Articles | Volume 17, issue 4
https://doi.org/10.5194/gmd-17-1765-2024
https://doi.org/10.5194/gmd-17-1765-2024
Development and technical paper
 | 
28 Feb 2024
Development and technical paper |  | 28 Feb 2024

Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space

Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita

Related authors

Evaluation of statistical climate reconstruction methods based on pseudoproxy experiments using linear and machine-learning methods
Zeguo Zhang, Sebastian Wagner, Marlene Klockmann, and Eduardo Zorita
Clim. Past, 18, 2643–2668, https://doi.org/10.5194/cp-18-2643-2022,https://doi.org/10.5194/cp-18-2643-2022, 2022
Short summary
Heinrich events show two-stage climate response in transient glacial simulations
Florian Andreas Ziemen, Marie-Luise Kapsch, Marlene Klockmann, and Uwe Mikolajewicz
Clim. Past, 15, 153–168, https://doi.org/10.5194/cp-15-153-2019,https://doi.org/10.5194/cp-15-153-2019, 2019
Short summary
The effect of greenhouse gas concentrations and ice sheets on the glacial AMOC in a coupled climate model
Marlene Klockmann, Uwe Mikolajewicz, and Jochem Marotzke
Clim. Past, 12, 1829–1846, https://doi.org/10.5194/cp-12-1829-2016,https://doi.org/10.5194/cp-12-1829-2016, 2016
Short summary

Related subject area

Climate and Earth system modeling
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024,https://doi.org/10.5194/gmd-17-3667-2024, 2024
Short summary
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024,https://doi.org/10.5194/gmd-17-3507-2024, 2024
Short summary
cfr (v2024.1.26): a Python package for climate field reconstruction
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024,https://doi.org/10.5194/gmd-17-3409-2024, 2024
Short summary
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024,https://doi.org/10.5194/gmd-17-3433-2024, 2024
Short summary
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024,https://doi.org/10.5194/gmd-17-3385-2024, 2024
Short summary

Cited articles

Barboza, L., Li, B., Tingley, M. P., and Viens, F. G.: Reconstructing past temperatures from natural proxies and estimated climate forcings using short- and long-memory models, Ann. Appl. Stat., 8, 1966–2001, 2014. a
Christiansen, B., Schmith, T., and Thejll, P.: A surrogate ensemble study of climate reconstruction methods: Stochasticity and robustness, J. Climate, 22, 951–976, https://doi.org/10.1175/2008JCLI2301.1, 2009. a
Clement, A., Bellomo, K., Murphy, L. N., Cane, M. A., Mauritsen, T., Rädel, G., and Stevens, B.: The Atlantic Multidecadal Oscillation without a role for ocean circulation, Science, 350, 320–324, https://doi.org/10.1126/science.aab3980, 2015. a
Download
Short summary
Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.