Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)
Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)
复制标题
社区土地模型（CLM4）中动态植被对碳氮循环反馈的影响
DOI：
10.1088/1748-9326/aa51d9
复制
发表时间：
2016
影响因子：
6.7
通讯作者：
P. Shao
中科院分区：
文献类型：
--
作者：
Koichi Sakaguchi;Xubin Zeng;L. Leung;P. Shao
陆地碳对大气CO2浓度（βL）和气候变暖（γL）的敏感性是影响未来变暖幅度的碳-气候反馈的重要组成部分。虽然这些敏感性可以通过地球系统模型来估计，但它们对陆地碳动态模型表示和固有模型假设的依赖性很少被研究。使用广泛使用的社区土地模型版本4作为例子，我们研究了βL和γL如何随规定的和动态的植被覆盖而变化。在20世纪后期，与规定的十年尺度植被相比，动态的两种敏感性都更大，γL的差异更强。后者是由于动态植被模型在代表热带和亚热带的落叶与万年青树木和树木与草之间的竞争的缺陷。植被覆盖的偏差改变了碳-氮循环的区域特征，使得植物生产力对变暖引起的氮矿化的增强反应不那么强烈，因此随着温度的升高，更多的碳流失到大气中。研究结果要求对土地碳敏感性进行系统评估，并对土地覆盖表示进行不同的假设，以帮助确定发展努力的优先顺序，并限制碳-气候反馈的不确定性。
Land carbon sensitivity to atmospheric CO2 concentration (βL) and climate warming (γL) is a crucial part of carbon-climate feedbacks that affect the magnitude of future warming. Although these sensitivities can be estimated by earth system models, their dependence on model representation of land carbon dynamics and the inherent model assumptions has rarely been investigated. Using the widely used Community Land Model version 4 as an example, we examine how βL and γL vary with prescribed versus dynamic vegetation covers. Both sensitivities are found to be larger with dynamic compared to prescribed vegetation on decadal timescale in the late twentieth century, with a more robust difference in γL. The latter is a result of dynamic vegetation model deficiencies in representing the competitions between deciduous versus evergreen trees and tree versus grass over the tropics and subtropics. The biased vegetation cover changes the regional characteristics of carbon-nitrogen cycles such that plant productivity responds less strongly to the enhancement of nitrogen mineralization with warming, so more carbon is lost to the atmosphere with rising temperature. The result calls for systematic evaluations of land carbon sensitivities with varying assumptions for land cover representations to help prioritize development effort and constrain uncertainties in carbon-climate feedbacks.
影响因子：
9.4
作者：
Galbraith, David;Levy, Peter E.;Meir, Patrick
通讯作者：
Meir, Patrick
影响因子：
18.3
作者：
Huntingford, Chris;Zelazowski, Przemyslaw;Cox, Peter M.
通讯作者：
Cox, Peter M.