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Fireworks and other pyrotechnics are acknowledged as sources of disturbance to wildlife, with evidence that many species react adversely to their sight and sound at discharge. However, how firework releases impact wildlife within a city landscape is poorly understood. Here, we explore the effect of fireworks on urban birds using an L-band staring radar (90-degree sector out to a 5 km range) to capture bird activity derived from flight tracks (i.e. 3D visualisation of individual flying birds built from radar detections) within the city of Birmingham, UK. Comparing the tracks between baseline periods with no fireworks and periods where fireworks are commonly discharged using a null model indicated that birds flew at higher elevations during firework periods (standardised effect sizes of 17.11, 26.54 and 5.83, for Diwali, Bonfire Night, and New Year's Eve, respectively). Birds also flew in more significant numbers (standardised effect sizes of 23.41, 7.98 and 7.19 for Diwali, Bonfire Night, and New Year's Eve, respectively). Therefore, bird activity was elevated during firework events at a time of night when many would otherwise be roosting. Such disturbance may have implications for avian biology since large public firework events occur at colder times of the year in the UK when birds have elevated thermoregulatory costs. [ABSTRACT FROM AUTHOR]

For the physical model testing of wave energy converters (WECs) in the wave basin, it is necessary to test the models in a small number of sea states. Previously, the H – T binning method was widely used to determine the sea states that are representative of an ocean area. However, it omitted much useful information such as the wave directionality. In this paper, a novel method, the K -means clustering technique is used in combination with High Frequency (HF) radar measured data from Wave Hub, UK. The results show that K -means clustering method better preserves the characteristics of the ocean area than the binning method. Furthermore, the impact of different regrouping methods on assessing the annual energy output of the model is investigated, by applying the K -means clustering method to a 1:25 two-body hinged raft WEC. It is found that although non-linear performance can be clearly observed in the model both physically and numerically. Due to the fact that most sea states from Wave Hub are out of the non-linearity range of the model, the non-linear effect on the overall performance of the WEC model in this ocean area is limited. It allows the annual energy output to be accurately predicted by using only a small number of representative sea states (defined as K) ≤15, based on K -means clustering method. • K -means method selected representative sea states tested on a physical WEC model. • K -means method is effective in selecting the sea states for WEC model testing. • Representative sea states can obtain accurate annual energy output estimation. • Non-linearity of WEC tested had limited influence on annual energy output estimation. [ABSTRACT FROM AUTHOR]

Accurate precipitation estimation with weather radars is essential for hydrological and meteorological applications. The differential reflectivity (ZDR) is a crucial weather radar measurement that helps to improve quantitative precipitation estimates using polarimetric weather radars. However, a system bias between the horizontal and vertical channels generated by the radar produces an offset in ZDR. Existing methods to calibrate ZDR measurements rely on the intrinsic values of the ZDR of natural targets (e.g. drizzle or dry snow) collected at high elevation angles (e.g. higher than 40 ∘ or even at 90 ∘), in which ZDR values close to 0 dB are expected. However, not all weather radar systems can scan at such high elevation angles or point the antenna vertically to collect precipitation measurements passing overhead. Therefore, there is a need to develop new methods to calibrate ZDR measurements using lower-elevation scans. In this work, we present and analyse a novel method for correcting and monitoring the ZDR offset using quasi-vertical profiles computed from scans collected at 9 ∘ elevations. The method is applied to radar data collected through 1 year of precipitation events by two operational C-band polarimetric weather radars in the UK. The proposed method shows a relative error of 0.1 dB when evaluated against the traditional approach based on ZDR measurements collected at 90 ∘ elevations. Additionally, the method is independently assessed using disdrometers located near the radar sites. The results showed a reasonable agreement between disdrometer-derived and radar-calibrated ZDR measurements. [ABSTRACT FROM AUTHOR]

