The Ghosts of Rana Plaza: In Bangladesh, one year after the worst accident in the history of the garment industry, recovery remains a fragile process, justice seems elusive, and reform has a long way to go.

Emergency Response Resilience to Floods Operationalised with Applied Geoinformatics

Developing a Taste for Coffee: Bangladesh, Nescafé, and Australian Student Photographers

District heating in case of power failure

Fire safety measures save lives and reduce economic losses caused by building fires. However, these benefits come at a cost, because fire safety is not free of charge. An economic optimum is achieved when the total costs of fire and fire safety are minimized. Of course, fire safety decisions cannot be based only on economic reasoning. The safety of building occupants is an important boundary condition for monetary optimization. Societal resources for life saving measures are limited and should be invested where the largest risk reduction can be achieved. Thus, also the definition of acceptance criteria for decisions regarding investments into life safety should be based on efficiency considerations. The focus of this thesis is on the optimization of societal investments for preventive building fire safety. The starting point is the formulation of a general decision problem consisting of two parts: monetary optimization and societal risk acceptance. The optimization may be performed either by a private decision-maker or at societal level. The acceptability of fire safety decisions with respect to life safety, on the other hand, is always evaluated from a societal point of view. Quantitative acceptance criteria can be derived based on the marginal life saving costs principle, which ensures that societal resources are directed to the most efficient risk reduction measures available. Decisions on fire safety measures are generally made by the owner of a building. At societal level, investments into building fire safety are controlled mainly based on codes and regulations. The owner is free to optimize fire safety using his own objective function, provided that he fulfils the minimum requirements defined by the code. Traditionally, fire safety is regulated based on prescriptive rules defining in detail which measures have to be taken to reduce fire risk. In order to increase the flexibility of code-based fire safety design, a number of countries around the world have adopted performance-based codes, which specify the design objectives, but leave the concrete choice of measures to the designers. Unfortunately, the code objectives are rarely formulated in quantitative terms. In this thesis it is shown how quantitative safety goals for code-based design may be derived from a generic risk-informed framework for balancing the costs and benefits of fire safety. Following this approach, both prescriptive and performance-based fire safety codes can be based on the same principles of monetary optimization and acceptable life safety. Fire safety decisions are decisions under uncertainty. Optimizing fire safety thus requires risk assessment for evaluating the effect of safety investments on the expected monetary and human consequences of fire. For a comparison between the uncertain benefits of fire safety measures and their costs, the risk has to be assessed in absolute terms, with as little bias as possible. The present thesis explores the use of statistical data to reduce the modelling bias resulting from assumptions and simplifications used to estimate the risk. A framework for the calibration of engineering fire risk models with data collected by, for instance, fire brigades or insurance companies is developed. The proposed approach allows a combination of engineering knowledge with observations from real fire events, making the best use of both sources of information.

