the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Aug 2026
CzechGrids Micro: microclimate temperature offset grids at 10 m resolution for the Czech Republic
Abstract. Microclimate represents climatic conditions at spatial scales of meters to tens of meters and often deviates substantially from regional macroclimate due to effects of local topography and land cover. These deviations shape species distributions, ecosystem processes, and organism responses to climate change, yet spatially explicit microclimatic data have long been unavailable at national scales.
Here we present a high-resolution (10 m) dataset of monthly microclimatic temperature offsets for the Czech Republic. Microclimate is expressed as offsets between in situ air temperature measurements at 2 m height and downscaled, elevation-corrected macroclimatic temperatures from the ERA5-Land climate reanalysis. Temperature offsets were modelled separately for mean, minimum, and maximum monthly air temperature using generalized additive models trained on a large network of forest microclimate loggers and standard meteorological stations, covering the period 2018–2024. To capture spatially explicit microclimatic effects, the models integrated variables representing topographic parameters, vegetation characteristics, urban heat island effects and their seasonal dynamics.
The resulting CzechGrids Micro dataset consists of 39 GeoTIFF rasters providing monthly and annual local air temperature offsets that can be combined with downscaled ERA5-Land data to derive absolute microclimatic temperatures for any user-defined periods. The maps are primarily intended for applications in ecological research, climate impact assessments, and adaptation planning at fine spatial scales.
The CzechGrids Micro monthly temperature offset grids are freely available at: https://doi.org/10.5281/zenodo.18472086 (Macek et al., 2026).
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- RC1: 'Comment on essd-2026-344', Anonymous Referee #1, 21 Oct 2026 reply
Data sets
CzechGrids Micro M. Macek et al. https://doi.org/10.5281/zenodo.18472086
Model code and software
CzechGrids Micro M. Macek et al. https://doi.org/10.5281/zenodo.18472086
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General comments
The manuscript and the dataset it presents are of high quality and represent a valuable contribution to several areas of ecological and microclimatic research. The high spatial and temporal resolution of the dataset, including monthly minimum, mean, and maximum offset values at a height of 2 m, further enhances its potential applications. Furthermore, the authors clearly describe potential uses of the dataset and discuss its limitations, particularly in relation to changes in tree cover and the temporal distance from the period for which the dataset was developed. The accompanying code and output files are also well documented and clearly organized, making them readily accessible and straightforward to use.
Overall, the dataset is well constructed and thoroughly documented. I have only a few minor comments and suggestions that could further improve the clarity and accessibility of the manuscript and the dataset.
Specific comments
Table 1. Please check the total number of stations reported. The number of stations listed in the table sums to 810, whereas the caption reports a total of 811 stations.
Line 110, Figure 1: Please clarify in the caption which numbers or labels correspond to local research sites and which correspond to regional sites. In the current version, readers need to cross-reference the text with Table 1 to identify the different locations.
Section 2.3.2 Model training (line 220): Please clarify the definition of the “calendar month” random effect, particularly whether it represents individual calendar months across different years or calendar months pooled across years. Given that the models use observations from 2018–2024, this distinction is important for understanding how interannual temporal variation is handled separately from the cyclic seasonal effect of month. Based on the shared code, the random effect may be defined using a month–year combination. If this is the case, please clarify this in the manuscript as well.
Line 270 and Figure 3: Please clarify the meaning of and distinction between the “station type” variable mentioned in the text and the “locality id” variable shown in Figure 3. It would be helpful to define these variables and explain their respective roles in Section 2.3.2, including clarifying how they are incorporated into the model training.
Line 464: Please provide a reference for the Kilpisjärvi dataset as well.
Section 4.3 Usage guidelines: Please consider adding a few sentences discussing the representation of built-up urban areas in the maps and the applicability of the dataset in these environments. The output files appear to contain values for urban areas, so it would therefore be useful to clarify whether these estimates are considered reliable and suitable for use in urban environments or whether their interpretation should be treated with caution.
Technical corrections
Figure 3: Figure 3 is not cited in the main text. Please add an appropriate in-text reference.
Line 365: There are typographical errors in the sentence. “Thise finding provide” should be corrected to either “These findings provide” or “This finding provides,” depending on the intended meaning. Later in the same sentence, “extend to which” should be corrected to “extent to which.”
Line 385: Please correct the typographical error “the growig season” to “the growing season.”
Line 455: Please check the use of parentheses in the sentence, as a parenthesis appears to be missing or there may be an extra opening parenthesis before the references.