Geoportal

Details

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General

Meta data ID	{5005B04A-A920-4F67-82FE-C9D6BBA9D72B}
Last modified	2024-04-10T13:11:31

Dataset creators

Contact person

First name	Stefan
Last name	Fronzek
Email	stefan.fronzek@syke.fi
Organisation	Finnish Environment Institute

Dataset creators

First name	Stefan
Last name	Fronzek
Organisation	Finnish Environment Institute

Project

Project name	PRUDENCE
Project funder	EC
Project identifier	EVK2-CT2001-00132

Description

Basic information

Dataset title	Energy demand indicator dataset in Climate Guide
Theme	Agriculture and Farming
Description	Climate change causes effects on the energy demand for cooling and heating of buildings with warmer temperature increasing the demand for cooling in the summer and decreasing the demand for heating. Degree-day indicators, calculated as the accumulated sum of temperature above (for cooling) or below (for heating) a threshold temperature, serve as a proxy for the energy demand. This dataset consists of cooling and heating energy demand indicators calculated on a regular 10 km x 10 km grid over Finland under current and future climate.
Language (dataset)	English
Keyword	climate change
Keyword	cooling
Keyword	energy
Keyword	heating
Keyword	indicator

Data processing steps

sampling

Description

30-year average are shown on a regular 10 km x 10 km over Finland for changes between the baseline period 1961-1990 and three future periods, 2010–2039, 2040–2069 and 2070–2099, under three future scenarios that were selected from the CMIP3 ensemble: low emissions (SRES B1) simulated with the HadCM3 Global Climate Model (GCM), medium emissions (SRES B2) expressed as the mean of six GCMs (see Fronzek et al. 2007), and high emissions (SRES A1FI)/ECHAM4 GCM.

Data processing steps

processing

Description

A relative measure of demand for air conditioning is the sum of temperatures exceeding a threshold temperature above which cooling would be required to maintain a comfortable room temperature (cooling degree-days). In Finland, the energy consumption of a building for cooling is almost proportional to the indoor and outdoor temperature difference. Here average CDD are calculated by accumulating mean daily temperatures throughout the year that lie above a threshold of 18°C (Fronzek et al. 2007). The demand for space heating is estimated as the sum of temperatures lower than a threshold temperature below which heating would be required to maintain a comfortable room temperature (heating degree-days or HDD). In Finland, the energy consumption of a building for heating is almost proportional to the indoor and outdoor temperature difference. Here average HDD are calculated by accumulating mean daily temperatures throughout the year that lie below a threshold of 18°C (30-year period). The analysis was carried out for 30-year averages, results are presented as the change between a future period and the baseline period 1961-1990. The following indicators are included: Cooling demand (unit: °Cd or degree-days above 18°C) Heating demand (°Cd or degree-days below 18°C)

Material time period

Start date	1961-01-01
End date	2099-12-31

Area

West Bounding Longitude	19.33
East Bounding Longitude	31.53
South Bounding Latitude	59.79
North Bounding Latitude	70.07

Distribution

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Action (default: None)	none
Reserved DOI	10.48488/74dg-5v42

Contact person

First name	Stefan
Last name	Fronzek
Email	stefan.fronzek@syke.fi
Organisation	Finnish Environment Institute

Resources

Resource content description	Maps of the climate change indicators can be viewed in climateguide.fi under the section ‘Impact scenarios of climate change’.
Web-address (URL)	https://www.climateguide.fi/articles/impact-scenarios-of-climate-change

Resources

Resource content description

The data can be accessed via a Web Feature Service (WFS) supporting versions 1.0.0 and 1.1.0. WFS services can be opened in various GIS applications, for example ArcGIS for Desktop and open source desktop application QGIS. Typically, the GIS applications loads data from a WFS service in a GML (Geography Markup Language) format. Additionally, the data can be loaded as zip compressed ESRI Shape files, a CSV file or a JSON file. The service includes 2 feature types representing energy demand simulations: energy_coolingdegreedays – change in cooling degree-days above 18 °C (%), energy_heatingdegreedays – change in heating degree-days below 18 °C (%). The attributes of each feature type are labelled as [climateModel]_[emissionScenario]_[timePeriod]_0_[valueType]. There are three climate models, hadcm3, mean (6-GCM ensemble mean) and eh4opyc; and three emission scenarios b1, b2 and a1fi. The timePeriod includes the start year and the end year of the period. There is one option for valueType, “rc” for relative change. For example, the attribute labeled as hadcm3_b1_20702099_0_rc describes the climate model HadCM3, the emission scenario SRES B1, the time period from 2070 to 2099 and relative change. In addition, there is an attribute labelled control_na_19611990_0_av with the absolute values (valueType “av”) for the baseline period 1961-1990 (in degree-days).

Web-address (URL)

https://paikkatiedot.ymparisto.fi/geoserver/ilmo-climateguide/wms?request=getcapabilities

Reference publications

Reference

Fronzek, S. and T.R. Carter (2007). Assessing uncertainties in climate change impacts on resource potential for Europe based on projections from RCMs and GCMs. Climatic Change, 81 (Suppl. 1), 357–371, https://doi.org/10.1007/s10584-006-9214-3

The license for open SYKE's open datasets is Creative Commons Attribution 4.0 International.

The data described here can be freely used to all purposes, provided that the source of the data is mentioned.

The citation for the dataset as given above.

Further information on the license:
https://creativecommons.org/licenses/by/4.0/legalcode (English)
https://creativecommons.org/licenses/by/4.0/legalcode.fi (Finnish)

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