Projected future autumn leaf phenology of deciduous trees
Data files
Dec 26, 2023 version files 10.80 GB
-
RCP45_CMC10SiteSpecificModels.zip
-
RCP45_CMC10SpeciesSpecificModels.zip
-
RCP45_CMC11SiteSpecificModels.zip
-
RCP45_CMC11SpeciesSpecificModels.zip
-
RCP45_CMC12SiteSpecificModels.zip
-
RCP45_CMC12SpeciesSpecificModels.zip
-
RCP45_CMC13SiteSpecificModels.zip
-
RCP45_CMC13SpeciesSpecificModels.zip
-
RCP45_CMC14SiteSpecificModels.zip
-
RCP45_CMC14SpeciesSpecificModels.zip
-
RCP45_CMC15SiteSpecificModels.zip
-
RCP45_CMC15SpeciesSpecificModels.zip
-
RCP45_CMC16SiteSpecificModels.zip
-
RCP45_CMC16SpeciesSpecificModels.zip
-
RCP45_CMC1SiteSpecificModels.zip
-
RCP45_CMC1SpeciesSpecificModels.zip
-
RCP45_CMC2SiteSpecificModels.zip
-
RCP45_CMC2SpeciesSpecificModels.zip
-
RCP45_CMC3SiteSpecificModels.zip
-
RCP45_CMC3SpeciesSpecificModels.zip
-
RCP45_CMC4SiteSpecificModels.zip
-
RCP45_CMC4SpeciesSpecificModels.zip
-
RCP45_CMC5SiteSpecificModels.zip
-
RCP45_CMC5SpeciesSpecificModels.zip
-
RCP45_CMC6SiteSpecificModels.zip
-
RCP45_CMC6SpeciesSpecificModels.zip
-
RCP45_CMC7SiteSpecificModels.zip
-
RCP45_CMC7SpeciesSpecificModels.zip
-
RCP45_CMC8SiteSpecificModels.zip
-
RCP45_CMC8SpeciesSpecificModels.zip
-
RCP45_CMC9SiteSpecificModels.zip
-
RCP45_CMC9SpeciesSpecificModels.zip
-
RCP85_CMC10SiteSpecificModels.zip
-
RCP85_CMC10SpeciesSpecificModels.zip
-
RCP85_CMC1SiteSpecificModels.zip
-
RCP85_CMC1SpeciesSpecificModels.zip
-
RCP85_CMC2SiteSpecificModels.zip
-
RCP85_CMC2SpeciesSpecificModels.zip
-
RCP85_CMC3SiteSpecificModels.zip
-
RCP85_CMC3SpeciesSpecificModels.zip
-
RCP85_CMC4SiteSpecificModels.zip
-
RCP85_CMC4SpeciesSpecificModels.zip
-
RCP85_CMC5SiteSpecificModels.zip
-
RCP85_CMC5SpeciesSpecificModels.zip
-
RCP85_CMC6SiteSpecificModels.zip
-
RCP85_CMC6SpeciesSpecificModels.zip
-
RCP85_CMC7SiteSpecificModels.zip
-
RCP85_CMC7SpeciesSpecificModels.zip
-
RCP85_CMC8SiteSpecificModels.zip
-
RCP85_CMC8SpeciesSpecificModels.zip
-
RCP85_CMC9SiteSpecificModels.zip
-
RCP85_CMC9SpeciesSpecificModels.zip
-
README.md
Abstract
Autumn leaf phenology (i.e. leaf colouring or leaf senescence) marks the end of the growing season, during which trees assimilate atmospheric CO2. Since autumn leaf phenology responds to climatic conditions, climate change affects the length of the growing season. Thus, autumn phenology is often modelled to assess possible climate change effects on future CO2 mitigating capacities and species compositions of forests.