Object-based radar rainfall nowcasting is a widely used technique for convective storm prediction. Currently, most existing object-based nowcasting methods primarily focus on predicting cell movements, neglecting the temporal evolution of cell properties such as size, shape, and intensity. Incorporating this evolution is critical for improving predictability in convective storms. While previous studies have used three-dimensional (3D) radar observations to capture vertical changes during convective cell formation, these efforts often analyse or reconstruct specific convective events. Integrating 3D radar information into operational object-based radar rainfall nowcasting remains an open challenge. This research addresses this challenge using deep learning (DL) techniques. More specifically, a DL-based prediction model is developed, which uses 2D and 3D cells' properties retrieved from 3D radar reflectivity data at the current time and across the past 15 min to predict the evolution of these properties over the next 15 min. This model could eventually be integrated into existing object-based nowcasting models. A total of 4708 cell lifecycles, extracted from high-resolution (5-min, 1-km, 24 levels at 0.5 km intervals) 3D radar data across the UK, are used to train the model, and a total of 1177 lifecycles are used for testing. The proposed model is shown to predict the evolution of single-core convective cells effectively, including changes in 2D projected geometry and mean 2D and 3D reflectivity. In particular, by incorporating information on the vertical evolution of convective cores, the prediction errors of mean reflectivity (in both 2D and 3D) can be reduced by approximately 50% at 15-min forecast lead time, as compared to a persistence forecast. Keywords: radar, tracking, convective cell, nowcasting, 3D, deep learning, lstm. • A deep-learning model that predicts single-core convective cell evolution. • Convective core altitudes aid cell mean reflectivity prediction. • Prediction errors of cell reflectivity are reduced by 50% at 15-min lead time. [ABSTRACT FROM AUTHOR]

High-resolution model simulations and radar observations are used to investigate the onset of vortex-genesis in a tornadic narrow cold-frontal rain band (NCFR). The timing and location of vortex-genesis was strongly constrained by a developing frontal wave, which tracked northeast across the United Kingdom and Ireland on 17 October 2011. In the simulations, vortices occurred preferentially during the early stages of wave development and just down-front of the wave centre, where large increases in vertical vorticity occurred in concert with decreases in the cross-frontal confluence. Vortex-genesis ceased as the frontal wave matured, due to the onset of frontal fracture. Two distinct scales of vortex-genesis are documented: primary vortex-genesis on themeso-γ-scale, and secondary vortex-genesis on the miso-scale. We show that horizontal shearing instability is the most likely vortex-genesis mechanism, consistent with previous theoretical work on the stability of vertical vortex strips in the presence of horizontal stretching deformation. Secondary vortices occurred along the braid regions between primary vortices where the shear zone became particularly narrow and intense. In the model, these vortices developed extremely rapidly (from small perturbations to maximum vertical vorticity in 5-15 min) and the strongest exhibited near-surface vertical vorticitymaxima approaching 10-1 s-1. Vortices of both scales were associated with characteristic local perturbations in the NCFR andwe show, by comparisonwith radar reflectivity data, that primary and secondary vortices were likely present in the real NCFR. Tornado reports were associated with small NCFR perturbations like those associated with the secondary vortices in the model simulations. Analysis of the sub-structure of individual simulated vortices suggests that tornado-genesis ismost likely within a region of intense near-surface vertical vorticity stretching at the north or northwest flank of the secondary vortices. [ABSTRACT FROM AUTHOR]

Subsurface geonergy can induce ground motion and seismicity, however a scarcity of observations usually obscures the mechanisms underpinning such behaviour. Here, we analyse Interferometric Synthetic Aperture Radar (InSAR) data from ERS, ENVISAT and Sentinel-1 satellites for the period 1995–2017 and interpret ground deformation in the area of the planned Cheshire UK GeoEnergy Observatory ahead of facility contruction. Ground motion is dominated by the compaction of tidal flat deposits overlying two paleo-valleys, trending NNW–SSE. The western paleo-valley experienced faster subsidence rates in the period 1995–2007, whereas the eastern paleo-valley subsided faster in the period 2016–2017. The research highlights how baseline assessment can help differentiate natural variation from any anthropogenic effects associated with the growth of new subsurface technologies. [ABSTRACT FROM AUTHOR]

