Future Weather Data Research Articles

우주환경 지상관측기 자료통합시스템 개발

Korea Astronomy and Space Science Institute, Daejeon 305-348, KoreaE-mail: jhbaek@kasi.re.kr(Received September 06, 2013; Accepted September 27, 2013)ABSTRACT We have developed a data integration system for ground-based space weather facilities in Korea Astronomy and Space Science Institute (KASI). The data integration system is necessary to analyze and use ground-based space weather data efficiently, and consists of a server system and data monitoring systems. The server system consists of servers such as data acquisition server or web server, and storage. The data monitoring systems include data collecting and processing applications and data display monitors. With the data integration system we operate the Space Weather Monitoring Lab (SWML) where real-time space weather data are displayed and our ground-based observing facilities are monitored. We expect that this data integration system will be used for the highly efficient processing and analysis of the current and future space weather data at KASI.Key words: space weather; data integration system; ground-based observational system: solar telescope, magnetometer, VHF radar

SWAT 모형을 이용한 미래 기후변화가 설마천 혼효림 유역의 증발산과 토양수분에 미치는 영향 평가

본 연구는 SWAT 모형을 이용하여 설마천 혼효림 유역(8.54 <TEX>$km^2$</TEX>)을 대상으로 RCP (AR5) 기후변화 시나리오에 따른 수문순환 영향을 평가하였다. 모형의 불확실성을 효과적으로 줄이기 위해 설마천 유역의 2007년부터 실측된 유량, 증발산량 및 토양수분을 이용하여 모형의 보정(2007~2008) 및 검증(2009~2010)을 수행하였다. 모형의 보정 및 검증결과 유출량의 <TEX>$R^2$</TEX>가 0.74~0.91로 분석되었고, 증발산량은 0.56~0.71, 토양수분은 0.45~0.71로 분석되어 토양수분으로부터 증발산이 발생하고 이로 인해 유출까지 영향을 미치는 물수지 현상을 잘 재현하고 있음을 알 수 있었다. 미래 기후자료로 AR5 RCP 4.5, 8.5 시나리오에 대한 모의결과 값을 이용하였고, 사용된 모델은 한반도 전망자료를 지역기후모델을 이용하여 역학적 상세화하여 기상청에서 제공하는 HadGEM3-RA 모형이며 오차 보정하여 사용하였다. 기후변화 시나리오 분석 결과 두가지 시나리오 모두 미래 기온은 <TEX>$0.9{\sim}4.2^{\circ}C$</TEX> 상승하고, 강수량은 7.9~20.4% 증가하였다. 또한 미래 유출량은 0.6~15.7% 증가한 반면에 유출률은 3.8~5.4% 감소하였고, 증발산비는 4.1~6.8% 증가, 토양수분은 4.3~5.5% 감소하였다. This study is to evaluate the future climate change impact on hydrological components in the Seolmacheon (<TEX>$8.54km^2$</TEX>) mixed forest catchment located in the northwest of South Korea using SWAT (Soil and Water Assessment Tool) model. To reduce the uncertainty, the model was spatially calibrated (2007~2008) and validated (2009~2010) using daily observed streamflow, evapotranspiration, and soil moisture data. Hydrological predicted values matched well with the observed values by showing coefficient of determination (<TEX>$R^2$</TEX>) from 0.74 to 0.91 for streamflow, from 0.56 to 0.71 for evapotranspiration, and from 0.45 to 0.71 for soil moisture. The HadGEM3-RA future weather data of Representative Concentration pathway (RCP) 4.5 and 8.5 scenarios of the IPCC (Intergovernmental Panel on Climate Change) AR5 (Assessment Report 5) were adopted for future assessment after bias correction of ground measured data. The future changes in annual temperature and precipitation showed an upward tendency from <TEX>$0.9^{\circ}C$</TEX> to <TEX>$4.2^{\circ}C$</TEX> and from 7.9% to 20.4% respectively. The future streamflow showed an increase from 0.6% to 15.7%, but runoff ratio showed a decrease from 3.8% to 5.4%. The future predicted evapotranspiration about precipitation increased from 4.1% to 6.8%, and the future soil moisture decreased from 4.3% to 5.5%.

