The World Settlement Footprint WSF 2015 version 2 (WSF2015 v2) is a 10m resolution binary mask outlining the extent of human settlements globally for the year 2015. Specifically, the WSF2015 v2 is a pilot product generated by combining multiple datasets, namely: • The WSF2015 v1 derived at 10m spatial resolution by means of 2014-2015 multitemporal Landsat-8 and Sentinel-1 imagery (of which ~217K and ~107K scenes have been processed, respectively); https://doi.org/10.1038/s41597-020-00580-5 • The High Resolution Settlement Layer (HRSL) generated by the Connectivity Lab team at Facebook through the employment of 2016 DigitalGlobe VHR satellite imagery and publicly released at 30m spatial resolution for 214 countries; https://arxiv.org/pdf/1712.05839.pdf • The novel WSF2019 v1 derived at 10m spatial resolution by means of 2019 multitemporal Sentinel-1 and Sentinel-2 imagery (of which ~ 1.2M and ~1.8M scenes have been processed, respectively); https://doi.org/10.1553/giscience2021_01_s33 The WSF2015 v1 demonstrated to be highly accurate, outperforming all similar existing global layers; however, the use of Landsat imagery prevented a proper detection of very small structures, mostly due to their reduced scale. Based on an extensive qualitative assessment, wherever available the HRSL layer shows instead a systematic underestimation of larger settlements, whereas it proves particularly effective in identifying smaller clusters of buildings down to single houses, thanks to the employment of 2016 VHR imagery. The WSF2015v v2 has been then generated by: i) merging the WSF2015 v1 and HRSL (after resampling to 10m resolution and disregarding the population density information attached); and ii) masking the outcome by means of the WSF2019 product, which exhibits even higher detail and accuracy, also thanks to the use of Sentinel-2 data and the proper employment of state-of-the-art ancillary datasets (which allowed, for instance, to effectively mask out all roads globally from motorways to residential).

The warning messages contain information about records from Voluntary Observing Ships (VOS) with unusable or incomplete entries for which a quality assessment cannot be performed. The file contains text information and, in the case of inconsistencies in the meteorological data, the relevant message is added in IMMT format.

Global maps of monthly mean surface air pressure derived from GME model data , WMO RA VI Regional Climate Centre (RCC) on Climate Monitoring

The raw data files contain all delayed mode weather reports from Voluntary Observing Ships (VOS) that were sent to the Voluntary Observing Ship Global Data Assembly Centres (VOS-GDACs). Quality control has been carried out in the country of origin, but verification by the VOS-GDACs has not yet taken place.

Global maps of monthly normals 1961-1990 of surface air pressure derived from GME model data, provided by WMO RA VI Regional Climate Centre (RCC) on Climate Monitoring

The World Settlement Footprint (WSF) 2019 is a 10m resolution binary mask outlining the extent of human settlements globally derived by means of 2019 multitemporal Sentinel-1 (S1) and Sentinel-2 (S2) imagery. Based on the hypothesis that settlements generally show a more stable behavior with respect to most land-cover classes, temporal statistics are calculated for both S1- and S2-based indices. In particular, a comprehensive analysis has been performed by exploiting a number of reference building outlines to identify the most suitable set of temporal features (ultimately including 6 from S1 and 25 from S2). Training points for the settlement and non-settlement class are then generated by thresholding specific features, which varies depending on the 30 climate types of the well-established Köppen Geiger scheme. Next, binary classification based on Random Forest is applied and, finally, a dedicated post-processing is performed where ancillary datasets are employed to further reduce omission and commission errors. Here, the whole classification process has been entirely carried out within the Google Earth Engine platform. To assess the high accuracy and reliability of the WSF2019, two independent crowd-sourcing-based validation exercises have been carried out with the support of Google and Mapswipe, respectively, where overall 1M reference labels have been collected based photointerpretation of very high-resolution optical imagery.

Annual lists containing information about the international data contributions to the Voluntary Observing Ship Global Data Assembly Centres (VOS-GDACs).

Global maps of anomalies of monthly mean surface air pressure derived from GME model data (reference period 1961-1990), WMO RA VI Regional Climate Centre (RCC) on Climate Monitoring

Global maps of mean surface air pressure (means and anomalies) derived from GME model data, provided by WMO RA VI Regional Climate Centre (RCC) an Climate Monitoring

Dregs data are part of the worldwide weather reports of the Voluntary Observing Ships (VOS) that are internationally exchanged via the Voluntary Observing Ship Global Data Assembly Centres (VOS-GDACs) on a quarterly basis. The dregs files contain records that were rejected during the quality check. This is mostly related to duplicate messages. The data format is International Maritime Meteorological Tape (IMMT) and from 2010 on also International Maritime Meteorological Archive (IMMA).