A quasi-stationary multicell thunderstorm affected parts of mid-Suffolk on Sunday 25 July 2021. The epicentre was the village of Brettenham, where extreme rainfall resulted in over 180mm falling in under 2 h. Local flooding occurred, including significant crop damage. The amount of rain observed in such a short duration challenges UK rainfall records. A detailed mesoanalysis is constructed to analyse the meteorological conditions present, using surface observations from a combination of conventional and privately owned automatic weather stations. During the afternoon of Sunday 25 July 2021, a series of heavy showers and thunderstorms affected portions of East Anglia, London, central southern and southeast England. These largely developed along marked convergence zones in a rather slack pressure pattern, and their slow movement resulted in locally high rainfall totals. Unofficial rain gauge measurements suggested as much as 120mm may have fallen in the Woodford area of northeast London and in the eastern suburbs of Hertford, with around 90mm also close to Haverhill (Suffolk). These areas all experienced flash flooding (BBC News, 2021a,b,c), but the main focus of this paper is mid-Suffolk where extreme but highly localised rainfall occurred that could challenge some UK rainfall records. This article uses a variety of datasets to explore the synoptic background and evolution, observed rainfall totals, impacts on the local area and comparisons with other significant short-duration rainfall events in the United Kingdom. To gain an understanding into the meteorological conditions present before and during this event, a mesoanalysis was constructed using data from over 350 privately owned automatic weather stations (AWS) across Norfolk, Suffolk, Essex and adjacent portions of Cambridgeshire and Hertfordshire. This data, provided by Weather Underground (WU), 1 was merged with existing synoptic observations from AWS operated by the Met Office to create a gridded dataset. While the exposure of each private AWS will likely vary considerably, no bias correction was applied to the raw data since the general siting of each AWS is not known and the rather slack pressure pattern on this day made it difficult to determine appropriate correction values with the nearest Met Office AWS. Nonetheless, some elements of filtering were employed in an attempt to reduce the number of potential erroneous measurements being used in the gridded fields. Wind speed and direction time-series for all private AWS between 0000 utc and 2359 utc on 25 July 2021 were subjectively examined, and sites with consistently erratic speed or direction, and/or poorly calibrated wind direction, were removed. Furthermore, for air and dewpoint temperature a threshold of two standard deviations was applied, with any values falling outside of this range manually checked and subsequently removed if necessary. All filtered observations at each timestep of interest were interpolated onto a 0.025° (~2.5km) horizontal resolution grid using the inverse-distance weighting method with a power of 2. A slight smoothing factor was then applied to avoid any one specific observation dominating too much. For each timestep, the observation from each contributing AWS closest to and within the 10min leading up to the observation time was used. A cut-off 500hPa low, originally located over the Bay of Biscay on Friday 23 July, slowly migrated northeastwards across the Brest peninsula on Saturday 24 July, while deepening. By the Sunday morning (25 July), the centre of the upper low was located over the eastern English Channel and this slowly filled in-situ through the day (Figure 1a). Cold air aloft associated with this upper low, and attendant areas of divergence due to positive vorticity advection (PVA), created an environment increasingly favourable for deep moist convection – and hence thunderstorms. At the surface, a slack pressure pattern dominated with a small low centre over the Cherbourg peninsula at 0000 utc 25 July; this feature drifted eastwards across northern France during the day (Figure 1b), and then northeastwards to become centred near Lille by 1800 utc. A separate small surface low, initially over northwest Germany at 0000 utc 25 July, shifted northwestwards across the North Sea while rotating around the parent low over northern France. However, the main axis between these two features appeared to remain to the southeast and then east of the UK. Much of East Anglia experienced extensive low cloud and mist during the morning, as confirmed by surface observations and visible satellite imagery, with air temperatures close to the dewpoint temperature of 16–17°C. Some patchy light rain and drizzle was evident on radar, in part associated with a frontolysing occlusion shown in Figure 1(b). Breaks in the low cloud eventually developed over the southern North Sea and migrated westwards, into Suffolk and southeast Norfolk during the mid to late morning, and it is these areas where the air temperature increased quickest. Examination of mesoanalyses during the morning revealed that the surface winds were broadly northeasterly across the whole of East Anglia, but there was evidence of