The study on modelled and measured weather data for building energy simulation programs for Malaysia

This paper will study the usability of future weather data generated from climate model for Malaysia. Detailed future weather data is required for the building energy assessment as input parameters. The future weather data required is normally achieved from climate prediction models. The purpose of this study is to examine the gaps between weather data generated by climate model and the data measured by weather station in Bayan Lepas, Penang. Furthermore, this studies also to establish the modelled weather data for the use for future building energy simulation program. In order to achieve this purpose, simulated weather data sets HadCM3 were supplied by the Hadley Centre in the UK. The measured weather data was supplied by Malaysian Meteorological Department for Bayan Lepas, Penang. The period of analysed time was 18 years from 1990 to 2007 where the available data overlaps between HadCM3 and measured data. Several major weather variables were used in these studies such as Dry-bulb temperature, Solar radiation and Wind speed. The outcome from this studies shows a good match between HadCM3 data and measured data indicates that HadCM3 model is suitable for the purpose of future building energy simulation for Malaysia.

기후변화 시나리오에 따른 건물부분의 영향

According to the Fourth Assessment Report of Intergovernmental Panel on Climate Change(IPCC) Working Group III, climate change is already in progress around the world, and it is necessary to execute mitigation in order to minimize adverse impacts. This paper suggests future climate change needs, employing IPCC Special Report on Emissions Scenarios(SRES) to predict temperature rises over the next 100 years. This information can be used to develop sustainable architecture applications for energy efficient buildings and renewable energy. Such climate changes could also affected the present supplies of renewable energy sources. This paper discusses one recent Fourth Assessment Report of IPCC (Mitigation of Climate Change) and the Hadley Centre climate simulation of relevant data series for South Korea. Result of this research may improve consistency and reliability of simulation weather data or climate change in order to take advantage of SRES and PRECIS QUMP. It is expected that these calculated test reference years will be useful to the designers of solar energy systems, as well as those who need daily solar radiation data for South Korea. Also, those results may contribute zero carbon and design of sustainable architecture establishing future typical weather data that should be gone ahead to energy efficient building design using renewable energy systems.

Impact of climate change on harvest security and biomass yield of two timothy ley harvesting systems in Norway

SUMMARYPredicted future climate changes in northern Europe include increased air temperature and altered precipitation patterns. There is a lack of knowledge about potential climate change effects on the biomass yield and security of agricultural crops. The present study determined the potential impact of future climate change on the yield and harvest security of timothy (Phleum pratense L.). Harvest security was assessed using data on accumulated precipitation and the length of dry spell period within the 7 days after cutting. Timothy production as a function of weather, soil and management practices was simulated using the LINGRA model for the periods 1961–90, 2046–65 and 2080–99, and the locations Apelsvoll, Ås, Sola, Tromsø and Værnes in Norway and harvest systems with 600 and 800 °C days between cuts. One hundred years of daily weather data were generated with the LARS-WG tool, using future daily weather data sets based on 12 Global Climate Models. Total seasonal biomass yield varied between 690 g dry matter (DM)/m2 for the 800 °C days harvesting regime in the period 1961–90 at Tromsø and 1548 g DM/m2 for the same harvesting regime in the period 2046–65 at Sola. In general, the biomass was higher in the two future periods than in 1961–90 across locations and harvesting regimes, mainly owing to more cuts per season. Accumulated precipitation after cutting varied between 12·2 mm after the first cut for the 600 °C days harvesting regime in the period 1961–90 at Værnes and 42·5 mm after the fourth cut in the 800 °C days harvesting regime in the period 2080–99 at Sola. The longest duration of dry spell 7 days after pre-planned harvest varied between 1·8 days after the fourth cut at Sola in the 600 °C days harvesting regime for the period 2080–99, and 3·9 days after the first cut at Ås in the 800 °C days harvesting regime for the period 2046–65. Potential consequences of these results are discussed.

UNDERSTANDING SPATIAL VARIABILITY OF CROPPING SYSTEM RESPONSE TO CLIMATE CHANGE IN PUNJAB STATE OF INDIA USING REMOTE SENSING DATA AND SIMULATION MODEL

