Towards a more detailed representation of high-latitude vegetation in the global land surface model ORCHIDEE (ORC-HL-VEGv1.0)

Author:

Druel ArsèneORCID,Peylin Philippe,Krinner Gerhard,Ciais Philippe,Viovy NicolasORCID,Peregon Anna,Bastrikov Vladislav,Kosykh Natalya,Mironycheva-Tokareva Nina

Abstract

Abstract. Simulation of vegetation–climate feedbacks in high latitudes in the ORCHIDEE land surface model was improved by the addition of three new circumpolar plant functional types (PFTs), namely non-vascular plants representing bryophytes and lichens, Arctic shrubs and Arctic C3 grasses. Non-vascular plants are assigned no stomatal conductance, very shallow roots, and can desiccate during dry episodes and become active again during wet periods, which gives them a larger phenological plasticity (i.e. adaptability and resilience to severe climatic constraints) compared to grasses and shrubs. Shrubs have a specific carbon allocation scheme, and differ from trees by their larger survival rates in winter, due to protection by snow. Arctic C3 grasses have the same equations as in the original ORCHIDEE version, but different parameter values, optimised from in situ observations of biomass and net primary productivity (NPP) in Siberia. In situ observations of living biomass and productivity from Siberia were used to calibrate the parameters of the new PFTs using a Bayesian optimisation procedure. With the new PFTs, we obtain a lower NPP by 31 % (from 55° N), as well as a lower roughness length (−41 %), transpiration (−33 %) and a higher winter albedo (by +3.6 %) due to increased snow cover. A simulation of the water balance and runoff and drainage in the high northern latitudes using the new PFTs results in an increase of fresh water discharge in the Arctic ocean by 11 % (+140 km3 yr−1), owing to less evapotranspiration. Future developments should focus on the competition between these three PFTs and boreal tree PFTs, in order to simulate their area changes in response to climate change, and the effect of carbon–nitrogen interactions.

Publisher

Copernicus GmbH

Reference117 articles.

1. Aiba, S.-I. and Kohyama, T.: Tree Species Stratification in Relation to Allometry and Demography in a Warm-Temperate Rain Forest, J. Ecol., 84, 207–218, https://doi.org/10.2307/2261356, 1996.

2. Ball, J. T., Woodrow, I. E., and Berry, J. A.: A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions, in: Progress in Photosynthesis Research, edited by: Biggins, J., 221–224, Springer Netherlands, Dordrecht, available at: http://link.springer.com/10.1007/978-94-017-0519-6_48 (last access: 28 April 2016), 1987.

3. Bastrikov, V., MacBean, N., Peylin, P., Bacour, C., Santaren, D., and Kuppel, S.: Land surface model parameter optimisation using in-situ flux data: comparison of gradient-based versus random search algorithms, in preparation, Geosci. Model Dev., 2018.

4. Baudena, M., Dekker, S. C., van Bodegom, P. M., Cuesta, B., Higgins, S. I., Lehsten, V., Reick, C. H., Rietkerk, M., Scheiter, S., Yin, Z., Zavala, M. A., and Brovkin, V.: Forests, savannas, and grasslands: bridging the knowledge gap between ecology and Dynamic Global Vegetation Models, Biogeosciences, 12, 1833–1848, https://doi.org/10.5194/bg-12-1833-2015, 2015.

5. Bentley, J. R., Seegrist, D., and Blakeman, D. A.: A technique for sampling low shrub vegetation, by cromwn volume classes, Res Note PSW-RN-215 Berkeley CA US Dep. Agric. For. Serv. Pac. Southwest For. Range Exp. Stn., 12 pp., 1970.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3