In this work, we present a new quantitative precipitation estimation (QPE) quality-control (QC) algorithm for the U.K. weather radar network. The real-time adaptive algorithm uses a neural network (NN) to select data from the lowest useable elevation scan to optimize the combined performance of two other radar data correction algorithms: ground-clutter mitigation [using Clutter Environment Analysis using Adaptive Processing (CLEAN-AP)] and vertical profile of reflectivity (VPR) correction. The NN is trained using 3D tiles of observed uncontaminated weather signals that are systematically combined with ground-clutter signals collected under dry weather conditions. This approach provides a way to simulate radar signals with a wide range of clutter contamination conditions and with realistic spatial structures while providing the uncontaminated "truth" with respect to which the performance of the QC algorithm can be measured. An evaluation of QPE products obtained with the proposed QC algorithm demonstrates superior performance as compared to those obtained with the QC algorithm currently used in operations. Similar improvements are also illustrated using radar observations from two periods of prolonged precipitation, showing a better balance between overestimation errors from using clutter-contaminated low-elevation radar data and VPR-induced errors from using high-elevation radar data. [ABSTRACT FROM AUTHOR]

The understanding of large‐scale rainfall microphysical characteristics plays a significant role in meteorology, hydrology and natural hazards managements. Traditional instruments for estimating raindrop size distribution (DSD), including disdrometers and ground dual‐polarization radars, are available only in limited areas. However, the development of space‐based radars and mesoscale numerical weather prediction models would allow for DSD estimation on a large scale. This study investigated the performance of the weather research and forecasting (WRF) model and the global precipitation measurement mission (GPM) dual‐frequency precipitation radar for DSD retrieval under different conditions. The DSD parameters (Dm and Nw), rain rate (R), rainfall kinetic energy (KE) and radar reflectivity (Z) were estimated in Chilbolton, United Kingdom, by using long‐term disdrometer observations for validation. The rainfall kinetic energy–rain rate (KE–R) and radar reflectivity–rain rate (Z–R) relationships were explored using a disdrometer, the WRF model and GPM. It was found that the DSD parameter distribution trends of the three approaches are similar although the WRF model has larger Dm and smaller Nw values. In terms of the rainfall microphysical relationship, GPM performs better when both Ku‐ and Ka‐band precipitation radars (KuPR and KaPR) observe precipitation simultaneously (R > 0.5 mm h−1), while the WRF model shows high accuracy in light rain (R < 0.5 mm h−1). The fusion of GPM and WRF model is recommended for the improved understanding of rainfall microphysical characteristics in ungauged areas. [ABSTRACT FROM AUTHOR]

Operational forecasting centres increasingly rely on convection‐permitting NWP simulations to assist in their forecasting of convective events. The evaluation of upgrades in the underlying NWP modelling system normally happens through routine verification using traditional metrics on two‐dimensional fields, such as gridded rainfall data. Object‐ and process‐based evaluation can identify specific physical mechanisms for model improvement, but such evaluation procedures normally require targeted and expensive field campaigns. Here, we explore the potential use of the UK operational radar network observations and its derived 3D composite product for evaluating the representation of convective storms in the Met Office Unified Model. A comparison of the 1 × 1 × 0.5 km 3D radar composites against observations made with the research‐grade radar at Chilbolton in the southern UK indicates that the 3D radar composite data can reliably be used to evaluate the morphology of convective storms. The 3D radar composite data are subsequently used to evaluate the development of convective storms in the Met Office Unified Model. Such analysis was previously unavailable due to a lack of 3D radar data of high temporal frequency. The operational nature of the UK radar data makes these 3D composites a valuable resource for future studies of the initiation, growth, development, and organisation of convective storms over the UK. [ABSTRACT FROM AUTHOR]

This work presents studies of naturally enhanced ion acoustic lines and the correlation they have with the electron temperature fluctuations on the eve and after the NEIAL events. The methodology used in this work is based on the analysis of European Incoherent Scatter Scientific Association raw data, archived at Rutherford- Appleton Laboratory (Harwell Oxford Campus) in the United Kingdom. The EISCAT Svalbard radar raw data were analyzed using two specialized programs: the Real Time Graph and the Grand Unified Incoherent Scatter Data Analysis Program, version 8.6. Our findings suggest a strong correlation between the NEIALs phenomenon and plasma parameter fluctuations such as the electron temperature in the Earth ionosphere. Our findings show that the plasma electron temperature progressively increases before the event, and progressively decreases after the event. [ABSTRACT FROM AUTHOR]

