Gridovi fine prostorne rezolucije dnevnih visina snijega za Rumunjsku (2005.–2015.)

This study presents the spatial interpolation procedure from snow depth measurements at weather stations implying the following stages: (1) Spatial interpolation at 1 km × 1 km resolution of the mean multiannual values (2005-2015) corresponding to each month, computed from the data extracted from the climatological database; (2) Computation of the daily deviations against the multiannual monthly mean for every day and year over 2005–2015 and their spatial interpolation; (3) Spatio-temporal datasets were obtained through merging the two surfaces obtained in stages 1 and 2. The anomalies were considered to be the ratio between the daily snow depth values and the climatology. The spatial variability of the data used in the first stage was accounted for through the use of a series of predictors derived from the digital elevation model (DEM). To plot the maps with the climatological normals (multiannual means), the Regression-Kriging (RK) spatial interpolation method was used. In order to choose the optimum method applied in spatializing deviations, four interpolation methods were tested using a cross-validation procedure: Multiquadratic, Ordinary Kriging (separated and pooled variograms) and 3d Kriging.Ova studija prikazuje proceduru prostorne interpolacije mjerenja dubine snijega na meteorološkim postajama koja podrazumijeva sljedeće faze: (1) prostorna interpolacija pri rezoluciji od 1 km x 1 km srednjih višegodišnjih vrijednosti (2005.–2015.), koja se provodi s podacima iz klimatološke baze; (2) izračunavanje dnevnih odstupanja od višegodišnjeg mjesečnog srednjaka za svaki dan i godinu tijekom razdoblja od 2005. do 2015. i njihova prostorna interpolacija; (3) prostorno-vremenski skup podataka dobiven je združivanjem procjena dobivenih u fazi 1 i 2. Odstupanja su definirana kao omjeri dnevnih vrijednosti dubine snijeg i klimatološkog srednjaka. Prostorna varijabilnost podataka korištenih u prvoj fazi objašnjena je korištenjem niza prediktora izvedenih iz digitalnog modela visina (DEM). Karte klimatoloških normala (višegodišnji srednjaci) izrađene su metodom prostorne interpolacije zvanom regresijski kriging (RK). Za odabir optimalne metode za prostornu interpolaciju odstupanja, testirane su četiri metode interpolacije i ocijenjene pomoću postupka poprečne validacije: multikvadratična, obični kriging (razdvojeni i skupni variogrami) i 3D kriging

A unifying modelling of multiple land degradation pathways in Europe

Land degradation is a complex socio-environmental threat, which generally occurs as multiple concurrent pathways that remain largely unexplored in Europe. Here we present an unprecedented analysis of land multi-degradation in 40 continental countries, using twelve dataset-based processes that were modelled as land degradation convergence and combination pathways in Europe’s agricultural (and arable) environments. Using a Land Multi-degradation Index, we find that up to 27%, 35% and 22% of continental agricultural (~2 million km2) and arable (~1.1 million km2) lands are currently threatened by one, two, and three drivers of degradation, while 10–11% of pan-European agricultural/arable landscapes are cumulatively affected by four and at least five concurrent processes. We also explore the complex pattern of spatially interacting processes, emphasizing the major combinations of land degradation pathways across continental and national boundaries. Our results will enable policymakers to develop knowledge-based strategies for land degradation mitigation and other critical European sustainable development goals

ROCADA: Romanian daily gridded climatic dataset (1961-2013) V1.0

Daily records of nine meteorological variables covering the interval 1961-2013 were used in order to create a state-of-the-art homogenized climatic dataset over Romania at a spatial resolution of 0.1°. All meteorological stations with full data records, as well as stations with up to 30 % missing data, were used for the following variables: air pressure (150 stations); minimum, maximum, and average air temperature (150 stations); soil temperature (127 stations); precipitation (188 stations); sunshine hours (135 stations); cloud cover (104 stations); relative humidity (150 stations). For each parameter, the data series were first homogenized with the software MASH (Multiple Analysis of Series for Homogenization); then, the data series were gridded by means of the software MISH (Meteorological Interpolation based on Surface Homogenized Data)