File

lange2020_lpj-guess_ipsl-cm5a-lr_ewembi_rcp26_2005soc_co2_pew_global_annual_2006_2099.nc4

ISIMIP2b DerivedOutputData lange2020 ipsl-cm5a-lr future 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/ipsl-cm5a-lr/future/lange2020_lpj-guess_ipsl-cm5a-lr_ewembi_rcp26_2005soc_co2_pew_global_annual_2006_2099.nc4
  • ISIMIP ID
    ef98d6f0-0000-4595-821a-f9523fd5931d
    Size
    18.7 MB
    Checksum (sha512)
    f332d7f0bf9205c5257aba79517b61b82e5bc5166d728db30bf3e8e3fbed52bc6ebde5c2d323c788fa76c7323e436c246899e671e55923fb83ec00e7f0a49053
    Version
    20210127

Specifiers

Simulation round
ISIMIP2b
Data product
Derived Output Data
Publication
Lange et al. 2020
Impact model
LPJ-GUESS
Climate forcing
IPSL-CM5A-LR
Period
Future
Bias adjustment
EWEMBI
Climate experiment
rcp26
Direct human forcing experiment
2005soc
Sensitivity experiment
co2
Variable
pew
Region
Global
Time step
annual
Start year
2006
End year
2099

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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