There is an urgent need for high-quality and high-spatial-resolution hourly precipitation products around the globe, including the UK. Although hourly precipitation products exist for the UK, these either contain large errors, or are insufficient in spatial resolution. An efficient way to solve this is to develop a merged precipitation product that combines the information and benefits from multiple data sources, improving both the spatial resolution and accuracy of hourly precipitation estimates over the UK. In this study, we develop a UK high-resolution gauge–radar–satellite merged hourly precipitation analysis: the UKGrsHP. It covers the UK from 12.5° W to 3.5° E, 49° N–60° N, with a spatial resolution of 0.01° × 0.01° in latitude/longitude (equivalent to 1 km resolution in the mid-latitudes). An optimal interpolation (OI)–based multi-source merging scheme with compound strategy is developed and tested for producing the UKGrsHP. Three input data sources are used: gauge analysis data interpolated from 1903 quality-controlled hourly observations, the UK Nimrod radar precipitation analysis and the GSMaP global satellite precipitation analysis. Using independent tests against ~ 220 independent gauge observations on 1 year's experimental UKGrsHP, covering the period from January to December 2014, we find that the final merged data performs better than three individual precipitation analyses used as inputs. A full version of the UKGrsHP starting in April 2004 is now under production, which will have wide applications in climate services and scientific research across multiple disciplines. [ABSTRACT FROM AUTHOR]

Water is a fundamental control on the deterioration of historic stone masonry, of which wind-driven rain (WDR) is an important source in the UK. Non-destructive testing methods for moisture measurement can characterise the response of masonry to short (but intense) periods of wind-driven rain. An important part of this response is how masonry functions as a system of stone units and mortar joints, in which mortar can act as a conduit for moisture. While non-destructive techniques are common in moisture surveying of built heritage, there are no agreed best practice methods for collection, handling, and visual representation of data. This study explores the comparative advantages of microwave and radar measurements in two field experiments of exposure to short (but intense) simulated wind-driven rain exposure to demonstrate when and how they are most effectively employed. A novel method of representing data as percentiles is explored to facilitate effective communication of moisture measurements. In the case of the granite wall (e.g. with components of strongly contrasting hygric properties), microwave and radar provided similar information. The average travel time of the radar signal (from the back wall reflection) demonstrated that radar can non-destructively identify water penetration through mortar joints. In the sandstone tower, the microwave measurements were able to clearly identify four different moisture regimes as a result of different intensities of WDR exposure. The radar measurements were suited to identifying distinctions between localised moisture contents within masonry units and mortar joints, which characterised how the masonry was functioning as a holistic system. The measurements on both the granite wall and the sandstone tower demonstrated that the radar is influenced by environmental conditions which influence surface condensation and equilibrium moisture contents. Representing the measurements as percentiles improved visual representation of measurements with colour scales and minimised potential skewing of normalisation and scales from extreme values/outliers. This paper demonstrates that both microwave and radar techniques can be useful for monitoring moisture in stone masonry systems. Material characteristics of the masonry system and the objective(s) of the investigation should be considered during selection of the appropriate technique(s). [ABSTRACT FROM AUTHOR]

Cybercrime is recognized as one of the top threats to UK economic security. On a daily basis, the computer networks of businesses suffer security breaches. A less explored dimension of this problem is cybercrimes committed by insiders. This paper provides a criminological analysis of corporate insider victimization. It begins by presenting reviews of insider criminal threats and routine activities theory as applied to cybercrime. Analysis of the nationally representative Cardiff University UK Business Cybercrime Survey then informs statistical models that predict the likelihood of businesses suffering insider cyber victimization, using routine activities and guardianship measures as predictors. [ABSTRACT FROM AUTHOR]