Abstract. The present study investigated the impact of climate change, as projected by the Global Climate Model, HadCM3 for two different storyline (A2, B2), on the total crop production of Punjab state of India and its spatial variability for three future periods (2020, 2050 and 2080). Gridded weather data (1*1 degree) from India Meteorological Department was used as baseline weather. Daily future weather data were generated from baseline and projected change for each weather parameter (maximum and minimum temperature, rain fall). Both baseline and future weather data were then interpolated to 25*25 km grid level. The cropping system model, CropSyst was used for simulating the climate change impact on crop productivity. Cropping system map generated from remote sensing data for Punjab was used for finding the major cropping systems in each of the 25 km grid. Using this information cropping system productivity in each grid was estimated for baseline weather as well as for projected weather. Spatial pattern was generated for the difference in grid yield for each scenario. Results showed yield decline in all cropping systems except for few grids during 2020 in B2 scenario. Aggregated district yield indicated that for A2 scenario, in the near future (2020) Roopnagar (in eastern Punjab) will be the most affected district with around 35 % reduction in cropping system yield where as Hoshiarpur (in north-eastern part) will be most affected during 2050 and 2080. For B2 scenario, Hoshiarpur was found to be the most vulnerable region for all the three periods.

Selection of climatic variables and time scales for future weather preparation in building heating and cooling energy predictions

The effects of future weather preparation using mean changes in different climatic variables at different time scales on residential building heating and cooling energy requirement predictions were investigated using dynamic building simulations. It was found that the predicted reductions in heating energy requirement obtained using any two future weather data sets are likely to be within or around 10% difference from each other if the future weather preparation incorporates at least the changes in the mean air temperatures. For cooling energy requirement predictions in temperate and hot climates, it is recommended to use future weather data prepared with the changes in at least two climatic variables, namely air temperature and humidity. However, for cooling energy requirement predictions in relatively cold climates, future weather preparation should consider the changes in mean monthly or seasonal climatic variables including at least air temperature, solar irradiance and humidity. Alternatively, changes in at least the mean monthly air temperature, daily maximum/minimum temperatures and humidity should be used. The cooling energy requirement predictions obtained using any two future weather data prepared with these recommended climatic variable sets are likely to be within or around 10% difference from each other.

Downscaling climate change scenarios for apple pest and disease modeling in Switzerland

Abstract. As a consequence of current and projected climate change in temperate regions of Europe, agricultural pests and diseases are expected to occur more frequently and possibly to extend to previously non-affected regions. Given their economic and ecological relevance, detailed forecasting tools for various pests and diseases have been developed, which model their phenology, depending on actual weather conditions, and suggest management decisions on that basis. Assessing the future risk of pest-related damages requires future weather data at high temporal and spatial resolution. Here, we use a combined stochastic weather generator and re-sampling procedure for producing site-specific hourly weather series representing present and future (1980–2009 and 2045–2074 time periods) climate conditions in Switzerland. The climate change scenarios originate from the ENSEMBLES multi-model projections and provide probabilistic information on future regional changes in temperature and precipitation. Hourly weather series are produced by first generating daily weather data for these climate scenarios and then using a nearest neighbor re-sampling approach for creating realistic diurnal cycles. These hourly weather series are then used for modeling the impact of climate change on important life phases of the codling moth and on the number of predicted infection days of fire blight. Codling moth (Cydia pomonella) and fire blight (Erwinia amylovora) are two major pest and disease threats to apple, one of the most important commercial and rural crops across Europe. Results for the codling moth indicate a shift in the occurrence and duration of life phases relevant for pest control. In southern Switzerland, a 3rd generation per season occurs only very rarely under today's climate conditions but is projected to become normal in the 2045–2074 time period. While the potential risk for a 3rd generation is also significantly increasing in northern Switzerland (for most stations from roughly 1% on average today to over 60% in the future for the median climate change signal of the multi-model projections), the actual risk will critically depend on the pace of the adaptation of the codling moth with respect to the critical photoperiod. To control this additional generation, an intensification and prolongation of control measures (e.g. insecticides) will be required, implying an increasing risk of pesticide resistances. For fire blight, the projected changes in infection days are less certain due to uncertainties in the leaf wetness approximation and the simulation of the blooming period. Two compensating effects are projected, warmer temperatures favoring infections are balanced by a temperature-induced advancement of the blooming period, leading to no significant change in the number of infection days under future climate conditions for most stations.

