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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/gmd-2020-29
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-29
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: methods for assessment of models 14 Apr 2020

Submitted as: methods for assessment of models | 14 Apr 2020

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This preprint is currently under review for the journal GMD.

Using the International Tree-Ring Data Bank (ITRDB) records as century-long benchmarks for land-surface models

Jina Jeong1, Jonathan Barichivich2,3, Philippe Peylin2, Vanessa Haverd4, Matthew J. McGrath2, Nicolas Vuichard2, Michael N. Evans5, Flurin Babst6,7,8, and Sebastiaan Luyssaert1 Jina Jeong et al.
  • 1Department of Ecological Sciences, VU University, 1081HV Amsterdam, the Netherlands
  • 2Laboratoire des Sciences du Climat et de l’Environnement, IPSL, CNRS/CEA/UVSQ, 91191 Gif sur Yvette, France
  • 3Instituto de Conservación Biodiversidad y Territorio, Universidad Austral de Chile, 5090000 Valdivia, Chile
  • 4CSIRO Oceans and Atmosphere, Canberra, 2601, Australia
  • 5Department of Geology & ESSIC, University of Maryland, MD 20742-4211, USA
  • 6Dendro Sciences Group, Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
  • 7School of Natural Resources and the Environment, University of Arizona, Tucson, USA
  • 8Laboratory of Tree-Ring Research, University of Arizona, Tucson, USA

Abstract. The search for a long-term benchmark for land-surface models (LSM) has brought tree-ring data to the attention of the land-surface community as they record growth well before human-induced environmental changes became important. The most comprehensive archive of publicly shared tree-ring data is the International Tree-ring Data Bank (ITRDB). Many records in the ITRDB have, however, been collected almost exclusively with a view on maximizing an environmental target signal (e.g. climate), which has resulted in a biased representation of forested sites and landscapes and thus limits its use as a data source for benchmarking. The aim of this study is to propose advances in land-surface modelling and data processing to enable the land-surface community to re-use the ITRDB data as a much-needed century-long benchmark. Given that tree-ring width is largely explained by phenology, tree size, and climate sensitivity, LSMs that intend to use it as a benchmark should at least simulate tree phenology, size-dependent growth, differently-sized trees within a stand, and responses to changes in temperature, precipitation and atmospheric CO2 con¬cen¬tra¬tions. Yet, even if LSMs were capable of accurately simulating tree-ring width, sampling biases in the ITRDB need to be accounted for. This study proposes two solutions: exploiting the observation that the variation due to size-related growth by far exceeds the variation due to environmental changes; and simulating a size-structured population of trees. Combining the proposed advances in modelling and data processing resulted in four complementary benchmarks - reflecting different usage of the information contained in the ITRDB - each described by two metrics rooted in statistics that quantify the performance of the benchmark. Although the proposed benchmarks are unlikely to be precise, they advance the field by providing a much-needed large-scale constraint on changes in the simulated maximum tree diameter and annual growth increment for the transition from pre-industrial to present-day environmental conditions over the past century. Hence, the proposed benchmarks open up new ways of exploring the ITRDB archive, stimulate the dendrochronological community to refine its sampling protocols to produce new and spatially unbiased tree-ring networks, and help the modelling community to move beyond the short-term benchmarking of LSM.

Jina Jeong et al.

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Jina Jeong et al.

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