Turbulent mixing processes are important in determining the evolution of convective clouds, and the production of convective precipitation. However, the exact nature of these impacts remains uncertain due to limited observations. Model simulations show that assumptions made in parametrizing turbulence can have a marked effect on the characteristics of simulated clouds. This leads to significant uncertainty in forecasts from convection‐permitting numerical weather prediction (NWP) models. This contribution presents a comprehensive method to retrieve turbulence using Doppler weather radar to investigate turbulence in observed clouds. This method involves isolating the turbulent component of the Doppler velocity spectrum width, expressing turbulence intensity as an eddy dissipation rate, ϵ. By applying this method throughout large datasets of observations collected over the southern United Kingdom using the (0.28° beam‐width) Chilbolton Advanced Meteorological Radar (CAMRa), statistics of convective cloud turbulence are presented. Two contrasting case days are examined: a shallow "shower" case, and a "deep convection" case, exhibiting stronger and deeper updraughts. In our observations, ϵ generally ranges from 10−3 to 10−1 m2/s3, with the largest values found within, around and above convective updraughts. Vertical profiles of ϵ suggest that turbulence is much stronger in deep convection; 95th percentile values increase with height from 0.03 to 0.1 m2/s3, compared to approximately constant values of 0.02–0.03 m2/s3 throughout the depth of shower cloud. In updraught regions on both days, the 95th percentile of ϵ has significant (p < 10−3) positive correlations with the updraught velocity, and the horizontal shear in the updraught velocity, with weaker positive correlations with updraught dimensions. The ϵ‐retrieval method presented considers a very broad range of conditions, providing a reliable framework for turbulence retrieval using high‐resolution Doppler weather radar. In applying this method across many observations, the derived turbulence statistics will form the basis for evaluating the parametrization of turbulence in NWP models. Turbulent mixing processes are important in determining the evolution of convective clouds, and the production of convective precipitation. To investigate turbulence in observed clouds, this contribution provides a comprehensive method to retrieve turbulence using Doppler weather radar. Statistics of convective cloud turbulence are presented through the analysis of retrievals (example in picture) over many observations in two contrasting case‐studies. [ABSTRACT FROM AUTHOR]

ABSTRACT Atkinson, J.; Esteves, L.S.; Williams, J.W.; McCann D.L., and Bell, P.S., 2018. The Application of X-Band Radar for Characterisation of Nearshore Dynamics on a Mixed Sand and Gravel Beach. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 281–285. Coconut Creek (Florida), ISSN 0749-0208. Remote sensing using X-band radar allows the estimation of wave parameters, near surface currents and the underlying bathymetry. This paper explores the use of radar to derive nearshore bathymetry at a complex site, at Thorpeness in Suffolk, UK. The site has a history of sporadic and focused erosion events along the beach frontage and as part of the X-Com project (X-band Radar and Evidence-Based Coastal Management Decisions) a radar system was deployed with the aim of further understanding the complex nearshore sediment processes influencing erosion. Initially, the bathymetric variation at the site is quantified through analysis of current and historic multibeam surveys. These indicate depth changes approaching 3 m. Subsequently, validation of the radar data against concurrent multibeam survey data has been undertaken. Results show that the radar derived bathymetry has a precision of ±1m at the site, with the largest errors being associated with areas of more complex bathymetry and where wave data quality was less suitable for analysis by the X-band radar bathymetry algorithms. It is concluded that although the accuracy of radar-derived bathymetry is lower than traditional multibeam survey, the low cost for high temporal coverage can be utilised for long-term monitoring of coastal sites where a cost-effective means of quantifying large-scale bathymetric changes is required. [ABSTRACT FROM AUTHOR]

• Precipitation data from an X-band radar in northern Scotland are assessed. • Assessment against river flow using a distributed hydrological model brings fresh insights. • Lowest usable beam elevation is the main limit on performance in this mountainous area. • Use of dual-polarisation estimators improves performance during summer months. • The X-band radar is suited for filling gaps in the existing C-band radar network. A set of Quantitative Precipitation Estimates (QPEs) from a dual-polarisation X-band radar observation campaign in a mountainous area of Northern Scotland is assessed with reference to observed river flows as well as being compared to estimates from the UK C-band radar and raingauge networks. Employing estimation methods of varying complexity, the X-band QPEs are trialled as alternative inputs to Grid-to-Grid (G2G), a distributed hydrological model, to produce simulated river flows for comparison with observations. This hydrological assessment complements and extends a previous meteorological assessment that used point raingauge data only. Precipitation estimates for two periods over the observation campaign in 2016 (March to April and June to August) are assessed. During the second period, increased incorporation of dual-polarisation variables into the radar processing chain is found to be of considerable benefit, whereas during the first period the low height of the melting layer often restricts their use. As a result of the complex topography in Northern Scotland, the Lowest Usable Elevation (LUE) of the X-band radar observations is found to be a stronger indicator of the hydrological model performance than range from the radar. For catchments with an LUE of less than 3 km, the best X-band QPE typically performs better for modelling river flow than using an estimate from the UK C-band radar network. The hydrological assessment framework used here brings fresh insights into the performance of the different QPEs, as well as providing a stimulus for targeted improvements to dual-polarisation radar-based QPEs that have wider relevance beyond the case study situation. [ABSTRACT FROM AUTHOR]

