Articles | Volume 16, issue 4
https://doi.org/10.5194/cp-16-1493-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-16-1493-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An empirical evaluation of bias correction methods for palaeoclimate simulations
Robert Beyer
CORRESPONDING AUTHOR
Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
Mario Krapp
Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
Andrea Manica
Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
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85 citations as recorded by crossref.
- Performance of bias corrected monthly CMIP6 climate projections with different reference period data in Turkey S. Oruc
- Assessing the impact of artificial snowmaking on Dagu Glacier variation: a case study from a tourism glacier Y. Xie et al.
- Regional Climate Review: CMIP6 GCM Precipitation Patterns in Northeast India A. Paul & S. Maji
- Water Resources Evaluation and Sustainability Considering Climate Change and Future Anthropic Demands in the Arequipa Region of Southern Peru J. Quiroz et al.
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- Bayesian hierarchical model for bias-correcting climate models J. Carter et al.
- Seasonal Spatial Distribution Patterns of Abralia multihamata in the East China Sea Region: Predictions Under Various Climate Scenarios M. Xu et al.
- Evaluating statistical and machine learning bias-correction methods for CMIP6 rainfall projections in a tropical megacity N. Miniandi et al.
- Evaluation of four gridded climate products for streamflow and drought simulations in the Kelantan River Basin, Malaysia H. Du et al.
- High-resolution Canada domain disturbance forcings suitable for land surface modeling applications J. Beaver et al.
- Climate change increases the interannual variance of summer crop yields globally through changes in temperature and water supply J. Proctor et al.
- A combined wavelet analysis-quantile mapping (WA-QM) method for bias correction: capturing the intra-annual temporal patterns in climate model precipitation simulations and projections X. Wu et al.
- Climatic windows for human migration out of Africa in the past 300,000 years R. Beyer et al.
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- Assessing agricultural drought risk under CMIP6 scenarios using hybrid AI models and satellite-derived TVDI M. Zare et al.
- Introduction of the BiasAdjustCXX command-line tool for the application of fast and efficient bias corrections in climatic research B. Schwertfeger et al.
- Different environmental variables predict body and brain size evolution in Homo M. Will et al.
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- Climate-driven Mediterranean fire hazard assessments for 2020–2100 on the light of past millennial variability M. Lestienne et al.
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- A statistics-based reconstruction of high-resolution global terrestrial climate for the last 800,000 years M. Krapp et al.
- Large-Scale Hydrological Models and Transboundary River Basins C. Skoulikaris
- Anthropogenic climate change will likely outpace coral range expansion N. Vogt-Vincent et al.
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- High performance computing to support land, climate, and user‐oriented services: The HIGHLANDER Data Portal M. Bottazzi et al.
- Modeling and assessing the impacts of climate change on groundwater recharge in endorheic basins of Northwest China W. Cheng et al.
- Selecting CMIP6 precipitation models by integrating relative importance metrics, compromise programming index, and Jenks optimized classification F. Ershadfath et al.
- Development of a prey-predator species distribution model for a large piscivorous fish: A case study for Japanese Spanish mackerel Scomberomorus niphonius and Japanese anchovy Engraulis japonicus S. Liu et al.
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- Continental-scale bias correction and random forest downscaling of CMIP6 precipitation across Europe S. Doshi et al.
- Climate change drives fish communities: Changing multiple facets of fish biodiversity in the Northwest Pacific Ocean S. Liu et al.
- Exploration of short-term predictions and long-term projections of Barents Sea cod biomass using statistical methods on data from dynamical models M. Koseki et al.
- Assessment of future photovoltaic power potential across the Qinghai-Tibet Plateau from the perspective of energy demand M. Duan et al.
- A 1 km monthly dataset of historical and future climate changes over China X. Hu et al.
- Future drought projections with CMIP6 in Eğirdir Lake basin (Türkiye) E. Şener & A. Davraz
- Landslide Susceptibility Mapping under the Climate Change Impact in the Chania Regional Unit, West Crete, Greece C. Nefros et al.
- Efficient photovoltaic power prediction to achieve carbon neutrality in China J. Gao et al.
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- A Multi Criteria Decision Analysis Approach for Regional Climate Model Selection and Future Climate Assessment in the Mono River Basin, Benin and Togo N. Hounguè et al.
- More is not always better: delta-downscaling climate model outputs from 30 to 5 min resolution has minimal impact on coherence with Late Quaternary proxies L. Timbrell et al.
- Assessing the impacts of climate and land cover change on groundwater recharge in a semi-arid region of Southern India N. Chandra & S. Sahoo
- Bias correction of daily precipitation from climate models, using the Q‐GAM method G. Lazoglou et al.
- A Large Ensemble Global Dataset for Climate Impact Assessments X. Gao et al.
- Global Climate Classification and Comparison to Mid-Holocene and Last Glacial Maximum Climates, with Added Aridity Information and a Hypertropical Class B. Hanberry
- Uncertainty-based saltwater intrusion prediction using integrated Bayesian machine learning modeling (IBMLM) in a deep aquifer J. Yin et al.
- Will climate change inevitably disrupt the cryospheric budget dynamics of the Third Pole? L. Ying et al.
Saved (final revised paper)
Latest update: 16 May 2026
Short summary
Even the most sophisticated global climate models are known to have significant biases in the way they simulate the climate system. Correcting model biases is therefore essential for creating realistic reconstructions of past climate that can be used, for example, to study long-term ecological dynamics. Here, we evaluated three widely used bias correction methods by means of a global dataset of empirical temperature and precipitation records from the last 125 000 years.
Even the most sophisticated global climate models are known to have significant biases in the...