Re-examining the U.K.'s greatest tornado outbreak: forecasting the limited extent of tornadoes along a cold front

On 23 November 1981, a strong cold front swept across the U.K., producing tornadoes from the west to the east coasts. An extensive campaign to collect tornado reports by the Tornado and Storm Research Organisation (TORRO) resulted in 104 reports, the largest U.K. outbreak. The front was simulated with a convection-permitting numerical model down to 200-m horizontal grid spacing to better understand its evolution and meteorological environment. The event was typical of tornadoes in the U.K., with convective available potential energy (CAPE) less than 150 J kg-1, 0-1-km wind shear of 10-20 m s-1, and a narrow cold-frontal rainband forming precipitation cores and gaps. A line of cyclonic absolute vorticity existed along the front, with maxima as large as 0.04 s-1. Some hook-shaped misovortices bore kinematic similarity to supercells. The narrow swath along which the line was tornadic was bounded on the equatorward side by weak vorticity along the line and on the poleward side by zero CAPE, enclosing a region where the environment was otherwise favorable for tornadogenesis. To determine if the 104 tornado reports were plausible, first possible duplicate reports were eliminated, resulting in as few as 58 tornadoes to as many as 90. Second, the number of possible parent misovortices that may have spawned tornadoes is estimated from model output. The number of plausible tornado reports in the 200-m grid-spacing domain was 22 and as many as 44, whereas the model simulation was used to estimate 30 possible parent misovortices within this domain. These results suggest that 90 reports was plausible.

Spatial housing economics: a survey

This introduction to the Virtual Special Issue surveys the development of spatial housing economics from its roots in neo-classical theory, through more recent developments in social interactions modelling, and touching on the role of institutions, path dependence and economic history. The survey also points to some of the more promising future directions for the subject that are beginning to appear in the literature. The survey covers elements hedonic models, spatial econometrics, neighbourhood models, housing market areas, housing supply, models of segregation, migration, housing tenure, sub-national house price modelling including the so-called ripple effect, and agent-based models. Possible future directions are set in the context of a selection of recent papers that have appeared in Urban Studies. Nevertheless, there are still important gaps in the literature that merit further attention, arising at least partly from emerging policy problems. These include more research on housing and biodiversity, the relationship between housing and civil unrest, the effects of changing age distributions - notably housing for the elderly - and the impact of different international institutional structures. Methodologically, developments in Big Data provide an exciting framework for future work.

Reducing defects through organizational learning within a Housing Association environment

Housing Associations (HAs) contribute circa 20% of the UK’s housing supply. HAs are however under increasing pressure as a result of funding cuts and rent reductions. Due to the increased pressure, a number of processes are currently being reviewed by HAs, especially how they manage and learn from defects. Learning from defects is considered a useful approach to achieving defect reduction within the UK housebuilding industry. This paper contributes to our understanding of how HAs learn from defects by undertaking an initial round table discussion with key HA stakeholders as part of an ongoing collaborative research project with the National House Building Council (NHBC) to better understand how house builders and HAs learn from defects to reduce their prevalence. The initial discussion shows that defect information runs through a number of groups, both internal and external of a HA during both the defects management process and organizational learning (OL) process. Furthermore, HAs are reliant on capturing and recording defect data as the foundation for the OL process. During the OL process defect data analysis is the primary enabler to recognizing a need for a change to organizational routines. When a need for change has been recognized, new options are typically pursued to design out defects via updates to a HAs Employer’s Requirements. Proposed solutions are selected by a review board and committed to organizational routine. After implementing a change, both structured and unstructured feedback is sought to establish the change’s success. The findings from the HA discussion demonstrates that OL can achieve defect reduction within the house building sector in the UK. The paper concludes by outlining a potential ‘learning from defects model’ for the housebuilding industry as well as describing future work.

Detecting defects in the UK new-build housing sector: a learning perspective

Rapid growth in the production of new homes in the UK is putting build quality under pressure as evidenced by an increase in the number of defects. Housing associations (HAs) contribute approximately 20% of the UK’s new housing supply. HAs are currently experiencing central government funding cuts and rental revenue reductions. As part of HAs’ quest to ramp up supply despite tight budget conditions, they are reviewing how they learn from defects. Learning from defects is argued as a means of reducing the persistent defect problem within the UK housebuilding industry, yet how HAs learn from defects is under-researched. The aim of this research is to better understand how HAs, in practice, learn from past defects to reduce the prevalence of defects in future new homes. The theoretical lens for this research is organizational learning. The results drawn from 12 HA case studies indicate that effective organizational learning has the potential to reduce defects within the housing sector. The results further identify that HAs are restricting their learning to focus primarily on reducing defects through product and system adaptations. Focusing on product and system adaptations alone suppresses HAs’ abilities to reduce defects in the future.