Llandegla research station. [ABSTRACT FROM AUTHOR]

Combined sewer overflows (CSOs) represent a common feature in combined urban drainage systems and are used to discharge excess water to the environment during heavy storms. To better understand the performance of CSOs, the UK water industry has installed a large number of monitoring systems that provide data for these assets. This paper presents research into the prediction of the hydraulic performance of CSOs using artificial neural networks (ANN) as an alternative to hydraulic models. Previous work has explored using an ANN model for the prediction of chamber depth using time series for depth and rain gauge data. Rainfall intensity data that can be provided by rainfall radar devices can be used to improve on this approach. Results are presented using real data from a CSO for a catchment in the North of England, UK. An ANN model trained with the pseudo-inverse rule was shown to be capable of predicting CSO depth with less than 5% error for predictions more than 1 hour ahead for unseen data. Such predictive approaches are important to the future management of combined sewer systems. [ABSTRACT FROM AUTHOR]

Abstract: A 7-year climatology of cool-season convective lines in the UK has been constructed using archived radar rainfall data. 103 lines meeting basic size, duration and intensity criteria were identified over the period September 2003 to February 2010. Of these, 87% occurred in association with frontal systems (mostly cold fronts). The remaining 13% occurred within polar-maritime air masses to the rear of frontal systems. Annual frequencies were highest over inland areas of southern and central England (5.0–7.5 events per 10,000km2, per year) and decreased markedly to the north (<1.0 events per 10,000km2, per year over north and west Scotland). Tornado and Storm Research Organisation (TORRO) tornado data revealed that 27.2% of lines produced at least one tornado. The environment of tornadic and non-tornadic lines was investigated by analysis of available observations, from which representative values of various environmental parameters were obtained. Tornadic lines were found to be associated with significantly larger pre-line surface-based CAPE, line-normal forward motion, cross-line horizontal wind veer, and cross-line temperature decrease. Furthermore, a tendency for tornadic lines to occur near the core, or under the left exit region, of mid-level jets was apparent. [Copyright &y& Elsevier]

The article reveals the radar solutions used in flood forecasting in Great Britain. The use of radar in predicting floods started through the Dee Weather Rader Project in the 1970s, which created the real-time rainfall measurement system. Various radar solutions applied in British flood forecasting operations include dual-polarisation, radar-based quantitative precipitation estimates, and short-term ensemble prediction system.

Radar has been applied to the study of insect migration for almost 40 years, but most entomological radars operate at Xband 9.4 GHz, 3.2 cm wavelength and can only detect individuals of relatively large species, such as migratory grasshoppers and noctuid moths, over all of their flight altitudes. Many insects including economically important species are much smaller than this, but development of the requisite higher power andor higher frequency radar systems to detect these species is often prohibitively expensive. In this paper, attention is focused upon the uses of some recentlydeployed meteorological sensing devices to investigate insect migratory flight behaviour, and especially its interactions with boundary layer processes. Records were examined from the verticallypointing 35 GHz ‘Copernicus’ and 94 GHz ‘Galileo’ cloud radars at Chilbolton Hampshire, England for 12 cloudless and convective occasions in summer 2003, and one of these occasions 13 July is presented in detail. Insects were frequently found at heights above aerosol particles, which represent passive tracers, indicating active insect movement. It was found that insect flight above the convective boundary layer occurs most often during the morning. The maximum radar reflectivity an indicator of aerial insect biomass was found to be positively correlated with maximum screen temperature. Copyright © 2009 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

