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

Abstract

Abstract. The search for a long-term benchmark for land-surface models (LSMs) has brought tree-ring data to the attention of the land-surface modelling community, as tree-ring data have recorded growth well before human-induced environmental changes became important. We propose and evaluate an improved conceptual framework of when and how tree-ring data may, despite their sampling biases, be used as century-long hindcasting targets for evaluating LSMs. Four complementary benchmarks – size-related diameter growth, diameter increment of mature trees, diameter increment of young trees, and the response of tree growth to extreme events – were simulated using the ORCHIDEE version r5698 LSM and were verified against observations from 11 sites in the independent, unbiased European biomass network datasets. The potential for big-tree selection bias in the International Tree-Ring Data Bank (ITRDB) was investigated by subsampling the 11 sites from European biomass network. We find that in about 95 % of the test cases, using ITRDB data would result in the same conclusions as using the European biomass network when the LSM is benchmarked against the annual radial growth during extreme climate years. The ITRDB data can be used with 70 % confidence when benchmarked against the annual radial growth of mature trees or the size-related trend in annual radial growth. Care should be taken when using the ITRDB data to benchmark the annual radial growth of young trees, as only 50 % of the test cases were consistent with the results from the European biomass network. The proposed maximum tree diameter and annual growth increment benchmarks may enable the use of ITRDB data for large-scale validation of the LSM-simulated response of forest ecosystems to the transition from pre-industrial to present-day environmental conditions over the past century. The results also suggest ways in which tree-ring width observations may be collected and/or reprocessed to provide long-term validation tests for land-surface models.

Divergent responses of photosynthesis and wood growth to climatic drivers

“…In other words, the climatic sensitivity predicted from ITRDB can be higher than the one at the averaged ecosystem level, but the direction of the climatic responses persists at both site and continental levels. A similar conclusion was reached from Jeong et al 44 by comparing TRW from ITRDB against the ones from unbiased datasets in Europe.…”

“…More importantly for the present study, their ability to document the life-long wood formation of individual trees enables determination of long-term and continuous inter-annual variability of growth dynamics, which is not possible by other widely applied observational approaches 7 . With rigorous preprocessing and bias correction, tree-ring records can be translated into biomass accumulation through the principle of allometry 42 , upscaled to the ecosystem level 43 , and used for benchmarking the performance of Dynamic Global Vegetation Models (DGVMs) 44 .…”

The International Tree-Ring Data Bank at Fifty: Status of Stewardship for Future Scientific Discovery

“…2010; Ault et al . 2014; Jeong et al . 2021) and provided accessible data to resource managers (Rice et al .…”

“…By capitalizing on the ways in which the network records variation in climate (St. George and Ault 2014), it has been used to develop large-scale, regional to continental reconstructions of drought (Cook and Krusic 2004;Cook et al 2010aCook et al , 2020Boucher et al 2011;Stahle et al 2016;Herrera and Ault 2017), temperature (Mann et al 1999;PAGES 2k Consortium 2013;Wilson et al 2016), soil moisture (Williams et al 2020;Zhang et al 2020), and seasonal precipitation (Stahle et al 2020), along with hundreds of more spatially specific reconstructions of runoff and other climatic features and phenomena. The strengths of dendroclimatic collections have also enabled assessments of climate and land-surface models (Cook et al 2010b;Woodhouse et al 2010;Ault et al 2014;Jeong et al 2021) and provided accessible data to resource managers (Rice et al 2009). Although some studies have demonstrated limitations for ecological forecasting because of the targeted nature of treering collections in the ITRDB (Nehrbass-Ahles et al 2014; Klesse et al 2018), the suite of tree-ring growth sensitivity to climate variation embedded in the network has nonetheless underscored vulnerabilities of global forests to anthropogenic climate change (Salzer et al 2009;Liu et al 2013;Williams et al 2013;Charney et al 2016;Babst et al 2019).…”

A 500-year annual runoff reconstruction for 14 selected European catchments

“…Reconstructed precipitation (P ) was derived by Pauling et al (2006) through principal component regression based on documented evidence (i.e. memoirs, annals and newspapers), speleothem proxy records (Proctor et al, 2000) and tree-ring chronologies from the International Tree-Ring Data Bank (ITRDB; Jeong et al, 2021) .…”