veering near eastern coasts during the late morning and early afternoon, presumably as a sea breeze developed in response to the increased thermal contrast between land and sea. The onshore breeze became increasingly perpendicular to the coast through the afternoon – the exact wind direction varied along the east coast due to the local orientation of the coastline.Where this east or southeasterly onshore wind met the synoptic northeasterly surface wind inland, a marked convergence zone (hereafter CZ) developed along a northeast–southwest line from southeast Norfolk to London. The shape and position of this boundary changed through the afternoon, in part due to the influence of outflow from nearby thunderstorms. ERA5 reanalysis (Hersbach et al., 2020) soundings suggest that an air temperature of 22–23°C was required for convective initiation (Figure 2). These values were reached in south Norfolk and across Suffolk by 1130 utc, with maximum temperatures of 24.9°C recorded at Cavendish and 24.2°C at both Charsfield and Wattisham during the afternoon. The first showers appeared as radar echoes around 1230 utc, and over the following hours (Figure 3) multiple clusters of thunderstorms developed along the CZ and drifted to the west–southwest before weakening, their westerly outflow winds at the surface helping to reinforce the existing CZ away to the east. Of particular interest was a thunderstorm that developed around 1440 utc near the A140, to the southwest of Eye (Suffolk). According to radar reflectivity, this storm reached peak intensity around 1500 utc whilst drifting southwestwards towards Woolpit (Suffolk), and spawned a daughter cell on its southern flank near Stowmarket shortly afterwards. This new thunderstorm grew rapidly in size and intensity over subsequent radar scans, and appeared to become quasi-stationary over Brettenham between 1520 utc and 1720 utc. Figure 2 reveals some slight directional and speed shear between the ground and 700hPa (approximately 0–3km) and a vorticity generation parameter (VGP; Rasmussen and Blanchard, 1998) of 0.11, suggesting the potential for updraughts to tilt away from downdraughts and thereby aiding cell organisation and longevity. There is evidence in radar data of back-building as daughter cells continued to develop near Stowmarket and drifted southwestwards over the same areas. The storm motion is estimated from Figure 2 at ~8kn, using 75% of the 0–6km shear. The mesoanalysis in Figure 4 highlights that the area of new cell development coincides with a particular distortion in the shape of the CZ, to the northeast of Stowmarket. This could perhaps be an artefact of the gridding of unevenly distributed observations, but evidence of diverging winds in the vicinity of Brettenham and a notable reduction in 2m temperature well away from the rain shield suggests outflow may have caused a portion of the CZ to bow outwards (i.e. towards the south and east), while remaining anchored on the northern flank. This therefore indicates particularly strong convergence given that winds flowing from the northeast, east, southeast and southwest all met in the vicinity of Stowmarket, allowing unimpeded advection of warm, unstable air over east Suffolk into the area, then subjected to forced ascent from the surface to generate new thunderstorm cells. This may explain, at least partly, why this particular area experienced prolonged and intense rainfall. It is clear by 1700 utc in Figure 3 that the multiple clusters of thunderstorms over west Suffolk and Essex had developed a substantial cold pool at the surface (this became even more significant by 1800 utc), and westerly outflow winds likely contributed to the eastward movement of the CZ, perhaps also aided by a weakening sea breeze by this stage as air temperatures began to reduce following peak surface heating, and the onshore flow became backed to the east once again. By 1800 utc it became increasingly difficult to identify the CZ as the surface winds had broadly reverted back to a northeasterly in most areas, as was the case during the morning. It seems the eastwards surge of the CZ and subsequent weakening, coupled with a reduction in air temperature in all areas, ultimately curtailed new thunderstorm development and the existing storms gradually decayed over the following hours. As highlighted in Figure 5, the storm was very localised with rainfall accumulations largely restricted to rural areas. Some residents of Stowmarket commented on social media that they had heard thunder for several hours but barely received a drop of rain. The highest rainfall measurements in the vicinity from the official Environment Agency network for the 24 h ending 0900 utc 26 July 2021 were 86.7mm at Buxhall, 83.0mm at Felsham and 55.5mm at Cockfield (Rookery Farm). Given no obvious rainfall detected by radar in the morning, and again during the overnight period, it is highly likely that all of these readings represent rainfall received from thunderstorms during the afternoon and early evening hours on 25 July. It is clear from Figure 5 that Brettenham was the epicentre. A farmer on the southwest side of the village, who had previously been a voluntary observer for the