A methodology for estimating seasonal cycles of atmospheric CO 2 resulting from terrestrial net ecosystem exchange (NEE) fluxes using the Transcom T3L2 pulse-response functions
A methodology for estimating seasonal cycles of atmospheric CO 2 resulting from terrestrial net ecosystem exchange (NEE) fluxes using the Transcom T3L2 pulse-response functions
复制标题
使用 Transcom T3L2 脉冲响应函数估算陆地净生态系统交换 (NEE) 通量引起的大气 CO 2 季节性循环的方法
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发表时间：
2012
期刊：
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通讯作者：
K. Gurney
中科院分区：
文献类型：
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作者：
C. Nevison;D. Baker;K. Gurney
抽象的。我们提出了一种将模拟的陆地净生态系统交换(NEE)碳通量转换为相应的大气CO2季节循环的方法。该方法基于Transcom 3 Level 2(T3L2)大气示踪传输模式(ATM)相互比较的脉冲响应函数。新的脉冲响应方法比完全的正向ATM模拟要快得多，允许以秒为单位计算二氧化碳季节循环，而不是正向模拟所需的几天或几周。此外，结果还估计了与地面NEE通量转换为大气信号有关的13个不同ATM之间的传输不确定性范围。我们用来自T3L2的存档前向ATM模拟结果对该方法进行了评估。后者还被用来估计与海洋和化石燃料影响相关的不确定性。我们在选定的监测点提供了11个不同的T3L2陆地区域对大气二氧化碳循环的贡献的区域细分。由来自共同体陆地模式的NEE通量强迫的脉冲响应代码的测试案例表明，对于许多陆地模型，模型结果和观测到的大气二氧化碳循环之间的差异将足够大，足以清楚地超越大气层大气的不确定性。
Abstract. We present a method for translating modeled terrestrial net ecosystem exchange (NEE) fluxes of carbon into the corresponding seasonal cycles in atmospheric CO2. The method is based on the pulse-response functions from the Transcom 3 Level 2 (T3L2) atmospheric tracer transport model (ATM) intercomparison. The new pulse-response method is considerably faster than a full forward ATM simulation, allowing CO2 seasonal cycles to be computed in seconds, rather than the days or weeks required for a forward simulation. Further, the results provide an estimate of the range of transport uncertainty across 13 different ATMs associated with the translation of surface NEE fluxes into an atmospheric signal. We evaluate the method against the results of archived forward ATM simulations from T3L2. The latter are also used to estimate the uncertainties associated with oceanic and fossil fuel influences. We present a regional breakdown at selected monitoring sites of the contribution to the atmospheric CO2 cycle from the 11 different T3L2 land regions. A test case of the pulse-response code, forced by NEE fluxes from the Community Land Model, suggests that for many terrestrial models, discrepancies between model results and observed atmospheric CO2 cycles will be large enough to clearly transcend ATM uncertainties.