UK CLIMATE
PROJECTIONS
Using UKCP09 to assess
adaptation measures
Author/Organisation
Rachel Capon, Ove Arup & Partners
Contents
1 Introduction
2
2
1.1
Disclaimer
2 Case Study: Living Room of a 1930s Semi-detached House
2
2.1
Base Case
2
2.2
Climate Change Adaptation Measures
2
2.3
Air Conditioning
3
3 Method
3
4 Conclusions
3
5 References
4
6 Figures
5
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Using UKCIP08 to assess adaptation measures
1 Introduction
The purpose of this worked example is to consider how the UKCP09 data may
be used for building simulation of a future climate. It develops the ‘morphing’
technique developed in CIBSE TM36 [1] to produce future weather year data from
the UKCP09 climate change projections. Unlike the previous UKCIP datasets, the
UKCP09 projections are probabilistic in nature and cover a range of uncertainties
in climate change. This worked example illustrates how this range of uncertainty
may be explored in relation to overheating risk in a typical 1930s house.
1.1 Disclaimer
The data used are dummy data. Furthermore the only UKCP09 projection used
is the temperature rise. Other relevant climate projection data, such as changes
in cloud cover, radiation and diurnal temperature range, will only be available
after the launch of UKCP09. Therefore, the results of the case study should not
be considered as a realistic output to influence design, merely as an example of
how the UKCP09 data could be used for building simulation.
2 Case Study: Living Room of a 1930s Semi-detached House
2.1 Base Case
The case study considered for this worked example is a house living room. The
house is typical two-storey semi-detached property of a 1930s construction, with
brick-cavity-brick external walls and internal masonry walls. The ground floor
is suspended and has wooden floorboards. The floor is carpeted. The original
windows are still intact with single glazing and timber frames.
As a worst-case scenario, the front of the house – and hence the living room –
has a south-west orientation. It is assumed that the house is occupied by a family
of two adults and three young children, thus the living room is at least partly
occupied throughout the day, from 9 a.m. until 10 p.m.
2.2 Climate Change Adaptation Measures
A suite of climate change adaptation measures has also been modelled. These
include:
• an awning for external solar control;
• new double-glazed sash windows to improve thermal insulation and allow
increased natural ventilation, especially night-time cooling;
• façade upgrade with cavity-wall insulation and more reflective wall coating;
• replace carpet with wooden floor;
• ceiling or desk fans to increase air movement (considered equivalent to a 2°C
comfort temperature decrease).
These measures are designed to be retrofitted to the house to minimize future
summer overheating risk.
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Using UKCIP08 to assess adaptation measures
2.3 Air Conditioning
The total power consumption* required for cooling by air-conditioning was
calculated by modelling with an oversized room unit. The air-conditioning was
set to cool whenever the operative temperature in the living room exceeded
the CIBSE comfort temperature limit (25 °C) during occupied hours [2]. The
actual power consumption depends on the efficiency of the air conditioning
equipment. In practice many occupants may choose a lower set-point for their
air-conditioning systems, which would result in increased power consumption
compared to the figures shown.
3 Method
The UKCP09 data was used to ‘morph’ the CIBSE Design Summer Year for
London. This technique has been previously applied using UKCIP02 data [3], and
the morphed weather years produced used to simulate future thermal response
of various types of buildings ([1], [4]).
However a novel feature of the UKCP09 data is that it gives an estimate of the
range of climate projections for a given location. These can be plotted as a
cumulative distribution function, a test example of which is shown in Figure 1.
The 10% cumulative probability corresponds to a low value for the projected
summer temperature rise. It is ‘very likely’ that the actual summer temperature
rise will exceed this value. The summer temperature rise is equally likely to be
above or below the 50% cumulative probability value, or ‘central estimate’.
The summer temperature rise is ‘very unlikely’ to exceed the 90% cumulative
probability value. (The converse is also true: the summer temperature rise is ‘very
unlikely’ to be less than the 10% projection and ‘very likely’ to be below the 90%
projection.)
The London DSY data for July was morphed using the summer temperature
change projections at cumulative probabilities of 10, 50 and 90%. Morphed July
DSY data was produced for each of these cumulative probabilities for both the
2050s and 2080s and for Medium and High emissions scenarios. A single UKCP09
grid-point over London was selected for which to extract climate projection data.
