Deutsch
 
Benutzerhandbuch Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Robust identification of local biogeophysical effects of land-cover change in a global climate model

MPG-Autoren

Winckler,  Johannes
IMPRS on Earth System Modelling, MPI for Meteorology, Max Planck Society;
Emmy Noether Junior Research Group Forest Management in the Earth System, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

/persons/resource/persons37304

Reick,  Christian H.
Global Vegetation Modelling, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

/persons/resource/persons37296

Pongratz,  Julia
Emmy Noether Junior Research Group Forest Management in the Earth System, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)

jcli-d-16-0067%2E1.pdf
(Verlagsversion), 5MB

Ergänzendes Material (frei zugänglich)
Zitation

Winckler, J., Reick, C. H., & Pongratz, J. (2017). Robust identification of local biogeophysical effects of land-cover change in a global climate model. Journal of Climate, 30, 1159-1176. doi:10.1175/JCLI-D-16-0067.1.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-002C-45EC-E
Zusammenfassung
Land-cover change (LCC) happens locally. However, in almost all simulation studies assessing biogeophysical climate effects of LCC, local effects (due to alterations in a model grid box) are mingled with nonlocal effects (due to changes in wide-ranging climate circulation). This study presents a method to robustly identify local effects by changing land surface properties in selected “LCC boxes” (where local plus nonlocal effects are present), while leaving others unchanged (where only nonlocal effects are present). While this study focuses on the climate effects of LCC, the method presented here is applicable to any land surface process that is acting locally but is capable of influencing wide-ranging climate when applied on a larger scale. Concerning LCC, the method is more widely applicable than methods used in earlier studies. The study illustrates the possibility of validating simulated local effects by comparison to observations on a global scale and contrasts the underlying mechanisms of local and nonlocal effects. In the MPI-ESM, the change in background climate induced by extensive deforestation is not strong enough to influence the local effects substantially, at least as long as sea surface temperatures are not affected. Accordingly, the local effects within a grid box are largely independent of the number of LCC boxes in the isolation approach.