There has been considerable investment in efforts to improve postoperative pain management, including the introduction of acute pain teams. There have also been a number of guidelines published on postoperative pain management and there is widespread agreement on how pain should be practically managed. Despite these advances, there is no apparent improvement in the number of patients experiencing moderately severe or extreme pain after surgery. This highlights significant scope for improvement in acute postoperative pain management. In January 2009, a multidisciplinary UK expert panel met to define and agree a practical framework to encourage implementation of the numerous guidelines and fundamentals of pain management at a local level. The panel recognised that to do this, there was a need to organise the information and guidelines into a simplified, accessible and easy-to-implement system based on their practical clinical experience. Given the volume of literature in this area, the Chair recommended that key international guidelines from professional bodies should be distributed and then reviewed during the meeting to form the basis of the framework. Consensus was reached by unanimous agreement of all ten participants. This report provides a framework for the key themes, including consensus recommendations based upon practical experience agreed during the meeting, with the aim of consolidating the key guidelines to provide a fundamental framework which is simple to teach and implement in all areas. Key priorities that emerged were: Responsibility, Anticipation, Discussion, Assessment and Response. This formed the basis of RADAR, a novel framework to help pain specialists educate the wider care team on understanding and prioritising the management of acute pain. Acute postoperative pain can be more effectively managed if it is prioritised and anticipated by a well-informed care team who are educated with regard to appropriate analgesic options and understand what the long-term benefits of pain relief are. The principles of RADAR provide structure to help with training and implementation of good practice, to achieve effective postoperative pain management. [ABSTRACT FROM AUTHOR]

In the context of flood management in urban areas in the UK, the Gaussian displacement spatial-temporal model (GDSTM) is used to generate a continuous rainfall field. The model makes the assumption that storms arrive according to a Poisson process in space and time, triggering another Poisson process of cell arrivals over the storm duration. These cells are displaced from the storm centre according to a normal distribution. Historic rainfall events are identified from a 3.5-year record of Met Office weather radar data from three different radars and the characteristics of the interior of each event are represented by 11 parameters. The process of event arrival is described by six additional parameters. For each month within the radar data record, a library of model parameters is obtained and used to develop simulations of 100 years of continuous, spatially varying rainfall at 5 min intervals and 1 km spatial resolution over three regions: London, Bradford and Glasgow. The objective is to use the synthetic data as input to existing urban drainage models to examine system performance. It is possible to reproduce standard statistics over the London region but the extreme values are underestimated when compared with statistics from the Flood Estimation Handbook (FEH). The mean rainfall is overestimated at the other sites but more agreement in simulating the extremes is observed when compared with the FEH. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we use an airborne synthetic aperture radar to map river flood inundation synoptically at fine spatial resolution (1.2m) along a ∼16km reach of the River Severn, west-central England. Images were obtained at four times through a large flood event between 8th and 17th November 2000 and processed using a statistical active contour algorithm to yield the flood shoreline at each time. Intersection of these data with a high vertical accuracy survey of floodplain topography obtained from airborne laser altimetry permitted the calculation of dynamic changes in inundated area, total reach storage and rates of reach dewatering. In addition, comparison of the data to gauged flow rates, the measured floodplain topography and map data giving the location of embankments and drainage channels on the floodplain yields new insights into the factors controlling the development of inundation patterns at a variety of scales. Finally, the data were used to assess the performance of a simple two-dimensional flood inundation model, LISFLOOD-FP, and allows us, for the first time, to validate the dynamic performance of the model. This process is shown to give new information into structural weaknesses of the model and suggests possible future developments, including the incorporation of a better description of floodplain hydrological processes in the hydraulic model to represent more accurately the dewatering of the floodplain. [Copyright &y& Elsevier]

• The correlations between the radar rainfall uncertainty and atmospheric fields are strong. • Three radar rainfall uncertainty adjustment schemes are proposed using a LSTM network. • The schemes can decrease the radar–gauge rainfall discrepancy by 22.52%, averagely. The unstable performance of radar rainfall measurement hinders its application in hydrology. Radar rainfall uncertainties induced by atmospheric conditions as raindrops fall from the radar sampling altitude to the ground are critical to radar-based quantitative precipitation estimation. However, these have rarely been considered in previous radar rainfall correction procedures. This study first demonstrates that the correlations between the radar–gauge rainfall discrepancy (RGD) and atmospheric fields are strong. A systematic radar-rainfall adjustment method is then proposed to decrease the discrepancies originating from changes in atmospheric conditions using a long short-term memory (LSTM) network. Three RGD adjustment models were established using a mass-variation scheme, a wind-drift scheme, and a combined mass-variation and wind-drift scheme, based on long-term (2013–2017) data covering most of the United Kingdom. The evaluation results demonstrate that all of the designed models performed well from overall, single-site, and event perspectives. Overall, the combined model, which exhibited the best performance, decreased the root-mean-square error between the rainfall levels measured by radar and gauges by 23.84%, increased Pearson's correlation coefficient from 0.23 to 0.53, and improved the critical success index of the radar rainfall estimation from 0.56 to 0.92. The results indicate that the performances of the proposed models improved with an increase in average relative humidity or wind speed, which demonstrates that they can correct rainfall under high levels of relative humidity and wind speed. This study establishes a highly capable and comprehensive adjustment framework for radar rainfall estimation uncertainty induced by atmospheric conditions, which is essential for achieving high-quality radar products. [ABSTRACT FROM AUTHOR]

