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. 2021 Jan 13;11:923. doi: 10.1038/s41598-020-79438-0

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Mean absolute error for the best model in each class at t + 1, t + 3, and t + 6 forecasting horizons for all provinces. The mean absolute error (y-axis) on the prediction (i.e., log) scale of the best model for each class for all provinces (x-axis). Provinces are ordered by latitude (x-axis, right is more northerly). There is a general decline in predictive power at farther forecasting horizons and at more northerly provinces; however, no single model or class of model performs best across all areas and all prediction horizons.