Pregled bibliografske jedinice broj: 654183
Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution
Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution // Journal of geophysical research. Atmospheres, 119 (2013), 5; 2294-2313 doi:10.1002/2013JD020803 (međunarodna recenzija, članak, znanstveni)
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Naslov
Spatio-temporal interpolation of daily temperatures
for global land areas at 1 km resolution
Autori
Kilibarda, Milan ; Hengl, Tomislav ; Heuvelink, Gerard B.M. ; Graeler, Benedikt ; Pebesma, Edzer ; Perčec Tadić, Melita ; Bajat, Branislav
Izvornik
Journal of geophysical research. Atmospheres (2169-897X) 119
(2013), 5;
2294-2313
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
air temperature ; global ; spatio-temporal prediction
Sažetak
Around 9000 stations from merged GSOD and ECA&D daily meteorological data sets were used to build spatio-temporal geostatistical models and predict daily air temperature at ground resolution of 1 km for the global land mass. Predictions were made for the mean, maximum and minimum temperature using spatio-temporal regression-kriging with a time series of MODIS 8 day images, topographic layers (DEM and TWI) and a geometrical temperature trend as covariates. The model and predictions were built for the year 2011 only, but the same methodology can be extended for the whole range of the MODIS LST images (2001–today). The accuracy of predicting daily temperatures has been assessed using leave-one-out cross-validation ; the standard approach is extended with block approach. The values were aggregated for blocks of land of size 500×500 km 13 to account for geographical point clustering of station data. All computations 14 were implemented in the R environment for statistical computing by combin- 15 16 ing functionality of the gstat package (geostatistical modelling), rgdal and raster packages (raster data loading and analysis), and snowfall package (cluster computing). - removed The results show that the average accuracy for predicting mean, maximum and minimum daily temperatures is RMSE=2°C for areas densely covered with stations, and between 2°C and 4°C for areas with lower station density. The lowest prediction accuracy was observed in highlands (>1000 m) and in Antarctica with a RMSE around 6°C. This automated geostatistical framework could be used to produce global archives of daily temperatures (new generation WorldClim repository) and to feed various global environmental models.
Izvorni jezik
Engleski
Znanstvena područja
Geologija
POVEZANOST RADA
Projekti:
MZOS-004-1193086-3035 - Klimatske varijacije i promjene i odjek u područjima utjecaja (Gajić-Čapka, Marjana, MZOS ) ( CroRIS)
Ustanove:
Državni hidrometeorološki zavod
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus