Published September 22, 2021
| Version
v1
Dataset
Open
Data from: High-resolution analysis of observed thermal growing season variability over northern Europe
Creators
- 1. Finnish Meteorological Institute
Contributors
Other:
Description
The dataset include the main output of the study Aalto et al. (2021), that is, the predicted spatial variability in mean growing season variables (1990-2019) and their temporal trends (1950-2019) over northern Europe. The produced high-resolution datasets (100 x 100 m) showcased the diversity in thermal GS conditions and impacts of climate change over northern Europe and are valuable in various forest management and ecosystem applications, and in adaptation to climate change.
Original publication: Aalto, J., Pirinen, P., Kauppi, P. E., Rantanen, M., Lussana, C., Lyytikäinen-Saarenmaa, P., & Gregow, H. (2021). High-resolution analysis of observed thermal growing season variability over northern Europe. Climate Dynamics. https://doi.org/10.1007/s00382-021-05970-y
Files
gs_layers.zip
Files
(1.8 GB)
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Additional details
Identifiers
- URL
- https://etsin.fairdata.fi/dataset/d45040e8-0bce-4143-b473-3e967ff89ebb
- B2SHARE Legacy Record ID
- ff569ebaa62a4e75bacafd76ad2a9ab6
Related works
- Is published in
- Other: 10.1007/s00382-021-05970-y (DOI)
Funding
- Ministry of Agriculture and Forestry of Finland (project Monituho, decision number VN/5514/2020)
- Academy of Finland Flagship funding (grant no. 337552)
FMI metadata
- Process step
- We define the thermal growing season as the period when daily mean temperature (Tday) is permanently at or above +5 °C. The beginning and end of the growing season was determined using the so-called integral method (see Ruosteenoja et al. 2016), which identifies the date after the absolute minimum of the sum(Tday-threshold) has been reached (GSbeg) and analogously GSend when 190 the absolute maximum of the sum(Tday-threshold) has been reached, but not earlier than 1st of June. To secure consistency of the final data layers, gs_len was produced by subtracting the predicted gs_end from the predicted gs_beg.
- Source data
- The data layers are in geotiff -format and in ETRS-LAEA coordinate reference system (epsg: 3035). Spatial resolution is 100 x 100 m.
- Lineage
- The accuracy of the produced layers have been evaluated againt weather station data using cross-validation. See the related research arcticle for details.
- Model
- Statistical modeling using generalized additive models (GAM)
- Parameter
- Data levels (meter, hectoPascal, degree, sigma pressure levels, other) in vertical direction(+/-) for example 1500 m or 850 hPa
- Supplemental information
- When using the data, please cite the paper by Aalto et al., (2021): https://doi.org/10.1007/s00382-021-05970-y
- Topic category
- climatologyMeteorologyAtmosphere
Parameter name
:
gs_beg
Parameter unit
:
DOY
Parameter description
:
Beginning of the thermal growing season
Parameter name
:
gs_end
Parameter unit
:
DOY
Parameter description
:
End of the thermal growing season
Parameter name
:
gs_len
Parameter unit
:
Days
Parameter description
:
Length of the growing season
Parameter name
:
gdds
Parameter unit
:
°C days
Parameter description
:
Degree day sum
Parameter name
:
gs_beg_trend
Parameter unit
:
days per year
Parameter description
:
Temporal trend in gs_beg
Parameter name
:
gs_end_trend
Parameter unit
:
days per year
Parameter description
:
Temporal trend in gs_end
Parameter name
:
gs_len_trends
Parameter unit
:
days per year
Parameter description
:
Temporal trend in gs_len
Parameter name
:
gdds_trend
Parameter unit
:
°C days per year
Parameter description
:
Temporal trend in GDDS
Level
:
surface
Temporal Coverage
Ranges:
Start date: 1949-12-31
End date: 2019-12-30
End date: 2019-12-30
Spans:
Span: