UKCP09 Weather Generator Research Articles

Making real options analysis more accessible for climate change adaptation. An application to afforestation as a flood management measure in the Scottish Borders

Climate change uncertainty makes decisions for adaptation investments challenging, in particular when long time horizons and large irreversible upfront costs are involved. Often the costs will be immediate and clear, but the benefits may be uncertain and only occur in the distant future. Robust decision-making methods such as real options analysis (ROA) handle uncertainty better and are therefore useful to guide decision-making for climate change adaptation. ROA allows for learning about climate change by developing flexible strategies that can be adjusted over time. Practical examples of ROA to climate change adaptation are still relatively limited and tend to be complex. We propose an application that makes ROA more accessible to policy-makers by using the user-friendly and freely available UK climate data of the UKCP09 weather generator, which provides projections of future rainfall, deriving transition probabilities for the ROA in a straightforward way and demonstrating how the analysis can be implemented in spreadsheet format using backward induction. The application is to afforestation as a natural flood management measure (NFM) in a rural catchment in Scotland. The applicability of ROA to broadleaf afforestation as a NFM has not been previously investigated. Different ROA strategies are presented based on varying the damage cost from flooding, fixed cost and the discount rate. The results illustrate how learning can lower the overall investment cost of climate change adaptation but also that the cost structure of afforestation does not lend itself very well to ROA.

Wind-driven rain and future risk to built heritage in the United Kingdom: Novel metrics for characterising rain spells

Wind-driven rain (WDR) is rain given a horizontal velocity component by wind and falling obliquely. It is a prominent environmental risk to built heritage, as it contributes to the damage of porous building materials and building element failure. While predicted climate trends are well-established, how they will specifically manifest in future WDR is uncertain. This paper combines UKCP09 Weather Generator predictions with a probabilistic process to create hourly time series of climate parameters under a high-emissions scenario for 2070–2099 at eight UK sites. Exposure to WDR at these sites for baseline and future periods is calculated from semi-empirical models based on long-term hourly meteorological data using ISO 15927-3:2009. Towards the end of the twenty-first century, it is predicted that rain spells will have higher volumes, i.e. a higher quantity of water will impact façades, across all 8 sites. Although the average number of spells is predicted to remain constant, they will be shorter with longer of periods of time between them and more intense with wind-driven rain occurring for a greater proportion of hours within them. It is likely that in this scenario building element failure – such as moisture ingress through cracks and gutter over-spill – will occur more frequently. There will be higher rates of moisture cycling and enhanced deep-seated wetting. These predicted changes require new metrics for wind-driven rain to be developed, so that future impacts can be managed effectively and efficiently.

Analysing changes in short-duration extreme rainfall events

Two approaches are presented for using the UKCP09 weather generator (WG) to assess changes in extreme short-duration rainfall. The first provides change factors for design storms of varying duration and frequency, building on established hydrological techniques and with uncertainty estimation. The second approach characterises and facilitates the selection of WG timeseries for use in impact models. The methods have been tested at ten case study sites around the UK. The results show an increase in the intensity of short-duration (1 h and 12 h) events in winter but a reduction in summer, although the latter is subject to high levels of uncertainty. The number of intense events increases slightly and more significantly for some locations, especially in winter. Generally, it is hard to establish any conclusions geographically, although increases in rainfall intensity and events in the Lake District site stand out. The methods provide practical techniques for utilising the UKCP09 WG to assess the impacts of climate change, in particular for urban drainage and sewer modelling.

Crop lodging induced by wind and rain

A methodology to estimate wind and rain effects on the four main growth crops in the United Kingdom is presented. The method is based on simulated weather scenarios acting on synthetic plants over a period of thirty years. The environmental data is generated with the UKCP09 Weather Generator considering future climate scenarios whereas plants are modelled as simple oscillators characterised by their mass, stiffness and damping. The joint probability of occurrence of wind and rain are estimated together with the conditions in which lodging would occur. The paper shows that the dynamic response of plants varies with season being the first three months of the year the most critical whilst the plants’ performances define crop failure velocities ranging between 4ms−1 and 23ms−1 and associated failure rates of 50% and 5% per unitary velocity.

