We produced the first daily gridded meteorological dataset at a 1-km spatial resolution across Serbia for 2000–2019, named MeteoSerbia1km. The dataset consists of five daily variables: maximum, minimum and mean temperature, mean sea-level pressure, and total precipitation. In addition to daily summaries, we produced monthly and annual summaries, and daily, monthly, and annual long-term means. Daily gridded data were interpolated using the Random Forest Spatial Interpolation methodology, based on using the nearest observations and distances to them as spatial covariates, together with environmental covariates to make a random forest model. The accuracy of the MeteoSerbia1km daily dataset was assessed using nested 5-fold leave-location-out cross-validation. All temperature variables and sea-level pressure showed high accuracy, although accuracy was lower for total precipitation, due to the discontinuity in its spatial distribution. MeteoSerbia1km was also compared with the E-OBS dataset ...with a coarser resolution: both datasets showed similar coarse-scale patterns for all daily meteorological variables, except for total precipitation. As a result of its high resolution, MeteoSerbia1km is suitable for further environmental analyses.
TY - JOUR
AU - Sekulić, Aleksandar
AU - Kilibarda, Milan
AU - Protić, Dragutin
AU - Bajat, Branislav
PY - 2021
UR - https://www.nature.com/articles/s41597-021-00901-2
UR - https://grafar.grf.bg.ac.rs/handle/123456789/2355
AB - We produced the first daily gridded meteorological dataset at a 1-km spatial resolution across Serbia for 2000–2019, named MeteoSerbia1km. The dataset consists of five daily variables: maximum, minimum and mean temperature, mean sea-level pressure, and total precipitation. In addition to daily summaries, we produced monthly and annual summaries, and daily, monthly, and annual long-term means. Daily gridded data were interpolated using the Random Forest Spatial Interpolation methodology, based on using the nearest observations and distances to them as spatial covariates, together with environmental covariates to make a random forest model. The accuracy of the MeteoSerbia1km daily dataset was assessed using nested 5-fold leave-location-out cross-validation. All temperature variables and sea-level pressure showed high accuracy, although accuracy was lower for total precipitation, due to the discontinuity in its spatial distribution. MeteoSerbia1km was also compared with the E-OBS dataset with a coarser resolution: both datasets showed similar coarse-scale patterns for all daily meteorological variables, except for total precipitation. As a result of its high resolution, MeteoSerbia1km is suitable for further environmental analyses.
PB - Springer Nature
T2 - Scientific Data
T1 - A high-resolution daily gridded meteorological dataset for Serbia made by Random Forest Spatial Interpolation
IS - 123
VL - 8
DO - 10.1038/s41597-021-00901-2
ER -
@article{
author = "Sekulić, Aleksandar and Kilibarda, Milan and Protić, Dragutin and Bajat, Branislav",
year = "2021",
url = "https://www.nature.com/articles/s41597-021-00901-2, https://grafar.grf.bg.ac.rs/handle/123456789/2355",
abstract = "We produced the first daily gridded meteorological dataset at a 1-km spatial resolution across Serbia for 2000–2019, named MeteoSerbia1km. The dataset consists of five daily variables: maximum, minimum and mean temperature, mean sea-level pressure, and total precipitation. In addition to daily summaries, we produced monthly and annual summaries, and daily, monthly, and annual long-term means. Daily gridded data were interpolated using the Random Forest Spatial Interpolation methodology, based on using the nearest observations and distances to them as spatial covariates, together with environmental covariates to make a random forest model. The accuracy of the MeteoSerbia1km daily dataset was assessed using nested 5-fold leave-location-out cross-validation. All temperature variables and sea-level pressure showed high accuracy, although accuracy was lower for total precipitation, due to the discontinuity in its spatial distribution. MeteoSerbia1km was also compared with the E-OBS dataset with a coarser resolution: both datasets showed similar coarse-scale patterns for all daily meteorological variables, except for total precipitation. As a result of its high resolution, MeteoSerbia1km is suitable for further environmental analyses.",
publisher = "Springer Nature",
journal = "Scientific Data",
title = "A high-resolution daily gridded meteorological dataset for Serbia made by Random Forest Spatial Interpolation",
number = "123",
volume = "8",
doi = "10.1038/s41597-021-00901-2"
}
Sekulić, A., Kilibarda, M., Protić, D.,& Bajat, B. (2021). A high-resolution daily gridded meteorological dataset for Serbia made by Random Forest Spatial Interpolation.
Scientific Data
Springer Nature., 8(123).
https://doi.org/10.1038/s41597-021-00901-2
Sekulić A, Kilibarda M, Protić D, Bajat B. A high-resolution daily gridded meteorological dataset for Serbia made by Random Forest Spatial Interpolation. Scientific Data. 2021;8(123)
Sekulić Aleksandar, Kilibarda Milan, Protić Dragutin, Bajat Branislav, "A high-resolution daily gridded meteorological dataset for Serbia made by Random Forest Spatial Interpolation" Scientific Data, 8, no. 123 (2021),
https://doi.org/10.1038/s41597-021-00901-2 .
,