Generating design reference years from the UKCP09 projections and their application to future air-conditioning loads

A method is developed to generate future design reference year (DRY) data from the United Kingdom Climate Impact Programme's 2009 (UKCP09) climate change projections for a variety of future time horizons and carbon emission assumptions. The method selects three near-extreme summer months and three near-extreme winter months and weaves them into an existing test reference year (TRY). Risk levels associated with the 85th percentile (broadly equivalent to existing Chartered Institution of Building Services Engineers [CIBSE] design summer years) of the cumulative distribution function of dry-bulb temperature and, for comparison, the 99th percentile are used. A comparison is made with DRYs generated using alternative methods from other research groups. The data are applied to future air-conditioning (cooling) loads analysis for a wide range of non-domestic case study building types. Simulations using a control DRY set applied to these buildings are used to develop a simplified regression-based calculation method for predicting future air-conditioning loads. The simplified model is shown to be applicable to future weather data without loss of accuracy, which makes it possible to carry out large numbers of future cooling loads predictions without the need to perform extensive and complex energy simulations. Practical applications: It is becoming increasingly necessary to design energy and comfort services for buildings with a whole-life perspective. To assist with this, the CIBSE future weather years can be used for building simulations through to the 2080s. In June 2009, the UK’s Department of the Environment, Food and Rural Affairs (Defra) with the support of the United Kingdom Climate Impacts Programme (UKCIP) published updated climate change projections using a probabilistic method. In future, the responsibility will rest with designers to select design data from a large number of probabilistic outcomes. This work develops a technique to select design weather data called a DRY at two alternative risk levels for use in building simulations through to the 2080s. A simplified method is also proposed to allow practitioners to generate large numbers of probabilistic design cooling loads without the need to perform extensive simulations.

Simulation of the future performance of low-energy evaporative cooling systems using UKCP09 climate projections

Recent activity in the development of future weather data for building performance simulation follows recognition of the limitations of traditional methods, which have been based on a stationary (observed) climate. In the UK, such developments have followed on from the availability of regional climate models as delivered in UKCIP02 and recently the probabilistic projections released under UKCP09. One major area of concern is the future performance and adaptability of buildings which employ exclusively passive or low-energy cooling systems.One such method which can be employed in an integral or retrofit situation is direct or indirect evaporative cooling. The effectiveness of evaporative cooling is most strongly influenced by the wet-bulb depression of the ambient air, hence is generally regarded as most suited to hot, dry climates. However, this technology has been shown to be effective in the UK, primarily in mixed-mode buildings or as a retrofit to industrial/commercial applications.Climate projections for the UK generally indicate an increase in the summer wet-bulb depression, suggesting an enhanced potential for the application of evaporative cooling. The paper illustrates this potential by an analysis of the probabilistic scenarios released under UKCP09, together with a detailed building/plant simulation of case study building located in the South-East of England. The results indicate a high probability that evaporative cooling will still be a viable low-energy technique in the 2050s.

Hydrologic modelling to assess the climate change impacts in a Southern Ontario watershed

In Southern Ontario, the Canard River watershed is the largest subwatershed of the Detroit River watershed on the Canadian side. The Soil and Water Assessment Tool (SWAT) model was implemented in the Canard River Watershed to understand the hydrologic regime and assess the impacts of potential future climate change on the hydrology of the watershed. The SWAT model was calibrated and validated against observed streamflow data. The Nash-Suttcliffe efficiencies of the model for monthly streamflow predictions were 0.81 and 0.83, respectively, during the calibration and validation periods. The LARS-WG, weather generator was employed to generate daily future weather data at local scale using the Canadian Regional Climate Model (CRCM) outputs under SRES A2 scenario for the years 2041 to 2070. It was found from the model results that the average annual streamflow could be increased by 12% compared to that over the base period from 1961 to 1990. The results also indicated that streamflow would be increased signifi...

Energy use, indoor temperature and possible adaptation strategies for air-conditioned office buildings in face of global warming

This paper discusses and summarises a recent systematic study on the implication of global warming on air conditioned office buildings in Australia. Four areas are covered, including analysis of historical weather data, generation of future weather data for the impact study of global warming, projection of building performance under various global warming scenarios, and evaluation of various adaptation strategies under 2070 high global warming conditions. Overall, it is found that depending on the assumed future climate scenarios and the location considered, the increase of total building energy use for the sample Australian office building may range from 0.4 to 15.1%. When the increase of annual average outdoor temperature exceeds 2 °C, the risk of overheating will increase significantly. However, the potential overheating problem could be completely eliminated if internal load density is significantly reduced.

