Heating and cooling degree days

Assessment versions

Published (reviewed and quality assured)

• No published assessments

Rationale

Justification for indicator selection

Space heating and cooling is responsible for a large fraction of European energy use. Heating degree days (HDDs) and cooling degree days (CDDs) are proxies for the energy demand needed to heat or cool, respectively, a home or a business. Both variables are derived from measurements of outside air temperature. The heating and cooling requirements for a given structure at a specific location are considered, to some degree, proportional to the number of HDDs and CDDs at that location. However, they also depend on a large number of other factors, in particular building design, energy prices, income levels and behavioural aspects.

Space heating is responsible for a large component of European energy use, so a decrease in the use of space heating has the potential to lead to a significant decrease in overall energy use. An increase in cooling demand would off-set in part or completely the gains from a reduced energy demand for space heating and the effects resulting from a reduction in heating demand. While heating is delivered to end users in different ways (individual boilers fuelled by oil, gas, and coal, and electricity and district heating), cooling is delivered currently almost exclusively through electricity. As a result, a given increase in cooling demand is generally associated with higher costs, a higher increase in primary energy demand and larger impacts on the peak capacity of supply networks than the same decrease in heating demand.

Scientific references

• IPCC, 2014a: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1132 pp.
• IPCC, 2014c: Europe. Kovats, R.S., R. Valentini, L.M. Bouwer, E. Georgopoulou, D. Jacob, E. Martin, M. Rounsevell, and J.-F. Soussana, 2014: Europe. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Barros, V.R., C.B. Field, D.J. Dokken, M.D. Mastrandrea, K.J. Mach, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1267-1326.

Indicator definition

• Time series of population-weighted heating and cooling degree days averaged over Europe

• Trend in heating and cooling degree days

Units

• Heating and cooling degree days (° C*d/yr)

Policy context and targets

Context description

In April 2013, the European Commission (EC) presented the EU Adaptation Strategy Package. This package consists of the EU Strategy on adaptation to climate change (COM/2013/216 final) and a number of supporting documents. The overall aim of the EU Adaptation Strategy is to contribute to a more climate-resilient Europe.

One of the objectives of the EU Adaptation Strategy is Better informed decision-making, which will be achieved by bridging the knowledge gap and further developing the European climate adaptation platform (Climate-ADAPT) as the ‘one-stop shop’ for adaptation information in Europe. Climate-ADAPT has been developed jointly by the EC and the EEA to share knowledge on (1) observed and projected climate change and its impacts on environmental and social systems and on human health, (2) relevant research, (3) EU, transnational, national and subnational adaptation strategies and plans, and (4) adaptation case studies.

Further objectives include Promoting adaptation in key vulnerable sectors through climate-proofing EU sector policies and Promoting action by Member States. Most EU Member States have already adopted national adaptation strategies and many have also prepared action plans on climate change adaptation. The EC also supports adaptation in cities through the Covenant of Mayors for Climate and Energy initiative.

In September 2016, the EC presented an indicative roadmap for the evaluation of the EU Adaptation Strategy by 2018.

In November 2013, the European Parliament and the European Council adopted the 7^th EU Environment Action Programme (7^th EAP) to 2020, ‘Living well, within the limits of our planet’. The 7^th EAP is intended to help guide EU action on environment and climate change up to and beyond 2020. It highlights that ‘Action to mitigate and adapt to climate change will increase the resilience of the Union’s economy and society, while stimulating innovation and protecting the Union’s natural resources.’ Consequently, several priority objectives of the 7^th EAP refer to climate change adaptation.

Targets

No targets have been specified.

