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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.

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.

Shipboard Automated Meteorological and Oceanographic System (SAMOS) air-sea fluxes, version 3, 2005-2024

Along ship track bulk turbulent heat and momentum fluxes derived using one-minute interval data collected by the Shipboard Automated Meteorological and Oceanographic System (SAMOS) initiative. The fluxes are provided as three products derived using three widely accepted air-sea flux algorithms (Smith 1988, COARE 3.6, and a 2023 update of Bourassa 2006). Datasets are organized by ship and flux algorithm. The dataset uses SAMOS data from 47 research vessels with observations spanning 2005-2024. Data include heat and momentum fluxes, state variables adjusted to 10 meters, and multiple inputs and outputs from the flux algorithms. These data have wide use for satellite product and model evaluation; air-sea interaction, marine biology, chemistry and geoscience research activities; climate science, and marine geoinformatics. Data coverage is the global oceans, but is concentrated around North America. Fluxes are derived from along cruise track navigational, meteorological, and oceanographic observations from 47 research vessels. Fluxes are derived at one-minute intervals (the same as the source observations) and take advantage of extensive quality control flags on the source SAMOS data. Additional QC flags are applied to the derived fluxes, height adjusted state variables, and other outputs of the flux algorithms. All data are provided in CF and ACDD compliant netCDF files, with extensive metadata. The uncompressed data volume is ca. 180 GB per algorithm.

Natural Forest Management in Caracarai, Roraima, Brazil

Objectives: Sustainable management of tropical moist forests through private forest owners will become increasingly important. Media report that in Brazil, particularly in Amazonia, approx. 80 percent of the timber harvested is from illegal sources. Private management of forests according to internationally acknowledged standards offers an opportunity to significantly lower the portion of illegally cut timber. Moreover, it contributes significantly to the conservation of the Amazon forest. Private forest owners show a clear long-term commitment towards the implementation of management standards according that is ecologically compatible, socially acceptable and economically viable. The project area, a pristine forest in legal Amazonia in the transition zone between moist tropical forests and savannas (cerrado), is extremely diverse in floristic and faunistic terms. The institute cooperates with the private forest owner. Main tasks are to document the faunistic and floristic diversity, to calculate the Annual Allowable Cut and to elaborate concepts for site-specific silviculture. Results: To date (Oct. 2006) the following activities were started: - a comprehensive inventory system for planning at the FMU-level has been successfully introduced; - the inventory system for the annual coupe area has been designed and data for the first coupe are being processed; - the annual allowable cut is currently calculated based on the results of the above described inventories; - two fauna surveys are completed; one focusing on large mammals and one on the avi-fauna. A long-term monitoring concept to assess the influence of forest management on the faunistic diversity is currently under development; - forest zoning is completed applying terrestrial surveys and interpreting high-resolution satellite images; - a study on the use of Bethollethia excelsa-fruits (Brazil nuts) is currently implemented; - a study on timber properties of lesser known species is currently implemented.

Shipboard Automated Meteorological and Oceanographic System (SAMOS) air-sea fluxes, version 2, 2005-2015

Along ship track bulk turbulent heat and momentum fluxes derived using one-minute interval data collected by the Shipboard Automated Meteorological and Oceanographic System (SAMOS) initiative. The fluxes are provided as three products derived using three widely accepted air-sea flux algorithms (Smith 1988, COARE 3.5, and a 2013 update of Bourassa 2006). Datasets are organized by ship and flux algorithm. The dataset uses SAMOS data from 19 research vessels with observations spanning 2005-2015. Data include heat and momentum fluxes, state variables adjusted to 10 meters, and multiple inputs and outputs from the flux algorithms. These data have wide use for satellite product and model evaluation; air-sea interaction, marine biology, chemistry and geoscience research activities; climate science, and marine geoinformatics. The data are concentrated in the oceans around North America, but select data are available from most ocean basins. Fluxes are derived from along cruise track navigational, meteorological, and oceanographic observations from 19 research vessels. Fluxes are derived at one-minute intervals (the same as the source observations) and take advantage of extensive quality control flags on the source SAMOS data. Additional QC flags are applied to the derived fluxes, height adjusted state variables, and other outputs of the flux algorithms. All data are provided in CF and ACDD compliant netCDF files, with extensive metadata. The uncompressed data volume is ca. 5 GB.

