LAGRANGIAN ERRORS: FEATURE RELATIVE VERIFICATION

A method of forecast verification is introduced that examines the errors in forecasts relative to a specific weather feature. The method is demonstrated on cyclones in and around North America during the winter season of 2013-2014. A simple method for identifying cyclone centers is employed based on the location of relative maximums in relative vorticity and relative minimums in height at the 850 hPa level. A grid is created, centered on the cyclone, onto which the forecast and observed values are interpolated. Errors are created from the difference between the forecast and observation. The errors from each cyclone are collected to make an error series and the mean error for each grid point is found. In this way, errors are analyzed following the feature(s), in a Lagrangian sense, as opposed to a more traditional method which allows weather features to be created in or pass through a fixed geographical region, in an Eulerian sense. Significance testing is performed in order to determine if the mean error field is field significant

TWO-STEP PRODUCTION OF 1,3-BUTADIENE FROM ETHANOL

A plant utilizing a two-step reaction process, which takes a 95% ethanol stream (by mass) and produces a 98% 1,3-butadiene stream, was designed for this project. The production goal for this plant was 200,000 tonnes of butadiene with the main motivation behind the project being the recent rise in butadiene prices. The process first passes ethanol through a catalytic dehydrogenation reactor to convert ethanol to acetaldehyde and hydrogen. A kinetic model was used to determine the reaction rates and operating conditions of the reactor. The acetaldehyde intermediate is further reacted with ethanol in a catalytic reactor to form butadiene. A hydrogen byproduct stream is also generated in this design and is purified for sale. This report provides a design and economic analysis for the production of butadiene on the Gulf Coast. Process flow sheets, energy and utility requirements, and equipment summaries are provided and analyzed. Process profitability is sensitive to the cost of both ethanol and butadiene. It is shown that the plant is very profitable for its expected 15-year lifespan with an expected internal rate of return of 40%, return on investment of 34%, and net present value of $172,000,000 (for a discount rate of 15$3.00/gallon. A combination of increased ethanol price and decreased butadiene price will also cause the plant to be unprofitable. Therefore, plant construction is only recommended given an acceptable price of ethanol and butadiene

Assessing the effect of weight and weight loss in obese persons with type 2 diabetes

The objective of this study was to assess specific areas of life in which obesity affects individuals with type 2 diabetes mellitus (T2DM), and changes that obese persons with T2DM experience with weight loss of varying degrees. Thirty in-depth interviews were conducted in persons identified as: age ≥40 years, diagnosed with T2DM for ≥2 years, on oral antihyperglycemic medications >3 months, BMI 30–35 kg/m2, having attempted to lose weight in the last 2 years. Participants (60% female, mean age 53 years, 53% Caucasian, mean BMI 32.2 kg/m2) agreed that 5% weight loss, while not reflective of an ultimate goal, would be meaningful and important; benefits were expected to accrue in physical functioning, self-confidence, blood glucose levels, and motivation to keep losing weight. Participants reported the greatest effect of weight loss on energy, physical activity, mobility, pain, and clothes/appearance. Participants reported weight affecting mood, with feelings of depression and frustration most commonly described. This research indicates that weight loss is likely to affect health-related quality of life in obese individuals with T2DM. Given the purported weight loss benefits of many emerging diabetic medications, it will be important to include measures of weight-related quality of life in future clinical trials of these agents

Assimilation of Dual-Polarimetric Radar Observations with WRF GSI

Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, more accurate estimate of liquid and solid cloud and precipitation can be provided. The upgrade of the traditional NWS WSR-88D radar to include dual-pol capabilities will soon be completed for the entire NEXRAD network. Therefore, the use of dual-pol radar network will have a broad impact in both research and operational communities. The assimilation of dual-pol radar data is especially challenging as few guidelines have been provided by previous research. It is our goal to examine how to best use dual-pol radar data to improve forecast of severe storm and forecast initialization. In recent years, the Development Testbed Center (DTC) has released the community Gridpoint Statistical Interpolation (GSI) DA system for the Weather Research and Forecasting (WRF) model. The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this study explores regional assimilation of the dual-pol radar variables from the WSR-88D radars for real case storms. Our presentation will highlight our recent effort on incorporating the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms, with a significant focus being on an improved representation of hydrometeor fields. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to dual-pol variables. Beyond the dual-pol variable assimilation procedure developing within a GSI framework, highresolution (1 km) WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. Further details of the methodology of data assimilation, the impact of different dual-pol variables, the influence on precipitation forecast will be presented at the conference