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Upscaled diurnal cycles of land-atmosphere fluxes: a new global half-hourly data product

期刊

EARTH SYSTEM SCIENCE DATA
卷 10, 期 3, 页码 1327-1365

出版社

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/essd-10-1327-2018

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资金

  1. European Union's Horizon Research and Innovation programme [640176]
  2. AmeriFlux (US Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program) [DE-FG02-04ER63917, DE-FG02-04ER63911]
  3. CFCAS
  4. NSERC
  5. BIOCAP
  6. Environment Canada
  7. NRCan
  8. CarboEuropeIP
  9. FAO-GTOS-TCO
  10. iLEAPS
  11. Max Planck Institute for Biogeochemistry
  12. National Science Foundation
  13. University of Tuscia
  14. Universite Laval and Environment Canada
  15. US Department of Energy

向作者/读者索取更多资源

Interactions between the biosphere and the atmosphere can be well characterized by fluxes between the two. In particular, carbon and energy fluxes play a major role in understanding biogeochemical processes on an ecosystem level or global scale. However, the fluxes can only be measured at individual sites, e.g., by eddy covariance towers, and an upscaling of these local observations is required to analyze global patterns. Previous work focused on upscaling monthly, 8-day, or daily average values, and global maps for each flux have been provided accordingly. In this paper, we raise the upscaling of carbon and energy fluxes between land and atmosphere to the next level by increasing the temporal resolution to subdaily timescales. We provide continuous half-hourly fluxes for the period from 2001 to 2014 at 0.5 degrees spatial resolution, which allows for analyzing diurnal cycles globally. The data set contains four fluxes: gross primary production (GPP), net ecosystem exchange (NEE), latent heat (LE), and sensible heat (H). We propose two prediction approaches for the diurnal cycles based on large-scale regression models and compare them in extensive cross-validation experiments using different sets of predictor variables. We analyze the results for a set of FLUXNET tower sites showing the suitability of our approaches for this upscaling task. Finally, we have selected one approach to calculate the global half-hourly data products based on predictor variables from remote sensing and meteorology at daily resolution as well as half-hourly potential radiation. In addition, we provide a derived product that only contains monthly average diurnal cycles, which is a lightweight version in terms of data storage that still allows studying the important characteristics of diurnal patterns globally. We recommend to primarily use these monthly average diurnal cycles, because they are less affected by the impacts of day-to-day variation, observation noise, and short-term fluctuations on subdaily timescales compared to the full half-hourly flux products. The global half-hourly data products are available at https://doi.org/10.17871/BACI.224.

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