Großräumige Analyse von Verbuschungsflächen mit NOAA-AVHRR-Daten in Namibia

Seit 1979 erfassen Satelliten der NOAA-Serie die Erde und liefern damit eine der längsten kontinuierlichen Bild-Datenreihen von Satelliten überhaupt. Durch ihre großflächige Abdeckung, ihre hohe zeitliche Auflösung und ihren kostengünstigen Empfang eignen sich diese Daten hervorragend zum Monitoring. Bislang werden diese langen Zeitreihen noch kaum herangezogen, um langfristige Veränderungen von Oberflächenphänomenen zu beschreiben, denn der Großteil der Fernerkundungsarbeiten beschäftigt sich mit neueren Sensoren und deren Anwendungen. Gerade vor dem Hintergrund der Landdegradierung durch unangepaßte Landnutzung in den Trockenräumen der Erde sollten die vorhandenen archivierten Datenreihen zur Langzeitanalyse aber genutzt werden und die Ergebnisse in Konzepte des Landmanagements einfließen. In Namibia vollzieht sich in den Nationalparks und dem Weideland die Landdegradierung durch eine massive Verbuschung, v.a. mit Acacia mellifera. Die Verbuschungsdynamik der letzten 20 Jahre soll in Etosha mit NOA-AVHRR-Daten erfasst werden. Die Ergebnisse aus dem Etosha-Nationalpark können dann zum Monitoring der Verbuschung in Namibia von örtlichen Institutionen eingesetzt werden. So ist die Inwertsetzung der Daten gewährleistet und durch die Weiterentwicklung der NOAA-Serie durch das MODIS-System auch für die Zukunft gewährleistet.

Oberflächenmodelle Hamburg - Höhenveränderung

Der Datensatz "Oberflächenmodelle Hamburg - Höhenveränderungen" stellt die mittleren Bodenbewegungen in einem ausgewählten Gebiet dar. Die Einheit ist dabei [mm/Jahr]. Um die angezeigten Informationen in dieser Genauigkeit zu erhalten werden Radardaten des TerraSAR-X-Satelliten mittels Radarinterferometrie über einen langen Zeitraum (Für den aktuellen Datensatz: 2015 bis 2024) ausgewertet und mittels eines komplexen Rechenprozesses verarbeitet. Die mittleren Bodenbewegungen werden zusätzlich jeweils aus allen Messpunkten innerhalb einer Zelle eines 35m-Raster über den gesamten Zeitreihenverlauf approximiert, sofern mehr als 15 Punkte in einem Raster vorliegen. Der hier gezeigte Datensatz soll einen Überblick über die Bodenbewegungen der letzten Dekade in Hamburg geben. Bei Fragen zum Datensatz, für detaillierte Auswertungen aus den Ursprungsdaten oder für Anfragen zu Radardaten wenden sie sich gerne an: fernerkundung@gv.hamburg.de

Nachtaufnahme Hamburg

Bei dieser Nachtaufnahme handelt es sich um ein Mosaik, welches aus zwei unterschiedlichen Datensätzen besteht. Datensatz 1 [Zentrum und Randgebiete] - Satellitenaufnahmen: Jilin-1 - Spektrale Auflösung: RGB - Aufnahmezeitraum: 12/21 – 01/22 - Quelle: Chang Guang Satellite Technology CO., LTD (CGSTL)/Veritas Imagery Services Ltd Datensatz 2 [vereinzelte Randgebiete] - Astronautenphotographie: NASA - Spektrale Auflösung: RGB - Aufnahmezeitraum: 03/22 - Quelle: Earth Science and Remote Sensing Unit, NASA Johnson Space Center; https://eol.jsc.nasa.gov/ Hinweise: Die Datensätze unterscheiden sich hinsichtlich ihrer geometrischen Auflösung. Die Datensätze sind spektral nicht zueinander kalibriert. Verwendung nur zu Visualisierungszwecken.

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