A New Data Set to Keep a Sharper Eye on Land-Air Exchanges

Pastorello, Gilberto; Papale, Dario; Chu, Housen; Trotta, Carlo; Agarwal, D.; Canfora, E.; Baldocchi, D. D.; Torn, M. S.

doi:10.1029/2017eo071597

Cited by 92 publications

(110 citation statements)

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“…In the past years, there has been substantial progress in the homogenisation and availability of these direct CO 2 flux measurements. The publicly available FLUXNET2015 data set includes more than 1500 site-years of data covering all major biome types from about 165 sites worldwide, spanning a period from 1991 (for some sites) up to 2014 (Pastorello et al, 2017). There has also been substantial progress in the specification of uncertainties in eddy covariance measurements of the land-atmosphere net CO 2 exchange flux (net ecosystem productivity, NEP) and its component fluxes (GPP and ecosystem respiration, R eco ).…”

Section: Observational Uncertaintymentioning

confidence: 99%

Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

et al. 2017

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Abstract. The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well errorcharacterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO 2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al. (2005), emphasising the rapid advance in relevant space-based observations.

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Section: Observational Uncertaintymentioning

confidence: 99%

Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

et al. 2017

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“…) and went through a rigorous quality assurance/quality control (QA/QC) procedure (Pastorello et al. ). The reference NEE (NEE_CUT_REF) was selected as the one with a higher model efficiency sum from the NEE datasets, in which NEE has been filtered with an ensemble of USTAR thresholds.…”

Section: Methodsmentioning

confidence: 99%

Seasonal differences in relationships between changes in spring phenology and dynamics of carbon cycle in grasslands

et al. 2019

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Global warming is dramatically altering the plant phenology of terrestrial ecosystem and thus has caused significant effects on the terrestrial carbon cycle. Many studies have investigated the relationships between the spring phenological changes and the dynamics of carbon cycle, but the seasonal differences in these relationships are still unclear. This study used eddy covariance measurements of grassland net ecosystem productivity (NEP) from nine FLUXNET sites (73 site‐years of data) to investigate the relationships between the spring phenological changes (i.e., early green‐up, EGU; middle green‐up, MGU; and late green‐up, LGU) and the dynamics of carbon cycle (including NEP; ecosystem respiration, ER; and gross ecosystem production, GEP) at a ten‐day scale. Weak relationships were found between the spring phenological changes and the dynamics of ER at all sites. The advance of spring phenology mainly caused significant increases in GEP (or NEP) during the initial 20–50 d after the green‐up date at most sites. With an advancement of 1 d in EGU (MGU and LGU), GEP and NEP were increased by 1.5–6.0 (3.5–7.1 and 2.4–4.7) and 0.7–3.6 (1.5–3.9 and 1.9–4.7) g C/m2 during the early growing season (EGS), respectively. The advance of spring phenology did not have significant impacts on GEP (or NEP) during the middle and late growing season (MGS and LGS) at most sites, but yielded a significant decrease in GEP (or NEP) during MGS at a few sites. As the grasslands turning green, the duration of the impact of the changes in EGU, MGU, and LGU on GEP (or NEP) was reduced, whereas the magnitude of the impact of the changes on the ten‐day cumulative GEP (or NEP) was increased at most sites. Thus, there were two possible impact models for the spring phenological changes on the dynamics of carbon cycle for grasslands: The advance of spring phenology only increases the GEP (or NEP) during EGS, and the advance of spring phenology only decreases the GEP (or NEP) during MGS. These results could be helpful in further understanding the influences of spring phenological changes on the dynamics of carbon cycle for grasslands.

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“…The recently released FLUXNET2015 dataset (December 2015, http://fluxnet.fluxdata.org/data/fluxnet2015-dataset/; Pastorello et al, ) provides a continuous, high‐quality dataset of surface heat fluxes and meteorological data across an extensive range of ecosystems (Baldocchi et al, , ; Agarwal et al, ). Following the International Geosphere‐Biosphere Programme (IGBP) classification, we selected the 65 eddy covariance towers from the FLUXNET2015 dataset across a wide range of climates and biomes, including croplands (CRO; 10 sites), deciduous broadleaf forests (DBF; 11 sites), evergreen broadleaf forests (EBF; six sites), evergreen needleleaf forests (ENF; 14 sites), grasslands (GRA; nine sites), mixed forests (MF; five sites), open shrublands (OSH; two sites), savannas (SAV; three sites), closed shrublands (CSH; two sites), and woody savannas (WAS; three sites).…”

Section: Methodsmentioning

confidence: 99%

A hierarchical Bayesian approach for multi‐site optimization of a satellite‐based evapotranspiration model

Feng

Zhu

et al. 2018

Hydrological Processes

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Modelling is an important tool in simulating and partitioning evapotranspiration (ET). To obtain realistic partitioning of ET, a hierarchical Bayesian (HB) method was used to fit the Priestly–Taylor Jet Propulsion Laboratory (PT‐JPL) model against the multi‐tower Flux Network (FLUXNET) datasets. Unique to the HB method is its ability to exchange of information between sites and simultaneously estimate the species‐and PFT‐level parameters. The results suggested that the sensitive parameters varied at the both species and PFT levels. The parameter β (water control of soil evaporation) exhibited relatively wide species‐and PFT‐level posterior distributions, indicating that the original parameterization of soil moisture constraint may be problematic. Generally, the model with parameters determined by the HB approach showed better performance in predicting and partitioning ET than the original model, especially in evergreen needleleaf forests, open shrublands, closed shrublands, and woody savannas. To overcome the problem of parameter uncertainty (equifinality), direct observations of different components of ET are urgently needed in future studies, and assessments the extent to which the parameter uncertainties are reduced by the use of additional data.

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A New Data Set to Keep a Sharper Eye on Land-Air Exchanges

Abstract: FLUXNET15, the latest update of the longest global record of ecosystem carbon, water, and energy fluxes, features improved data quality, new data products, and more open data sharing policies.

Cited by 92 publications

References 0 publications

Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

Seasonal differences in relationships between changes in spring phenology and dynamics of carbon cycle in grasslands

A hierarchical Bayesian approach for multi‐site optimization of a satellite‐based evapotranspiration model

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