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Grundwassermessstelle APP_GWMN_665

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_665 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper N8 : Südholstein. Es liegen insgesamt 22716 Messwerte vor. Es liegen außerdem 8 Probenentnahmen vor (siehe Resourcen).

Area Management, Restriction, Regulation Zones and Reporting Units / Maränengewässer in Brandenburg

Der Datensatz Area Management, Restriction, Regulation Zones and Reporting Units / Maränengewässer in Brandenburg ist die Datengrundlage der interoperablen INSPIRE-Darstellungs- (WMS) und Downloaddienste (WFS): - Maränengewässer in Brandenburg - INSPIRE View-Service AM (WMS-AM-MG) - Maränengewässer in Brandenburg - INSPIRE Download-Service AM (WFS-AM-MG) Der Dienst stellt die Flächen der Maränengewässer Brandenburgs zum Download bereit. Dabei erfolgte eine sog. Schematransformation und Belegung der INSPIRE-relevanten Attribute. Der Datensatz Area Management, Restriction, Regulation Zones and Reporting Units / Maränengewässer in Brandenburg ist die Datengrundlage der interoperablen INSPIRE-Darstellungs- (WMS) und Downloaddienste (WFS): - Maränengewässer in Brandenburg - INSPIRE View-Service AM (WMS-AM-MG) - Maränengewässer in Brandenburg - INSPIRE Download-Service AM (WFS-AM-MG) Der Dienst stellt die Flächen der Maränengewässer Brandenburgs zum Download bereit. Dabei erfolgte eine sog. Schematransformation und Belegung der INSPIRE-relevanten Attribute.

Forschungsgruppe (FOR) 2589: Zeitnahe Niederschlagsschätzung und -vorhersage; Near-Realtime Quantitative Precipitation Estimation and Prediction (RealPEP), sub project: Coordination Funds

High-quality near-real time Quantitative Precipitation Estimation (QPE) and its prediction for the next hours (Quantitative Precipitation Nowcasting, QPN) is of high importance for many applications in meteorology, hydrology, agriculture, construction, water and sewer system management. Especially for the prediction of floods in small to meso-scale catchments and of intense precipitation over cities timely, the value of high-resolution, and high-quality QPE/QPN cannot be overrated. Polarimetric weather radars provide the undisputed core information for QPE/QPN due to their area-covering and high-resolution observations, which allow estimating precipitation intensity, hydrometeor types, and wind. Despite extensive investments in such weather radars, QPE is still based primarily on rain gauge measurements since more than 100 years and no operational flood forecasting system actually dares to employ radar observations for QPE. RealPEP will advance QPE/QPN to a stage, that it verifiably outperforms rain gauge observations when employed for flood predictions in small to medium-sized catchments. To this goal state-of-the?art radar polarimetry will be sided with attenuation estimates from commercial microwave link networks for QPE improvement, and information on convection initiation and evolution from satellites and lightning counts from surface networks will be exploited to improve QPN. With increasing forecast horizons the predictive power of observation-based nowcasting quickly deteriorates and is outperformed by Numerical Weather Prediction (NWP) based on data assimilation, which fails, however, for the first hours due to the lead time required for model integration and spin-up. Thus, RealPEP will merge observation-based QPN with NWP towards seamless prediction in order to provide optimal forecasts from the time of observation to days ahead. Despite recent advances in simulating surface and sub-surface hydrology with distributed, physicsbased models, hydrologic components for operational flood prediction are still conceptual, need calibration, and are unable to objectively digest observational information on the state of the catchments. RealPEP will prove that in combination with advanced QPE/QPN physics-based hydrological models sided with assimilation of catchment state observations will outperform traditional flood forecasting in small to meso-scale catchments.

Hydroklima, Variabilität und Telekonnektionen im Bereich des tropischen Atlantik und Pazifik während des letzten Interglazials und des Holozäns - Erkenntnisse aus der Erdsystemmodellierung und Korallendaten (TAPIOLA)

