A Multiyear Gridded Data Ensemble of Surface Biogenic Carbon Fluxes for North America: Evaluation and Analysis of Results. Issue 2 (18th February 2020)

• Record Type: Journal Article
• Authors: Zhou, Yu; Williams, Christopher A.; Lauvaux, Thomas; Davis, Kenneth J.; Feng, Sha; Baker, Ian; Denning, Scott; Wei, Yaxing
• Is Part Of: Journal of geophysical research. Volume 125:Issue 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-02-18
• Subjects: parameters -- sensitivity analysis -- model‐data comparison -- biogeochemical modeling; Geobiology -- Periodicals; Biogeochemistry -- Periodicals; Biotic communities -- Periodicals; Geophysics -- Periodicals; 577.14
• DOI: 10.1029/2019JG005314
• Languages: English
• ISSNs: 2169-8953

Abstract

Abstract: Accurate and fine‐scale estimates of biogenic carbon fluxes are critical for measuring and monitoring the biosphere's responses and feedback to the climate system. Currently available data products from flux towers and model‐intercomparison projects struggle to adequately represent spatiotemporal dynamics of surface biogenic carbon fluxes, and to quantify their uncertainties, which also are crucial to atmospheric inversion systems. To address these gaps, we introduce a new perturbed‐parameter model ensemble with the CASA model to estimate surface biogenic carbon fluxes at monthly and 3‐hourly scales for North America at ~500‐m and 5‐km resolutions. We first use the Extended Fourier Amplitude Sensitivity Testing to choose the three most sensitive parameters to be perturbed, maximum light use efficiency ( E max ), optimal temperature of photosynthesis ( T opt ), and temperature response of respiration ( Q 10 ). The initial range for each parameter is broadly sampled for the L1 ensemble, but then we pruned E max with site‐level primary productivity to derive an L2 ensemble with narrower uncertainty ranges. Ensembles are strongly correlated with site‐level results at both monthly and 3‐hourly scales, and the spread across L1/L2 ensemble members encompasses the range of AmeriFlux observations. Monthly variability in the L2 ensemble mean is 85% of the observed variability. The L2 ensemble outperforms diverse data products with the highest Taylor skill scores at diurnal to annual scales. The ensemble's seasonality agrees well with other models for most biome types and in high and middle latitudes, but inconsistencies are found in subtropical and tropical ecoregions and for annual totals over North America. Key Points: By perturbing three key model parameters, the mean of the new ensemble outperforms other model products in comparison to flux tower data Seasonal net carbon exchange shows consistency with other model products in high‐ and middle‐latitude regions and at continental scales Cold‐season respiration needs to be suppressed and maximum light use efficiency needs to be varied seasonally