engleski

Gridded monthly temperature fields for Croatia for the 1981–2010 period

At least six reasons why gridded data are so important in meteorology, climatology and other research fields are described in [Haylock et al., 2008]. Among those the two are especially interesting to us: [1] such interpolated data sets allow best estimates of meteorological variables at locations away from observing stations, thereby allowing studies of local climate in data-sparse regions, [2] validation of Regional Climate Models (RCMs) that generally represent area averaged rather than point processes is most appropriate with interpolated observed data for present climate since such comparison assumes that the observations and model are indicative of processes at the same spatial scale. Hence, there is a high motivation to derive sets of gridded climate data of different temporal and spatial scales for Croatia. Moreover, the intention is to outperform in accuracy, and provide the fields in higher spatial resolution, than available similar European projects. There are several important gridded data sets derived from observations only: [1] the gridded E-OBS of mean daily temperature and precipitation, [2] the EURO4M-APGD Alpine daily precipitation set [Isotta et al., 2014] of 5 km resolution for 1971–2008, [3] GPCC-FD monthly precipitation data set (1901–2013) on coarser 0.5°~56 km resolution and [4] the CRU TS v. 3.23 data set of temperature, precipitation, air pressure and water vapor (1901-2014). Most of the previously mentioned data sets are developed with some variant of regression on climatic factors and interpolation of the anomalies. We will investigate the spatial and temporal scale of those products compared to a newly derived gridded monthly temperature fields for Croatia for the 1981–2010 period. Those grids will be derived with geostatistical methods using regression on climatic factors and interpolation of the anomalies also.

gridded climate data ; monthly temperature ; regression kriging

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