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. The operational NO2 total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The operational NO2 tropospheric column products are generated using the algorithm GDP (GOME Data Processor) version 4.x for NO2 [Valks et al. (2011)] integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The total NO2 column is retrieved from GOME solar back-scattered measurements in the visible wavelength region using the DOAS method. An additional algorithm is applied to derive the tropospheric NO2 column: after subtracting the estimated stratospheric component from the total column, the tropospheric NO2 column is determined using an air mass factor based on monthly climatological NO2 profiles from the MOZART-2 model. 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. 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. The operational HCHO total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. 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/
Waldökosysteme sind vielfältigen Belastungen ausgesetzt. Um rechtzeitig ungünstigen Entwicklungen entgegensteuern zu können, ist eine fortlaufende Überwachung des Waldzustandes notwendig. Dieses forstliche Umweltmonitoring erfolgt in Rheinland-Pfalz mit Hilfe von landesweiten Übersichtserhebungen (Level-I: Kronenzustandserhebung, Bodenzustandserhebung oder Waldernährungserhebung auf einem systematischen Raster) und anhand von Intensivuntersuchungen an Waldökosystem-Dauerbeobachtungsflächen (Level-II kontinuierliche Messungen der Luftschadstoffbelastung und der Witterungsverläufe sowie eine fortlaufende Beobachtung der Reaktionen der Waldökosysteme auf natürliche und anthropogene Stresseinflüsse an ausgewählten für die wichtigsten Waldstandorte in Rheinland-Pfalz charakteristischen Flächen). Erfasst werden u.a.: Kronenzustand (terrestrisch und aus IRC-Luftbildern); Waldwachstum; Nährstoffversorgung; Bodenvegetation; Bodenzustand; Baumflechten; Feinwurzeln; Mykorrhiza; Streufall; Ozonschadsymptome; Phänologie; Klima; Witterung; Luftschadstoffimmission; Luftschadstoffdeposition; Bodenwasser; Quellwasser. Anhand dieser Ergebnisse erfolgen Bewertungen zu den Themen: Wasserhaushalt, Bioelementhaushalt, Bodenversauerung, Stickstoffsättigung, Überschreitungen der ökologischen Belastungsgrenzen durch Luftschadstoffe (critical loads, AOT 40 etc.). Alle wesentlichen Befunde und umfangreiche Bewertungen können auch unter www.fawf.wald-rlp.de und hier unter: Forschungsschwerpunkte/Forstliches Umweltmonitoring eingesehen werden.
The IUKD23 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IU): Upper air T1T2A1 (IUK): Radio soundings from fixed land stations (up to 100 hPa) A2 (D): 90°E - 0° northern hemisphere(The bulletin collects reports from stations: 10184;Greifswald;) (Remarks from Volume-C: High resolution 2 sec., BUFR309057) IUKD23 BUFR bulletin available 10184 Greifswald from EDZW (Deutscher Wetterdienst) up to 100 hPa at 00 UTC, 12 UTC, ON DEMAND 06 UTC, 18 UTC
The IUKD27 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IU): Upper air T1T2A1 (IUK): Radio soundings from fixed land stations (up to 100 hPa) A2 (D): 90°E - 0° northern hemisphere(The bulletin collects reports from stations: 10739;Stuttgart (Schnarrenberg);) (Remarks from Volume-C: High resolution 2 sec., BUFR309057) IUKD27 BUFR bulletin available 10739 Stuttgart from EDZW (Deutscher Wetterdienst) up to 100 hPa. at 00 UTC, 12 UTC, ON DEMAND 06 UTC, 18 UTC
