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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).

Schwerpunktprogramm (SPP) 1158: Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas; Bereich Infrastruktur - Antarktisforschung mit vergleichenden Untersuchungen in arktischen Eisgebieten, Variation der antarktischen Wolkenkondensationskern- (CCN) und Eiskeim- (INP) Konzentrationen und Eigenschaften an NEumayer III im Vergleich zu deren Werten in der Arktis an der Forschungsstation Villum (VACCINE+)

Das aktuelle Klima der Erde verändert sich schneller, als von den meisten wissenschaftlichen Prognosen vorhergesagt wurde. Dabei erwärmen sich die Polargebiete schnellsten von allen Regionen der Erde. Die Polargebiete haben auch starke globale Auswirkungen auf das Erdklima und beeinflussen daher das Leben und die Lebensgrundlagen auf der ganzen Welt. Trotz der großen Fortschritte der Polarforschung der letzten Jahre gibt es nach wie vor schlecht verstandene Prozesse; einer davon ist die Aerosol-Wolke-Klima-Wechselwirkung, die daher auch nicht zufriedenstellend modelliert werden können. Wolken und deren Wechselwirkungen im Klimasystem sind eine der schwierigsten Komponenten bei der Modellierung, insbesondere in den Polarregionen, da es dort besonders schwierig ist, qualitativ hochwertige Messungen zu erhalten. Die Verfügbarkeit hochwertiger Messungen ist daher von entscheidender Bedeutung, um die zugrunde liegenden Prozesse zu verstehen und in Modelle integrieren zu können. Im ersten Teil des hier vorgeschlagenen Projekts schlagen wir, d.h. TROPOS, vor, die bestehenden Aerosolmessungen an der Neumayer III-Station um in-situ Wolkenkondensationskern- (CCN) und Eiskeim- (INP) Messungen zu erweitern für einen Zeitraum von fast zwei Jahren. Die erfassten Daten wie Anzahl der Konzentrationen, Hygroskopizität, INP-Gefrierspektren usw. werden mit meteorologischen Informationen (z.B. Rückwärtstrajektorien) und Informationen über die chemische Zusammensetzung der vorherrschenden Aerosolpartikel verknüpft, um Quellen für INP und CCN über den gesamten Jahreszyklus zu identifizieren. In einem optionalen dritten Jahr wollen wir die Ergebnisse der südlichen Hemisphäre mit den TROPOS-Langzeitmessungen des CCN und INP aus der Arktis (Villum Research Station) vergleichen, welche uns im Rahmen dieses Projekts von DFG-finanzierten TR 172, AC3, Projekt B04 zur Verfügung stehen werden. Ein Ergebnis des beantragten Projekts wird ein tieferes Verständnis dafür sein, welche Prozesse die CCN- und INP-Population in hohen Breiten dominieren. Die im Rahmen des vorliegenden Projekts gesammelten quantitativen Informationen über CCN und INP in hohen Breiten werden öffentlich zugänglich veröffentlicht, z.B. für die Evaluierung globaler Modelle und Satellitenretrievals.

G20/2025/160 - Neugenehmigung eines BHKW in 24589 Nortorf

Die Stadtwerke Nortorf AöR, Poststraße 21, 24589 Nortorf plant die Neuanlage eines Satelliten Blockheizkraftwerkes in 24589 Nortorf, Heinkenborsteler Weg, Gemarkung Nortorf, Flur 543, Flurstücke 6, 7, 8, 9. Gegenstand des Genehmigungsantrags sind im Wesentlichen folgende Maßnahmen: • Errichtung eines Blockheizkraftwerks in einem Gebäude mit einer Feuerungswärmeleistung von 9,369 Megawatt, mit dazugehörenden Kühlaggregaten, • Errichtung eines Abgaskamins mit einer Höhe von 10,40 m, • Errichtung eines Warmwasserspeichers mit einer Höhe von 16,59 m und einem Außendurchmesser von 16,27 m, einem Volumen von 3.000 Kubikmetern, • Errichtung eines AdBlue Tanks mit einem Fassungsvermögen von 9.000 Litern.

Updated global compilation of coccolithophore calcification measurements from unperturbed water samples including ancillary data