The natural ventilation performance of buildings under alternative future weather projections

Different climate change projections, such as UK Climate Impacts Program (UKCIP02) and 2009 UK Climate projections (UKCP09), have generated a large quantity of data that represent a range of possible future weather scenarios. This article investigates the potential consequences of alternative scenarios for the natural ventilation of non-domestic buildings. The article considers future natural ventilation rates in example buildings, the risk of summer overheating and whether natural ventilation will be a viable thermal control option for future summers. The wind is obviously a key driver of natural ventilation, and a necessary component of building simulation weather files. Problems associated with the generation of wind data from UKCP09 for the natural ventilation analyses are discussed and the influence of differences in weather files on predicted performance considered. These differences are important to the understanding of the consequences for the wider use of UKCP09 derived weather data for building energy evaluation. Practical applications: Weather data are widely used in practice to evaluate the potential and performance of natural ventilation in non-domestic buildings. The predicted differences in future weather data will have direct implications for the design of naturally ventilated buildings, and engineers will need to be aware of the possible implications these climatic differences will create.

Generating test reference years from the UKCP09 projections and their application in building energy simulations

In this study, test reference year (TRY) data for three UK cities are generated from the new UKCP09 climate change projections 1 for a variety of future time horizons and carbon emission scenario assumptions. The data are applied to the energy simulation of three commercial buildings and one house for the three city locations (London, Manchester and Edinburgh), three future time horizons in this century and three carbon emission scenarios. Results are compared with those generated using alternative TRYs from two other research groups who used UKCP09 1 as well as with the existing TRY data sets which form the CIBSE Future Weather Years 2 in order to produce robust results. Results of future simulations of peak summer operative temperatures, peak cooling demand, annual cooling energy, peak heating demand and annual heating energy are presented for the four building case studies benchmarked against control weather data for the period 1960–1989. The results show increasing internal operative temperatures (non-air-conditioned) and increasing air-conditioning demands (air-conditioned) throughout this century and though peak heating demands remain similar to control data, annual heating energy consumptions can be expected to fall sharply. Practical applications: Currently, practitioners can use Test Reference Years for use in building energy simulations. In 2009, the CIBSE released Future Weather Years, which go further by allowing practitioners to explore the thermal and comfort behaviour of buildings at future time horizons thus helping to ‘future proof’ a design. In 2009, the United Kingdom Climate Impacts Programme released a new generation of climate change scenario data (the UKCP09 climate change projections) using probabilistic methods. These are the most comprehensive data yet and provides a greater degree of detail than was available to generate the CIBSE Future Weather Years. It is therefore likely that the new data will gradually become the normal basis for investigating future building thermal and comfort response. In this study, a sample of TRY is generated from the UKCP09 data and applied to the simulation of a sample of ‘real’ buildings. The results are compared with both the existing CIBSE Future Weather Years as well as with Test Reference Years generated using UKCP09 by two other research groups. The results provide a robust way forward for simulating building thermal and comfort response using future weather data.

Impact analysis of drought, water excess and salinity on grass production in The Netherlands using historical and future climate data

The coupled SWAP–WOFOST model was used to study the effects of increasing salinity of groundwater, drought and water excess on grass production in The Netherlands. WOFOST simulates crop growth and SWAP simulates transport of water, solutes and heat in the vadose zone. The model was tested using several datasets from field experiments. We applied the models at regional scale where we quantified the impact of various groundwater salinity levels on grass growth and production using historical weather data (1971–2000). The salt concentrations in the subsoil were derived from the National Hydrological Instrument. The results show that salinity effects on grass production are limited. In wet years the excess rainfall will infiltrate the soil and reduce salt water seepage. In a next step we used future weather data for the year 2050, derived from 3 Global Circulation Models. From each model we used data from two CO 2 emission scenarios. As expected higher temperatures increased drought stress, however, the production reduction as a result of salt water in the root zone is limited. Salt stress mainly occurred when irrigation was applied with saline water. The increased CO 2 concentration in combination with the limited drought stress resulted in increasing simulated actual and potential yields. Overall conclusion for grassland in The Netherlands: drought stress is stronger than stress caused by water excess which on its turn is stronger than salinity stress. Future water demand for irrigation may increase by 11–19% and result in water scarcity if water supply is insufficient.