Environment Agency from 1997 to 2013 and has continued to keep rainfall records with the same equipment since (Figure 6), measured 181.3mm for the day. A neighbour with an AWS approximately 0.1km to the northeast recorded 161.0mm, although this figure may have been higher in reality considering tipping bucket rain gauges can underestimate accumulations during high rain rates (Burt, 2005). Another farmer at Pound Farm, ~0.8km to the southwest, recorded an estimated 200mm, using a 105mm manual rain gauge that had to be emptied twice – the first time it had overflowed, and the second occurrence had not quite reached full capacity. Given these broadly similar observed values in close proximity to each other, and the equipment used, suggests the 181.3mm is likely reliable. Another (former) resident of Brettenham kindly provided monthly rainfall measurements that both he and his father had collected in the village from 1955 to 2015, including a spell at Old Buckenham School for Anglian Water. The most recent 30-year average for July from this dataset (1986–2015) is 59.0mm, and during the whole 61-year record only one month produced rainfall higher than July 2021: June 1985 with 191.0mm. Unfortunately, daily figures were not available; however, analysis of HadUK-Grid (Hollis et al., 2021) for the nearest grid point suggests that this rainfall was likely spread over multiple days through the month. As such, rainfall of the intensity experienced on 25 July 2021 has never been recorded in Brettenham before (at least not since 1955). Estimates from Figure 5 suggest that the area of 100mm accumulations or higher was approximately 6.3km at its widest, creating some steep rainfall gradients in the vicinity. An unofficial gauge to the north of Hitcham, 2.1km to the southeast of Brettenham, measured 43mm, suggesting a gradient of ~66mmkm−1. This is comparable to the south Norfolk storm on 16 August 2020 (Holley et al., 2021). According to the local parish council, at least 28 dwellings experienced some internal flooding, mostly due to run-off from roads or fields, including the local school. The intensity of the rain, accompanied by small hail, was said to have flattened some crops, in particular a narrow strip of land running from Hitcham through Brettenham and Dux Street towards Felsham, according to another local farmer. Several large diameter trees were also reportedly knocked down – all occurring at the beginning of the crucial harvest period. According to Suffolk Fire and Rescue Service, 37 incidents were reported related to flooding in the Haverhill area between 1545 utc and 2100 utc (Suffolk County Council, personal communication, 15 September 2021) from a separate thunderstorm complex well to the west. However, despite 83 cloud-to-ground lightning strikes detected in the same domain as Figure 5 by the Météorage network 2 , no lightning-related incidents were reported. An attempt has been made to verify the duration in which the rain fell at Brettenham in Figure 7. Since a complete set of high-resolution temporal data is not available from a rain gauge, composite radar reflectivity is used as a substitute for both the grid cell with the highest estimated accumulation (r max = 148.4mm, located to the north of Brettenham and therefore slightly displaced to the northeast of the highest observed values), and the nearest grid cell to the Snowdon rain gauge (r near = 100.4mm, on the south side of the village). Figure 7 suggests that there was a short-duration shower broadly between 1430 and 1500 utc, with an accumulation of 0.8mm at the nearby AWS. This was not noted by the farmer, and so it is possible this small amount of rain may need to be subtracted from the final event total. The exact start time of the main thunderstorm varies depending on data source; the observer in the village reported the event began at 1540 utc and ended at 1720 utc, however data from the AWS suggests rain had already accumulated between 1529 and 1534 utc (since the data were largely uploaded in 5min intervals). A short power cut occurred in the village, apparently only lasting 2–3min, but there was a prolonged data outage at the AWS with no observations between 1606 utc (when it had recorded 62.2mm) and 1729 utc (when the full event total of 161.0mm was reported). Regular observations from the AWS were restored thereafter but with no additional rainfall, suggesting the rain had ceased at or before 1729 utc. Therefore, the total duration of the event was probably between 100 and 120min – but no more than 2 h – and is likely to have produced around 180.5mm when taking into account the earlier shower. According to radar data for r max (Figure 7), the storm reached a peak rain rate of 210mmh−1 at 1610 utc (perhaps contaminated somewhat by small hail), with rain rates exceeding 100mmh−1 noted on 11 separate scans in total, of which 9 were consecutive suggesting that rainfall of at least this intensity was maintained over a 45min period (assuming no weakening between each 5min scan). It is worth noting that the AWS had recorded more rainfall prior to the power cut than either r max or r near at the same time, suggesting that the composite reflectivity product had