VODCA2GPP – a new, global, long-term (1988–2020) gross primary production dataset from microwave remote sensing
<p>Long-term global monitoring of terrestrial gross primary production (GPP) is crucial for assessing ecosystem responses to global climate change. In recent decades, great advances have been made in estimating GPP and many global GPP datasets have been published. These datasets are based on o...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-03-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/14/1063/2022/essd-14-1063-2022.pdf |
| Summary: | <p>Long-term global monitoring of terrestrial gross primary
production (GPP) is crucial for assessing ecosystem responses to global
climate change. In recent decades, great advances have been made in
estimating GPP and many global GPP datasets have been published. These
datasets are based on observations from optical remote sensing, are
upscaled from in situ measurements, or rely on process-based models.
Although these approaches are well established within the scientific
community, datasets nevertheless differ significantly.</p>
<p>Here, we introduce the new VODCA2GPP dataset, which utilizes microwave
remote sensing estimates of vegetation optical depth (VOD) to estimate GPP
at the global scale for the period 1988–2020. VODCA2GPP applies a previously
developed carbon-sink-driven approach (Teubner et al., 2019, 2021) to
estimate GPP from the Vegetation Optical Depth Climate Archive (Moesinger et
al., 2020; Zotta et al., 2022), which merges VOD observations from
multiple sensors into one long-running, coherent data record. VODCA2GPP was
trained and evaluated against FLUXNET in situ observations of GPP and
compared against largely independent state-of-the-art GPP datasets from
the Moderate Resolution Imaging Spectroradiometer (MODIS), FLUXCOM, and the TRENDY-v7 process-based model ensemble.</p>
<p>The site-level evaluation with FLUXNET GPP indicates an overall robust
performance of VODCA2GPP with only a small bias and good temporal agreement.
The comparisons with MODIS, FLUXCOM, and TRENDY-v7 show that VODCA2GPP
exhibits very similar spatial patterns across all biomes but with a
consistent positive bias. In terms of temporal dynamics, a high agreement
was found for regions outside the humid tropics, with median correlations
around 0.75. Concerning anomalies from the long-term climatology, VODCA2GPP
correlates well with MODIS and TRENDY-v7 (Pearson's <span class="inline-formula"><i>r</i></span> 0.53 and 0.61) but
less well with FLUXCOM (Pearson's <span class="inline-formula"><i>r</i></span> 0.29). A trend analysis for the period
1988–2019 did not exhibit a significant trend in VODCA2GPP at the global scale
but rather suggests regionally different long-term changes in GPP. For the
shorter overlapping observation period (2003–2015) of VODCA2GPP, MODIS, and
the TRENDY-v7 ensemble, significant increases in global GPP were found.
VODCA2GPP can complement existing GPP products and is a valuable dataset for
the assessment of large-scale and long-term changes in GPP for global
vegetation and carbon cycle studies. The VODCA2GPP dataset is available at the TU Data Repository of TU Wien (<a href="https://doi.org/10.48436/1k7aj-bdz35">https://doi.org/10.48436/1k7aj-bdz35</a>, Wild et al.,
2021).</p> |
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| ISSN: | 1866-3508 1866-3516 |