Data and Tools

Carbon turnover times: Naixin has synthesized and processed multiple global datasets of gross primary productivity, soil carbon, and vegetation carbon, to generate a large ensemble of global whole ecosystem carbon turnover times (Fan et al., 2020). The previous dataset developed by Nuno has already been used for evaluation of Earth System Models (Carvalhais et al., 2014). Both these data are publicly available through the data portal of Max Planck Institute for Biogeochemistry.

ESMValTool: The Earth System Model Evaluation Tool (ESMValTool) is a community-development that aims at improving, diagnosing and understanding the causes and effects of model biases and inter-model spread. Within CRESCENDO project, Sujan contributed an ESMValTool “recipe” that diagnoses the ESM simulations of 𝝉.

Forest age: based on forest inventory data, Simon developed a ML model to derive forest stand age from global remote sensing and climate data.

Global Aboveground Biomass: we collaborated with GAMMA Remote Sensing, within the GlobBiomass ESA DUE consortium, to develop a global high resolution map of above ground biomass. The data can be found here: https://doi.pangaea.de/10.1594/PANGAEA.894711.

Lambda: Çağlar (GDM/MDI) developed a new ecohydrological dataset of metrics characterizing the vegetation dynamics under moisture limitation in Africa using daily time series of Fraction of Vegetation Cover (FVC) from the geostationary METEOSAT satellite (Küçük et al., 2020).

TEA: Transpiration Estimation Algorithm: Jake (GDM/MDI) makes available data (https://zenodo.org/record/3978408#.YECpgWLPx_V), the algorithms and some of the tools developed in investigating the evapotranspiration flux partitioning from eddy covariance data (https://github.com/jnelson18/TranspirationEstimationAlgorithm).