Related policy documents

• 7th Environment Action Programme
  DECISION No 1386/2013/EU OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 20 November 2013 on a General Union Environment Action Programme to 2020 ‘Living well, within the limits of our planet’. In November 2013, the European Parliament and the European Council adopted the 7 th EU Environment Action Programme to 2020 ‘Living well, within the limits of our planet’. This programme is intended to help guide EU action on the environment and climate change up to and beyond 2020 based on the following vision: ‘In 2050, we live well, within the planet’s ecological limits. Our prosperity and healthy environment stem from an innovative, circular economy where nothing is wasted and where natural resources are managed sustainably, and biodiversity is protected, valued and restored in ways that enhance our society’s resilience. Our low-carbon growth has long been decoupled from resource use, setting the pace for a safe and sustainable global society.’
• Climate-ADAPT: Adaptation in EU policy sectors
  Overview of EU sector policies in which mainstreaming of adaptation to climate change is ongoing or explored
• Climate-ADAPT: Country profiles
  Overview of activities of EEA member countries in preparing, developing and implementing adaptation strategies
• DG CLIMA: Adaptation to climate change
  Adaptation means anticipating the adverse effects of climate change and taking appropriate action to prevent or minimise the damage they can cause, or taking advantage of opportunities that may arise. It has been shown that well planned, early adaptation action saves money and lives in the future. This web portal provides information on all adaptation activities of the European Commission.
• EU Adaptation Strategy Package
  In April 2013, the European Commission adopted an EU strategy on adaptation to climate change, which has been welcomed by the EU Member States. The strategy aims to make Europe more climate-resilient. By taking a coherent approach and providing for improved coordination, it enhances the preparedness and capacity of all governance levels to respond to the impacts of climate change.

Methodology

Methodology for indicator calculation

HDDs and CDDs are defined relative to a base temperature — the outside temperature — below which a building is assumed to need heating or cooling. They can be computed in different ways, depending, among other things, on the specific target application and the availability of sub-daily temperature data. The previous version of this indicator applied the methodology of Eurostat, which uses daily mean temperature only and has a jump discontinuity when daily mean temperature falls below the base temperature. This indicator uses an approach developed by the UK Met Office, which uses daily mean, minimum and maximum temperatures and does not exhibit a discontinuity. Note that this approach, being based on both minimum (T_n) and maximum (T_x) temperatures and not solely on the mean temperature (T_m), increases the accuracy of HDDs and CDDs for the purpose of gauging the impacts of climate change on energy demand, because the cooling of the environment depends more on T_x than on T_m, while T_n is more relevant for heating. The baseline temperatures for HDDs and CDDs are 15.5 °C and 22 °C, respectively. As a result of the methodological changes, the magnitudes of the trends between the previous version and this version of the indicator cannot be directly compared.

The aggregation of regional changes in HDDs and CDDs to larger areas can be done using area weighting or population weighting (with a fixed population). Population weighting is preferable for estimating trends in energy demand over large regions with an uneven population distribution, such as Europe.

Methodology for gap filling

Not applicable

Methodology references

• Spinoni et al., 2015: European degree-day climatologies and trends for the period 1951–2011. Spinoni, J., Vogt, J. and Barbosa, P., 2015, 'European degree-day climatologies and trends for the period 1951–2011', International Journal of Climatology 35(1), 25–36 (doi: 10.1002/joc.3959).

Data specifications

EEA data references

• No datasets have been specified here.

External data references

• European degree-day climatologies and trends for the period 1951–2011 (Dataset URL is not available)
• E-OBS gridded dataset
• GEOSTAT 2011 grid dataset

Data sources in latest figures

Uncertainties

Methodology uncertainty

Not applicable

Data sets uncertainty

The climatological input datasets for computing HDDs and CDDs for Europe combine temperature data with daily resolution from three different station datasets — the JRC’s MARS meteorological database, the NOAA National Climatic Data Center (NCDC)’s Global Historical Climatology Network dataset and the European Climate and Assessment Dataset of the Royal Meteorological Institute of the Netherlands and from one gridded dataset (E-OBS versions 10 and 11). These datasets are considered rather robust. However, different definitions exist for computing HDDs and CDDs, which can lead to different magnitudes of calculated trends.

Rationale uncertainty

No uncertainty has been specified