Adapting Scotland’s forests to climate change using an action expiration chart

The inherent uncertainty of climate change impacts is one of the main challenges for adaptation in environmental management. The lack of knowledge about climate impacts on ecosystem services at high spatial and temporal resolution limits when and what adaptation measures should be taken. We addressed these limits by assessing four ecosystem services—forest production, tree growth, sequestered carbon, and tourism potential—under drought or climate change. To support adaptation, we adapted the existing concept of ‘dynamic adaptive policy pathways’ for forest management by developing an action expiration chart, which helps to define expiry dates for forestry actions using ecosystem services delivery thresholds. We assessed services for Sitka spruce, Scots pine, and pedunculate oak on the National Forest Estate in Scotland for the next 80 years using probabilistic climate change data from the UKCP09 weather generator. Findings showed that drought would have an overall long-term negative impact on the provision of three services with a decrease up to 41%, whereas climate change has a positive impact on tourism potential with up to five times higher frequency of good climate conditions during summer months. Furthermore, the results highlighted when forestry actions, mainly in the lowlands, will reach their environmental limits during the next 80 years. Our findings reduce knowledge uncertainty and highlight when and where adaptation should be implemented to ensure the provision of future forest ecosystem services in Scotland.

Irrigation demand modelling using the UKCP09 weather generator: lessons learned

The determination of irrigation demand is typically based on crop modelling using a long historic record of local daily weather data. However, there are rarely adequate weather station records near to given sites; often any local records cover a limited number of years, are incomplete, costly or are of poor quality. This paper examines whether version 1 of the UKCP09 weather generator can provide a simpler and effective method of calculating irrigation demand with sufficient accuracy for regulatory and design purposes. The irrigation demands at seven sites distributed around England were modelled using the UKCP09 baseline climatology and compared with results modelled using daily observed weather records. For the design dry year used for irrigation planning, the weather generator replicated the observed conditions with reasonable accuracy. The weather generator was however less successful at replicating extreme dry years. These results are encouraging but also provide a note of caution for the use of these generated datasets for studying current irrigation demand and by implication for modelling future needs under climate change. The study also demonstrated a simple sub-sampling approach for reducing the processing demands if using the dataset in more complex models, though this would not remove any underlying error.

An investigation into future performance and overheating risks in Passivhaus dwellings

In response to UK government policy mandating the construction of ‘zero carbon’ homes by 2016 there have been significant changes in the way dwellings are being designed and built. Recent years have seen a rapid uptake in the adoption of the German Passivhaus standard as a template for ultra-low energy and zero carbon buildings in the UK. Despite genuine motivations to mitigate climate change and fuel poverty there is a lack of research investigating the long-term performance of Passivhaus buildings in a rapidly changing UK climate. This paper sets out to investigate whether Passivhaus dwellings will be able to provide high standards of thermal comfort in the future or whether they are inherently vulnerable to overheating risks. Scenario modelling using probabilistic data derived from the UKCP09 weather generator (WG) in conjunction with dynamic simulation and global sensitivity analysis techniques are used to assess the future performance of a range of typical Passivhaus dwellings relative to an identical Fabric Energy Efficiency Standard (FEES) compliant dwelling over its notional future lifespan. The emphasis of this study is to understand what impact climate change will pose to overheating risks for Passivhaus dwellings relative to the de facto (i.e. FEES) alternative, and which design factors play a dominant role in contributing to this risk. The results show that optimization of a small number of design inputs, including glazing ratios and external shading devices, can play a significant role in mitigating future overheating risks.