Single cell storms in the United Kingdom can produce lightning, despite apparently only having developed to towering cumulus rather than cumulonimbus. Such marginal thunderstorms still present severe weather hazards but are difficult to identify and predict and therefore provide a warning. Observations from the Met Office radar mosaic and ATDNet (Arrival Time Difference Network) show that these single cell storms demonstrate a characteristic increase in the area of high reflectivity storm core during the 15 min prior to the first lightning. By using the Met Office Unified Model to investigate reflectivity development in modelled storms, a microphysical explanation for the observed reflectivity increase is identified. During a rapid reflectivity increase, the updraft area at the melting layer, the peak updraft velocity and the storm graupel mass increase. The three quantities examined are linked to each other and to the generation of charge within the storm. The production of graupel is promoted by the increase in updraft area and charge separation is enhanced by the faster peak updraft velocity. This explains some of the physical differences between single cell storms that produce lightning and apparently similar storm systems which do not. It also provides a new basis with which to predict lightning hazard for marginal storms. Single cell storms in the United Kingdom can produce lightning, despite apparently only having developed to towering cumulus rather than cumulonimbus. Observations show that these single cell storms demonstrate an increase in the area of high reflectivity storm core during the 15 min prior to the first lightning. During a reflectivity increase, the updraft area at the melting layer, the peak updraft velocity and the storm graupel mass increase. [ABSTRACT FROM AUTHOR]

This work is part of the EU-funded FloodCitiSense project, the aim of which is to develop an urban pluvial flood forecasting and warning service for and by the citizens. The specific focus of this work is to characterise convective storm features over one of the project pilot cities – Birmingham (UK) – and in turn to provide useful 'local' knowledge that can contribute to the development of the pluvial flood forecasting service. The proposed work comprises two stages: 1) development of a regional convective rain cell database, and 2) characterisation of storm cells' features in relation to the pilot. In the initial development of the database, individual convective rain cells and the traces between any two successive cells were extracted from the high-resolution UK Met Office (Nimrod) radar rainfall archive for the period of 2005-2017 over a 500 × 500 km2 area centred at Birmingham city. These cells and traces were identified using a new object-based convective storm cell tracking algorithm developed by Muñoz et al. (2018). Incorporating an optical flow-based rain-field tracking and a multi-threshold object identification techniques, this new algorithm enables the accurate isolation and tracking of convective rain cells from high-resolution radar reflectivity data. The extracted rain cells and traces were then stored in an open-source database, called TimescaleDB (http://www.timescale.com/). In the second stage, the specific properties of the identified cells and traces and their relationship to the pilot city were extracted from the database for further analyses. These include characterising statistical features of rain cells' intensities, extents, lifespans and their inter-relationships, and mapping the locations of rain cells, traces and given properties over the pilot city. Preliminary results of rain cell and trace mapping enable us to locate the 'hotspots' that are prone to the initiation and maturing of convective cells. In addition, the mapping of the traces suggests the existence of certain storm 'corridors' in the southern part of Birmingham city. This provides valuable 'local' knowledge to the development of urban pluvial flood forecasting and warning services. [ABSTRACT FROM AUTHOR]

Presents a letter to the editor of the April 1987 issue of the 'Bulletin of the Atomic Scientists,' commenting on correspondent Jeff Smith's reference to U.S. president Ronald Reagan's comparison of the Star Wars military policy with Great Britain's development of radar just in time for World War II.