Über dem Nordatlantik und Europa wird die Variabilität der großräumigen Wetterbedingungen von quasistationären, langandauernden und immer wiederkehrenden Strömungsmustern â€Ì sogenannten Wetterregimen â€Ì geprägt. Diese zeichnen sich durch das Auftreten von Hoch- und Tiefdruckgebieten in bestimmten Regionen aus. Verlässliche Wettervorhersagen auf Zeitskalen von einigen Tagen bis zu einigen Monaten im Voraus hängen von einer korrekten Darstellung der Lebenszyklen dieser Strömungsregime in Computermodellen ab. Um das zu erreichen müssen insbesondere Prozesse, die günstige Bedingungen zur Intensivierung von Tiefdruckgebieten aufrecht erhalten, und Prozesse, die den Aufbau von stationären Hochdruckgebieten (blockierende Hochs) begünstigen, richtig wiedergegeben werden. Aktuelle Forschung deutet stark darauf hin, dass Atmosphäre-Ozean Wechselwirkungen, insbesondere entlang des Golfstroms, latente Wärmefreisetzung in Tiefs, und Kaltluftausbrüche aus der Arktis dabei eine entscheidende Rolle spielen. Dennoch mangelt es an grundlegendem Verständnis wie solche Luftmassentransformationen über dem Ozean die großskalige Höhenströmung beeinflussen. Darüber hinaus ist die Relevanz solcher Prozesse für Lebenszyklen von Wetterregimen unerforscht. In dieser anspruchsvollen drei-jährigen Kollaboration zwischen KIT und ETH Zürich streben wir an ein ganzheitliches Verständnis zu entwickeln, wie Wärmeaustausch zwischen Ozean und Atmosphäre und diabatische Prozesse in der Golfstromregion die Variabilität der großräumigen Strömung über dem Nordatlantik und Europa prägen. Zu diesem Zweck werden wir ausgefeilte Diagnostiken zur Charakterisierung von Luftmassen mit neuartigen Diagnostiken zur Bestimmung des atmosphärischen Energiehaushaltes verbinden und damit den Ablauf von Wetterregimen und Regimewechseln in aktuellen hochaufgelösten numerischen Modelldatensätzen und mit Hilfe von eigenen Sensitivitätsstudien untersuchen. Dazu werden wir unsere Expertise in größräumiger Dynamik und Wettersystemen, sowie Atmosphäre-Ozean Wechselwirkungen â€Ì insbesondere während arktischen Kaltluftausbrüchen â€Ì und der Lagrangeâ€Ìschen Untersuchung atmosphärischer Prozesse nutzen. Im Detail werden wir (i) ein dynamisches Verständnis entwickeln, wie Luftmassentransformationen entlang des Golfstroms die Höhenströmung über Europa beeinflussen, mit Fokus auf blockierenden Hochdruckgebieten, (ii) die Bedeutung von Luftmassentransformationen und diabatischer Prozesse für den Erhalt von Bedingungen, die die Intensivierung von Tiefdruckgebieten während bestimmter Wetterregimelebenszyklen bestimmen, untersuchen, (iii) diese Erkenntnisse in ein einheitliches und quantitatives Bild vereinen, welches die Prozesse, die den Einfluss des Golfstroms auf die großräumige Wettervariabilität prägen, zusammenfasst und (iv) die Güte dieser Prozesse in aktuellen numerischen Vorhersagesystemen bewerten. Diese Grundlagenforschung wird wichtige Erkenntnisse zur Verbesserung von Wettervorhersagemodellen liefern.
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. The operational BrO (Bromine monoxide) total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. For more details please refer to https://atmos.eoc.dlr.de/app/missions/gome2
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. The operational ozone total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The new improved DOAS-style (Differential Optical Absorption Spectroscopy) algorithm called GDOAS, was selected as the basis for GDP version 4.0 in the framework of an ESA ITT. GDP 4.x performs a DOAS fit for ozone slant column and effective temperature followed by an iterative AMF / VCD computation using a single wavelength. 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. 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/
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 optical thickness is computed using libRadtran [Mayer and Kylling (2005)] radiative transfer simulations taking as input the cloud-top albedo retrieved with ROCINN. 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/
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