API src

Found 3123 results.

Related terms

Multibeam bathymetry processed data (EM 1002 echosounder entire dataset) of RV MARIA S. MERIAN during cruise MSM62/2

Swath sonar bathymetry data used for that dataset was recorded during RV MARIA S. MERIAN cruise MSM62/2 using Kongsberg EM1002 multibeam echosounder. The cruise took place between 23.03.2017 and 27.03.2017 in the Baltic Sea. The cruise aimed to investigate the impact of the Littorina transgression on the inflow of saline waters into the western Baltic and assessed the potential for future diminution of ventilation in the central and northern deeper basins due to isostatic uplift [CSR]. CI Citation: Paul Wintersteller (seafloor-imaging@marum.de) as responsible party for bathymetry raw data ingest and approval. During the MSM62/2 cruise, the moonpooled KONGSBERG EM1002 multibeam echosounder (MBES) was utilized to perform bathymetric mapping in shallow depths. The echosounder has a curved transducer in which 111 beams are formed for each ping while the seafloor is detected using amplitude and phase information for each beam sounding. For further information on the system, consult https://www.km.kongsberg.com/. Postprocessing and products were conducted by the Seafloor-Imaging & Mapping group of MARUM/FB5, responsible person Paul Wintersteller (seafloor-imaging@marum.de). The open source software MB-System (Caress, D. W., and D. N. Chayes, MB-System: Mapping the Seafloor, https://www.mbari.org/products/research-software/mb-system, 2017) was utilized for this purpose. A sound velocity correction profile was applied to the MSM62/2 data; there were no further corrections for roll, pitch and heave applied during postprocessing. A tide correction was applied, based on the Oregon State University (OSU) tidal prediction software (OTPS) that is retrievable through MB-System. CTD measurements during the cruise were sufficient to represent the changes in the sound velocity throughout the study area. Using Mbeditviz, artefacts were cleaned manually. NetCDF (GMT) grids of the edited data as well as statistics were created with mbgrid. The published bathymetric EM1002 grid of the cruise MSM62/2 has a resolution of 15 m. No total propagated uncertainty (TPU) has been calculated to gather vertical or horizontal accuracy. A higher resolution is, at least partly, achievable. The grid extended with _num represents a raster dataset with the statistical number of beams/depths taken into account to create the depth of the cell. The extended _sd -grid contains the standard deviation for each cell. The DTMs projections are given in Geographic coordinate system Lat/Lon; Geodetic Datum: WGS84.

Water exploitation index, plus (WEI+), (2000-2023)

An indicator comparing water use versus renewable freshwater resources as percentage in a given area and time resolution e.g. annual water scarcity at country level.

The forecast data for u component of wind at 850hPa [m/s] from GPC_Offenbach (DWD).

This resource contains the monthly mean u component of wind at 850hPa [m/s] for 6 months. 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) on about the 15th of each month. 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 forecast 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.

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

This resource contains the monthly mean sea surface temperature [K] for 6 months. 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) on about the 15th of each month. 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 forecast 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.

The forecast data for precipitation [kg/m^2] from GPC_Offenbach (DWD).

This resource contains the monthly mean precipitation [kg/m^2] for 6 months. 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) on about the 15th of each month. 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 forecast 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.

The hindcast data for u component of wind at 850hPa [m/s] from GPC_Offenbach (DWD).

This resource contains the monthly mean u component of wind at 850hPa [m/s] 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.

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.

The hindcast data for 500hPa geopotential height [gpm] from GPC_Offenbach (DWD).

This resource contains the monthly mean 500hPa geopotential height [gpm] 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.

Zwei Quellen erschließen: Die konjunktive Nutzung von Grund- und Oberflächenwasser in der Landwirtschaft Nordwestchinas

In Nordchina ist im Laufe des letzten halben Jahrhunderts die Nutzung des Grundwassers für die Agrarproduktion rasant gestiegen, allen voran in Gebieten, die zuvor mit Oberflächenwasser bewässert worden waren. Obwohl sich die Grundwasserförderung positiv auf den ländlichen Wohlstand auswirkt, hat sie oft negative Folgen für die Nachhaltigkeit lokaler Wassernutzung. Es wird behauptet, dass ein koordinierteres Management von Regenwasser - und Grundwasservorrat und -aufbewahrung - die sogenannte Verbundwassernutzung (conjunctive management) - zu einer nachhaltigeren, adaptiven Nutzung der Ressourcen führt. Das Forschungsvorhaben analysiert die Auswirkung der lokalen Grund- und Oberflächenwasserpolitik auf die Wassernutzung der Landwirte. Basierend auf einer Haushaltsstudie, welche in drei Binnenflussbecken in Nordwestchina durchgeführt wurde, wird bestimmt, welche physischen und welche institutionellen Wasserzugangsindikatoren am entscheidendsten für die Wahl der Wassernutzung durch die Bauern sind. Zusätzlich zur Haushaltsstudie werden Interviews mit Wasserbehörden und anderen Personen in Schlüsselpositionen geführt, um Einblicke in Politikmaßnahmen und Institutionen im Wassereinzugsgebiet zu erhalten. Durch das Vergleichen der Gewässerpolitiken mit den Produktionsergebnissen auf Betriebsebene, wird untersucht, in welchem Umfang die Verbundwassernutzung in die Praxis umgesetzt wird.

EU Climate Policy Tracker

The EU Climate Policy Tracker (EU CPT) presents up-to-date developments in climate and energy policies in the EU-27. Although government policy is the single most influential driver behind the fight against climate change, there is limited information about the status of the policies that influence increases or decreases in emissions. The EU Climate Policy Tracker (EU CPT) is intended to bridge this gap. The project holds two references in focus at the same time: a 2050 goal of near total decarbonisation, and our current policy trajectory. A uniquely developed scoring method, modelled on appliance efficiency labels (A-G), gives an indication of how Member States are doing compared to a low-carbon policy package. This results in aggregated scores, supported with a rich background of information, for all Member States, at EU level, and for different economic sectors. The project is intended to be a resource for those seeking information, a means of sharing best practice, and a way of holding policymakers to account. In 2011 we updated our initial rating from November 2010. The findings of 2010 showed that the average score across the EU was an E, indicating that the level of effort needed to treble to be on track to reach the 2050 vision. Looking at the developments in 2011, we can see that there has been considerable activity in many countries, though the overall scoring has generally remained constant: positive actions are counteracted by negative developments or budget cuts. The EU CPT is a joint project by Ecofys and WWF. The project is funded by the European Climate Foundation. Visit the EU Climate Policy Tracker on: www.climatepolicytracker.eu.

1 2 3 4 5 … 311 312 313