Quantification of uncertainty sources in a probabilistic climate change assessment of future water shortages

As the incorporation of probabilistic climate change information into UK water resource management gathers apace, understanding the relative scales of the uncertainty sources in projections of future water shortage metrics is necessary for the resultant information to be understood and used effectively. Utilising modified UKCP09 weather generator data and a multi-model approach, this paper represents a first attempt at extending an uncertainty assessment of future stream flows under forced climates to consider metrics of water shortage based on the triggering of reservoir control curves. It is found that the perturbed physics ensemble uncertainty, which describes climate model parameter error uncertainty, is the cause of a far greater proportion of both the overall flow and water shortage per year probability uncertainty than that caused by SRES emissions scenario choice in the 2080s. The methodology for producing metrics of future water shortage risk from UKCP09 weather generator information described here acts as the basis of a robustness analysis of the North Staffordshire WRZ to climate change, which provides an alternative approach for making decisions despite large uncertainties, which will follow.

Will catchment characteristics moderate the projected effects of climate change on flow regimes in the Scottish Highlands?

AbstractRegional climate models were used with the UKCP09 weather generator to downscale outputs from the HadCM3 General Circulation Model, to project climate change by 2050 in the Scottish Highlands. The resulting hydroclimatic data were used to drive a tracer‐aided hydrological model to assess likely changes in flow regimes in three experimental catchments. These are located along a hydroclimatic transect from the wet, mild western Highlands (Strontian), through the colder, more continental central Highlands (Allt a' Mharcaidh), to the drier eastern Highlands (Girnock). At all sites, temperatures are projected to increase by around 2 °C, with associated increases in potential evapotranspiration. Precipitation is expected to increase by around 10–15% at Strontian but remains slightly changed at the Allt a' Mharcaidh and Girnock. However, the seasonal distribution of precipitation is projected to change, increasing in winter and decreasing in summer. Cautious interpretation of model outputs indicates that flows are likely to change accordingly at all sites, though the characteristics of each catchment result in some subtle differences. At Strontian, marked increases in winter high flows are expected, at the Allt a' Mharcaidh, reduction in winter snowfall and reduced snowpack will increase winter high flows and moderate the influence of spring melts. In the Girnock, decreasing summer low flows are the most notable element of change. These subtle differences in response to climatic drivers are consistent with the distinct storage characteristics of the catchments which in turn reflect their landscape evolution histories. Copyright © 2012 John Wiley & Sons, Ltd.

Using the UKCP09 probabilistic scenarios to model the amplified impact of climate change on drainage basin sediment yield

Abstract. Precipitation intensities and the frequency of extreme events are projected to increase under climate change. These rainfall changes will lead to increases in the magnitude and frequency of flood events that will, in turn, affect patterns of erosion and deposition within river basins. These geomorphic changes to river systems may affect flood conveyance, infrastructure resilience, channel pattern, and habitat status as well as sediment, nutrient and carbon fluxes. Previous research modelling climatic influences on geomorphic changes has been limited by how climate variability and change are represented by downscaling from global or regional climate models. Furthermore, the non-linearity of the climatic, hydrological and geomorphic systems involved generate large uncertainties at each stage of the modelling process creating an uncertainty "cascade". This study integrates state-of-the-art approaches from the climate change and geomorphic communities to address these issues in a probabilistic modelling study of the Swale catchment, UK. The UKCP09 weather generator is used to simulate hourly rainfall for the baseline and climate change scenarios up to 2099, and used to drive the CAESAR landscape evolution model to simulate geomorphic change. Results show that winter rainfall is projected to increase, with larger increases at the extremes. The impact of the increasing rainfall is amplified through the translation into catchment runoff and in turn sediment yield with a 100% increase in catchment mean sediment yield predicted between the baseline and the 2070–2099 High emissions scenario. Significant increases are shown between all climate change scenarios and baseline values. Analysis of extreme events also shows the amplification effect from rainfall to sediment delivery with even greater amplification associated with higher return period events. Furthermore, for the 2070–2099 High emissions scenario, sediment discharges from 50-yr return period events are predicted to be 5 times larger than baseline values.