This database expands the Poulton et al., 2018 (doi:10.1594/PANGAEA.888182) database of pelagic calcium carbonate (CP) rate measurements from isotopic tracer uptake in incubated discrete water samples, as discussed in Daniels et al., 2018 (doi:10.5194/essd-10-1859-2018), and accompanies Marsh et al. (in prep.). The database now includes more CP (new data n = 400; complete database n = 3165), net primary production rate (PP) (new data n = 399; complete database n = 3150), total coccolithophore cell counts (new data n = 240; complete database n = 1512), and Emiliania huxleyi cell counts (new data n = 27; complete database n = 612). This expanded database maintains the record of data, including the principal investigator, expedition, OS region, doi reference (where available), collection date and year, sample ID, latitude, longitude, sampling and light depth, and method of measuring CP. We further expand the Poulton et al. (2018) data collection by including ancillary and environmental data, including: optical depth (OD, n = 3165), pHtotal (hereinafter referred to as pHT, n = 398), temperature (n = 1160), salinity (n = 1161), and the concentrations of chlorophyll a (n = 1363), NOx (NO3 or the sum of NO3 + NO2, n = 1161), silicic acid (Si(OH)4, n= 1156), phosphate (PO4, n = 1232), dissolved inorganic carbon (DIC, n = 318), total alkalinity (TA, n = 307), bicarbonate ion concentration (n = 349), and carbonate ion concentration (n = 352). All data was matched to CP, sample bottle identifiers (Niskin bottle numbers), and/or sampling depth values. This global database (81 °N - 64 °S, 132 °E - 174 °W) now covers expeditions and upper ocean measurements (0 - 193 m) from 1989 to 2024. Global in-situ geolocated data spanning time is valuable for modelling, satellite algorithms, and capturing calcium carbonate production in the global ocean. This expanded database, including the environmental, nutrient, chlorophyll a, and carbonate chemistry data, also allows for analysis of factors influencing calcium carbonate production on a global scale. This data amalgamation contributes to understanding the biogeochemistry of the oceans, global carbon cycle, and ocean acidification.

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

Trajectories and sensor data from drifter deployment number 03 during MS FRITZ REUTER and RV HEINCKE cruise HE644

During cruise HE644 (joint campaign of MS FRITZ REUTER and RV HEINCKE), Lagrangian surface drifters (Meyerjürgens et al., 2019; Deyle et al., 2024) were deployed from MS FRITZ REUTER, following the near-surface water motion, therefore allowing for observations within a moving water mass over extended periods with minimal disturbance to the surrounding water. Coordinates of the drifter position were transmitted by a GPS satellite tracker (inReach® Messenger from Garmin Ltd.) at two-minute intervals. Position data was processed after Deyle et al. (2024) and is available on minutely resolution in this dataset. For original trajectories see "<DOI>". In addition, the drifters were equipped with (down to 1.75 m depth) instrument chains including temperature and lightweight CTD (conductivity, temperature, depth) sensors. Depth in water was only recorded by RBRbrevio³ sensors, for others the depth was measured during sensor chain preparation and saved in the data array as fixed depth. The in situ temperature was recorded at up to six different depths using RBRsolo³, RBRbrevio³ (both sample frequency 1-2 Hz) and Aqua TROLL® 100 sensors (sample frequency 1 min-1). Conductivity was measured at up to three different depths, using RBRbrevio³ and Aqua TROLL® 100 sensors. RBR sensors were calibrated to a measurement uncertainty of ± 0.002 °C and ± 0.003 mS cm-1, whereas the TROLL sensors have a measurement uncertainty of ± 0.1 °C and ± 0.5%. For details on the sensor data processing see the appropriate processing report.

Trajectories and sensor data from drifter deployment number 12 during MS FRITZ REUTER and RV HEINCKE cruise HE644

During cruise HE644 (joint campaign of MS FRITZ REUTER and RV HEINCKE), Lagrangian surface drifters (Meyerjürgens et al., 2019; Deyle et al., 2024) were deployed from MS FRITZ REUTER, following the near-surface water motion, therefore allowing for observations within a moving water mass over extended periods with minimal disturbance to the surrounding water. Coordinates of the drifter position were transmitted by a GPS satellite tracker (inReach® Messenger from Garmin Ltd.) at two-minute intervals. Position data was processed after Deyle et al. (2024) and is available on minutely resolution in this dataset. For original trajectories see "<DOI>". In addition, the drifters were equipped with (down to 1.75 m depth) instrument chains including temperature and lightweight CTD (conductivity, temperature, depth) sensors. Depth in water was only recorded by RBRbrevio³ sensors, for others the depth was measured during sensor chain preparation and saved in the data array as fixed depth. The in situ temperature was recorded at up to six different depths using RBRsolo³, RBRbrevio³ (both sample frequency 1-2 Hz) and Aqua TROLL® 100 sensors (sample frequency 1 min-1). Conductivity was measured at up to three different depths, using RBRbrevio³ and Aqua TROLL® 100 sensors. RBR sensors were calibrated to a measurement uncertainty of ± 0.002 °C and ± 0.003 mS cm-1, whereas the TROLL sensors have a measurement uncertainty of ± 0.1 °C and ± 0.5%. For details on the sensor data processing see the appropriate processing report.

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.

Sentinel-5P TROPOMI – Aerosol Index (AI), Level 3 – Global

Aerosol Index (AI) as derived from TROPOMI observations. AI is an indicator for episodic aerosol plumes from dust outbreaks, volcanic ash, and biomass burning. 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.

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Würzburg, 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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