A high-resolution daily gridded meteorological dataset for Serbia made by Random Forest Spatial Interpolation
Samo za registrovane korisnike
2021
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
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.
Ključne reči:
RFSI / temperature / sea level pressure / precipitation / MeteoSerbia1kmIzvor:
Scientific Data, 2021, 8, 123Izdavač:
- Springer Nature
Finansiranje / projekti:
- CERES - Eo-Based Information for Smarter Agriculture and Carbon Farming (RS-6527073)
- BEACON - Boosting Agricultural Insurance based on Earth Observation data (EU-821964)