Methodologies for the generation of design summer years for building energy simulation using UKCP09 probabilitic 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.

Recent advances in global electric circuit coupling between the space environment and the troposphere

The global atmospheric electric circuit is driven by thunderstorms and electrified rain/shower clouds and is also influenced by energetic charged particles from space. The global circuit maintains the ionosphere as an equipotential at∼+250 kV with respect to the good conducting Earth (both land and oceans). Its “load” is the fair weather atmosphere and semi-fair weather atmosphere at large distances from the disturbed weather “generator” regions. The main solar-terrestrial (or space weather) influence on the global circuit arises from spatially and temporally varying fluxes of galactic cosmic rays (GCRs) and energetic electrons precipitating from the magnetosphere. All components of the circuit exhibit much variability in both space and time. Global circuit variations between solar maximum and solar minimum are considered together with Forbush decrease and solar flare effects. The variability in ion concentration and vertical current flow are considered in terms of radiative effects in the troposphere, through infra-red absorption, and cloud effects, in particular possible cloud microphysical effects from charging at layer cloud edges. The paper identifies future research areas in relation to Task Group 4 of the Climate and Weather of the Sun-Earth System (CAWSES-II) programme.

A Wiener-Hopf type factorization for the exponential functional of Levy processes

For a Lévy process ξ=(ξt)t≥0 drifting to −∞, we define the so-called exponential functional as follows: Formula Under mild conditions on ξ, we show that the following factorization of exponential functionals: Formula holds, where × stands for the product of independent random variables, H− is the descending ladder height process of ξ and Y is a spectrally positive Lévy process with a negative mean constructed from its ascending ladder height process. As a by-product, we generate an integral or power series representation for the law of Iξ for a large class of Lévy processes with two-sided jumps and also derive some new distributional properties. The proof of our main result relies on a fine Markovian study of a class of generalized Ornstein–Uhlenbeck processes, which is itself of independent interest. We use and refine an alternative approach of studying the stationary measure of a Markov process which avoids some technicalities and difficulties that appear in the classical method of employing the generator of the dual Markov process.

Controlling market power of vertically integrated firms in electricity networks: demand response of aggregator agents

This article reports the results of an experiment that examined how demand aggregators can discipline vertically-integrated firms - generator and distributor-retailer holdings-, which have a high share in wholesale electricity market with uniform price double auction (UPDA). We initially develop a treatment where holding members redistribute the profit based on the imposition of supra-competitive prices, in equal proportions (50%-50%). Subsequently, we introduce a vertical disintegration (unbundling) treatment with holding-s information sharing, where profits are distributed according to market outcomes. Finally, a third treatment is performed to introduce two active demand aggregators, with flexible interruptible loads in real time. We found that the introduction of responsive demand aggregators neutralizes the power market and increases market efficiency, even beyond what is achieved through vertical disintegration.

The statistical downscaling model-decision centric (SDSM-DC): conceptual basis and applications

Regional climate downscaling has arrived at an important juncture. Some in the research community favour continued refinement and evaluation of downscaling techniques within a broader framework of uncertainty characterisation and reduction. Others are calling for smarter use of downscaling tools, accepting that conventional, scenario-led strategies for adaptation planning have limited utility in practice. This paper sets out the rationale and new functionality of the Decision Centric (DC) version of the Statistical DownScaling Model (SDSM-DC). This tool enables synthesis of plausible daily weather series, exotic variables (such as tidal surge), and climate change scenarios guided, not determined, by climate model output. Two worked examples are presented. The first shows how SDSM-DC can be used to reconstruct and in-fill missing records based on calibrated predictor-predictand relationships. Daily temperature and precipitation series from sites in Africa, Asia and North America are deliberately degraded to show that SDSM-DC can reconstitute lost data. The second demonstrates the application of the new scenario generator for stress testing a specific adaptation decision. SDSM-DC is used to generate daily precipitation scenarios to simulate winter flooding in the Boyne catchment, Ireland. This sensitivity analysis reveals the conditions under which existing precautionary allowances for climate change might be insufficient. We conclude by discussing the wider implications of the proposed approach and research opportunities presented by the new tool.

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed.

Dual mycorrhizal associations of jarrah (Eucalyptus marginata) in a nurse-pot system

Jarrah (Eucalyptus marginata Donn ex Sm.) plants, like many other eucalypts, can form symbiotic associations with both arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi. To study this tripartite relationship we developed a novel nurse-pot system to allow us to investigate the extent and temporal colonisation dynamics of jarrah by two AM species (Rhizophagus irregularis (Błaszk., Wubet, Renker & Buscot) C. Walker & A. Schüßler comb. nov. and Scutellospora calospora Nicol. & Gerd.) and two putative ECM species (Austroboletus occidentalis Watling & N.M. Greg. and Scleroderma sp.) and their potential effects on jarrah growth and nutrition. Our nurse-pot system, using jarrah as both the nurse plant and test plant, was developed to establish extraradical hyphal networks of both AM and ECM fungi that act as single or dual inoculum for test plants. Mycorrhizal colonisation was described and quantified, and growth and nutritional effects measured and analysed. Mycorrhizal colonisation increased with time for the test seedlings exposed to hyphae networks from S. calospora and Scleroderma sp. The nurse-pot system was effective at initiating colonisation of functioning AM or (putative) ECM systems separately but the ECM symbiosis was inhibited where a dual AM + ECM inoculum (R. irregularis and Scleroderma sp.) was present. The presence of S. calospora, A. occidentalis and Scleroderma sp. individually significantly increased the shoot biomass of seedlings compared with non-mycorrhizal controls. The two AM isolates had different physiological effects on jarrah plants. S. calospora improved growth and micronutrient uptake of jarrah seedlings whereas no positive response was observed with R. irregularis. In addition, as an interesting observation, the non-responsive AM fungus R. irregularis suppressed the ECM symbiosis in dually inoculated plants where ECM structures, positive growth response and nutritional effects were absent. When inoculated individually, ECM isolates dominated the growth response and uptake of P and other nutrients in this dual symbiotic plant. Despite the positive growth response in the A. occidentalis treatment, ECM structures were not observed in either nurse or test seedlings. From the effects of A. occidentalis on jarrah we hypothesise that this fungus forms a functional mycorrhizal-type partnership even without forming archetypal structures in and on the root