data

Climate model datasets

EURO-CORDEX

Generated using the DKRZ intake-esm stores

Data specifications:

Project: CORDEX
Experiments:
- historical (1976-2005)
- rcp45, rcp85 (2041-2070)
Frequency: day
Domain: EUR-11 (12.5 km)
Variables: evspsblpot, pr, rsds, tas
ESGF node: NSC LIU
Driving models (and ensemble):
- MPI-M-MPI-ESM-LR (r1i1p1)
- CNRM-CERFACS-CNRM-CM5 (r1i1p1)
- MOHC-HadGEM2-ES (r1i1p1)
- ICHEC-EC-EARTH (r12i1p1)
RCM: RCA4

To automate downloading these data, run the Wget script(s):

./wget-esg-dn1.nsc.liu.se.sh

The data will be downloaded to the working directory. To move the files into subdirectories:

./move-eurocordex-downloads.sh

ESGF login credentials will be requested once the script is run. See the ESGF Wget documentation for more information. If there is a username/password authentication failure, ensure the ESGF user account being used has joined the CORDEX research group.

Links:

Jacob, D. et al. (2014). 'EURO-CORDEX: new high-resolution climate change projections for European impact research', Regional Environmental Change, vol. 14, no. 2, pp. 563–578. DOI: 10.1007/s10113-013-0499-2.

HiResIreland

https://epa.ie/pubs/reports/research/climate/researchreport339/

Data specifications:

Experiments:
- historical (1976-2005)
- rcp45, rcp85 (2041-2070)
Frequency: day
Resolution: 4 km
Variables: ET, T_2M, TOT_PREC, ASWDIR_S, ASWDIFD_S
Driving models (and ensemble):
- MPI-M-MPI-ESM-LR (r1i1p1)
- CNRM-CERFACS-CNRM-CM5 (r1i1p1)
- MOHC-HadGEM2-ES (r1i1p1)
- ICHEC-EC-EARTH (r12i1p1)
RCM: COSMO5-CLM

Nolan, P. and Flanagan, J. (2020). High-resolution Climate Projections for Ireland - A Multi-model Ensemble Approach (2014-CCRP-MS.23), EPA Research Programme 2014-2020, EPA Research Report, Johnstown Castle, Co. Wexford, Ireland, Environmental Protection Agency (EPA). Online. (Accessed 23 June 2022).

Meteorological data

Met Éireann Reanalysis (MÉRA)

https://www.met.ie/climate/available-data/mera

Variable	Identifier	Unit
Surface pressure*	`1 105 0 0`	Pa
2 m temperature	`11 105 2 0`	K
Maximum temperature*	`15 105 2 2`	K
Minimum temperature*	`16 105 2 2`	K
u-component of 10 m wind*	`33 105 10 0`	m s⁻¹
v-component of 10 m wind*	`34 105 10 0`	m s⁻¹
2 m relative humidity*	`52 105 2 0`	%
Total precipitation	`61 105 0 4`	kg m⁻²
Net shortwave irradiance*	`111 105 0 4`	J m⁻²
Net longwave irradiance*	`112 105 0 4`	J m⁻²
Global irradiance	`117 105 0 4`	J m⁻²

Variables marked with an * are used to derive evapotranspiration using the FAO Penman-Monteith equation. Note that the irradiance variables are incorrectly assigned W m⁻² as their unit in the GRIB files.

Variable types (the time-range indicator is the final number in the identifier):

Instantaneous (time-range indicator equal to 0) parameters produced by the atmospheric model available at or near the surface.
Accumulated (time-range indicator equal to 4) parameters produced by the atmospheric model available at or near the surface. All accumulations are initiated at the start of each forecast and are valid at the forecast step indicated in the data.
Parameters that are valid over a specified period of time (time-range indicator equal to 2) produced by the atmospheric model at or near the surface. All such parameters are valid for the previous forecast hour; e.g. the maximum temperature at forecast hour 24 is the maximum temperature between hours 23 and 24. These parameters are reset each hour by the forecast model.

The third timestep of the three-hour forecasts (FC3hr) were taken and resampled to daily resolution. Precipitation and irradiance variables are accumulated over a three-hour period in the third forecast step, so conversions were done during the resampling (see https://confluence.ecmwf.int/pages/viewpage.action?pageId=197702790).

Whelan, E., Hanley, J., and Gleeson, E. (2017). The MÉRA Data Archive, Technical Note, Dublin, Ireland, Met Éireann. [Online]. Available at https://hdl.handle.net/2262/81711 (Accessed 15 November 2022).

