The alcohol problem in the Richmond metropolitan area and management\u27s role in combating it

The purpose of the thesis 1 s to show something of the seriousness of the alcohol problem as it is effecting business and industrial organisations. At the same time I have tried to develop information which will be useful to management, especially in the Richmond area, in combating the problem. Much of the information obtained has been on a confidential basis which has been necessary because of the nature of the problem. I wish to thank all of those who have taken the time to furnish information. I particularly wish to thank Dr. Thomas S. Berry, Dr. Milton A. Maxwell, and Mr. Kenneth Lee for valued advice and encouragement. Many others have contributed and include heads of business organizations and their medical staff members, statisticians, medical directors end others connected with medical centers. I wish to acknowledge the invaluable help of Dr. Ebbe Hoff and Mrs. George Ossman, members of the team at the Medical College Clinic for Alcoholics. My thanks also goes to those in the community who are working so valiently to lessen the alcohol problem in the City of Richmond and Counties of Henrico and Chesterfield. Many of these people have offered suggestions and have allowed me to attend meetings and discussions held within the areas mentioned. And lastly to AA who are doing an outstanding job in Richmond. My heartfelt thanks and appreciation to a wonderful organization and a fine Richmond group

The diurnal nature of future extreme precipitation intensification

Short‐duration, high‐impact precipitation events in the extratropics are invariably convective in nature, typically occur during the summer, and are projected to intensify under climate change. The occurrence of convective precipitation is strongly regulated by the diurnal convective cycle, peaking in the late afternoon. Here we perform very high resolution (convection‐permitting) regional climate model simulations to study the scaling of extreme precipitation under climate change across the diurnal cycle. We show that the future intensification of extreme precipitation has a strong diurnal signal and that intraday scaling far in excess of overall scaling, and indeed thermodynamic expectations, is possible. We additionally show that, under a strong climate change scenario, the probability maximum for the occurrence of heavy to extreme precipitation may shift from late afternoon to the overnight/morning period. We further identify the thermodynamic and dynamic mechanisms which modify future extreme environments, explaining both the future scaling's diurnal signal and departure from thermodynamic expectations

High-resolution regional modelling of changing extreme precipitation

Extreme precipitation is of interest because of the often dramatic effects that it can have on society and the environment. In this thesis, high-resolution regional modelling experiments are used to study how climatic changes affect regional precipitation extremes, with a focus on the Black Sea and Mediterranean (BSM) region. The impact of model resolution, in particular at convection-permitting (CP) scales, on the representation of changes in extreme precipitation is also examined. The added value of high-resolution regional models, at up to CP resolution, for reproducing observed extreme precipitation events is established in chapter 3. In chapter 4, the July 2012 precipitation extreme in the Black Sea town of Krymsk is taken as a showcase example for studying the impact of sea surface temperature (SST) increase on convective extremes, and simulated under a range of SST forcings. The crucial role of recent SST increase in the intensity of the event is revealed. A highly nonlinear precipitation response to incremental SST increase suggests that the Black Sea may have exceeded a regional SST threshold. The physical mechanism identified indicates that BSM coastal regions may face abrupt amplifications of convective precipitation under continued SST increase, and illustrates the limitations of thermodynamical bounds for estimating the temperature scaling of convective extremes. The added value of CP models for simulating changes in convective extremes is explored by comparing how the intensity of the Krymsk event responds to increasing SSTs in simulations with explicit and parametrized convection. Compared at the same spatial scale, the strongly nonlinear extreme precipitation response to SST increase in the CP simulations is not evident when convection is parametrized. The physical mechanisms behind the different responses are the focus of chapter 5

A classification algorithm for selective dynamical downscaling of precipitation extremes

High-resolution climate data O(1km) at the catchment scale can be of great value to both hydrological modellers and end users, in particular for the study of extreme precipitation. While dynamical downscaling with convection-permitting models is a valuable approach for producing quality high-resolution O(1km) data, its added value can often not be realized due to the prohibitive computational expense. Here we present a novel and flexible classification algorithm for discriminating between days with an elevated potential for extreme precipitation over a catchment and days without, so that dynamical downscaling to convection-permitting resolution can be selectively performed on high-risk days only, drastically reducing total computational expense compared to continuous simulations; the classification method can be applied to climate model data or reanalyses. Using observed precipitation and the corresponding synoptic-scale circulation patterns from reanalysis, characteristic extremal circulation patterns are identified for the catchment via a clustering algorithm. These extremal patterns serve as references against which days can be classified as potentially extreme, subject to additional tests of relevant meteorological predictors in the vicinity of the catchment. Applying the classification algorithm to reanalysis, the set of potential extreme days (PEDs) contains well below 10% of all days, though it includes essentially all extreme days; applying the algorithm to reanalysis-driven regional climate simulations over Europe (12km resolution) shows similar performance, and the subsequently dynamically downscaled simulations (2km resolution) well reproduce the observed precipitation statistics of the PEDs from the training period. Additional tests on continuous 12km resolution historical and future (RCP8.5) climate simulations, downscaled in 2km resolution time slices, show the algorithm again reducing the number of days to simulate by over 90% and performing consistently across climate regimes. The downscaling framework we propose represents a computationally inexpensive means of producing high-resolution climate data, focused on extreme precipitation, at the catchment scale, while still retaining the advantages of convection-permitting dynamical downscaling

