VODCA2GPP - A new global, long-term (1988-2020) GPP dataset from passive microwave remote sensing

Abstract

Long-term global monitoring of terrestrial Gross Primary Production (GPP) is crucial for assessing ecosystem response 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 either 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.

Here, we introduce the new VODCA2GPP product (Wild et al., 2021), which utilizes microwave remote sensing estimates of Vegetation Optical Depth (VOD) to estimate GPP at 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), 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 MODIS, FLUXCOM GPP and the TRENDY-v7 process-based model ensemble.

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 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 GPP (Pearson’s r: 0.53 and 0.61) but less well with FLUXCOM GPP (Pearson’s r: 0.29). A trend analysis for the period 1988-2019 did not exhibit a significant trend in VODCA2GPP at global scale but rather suggests regionally different long-term changes in GPP. For the shorter overlapping observation period (2003-2015) of VODCA2GPP, MODIS GPP, and the TRENDY-v7 ensemble significant increases of 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 freely accessible at TU Wien Research Data (https://doi.org/10.48436/1k7aj-bdz35; Wild et al., 2021).