under-estimated the intensity of the rain. The highest 1-h accumulation estimated by r max is 108.8mm, occurring between 1545 utc and 1645 utc (and 93.4mm for a whole hour ending at 1700 utc). However, if a simple scaling factor is applied such that the event total radar estimate is scaled to the observed Snowdon gauge value, then the highest 1-h accumulation could in theory have been closer to ~134mm. Both of these potential values exceed the current UK 1-h rainfall record of 92mm at Maidenhead on 12 July 1901 3 (Meteorological Office, 1926; Ross et al., 2009). Other notable short-duration events in the UK, over similar durations and based on autographic records, include 90mm in 55min at Eskdalemuir, Dumfries-shire, on 26 June 1953 (Meteorological Office, 1953) and 86mm in 60min at Lesnewth, Cornwall on 16 August 2004 (Burt, 2005). ‘Eye’ observations, but with good supporting evidence, also indicated falls of 110mm in 58min at Wheatley, Oxfordshire on 9 June 1910 (Webb, 2011) and 97mm in 45min at Orra Begg, Northern Ireland on 1 August 1980 (Woodley, 1981). It is plausible that the rainfall at Brettenham also challenges the UK 2-h record; the 193mm at Walshaw Dean Lodge (West Yorkshire) on 19 May 1989 (Acreman, 1989; Collinge et al., 1990) is disputed by some (as detailed in, for example, Collier (1991)), and so the next highest accepted 2-h rainfall record is currently 155mm in 109min at Hewenden Reservoir (also West Yorkshire) on 11 June 1956 (Collinge et al., 1992). Even accounting for a small reduction to the event total for the preceding shower, the rainfall at Brettenham would also exceed this 2-h record for the amount of rain and possibly also the duration in which it fell. Estimates from satellite data indicate that cloud top temperatures were as low as −52°C, which would suggest cloud heights peaked at ~34 000ft (~10 400m). Assuming the ~1100Jkg−1 convective available potential energy (CAPE) estimated in Figure 2 was evenly distributed through the troposphere and air parcels started from the surface at rest, a mean vertical velocity of 11.7ms−1 is calculated when taking into account entrainment of surrounding air and effects of precipitation loading by halving the theoretical maximum updraft speed at the equilibrium level (w max = √(2 × CAPE)). Therefore, an air parcel from the boundary layer would in theory reach the tropopause in just under 14min, resulting in a rain rate of very approximately 140mmh−1 assuming all precipitable water vapour (PWV) available in the column (estimated at 33mm in Figure 2) was condensed out and fell to the ground as precipitation. In reality, this rain rate may be closer to 70mmh−1 since typically 50% or more of precipitation tends to evaporate into the surrounding air as it descends, especially when the air is rather dry. This event is remarkably similar to 16 August 2020 in south Norfolk, when a multicell thunderstorm cluster produced as much as 240mm of rain and set a new UK August daily rainfall record (Holley et al., 2021). Both events occurred in an environment with relatively high PWV, slow storm motion and enhanced low-level convergence aiding continuous backbuilding. Synoptic surface winds were northeasterly in both events within a slack surface pressure pattern, and while winds aloft were slightly different both days involved a mid/upper-level low that had originated from the Bay of Biscay. Aside from subtle differences between the various indices listed in this paper and Holley et al. (2021), the main difference between the two events is that the Brettenham storm was of much shorter duration than south Norfolk in 2020, but still produced impressive rainfall accumulations nonetheless. Clusters of heavy showers and thunderstorms affected portions of East Anglia, central southern and southeast England on 25 July 2021, producing local flash flooding in places. Of particular interest was a quasi-stationary multicell thunderstorm that affected parts of mid-Suffolk, especially the village of Brettenham where 181.3mm of rain was recorded by a storage rain gauge that was formerly part of the Environment Agency registered network, most of which fell in less than 2 h. The thunderstorms developed along a marked CZ where a northeasterly synoptic surface wind met an east or southeasterly onshore wind, likely enhanced by a sea breeze. Light steering winds aloft, combined with backbuilding and high tropospheric moisture, resulted in prolonged torrential downpours and flash flooding in the village. The rainfall observed, especially when considering the relatively short duration, is unprecedented in the local area and potentially challenges some UK records. The authors would like to thank colleagues at Weatherquest for their comments and access to various resources, Neil Klotz (Environment Agency) and local residents and farmers, in particular Roger Bere, for providing rainfall measurements and information on impacts in the area. We are also very grateful to Weather Underground for enabling use of home AWS data in our mesoanalysis, and more especially the owners of the private AWS. Finally, special thanks are offered to the anonymous reviewers for their useful feedback on the manuscript.

