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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).

Airglow-Forschung mit astronomischen Spektren

In der oberen Erdatmosphäre ab 70 km herrschen spezielle Bedingungen, die ein Leuchten im sichtbaren und infraroten Licht verursachen. Die Airglow genannten Emissionen werden durch solare extreme Ultraviolettstrahlung hervorgerufen, die Luftmoleküle zerstört und Atome ionisert. Daraufhin finden diverse chemische Reaktionen und physikalische Prozesse statt, die teilweise zur Lichtemission durch verschiedene Atome und Moleküle führen. Bedeutend sind z.B. die Beiträge durch Sauerstoff- und Natriumatome sowie Hydroxyl-, Sauerstoff- und Eisenoxidmoleküle. Airglow ist zeitlich und räumlich sehr variabel und die damit verbundenen komplexen Prozesse sind noch nicht vollständig verstanden.Die direkte Erforschung der oberen Atmosphäre ist schwierig, da nur Raketen diese Höhe erreichen können. Daher werden hauptsächlich erd- und satellitengebundene Fernerkundungsmethoden angewendet. Die verbreitetsten Messverfahren erfassen nur einen kleinen Teil des Lichtspektrums, womit viele der gleichzeitigen und teilweise verknüpften Emissionen nicht studiert werden können.Eine bisher wenig genutzte aber vielversprechende Methode zur Airglowmessung sind astronomische Spektren von bodengebundenen Teleskopen. Neben dem Licht vom astronomischen Objekt zeigen diese immer auch atmosphärische Emissionen. Für astronomische Anwendungen müssen diese Beiträge aufwändig entfernt werden, aber für die Atmosphärenforschung sind sie wertvoll, zumal die Spektrographen an großen Teleskopen besonders leistungsfähig sind. Speziell Instrumente, die einen großen Spektralbereich abdecken, erlauben simultane Messungen von vielen verschiedenen Airglowemissionen.Das geplante Projekt wird auf Aufnahmen verschiedener Spektrographen am Very Large Telescope in Nordchile und Apache Point Observatory in New Mexico basieren. Der volle Datensatz, beginnend im Jahr 2000, wird um die 100.000 Spektren umfassen. Er wird viel größer sein als alles was bisher unter Nutzung von astronomischen Daten zur Erdatmosphäre publiziert worden ist.Das Projektziel ist die Charakterisierung der zeitlichen Variationen aller beobachtbaren Airglowemissionen in der oberen Erdatmosphäre mit besonderen Fokus auf (1) Linienemissionen von Hydroxyl- und Sauerstoffmolekülen, besonders im Hinblick auf ihren Wert als Temperaturindikator für die Klimaforschung, (2) Kontinuumsemission von Metall- und Stickoxiden und (3) hochvariablen aber zumeist schwachen Linienemissionen in der Ionosphäre. Die Analyse wird auch Modell-, ergänzende Satelliten- und bodengestützte Daten berücksichtigen. Die dabei gewonnenen Erkenntnisse werden einen signifikanten Beitrag zum Verständnis der chemischen und physikalischen Prozesse in der oberen Atmosphäre, aber auch zur Atom- und Molekülphysik liefern. Mit besseren Modellen der Emissionen wird es auch möglich werden die natürliche Nachthimmelshelligkeit genauer abzuschätzen und astronomische Daten besser zu verarbeiten.

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Potsdam, 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.

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.

Schwerpunktprogramm (SPP) 1294: Bereich Infrastruktur - Atmospheric and Earth system research with the 'High Altitude and Long Range Research Aircraft' (HALO), CoMet (Carbon Dioxide and Methane) Mission

Confronting Climate Change is one of the paramount societal challenges of our time. The main cause for global warming is the increase of anthropogenic greenhouse gases in the Earth's atmosphere. Together, carbon dioxide and methane, being the two most important greenhouse gases, globally contribute to about 81% of the anthropogenic radiative forcing. However, there are still significant deficits in the knowledge about the budgets of these two major greenhouse gases such that the ability to accurately predict our future climate remains substantially compromised. Different feedback mechanisms which are insufficiently understood have significant impact on the quality of climate projections. In order to accurately predict future climate of our planet and support observing emission targets in the framework of international agreements, the investigation of sources and sinks of the greenhouse gases and their feedback mechanisms is indispensable. In the past years, inverse modelling has emerged as a key method for obtaining quantitative information on the sources and sinks of the greenhouse gases. However, this technique requires the availability of sufficient amounts of precise and independent data on various spatial scales. Therefore, observing the atmospheric concentrations of the greenhouse gases is of significant importance for this purpose. In contrast to point measurements, airborne instruments are able to provide regional-scale data of greenhouse gases which are urgently required, though currently lacking. Providing such data from remote sensing instruments supported by the best currently available in-situ sensors, and additionally comparing the results of the greenhouse gas columns retrieved from aircraft to the network of ground-based stations is the mission goal of the HALO CoMet campaign. The overarching objective of HALO CoMet is to improve our understanding and to better quantify the carbon dioxide and methane cycles. Through analysing the CoMet data, scientists will accumulate new knowledge on the global distribution and temporal variation of the greenhouse gases. These findings will help to better understand the global carbon cycle and its influence on climate. These new findings will be utilized for predicting future climate change and assessing its impact. Within the frame of CoMet and due to the operational possibilities we will concentrate on small to sub-continental scales. This does not only allow to identify local emission sources of greenhouse gases, but also opens up the opportunity to use important remote sensing and in-situ data information for the inverse modelling approach for regional budgeting. The project also aims at developing new methodologies for greenhouse gas measurements, and promotes technological developments necessary for future Earth-observing satellites.