Are mortgage lenders guilty of the housing bubble? A UK perspective

Existing theoretical models of house prices and credit rely on continuous rationality of consumers, an assumption that has been frequently questioned in recent years. Meanwhile, empirical investigations of the relationship between prices and credit are often based on national-level data, which is then tested for structural breaks and asymmetric responses, usually with subsamples. Earlier author argues that local markets are structurally different from one another and so the coefficients of any estimated housing market model should vary from region to region. We investigate differences in the price–credit relationship for 12 regions of the UK. Markov-switching is introduced to capture asymmetric market behaviours and turning points. Results show that credit abundance had a large impact on house prices in Greater London and nearby regions alongside a strong positive feedback effect from past house price movements. This impact is even larger in Greater London and the South East of England when house prices are falling, which are the only instances where the credit effect is more prominent than the positive feedback effect. A strong positive feedback effect from past lending activity is also present in the loan dynamics. Furthermore, bubble probabilities extracted using a discrete Kalman filter neatly capture market turning points.

Evaluation of the Plant–Craig stochastic convection scheme (v2.0) in the ensemble forecasting system MOGREPS-R (24 km) based on the Unified Model (v7.3)

The Plant–Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic scheme only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant–Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant–Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

Reactivity of Nellore steers in two feedlot housing systems and its relationship with plasmatic cortisol

To evaluate reactivity to assess the temperament of Nellore steers in two feedlot housing systems (group pen or individual pen) and its relationship with plasmatic cortisol, 36 experimental units were observed five times at 28-day intervals of weight management during a 112-day feedlot confinement. A reactivity score scale ranging from 1 to 5 was applied when an animal was in the chute system. To the calmest animal, a reactivity score of 1 was ascribed and to the most agitated, 5. Blood samples were collected for cortisol analysis. No differences were found in reactivity and feedlot system. There was a relationship noted between reactivity and feedlot time in both housing systems (P < 0.01). There was a relation between reactivity and cortisol levels for group animals (P = 0.0616) and for individual ones (P < 0.01). Cortisol levels varied among housing systems (P < 0.01). Feedlot time influenced the cortisol levels (P < 0.09 individual; P < 0.01 group) and when variable time was included, these levels changed, decreasing in the group pen and increasing in individual pens. The continuous handling reduces reactivity and plasmatic cortisol, and group pen system seems to be less stressfully than individual pens. (C) 2010 Elsevier B.V. All rights reserved.

A Plant Needs Ants like a Dog Needs Fleas: Myrmelachista schumanni Ants Gall Many Tree Species to Create Housing

Hundreds of tropical plant species house ant colonies in specialized chambers called domatia. When, in 1873, Richard Spruce likened plant-ants to fleas and asserted that domatia are ant-created galls, he incited a debate that lasted almost a century. Although we now know that domatia are not galls and that most ant-plant interactions are mutualisms and not parasitisms, we revisit Spruce`s suggestion that ants can gall in light of our observations of the plant-ant Myrmelachista schumanni, which creates clearings in the Amazonian rain forest called ""supay-chakras,"" or ""devil`s gardens."" We observed swollen scars on the trunks of nonmyrmecophytic canopy trees surrounding supay-chakras, and within these swellings, we found networks of cavities inhabited by M. schumanni. Here, we summarize the evidence supporting the hypothesis that M. schumanni ants make these galls, and we hypothesize that the adaptive benefit of galling is to increase the amount of nesting space available to M. schumanni colonies.

