Spatio-temporal regression kriging model of mean daily temperature for Croatia
Само за регистроване кориснике
2020
Чланак у часопису (Објављена верзија)
,
Springer Nature
Метаподаци
Приказ свих података о документуАпстракт
High resolution gridded mean daily temperature datasets are valuable for research and applications in agronomy, meteorology, hydrology, ecology, and many other disciplines depending on weather or climate. The gridded datasets and the models used for their estimation are being constantly improved as there is always a need for more accurate datasets as well as for datasets with a higher spatial and temporal resolution. We developed a spatio-temporal regression kriging model for Croatia at 1 km spatial resolution by adapting the spatio-temporal regression kriging model developed for global land areas. A geometrical temperature trend, digital elevation model, and topographic wetness index were used as covariates together with measurements from the Croatian national meteorological network for the year 2008. This model performed better than the global model and previously developed models for Croatia, based on MODIS land surface temperature images. The R2 was 97.8% and RMSE was 1.2 °C for le...ave-one-out and 5-fold cross-validation. The proposed national model still has a high level of uncertainty at higher altitudes leaving it suitable for agricultural areas that are dominant in lower and medium altitudes.
Кључне речи:
Spatio-temporal regression kriging / Mean daily temperature / R meteo package / Gridded dataИзвор:
Theoretical and Applied Climatology, 2020, 140, 101-114Издавач:
- Springer Nature
Финансирање / пројекти:
- Улога и имплементација државног просторног плана и регионалних развојних докумената у обнови стратешког истраживања, мишљења и управљања у Србији (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-47014)
- Просторни, еколошки, енергетски и друштвени аспекти развоја насеља и климатске промене - међусобни утицаји (RS-MESTD-Technological Development (TD or TR)-36035)
- BEACON - Boosting Agricultural Insurance based on Earth Observation data (EU-H2020-821964)
Напомена:
- The authors would like to thank to the National Oceanic and Atmospheric Administration (NOAA) for providing GSOD data and Croatian Meteorological and Hydrological Service (http://meteo.hr) for CMDT dataset. We would also like to thank Hengl et al. (2012) for reproducible research paper published in Theoretical and Applied Climatology Journal and the R-sig-geo community for developing free and open tools for space-time modeling.
DOI: https://doi.org/10.1007/s00704-019-03077-3
ISSN: 1434-4483
WoS: 000504158100002
Scopus: 2-s2.0-85077156104
URI
https://link.springer.com/article/10.1007/s00704-019-03077-3https://grafar.grf.bg.ac.rs/handle/123456789/2257
Колекције
Институција/група
GraFarTY - JOUR AU - Sekulić, Aleksandar AU - Kilibarda, Milan AU - Protić, Dragutin AU - Perčec-Tadić, Melita AU - Bajat, Branislav PY - 2020 UR - https://link.springer.com/article/10.1007/s00704-019-03077-3 UR - https://grafar.grf.bg.ac.rs/handle/123456789/2257 AB - High resolution gridded mean daily temperature datasets are valuable for research and applications in agronomy, meteorology, hydrology, ecology, and many other disciplines depending on weather or climate. The gridded datasets and the models used for their estimation are being constantly improved as there is always a need for more accurate datasets as well as for datasets with a higher spatial and temporal resolution. We developed a spatio-temporal regression kriging model for Croatia at 1 km spatial resolution by adapting the spatio-temporal regression kriging model developed for global land areas. A geometrical temperature trend, digital elevation model, and topographic wetness index were used as covariates together with measurements from the Croatian national meteorological network for the year 2008. This model performed better than the global model and previously developed models for Croatia, based on MODIS land surface temperature images. The R2 was 97.8% and RMSE was 1.2 °C for leave-one-out and 5-fold cross-validation. The proposed national model still has a high level of uncertainty at higher altitudes leaving it suitable for agricultural areas that are dominant in lower and medium altitudes. PB - Springer Nature T2 - Theoretical and Applied Climatology T1 - Spatio-temporal regression kriging model of mean daily temperature for Croatia EP - 114 SP - 101 VL - 140 DO - https://doi.org/10.1007/s00704-019-03077-3 ER -
@article{ author = "Sekulić, Aleksandar and Kilibarda, Milan and Protić, Dragutin and Perčec-Tadić, Melita and Bajat, Branislav", year = "2020", abstract = "High resolution gridded mean daily temperature datasets are valuable for research and applications in agronomy, meteorology, hydrology, ecology, and many other disciplines depending on weather or climate. The gridded datasets and the models used for their estimation are being constantly improved as there is always a need for more accurate datasets as well as for datasets with a higher spatial and temporal resolution. We developed a spatio-temporal regression kriging model for Croatia at 1 km spatial resolution by adapting the spatio-temporal regression kriging model developed for global land areas. A geometrical temperature trend, digital elevation model, and topographic wetness index were used as covariates together with measurements from the Croatian national meteorological network for the year 2008. This model performed better than the global model and previously developed models for Croatia, based on MODIS land surface temperature images. The R2 was 97.8% and RMSE was 1.2 °C for leave-one-out and 5-fold cross-validation. The proposed national model still has a high level of uncertainty at higher altitudes leaving it suitable for agricultural areas that are dominant in lower and medium altitudes.", publisher = "Springer Nature", journal = "Theoretical and Applied Climatology", title = "Spatio-temporal regression kriging model of mean daily temperature for Croatia", pages = "114-101", volume = "140", doi = "https://doi.org/10.1007/s00704-019-03077-3" }
Sekulić, A., Kilibarda, M., Protić, D., Perčec-Tadić, M.,& Bajat, B.. (2020). Spatio-temporal regression kriging model of mean daily temperature for Croatia. in Theoretical and Applied Climatology Springer Nature., 140, 101-114. https://doi.org/https://doi.org/10.1007/s00704-019-03077-3
Sekulić A, Kilibarda M, Protić D, Perčec-Tadić M, Bajat B. Spatio-temporal regression kriging model of mean daily temperature for Croatia. in Theoretical and Applied Climatology. 2020;140:101-114. doi:https://doi.org/10.1007/s00704-019-03077-3 .
Sekulić, Aleksandar, Kilibarda, Milan, Protić, Dragutin, Perčec-Tadić, Melita, Bajat, Branislav, "Spatio-temporal regression kriging model of mean daily temperature for Croatia" in Theoretical and Applied Climatology, 140 (2020):101-114, https://doi.org/https://doi.org/10.1007/s00704-019-03077-3 . .