Coupling of Mesoscale Weather Models to Business Operations Utilizing Visual Data Fusion (original) (raw)

And Implementation of a Mesoscale Numerical Weather Prediction and Visualization System

1998

Weather-sensitive business operations are primarily reactive to short-term (3 to 36 hours), local conditions (city, county, state) due to unavailability of appropriate predicted data at this temporal and spatial scale. This situation is commonplace in a number of applications including, but not limited to transportation, agriculture, energy, insurance, entertainment, construction, communications and emergency planning. Typically, what optimization that is applied to these processes to enable proactive efforts utilize either historical weather data as a predictor of trends or the results of synoptic-scale weather models. Alternatively, mesoscale (cloud-scale) numerical weather models operating at higher resolution in space and time with more detailed physics has shown "promise" for many years as a potential enabler of pro-active decision making for both economic and societal value. They may offer greater precision and accuracy within a limited geographic region for problems...

Implementation of Mesoscale Numerical Weather Prediction for Weather-Sensitive Business Operations

1998

For many applications, expected local weather conditions during the next day or two are critical factors in planning operations and making effective decisions. Typically, what optimization that is applied to these processes to enable proactive efforts utilize either historical weather data as a predictor of trends or the results of synoptic-scale weather models. Alternatively, mesos-cale numerical weather models operating at higher resolution in space and time with more detailed physics may offer greater precision and accuracy within a limited geographic region for problems with short-term weather sensitivity (e.g., Mass et al, 2002; Gall and Shapiro, 2000). Such forecasts can be used for competitive advantage or to improve operational efficiency and safety. To evaluate this hypothesis, a prototype system, dubbed "Deep Thunder", has been implemented for the New York City area.

The integration of meteorological satellite imagery and numerical dynamical forecast models

Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences, 1988

Imagery of clouds, water vapour, and thermal structure as achieved in real-time from geostationary satellites can play an important role in the dynamic verification and reinitialization of numerical weather-prediction models used for short-range prediction of intense weather. By overlaying hourly interval model forecast fields over satellite imagery, the validity of the evolving forecast can be subjectively assessed and phase and amplitude errors can be diagnosed in a dynamic manner. Videographic interactive computer systems designed for the purpose should enable improved numerical weather forecasts to be made through the dynamic use of satellite imagery. This approach is demonstrated by using the Man—Computer Interactive Data Access System (McIDAS) at the University of Wisconsin for a case of the development of a cyclone over the east coast of the U.S.A.

The Mesoscale Forecasting Process: Applying the Next Generation Mesoscale Forecast

The weather forecast effort has progressed a long way past its embryonic stage of the barotropic forecast. Both computer power and our knowledge of atmospheric processes have increased substantially over the years, allowing for the classification of many weather phenomena into scales, including the global/hemispheric scale, the synoptic scale, the mesoscale, and the microscale. These scales represent the cascade of energy that occurs in the atmosphere, with hemispheric features providing energy for the synoptic scale, synoptic features providing energy for the mesoscale, and so forth. Many observation and modeling tools exist to aid the forecaster along the way, including RAOB soundings, satellite imagery, wind profiler data, radar data, lightning data, and model data, and all are useful in mesoscale forecasting. When performing a mesoscale forecast, however, it is prudent to use a mesoscale model, such as the Air Force Weather Agency's (AFWA) Weather Research and Forecasting (WRF) model.

Whither the Weather Analysis and Forecasting Process?

Weather and Forecasting, 2003

An argument is made that if human forecasters are to continue to maintain a skill advantage over steadily improving model and guidance forecasts, then ways have to be found to prevent the deterioration of forecaster skills through disuse. The argument is extended to suggest that the absence of real-time, high quality mesoscale surface analyses is a significant roadblock to forecaster ability to detect, track, diagnose, and predict important mesoscale circulation features associated with a rich variety of weather of interest to the general public.

Web-Based Dissemination and Visualization of Mesoscale Weather Models for Business Operations

1998

Visualization is critical to the effective analysis, dissemination and assessment of data generated by numerical weather prediction. In that regard, consider two aspects of our previous work. First is the need to develop appropriate mapping of user goals to the design of pictorial content by considering both the underlying data characteristics and the perception of the visualization (Treinish, 2001). The second is the adaptation of these ideas from workstation or PC/game-class threedimensional graphics systems with sufficient bandwidth for timely access to the model data to remote access via the world-wide-web (Treinish, 2002b). In this situation, the limitation in bandwidth is the primary bottleneck since desktop systems can support interactive visualization of typical model data.