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Data · dataset · 2021

VODCA2GPP

Listed in TU Wien Research Data

Description

The data descriptor paper can be accessed here: doi.org/10.5194/essd-14-1063-2022 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- Gross Primary Productivity (GPP) describes the amount of carbohydrates that is produced by vegetation's synthesis of CO2 and is therefore crucial in the assessment of the global carbon cycle.

VODCA2GPP represents the first microwave remote sensing derived GPP dataset and covers the period between 1988-2020. The data is sampled on a regular 0.25°x 0.25° grid and is based on the novel sink-driven GPP estimation approach introduced by Teubner et al. (2019) and Teubner et al. (2021) . It utilizes the new merged-frequency Vegetation Optical Depth Climate Archive (VODCA CXKu; Zotta et al., in preparation) in combination with ERA5-Land air temperature data to produce a coherent long-term data record of global GPP.

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The dataset also includes an uncertainty metric (var_name: 'Uncertainties' ) which indicates regions where VODCA2GPP estimates tend to be less robust. We advise users to take these uncertainties into account when analyzing the VODCA2GPP data. For more details concerning the production of VODCA2GPP and its accuracy assessment please be referred to our dataset paper which was published in Earth System Science Data Wild et al. (2022 ).

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Satellite remote sensing 65%
Provenance · 1 source records, 8 field assertions
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