Sensitivity of building cooling loads to future weather predictions

The interaction and the relationship between global warming and thermal performance buildings are dynamic in nature. In order to model and understand this behaviour, different approaches, including that of keeping the weather variable unchanged, the morphing approach and the diurnal modelling method, have been used to project and generate future weather data. Among these approaches, various assumptions of change in solar radiation, air humidity and/or wind characteristics may be adopted. In this article, an example is presented to illustrate the generation of future weather data for the different global warming scenarios in Australia. The sensitivity of building cooling loads to possible changes in assumed values used in future weather data generation is investigated. It is shown that, with a ±10% change in proposed future values of solar radiation, air humidity or wind characteristics, the corresponding change in the cooling load of the modeled sample office building at different Australian capital cities would not exceed 6, 4 and 1.5% respectively. It is also found that with ±10% changes in the proposed weather variables of the 2070-High future scenario and of the current weather scenario, the corresponding change in the cooling loads at different locations may be weaker (up to 2% difference in Hobart for ±10% change in global solar radiation), similar (less than 0.6% difference in Hobart for ±10% change in wind speed) or stronger (up to 1.6% difference in Hobart for ±10% change in relative humidity) in the 2070-High future scenario than it is in the current weather scenario.

The impact of the projected changes in temperature on heating and cooling requirements in buildings in Dhaka, Bangladesh

Dhaka, the capital of Bangladesh, is a fast growing megacity with a population of 12.8 million. Due to its tropical location, dense urban morphology and higher than average density of population, buildings in Dhaka are likely to be adversely affected by the projected changes in climate, in particular by the increases in temperature. Buildings play a vital role in most aspects of our lives and their energy consumption patterns affect climate change mitigation and adaptation strategies. It is important to understand the likely impact of the projected increases in temperature on cooling and heating requirements in buildings in future climates. In this research, global projections on changes in temperature are temporally downscaled using a statistically averaged baseline present-day hourly weather data to generate future weather data in three timeslices: 2020s, 2050s and 2080s. Time series data for the present-day and future climates are analyzed as well as heating and cooling degree-days are calculated. Analysis shows that heating degree-days decrease whereas cooling degree-days continue to increase in future climates. The magnitude of change in monthly cooling degree-days is uneven and is greater in winter months than in summer and monsoon. Increased occurrences of temperatures above comfort threshold throughout the year are likely to have significant consequences for human health and wellbeing. The severity and duration of outdoor temperatures in the form of increased cooling degree-days in future climates will result in a surge in demand for energy for comfort cooling, which will add further stress to the already stressed energy infrastructure in the country. Prompt actions from stakeholders are, therefore, essential to enhance the resilience of Dhaka’s buildings to climate change.

The Development of Future Weather Data Files for Norway

The Development of Future Weather Data Files for Norway

Low energy refurbishment strategies for health buildings

Public health buildings contribute significantly to UK carbon emissions. New build initiatives have received more attention than the considerable opportunities to reduce carbon emissions within the retained health estate. The research reported here has considered the environmental performance of a typical medium rise, medium depth, concrete-framed, late 1960s acute hospital following low energy environmental design interventions. The interventions are made to optimize daylighting and natural ventilation/cooling whilst reducing overheating caused by summer time solar gains. Three options are investigated: advanced natural ventilation using plena and exhaust stacks; fan-assisted natural ventilation in which fans are used in the exhaust stacks; and mechanical ventilation/cooling with heat recovery. Computer simulations have been carried out to predict the influence on thermal performance (overheating risk) and energy consumption of each of these options on the original design. For each case, current weather data, and future weather data for the years 2020, 2050 and 2080, have been used.

Quantifying the effects of climate change and risk level on peak load design in buildings

Good building design aims to balance providing a comfortable internal environment for as much of the time as possible within a variety of constraints. An important factor is the expected weather, but in a changing climate this poses additional challenges to engineers and architects. This paper examines the effects of increased external temperature on the size of the central air conditioning and heating plant for an example building. It is found that for each 1°C rise in external temperatures, the peak cooling load increases approximately by 10%, the chiller power by 14% and fan power for distribution by 30-50%. These are relatively large increases in power needed to counteract rising external temperature and the paper considers the choice of risk level for sizing building plant. From HadRM3 data, the future frequency distribution of higher external temperatures is examined to evaluate the effects on plant size of designing to a fixed percentile of risk. Projected changes in absolute humidity are also discussed. Practical applications: Climate change is an important topic for building services engineers, resulting in the UK in the new, performance-based Building Regulations Part L. New, future weather data will also become available with different climate change scenarios. This paper examines the implications of both climate change and the risk level on the peak load for natural ventilation or air conditioning and heating that is used in the design of systems.