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

Gidded Level 3 H2O total columns. The Earth's capacity to sustain life is attributed to two mechanisms: the greenhouse effect and the hydrological cycle. Water vapour in the atmosphere is a critical component of both processes and the main naturally occurring greenhouse gas in the Earth's climate system. Water in gaseous form varies more than other greenhouse gases. Monitoring atmospheric water vapour globally is essential to understand its climate impacts. Measurements of water vapor columns are derived from satellite observations of solar radiation in the ultraviolet and visible (430 – 450 nm) spectral ranges. A water vapour absorption band is detectable across some European Sentinel platforms (Sentinel-4, Sentinel-5P and 5), former (GOME and SCIAMACHY) and future instruments (CO2M). This absorption signature by water vapor is used to derive the shown concentrations with the Differential Optical Absorption Spectroscopy (DOAS) technique. The retrieval methodology, as applied to the fleet of available platforms, demonstrates several advantages, including optimal sensitivity and coverage characteristics across both oceans and continents, enhanced temporal sampling frequency for weather applications, and continuous extension of long-term datasets for climate study purposes. This is accomplished by DLR in the framework of the EUMETSAT's Satellite Application Facility on Atmospheric Composition (AC-SAF) monitoring where DLR generates operational GOME-2 / MetOp products.

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).

G20/2026/027 - Neugenehmigung eines Satelliten-BHKW in 24363 Holtsee

Die Dujos Holtsee GmbH & Co. KG in 24363 Holtsee, Trömbek 2a, plant die Neuanlage eines Satelliten Blockheizkraftwerkes in 24363 Holtsee, Dorfstraße 8a, Gemarkung Holtsee, Flur 3, Flurstücke 35/30 und 72/16. Gegenstand des Genehmigungsantrags sind im Wesentlichen folgende Maßnahmen: • Errichtung eines Blockheizkraftwerkes in einem Gebäude mit einer Feuerungswärmeleistung von 5,913 Megawatt mit dazugehörenden Kühlaggregaten, • Errichtung eines Abgaskamins mit einer Höhe von 22,9 m; • Errichtung eines Warmwasserspeichers mit einer Höhe von 17,50 m und einem Außendurchmesser von 12,73 m mit einem Volumen von 2.000 Kubikmetern, • Errichtung eines AdBlue Tanks mit einem Fassungsvermögen von 4.500 Litern.

The ESA Earth System Model 3.0

The ESA Earth System Model (ESA ESM) provides a synthetic data set of the time-variable global gravity field that includes realistic mass variations in atmosphere, oceans, terrestrial water storage, continental ice sheets, and the solid Earth on a wide set of spatial and temporal frequencies. For more than 10 years already, it is widely applied as a source model in end-to-end simulation studies for future gravity missions, but has been also utilized to study novel gravity observing concepts on the ground. For those purposes, the ESM needs to include a wide range of signals even at very small spatial scales which might not yet have been reliably observed by any active satellite mission. The updated ESA ESM 3.0 improves upon its predecessor by utilizing ECMWF’s ERA5 atmospheric reanalysis along with dedicated simulated ocean bottom pressure data from the MPIOM ocean model. In addition, it offers a small ensemble of co- and post-seismic earthquake signals, an updated GIA model, additional ice mass balance signals from previously not considered Arctic glaciers, sub-monthly surface-mass balance changes and a more realistic representation of ice sheet dynamics. Extreme hydrometeorological events as well as climate-driven and anthropogenic impacts on continental water storage are represented through an update of the hydrological component. Additionally, the ESM separately includes ocean bottom pressure variations along the western slope of the Atlantic, representing variations in the meridional overturning circulation as a critically important component of the interactively coupled global climate system as well as estimated trend signals from sediment erosion and subsequent marine deposition. The ESA ESM 3.0 is available with a 6-hourly resolution from January 2007 until December 2020 in the from of Stokes coefficients up to degree and order 180.

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Berlin-West, 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.

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