MODELLING AND FORECASTING INFLATION RATES IN GHANA: AN APPLICATION OF SARIMA MODELS

Ghana faces a macroeconomic problem of inflation for a long period of time. The problem in somehow slows the economic growth in this country. As we all know, inflation is one of the major economic challenges facing most countries in the world especially those in African including Ghana. Therefore, forecasting inflation rates in Ghana becomes very important for its government to design economic strategies or effective monetary policies to combat any unexpected high inflation in this country. This paper studies seasonal autoregressive integrated moving average model to forecast inflation rates in Ghana. Using monthly inflation data from July 1991 to December 2009, we find that ARIMA (1,1,1)(0,0,1)12 can represent the data behavior of inflation rate in Ghana well. Based on the selected model, we forecast seven (7) months inflation rates of Ghana outside the sample period (i.e. from January 2010 to July 2010). The observed inflation rate from January to April which was published by Ghana Statistical Service Department fall within the 95% confidence interval obtained from the designed model. The forecasted results show a decreasing pattern and a turning point of Ghana inflation in the month of July.

Daily Calls Volume Forecasting

A massive amount has been written about forecasting but few articles are written about the development of time series models of call volumes for emergency services. In this study, we use different techniques for forecasting and make the comparison of the techniques for the call volume of the emergency service Rescue 1122 Lahore, Pakistan. For the purpose of this study data is taken from emergency calls of Rescue 1122 from 1st January 2008 to 31 December 2009 and 731 observations are used. Our goal is to develop a simple model that could be used for forecasting the daily call volume. Two different approaches are used for forecasting the daily call volume Box and Jenkins (ARIMA) methodology and Smoothing methodology. We generate the models for forecasting of call volume and present a comparison of the two different techniques.

Forecasting with Vector Nonlinear Time Series Models

This work concerns forecasting with vector nonlinear time series models when errorsare correlated. Point forecasts are numerically obtained using bootstrap methods andillustrated by two examples. Evaluation concentrates on studying forecast equality andencompassing. Nonlinear impulse responses are further considered and graphically sum-marized by highest density region. Finally, two macroeconomic data sets are used toillustrate our work. The forecasts from linear or nonlinear model could contribute usefulinformation absent in the forecasts form the other model.

Energy savings potential in existing houses : Energy simulation results for Dalarna's single-family housing stock

Vägar till en halverad energianvändning i Dalarnas byggnadsbestånd

Tha contribution of home-based technology to older people's quality of life in extra care housing

Background: British government policy for older people focuses on a vision of active ageing and independent living. In the face of diminishing personal capacities, the use of appropriate home-based technology (HBT) devices could potentially meet a wide range of needs and consequently improve many aspects of older people's quality of life such as physical health, psychosocial well-being, social relationships, and their physical or living environment. This study aimed to examine the use of HBT devices and the correlation between use of such devices and quality of life among older people living in extra-care housing (ECH).  Methods: A structured questionnaire was administered for this study. Using purposive sampling 160 older people living in extra-care housing schemes were selected from 23 schemes in England. A face-to-face interview was conducted in each participant's living unit. In order to measure quality of life, the SEIQoL-Adapted and CASP-19 were used.  Results: Although most basic appliances and emergency call systems were used in the living units, communally provided facilities such as personal computers, washing machines, and assisted bathing equipment in the schemes were not well utilised. Multiple regression analysis adjusted for confounders including age, sex, marital status, living arrangement and mobility use indicated a coefficient of 1.17 with 95% CI (0.05, 2.29) and p = 0.04 [SEIQoL-Adapted] and 2.83 with 95% CI (1.17, 4.50) and p = 0.001 [CASP-19].  Conclusions: The findings of the present study will be value to those who are developing new form of specialised housing for older people with functional limitations and, in particular, guiding investments in technological aids. The results of the present study also indicate that the home is an essential site for developing residential technologies.

Extended local labor markets due to high speed trains : Visualization of estimations in the Swedish national travel demand forecasting tool, SAMPERS

Wider economic benefits resulting from extended geographical mobility is one argument for investments in high-speed rail. More specifically, the argument for high-speed trains in Sweden has been that they can help to further spatially extend labor market regions which in turn has a positive effect on growth and development. In this paper the aim is to cartographically visualize the potential size of the labor markets in areas that could be affected by possible future high-speed trains. The visualization is based on the forecasts of labor mobility with public transport made by the Swedish national mobility transport forecasting tool, SAMPERS, for two alternative high-speed rail scenarios. The analysis, not surprisingly, suggests that the largest impact of high-speed trains results in the area where the future high speed rail tracks are planned to be built. This expected effect on local labor market regions of high-speed trains could mean that possible regional economic development effects also are to be expected in this area. However, the results, in general, from the SAMPERS forecasts indicaterelatively small increases in local labor market potentials.