Dataset Open Access

MeteoSerbia1km: the first daily gridded meteorological dataset at a 1-km spatial resolution across Serbia for the 2000–2019 period

Sekulić, Aleksandar; Kilibarda, Milan; Protić, Dragutin; Bajat, Branislav

MeteoSerbia1km is the first daily gridded meteorological dataset at a 1-km spatial resolution across Serbia for the 2000–2019 period. The dataset consists of five daily variables: maximum, minimum and mean temperature, mean sea level pressure, and total precipitation. Besides daily summaries, it contains monthly and annual summaries, daily, monthly, and annual long term means (LTM). Daily gridded data were interpolated using the Random Forest Spatial Interpolation methodology based on Random Forest and using nearest observations and distances to them as spatial covariates, together with environmental covariates.

Complete script in R and datasets used for modelling, tuning, validation, and prediction of daily meteorological variables are available here.

If you discover a bug, artifact or inconsistency in the MeteoSerbia1km maps, or if you have a question please use this channel.

File naming convention of .zip files and containing MeteoSerbia1km files:

  • Daily summaries per year: day_yyyy_proj.zip
    • var_day_yyyymmdd_proj.tif
  • Monthly summaries: mon_proj.zip
    • var_mon_yyyymm_proj.tif
  • Annual summaries: ann_proj.zip
    • var_ann_yyyy_proj.tif
  • Daily, monthly and annual LTM: ltm_proj.zip
    • daily LTM: var_ltm_day_mmdd_proj.tif
    • monthly LTM: var_ltm_mon_mm_proj.tif
    • annual LTM: var_ltm_ann_proj.tif

where:

  • var is a daily meteorological variable name - tmax, tmin, tmean, slp, or prcp
  • proj is a dataset projection - wgs84 or utm34

Units of the dataset values are

  • temperature (Tmean, Tmax, and Tmin) - tenths of a degree in the Celsius scale (℃)
  • SLP - tenths of a mbar
  • PRCP - tenths of a mm

All dataset values are stored as integers (INT32 data type) in order to reduce the size of the GeoTIFF files, i.e., temperature values should be divided by 10 to obtain degrees Celsius, and the same for SLP and PRCP to obtain millibars and millimeters.
 