Here, we give access to the entire dataset of projected autumn phenology analyzed in Meier and Bigler (2023). The data was derived from different combinations of 21 process-oriented phenology models, 5 optimization algorithms, ≥7 sampling procedures, and 26 climate model chains from two representative concentration pathways. The dataset contains the average autumn phenology per site and for the years 2080-2099 according to each combination that led to a successful calibration. Calibration and validation were based on >45 000 observations for common beech (Fagus sylvatica L.), pedunculate oak (Quercus robur L.), and European larch (Larix decidua Mill.) from 500 Central European sites each.
Cite as Meier, M., & Bigler, C. (2023). Process-oriented models of autumn leaf phenology: Ways to sound calibration and implications of uncertain projections. Geoscientific Model Development, 16(23), 7171–7201. https://doi.org/10.5194/gmd-16-7171-2023
README: Projected autumn leaf phenology of deciduous trees
Autumn leaf phenology was projected to the years 2080-2099 with different process-oriented models that were calibrated as either site- or species-specific models. The calibrations differed in the choice of optimization algorithms and choice of sampling procedures. The models werte driven with downscaled projected climate data from 16 and 10 different climate model chains based on the representative concetration pathways 4.5 and 8.5, respectively, which we derived from the CMIP5-based CORDEX-EUR-11 datasets (Riahi et al. 2011, Thomson et al. 2011, Jacob et al. 2014).
For more detailed information consult the original publication Meier and Bigler (2023).
Please cite as
Meier, M., & Bigler, C. (2023). Process-oriented models of autumn leaf phenology: Ways to sound calibration and implications of uncertain projections. Geoscientific Model Development, 16(23), 7171–7201. https://doi.org/10.5194/gmd-16-7171-2023
References
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., Braun, A., Colette, A., Deque, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., … Yiou, P. (2014). EURO-CORDEX: New high-resolution climate change projections for European impact research. Regional Environmental Change, 14(2), 563–578. https://doi.org/10.1007/s10113-013-0499-2
Meier, M., & Bigler, C. (2023). Process-oriented models of autumn leaf phenology: Ways to sound calibration and implications of uncertain projections. Geoscientific Model Development, 16(23), 7171–7201. https://doi.org/10.5194/gmd-16-7171-2023
Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., Kindermann, G., Nakicenovic, N., & Rafaj, P. (2011). RCP 8.5—A scenario of comparatively high greenhouse gas emissions. Climatic Change, 109(1), 33–57. https://doi.org/10.1007/s10584-011-0149-y
Thomson, A. M., Calvin, K. V., Smith, S. J., Kyle, G. P., Volke, A., Patel, P., Delgado-Arias, S., Bond-Lamberty, B., Wise, M. A., Clarke, L. E., & Edmonds, J. A. (2011). RCP4.5: A pathway for stabilization of radiative forcing by 2100. Climatic Change, 109(1), 77–94. https://doi.org/10.1007/s10584-011-0151-4
Description of the Data and file structure
Each zip folder contains corresponding Rds files that can be opened in R with the base function readRDS().
There is one file for projections based on site- or species-specific models and per combination of representative concentration pathway, species, and model. The data are...
