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The existing medium-resolution land cover time series produced under the European Space Agency's Climate Change Initiative provides 29 years (1992-2020) of annual land cover maps at 300-m resolution, allowing for a detailed study of land change dynamics over the contemporary era. Because models need 2D parameters rather than 2D land cover information, the land cover classes must be converted into model-appropriate plant functional types (PFTs) to apply this time series to Earth system and land surface models. The first generation cross-walking table that was presented with the land cover product prescribed pixel-level PFT fractional compositions that varied by land cover class but lacked spatial variability. Here we describe a new ready-to-use data product for climate modelling: spatially explicit annual maps of PFT fractional composition at 300 m resolution for 1992-2020, created by fusing the 300 m medium-resolution land cover product with several existing high-resolution datasets using a globally consistent method. In the resulting data product, which has 14 layers for each of the 29 years, pixel values at 300-m resolution indicate the percentage cover (0-100 %) for each of 14 PFTs, with pixel-level PFT composition exhibiting significant intra-class spatial variability at the global scale. We additionally present an updated version of the user tool that allows users to modify the baseline product (e.g., re-mapping, re-projection, PFT conversion, and spatial sub-setting) to meet individual needs. Finally, these new PFT maps have been used in two land surface models - ORCHIDEE and JULES - to demonstrate their benefit over the conventional maps based on a generic cross-walking table. Regional changes in the fractions of trees, short vegetation, and bare soil cover induce changes in surface properties, such as the albedo, leading to significant changes in surface turbulent fluxes, temperature, and vegetation carbon stocks. [ABSTRACT FROM AUTHOR]

This paper presents a new global, operational burned area (BA) product at 300 m, called C3SBA10, generated from Sentinel-3 Ocean and Land Colour Instrument (OLCI) near-infrared (NIR) reflectance and Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly data. This product was generated within the Copernicus Climate Change Service (C3S). Since C3S is a European service, it aims to use extensively the European Copernicus satellite missions, named Sentinels. Therefore, one of the components of the service is adapting previous developed algorithms to the Sentinel sensors. In the case of BA datasets, the precursor BA dataset (FireCCI51), which was developed within the European Space Agency's (ESA) Climate Change Initiative (CCI), was based on the 250 m-resolution NIR band of the MODIS sensor, and the effort has been focused on adapting this BA algorithm to the characteristics of the Sentinel-3 OLCI sensor, which provides similar spatial and temporal resolution to MODIS. As the precursor BA algorithm, the OLCI's one combines thermal anomalies and spectral information in a two-phase approach, where first thermal anomalies with a high probability of being burned are selected, reducing commission errors, and then a contextual growing is applied to fully detect the BA patch, reducing omission errors. The new BA product includes the full time-series of S3 OLCI data (2017-present). Following the specifications of the FireCCI project, the final datasets are provided in two different formats: monthly full-resolution continental tiles, and monthly global files with aggregated data at 0.25-degree resolution. To facilitate the use by global vegetation dynamics and atmospheric emission models several auxiliary layers were included, such as land cover and cloud-free observations. The C3SBA10 product detected 3.77 Mkm2, 3.59 Mkm2, and 3.63 Mkm2 of annual BA from 2017 to 2019, respectively. The quality and consistency assessment of C3SBA10 and the precursor FireCCI51 was done for the common period (2017-2019). The global spatial validation was performed using reference data derived from Landsat-8 images, following a stratified random sampling design. The C3SBA10 showed commission errors between 14-22 % and omission errors from 50 to 53 %, similar to those presented by the FireCCI51 product. The temporal reporting accuracy was also validated using 4.7 million active fires. 88 % of the detections were made within 10 days after the fire by both products. The spatial and temporal consistency assessment performed between C3SBA10 and FireCCI51 using four different grid sizes (0.05º, 0.10º, 0.25º, and 0.50º) showed global, annual correlations between 0.93 and 0.99. This high consistency between both products ensures a global BA data provision from 2001 to present. The datasets are freely available through the Copernicus Climate Data Store (CDS) repository (DOI: https://doi.org/10.24381/cds.f333cf85, Lizundia-Loiola et al. (2020a)). [ABSTRACT FROM AUTHOR]