The appropriate spatial resolution of future weather files for building simulation

Building thermal modelling packages require weather data to predict representative internal conditions. Typically, around the world, reference weather years of various forms are used which are created from observations at aparticular location. However, it is unlikely that this location is identical to that of the building. This can lead toweather files for coastal locations being applied to inland and upland sites or vice versa. In the UK, the UKCP09 weather generator has the ability to produce weather at a 5 km resolution. Currently, it is unclear how useful this extra spatial resolution will be and it is this question that is addressed here. It is found that for both future and present climate, the spatial variability of the weather is the dominating factor. Although there are geographies where a low spatial resolution can be used, there are regions where a much higher resolution is necessary.

The use of probabilistic weather generator information for climate change adaptation in the UK water sector

Adapting to climate change in the water sector requires abandoning two crucial assumptions. First, that the climate represented in the instrumental record is representative of the future. Instead, future water resource planning cannot be based on old measurements (or sequences derived from attaching change factors to instrumental data) and it should be recognized that stationarity is no longer viable, and, second, that climate modelling can be expected to give precise and certain predictions of the future. Instead, probabilistic projections of the future that take into account the full range of uncertainty should form the basis of robust climate change adaptation plans. As a response to the first assumption, it is suggested that stochastic weather generators represent a particularly useful approach to understanding the impacts of future climate change on water resources at a catchment scale, particularly given the recent release of ‘science-hidden’ tools such as the UKCP09 weather generator. With regards to the second assumption, it is suggested that modelling activity should identify the range of plausible futures to develop probabilities of risk, using those robust decision-making techniques which can gauge the performance of potential adaptation strategies. The best practice for delivering a replicable and practical hydroclimatological impact assessment for UK water resources at a catchment scale is identified, and an hypothetical example is outlined. It is suggested that although augmenting the resilience of water resources to climate change on a catchment scale is dependent on using the correct modelling tools, the robustness of the method with which that information is used to make adaptation decisions is equally as important. Copyright © 2012 Royal Meteorological Society

Methodologies for the generation of design summer years for building energy simulation using UKCP09 probabilistic climate projections

Design summer years representing near-extreme hot summers have been used in the United Kingdom for the evaluation of thermal comfort and overheating risk. The years have been selected from measured weather data basically representative of an assumed stationary climate. Recent developments have made available ‘morphed’ equivalents of these years by shifting and stretching the measured variables using change factors produced by the UKCIP02 climate projections. The release of the latest, probabilistic, climate projections of UKCP09 together with the availability of a weather generator that can produce plausible daily or hourly sequences of weather variables has opened up the opportunity for generating new design summer years which can be used in risk-based decision-making. There are many possible methods for the production of design summer years from UKCP09 output: in this article, the original concept of the design summer year is largely retained, but a number of alternative methodologies for generating the years are explored. An alternative, more robust measure of warmth (weighted cooling degree hours) is also employed. It is demonstrated that the UKCP09 weather generator is capable of producing years for the baseline period, which are comparable with those in current use. Four methodologies for the generation of future years are described, and their output related to the future (deterministic) years that are currently available. It is concluded that, in general, years produced from the UKCP09 projections are warmer than those generated previously. Practical applications: The methodologies described in this article will facilitate designers who have access to the output of the UKCP09 weather generator (WG) to generate Design Summer Year hourly files tailored to their needs. The files produced will differ according to the methodology selected, in addition to location, emissions scenario and timeslice.

Thermal building simulation using the UKCP09 probabilistic climate projections

This article investigates how to use UK probabilistic climate-change projections (UKCP09) in rigorous building energy analysis. Two office buildings (deep plan and shallow plan) are used as case studies to demonstrate the application of UKCP09. Three different methods for reducing the computational demands are explored: statistical reduction (Finkelstein-Schafer [F-S] statistics), simplification using degree-day theory and the use of metamodels. The first method, which is based on an established technique, can be used as reference because it provides the most accurate information. However, it is necessary to automatically choose weather files based on F-S statistic by using computer programming language because thousands of weather files created from UKCP09 weather generator need to be processed. A combination of the second (degree-day theory) and third method (metamodels) requires only a relatively small number of simulation runs, but still provides valuable information to further implement the uncertainty and sensitivity analyses. The article also demonstrates how grid computing can be used to speed up the calculation for many independent EnergyPlus models by harnessing the processing power of idle desktop computers.

