diff --git a/README-pypi.md b/README-pypi.md deleted file mode 100644 index be5d934..0000000 --- a/README-pypi.md +++ /dev/null @@ -1,90 +0,0 @@ -# SBCK (Statistical Bias Correction Kit) - -## Features -- python3 and R version -- c++ independent files for Sparse Histogram -- Implement classic methods of bias correction (see [8,9] for the definition of bias correction) -- Quantile Mapping [5,7,14], parametric and non parametric version -- CDFt methods [6] -- OTC and dOTC methods [9] -- R2D2 method [11] -- MBCn method [4] -- QDM method [3] -- MRec method [1] -- ECBC method [12] -- TSMBC method [15], for autocorrelations. - -## How to select a bias correction method ? - -This summary of ability of each method to perform a bias correction is proposed by François, (2020). Please refer to -this article for further interpretation. - -| Characteristics | CDF-t | R2D2 | dOTC | MBCn | MRec | -|---------------------------------------------| :-----: | :----: | :----: | :----: | :----: | -| Correction of univariate dist. prop. | Yes | Yes | Yes | Yes | Yes | -| Modification of correlations of the model | No | Yes | Yes | Yes | Yes | -| Capacity to correct inter-var. prop. | No | Yes | Yes | Yes | Yes | -| Capacity to correct spatial prop. | No | Yes | Yes | ~ | ~ | -| Capacity to correct temporal prop. | No | No | No | No | No | -| Preserve the rank structure of the model | Yes | ~ | ~ | ~ | ~ | -| Capacity to correct small geographical area | n.a. | Yes | Yes | Yes | Yes | -| Capacity to correct large geographical area | n.a. | ~ | ~ | ~ | No | -| Allow for change of the multi-dim. prop. | Yes | No | Yes | ~ | Yes | - - -## Python instruction - -Requires: -- python3 -- [Eigen](http://eigen.tuxfamily.org/index.php?title=Main_Page) -- numpy -- scipy -- pybind11 - -For python, just use the command: -``` -pip3 install . -``` - -If the Eigen library is not found, use: -``` -pip3 install . eigen="path-to-eigen" -``` - -## License - -Copyright(c) 2021 / 2023 Yoann Robin - -This file is part of SBCK. - -SBCK is free software: you can redistribute it and/or modify -it under the terms of the GNU General Public License as published by -the Free Software Foundation, either version 3 of the License, or -(at your option) any later version. - -SBCK is distributed in the hope that it will be useful, -but WITHOUT ANY WARRANTY; without even the implied warranty of -MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -GNU General Public License for more details. - -You should have received a copy of the GNU General Public License -along with SBCK. If not, see . - - -## References -- [[1]](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2011WR011524) Bárdossy, A. and Pegram, G.: Multiscale spatial recorrelation of RCM precipitation to produce unbiased climate change scenarios over large areas and small, Water Resources Research, 48, 9502–, https://doi.org/10.1029/2011WR011524, 2012. -- [2] Bazaraa, M. S., Jarvis, J. J., and Sherali, H. D.: Linear Programming and Network Flows, 4th edn., John Wiley & Sons, 2009. -- [[3]](https://doi.org/10.1175/JCLI-D-14-00754.1) Cannon, A. J., Sobie, S. R., and Murdock, T. Q.: Bias correction of simulated precipitation by quantile mapping: how well do methods preserve relative changes in quantiles and extremes?, J. Climate, 28, 6938–6959, https://doi.org/10.1175/JCLI-D-14-00754.1, 2015. -- [[4]](https://link.springer.com/article/10.1007/s00382-017-3580-6) Cannon, Alex J.: Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables, Climate Dynamics, nb. 1, vol. 50, p. 31-49, 10.1007/s00382-017-3580-6, 2018. -- [[5]](https://doi.org/10.1016/j.gloplacha.2006.11.030) Déqué, M.: Frequency of precipitation and temperature extremes over France in an anthropogenic scenario: Model results and statistical correction according to observed values, Global Planet. Change, 57, 16–26, https://doi.org/10.1016/j.gloplacha.2006.11.030, 2007. -- [[6]](https://doi.org/10.1029/2009GL038401) Michelangeli, P.-A., Vrac, M., and Loukos, H.: Probabilistic downscaling approaches: Application to wind cumulative distribution functions, Geophys. Res. Lett., 36, L11708, https://doi.org/10.1029/2009GL038401, 2009. -- [7] Panofsky, H. A. and Brier, G. W.: Some applications of statistics to meteorology, Mineral Industries Extension Services, College of Mineral Industries, Pennsylvania State University, 103 pp., 1958. -- [[8]](https://doi.org/10.1016/j.jhydrol.2010.10.024) Piani, C., Weedon, G., Best, M., Gomes, S., Viterbo, P., Hagemann, S., and Haerter, J.: Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models, J. Hydrol., 395, 199–215, https://doi.org/10.1016/j.jhydrol.2010.10.024, 2010. -- [[9]](https://doi.org/10.5194/hess-23-773-2019) Robin, Y., Vrac, M., Naveau, P., Yiou, P.: Multivariate stochastic bias corrections with optimal transport, Hydrol. Earth Syst. Sci., 23, 773–786, 2019, https://doi.org/10.5194/hess-23-773-2019 -- [[10]](https://arxiv.org/abs/1306.0895) Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances. arXiv, https://arxiv.org/abs/1306.0895 -- [[11]](https://doi.org/10.5194/hess-22-3175-2018) Vrac, M.: Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2 D2 ) bias correction, Hydrol. Earth Syst. Sci., 22, 3175–3196, https://doi.org/10.5194/hess-22-3175-2018, 2018. -- [[12]](https://doi.org/10.1175/JCLI-D-14-00059.1) Vrac, M. and P. Friederichs, 2015: Multivariate—Intervariable, Spatial, and Temporal—Bias Correction. J. Climate, 28, 218–237, https://doi.org/10.1175/JCLI-D-14-00059.1 -- [13] Wasserstein, L. N. (1969). Markov processes over denumerable products of spaces describing large systems of automata. Problems of Information Transmission, 5(3), 47-52. -- [[14]](https://doi.org/10.1023/B:CLIM.0000013685.99609.9e) Wood, A. W., Leung, L. R., Sridhar, V., and Lettenmaier, D. P.: Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs, Clim. Change, 62, 189–216, https://doi.org/10.1023/B:CLIM.0000013685.99609.9e, 2004. -- [[15]](https://doi.org/10.5194/esd-2021-12) Robin, Y. and Vrac, M.: Is time a variable like the others in multivariate statistical downscaling and bias correction?, Earth Syst. Dynam. Discuss. [preprint], https://doi.org/10.5194/esd-2021-12, in review, 2021. -- François, B., Vrac, M., Cannon, A., Robin, Y., and Allard, D.: Multivariate bias corrections of climate simulations: Which benefits for which losses?, Earth Syst. Dyn., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, https://esd.copernicus.org/articles/11/537/2020/, 2020.