Evaluation of atmospheric and terrestrial effects in the carbon cycle for forest and grassland ecosystems using a remote sensing and modeling approach,Agricultural and Forest Meteorology

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Evaluation of atmospheric and terrestrial effects in the carbon cycle for forest and grassland ecosystems using a remote sensing and modeling approach
Agricultural and Forest Meteorology ( IF 5.6 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.agrformet.2020.108187
Muhammad Umair , Daeun Kim , Ram L. Ray , Minha Choi

Abstract Soil moisture (SM) and vapor pressure deficit (VPD) are key variables that affect the carbon, water, and energy cycles. Very few studies have been conducted to evaluate their impacts on site-specific ecosystems, especially in mountainous regions and plains using an integrated remote sensing and modeling approach. This study used two flux tower sites, P301 (forest–ecosystem), Prairie View A&M University (PVAMU) (grassland–ecosystem) to evaluate gross primary production (GPP), sensible heat flux (H), and latent heat flux (LE). The community land model (CLM4) and soil moisture active passive (SMAP) carbon product were employed and evaluated using the flux tower data from 2016 to 2018. From the CLM4 and SMAP estimation of GPP, the CLM4 showed better accuracy at P301, whereas SMAP performed better at PVAMU. The SMAP overestimated GPP at P301, which could be due to the coarse footprint of SMAP (9 × 9 km). CLM4 overestimated GPP during the growing season at PVAMU, which could be due to the structural and parametric uncertainties. The H at P301 showed good agreement between the CLM4 results and flux tower measurements. However, H at the PVAMU site was most likely affected by the precipitation. Moreover, at P301, VPD was effective in controlling the carbon and water fluxes (GPP and LE) with a positive partial correlation (p–value

中文翻译：

使用遥感和建模方法评估森林和草地生态系统碳循环中的大气和陆地效应

摘要土壤水分 (SM) 和蒸汽压差 (VPD) 是影响碳、水和能量循环的关键变量。很少有研究使用综合遥感和建模方法评估它们对特定地点生态系统的影响，特别是在山区和平原。本研究使用两个通量塔站点，P301（森林-生态系统）、Prairie View A&M 大学 (PVAMU)（草地-生态系统）来评估初级生产总值 (GPP)、显热通量 (H) 和潜热通量 (LE) . 采用群落土地模型 (CLM4) 和土壤水分主动被动 (SMAP) 碳产品，并使用 2016 年至 2018 年的通量塔数据进行评估。从 GPP 的 CLM4 和 SMAP 估计，CLM4 在 P301 处显示出更好的准确性，而 SMAP在 PVAMU 表现更好。SMAP 高估了 P301 的 GPP，这可能是由于 SMAP 的粗略足迹（9 × 9 公里）。CLM4 高估了 PVAMU 生长季节的 GPP，这可能是由于结构和参数的不确定性。P301 处的 H 在 CLM4 结果和通量塔测量值之间显示出良好的一致性。然而，PVAMU 站点的 H 最有可能受到降水的影响。此外，在 P301 处，VPD 可有效控制碳和水通量（GPP 和 LE），且呈正偏相关（p 值 PVAMU 站点的 H 最有可能受到降水的影响。此外，在 P301 处，VPD 可有效控制碳和水通量（GPP 和 LE），且呈正偏相关（p 值 PVAMU 站点的 H 最有可能受到降水的影响。此外，在 P301 处，VPD 可有效控制碳和水通量（GPP 和 LE），且呈正偏相关（p 值

更新日期：2020-12-01

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