Assessing the risk of climate change for buildings: A comparison between multi-year and probabilistic reference year simulations

Given a changing climate, there is a need to provide data for future years so that practicing engineers can investigate the impact of climate change on particular designs and examine any risk the client might be exposed to. In addition, such files are of use to building scientists in developing generic solutions to problems such as elevated internal temperatures and poor thermal comfort. With the release of the UK Climate Projections (UKCP09) [1], and the publication of a methodology for the creation of probabilistic future reference years using the UKCP09 weather generator [2], it is possible to model future building performance. However, the collapse of the distribution of possibilities inherent in the UKCP09 method into a single reference year or a small number of reference years, potentially means the loss of most of the information about the potential range of the response of the building and of the risk occupants might be subject to. In this paper we model for the first time the internal conditions and energy use of a building with all 3000 example years produced by the UKCP09 weather generator in an attempt to study the full range of response and risk. The resultant histograms and cumulative distribution functions are then used to examine whether single reference years can be used to answer questions about response and risk under a changing climate, or whether a more probabilistic approach is unavoidable.

The creation of wind speed and direction data for the use in probabilistic future weather files

Pseudo weather data with a high temporal resolution are of use in many fields including the modelling of agricultural systems, the placement of wind turbines and building thermal simulations. With the publication of the 2009 UK Climate Projections (UKCP09) such data can be created for future years and for various predictions of climate change. Unfortunately such — UKCP09 — data does not include information about wind speed or direction due to a lack of robustness. Here we demonstrate a methodology for generating such wind data on an hourly time grid from a consideration of the potential evapotranspiration reported by the UKCP09 weather generator and information related to the correlation between observed wind speed, direction and time of year. We find our pseudo wind data is consistent with the historic observed wind. Furthermore, when used within a dynamic thermal simulation of a building, the use of such pseudo wind data generates a consistent internal environment in terms of ventilation rates, temperatures and energy use that is indistinguishable from simulations completed using historic observed weather for both single-sided and cross-ventilated buildings. Practical applications: The methodology presented in this paper will allow academics and building engineers to create realistic hourly wind speed and direction data for inclusion with the future climate data of UKCP09. This will allow the creation of consistent future weather years for use in areas such as building thermal simulation.

On the creation of future probabilistic design weather years from UKCP09

Weather data are used extensively by building scientists and engineers to study the performance of their designs, help compare design alternatives and ensure compliance with building regulations. Given a changing climate, there is a need to provide data for future years so that practising engineers can investigate the impact of climate change on particular designs and examine any risk the commissioning client might be exposed to. In addition, such files are of use to building scientists in developing generic solutions to problems such as elevated internal temperatures and poor thermal comfort. With the publication of the UK Climate Projections (UKCP09) such data can be created for future years up to 2080 and for various probabilistic projections of climate change by the use of a weather generator. Here, we discuss a method for the creation of future probabilistic reference years for use within thermal models. In addition, a comparison is made with the current set of future weather years based on the UKCIP02 projections. When used within a dynamic thermal simulation of a building, the internal environments created by the current set of future weather files lie within the range of the internal environments created by the probabilistic reference years generated by the weather generator. Hence, the main advantages of the weather generator are seen to lie in its potentially greater spatial resolution, its ability to inform risk analysis and that such files, unlike ones based on observed data, carry no copyright. Practical applications: The methodology presented in this article will allow academics and buildings engineers to create realistic hourly future weather files using the future climate data of UKCP09 weather generator. This will allow the creation of consistent future weather years for use in areas such as building thermal simulation.