Where Ordinary Activities Lead to War

Shah Alam, a city near the Klang River, is susceptible to flooding due to its urban transformation from oil palm plantations. Heavy rainfall, tropical storms, and flash floods have caused widespread flooding, landslides, power outages, disrupted water treatment plants, and port operations. The Malaysian government has faced criticism for its delayed response and apathy towards the disaster. This study aims to provide a unique perspective on flash flood problems and solutions in Shah Alam, focusing on the opinions and ideas of existing multi-stakeholder groups, particularly at the local level. Primary data was gathered through informal interviews and secondary data was obtained through a thorough examination of books, journals, research papers, and government reports. The thematic analysis of both primary and secondary data using Taguette tools found that the problem of disaster management in Shah Alam is related to inadequate proactive leadership roles of the local authority for coordination and collaboration among relevant agencies, as well as inadequate communication and data support systems. This leads to weaknesses in collaboration among agencies, making it difficult to carry out large-scale projects. Additionally, weaknesses in communication and information sharing are evident, where critical information such as weather forecasts are needed by rescue agencies to better prepare for disasters. Thus, the presence of NADMA in local level and a centralised data centre by the local authority with full cooperation from government agencies is important to improve the disaster management including flood risks.

Rainfall-induced disaster is long duration disasters that have a probability of power failure that makes disaster worst due to lack of communication. Flash Flood, long duration flood, and landslides are few examples of them. In this case, Communication between victims is a challenging job. This paper presents an idea to overcome these kinds of situations. Different tools have been developed Alert about disaster including in flood disaster but during the flood, power failure makes these impossible to work for a long duration while flood is long duration disaster. This paper introducing an Alert Network designed by different technologies including WSN, MANET, and IoT. This architecture will be able to communicate in absence of any fixed infrastructure as well as it will be able to communicate through the social media if available. For supporting the architecture, the use of the screen with a solar cell as well as OLED with a screen to enhance the battery life of a Smartphone is discussed.

The old building has a vital value in modern life, because these old buildings possess a social cultural significance, having historical value and meeting the aesthetic and contemporary lifestyle ingredients. Besides, these historical buildings are also very important in education and in our life, which is also a growing awareness to people. The study is to investigate the building of a compound traditional pastry shop. This building, which is constructed during the period of Japanese occupation, was Dr. Miyahara Takekuma’s hospital, called “MIYAHARA Hospital” or “MIYAHARA Ophthalmology Clinic.” At that time, Dr. Miyahara Takekuma had previously studied in Germany before he served as a doctor of a public hospital in Taiwan. Then, in 1926 he resigned and started to run his own business, and founded MIYAHARA ophthalmology clinic in 1930. In addition, Dr. Miyahara Takekuma also served as a councilor in Taichung Prefecture before. After the surrender of the Empire of Japan in 1945, all the Japanese were withdrawn from Taiwan, including Dr. Miyahara Takekuma. His mansion then became the Governor of Taichung’s formal residence. As for MIYAHARA ophthalmology clinic, it was confiscated by the government, and changed into the Health Division of Civil Affairs Bureau of Taichung City, and then changed again into the Public Health Center of Taichung City in the following year, which was the original site of the Public Health Bureau of Taichung City Government. Then, Since the Public Health Bureau moved out here, the MIYAHARA ophthalmology clinic has been damaged by nature disasters over the years and has become a dangerous building. Fortunately, the signboard “The Public Health Center of Taichung City” was still preserved well. After reconstruction, this rickety historical building has been inserted perfectly with glass windows which create a communion between the old and new, that is nowadays’ DAWNCAKE flagship shop--- MIYAHARA ophthalmology clinic, opened by a pastry dealer. The shop named “MIYAHARA ophthalmology clinic” is opened by the well-known DAWNCAKE shop in Taichung. It has many chain stores such as Travelers Shop, Native Pineapple shop, Mother Nature Shop, Monastery Shop etc. And the one, MIYAHARA ophthalmology clinic, near Taichung train station is built as DAWNCAKE’s flagship shop. In fact, the building had already been bought before the government completely took it over. And owing to the owner of the building has a basic understanding on historic monuments, history and culture, and has great interest in literary language. Therefore, basing on these, the owner put a lot of efforts in the renovation of the interior decoration of the historical building. He wants to preserve the main structure of the old building and renovate with modern architecture to create a unique architectural style. Consequently, combining with the innovative idea of the building owner, the history at that time and the new architecture from the western, it brings an interesting atmosphere to customers when their eye are first caught by the seeming old and seeming new space. And without pressing a great deal of the posters, the building decorated with the wall painting instead to show the changes of the time and history in order to give the historical building a brand-new life.

