Preprints
https://doi.org/10.5194/essd-2020-58
https://doi.org/10.5194/essd-2020-58

  19 Jun 2020

19 Jun 2020

Review status: a revised version of this preprint is currently under review for the journal ESSD.

Standardized flux seasonality metrics: A companion dataset for FLUXNET annual product

Linqing Yang and Asko Noormets Linqing Yang and Asko Noormets
  • 1Department of Ecology and Conservation Biology, Texas A&M University, College Station, TX, USA

Abstract. Phenological events are integrative and sensitive indicators of ecosystem processes that respond to climate, water and nutrient availability, disturbance, and environmental change. The seasonality of ecosystem processes, including biogeochemical fluxes, can similarly be decomposed to identify key transition points and phase durations, which can be determined with high accuracy, and are specific to the processes of interest. As the seasonality of different processes differ, it can be argued that the interannual trends and responses to environmental forcings can be better described through the fluxes’ own temporal characteristics than through correlation to traditional phenological events like bud-break or leaf coloration. Here we present a global dataset of seasonality or phenological metrics calculated for gross primary productivity (GPP), ecosystem respiration (RE), latent heat (LE) and sensible heat (H) calculated for the FLUXNET 2015 Dataset of about 200 sites and 1500 site-years of data. The database includes metrics (i) on absolute flux scale for comparisons with flux magnitudes, and (ii) on normalized scale for comparisons of change rates across different fluxes. Flux seasonality was characterized by fitting a single-pass double-logistic model to daily flux integrals, and the derivatives of the fitted time series were used to extract the phenological metrics marking key turning points, season lengths and rates of change. Seasonal transition points could be determined with 95 % confidence interval of 6–11 days for GPP, 8–14 days for RE, 10–15 days for LE and 15–23 days for H. The phenology metrics derived from different partitioning methods diverged, at times significantly.

This Flux Seasonality Metrics Database (FSMD) can be accessed at U.S. Department of Energy’s (DOE) Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE, https://data.ess-dive.lbl.gov/view/doi:10.15485/1602532; Yang and Noormets, 2020). We hope that it will facilitate new lines of research, including (1) validating and benchmarking ecosystem process models, (2) parameterizing satellite remote sensing phenology and Phenocam products, (3) optimizing phenological models, and (4) generally expanding the toolset for interpreting ecosystems responses to changing climate.

Linqing Yang and Asko Noormets

 
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Linqing Yang and Asko Noormets

Linqing Yang and Asko Noormets

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Short summary
We present a flux seasonality metrics database (FSMD) depicting a set of standardized metrics of ecosystem biogeochemical fluxes of CO2, water and energy, including transition dates, phase lengths and rates of change with uncertainty estimates. FSMD allows assessment of spatial and temporal patterns in developmental dynamics, validation of novel aspects of phenology product, and process models. It is calculated from FLUXNET2015 data product and will be updated with new FLUXNET data releases.