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Indicator Assessment
Observed trend in heating and cooling degree days (1981-2017)
Projected linear trend in heating (HDD) and cooling degree days (CDD) over the period 1981-2100 under two scenarios
Past trends
The annual population-weighted heating degree days (HDDs) decreased by 6 % between the periods 1950–1980 and 1981–2017. The decrease during the period 1981–2017 was on average 6.5 HDDs per year, although with substantial inter-annual variation (Figure 1, left); this linear trend corresponds to an annual decrease of 0.3 % (relative to the 1950–1980 average). The annual population-weighted cooling degree days (CDDs) increased by 33 % between the periods 1950–1980 and 1981–2017. The increase during the period 1981–2017 was on average 0.9 CDDs per year, although with substantial inter-annual variation (Figure 1, right); this linear trend corresponds to an annual increase of 1.4 % (relative to the 1950–1980 average) [i].
Figure 1 further illustrates that HDDs and CDDs did not show a clear trend in the period 1950–1980. (The declining trend for CDDs shown in Figure 1 (right panel) is highly sensitive to the choice of start year). Since the beginning of the 1980s, however, Europe has started experiencing a markedly declining overall trend in HDDs, and a markedly increasing trend in CDDs, which points to a general increase in cooling needs and a general decrease in heating needs.
The relative increase in CDDs is much larger than the relative decrease in HDDs, because of lower absolute values. In principle, HDD and CDD values can be added together to give a new indicator, energy degree days, However, heating and cooling systems are generally based on different technologies, with different primary energy needs and economic costs [ii].
Figure 2 (left panel) shows that the decrease in HDDs has been particularly strong in Finland and Sweden in northern Europe, i.e. where the energy demand for heating is highest, but also in Greece, Italy and Turkey in southern Europe. Note that the quality and representativeness of the meteorological data from sparse areas - in particular over mountainous regions - in some southern European countries are lower than the overall quality over Europe. Figure 2 (right panel) shows that the increase in CDDs has been particularly strong in southern Europe (roughly latitudes below 45 °N), i.e. where the energy demand for cooling is highest.
Projections
The trend of a decreasing number of HDDs and an increasing number of CDDs in Europe will continue in the future. Figure 3 shows projections for HDDs and CDDs until 2100 for the two global forcing (emissions) scenarios RCP4.5 and RCP8.5. Note that neither of these scenarios is compatible with the goals of the Paris Agreement. To facilitate comparison between observed and projected changes, Figure 3 applies the same units as Figure 2, i.e. projected changes are expressed as linear trends during the period 1981–2100. The pattern of projected changes in Figure 3 is generally similar to that of the observed trends in Figure 2. One notable exception refers to HDD trends in Italy. The rapid decrease in HDDs over Italy shown in Figure 2 is not matched in Figure 3. The pace of change under the RCP8.5 scenario (lower panels in Figure 3) is similar to that observed since 1981; under the RCP4.5 scenario, the observed pace of change would decrease (upper panels in Figure 3) [iii].
Several model-based studies agree that the projected changes in temperature reduce the total energy demand in cold countries, such as Norway, whereas total energy demand increases in warm countries, such as Italy or Spain. The studies also agree that increases or decreases in total energy or electricity demand at the national level as a result of climate change alone will be below 5 % by the middle of the century [iv]. Although these changes are rather minor, adaptation needs can arise from their combination with socio-economic changes (e.g. increased availability of cooling systems) and from changes in peak energy demand.
Peak electricity demand for cooling, which is almost exclusively provided by electricity, will increase throughout Europe. The largest absolute increases in electricity peak demand for cooling have been projected for Italy, Spain and France [v]. The main adaptation challenge relates to the stability of electricity networks during heat waves when an increased peak electricity demand for cooling may coincide with limited cooling water supply for thermal and hydropower generation.
[i] J. Spinoni, J. Vogt, and P. Barbosa, ‘European Degree-Day Climatologies and Trends for the Period 1951–2011’,International Journal of Climatology 35, no. 1 (2015): 25–36, https://doi.org/10.1002/joc.3959.