Subhourly rainfall in a convection-permitting model

Convection-permitting models (CPMs)—the newest generation of high-resolution climate models—have been shown to greatly improve the representation of subdaily and hourly precipitation, in particular for extreme rainfall. Intense precipitation events, however, often occur on subhourly timescales. The distribution of subhourly precipitation, extreme or otherwise, during a rain event can furthermore have important knock-on effects on hydrological processes. Little is known about how well CPMs represent precipitation at the subhourly timescale, compared to the hourly. Here we perform multi-decadal CPM simulations centred over Catalonia and, comparing with a high temporal-resolution gauge network, find that the CPM simulates subhourly precipitation at least as well as hourly precipitation is simulated. While the CPM inherits a dry bias found in its parent model, across a range of diagnostics and aggregation times (5, 15, 30 and 60 min) we find no consistent evidence that the CPM precipitation bias worsens with shortening temporal aggregation. We furthermore show that the CPM excels in its representation of subhourly extremes, extending previous findings at the hourly timescale. Our findings support the use of CPMs for modelling subhourly rainfall and add confidence to CPM-based climate projections of future changes in subhourly precipitation, particularly for extremes

Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)

Lagrangian analysis of convective precipitation involves identifying convective cells (“objects”) and tracking them through space and time. The Lagrangian approach helps to gain insight into the physical properties and impacts of convective cells and, in particular, how these may respond to climate change. Lagrangian analysis requires both a fixed definition of what constitutes a convective object and a reliable tracking algorithm. Whether the climate-change signals of various object properties are sensitive to the choice of tracking algorithm or to how a convective object is defined has received little attention. Here we perform ensemble pseudo-global-warming experiments at a convection-permitting resolution to test this question. Using two conceptually different tracking algorithms, Lagrangian analysis is systematically repeated with different thresholds for defining a convective object, namely minimum values for object area, intensity and lifetime. It is found that the threshold criteria for identifying a convective object can have a strong and statistically significant impact on the magnitude of the climate-change signal, for all analysed object properties. The tracking method, meanwhile, has no impact on the climate-change signal as long as the precipitation data have a sufficiently high temporal resolution: in general, the lower the minimum permitted object size is, the higher the precipitation data's temporal resolution must be. For the case considered in our study, these insights reveal that irrespective of the tracking method, projected changes in the characteristics of convective rainfall vary considerably between cells of differing intensity, area and lifetime

Evidence for added value of convection-permitting models for studying changes in extreme precipitation

Climate model resolution can affect both the climate change signal and present-day representation of extreme precipitation. The need to parametrize convective processes raises questions about how well the response to warming of convective precipitation extremes is captured in such models. In particular, coastal precipitation extremes can be sensitive to sea surface temperature (SST) increase. Taking a recent coastal precipitation extreme as a showcase example, we explore the added value of convection-permitting models by comparing the response of the extreme precipitation to a wide range of SST forcings in an ensemble of regional climate model simulations using parametrized and explicit convection. Compared at the same spatial scale, we find that the increased local intensities of vertical motion and precipitation in the convection-permitting simulations play a crucial role in shaping a strongly nonlinear extreme precipitation response to SST increase, which is not evident when convection is parametrized. In the convection-permitting simulations, SST increase causes precipitation intensity to increase only until a threshold is reached, beyond which further SST increase does not enhance the precipitation. This flattened response results from an improved representation of convective downdrafts and near-surface cooling, which damp the further intensification of precipitation by stabilizing the lower troposphere locally and also create cold-pools that cause subsequent convection to be triggered at sea, rather than by the coastal orography. These features are not well represented in the parametrized convection simulations, resulting in precipitation intensity having a much more linear response to increasing SST

Present and future diurnal hourly precipitation in 0.11° EURO-CORDEX models and at convection-permitting resolution

The diurnal cycle of precipitation (DCP) is a core mode of precipitation variability in regions and seasons where the dominant precipitation type is convective. The occurrence of extreme precipitation is often closely linked to the DCP. Future changes in extreme precipitation may furthermore, in certain regions, exhibit a strong diurnal signal. Here we investigate the present and future diurnal cycle of hourly precipitation in the state-of-the-art 0.11°C EURO-CORDEX (EC-11) ensemble and in a convection-permitting model (CPM), with a focus on extremes. For the present climate, long-standing timing and frequency biases in the DCP found in lower-resolution models persist in the EC-11 ensemble. In the CPM, however, these biases are largely absent, particularly the diurnal distribution of extremes, which the EC-11 ensemble misrepresents. For future changes to hourly precipitation, we find clear diurnal signals in the CPM and in EC-11 models, with high regional and intra-ensemble variability. The diurnal signal typically peaks in the morning. Interestingly, the EC-11 ensemble mean shows reasonable agreement with the CPM on the diurnal signal's timing, showing that this feature is representable by models with parametrized convection. Comparison with the CPM suggests that EC-11 models greatly underestimate the amplitude of this diurnal signal. Our study highlights the advantages of CPMs for investigating future precipitation change at the diurnal scale, while also showing the EC-11 ensemble capable of detecting a diurnal signal in future precipitation change