This research was funded by CERES project, by the Science Fund of the Republic of Serbia – Program for Development of Projects in the Field of Artificial Intelligence, with grant number 6527073, and by BEACON Horizon 2020 Research and Innovation programme under Grant agreement No. 821964. The authors would like to acknowledge OGIMET service (https://www.ogimet.com/), NASA Goddard Space Flight Center (https://www.nasa.gov/goddard), ECA&D project (https://www.ecad.eu), and PIS Vojvodina (http://www.pisvojvodina.com/Shared%20Documents/AMS_pristup.aspx) for providing OGIMET, IMERG, E-OBS, and AMSV data. We would like to thank the R-sig-geo community for developing free and open tools for spatial modeling, and all researchers and developers of R packages that made MeteoSerbia1km data making possible.
Files (7.2 GB)
Name Size
ann_utm34.zip
md5:516a8b4736844dafc749969904bb5ff3
12.8 MB Download
ann_wgs84.zip
md5:4d46cd8fa7c0fe882a253b23e9618638
12.5 MB Download
day_2000_utm34.zip
md5:0a96edfe3dca30c9e76a1185943d50c0
156.6 MB Download
day_2000_wgs84.zip
md5:ea08e4c7db10252e63ff5ddeddb2ea0e
152.8 MB Download
day_2001_utm34.zip
md5:ab8a13b0ee72de7624e2019b48c23579
168.4 MB Download
day_2001_wgs84.zip
md5:bdcbe4af91b86d0c6c95d77c759f87e7
164.3 MB Download
day_2002_utm34.zip
md5:964c1683b4ca1b8b0f375e710a51fe71
168.2 MB Download
day_2002_wgs84.zip
md5:304bb39e328716d407edca9aeb19758c
164.0 MB Download
day_2003_utm34.zip
md5:b6a17a635687ffbfc39d91a3d9bf95c9
166.1 MB Download
day_2003_wgs84.zip
md5:1824c019e071f626d2827fe2da338c59
162.0 MB Download
day_2004_utm34.zip
md5:b5f5adf8c69ed763c1e7431a750bd7b1
169.7 MB Download
day_2004_wgs84.zip
md5:48b90dd7848f49a2d4ee5f16fbdc93d5
165.7 MB Download
day_2005_utm34.zip
md5:47849e42ea04841afe03695cd002a478
169.7 MB Download
day_2005_wgs84.zip
md5:8cab344ac306b1600c9f9a17489bde7d
165.6 MB Download
day_2006_utm34.zip
md5:b66344645c7cab32c11286e1237a7615
167.5 MB Download
day_2006_wgs84.zip
md5:e4fe00120e922ec265f663f381657256
163.5 MB Download
day_2007_utm34.zip
md5:9d558e21f433e81474ae8fbdc6cc8b78
167.3 MB Download
day_2007_wgs84.zip
md5:9f78d821025125308e7f458139656838
163.2 MB Download
day_2008_utm34.zip
md5:606e81143c2b5209097bd07490207402
168.1 MB Download
day_2008_wgs84.zip
md5:ac0e80213e192e6de69335c032ac120a
164.1 MB Download
day_2009_utm34.zip
md5:320866fcb3905f55f34452a18ffca315
170.8 MB Download
day_2009_wgs84.zip
md5:ccfae38787707e5f7dcc4ed21e5f1ac6
166.8 MB Download
day_2010_utm34.zip
md5:e4f83f0436b087d79e17050f50b1b55a
172.2 MB Download
day_2010_wgs84.zip
md5:6176dcc3a07f79c809cbe6d3b8acb613
168.2 MB Download
day_2011_utm34.zip
md5:dad62f58fc418410a0b7fc8140125d2b
164.8 MB Download
day_2011_wgs84.zip
md5:4162507bba8e908bb111c8e12ad9b4f2
161.0 MB Download
day_2012_utm34.zip
md5:96ad3bd8d5d056ee608fac4a12546e5b
166.8 MB Download
day_2012_wgs84.zip
md5:06818c0c78886b55ca121e0c0bbf47b4
162.9 MB Download
day_2013_utm34.zip
md5:f4710dea1d5a3692b977b0008177279b
168.5 MB Download
day_2013_wgs84.zip
md5:649aeb8bbd39fc1ae43936fc235a0a58
164.7 MB Download
day_2014_utm34.zip
md5:85276504ef28a9248bc2dc13d9fe9b0a
171.0 MB Download
day_2014_wgs84.zip
md5:ba84f2d34f6b169b5935aed5b6ab6ba1
167.2 MB Download
day_2015_utm34.zip
md5:6a4e0497f5868969a8be29f15a0fc990
166.6 MB Download
day_2015_wgs84.zip
md5:f00c04e141210cac3ce38c0518423af6
162.9 MB Download
day_2016_utm34.zip
md5:924da132130d6c876fbc7b4c6a6518c4
165.8 MB Download
day_2016_wgs84.zip
md5:bad35db1f26fb4049f23ca3490e5d08e
162.2 MB Download
day_2017_utm34.zip
md5:e525b0da252fbe889bb0e93b2e79e563
166.3 MB Download
day_2017_wgs84.zip
md5:7fd6678fea069386cd9392bef3d1e241
162.6 MB Download
day_2018_utm34.zip
md5:1a258f6adc3b2dc4e39d9baeb5e178fe
169.7 MB Download
day_2018_wgs84.zip
md5:ca48b58b997507f39bbcf2bde6c1a521
166.0 MB Download
day_2019_utm34.zip
md5:faa652011d68ad30c6900c620d956412
168.0 MB Download
day_2019_wgs84.zip
md5:356ac7e9805f2541e43e74cfd7a3f591
164.3 MB Download
ltm_utm34.zip
md5:31d9d88a3dd6562730e71736a70d2409
162.5 MB Download
ltm_wgs84.zip
md5:cba2c0ea8ea9e7ac982a863e975fb53c
158.6 MB Download
mon_utm34.zip
md5:32ab7c11e37bb961b612ab308b9975e6
135.6 MB Download
mon_wgs84.zip
md5:14b981c9c2f4aed959704921ff486c3e
132.6 MB Download
  • Sekulić, A., Kilibarda, M., Heuvelink, G. B., Nikolić, M. & Bajat, B. Random Forest Spatial Interpolation.Remote. Sens. 12, 1687, https://doi.org/10.3390/rs12101687 (2020).

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