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Title: Flux Seasonality Metrics Database: A companion dataset for FLUXNET annual product

Abstract

This dataset include standardized phenological transition dates, and derived season lengths of active, dormant and transition seasons of ecosystem carbon and energy fluxes, as reported in FLUXNET. Such metrics are unique in that they characterize the seasonal dynamics of these fluxes in their own terms rather than in reference to traditional phenology indicators that mostly relate to vegetation structural characteristics. The Flux Seasonality Metrics Database (FSMD) generated 17 standardized seasonality metrics for 4 different fluxes including gross primary productivity (GPP), ecosystem respiration (RE), latent heat (LE) and sensible heat (H) reported in FLUXNET2015 Dataset for about 200 sites and 1500 site-years of data globally. Each metric is reported as an estimate and a confidence interval, which is a function of data coverage and flux variability. We anticipate that the FSMD will facilitate new model validation exercises, and stimulate new research in global change and Earth science disciplines where land-atmosphere exchange dynamics play a central role.

Creator(s)/Author(s):
ORCiD logo ; ORCiD logo
Publication Date:
Product Type:
Dataset
Research Org.:
Environmental System Science Data Infrastructure for a Virtual Ecosystem; North Carolina Ameriflux Core Site Cluster
Sponsoring Org.:
U.S. DOE > Laboratory Directed Research and Development (LDRD) > Lawrence Livermore National Laboratory
Subject:
54 ENVIRONMENTAL SCIENCES
Keywords:
EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS; EARTH SCIENCE > BIOSPHERE > VEGETATION > PLANT PHENOLOGY; EARTH SCIENCE > AGRICULTURE > PLANT COMMODITIES > VEGETABLE PRODUCTS; EARTH SCIENCE > AGRICULTURE > FOREST SCIENCE > FOREST PRODUCTS/COMMODITIES; EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC RADIATION > HEAT FLUX; EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > BIOGEOCHEMICAL CYCLES; EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > PHOTOSYNTHESIS; EARTH SCIENCE > AGRICULTURE > AGRICULTURAL PLANT SCIENCE; EARTH SCIENCE > AGRICULTURE > FOREST SCIENCE; EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS
OSTI Identifier:
1602532
DOI:
10.15485/1602532

Citation Formats

Yang, Linqing, and Noormets, Asko. Flux Seasonality Metrics Database: A companion dataset for FLUXNET annual product. United States: N. p., 2020. Web. doi:10.15485/1602532.
Yang, Linqing, & Noormets, Asko. Flux Seasonality Metrics Database: A companion dataset for FLUXNET annual product. United States. doi:10.15485/1602532.
Yang, Linqing, and Noormets, Asko. 2020. "Flux Seasonality Metrics Database: A companion dataset for FLUXNET annual product". United States. doi:10.15485/1602532. https://www.osti.gov/servlets/purl/1602532. Pub date:Wed Jan 01 00:00:00 EST 2020
@article{osti_1602532,
title = {Flux Seasonality Metrics Database: A companion dataset for FLUXNET annual product},
author = {Yang, Linqing and Noormets, Asko},
abstractNote = {This dataset include standardized phenological transition dates, and derived season lengths of active, dormant and transition seasons of ecosystem carbon and energy fluxes, as reported in FLUXNET. Such metrics are unique in that they characterize the seasonal dynamics of these fluxes in their own terms rather than in reference to traditional phenology indicators that mostly relate to vegetation structural characteristics. The Flux Seasonality Metrics Database (FSMD) generated 17 standardized seasonality metrics for 4 different fluxes including gross primary productivity (GPP), ecosystem respiration (RE), latent heat (LE) and sensible heat (H) reported in FLUXNET2015 Dataset for about 200 sites and 1500 site-years of data globally. Each metric is reported as an estimate and a confidence interval, which is a function of data coverage and flux variability. We anticipate that the FSMD will facilitate new model validation exercises, and stimulate new research in global change and Earth science disciplines where land-atmosphere exchange dynamics play a central role.},
doi = {10.15485/1602532},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {1}
}

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