利用不确定的全碳循环基准评估巴西的两个陆地表面模型

Auguste Caen, T. Luke Smallman, Aline Anderson de Castro, Eddy Robertson, Celso von Randow, Manoel Cardoso, Mathew Williams
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引用次数: 4

摘要

不同模式对热带生态系统碳循环的预测存在差异,这是由于对碳库周转或转运时间等内部过程的模拟存在差异。需要对最近的这些过程进行估计,以测试模型表示,从而在生物群系内部和跨生物群系的模型预测中建立信心。在这里,我们评估了2001 - 2010年期间巴西生物群落的碳循环过程在两个陆地表面模型[联合英国陆地环境模拟器(JULES)和陆地表面过程综合模型(内陆)]中的表现。使用ILAMB系统评估模型输出。使用碳数据模型框架创建了概率基准数据,该模型吸收了叶面积指数的观测时间序列以及木质生物量和土壤c的地图。新的定制不确定性度量评估模型是否在基准不确定性范围内。由于干扰效应和参数误差的原因,模拟在植被类型均匀的区域效果较好,而在生物群落之间的过渡带则较差。整个巴西的生物圈-大气总通量进行了可靠的模拟。然而,净生态系统交换的基准不确定性太高,无法提供准确的模型评估。低碳生态系统内部碳分配和不同碳库动态差异显著。JULES模型死C股更准确,而活C股最好解决内陆。JULES对C木材库的高估是由于高估了木材的输入和木材的运输时间。内陆对死亡碳储量的低估是由于对死亡有机质运输时间的低估。这些模式在模拟年平均通量方面优于季节变化。对月度净碳交换的分析表明,INLAND正确地模拟了季节性,但高估了幅度,而JULES正确地模拟了年度幅度,但与基准不符。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Evaluating two land surface models for Brazil using a full carbon cycle benchmark with uncertainties

Evaluating two land surface models for Brazil using a full carbon cycle benchmark with uncertainties

Forecasts of tropical ecosystem C cycling diverge among models due to differences in simulation of internal processes such as turnover, or transit times, of carbon pools. Estimates of these processes for the recent past are needed to test model representations, and so build confidence in model forecasts within and across biomes. Here, we evaluate carbon cycle process representation in two land surface models [Joint UK Land Environment Simulator (JULES) and Integrated Model of Land Surface Processes (INLAND)] for the period 2001–10 across Brazilian biomes. Model outputs are evaluated using the ILAMB system. Probabilistic benchmarking data were created using the carbon data model framework that assimilates observational times series of leaf area index and maps of woody biomass and soil C. New custom uncertainty metrics assess if models are within benchmark uncertainties. Simulations are better in homogeneous areas of vegetation type, and are less robust at ecotones between biomes, likely due to disturbance effects and parameter errors. Gross biosphere-atmosphere fluxes are robustly modelled across Brazil. However, benchmark uncertainty is too high on net ecosystem exchange to provide an accurate evaluation of the models. The LSMs have significant differences in internal carbon allocation and the dynamics of the different C pools. JULES models dead C stocks more accurately while living C stocks are best resolved for INLAND. JULES' over-estimate of the C wood pool results from over-estimation of both inputs to wood and the transit time of wood. INLAND's under-estimate of dead C stocks arises from an under-estimate of the transit time of dead organic matter. The models are better at simulating annual averages than seasonal variation of fluxes. Analyses of monthly net C exchanges show that INLAND correctly simulates seasonality, but over-estimates amplitudes, whereas JULES correctly simulates the annual amplitudes, but is out of phase with the benchmark.

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