An impervious surface generates high storm water runoff volumes which overwhelm drainage systems caused frequent urban flash flood episodes. Green roof is a highly efficient green infrastructure in reducing urban storm water runoff. Studies have agreed on most important green roof characteristics that contributed in reducing storm water runoff are substrates depth, type of vegetation, and roof slope. However, to date, no study has drawn a connection between these performances and cost that contributes to the performance. This is important as cost is the utmost barrier for green roof implementation. Therefore, this study motivates to assess cost and benefit of substrates depth, type of vegetation, and roof slope for intensive and extensive green roof. Roof slope is the utmost cost-efficient green roof characteristics for storm water runoff reduction at 1: 1.5 and 1: 2.2 for extensive and intensive green roof. Type of vegetation contributes to the highest cost for both green roofs. Substrate depth is only cost-efficient for intensive green roof at ratio 1: 1.4. This study is significant in encouraging building owner and investor to implement green roof by providing substantial evidence on it efficiencies and cost that contributes to the effectiveness. This will eventually promote the growth of green building within building sectors.

Climate change will bring new challenges to IT managers and business continuity and disaster recovery (BC/DR) planners in years to come. Experts - including researchers from the Met Office and Newcastle University, and Edward Hanna, professor of climate change at the University of Sheffield - suggest climate change could lead to an increase in severe weather phenomena such as flash flooding and 'weather bombs', intense storms with low centre pressure triggered by jet stream changes.1-3 This severe weather can in turn lead to blackouts.Severe weather events can lead to power outages, floods and other disasters that can severely disrupt your business. And climate change may increase outbreaks of disease, which could leave you short-staffed.Responses to these threats need to be flexible and deep. Using the right resources and enlisting the assistance of strategic vendors can alleviate some of the stress during an unexpected interruption and help you improve your ability to get back to business quickly when disaster strikes, explains Matt Kingswood of IT Specialists.

