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The finite-difference solution to a balance equation model is discussed in terms of the solution to a coupled, linear elliptic system with variable coefficients (both in space and time). By suitably arranging the unknowns in their...
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The finite-difference solution to a balance equation model is discussed in terms of the solution to a coupled, linear elliptic system with variable coefficients (both in space and time). By suitably arranging the unknowns in their finite-difference analogs, this coupled system is in fact no more than just one large linear algebraic system. Thus for a two-level model, the problem of solving a system of four coupled equations becomes that of solving a single algebraic system of (4JK) unknowns.
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A three-step objective analysis technique for initializing Fleet Numerical Weather Central's Primitive Equation Forecast Model in the 63x63 Northern Hemisphere Polar Stereographic Grid is described. In the first step, an analysis ...
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A three-step objective analysis technique for initializing Fleet Numerical Weather Central's Primitive Equation Forecast Model in the 63x63 Northern Hemisphere Polar Stereographic Grid is described. In the first step, an analysis is performed at 10 mandatory pressure levels. In the second step, the mandatory pressure level heights are transformed into sigma coordinates by using a mass structure conversion procedure which describes the physical properties of an air column through static stability parameters over defined pressure increments. In the third step, raw data are converted to sigma coordinates by an identical procedure and reanalyzed in sigma coordinates by using the transformed pressure level analysis as initial guess. The applied numerical analysis method is based on the pattern-conserving analysis technique FIB (Field by Information Blending) which allows wind and height reports to be treated as independent information sets and to be analyzed simultaneously.
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The long-term goal of this project is to developing a seamless weather and climate prediction system that has capability to predict accurately both weather phenomena such as tropical cyclones (TC) and other extreme weather events ...
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The long-term goal of this project is to developing a seamless weather and climate prediction system that has capability to predict accurately both weather phenomena such as tropical cyclones (TC) and other extreme weather events and longer climate-scale phenomena such as the Madden-Julian Oscillation (MJO) and the El Nino-Southern Oscillation (ENSO). Organized moist convections in the tropical atmosphere have their origins at space scale of less than 10 km, and they play a key role in the initiation and maintenance of mesoscale weather events such as super cloud clusters and large-scale phenomena such as MJO. The Navy is in urgent need to develop such a global high resolution model that has a proper dynamic core and physics packages and is capable of representing realistically convection and clouds across a wide range of spatial and temporal scales and suitable for prediction of extreme events in regional and global scales.
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This Technical Note describes the Air Weather Service Primitive-Equation (AWSPE) models in use at the Air Force Global Weather Central (AFGWC). There are 6-layer and 7-layer AWSPE versions. We present a brief history of the models...
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This Technical Note describes the Air Weather Service Primitive-Equation (AWSPE) models in use at the Air Force Global Weather Central (AFGWC). There are 6-layer and 7-layer AWSPE versions. We present a brief history of the models at AFGWC as well as their forerunners at the National Meteorological Center. We then present the technical details of both models. Parts I and II describe the 6-layer and 7-layer versions, respectively.
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The data from twenty years of the NCEP numerical weather model have been used to calculate the IMF hydrostatic mapping function for several sites distributed in latitude from -66 deg to +78 deg. Comparison of heights estimated wit...
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The data from twenty years of the NCEP numerical weather model have been used to calculate the IMF hydrostatic mapping function for several sites distributed in latitude from -66 deg to +78 deg. Comparison of heights estimated with the NMF hydrostatic map ...
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This purpose of this research project is to provide a current benefit-cost assessment for weather information in winter road maintenance. To this end, the research team first summarized the weather information resources used by tr...
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This purpose of this research project is to provide a current benefit-cost assessment for weather information in winter road maintenance. To this end, the research team first summarized the weather information resources used by transportation agency personnel in making winter maintenance decisions and investigated how weather information was used to support winter maintenance operations, through extensive literature reviews and surveys to winter maintenance professionals and the meteorological community. Following this, the research team developed a model for winter maintenance costs. A methodology of artificial neural network and sensitivity analysis was proposed and applied to three case studies to analyze the benefits and costs associated with the use of weather information. The benefitcost analyses showed that the use of weather information could bring more benefits than costs. Moreover, it was found that winter maintenance costs could be reduced by improving the accuracy of weather information and/or increasing the use of weather information. Finally, this study identified secondary benefits of deploying and using road weather information systems. These research results should help transportation agencies to guide and direct future investment in weather information services and technologies.
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Comparison of 500 mb progs from the 6-layer primitive equation baroclinic and the 3-level baroclinic models during the test period indicated a slight superiority of the former in the average in terms of S1 score. The 6-layer model...
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Comparison of 500 mb progs from the 6-layer primitive equation baroclinic and the 3-level baroclinic models during the test period indicated a slight superiority of the former in the average in terms of S1 score. The 6-layer model was definitely superior in two-thirds of the cases during the test period with an improvement of nearly 11 percentage points in skill over persistence. This in itself may not have been sufficient to warrant a substitution for the 3-level model but the potentialities of the new model for better forecasts at other levels, and derivatives of these forecasts, were great. This was confirmed by the very definitely superior performance of the 6-layer model surface prog over the comparable Reed progs made with the 3-level model and the very good showing of the 36 hour numerical progs as compared to the independently produced subjective 30 hour A and FD progs during the test period. The new model is still in a shakedown period; changes in the program are being introduced from time to time. More definitive studies of the performance will be made during the more active fall and winter seasons. For one, subjective examination of the 500 mb progs appeared to indicate that short wave troughs were moved too slowly by the model. The introduction of the 'desmoothing' operator was expected to correct this fault, if it is one, but no evidence is yet available to confirm this. (Author)
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The Generalized Exponential Markov (GEM) model uses the local standard airways observation (SAO) to predict hour-by-hour the following elements: temperature, pressure, dew point depression, first and second cloud-layer height and ...
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The Generalized Exponential Markov (GEM) model uses the local standard airways observation (SAO) to predict hour-by-hour the following elements: temperature, pressure, dew point depression, first and second cloud-layer height and amount, ceiling, total cloud amount, visibility, wind, and present weather conditions. GEM is superior to persistence at all projections for all elements in a large independent sample. A minute-by-minute GEM forecasting system utilizing the Automated Weather Observation System (AWOS) is under development.
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