Intensity-dependent parameterization of elevation effects in precipitation analysis

Elevation effects in long-term (monthly to inter-annual) precipitation data have been widely studied and are taken into account in the regionalization of point-like precipitation amounts by using methods like external drift kriging and cokriging. On the daily or hourly time scale, precipitation-elevation gradients are more variable, and difficult to parameterize. For example, application of the annual relative precipitation-elevation gradient to each 12-h sub-period reproduces the annual total, but at the cost of a large root-mean-square error. If the precipitation-elevation gradient is parameterized as a function of precipitation rate, the error can be substantially reduced. It is shown that the form of the parameterization suggested by the observations conforms to what one would expect based on the physics of the orographic precipitation process (the seeder-feeder mechanism). At low precipitation rates, orographic precipitation is "conversion-limited", thus increasing roughly linearly with precipitation rate. At higher rates, orographic precipitation becomes "condensation-limited" thus leading to an additive rather than multiplicative orographic precipitation enhancement. Also it is found that for large elevation differences it becomes increasingly important to take into account those events where the mountain station receives precipitation but the valley station remains dry

Combining 2-m temperature nowcasting and short range ensemble forecasting

During recent years, numerical ensemble prediction systems have become an important tool for estimating the uncertainties of dynamical and physical processes as represented in numerical weather models. The latest generation of limited area ensemble prediction systems (LAM-EPSs) allows for probabilistic forecasts at high resolution in both space and time. However, these systems still suffer from systematic deficiencies. Especially for nowcasting (0–6 h) applications the ensemble spread is smaller than the actual forecast error. This paper tries to generate probabilistic short range 2-m temperature forecasts by combining a state-of-the-art nowcasting method and a limited area ensemble system, and compares the results with statistical methods. The Integrated Nowcasting Through Comprehensive Analysis (INCA) system, which has been in operation at the Central Institute for Meteorology and Geodynamics (ZAMG) since 2006 (Haiden et al., 2011), provides short range deterministic forecasts at high temporal (15 min–60 min) and spatial (1 km) resolution. An INCA Ensemble (INCA-EPS) of 2-m temperature forecasts is constructed by applying a dynamical approach, a statistical approach, and a combined dynamic-statistical method. The dynamical method takes uncertainty information (i.e. ensemble variance) from the operational limited area ensemble system ALADIN-LAEF (Aire Limitée Adaptation Dynamique Développement InterNational Limited Area Ensemble Forecasting) which is running operationally at ZAMG (Wang et al., 2011). The purely statistical method assumes a well-calibrated spread-skill relation and applies ensemble spread according to the skill of the INCA forecast of the most recent past. The combined dynamic-statistical approach adapts the ensemble variance gained from ALADIN-LAEF with non-homogeneous Gaussian regression (NGR) which yields a statistical mbox{correction} of the first and second moment (mean bias and dispersion) for Gaussian distributed continuous variables. Validation results indicate that all three methods produce sharp and reliable probabilistic 2-m temperature forecasts. However, the statistical and combined dynamic-statistical methods slightly outperform the pure dynamical approach, mainly due to the under-dispersive behavior of ALADIN-LAEF outside the nowcasting range. The training length does not have a pronounced impact on forecast skill, but a spread re-scaling improves the forecast skill substantially. Refinements of the statistical methods yield a slight further improvement

Regional Variation in Physician Adoption of Antipsychotics: Impact on US Medicare expenditures

Background—Regional variation in US Medicare prescription drug spending is driven by higher prescribing of costly brand-name drugs in some regions. This variation likely arises from differences in the speed of diffusion of newly-approved medications. Second-generation antipsychotics were widely adopted for treatment of severe mental illness and for several off-label uses. Rapid diffusion of new psychiatric drugs likely increases drug spending but its relationship to non-drug spending is unclear. The impact of antipsychotic diffusion on drug and medical spending is of great interest to public payers like Medicare, which finance a majority of mental health spending in the U.S.National Institute of Mental Health (U.S.) (R01 MH093359

