Automated Author Profile

Amann, Thorben

0000-0001-9347-0615

Current S-Index

18.1

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

3.6

Average Dataset Index per dataset

Total Datasets

5

Total datasets for this author

Average FAIR Score

96.2%

Average FAIR Score per dataset

Total Citations

19

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Chemical weathering of loess - link to GIS data

This dataset includes shapefiles of recent and LGM loess distribution, which were used to quantify chemical weathering fluxes of loess deposits for the LGM, the mid-Holocene and the recent time.

Authors

  • Börker, Janine ;
  • Hartmann, Jens ;
  • Amann, Thorben ;
  • Romero-Mujalli, Gibran ;
  • Moosdorf, Nils ;
  • Jenkins, Chris
0 Citations0 Mentions96% FAIR2.4 Dataset Index
10.1594/pangaea.915792January 2020

Chemical river data from drained loess areas

No description available

Authors

  • Börker, Janine ;
  • Hartmann, Jens ;
  • Amann, Thorben ;
  • Romero-Mujalli, Gibran ;
  • Moosdorf, Nils ;
  • Jenkins, Chris
4 Citations0 Mentions96% FAIR2.4 Dataset Index
10.1594/pangaea.915784January 2020

Alkalinity measurements of a loess column experiment in the laboratory under pCO2 atmospheric conditions

This dataset includes alkalinity measurements of a loess weathering column experiment, which was conducted under laboratory conditions with atmospheric pCO2.

Authors

  • Börker, Janine ;
  • Hartmann, Jens ;
  • Amann, Thorben ;
  • Romero-Mujalli, Gibran ;
  • Moosdorf, Nils ;
  • Jenkins, Chris
0 Citations0 Mentions96% FAIR2.4 Dataset Index
10.1594/pangaea.915790January 2020

Alkalinity measurements of a loess column experiment in the laboratory under pCO2 saturated conditions

This dataset includes alkalinity measurements of a loess weathering column experiment, which was conducted under laboratory conditions with saturated pCO2.

Authors

  • Börker, Janine ;
  • Hartmann, Jens ;
  • Amann, Thorben ;
  • Romero-Mujalli, Gibran ;
  • Moosdorf, Nils ;
  • Jenkins, Chris
0 Citations0 Mentions96% FAIR1.0 Dataset Index
10.1594/pangaea.915791January 2020

Global Unconsolidated Sediments Map Database v1.0 (shapefile and gridded to 0.5° spatial resolution)

Mapped unconsolidated sediments cover half of the global land surface. They are of considerable importance for many Earth surface processes like weathering, hydrological fluxes or biogeochemical cycles. Ignoring their characteristics or spatial extent may lead to misinterpretations in Earth System studies. Therefore, a new Global Unconsolidated Sediments Map database (GUM) was compiled, using regional maps specifically representing unconsolidated and quaternary sediments. The new GUM database provides insights into the regional distribution of unconsolidated sediments and their properties. The GUM comprises 911,551 polygons and describes not only sediment types and subtypes, but also parameters like grain size, mineralogy, age and thickness, where available. Previous global lithological maps or databases lacked detail for reported unconsolidated sediment areas or missed large areas, and reported a global coverage of 25 to 30%, considering the ice-free land area. Here, alluvial sediments cover about 23% of the mapped total ice-free area, followed by aeolian sediments (~21%), glacial sediments (~20%), and colluvial sediments (~16%). A specific focus during the creation of the database was on the distribution of loess deposits, since loess is highly reactive and relevant to understand geochemical cycles related to dust deposition and weathering processes. An additional layer compiling pyroclastic sediment is added, which merges consolidated and unconsolidated pyroclastic sediments. The compilation shows latitudinal abundances of sediment types related to climate of the past.

Authors

  • Börker, Janine ;
  • Hartmann, Jens ;
  • Amann, Thorben ;
  • Romero-Mujalli, Gibran
15 Citations0 Mentions96% FAIR9.9 Dataset Index
10.1594/pangaea.884822January 2018