File

lange2020_lpj-guess_hadgem2-es_ewembi_picontrol_histsoc_co2_pew_global_annual_1861_2005.nc4

ISIMIP2b DerivedOutputData lange2020 hadgem2-es historical lpj-guess pew 20210127

Cite as

Stefan Lange, Jan Volkholz, Tobias Geiger, Fang Zhao, Iliusi Vega del Valle, Ted Veldkamp, Christopher Reyer, Lila Warszawski, Veronika Huber, Jonas Jägermeyr, Jacob Schewe, David N. Bresch, Matthias Büchner, Jinfeng Chang, Philippe Ciais, Marie Dury, Kerry Emanuel, Christian Folberth, Dieter Gerten, Simon N. Gosling, Manolis Grillakis, Naota Hanasaki, Alexandra‐Jane Henrot, Thomas Hickler, Yasushi Honda, Akihiko Ito, Nikolay Khabarov, Aristeidis Koutroulis, Wenfeng Liu, Christoph Müller, Kazuya Nishina, Sebastian Ostberg, Hannes Müller Schmied, Sonia I. Seneviratne, Tobias Stacke, Jörg Steinkamp, Wim Thiery, Yoshihide Wada, Sven Willner, Hong Yang, Minoru Yoshikawa, Chao Yue, Katja Frieler (2020): Land area fractions and population fractions exposed to extreme climate impact events derived from ISIMIP2b output data (v1.0). ISIMIP Repository. https://doi.org/10.48364/ISIMIP.924045

Properties

  • Path
    ISIMIP2b/DerivedOutputData/Lange2020/LPJ-GUESS/hadgem2-es/historical/lange2020_lpj-guess_hadgem2-es_ewembi_picontrol_histsoc_co2_pew_global_annual_1861_2005.nc4
  • ISIMIP ID
    7778bd83-5888-4f6f-a1b6-ee0840990abc
    Size
    26.3 MB
    Checksum (sha512)
    377cc840c91ea5f54c2aa4fc05bca60716d61a92499ca08069c0fe220c539ef9b8279c07152ec0fe59a3c7a21cb0cefb41373214b6687aae74b2ef81d3a59588
    Version
    20210127

Specifiers

Simulation round
ISIMIP2b
Data product
Derived Output Data
Publication
Lange et al. 2020
Impact model
LPJ-GUESS
Climate forcing
HadGEM2-ES
Period
Historical
Bias adjustment
EWEMBI
Climate experiment
picontrol
Direct human forcing experiment
histsoc
Sensitivity experiment
co2
Variable
pew
Region
Global
Time step
annual
Start year
1861
End year
2005

Rights

CC0 1.0 Universal Public Domain Dedication
CC0 1.0 Universal Public Domain Dedication (CC0 1.0)
When using ISIMIP data for your research, please appropriately credit the data providers, e.g. either by citing the DOI for the dataset, or by appropriate acknowledgment. We strongly encourage to offer co-authorship to at least a representative of the data providers. Further information can be found in our terms of use.

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