Pollutant dispersion in a developing valley cold-air pool

Pollutants are trapped and accumulate within cold-air pools, thereby affecting air quality. A numerical model is used to quantify the role of cold-air-pooling processes in the dispersion of air pollution in a developing cold-air pool within an alpine valley under decoupled stable conditions. Results indicate that the negatively buoyant downslope flows transport and mix pollutants into the valley to depths that depend on the temperature deficit of the flow and the ambient temperature structure inside the valley. Along the slopes, pollutants are generally entrained above the cold-air pool and detrained within the cold-air pool, largely above the ground-based inversion layer. The ability of the cold-air pool to dilute pollutants is quantified. The analysis shows that the downslope flows fill the valley with air from above, which is then largely trapped within the cold-air pool, and that dilution depends on where the pollutants are emitted with respect to the positions of the top of the ground-based inversion layer and cold-air pool, and on the slope wind speeds. Over the lower part of the slopes, the cold-air-pool-averaged concentrations are proportional to the slope wind speeds where the pollutants are emitted, and diminish as the cold-air pool deepens. Pollutants emitted within the ground-based inversion layer are largely trapped there. Pollutants emitted farther up the slopes detrain within the cold-air pool above the ground-based inversion layer, although some fraction, increasing with distance from the top of the slopes, penetrates into the ground-based inversion layer.Peer reviewe

Global predictability of temperature extremes

Extreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the world’s population is not yet protected by such systems, including many data-scarce but also highly vulnerable regions. In this study, we assess at a global level where such systems have the potential to be effective at reducing risk from temperature extremes, characterizing (1) long-term average occurrence of heatwaves and coldwaves, (2) seasonality of these extremes, and (3) short-term predictability of these extreme events three to ten days in advance. Using both the NOAA and ECMWF weather forecast models, we develop global maps indicating a first approximation of the locations that are likely to benefit from the development of seasonal preparedness plans and/or short-term early warning systems for extreme temperature. The extratropics generally show both short-term skill as well as strong seasonality; in the tropics, most locations do also demonstrate one or both. In fact, almost 5 billion people live in regions that have seasonality and predictability of heatwaves and/or coldwaves. Climate adaptation investments in these regions can take advantage of seasonality and predictability to reduce risks to vulnerable populations

Changes in Drug Utilization during a Gap in Insurance Coverage: An Examination of the Medicare Part D Coverage Gap

Jennifer Polinski and colleagues estimated the effect of the "coverage gap" during which US Medicare beneficiaries are fully responsible for drug costs and found that the gap was associated with a doubling in discontinuing essential medications

City of Ivanhoe Comprehensive Plan 2018-2038

the City of Ivanhoe is located in Tyler County, which is in southeastern Texas near the Louisiana border. The land is gently rolling, with an elevation ranging from 100 to 400 feet above sea level. Texas Target Communities developed this document in partnership with the City of Ivanhoe. In the summer of 2016, Tyler County and the City of Ivanhoe collaborated with Texas Target Communities to assess current community conditions and explore future development strategies. The project aimed to enhance community-wide discussion through a public participatory process, resulting in developing a comprehensive plan to help guide the future growth of the County and City. A representative task force of community members engaged in a participatory planning process, including visioning, goal setting, alternative scenario exploration, and strategies for implementation. Using courses on campus, TAMU urban planning students were exposed to the planning process and explored innovative ideas. The result of this collaboration is this document, which provides strategies for the community’s growth utilizing the natural resource and the assets of the City.The Ivanhoe Comprehensive Plan 2017-2037 provides guidance for the future development of the city. In the summer of 2016, Tyler County and the City of Ivanhoe collaborated with Texas Target Communities to assess current community conditions and explore future development strategies., which resulted in this comprehensive plan document.Texas Target Communitie

Überlegungen zur rolle des übersetzers

Раздел 4. Актуальные вопросы литературоведения, переводоведения и практики перевод

Improved nowcasting of precipitation based on convective analysis fields

The high-resolution analysis and nowcasting system INCA (<b>I</b>ntegrated <b>N</b>owcasting through <b>C</b>omprehensive <b>A</b>nalysis) developed at the Austrian national weather service provides three-dimensional fields of temperature, humidity, and wind on an hourly basis, and two-dimensional fields of precipitation rate in 15 min intervals. The system operates on a horizontal resolution of 1 km and a vertical resolution of 100&ndash;200 m. It combines surface station data, remote sensing data (radar, satellite), forecast fields of the numerical weather prediction model ALADIN, and high-resolution topographic data. An important application of the INCA system is nowcasting of convective precipitation. Based on fine-scale temperature, humidity, and wind analyses a number of convective analysis fields are routinely generated. These fields include convective boundary layer (CBL) flow convergence and specific humidity, lifted condensation level (LCL), convective available potential energy (CAPE), convective inhibition (CIN), and various convective stability indices. Based on the verification of areal precipitation nowcasts it is shown that the pure translational forecast of convective cells can be improved by using a decision algorithm which is based on a subset of the above fields, combined with satellite products