Die Dynamik von Atmosphäre und Ozean in den Tropen stellt ein wichtiges Element des heutigen Erdsystems dar. Wie sich die Tropen jedoch unter anthropogenem Einfluss zukünftig verändern werden, unterliegt großen Unsicherheiten.Daher schlagen wir vor, aus der Paläoperspektive Warmzeiten des Klimas der Vergangenheit mithilfe des iCESM1.2-Erdsystemmodells zu untersuchen, welches explizit Wasserisotope simuliert. Das Design dieser Zeitscheibenexperimente ist auf verschiedene Abschnitte des letzten Interglazials und des mittleren bis späten Holozäns zugeschnitten und erlaubt es, die vom Modell simulierte Saisonalität und interannuelle Variabilität des Hydroklimas mit Daten aus einem einzigartigen Satz fossiler Flachwasserkorallen zu vergleichen. Diese wurden bei Bonaire (Südliche Karibik) gewonnen und liefern Informationen über Meeresoberflächentemperaturen (SST) und Variationen des hydrologischen Kreislaufs in vergangenen Warmzuständen.Die explizite Darstellung von Wasserisotopen im Modell erlaubt einen direkten Vergleich mit den Korallendaten und eine detailliertere Beschreibung des hydrologischen Kreislaufs in vergangen Warmphasen.Im letzten Interglazial folgte die aus Korallen angezeigte Saisonalität der SST in der Karibik der orbital angetriebenen Einstrahlung. Es wurde bisher kaum untersucht, wie interannuelle Variabilität auf unterschiedliche Nuancen interglazialen Antriebs reagiert und ob die Korallensignale auch dekadische Variabilität in der Karibik widerspiegeln. Hier erwarten wir neue Erkenntnisse aus der vom Modell simulierten Variabilität und eine erweiterte Interpretation des Hydroklima-Signals aus fossilen Korallen.Aus dem späten bis mittleren Holozän existieren fossile Korallen für sehr ähnliche Zeitabschnitte sowohl aus der Karibik als auch aus dem tropischen Pazifik, was großes Potential bietet, um die atmosphärische Brücke und die Kovariabilität zwischen den beiden Ozeanbecken aus Korallen- und Modellperspektive zu untersuchen.Die globalen Modellsimulationen werden neue Erkenntnisse zu interannueller Klimavariabilität in der Karibik und ihrer Kopplung mit dem tropischen Atlantik und Pazifik für vergangene Warmzeiten erlauben, was aus Korallendaten allein nicht möglich ist. Wir werden die Hypothese testen, dass das wichtigste Phänomen interannueller Klimavariabilität, das El-Niño/Southern-Oscillation-Phänomen (ENSO), und damit verbundene Fernwirkungen wesentlich zur interannuellen Klimavariabilität in der Karibik beitragen und die unterschiedlichen Ausprägungen von ENSO dabei von Bedeutung sind. Ferner sollen die Modellsimulationen genutzt werden, ENSO-Dynamik und ENSO-Fernwirkungen in vergangenen Warmzeiten zu untersuchen. Dies ist von großer Relevanz in Anbetracht der Unsicherheiten, wie ENSO und das tropische Hydroklima auf den zukünftigen Klimawandel reagieren werden.

Grundwassermessstelle APP_GWMN_646

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_646 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper EL15 : Bille - Altmoränengeest Süd. Es liegen insgesamt 31046 Messwerte vor. Es liegen außerdem 30 Probenentnahmen vor (siehe Resourcen).

