학술논문

The Impact of Climate Forcing Biases and the Nitrogen Cycle on Land Carbon Balance Projections.
Document Type
Article
Source
Journal of Advances in Modeling Earth Systems. Jan2024, Vol. 16 Issue 1, p1-22. 22p.
Subject
*CARBON cycle
*NUTRIENT cycles
*CLIMATE change mitigation
*ATMOSPHERIC carbon dioxide
*CLIMATE change
*NITROGEN cycle
*ATMOSPHERIC nitrogen
Language
ISSN
1942-2466
Abstract
Earth System Models (ESMs) project that the terrestrial carbon sink will continue to grow as atmospheric CO2 increases, but this projection is uncertain due to biases in the simulated climate and how ESMs represent ecosystem processes. In particular, the strength of the CO2‐fertilization effect, which is modulated by nutrient cycles, varies substantially across models. This study evaluates land carbon balance uncertainties for the Canadian Earth System Model (CanESM) by conducting simulations where the latest version of CanESM's land surface component is driven offline with raw and bias‐adjusted CanESM5 climate forcing data. To quantify the impact of nutrient limitation, we complete simulations where the nitrogen cycle is enabled or disabled. Results show that bias adjustment improves model performance across most ecosystem variables, primarily due to reduced biases in precipitation. Turning the nitrogen cycle on increases the global land carbon sink during the historical period (1995–2014) due to enhanced nitrogen deposition, placing it within the Global Carbon Budget uncertainty range. During the future period (2080–2099), the simulated land carbon sink increases in response to bias adjustment and decreases in response to the dynamic carbon‐nitrogen interaction, leading to a net decrease when both factors are acting together. The dominating impact of the nitrogen cycle demonstrates the importance of representing nutrient limitation in ESMs. Such efforts may produce more robust carbon balance projections in support of global climate change mitigation policies such as the 2015 Paris Agreement. Plain Language Summary: The implementation of global climate change policies relies on our ability to predict how the global carbon cycle will evolve in the future. Climate models project that the biosphere will continue to absorb more CO2 than it emits, keeping atmospheric CO2 levels lower than they would be otherwise. However, the strength of this net CO2 uptake varies considerably among models. This is because of differences in the simulated climate as well as the use of different methods for simulating plant growth. This study evaluates the importance of both factors by running one model with different climate data sets and model configurations. Our results show that the future net CO2 uptake by plants increases when removing biases in climatic conditions and decreases when accounting for the impact of soil nutrients on plant growth, leading to a net decrease when both factors are acting together. The dominating impact of the nutrients demonstrates the importance of representing nutrient limitation in climate models. Such efforts may produce more robust carbon balance projections in support of global climate change mitigation policies such as the 2015 Paris Agreement. Key Points: Bias adjustment of climate forcing improves model performance across most variables, primarily due to reduced biases in precipitationThe inclusion of the N cycle increases the simulated C sink during the historical period, placing it within the observed uncertainty rangeThe future C sink increases with bias adjustment and decreases with the N cycle, resulting in a net decrease when both factors are at play [ABSTRACT FROM AUTHOR]