Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model

Abstract

Abstract. Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a processbased tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the timeaveraged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.

Global Evaluation of Proxy System Models for Stable Water Isotopes With Realistic Atmospheric Forcing

“…GCMs and PSMs are useful tools to compare and analyze paleoclimate simulations and proxy data (e.g., Calay et al, 2014;Dee et al, 2015;Evans et al, 2013;Pausata et al, 2011;Shinha et al, 2015) and as observational operators for climate data assimilation (e.g., Acevedo et al, 2017;Dee et al, 2016;Hakim et al, 2016;Okazaki & Yoshimura, 2017;Steiger et al, 2017). Because climate data assimilation has attracted increasing attention in recent years, these models are of vital importance.…”

“…For example, PSMs make it possible not only to disentangle the climatic information recorded in proxies but also to evaluate climate simulations (Dee et al, 2015;Evans et al, 2013). It is also possible to use proxy data directly in data assimilation for paleoclimate reconstruction using PSMs as observation operators (e.g., Acevedo et al, 2017;Dee et al, 2016;Hakim et al, 2016;Okazaki & Yoshimura, 2017;Steiger et al, 2017). Considering the potential applications of PSMs, their evaluation is critically important.…”

A pseudoproxy assessment of data assimilation for reconstructing the atmosphere–ocean dynamics of hydroclimate extremes

“…As discussed in Steiger et al (2014 and Hakim et al (2016), the offline approach is well suited to a paleoclimate context in which it has been shown to be highly skillful at annual timescales without the immense computational costs of a traditional online approach. Moreover, tests of offline vs. online approaches for paleoclimate have so far shown no improvement in reconstruction skill with an online method (Matsikaris et al, 2015;Acevedo et al, 2017).…”

An Artificial Neural Networks‐Based Tree Ring Width Proxy System Model for Paleoclimate Data Assimilation

“…In that regard, the creation of proxy system models (PSMs; the so‐called observation operators in data assimilation framework) (Evans et al, ) used to map climatic variables onto proxy variables is particularly important, because PSMs considerably affect the degree to which the background field can be corrected by the observational data (Fang & Li, ; Li, ). Duo to their widespread distribution, accurate dating results, high temporal resolution, and coherent climate signal, tree ring proxies, including the tree ring width (TRW) and latewood density, are the most commonly assimilated proxies in PDA (Acevedo et al, , ; Dee et al, , ; Hakim et al, ). Previous PDA studies that assimilated TRW adopted either a linear univariate model (LUM), which maps temperatures onto tree ring proxies (Dee et al, ; Hakim et al, ) or a physically based model known as VS‐Lite (VSL; Tolwinski‐Ward et al, , ) that nonlinearly relates tree ring growth to temperature and precipitation (Acevedo et al, , ; Dee et al, ).…”

“…Duo to their widespread distribution, accurate dating results, high temporal resolution, and coherent climate signal, tree ring proxies, including the tree ring width (TRW) and latewood density, are the most commonly assimilated proxies in PDA (Acevedo et al, 2015(Acevedo et al, , 2017Dee et al, 2015Dee et al, , 2016Hakim et al, 2016). Previous PDA studies that assimilated TRW adopted either a linear univariate model (LUM), which maps temperatures onto tree ring proxies (Dee et al, 2016;Hakim et al, 2016) or a physically based model known as VS-Lite (VSL;Tolwinski-Ward et al, 2011) that nonlinearly relates tree ring growth to temperature and precipitation (Acevedo et al, 2015(Acevedo et al, , 2017Dee et al, 2016). At present, however, it is difficult to draw a deterministic conclusion regarding the suitability of TRW PSMs for PDA due to two factors: (1) the complex responses of radial tree growth to various climatic factors (Evans et al, 2006;Vaganov et al, 2006;Tolwinski-Ward et al, 2011 are still difficult to understand and describe well, and thus, current TRW PSMs still have clear limitations (Goosse, 2016) and (2) the lack of comprehensive comparisons of TRW PSMs under realistic conditions using existing TRW chronologies rather than pseudo-TRW data (e.g., Acevedo et al, 2015Acevedo et al, , 2017Dee et al, 2016).…”