Column name | Description |
---|---|
Delta_100 | The projected difference between the average autumn phenology for the years 2080-2099 (projected) and for the years 1980-1999 (observed) [days]. |
avDOY_projected | The the average autumn phenology for the years 2080-2099 [day of year]. |
avYear_projected | The the average year that corresponds to avDOY_projected [year]. |
avDOY_historical | The the average autumn phenology observed for the years 1980-1999 or last 20 years of the recordings [day of year]. |
avYear_historical | The the average year that corresponds to the avDOY_historical [year]. |
Site | The ID of the site of the observation, which corresponds to the PEP_ID of the PEP725 dataset. |
Species | The species to which the data corresponds (i.e. one of beech, oak, or larch). |
RepresentativeConcentrationPathway | The representative concentration pathway RCP 4.5 or RCP 8.5. |
ClimateModelChain | The climate model chain CMC1, ..., CMC16, referring to the table Appendix S1: Table S5 in Meier and Bigler (2023). |
Model | The process-oriented model for autumn phenology that generated the modelled data. |
Type | Was the data modelled with a site- or species-specific model? |
Algorithm | Which optimization algorithm was used to calibrate the model? (EGO, TREGO, GenSA, PSO, or CMA-ES executed in normal, norm., or extensive, extd., mode). |
SamplingProcedure | The procedure according to which observations or sites were selected for the site- or species-specific calibration, respectively. |
NoOfSites** | The number of sites included in the calibration sample for the species-specific calibration. |
SubDraw** | The draw of the sample, as each sample for species-specific calibration was drawn five times, except for the full sample. |
SiteOfCalibration** | Was this site also used in the calibration of the species-specific model? (TRUE or FALSE). |
n_Delta_100* | Number of projected Delta_100 (i.e. rows) in that very file. |
n_NA_Delta_100* | Number of projected Delta_100 that resulted in NA values in that very file. |
n_Delta_100_Pop** | Number of projected Delta_100 (i.e. rows) in that very file. |
n_NA_Delta_100_Pop** | Number of projected Delta_100 that resulted in NA values in that very file. |
n_Delta_100_Spl** | Number of projected Delta_100 for which SiteOfCalibration was "TRUE" in that very file. |
n_NA_Delta_100_Spl** | Number of projected Delta_100 for which SiteOfCalibration was "TRUE" and that resulted in NA values in that very file. |
* Applies only to site-specific models.
** Applies only to species-specific models.
Reference
Meier, M., & Bigler, C. (2023). Process-oriented models of autumn leaf phenology: Ways to sound calibration and implications of uncertain projections. Geoscientific Model Development, 16(23), 7171–7201. https://doi.org/10.5194/gmd-16-7171-2023
Sharing/access Information
The CORDEX-EUR-11 data was obtained from the Institute for Atmospheric and Climate Science (IAC) at ETH Zurich on August 2021.
Methods
Autumn leaf phenology was projected to the years 2080-2099 with different process-oriented models that were calibrated as either site- or species-specific models. The calibrations differed in the choice of optimization algorithms and choice of sampling procedures. The models werte driven with downscaled projected climate data from 16 and 10 different climate model chains based on the representative concetration pathways 4.5 and 8.5, respectively, which we derived from the CMIP5-based CORDEX-EUR-11 datasets (Riahi et al. 2011, Thomson et al. 2011, Jacob et al. 2014).
The CORDEX-EUR-11 data was obtained from the Institute for Atmospheric and Climate Science (IAC) at ETH Zurich on August 2021.
For more detailed information consult the original publication Meier and Bigler (2023).
References
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., Braun, A., Colette, A., Deque, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., … Yiou, P. (2014). EURO-CORDEX: New high-resolution climate change projections for European impact research. Regional Environmental Change, 14(2), 563–578. https://doi.org/10.1007/s10113-013-0499-2
Meier, M., & Bigler, C. (2023). Process-oriented models of autumn leaf phenology: Ways to sound calibration and implications of uncertain projections. Geoscientific Model Development, 16(23), 7171–7201. https://doi.org/10.5194/gmd-16-7171-2023
Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., Kindermann, G., Nakicenovic, N., & Rafaj, P. (2011). RCP 8.5—A scenario of comparatively high greenhouse gas emissions. Climatic Change, 109(1), 33–57. https://doi.org/10.1007/s10584-011-0149-y
Thomson, A. M., Calvin, K. V., Smith, S. J., Kyle, G. P., Volke, A., Patel, P., Delgado-Arias, S., Bond-Lamberty, B., Wise, M. A., Clarke, L. E., & Edmonds, J. A. (2011). RCP4.5: A pathway for stabilization of radiative forcing by 2100. Climatic Change, 109(1), 77–94. https://doi.org/10.1007/s10584-011-0151-4
Usage notes
The Rds files in the zip folders can be opened in the software R (R Core Team, 2022) with the base function readRDS().