INM RAS 气候模型的氮循环模块

IF 0.5 4区 数学 Q4 MATHEMATICS, APPLIED
Alexey Yu. Chernenkov, Evgeny M. Volodin, Victor M. Stepanenko
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引用次数: 0

摘要

氮是地球上最丰富的化学元素之一,在全球环境变化中发挥着重要作用。主要的地球系统模式包括复杂程度不同的碳氮循环耦合模块,但 INM RAS 气候模式系列尚未包含明确的氮循环描述。本文在简化 JULES-CN 模式的基础上,对陆地氮循环进行了参数化,并与 INM-CM 陆地碳循环模块进行了耦合使用。在 1850-2100 年期间,使用氮反馈禁用和启用版本的独立碳循环模型进行了数值模拟。模拟的全球碳库与其他实施了氮循环的模型结果显示出良好的一致性。考虑到碳循环的氮限制,具体说明了 1850 年至 20 世纪中期陆地生态系统总碳储存的模拟动态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nitrogen cycle module for INM RAS climate model
Nitrogen is one of the most abundant chemical elements on the Earth and plays an important role in global environmental change. Leading Earth system models include coupled carbon and nitrogen cycle modules of varying complexity, but the INM RAS climate model family has not yet included an explicit N-cycle description. This paper presents a parameterization of the terrestrial N-cycle based on a simplification of the JULES-CN model, adapted for coupled use with the INM-CM land C-cycle module. Numerical simulations were carried out with a standalone carbon cycle model with nitrogen feedback disabled and enabled versions for the period 1850–2100. The simulated global pools show good agreement with results of other models with an implemented N-cycle. Taking into account the N-limitation of the C-cycle, the modelled dynamics of total carbon storage in terrestrial ecosystems from 1850 to the mid-20th century is specified.
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来源期刊
CiteScore
1.40
自引率
16.70%
发文量
31
审稿时长
>12 weeks
期刊介绍: The Russian Journal of Numerical Analysis and Mathematical Modelling, published bimonthly, provides English translations of selected new original Russian papers on the theoretical aspects of numerical analysis and the application of mathematical methods to simulation and modelling. The editorial board, consisting of the most prominent Russian scientists in numerical analysis and mathematical modelling, selects papers on the basis of their high scientific standard, innovative approach and topical interest. Topics: -numerical analysis- numerical linear algebra- finite element methods for PDEs- iterative methods- Monte-Carlo methods- mathematical modelling and numerical simulation in geophysical hydrodynamics, immunology and medicine, fluid mechanics and electrodynamics, geosciences.
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