Valentia Observatory time series

Sample data for testing grass growth model. This location was used as it is characterised by a continuous growing season, and was useful in determining the right implementation of the growing season and seasonality in the grass growth model. The data is subset from raw data downloaded from Met Éireann's servers.

Site-specific characteristics

Stocking rate derived using the Census of Agriculture

ROI (CSO)

NI (DAERA)

Nitrogen nutritional index derived using JRC-ESDAC data

Maps of Soil Chemical properties at European scale based on LUCAS 2009/2012 topsoil data: https://esdac.jrc.ec.europa.eu/content/chemical-properties-european-scale-based-lucas-topsoil-data

The chemical properties maps for the European Union were produced using Gaussian process regression (GPR) models. Resolution: 500m. Format: TIFF; projection information: ETRS89 / LAEA Europe. Soil nitrogen distribution is dependent on soil organic carbon, vegetation and climate and soil texture.

With 22,000 sampled locations the LUCAS soil database is unique in Europe for the number of available observations, its spatial coverage and its temporal resolution. The interpolated maps of chemical properties offer a better overview of the distribution of soil chemical properties in the EU to the scientific community and to policy makers. The derived maps will establish baselines that will help monitor soil quality and provide guidance to agro-environmental research and policy developments in the European Union.

Soil water-holding capacity derived using JRC-ESDAC data

European Soil Database Derived data: https://esdac.jrc.ec.europa.eu/content/european-soil-database-derived-data

Total available water content from PTF

Grass growth measurements

GrassCheck NI

https://agrisearch.org/grasscheck

Grass growth measurements for Northern Ireland

Manually extracted from information provided in GrassCheck weekly bulletins: https://www.agrisearch.org/bulletins

The grass growth data is aggregated at county level and is measured in kg DM ha⁻¹ day⁻¹. Frequency is weekly.

Huson, K. M., Lively, F. O., Aubry, A., Takahashi, T., Gordon, A., and McDonnell, D. A. (2020). 'GrassCheck: monitoring grass growth and maximizing grass utilisation on UK farms', in Virkajärvi, P. et al. (eds), Meeting the future demands for grassland production, Grassland Science in Europe, Helsinki, Finland, European Grassland Federation, vol. 25, pp. 716–718. Online. (Accessed 13 September 2022).

PastureBase Ireland

https://pasturebase.teagasc.ie

Hanrahan, L., Geoghegan, A., O'Donovan, M., Griffith, V., Ruelle, E., Wallace, M., and Shalloo, L. (2017). 'PastureBase Ireland: A grassland decision support system and national database', Computers and Electronics in Agriculture, vol. 136, pp. 193–201. DOI: 10.1016/j.compag.2017.01.029.

Boundaries

Island of Ireland

NUTS (Nomenclature of territorial units for statistics): https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units/nuts

Natural Earth 10 m boundary: https://www.naturalearthdata.com/downloads/10m-physical-vectors/10m-land/

Electoral divisions

The Census of Agriculture data are aggregated by electoral division or ward.

ROI electoral divisions: https://data-osi.opendata.arcgis.com/datasets/osi::electoral-divisions-osi-national-statutory-boundaries-2019

UK Wards: https://geoportal.statistics.gov.uk/datasets/ons::wards-december-2022-boundaries-uk-bfc

Counties

The grass growth measurements, PastureBase Ireland and Grass Check NI, are aggregated at county level.

Ordnance Survey Ireland (OSi) National Statutory Boundaries - 2019: https://data-osi.opendata.arcgis.com/datasets/osi::counties-osi-national-statutory-boundaries-2019/about
Ordnance Survey Northern Ireland (OSNI) Open Data - Largescale Boundaries - County Boundaries: https://www.opendatani.gov.uk/dataset/osni-open-data-largescale-boundaries-county-boundaries1

Other data (unused in analysis)

Grass10

Data taken from Teagasc Grass10 newsletters: https://www.teagasc.ie/crops/grassland/grass10/

Agro-environmental regions in Holden and Brereton (2004)

Six agroclimatic regions have been derived from the map available in the following paper:

Holden, N. M. and Brereton, A. J. (2004). 'Definition of agroclimatic regions in Ireland using hydro-thermal and crop yield data', Agricultural and Forest Meteorology, vol. 122, no. 3, pp. 175–191. DOI: 10.1016/j.agrformet.2003.09.010.

A screenshot of the map was taken, then georeferenced in QGIS/GDAL using the steps detailed in holden_brereton_2004_regions.sh.

List of references

Available on Zotero: https://www.zotero.org/groups/4706660/climag/collections/N6IJMX95

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