Objective weather types of Deutscher Wetterdienst derived from different Reanalysis and Global Climate Model simulations for the control run (1951-2000) and the projection period (2000-2100). On the one hand, the dataset is useful for evaluation of representative circulation statistics in Central Europe, on the other hand, for the analysis of future weather types due to climate change. Added temperature and precipitation data allow to study the weather type effectiveness for these important climate parameters.
Das NABO hat grundsaetzlich zwei Aufgaben wahrzunehmen: Die landesweite Erfassung und Beurteilung typischer Schadstoffbelastungen der Boeden. Das Verfolgen der zeitlichen Entwicklung als Voraussetzung zur Frueherkennung und Prognose moeglicher Bodenbelastungen durch Schadstoffe. Das NABO ist ein Referenzmessnetz. Es dient als Entscheidungsgrundlage und Erfolgskontrolle vorsorglicher Bodenschutzmassnahmen.
DWD’s fully automatic MOSMIX product optimizes and interprets the forecast calculations of the NWP models ICON (DWD) and IFS (ECMWF), combines these and calculates statistically optimized weather forecasts in terms of point forecasts (PFCs). Thus, statistically corrected, updated forecasts for the next ten days are calculated for about 5400 locations around the world. Most forecasting locations are spread over Germany and Europe. MOSMIX forecasts (PFCs) include nearly all common meteorological parameters measured by weather stations. For further information please refer to: [in German: https://www.dwd.de/DE/leistungen/met_verfahren_mosmix/met_verfahren_mosmix.html ] [in English: https://www.dwd.de/EN/ourservices/met_application_mosmix/met_application_mosmix.html ]
Objective weather types of Deutscher Wetterdienst derived from different Reanalysis and Global Climate Model simulations for the control run (1951-2000) and the projection period (2000-2100). Furthermore, the NAO-index is also provided. On the one hand, the dataset is useful for evaluation of representative circulation statistics in Central Europe, on the other hand, for the analysis of future weather types due to climate change. Added temperature and precipitation data allow to study the weather type effectiveness for these important climate parameters.
Objective weather types of Deutscher Wetterdienst derived from different Reanalysis and Global Climate Model simulations for the control run (1951-2000) and the projection period (2000-2100). Forthermore, the NAO-index is also provided. On the one hand, the dataset is useful for evaluation of representative circulation statistics in Central Europe, on the other hand, for the analysis of future weather types due to climate change. Added temperature and precipitation data allow to study the weather type effectiveness for these important climate parameters.
Dieser Datenbestand dient der Analyse atmosphärischer Zirkulationsbedingungen (Wetterlagen, NAO) im nordatlantisch-mitteleuropäischen Sektor wie sie von Reanalyse- und globalen Klimamodellen (Status: 2010) simuliert werden. Ausgewählt wurden solche Klimamodelläufe, die für Mitteleuropa oder Deutschland regionalisiert wurden. Mit dem Datenbestand kann einerseits die Eignung der verschiedenen Modelle zur Reproduktion der beobachteten Zirkulationsverhälnisse (1950-2000) geprüft werden. Andererseits können simulierte Änderungen (2001-2100) ausgewertet werden. Zusätzlich werden Temperatur -und Niederschlagsdaten bereitgestellt, mit denen die Wetterwirksamkeit der Wetterlagen je GCM bewertet werden kann.
SEMISYS is the Sensor Meta Information System of the German Research Centre for Geosciences. The precise analysis of GNSS observation data is based upon a variety of metadata from different sources, including station and satellite metadata. A high evaluation quality must be ensured by the consistency and integrity of this metadata. The station and satellite metadata are currently maintained in ASCII based files that make the extraction of key information used for the data evaluation difficult. To get rid of the restrictions caused by the file based metadata management, the Operational Data Center (ODC) group of the GFZ developed a Sensor Meta Information System (semisys) for the central, format independent and validated storage of station and satellite metadata based upon client/server technology and an object-relational database. The following processing related metadata is currently stored in semisys: * Station metadata extracted from IGS site logs (for different projects) * Processed station coordinates (EPOS) and ocean loading values (calculated by Onsala Space Observatory) * Hardware metadata (receiver, antenna, radome) * Satellite parameter for GPS, GLONASS, Galileo, BeiDou, QZSS and SBAS * Notice Advisories for GPS, GLONASS and Galileo (NANU, NAGU) * ANTEX for GPS, GLONASS and Galileo
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