[ii] Maximilian Auffhammer and Erin T. Mansur, ‘Measuring Climatic Impacts on Energy Consumption: A Review of the Empirical Literature’,Energy Economics 46 (1 November 2014): 522–30, https://doi.org/10.1016/j.eneco.2014.04.017; Giuliano Buceti, ‘Climate Change and Vulnerabilities of the European Energy Balance’,Journal of Sustainable Development of Energy, Water and Environment Systems 3, no. 1 (30 March 2015): 106–17, https://doi.org/10.13044/j.sdewes.2015.03.0008.
[iii] Jonathan Spinoni et al., ‘Changes of Heating and Cooling Degree-Days in Europe from 1981 to 2100’,International Journal of Climatology 38 (April 2018): e191–208, https://doi.org/10.1002/joc.5362.
[iv] Silvana Mima and Patrick Criqui, ‘The Costs of Climate Change for the European Energy System, an Assessment with the POLES Model’,Environmental Modeling & Assessment 20, no. 4 (2015): 303–19, https://doi.org/10.1007/s10666-015-9449-3; Andrea Damm et al., ‘Impacts of +2 °C Global Warming on Electricity Demand in Europe’,Climate Services, IMPACT2C - Quantifying projected impacts under 2°C warming, 7 (1 August 2017): 12–30, https://doi.org/10.1016/j.cliser.2016.07.001; Leonie Wenz, Anders Levermann, and Maximilian Auffhammer, ‘North–South Polarization of European Electricity Consumption under Future Warming’,Proceedings of the National Academy of Sciences, 23 August 2017, 201704339, https://doi.org/10.1073/pnas.1704339114.
[v] Damm et al., ‘Impacts of +2 °C Global Warming on Electricity Demand in Europe’.
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'. This shall be achieved by bridging the knowledge gap and further developing the European climate adaptation platform (Climate-ADAPT) as the ‘first-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 sub-national adaptation strategies and plans; and (4) adaptation case studies. It was relaunched in early 2019 with a new design and updated content. 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 November 2018, the Commission published its evaluation of the 2013 EU Adaptation Strategy. The evaluation package includes a Report from the Commission, a Commission Staff Working Document, the Adaptation preparedness scoreboard country fiches, and the reports from the JRC PESETA III project. This evaluation includes recommendations for the further development and implementation of adaptation policies at all levels.
In November 2013, the European Parliament and the European Council adopted the 7th EU Environment Action Programme (7th EAP) to 2020, ‘Living well, within the limits of our planet’. The 7th 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 7th EAP refer to climate change adaptation.
In February 2016, the Commission published an EU Strategy on Heating and Cooling, which aims to decarbonise the heating and cooling of buildings through different technologies and measures, in line with wider EU climate and energy policies.
No targets have been specified.
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. Previous versions of this indicator published before 2016 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 (Tn) and maximum (Tx) temperatures and not solely on the mean temperature (Tm), 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 Tx than on Tm, while Tn 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 this version of the indicator and versions published before 2016 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.
Not applicable
Not applicable
The climatological input data sets for computing past trends for HDDs and CDDs in Europe combine temperature data with daily resolution from three different station data sets — the JRC’s MARS meteorological database, the NOAA National Climatic Data Center (NCDC)’s Global Historical Climatology Network data set and the European Climate and Assessment Dataset of the Royal Meteorological Institute of the Netherlands — and from one gridded data set (E-OBS versions 17). The resulting trends are considered robust in most regions, but there are open questions for some regions with poor station coverage.
HDD and CDD projections are derived from the ensemble mean of 11 high‐resolution bias‐adjusted EURO‐CORDEX simulations. Climate simulations are associated with uncertainties related to the underlying emissions or forcing scenario, natural variability and model uncertainty. However, temperature is generally simulated better than other climate variables, and the use of multi-model averages and of bias adjustment further reduces errors in individual simulations.
Different definitions exist for computing HDDs and CDDs, which can lead to different magnitudes of calculated trends.
No uncertainty has been specified
For references, please go to https://www.eea.europa.eu/data-and-maps/indicators/heating-degree-days-2/assessment or scan the QR code.
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