Not surprisingly, this is the grid-point which contains the highest urban land
fraction in UKCP09.
Once the set of morphed weather data had been produced, they were used to
model the house living room for each of the cases described above: the base case
of the completely unadapted house, the house with climate change adaptation
measures retrofitted and the house cooled using air-conditioning. In total, thirtynine runs were performed, including the present-day DSY.
4 Conclusions
Various measures can be used to quantify overheating, such as cooling degree
hours (CDH) above the CIBSE comfort temperature (25°C) or peak occupied
temperature (Tpeak). It is assumed that cooling degree hours and the peak occupied
temperature increase with the external temperature. Hence, the ‘very likely’
range of CDH (or Tpeak) in a future climate lies between the values computed using
the 10 and 90% summer temperature rise projections. The ‘central estimate’ of
CDH (or Tpeak) corresponds to the value computed using the 50% projection.
* The power consumption was calculated from the cooling load output by the model
assuming a Coefficient of Performance of 2.5 for the system.
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Using UKCIP08 to assess adaptation measures
Both CDH and Tpeak have been calculated and plotted for the various cases
and are shown in Figures 2 and 3 for the High emissions scenario. The results
indicate that, even under the High emissions scenario, the suite of climate
change adaptations provides good protection against future overheating when
compared to the present-day base case, even up to the 2080s. In the climate
change adapted house, the very likely range of peak occupied temperature is
28.0-32.8°C in the 2080s. This is considerably lower than both the present day
Tpeak in the base case, 35.7°C and the projected very likely range of Tpeak for the
base case in the 2080s, 37.8–43.0°C. The very likely range of cooling degree hours
is similarly reduced, compared to the base case, with the suite of climate change
adaptations in place.
Under the Medium emissions scenario, the projected range of temperature rise is
lower, but still significant. Therefore there remains a significant overheating risk
in the base case, which could warrant adaptation.
Air-conditioning can also be used to protect against overheating, but it has
major drawbacks. The amount of power consumed for cooling will continue to
rise, as temperatures rise (Figure 4). This could have a considerable financial cost,
particularly in light of rising fuel prices. Warm air will be exhausted by the system
outside the dwelling, raising the external air temperature and discomfort, and
eventually impacting on the indoor air temperature. The most compelling reason
for avoiding air-conditioning is environmental. The use of air-conditioning will
undoubtedly contribute to rising greenhouse gas emissions, thus exacerbating
rather than mitigating climate change.
Of course, retrofitting climate change adaptations will have cost implications,
especially in terms of initial capital cost. However this should be compared
with the ongoing financial cost of running and maintaining an air-conditioning
system, together with its environmental cost in terms of carbon emissions.
5 References
1. Climate Change and the Indoor Environment: Impacts and Adaptation, CIBSE
TM36, 2005
2. Environmental Design, CIBSE Guide A, 2006
3. Climate Change Scenarios for the United Kingdom: The UKCIP02
Scientific Report, 2002 Download from: http://www.ukcip.org.uk/index.
php?option=com_content&task=view&id=353&Itemid=408
4. Your Home in a Changing Climate: Retrofitting Existing Homes for Climate
Change Impact, GLA, 2008. Download from: http://www.london.gov.uk/trccg/
publications.jsp
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Using UKCIP08 to assess adaptation measures
6 Figures
Figure 1: Sample cumulative distribution function for change in Temperature from
UKCP09 data. This example is for the Medium emissions scenario and the 2080s timeslice.
Figure 2: Cooling Degree Hours for July DSY for Base Case and Climate Change Adapted
house living room, from the present day to the 2080s, under the High emissions
scenario.
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Using UKCIP08 to assess adaptation measures
Figure 3: Very likely range of Peak Occupied Temperature for July DSY for Base Case and
Climate Change Adapted house living room, from the present day to the 2080s, under
the High emissions scenario.
Figure 4: Cooling Degree Hours for Base Case and Power Consumption for AirConditioned house living room, for July DSY, from the present day to the 2080s, under
the High emissions scenario.
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