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一种用于估算多年冻土碳-气候反馈的简化的、数据受限方法。

A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.

作者信息

Koven C D, Schuur E A G, Schädel C, Bohn T J, Burke E J, Chen G, Chen X, Ciais P, Grosse G, Harden J W, Hayes D J, Hugelius G, Jafarov E E, Krinner G, Kuhry P, Lawrence D M, MacDougall A H, Marchenko S S, McGuire A D, Natali S M, Nicolsky D J, Olefeldt D, Peng S, Romanovsky V E, Schaefer K M, Strauss J, Treat C C, Turetsky M

机构信息

Earth Sciences Division, Lawrence Berkeley National Lab, Berkeley, CA, USA

Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA.

出版信息

Philos Trans A Math Phys Eng Sci. 2015 Nov 13;373(2054). doi: 10.1098/rsta.2014.0423.

Abstract

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2-33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9-112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of -14 to -19 Pg C °C(-1) on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10-18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.

摘要

我们提出了一种方法,利用一个简化的、数据驱动的模型来估算多年冻土大规模解冻产生的反馈,该模型结合了三个要素:土壤碳(C)地图和剖面,以确定多年冻土中碳的分布和类型;孵化实验,以量化解冻后碳损失的速率;以及响应气候变暖的土壤热动力学模型。我们将这种方法称为多年冻土碳网络孵化-泛北极热尺度方法(PInc-PanTher)。该方法假设碳库在冻结时根本不会分解,但一旦解冻,就会根据土壤温度遵循设定的分解轨迹。这些轨迹是根据一个三库分解模型确定的,该模型使用特定于土壤层类型的参数拟合孵化数据。我们计算了维持当前气候下稳态碳平衡所需的凋落物碳输入,并保持这些输入不变。土壤温度取自生态系统模型模拟的土壤热模块,该模拟由2010年至2100年期间两种变暖情景下一组共同的未来气候变化异常驱动。在中等变暖情景(RCP4.5)下,该方法预测多年冻土土壤碳损失为12.2-33.4Pg C;在高变暖情景(RCP8.5)下,该方法预测碳损失为27.9-112.6Pg C。在这两种情景下,预测的碳损失大致与全球温度变化呈线性比例关系。这些结果表明,在100年的时间尺度上,冻土碳对气候变化的全球敏感性(γ敏感性)为-14至-19Pg C °C-1。对于CH4排放,我们的方法假设一个固定的饱和面积,并且CH4排放的增加与缺氧土壤中异养呼吸的增加有关,在RCP4.5和RCP8.5情景下,CH4排放分别增加7%和35%,这增加了约10-18%的额外温室气体强迫。这里提出的简化方法忽略了许多可能放大或减轻多年冻土土壤碳释放的重要过程,但作为对强迫的、大规模多年冻土碳对变暖响应的数据驱动估计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f3c/4608038/b0730e2b522c/rsta20140423-g1.jpg

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