<p>In South America, southern parts of Brazil, Paraguay and northeast Argentina are regions particularly prone to high impact weather (intensive lightning activity, high precipitation, hail, flash floods and occasional tornadoes), mostly associated with extra-tropical cyclones, frontal systems and Mesoscale Convective Systems. In the south of Brazil, agricultural industry and electrical power generation are the main economic activities. This region is responsible for 35% of all hydro-power energy production in the country, with long transmission lines to the main consumer regions, which are severely affected by these extreme weather conditions. Intense precipitation events are a common cause of electricity outages in southern Brazil, which ranks as one of the regions in Brazil with the highest annual lightning incidence, as well. Accurate precipitation forecasts can mitigate this kind of problem. Despite improvements in the precipitation estimates and forecasts, some difficulties remain to increase the accuracy, mainly related to the temporal and spatial location of the events. Although several options are available, it is difficult to identify which deterministic forecast is the best or the most reliable forecast. Probabilistic products from large ensemble prediction systems provide a guide to forecasters on how confident they should be about the deterministic forecast, and one approach is using post processing methods such as machine learning (ML), which has been used to identify patterns in historical data to correct for systematic ensemble biases.</p><p>In this paper, we present a study, in which we used 20 members from the Global Ensemble Forecast System (GEFS) and 50 members from European Centre for Medium-Range Weather Forecasts (ECMWF)  during 2019-2021,  for seven daily precipitation thresholds: 0-1.0mm, 1.0mm-15mm, 15mm-40mm, 40mm-55mm, 55mm-105mm, 105mm-155mm and over 155mm. A ML algorithm was developed for each day, up to 15 days of forecasts, and several skill scores were calculated, for these daily precipitation thresholds. Initially, to select the best members of the ensembles, a gradient boosting algorithm was applied, in order to improve the skill of the model and reduce processing time. After preprocessing the data, a random forest classifier was used to train the model. Based on hyperparameter sensitivity tests, the random forest required 500 trees, a maximum tree depth of 12 levels, at least 20 samples per leaf node, and the minimization of entropy for splits. In order to evaluate the models, we used a cross-validation on a limited data sample. The procedure has a single parameter that refers to the number of groups that a given data sample is to be split into. In our work we created a twenty-six fold cross validation with 30 days per fold to verify the forecasts. The results obtained by the RF were evaluated through estimated value versus observed value. For the forecast range, we found values above 75% for the precision metrics in the first 3 days, and around 68% in the next days. The recall was also around 80% throughout the entire forecast range,  with promising results to apply this technique operationally, which is our intent in the near future. </p>

The potential to create extreme events is an inherent property of complex systems. Since our highly structured society is particularly sensitive to extreme events such as larger power failures in electric networks, stock market crashes, epedemics caused by new types of viruses, flash floods by summer storms, their potential predictability is of highest relevance. In this contribution we assume a physical point of view and concentrate on a specific phenomenon, namely on turbulent wind gusts. We show how a rather general model, namely a continuous state Markov chain, can be employed for data driven predictions of strong wind gusts. A Markov chain can represent arbitrary finite memory processes within the range of deterministic chaotic systems on the one extreme to uncorrelated white noise on the other, but its particular strenght lies in between: Nonlinear stochastic processes. Clearly, the modelling of the turbulent flow at a single site by a Markov chain is an approximation, whose accuracy will be discussed in the talk. From a statistical point of view, the focus on the prediction of extreme events implies the usage of unconventional cost junctions, such that our predictor does not neccessarily perform well on “normal” bulk events, but has a surprisingly good performance on extreme events.

THE TWO FEATURE articles presented in this issue of Frontiers of Health Services Management speak to the challenges of Hurricane Katrina. The Tulane experience lists a multitude of problems, solutions, and successes, whereas the article by Drs. Rodriguez and Aguirre speaks to the impact on the infrastructure following the hurricane. In the federal report, "The Federal Response to Hurricane Katrina," the White House (2006) has labeled Katrina as "the most destructive natural disaster in U.S. history." Dr. E. L. Quarantelli (2006) might call Katrina a catastrophe. Regardless of what one calls the event, Hurricane Katrina has shown that the challenges leading up to and following a disaster/catastrophe will overwhelm everyone. People must understand that they cannot wait for a government, any government, to help them. We must be prepared to help ourselves.

Masuda city suffered heavy damage from flooding after the concentrated heavy rain on 23, July, 1983. In the two weeks following the disaster 302 patients, 207 males and 95 females, aging from first decade to eighth decade, visited our outpatients clinic. About half of them had injuries to their feet from glass fragments and nails suffered when they were seeking refugee or removing wood and mud. We were afraid of an outbreak of an outbreak of tetanus, but fortunately neither tetanus nor dysentery broke out. Power failure restricted the use of elevators and roentogenographic examinations. We ran short of gauze, drapes and gowns, Medical staff also suffered and some of them were absent from the hospital. It was rumored that tetanus and dysentery were going around. We keenly felt the necessity of a wireless-telephone between the hospital and administrative organs an temporary facilities which accommodated injured patients who had lost their houses. Typhoons and concentrated heavy rain will occur again in the future. We must seriously take up the problems of preparing for a possible flood.