-2-instruments. In the troposphere HCHO is a short-lived atmospheric constituent caused by incomplete combustion processes, e.g. fossil fuel consumption or biomass buring or it is build by atmospheric chemical species from other volatile organic component (VOCs). It plays an important role in the build up of tropospheric ozone. The total HCHO column is retrieved from GOME solar back-scattered measurements in the UV wavelength region 328.5nm to 346nm [using the DOAS method]. In addition, an air mass factor based on monthly climatological HCHO profiles is considered. 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. Three instruments operate on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in 2006, 2012, and 2018, respectively. GOME-2 measures a range of atmospheric trace constituents, with the emphasis on global ozone distribution. 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 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF).

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

Gridded Level 3 cloud optical thickness derived from Metop/GOME observations. Cloud physical properties (cloud fraction, cloud top height, cloud optical thickness) are derived from GOME/GOME-2 observations using the OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks). 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/ 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. Three instruments operate on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in 2006, 2012, and 2018, respectively. GOME-2 measures a range of atmospheric trace constituents, with the emphasis on global ozone distribution. 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 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF).

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Weil-Rhein, 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.

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.

Windanalyse in der mittleren Atmosphäre mittels nächtlicher RMR-Lidar-Messungen in mittleren Breiten in Kühlungsborn (AMUN)

Der horizontale Wind nimmt eine Schlüsselrolle in der Dynamik der Atmosphäre ein. Insbesondere beeinflusst er die Ausbreitung und Dissipation von Schwerewellen und thermischen Gezeiten in der mittleren Atmosphäre. Simultane Wind- und Temperaturmessungen bieten dabei die einzigartige Möglichkeit, sowohl kinetische als auch potentielle Energiedichten der Schwerewellen zu berechnen, aus denen wiederum intrinsische Wellenparameter ableitbar sind. Windmessungen in der mittleren Atmosphäre sind jedoch insbesondere im Höhenbereich zwischen 35 und 75 km sehr selten, da hier weder Radiosonden noch Radars Daten liefern und Wind-Radiometer bzw. Satelliten keine für die Untersuchung von Schwerewellen ausreichend große Genauigkeit und Auflösung haben. Deshalb wollen wir in Kühlungsborn/Deutschland (54° N, 12° O) ein neues Lidar aufbauen, mit dem bei gekippten Teleskopen der Horizontalwind aus der Dopplerverschiebung der Rayleigh-Rückstreuung bestimmt werden kann. Neben der Erstellung einer Wind-Klimatologie steht vor allem die Untersuchung der Ausbreitung von Trägheitsschwerewellen in der mittleren Atmosphäre im Vordergrund. Dazu werden wir u.a. horizontale und vertikale Impulsflüsse und die Höhe des Impulsübertrags an die Hintergrundatmosphäre bestimmen. Diese für die Energiebilanz der Atmosphäre wesentlichen Parameter liefern wichtige Vergleichsgrößen für Zirkulationsmodelle. Ferner werden wir intrinsische Welleneigenschaften aus Wind-Hodographen analysieren, die für andere bodengebundene Messsysteme in der Regel nicht zugänglich sind. Unter Einbeziehung des lokalen Hintergrundwindes sollen aufwärts und abwärts propagierende Schwerewellen eindeutig getrennt und quantifiziert werden. Die Analysen werden insgesamt unser Verständnis der vertikalen Kopplung und der zu Grunde liegenden Zirkulation in der mittleren Atmosphäre deutlich verbessern. Das neue Lidarsystem ergänzt ein in Nordnorwegen am ALOMAR-Observatorium (69° N, 16° O) vorhandenes Windlidar, welches ebenfalls vom IAP betrieben wird. In diesem Projekt wird die dabei erworbene Expertise genutzt, um die Entwicklungsrisiken für das neue Lidar zu minimieren und schwerpunktmäßig Windmessungen in der mittleren Atmosphäre durchzuführen und zu interpretieren.

Gemeinsame nationale Initiative zur Validierung von EarthCARE, Teilvorhaben DWD

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