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METOP GOME-2 - Cloud Top Pressure (CTP) - 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. OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks) are used for retrieving the following geophysical cloud properties from GOME and GOME-2 data: cloud fraction (cloud cover), cloud-top pressure (cloud-top height), and cloud optical thickness (cloud-top albedo). OCRA is an optical sensor cloud detection algorithm that uses the PMD devices on GOME / GOME-2 to deliver cloud fractions for GOME / GOME-2 scenes. ROCINN takes the OCRA cloud fraction as input and uses a neural network training scheme to invert GOME / GOME-2 reflectivities in and around the O2-A band. VLIDORT [Spurr (2006)] templates of reflectances based on full polarization scattering of light are used to train the neural network. ROCINN retrieves cloud-top pressure and cloud-top albedo. The cloud-top pressure for GOME scenes is derived from the cloud-top height provided by ROCINN and an appropriate pressure profile. 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/

Master tracks in different resolutions during POLAR 5 campaign P5-256_COMPEX-EC_2025

Raw data acquired by GPS1 position sensors on board research aircraft Polar 5 during the campaign P5-256_COMPEX-EC_2025 were processed to receive a validated master track which can be used as reference of further expedition data. Novatel FlexPak6 GPS receiver was used as navigation sensors during the campaign. Data were downloaded from AWI Datamanagement System (https://dms.awi.de) with a resolution of 1 sec. Processed data are provided as a master track with 1 sec resolution and a generalized track with a reduced set of the most significant positions of the master track. A detailed report on processing is also available for each flight.

Analyse des Potentials mechanischer Unkrautbekaempfung

Die Arbeiten aus dem vorhergehenden Zeitraum wurden fortgefuehrt. Wiederum erwies sich die Rollhacke mit zusaetzlichen Hackscharen wegen ihrer geringen Verstopfungsneigung und hohen Flaechenleistung auch fuer Rueben als gut geeignet. Der Vorauflaufeinsatz von Striegeln brachte gute Ergebnisse. Der Einsatz einer modifizierten Hacke brachte selbst bei Getreide (12 cm Reihenabstand) in Marokko so gute Erfolge, dass mechanische Verfahren auch kostenmaessig gut mit chemischen Verfahren konkurrieren koennen. Die Technikwirkungsanalyse einer in Entwicklung befindlichen selektiven, sensorgesteuerten Reihenhackmaschine erwies sich beim Maiseinsatz pflanzenbaulich-oekonomisch der Feldspritze ebenbuertig, oekologische jedoch deutlich ueberlegen.

Timeline - Land Surface Temperature (Mean) Level 3 - Europe, Monthly

This dataset provides monthly maximum Land Surface Temperature (LST) values over Europe, derived from 1-km AVHRR observations. The data is generated by DLR and provided in the framework of the TIMELINE project. LST values are retrieved using physically-based split- and mono-window algorithms and corrected for atmospheric influences and surface emissivity. Only cloud-free observations with sensor view angles below 50 degrees are used. Due to reliance on infrared observations, data may be limited under persistent cloud cover. To ensure temporal consistency across sensors and overpass times, an orbit drift correction method was applied. This method harmonizes LST values to a fixed reference time of 13:00 local solar time, approximating the daily maximum temperature. The dataset is gridded in a 1-km LAEA ETRS89 projection. The product is provided in four tiles, covering the extent of the European Environmental Agency (EEA) reference grid, which includes the area from 900 000 m East and 900 000m North to 7 400 000m East and 5 500 000m North. The TIMELINE (TIMe Series Processing of Medium Resolution Earth Observation Data assessing Long-Term Dynamics In our Natural Environment) project, led by the German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR), focuses on generating a consistent, multi-decadal time series derived from NOAA and Metop AVHRR data. Spanning more than 40 years from the early 1980s to the present this dataset covers Europe and North Africa. TIMELINE establishes an operational environment for the systematic reprocessing of AVHRR raw data into Level 1b, Level 2, and Level 3 geoinformation products at 1.1 km spatial resolution. These products maintain uniform standards in format, projection, and spatial coverage. The dataset includes a comprehensive suite of land and atmospheric parameters such as atmospherically corrected surface reflectance, NDVI, snow cover, fire hotspots, burnt area, land and sea surface temperatures, and various cloud physical properties (e.g., cloud top temperature). By combining traditional and innovative remote sensing products with robust processing algorithms and state-of-the-art validation techniques, TIMELINE provides a unique, high-quality dataset for global change research.

Master tracks in different resolutions of HEINCKE cruise HE664, Bremerhaven - Bremerhaven, 2025-07-05 - 2025-07-20

Raw data acquired by position sensors on board RV Heincke during expedition HE664 were processed to receive a validated master track which can be used as reference of further expedition data. During HE664 the inertial navigation system IXSEA PHINS III and the GPS receivers Trimble Marine SPS461 and SAAB R5 SUPREME NAV were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.awi.de) with a resolution of 1 sec. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.

DE HH INSPIRE WFS SWIS Sensoren

Dieser Web Feature Service (WFS) stellt die Standorte der von der Freien und Hansestadt Hamburg betriebenen Sensoren des Straßenwetterinformationssystems SWIS zum Download bereit. Zur genaueren Beschreibung der Daten und Datenverantwortung nutzen Sie bitte den Verweis zur Datensatzbeschreibung.

DE HH INSPIRE WMS SWIS Sensoren

Dieser Web Map Service (WMS) stellt die Standorte der von der Freien und Hansestadt Hamburg betriebenen Sensoren des Straßenwetterinformationssystems SWIS dar. Zur genaueren Beschreibung der Daten und Datenverantwortung nutzen Sie bitte den Verweis zur Datensatzbeschreibung.

Tracing the Fate of Contaminants in a Model Ecosystem

Scientists from the Palestinian authority, Israel and Germany, all involved in different aspects of analytical research, have joined in order to conduct an environmental study, which aims to understand the fate of selected contaminants in a model ecosystem. For this purpose, two typical terrestrial sites in the Middle East, one in the Palestinian authority and the other in Israel, have been selected, comprising a partially polluted area and a natural reserve as a reference. In these areas, the fate (chemical and physical transformations) of typical pollutants such as heavy metals (Pb, Cu, Zn, Cd, Fe), metalloids (As, Sn, Sb), organic dyes and air contaminants (O3, NOx, SO2) will be studied. This will also involve the determination of all the environmental conditions for the chemical transformation, which should shed some light on the dynamics of the ecosystems. At the same time novel inexpensive sensors and analytical procedures will be developed, which are necessary for the analysis of contaminants in this area. The goals will be accomplished by combined efforts of all partners.

Umweltbundesamt - Feinstaubemissionen der Partikelgröße PM10

Stäube sind feste Teilchen der Außenluft, die nicht sofort zu Boden sinken, sondern eine gewisse Zeit in der Atmosphäre verweilen. Nach ihrer Größe werden Staubpartikel in verschiedene Klassen eingeteilt. Als Feinstaub (PM10) bezeichnet man Partikel mit einem aerodynamischen Durchmesser von weniger als 10 Mikrometer (µm). Dargestellt wird der Durchschnitt aller Messwerte eines Sensors der letzten Stunde.

openSenseMap: Sensor Box idrop-f18037

Visualized position. Position does not represent exact sample coordinates. Do not use data set as point data.

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