Skip to Main content Skip to Navigation
Journal articles

Historically-based run-time bias corrections substantially improve model projections of 100 years of future climate change

Abstract : Abstract Climate models and/or their output are usually bias-corrected for climate impact studies. The underlying assumption of these corrections is that climate biases are essentially stationary between historical and future climate states. Under very strong climate change, the validity of this assumption is uncertain, so the practical benefit of bias corrections remains an open question. Here, this issue is addressed in the context of bias correcting the climate models themselves. Employing the ARPEGE, LMDZ and CanAM4 atmospheric models, we undertook experiments in which one centre’s atmospheric model takes another centre’s coupled model as observations during the historical period, to define the bias correction, and as the reference under future projections of strong climate change, to evaluate its impact. This allows testing of the stationarity assumption directly from the historical through future periods for three different models. These experiments provide evidence for the validity of the new bias-corrected model approach. In particular, temperature, wind and pressure biases are reduced by 40–60% and, with few exceptions, more than 50% of the improvement obtained over the historical period is on average preserved after 100 years of strong climate change. Below 3 °C global average surface temperature increase, these corrections globally retain 80% of their benefit.
Document type :
Journal articles
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-03263686
Contributor : Françoise Pinsard <>
Submitted on : Friday, June 18, 2021 - 8:06:26 AM
Last modification on : Tuesday, July 13, 2021 - 3:27:29 AM

File

s43247-020-00035-0.pdf
Publication funded by an institution

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Gerhard Krinner, Viatcheslav Kharin, Romain Roehrig, John Scinocca, Francis Codron. Historically-based run-time bias corrections substantially improve model projections of 100 years of future climate change. Communications Earth & Environment, Springer Nature, 2020, 1 (29), ⟨10.1038/s43247-020-00035-0⟩. ⟨hal-03263686⟩

Share

Metrics

Record views

62

Files downloads

73