The HiGridTemp project supported by a grant of Ministery of Research and Innovation, CNCS – UEFISCDI, project number PN-III-P1-1.1-PD-2016-1579, within PNCDI III, aims to create an enhanced and up-to-date gridded temperature dataset at the finest spatial and temporal scale using combined ground-based and satellite products as main inputs, along the period 2009-2016. The originality of the project consists in the fact that it is for the first time when an hourly gridded dataset is constructed over Romania using state-of-the-art spatial statistical techniques. Another element of originality consists in providing to the Academia and other end-users a freely available dataset of hourly temperature at 1km resolution, which could create relevant input for developing other socio-economical domains highly depending on climatological information.
Hourly data series from the weather stations network of the National Meteorological Administration and LST satellite products will be used, while supplementary data will refer to a series of predictors derived from the digital terrain model, as well as from land use/land cover data (e.g., CORINE Land Cover). The resulted database will be exploited for a detailed analysis of the actual climate and for investigating the climate variability in Romania, at fine (spatio-temporal) scale. As regards the methodology, another innovation is that the gridded datasets will be created using exclusively open source software, dedicated to both the processing and statistical analysis of geo-spatial datasets. Data and metadata will be made available in a standard format, regularly used by the scientific community, and which is portable (machine independent) and self-describing (files can be examined and read by the appropriate software without disclosing the file’s structural details to the user).
The main project outputs will consist in the online publication of enhanced maps illustrating the spatial distribution of the air temperature, and methodological guidelines to support further applications and knowledge transfer.