Interview about the 35th GRDC anniversary on the BfG website

Question: Dr Mischel, why was GRDC set up, and how long has it been hosted by BfG? Dr Simon Mischel: GRDC has been hosted by BfG since 1988. However, its origins lie in the first Global Atmospheric Research Programme, for which the WMO collected discharge data in the early 1980s. In actual fact, the primary aim of this programme was to collect physical parameters to gain a better understanding of processes in the atmosphere. However, it quickly became clear that discharge data plays a huge role in improving understanding of the climate. To begin with, this initial data set, which forms the core of GRDC, was hosted by LMU Munich. To establish a permanent service provision, the WMO mandated BfG, a departmental research institute of the German Federal Government, to set up GRDC. Finally, on 14 November 1988, the Global Runoff Data Centre was officially established at BfG in Koblenz under the auspices of the WMO. What is the main function of GRDC, and where does the data come from? Ever since it was set up, the core function of GRDC has been to collect and maintain historical river discharge data and make this available for international research projects. The data comes primarily from the national hydrological services in the WMO member states. Data is transmitted on a voluntary basis, but various WMO resolutions encourage the member states to supply data to GRDC. Support from the WMO is therefore hugely important to us. Once we’ve received the data, we check it, convert it into a standardised format and add it to our database. Users anywhere in the world can then download the data via the GRDC data portal. We have been working successfully in this way – as a facilitator between producers and us-ers of hydrological data – for some 35 years. We have also been a key partner in a number of data collection and data management projects. Why is discharge data important, and for which studies is it used? The “discharge” hydrological parameter is an important variable, both in the global water cycle and for water resource management. Moreover, discharge is also a relevant climate variable, since the flow of freshwater into oceans has an impact on temperature distribution, the salt content of the seas and oceanographic circulation systems. According to our statistics, over the last two years, GRDC data was requested by users from more than 130 countries. Around three quarters of all the associated studies are connected to the climate or hydrometeorology, and the data is frequently used to calibrate and validate numerical models, such as in relation to hydrological drought and flood monitoring services. Users range from students who need the data for a thesis or dissertation to international research programmes and organisations conducting global studies. GRDC itself is also involved in some of these studies, such as the WMO “State of Global Water Resources” report and the “Global Climate Observing System (GCOS)” report, the findings of which directly inform UN Climate Change Conferences. How good is the data coverage, and in what resolution is the data available? GRDC hosts the most extensive global database of quality-controlled discharge data – year-book data or historical data. We collect only daily and monthly mean values – no unverified real-time data is collected. We currently have discharge data from approximately 10,700 stations in 160 countries in the database. Most of these stations are in Europe and North America, and the average time-record length is 40 years. The longest time record, which originates from the Dresden station on the Elbe, dates back to 1806. It is important that we map data sets that are as long and complete as possible for climate research and hydrological modelling. We particularly include data from stations that reflect the hydrology of a river or region. Stations located in the estuaries of major rivers are also important for better quantifying the volume of freshwater entering our oceans. Stations where there is minimal human influence are also valuable and attract a great deal of interest in relation to global change and climate change. Discharge is just one of many important hydrological parameters. Are there other global data centres? GRDC works in close collaboration with the International Centre for Water Resources and Global Change (ICWRGC), which is based at BfG. ICWRGC also hosts two other global water data centres, namely the GEMS/Water Data Centre (GWDC), which collects water quality data on behalf of the United Nations Environment Programme, and the International Soil Moisture Network ISMN. In Germany, there is also the Global Precipitation Climatology Centre (GPCC), which is operated by Germany’s National Meteorological Service DWD. World-wide, there are also other global water data centres, which are collectively responsible for collecting different parameters relating to the hydrological cycle (e.g. for groundwater, isotopes, lake observations and glacier observations). These are operated by other nations and under the auspices of various organisations. They are important partner data centres for us, and we work in close collaboration with them in the context of the Global Terrestrial Network – Hydrology (GTN-H), which is hosted in the ICWRGC under a mandate from the WMO. The GTN-H is a Global Climate Observing System (GCOS) programme. In this international network, we are a strong partner in the UN-Water “family” and contribute towards United Nations reporting. As the new head of GRDC, which challenges are you looking forward to? As the new head, I am naturally keen to successfully carry forward the GRDC brand – a brand that is held in high esteem all over the world – and to continue looking after and expanding existing collaborations. To give you some examples, these particularly include contact with our users, data suppliers, the WMO as patron, ICWRGC as an international partner at BfG and our partner data centres. However, as a team, we are, of course, also aware of the very fast technical progress that is being made in relation to data and digitalisation. For example, the global call for open and large datasets that comply with the FAIR (findable, accessible, interoperable, reusable) principles is constantly growing. We are therefore already working, step by step, on making GRDC “fair”. This includes use of free software and offering our users access to data via data repositories and programming interfaces. A recent milestone in this respect is the publication of the Caravan dataset. With this, we can offer researchers a partial dataset of free GRDC stations, including meteorological data and river basin attributes. Our aim is to develop GRDC as a digital service provider for global discharge data and operate it at BfG on the basis of reliable data infrastructure.

The hindcast data for sea surface temperature [K] from GPC_Offenbach (DWD).

This resource contains the monthly mean sea surface temperature [K] for 6 months. The period of hindcast data is January, 1993 - December, 2019. The format of resource is GRIB2. It is provided through the web site of WMO Lead Centre for LRF MME (Long Range Forecast Multi-Model Ensemble). The web site requests a user account. The Grade A(GPCs) and Grade B(NMHSs, RCCs) users can download the data USAGE: Menu: Data and Plot > Data Exchange > Search/Download. This hindcast data is made by GPC_Offenbach (DWD) using an operational seasonal prediction system. For more detailed information about the seasonal forecasts of GPC_Offenbach (DWD) visit the web site http://www.dwd.de/EN/ourservices/seasonals_forecasts/start.html.

Grundwassermessstelle APP_GWMN_300

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_300 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper EI14 : Eider/Treene - Geest. Es liegen insgesamt 43975 Messwerte vor. Es liegen außerdem 47 Probenentnahmen vor (siehe Resourcen).

Grundwassermessstelle APP_GWMN_310

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_310 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper ST15 : Trave - Nordwest. Es liegen insgesamt 37725 Messwerte vor. Es liegen außerdem 4 Probenentnahmen vor (siehe Resourcen).

Inorganic geochemistry of sedimentary rocks in the catchment of river Thuringian Saale during the last 600 Ma

A literature retrieval was performed for whole rock geochemical analyses of sedimentary, magmatic and metamorphic rocks in the catchment of River Thuringian Saale for the past 600 Ma. Considering availability and coincidence with paleontological an facies data the following indicators seem suitable to detect environmental and climatic changes: biogenic P for Paleoproductivity, STI Index for weathering intensity, Ni/Co-ratio for redox conditions, relative enrichments of Co, Ba and Rb versus crustal values for volcanic activity at varying differentiation. The Mg/Ca-ratio as proxy for salinity is applicable in evaporites. The binary plot Nb/Y versus Zr/TiO2 indicates a presently eroded volcanic level of the Bohemian Massif as catchment area for the Middle Bunter, whereas higly differentiated volcanics provided source material for Neoproterozoic greywackes. A positive Eu-anomaly is limited to the Lower Bunter and implies mafic source rocks perhaps formerly located in the Bohemian Massif.

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