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LTER Zöbelboden, Austria, Soil water chemistry 2014
No full textSoil water chemistry of two forest stands in the site LTER Zöbelboden from the year 201
TOAR timeseries of ground-level ozone at station XiangGeLiLa (XGLL), China
No full textTimeseries of 1-hourly measurements of ground-level ozone at station XiangGeLiLa (XGLL), China.
These data were provided by Prof.Dr. Xiaobin Xu of Key Laboratory for Atmospheric Chemistry (KLAC), Chinese Academy of Meteorological Sciences (CAMS), China Meteorological Administration (CMA) in the context of the Tropospheric Ozone Assessment Report (TOAR).
For further information about TOAR see http://www.igacproject.org/activities/TOAR.
An uptodate record of this data can be found in the TOAR database at https://toar-data.fz-juelich.de/api/getCoverage/?id=48239&sampling_method=hourly (not yet implemented)This timeseries belongs to the collection http://doi.org/10.34730/6d0dcdd6e04e4e62a73ede44da9c076c of TOAR datasets from station XiangGeLiLa (XGLL), China.The data are formatted as a csv file with variable header information. Each header line begins with # and contains key: value metadata elements.
The data file was generated by the TOAR database query https://toar-data.fz-juelich.de/api/getCoverage/?id=XGLL&sampling_method=hourly&version_tag=1.0 (not yet implemented).
A detailed description of the file format and the metadata elements can be found at: https://toar-data-portal.fz-juelich.de/docs/surfacedata/TOAR_file_format_v2.pdf (not yet implemented).
Software tools for working with these data are available at https://jugit.fz-juelich.de/m.schultz/toar-public-utilities
LTER Tatrzanski National Park, Vegetation Data 2001-2019
No full textVegetation survey data of the 0,25 ha study area at the Tatrzanski National Park, Poland (LTER_EU_PL_017) between the years 2001 and 2019. The percentage cover of every vascular plant was determined on permanently marked subplots (25 m²) in the 120-year-old spruce stand
Density of phytoplankton in Lake Santo Parmense (may 1990)
No full textDataset provides phytoplankton densities recorded in Lake Santo Parmense on one date in may 1990. Samples were collected by means of a Ruttner bottle at different depths over the whole water column at the point of maximum depth of the lake. An integrated sample was subsequently obtained by combining equal proportions of samples collected at the various depths and phytoplankton were identified and counted with an inverted microscope according to Utermöhl (1958)
LTER Zöbelboden, Austria, Runoff Water Chemistry, 2018
No full textRunoff water chemistry data of the LTER station Zöbelboden from the year 201
TOAR data collection at station AKeDaLa (AKDL), China
No full textCollection of air quality (and meteorological) measurement data at station AKeDaLa (AKDL), China.
These data were provided by Prof.Dr. Xiaobin Xu of Key Laboratory for Atmospheric Chemistry (KLAC), Chinese Academy of Meteorological Sciences (CAMS), China Meteorological Administration (CMA) in the context of the Tropospheric Ozone Assessment Report (TOAR).
For further information about TOAR see http://www.igacproject.org/activities/TOAR.
An uptodate record of this data collection can be found in the TOAR database at https://toar-data.fz-juelich.de/api/getStationMeta/?id=AKDL (not yet implemented)The data contained in this collection are formatted as csv files with variable header information. Each header line begins with # and contains key: value metadata elements.
The data files in this collection were generated by TOAR database queries. For details, see technical information provided with each single station series.TOAR timeseries of ground-level ozone at station AKeDaLa (AKDL), China: http://doi.org/10.34730/2e09b60f05c04df3afb90e0c9a165d1
LTER Zöbelboden, Austria, Litterfall chemistry, 2014
No full textLitterfall chemistry data of the LTER station Zöbelboden from the year 201
LTER Zöbelboden, Austria, Soil water chemistry 2015
No full textSoil water chemistry of two forest stands in the site LTER Zöbelboden from the year 2015
TOAR timeseries of ground-level ozone at station Shangdianzi (SDZ54421), China
No full textTimeseries of 1-hourly measurements of ground-level ozone at station Shangdianzi (SDZ54421), China.
These data were provided by Prof.Dr. Xiaobin Xu of Key Laboratory for Atmospheric Chemistry (KLAC), Chinese Academy of Meteorological Sciences (CAMS), China Meteorological Administration (CMA) in the context of the Tropospheric Ozone Assessment Report (TOAR).
For further information about TOAR see http://www.igacproject.org/activities/TOAR.
An uptodate record of this data can be found in the TOAR database at https://toar-data.fz-juelich.de/api/getCoverage/?id=SDZ54421&sampling_method=hourly (not yet implemented)This timeseries belongs to the collection http://doi.org/10.34730/f4e3583024e84467aa7c2d24d5f4861d of TOAR datasets from station Shangdianzi (SDZ54421), China.The data are formatted as a csv file with variable header information. Each header line begins with # and contains key: value metadata elements.
The data file was generated by the TOAR database query https://toar-data.fz-juelich.de/api/getCoverage/?id=48233&sampling_method=hourly&version_tag=1.0 (not yet implemented).
A detailed description of the file format and the metadata elements can be found at: https://toar-data-portal.fz-juelich.de/docs/surfacedata/TOAR_file_format_v2.pdf (not yet implemented).
Software tools for working with these data are available at https://jugit.fz-juelich.de/m.schultz/toar-public-utilities
IntelliO3-ts: Source code and data
No full textHere we provide the source code and required data sets to reproduce all results related to "IntelliO3-ts v1.0: A neural network approach to predict near-surface ozone concentrations in Germany" by F. Kleinert, L. H. Leufen and M. G. Schultz, submitted to GMD (gmd-2020-169).
You can untar the file by executing `tar -xzvf IntelliO3-ts.tar.gz`.
The README includes all installation instructions.
IntelliO3-ts-tar.gz contains source code and data, while IntelliO3-ts_source-code-only.tar.gz is identical to https://gitlab.version.fz-juelich.de/toar/machinelearningtools/-/tree/IntelliO3-ts-v1.0_initial-submit
The License for the source code is included in the tar.gz files and available through the GitLab link above