首页> 外文期刊>Biogeosciences >Assessing biotic contributions to COsub2/sub fluxes in northern China using the Vegetation, Photosynthesis and Respiration Model (VPRM-CHINA) and observations from 2005 to 2009
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Assessing biotic contributions to COsub2/sub fluxes in northern China using the Vegetation, Photosynthesis and Respiration Model (VPRM-CHINA) and observations from 2005 to 2009

机译:利用植被,光合作用和呼吸模型(VPRM-CHINA)以及2005年至2009年的观测评估中国北方对CO 2 通量的生物贡献

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Accurately quantifying the spatiotemporal distribution of the biological component of COsub2/sub surface–atmosphere exchange is necessary to improve top-down constraints on China's anthropogenic COsub2/sub emissions. We provide hourly fluxes of COsub2/sub as net ecosystem exchange (NEE; μ mol COsub2/sub m sup?2/sup s sup?1/sup ) on a 0.25 ° × 0.25 ° grid by adapting the Vegetation, Photosynthesis, and Respiration Model (VPRM) to the eastern half of China for the time period from 2005 to 2009; the minimal empirical parameterization of the VPRM-CHINA makes it well suited for inverse modeling approaches. This study diverges from previous VPRM applications in that it is applied at a large scale to China's ecosystems for the first time, incorporating a novel processing framework not previously applied to existing VPRM versions. In addition, the VPRM-CHINA model prescribes methods for addressing dual-cropping regions that have two separate growing-season modes applied to the same model grid cell. We evaluate the VPRM-CHINA performance during the growing season and compare to other biospheric models. We calibrate the VPRM-CHINA with ChinaFlux and FluxNet data and scale up regionally using Weather Research and Forecasting (WRF) Model v3.6.1 meteorology and MODIS surface reflectances. When combined with an anthropogenic emissions model in a Lagrangian particle transport framework, we compare the ability of VPRM-CHINA relative to an ensemble mean of global hourly flux models (NASA CMS – Carbon Monitoring System) to reproduce observations made at a site in northern China. The measurements are heavily influenced by the northern China administrative region. Modeled hourly time series using vegetation fluxes prescribed by VPRM-CHINA exhibit low bias relative to measurements during the May–September growing season. Compared to NASA CMS subset over the study region, VPRM-CHINA agrees significantly better with measurements. NASA CMS consistently underestimates regional uptake in the growing season. We find that during the peak growing season, when the heavily cropped North China Plain significantly influences measurements, VPRM-CHINA models a COsub2/sub uptake signal comparable in magnitude to the modeled anthropogenic signal. In addition to demonstrating efficacy as a low-bias prior for top-down COsub2/sub inventory optimization studies using ground-based measurements, high spatiotemporal resolution models such as the VPRM are critical for interpreting retrievals from global COsub2/sub remote-sensing platforms such as OCO-2 and OCO-3 (planned). Depending on the satellite time of day and season of crossover, efforts to interpret the relative contribution of the vegetation and anthropogenic components to the measured signal are critical in key emitting regions such as northern China – where the magnitude of the vegetation COsub2/sub signal is shown to be equivalent to the anthropogenic signal.
机译:准确定量CO 2 地表-大气交换生物成分的时空分布对于改善对中国人为CO 2 排放量的自上而下的约束是必要的。我们提供每小时CO 2 的通量作为净生态系统交换(NEE;μmol CO 2 m ?2 s ?1 )在0.25°×0.25°的网格上,通过将植被,光合作用和呼吸模型(VPRM)应用于2005年至2009年的中国东部地区; VPRM-CHINA的最小经验参数化使其非常适合于逆建模方法。这项研究与以前的VPRM应用不同,该研究首次将其大规模应用到中国的生态系统中,并结合了以前不适用于现有VPRM版本的新颖处理框架。另外,VPRM-CHINA模型规定了解决双裁剪区域的方法,该双裁剪区域将两个单独的生长季节模式应用于同一模型网格。我们评估了VPRM-CHINA在生长期的表现,并与其他生物圈模型进行了比较。我们使用ChinaFlux和FluxNet数据校准VPRM-CHINA,并使用天气研究和预报(WRF)模型v3.6.1气象学和MODIS表面反射率在区域范围内进行扩展。当在拉格朗日粒子传输框架中结合人为排放模型时,我们将VPRM-CHINA的能力与全球小时通量模型(NASA CMS –碳监测系统)的整体平均值进行比较,以再现在中国北方某地点所做的观测。测量结果受到中国北方行政区域的严重影响。使用VPRM-CHINA规定的植被通量对小时时间序列进行建模,相对于5月至9月生长期的测量值而言,偏差较小。与研究区域内的NASA CMS子集相比,VPRM-CHINA在测量方面明显更好。 NASA CMS一直低估了生长季节的区域吸收率。我们发现,在高峰季节,当收成严重的华北平原显着影响测量值时,VPRM-CHINA模拟了一个CO 2 吸收信号,其强度与模拟的人为信号相当。除了通过地面测量证明自上而下的CO 2 库存优化研究具有低偏见的有效性外,高时空分辨率模型(例如VPRM)对于解释全球CO < sub> 2 遥感平台,例如OCO-2和OCO-3(已计划)。根据卫星的一天中的时间和分频的季节,解释植被和人为成分对被测信号的相对贡献的努力在诸如中国北方这样的关键发射区至关重要,那里的植被CO 2的大小信号显示为与人为信号等效。

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