VODCA2GPP – a new, global, long-term (1988–2020) gross primary production dataset from microwave remote sensing

[摘要] Long-term global monitoring of terrestrial gross primaryproduction (GPP) is crucial for assessing ecosystem responses to globalclimate change. In recent decades, great advances have been made inestimating GPP and many global GPP datasets have been published. Thesedatasets are based on observations from optical remote sensing, areupscaled from in situ measurements, or rely on process-based models.Although these approaches are well established within the scientificcommunity, datasets nevertheless differ significantly. Here, we introduce the new VODCA2GPP dataset, which utilizes microwaveremote sensing estimates of vegetation optical depth (VOD) to estimate GPPat the global scale for the period 1988–2020. VODCA2GPP applies a previouslydeveloped carbon-sink-driven approach (Teubner et al., 2019, 2021) toestimate GPP from the Vegetation Optical Depth Climate Archive (Moesinger etal., 2020; Zotta et al., 2022​​​​​​​), which merges VOD observations frommultiple sensors into one long-running, coherent data record. VODCA2GPP wastrained and evaluated against FLUXNET in situ observations of GPP andcompared against largely independent state-of-the-art GPP datasets fromthe Moderate Resolution Imaging Spectroradiometer (MODIS), FLUXCOM, and the TRENDY-v7 process-based model ensemble. The site-level evaluation with FLUXNET GPP indicates an overall robustperformance of VODCA2GPP with only a small bias and good temporal agreement.The comparisons with MODIS, FLUXCOM, and TRENDY-v7 show that VODCA2GPPexhibits very similar spatial patterns across all biomes but with aconsistent positive bias. In terms of temporal dynamics, a high agreementwas found for regions outside the humid tropics, with median correlationsaround 0.75. Concerning anomalies from the long-term climatology, VODCA2GPPcorrelates well with MODIS and TRENDY-v7 (Pearson's r 0.53 and 0.61) butless well with FLUXCOM (Pearson's r 0.29). A trend analysis for the period1988–2019 did not exhibit a significant trend in VODCA2GPP at the global scalebut rather suggests regionally different long-term changes in GPP. For theshorter overlapping observation period (2003–2015) of VODCA2GPP, MODIS, andthe TRENDY-v7 ensemble, significant increases in global GPP were found.VODCA2GPP can complement existing GPP products and is a valuable dataset forthe assessment of large-scale and long-term changes in GPP for globalvegetation and carbon cycle studies. The VODCA2GPP dataset is available at the TU Data Repository of TU Wien ( https://doi.org/10.48436/1k7aj-bdz35 , Wild et al.,2021).

[学科分类] 眼科学