Search Results
You are looking at 1 - 4 of 4 items for
- Author or Editor: Scott P. Swerdlin x
- Refine by Access: All Content x
An operational mesoscale model–based forecasting system has been developed for use by U.S. Army Test and Evaluation Command meteorologists in their support of test-range operations. This paper reports on the adaptation of this system to permit its rapid deployment in support of a variety of civilian and military emergency-response applications. The innovation that allows for this rapid deployment is an intuitive graphical user interface that permits a non-expert to quickly configure the model for a new application, and launch the forecast system to produce operational products without further intervention. The graphical interface is Web based and can be run on a wireless laptop or a personal digital assistant in the field. The instructions for configuring the modeling system are transmitted to a compute engine [generally a personal computer (PC) cluster], and forecast products are placed on a Web site that can be accessed by emergency responders or other forecast users. This system has been used operationally for predicting the potential transport and dispersion of hazardous material during the 2002 Winter Olympics in Salt Lake City, Utah, and during military operations in Afghanistan. It has also been used operationally to satisfy the rapidly evolving needs of wildfire managers. Continued use of the modeling system by non-experts will allow developers to refine the graphical interface and make the model and the interface more fault tolerant with respect to the decisions of model users.
An operational mesoscale model–based forecasting system has been developed for use by U.S. Army Test and Evaluation Command meteorologists in their support of test-range operations. This paper reports on the adaptation of this system to permit its rapid deployment in support of a variety of civilian and military emergency-response applications. The innovation that allows for this rapid deployment is an intuitive graphical user interface that permits a non-expert to quickly configure the model for a new application, and launch the forecast system to produce operational products without further intervention. The graphical interface is Web based and can be run on a wireless laptop or a personal digital assistant in the field. The instructions for configuring the modeling system are transmitted to a compute engine [generally a personal computer (PC) cluster], and forecast products are placed on a Web site that can be accessed by emergency responders or other forecast users. This system has been used operationally for predicting the potential transport and dispersion of hazardous material during the 2002 Winter Olympics in Salt Lake City, Utah, and during military operations in Afghanistan. It has also been used operationally to satisfy the rapidly evolving needs of wildfire managers. Continued use of the modeling system by non-experts will allow developers to refine the graphical interface and make the model and the interface more fault tolerant with respect to the decisions of model users.
Abstract
The use of a mesoscale model–based four-dimensional data assimilation (FDDA) system for generating mesoscale climatographies is demonstrated. This dynamical downscaling method utilizes the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), wherein Newtonian relaxation terms in the prognostic equations continually nudge the model solution toward surface and upper-air observations. When applied to a mesoscale climatography, the system is called Climate-FDDA (CFDDA). Here, the CFDDA system is used for downscaling eastern Mediterranean climatographies for January and July. The downscaling method performance is verified by using independent observations of monthly rainfall, Quick Scatterometer (QuikSCAT) ocean-surface winds, gauge rainfall, and hourly winds from near-coastal towers. The focus is on the CFDDA system’s ability to represent the frequency distributions of atmospheric states in addition to time means. The verification of the monthly rainfall climatography shows that CFDDA captures most of the observed spatial and interannual variability, although the model tends to underestimate rainfall amounts over the sea. The frequency distributions of daily rainfall are also accurately diagnosed for various regions of the Levant, except that very light rainfall days and heavy precipitation amounts are overestimated over Lebanon. The verification of the CFDDA against QuikSCAT ocean winds illustrates an excellent general correspondence between observed and modeled winds, although the CFDDA speeds are slightly lower than those observed. Over land, CFDDA- and the ECMWF-derived wind climatographies when compared with mast observations show similar errors related to their inability to properly represent the local orography and coastline. However, the diurnal variability of the winds is better estimated by CFDDA because of its higher horizontal resolution.
Abstract
The use of a mesoscale model–based four-dimensional data assimilation (FDDA) system for generating mesoscale climatographies is demonstrated. This dynamical downscaling method utilizes the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), wherein Newtonian relaxation terms in the prognostic equations continually nudge the model solution toward surface and upper-air observations. When applied to a mesoscale climatography, the system is called Climate-FDDA (CFDDA). Here, the CFDDA system is used for downscaling eastern Mediterranean climatographies for January and July. The downscaling method performance is verified by using independent observations of monthly rainfall, Quick Scatterometer (QuikSCAT) ocean-surface winds, gauge rainfall, and hourly winds from near-coastal towers. The focus is on the CFDDA system’s ability to represent the frequency distributions of atmospheric states in addition to time means. The verification of the monthly rainfall climatography shows that CFDDA captures most of the observed spatial and interannual variability, although the model tends to underestimate rainfall amounts over the sea. The frequency distributions of daily rainfall are also accurately diagnosed for various regions of the Levant, except that very light rainfall days and heavy precipitation amounts are overestimated over Lebanon. The verification of the CFDDA against QuikSCAT ocean winds illustrates an excellent general correspondence between observed and modeled winds, although the CFDDA speeds are slightly lower than those observed. Over land, CFDDA- and the ECMWF-derived wind climatographies when compared with mast observations show similar errors related to their inability to properly represent the local orography and coastline. However, the diurnal variability of the winds is better estimated by CFDDA because of its higher horizontal resolution.
Abstract
This study builds upon previous efforts to document the performance of the U.S. Army Test and Evaluation Command’s Four-Dimensional Weather Modeling System using conventional metrics. Winds, temperature, and specific humidity were verified for almost 15 000 forecasts at five U.S. Army test ranges using near-surface mesonet data. The primary objective was to use conventional metrics to characterize the degree to which forecast accuracy varies from range to range, within the diurnal cycle, with elapsed forecast time, and among the seasons. It was found that there are large interrange differences in forecast error, with larger errors typically associated with the ranges located near complex orography. Similarly, significant variations in accuracy were noted for different times in the diurnal cycle, but the diurnal dependency varied greatly among the ranges. Factor of 2 differences in accuracy were also found across the seasons.
Abstract
This study builds upon previous efforts to document the performance of the U.S. Army Test and Evaluation Command’s Four-Dimensional Weather Modeling System using conventional metrics. Winds, temperature, and specific humidity were verified for almost 15 000 forecasts at five U.S. Army test ranges using near-surface mesonet data. The primary objective was to use conventional metrics to characterize the degree to which forecast accuracy varies from range to range, within the diurnal cycle, with elapsed forecast time, and among the seasons. It was found that there are large interrange differences in forecast error, with larger errors typically associated with the ranges located near complex orography. Similarly, significant variations in accuracy were noted for different times in the diurnal cycle, but the diurnal dependency varied greatly among the ranges. Factor of 2 differences in accuracy were also found across the seasons.
Abstract
Given the rapid increase in the use of operational mesoscale models to satisfy different specialized needs, it is important for the community to share ideas and solutions for meeting the many associated challenges that encompass science, technology, education, and training. As a contribution toward this objective, this paper begins a series that reports on the characteristics and performance of an operational mesogamma-scale weather analysis and forecasting system that has been developed for use by the U.S. Army Test and Evaluation Command. During the more than five years that this four-dimensional weather system has been in use at seven U.S. Army test ranges, valuable experience has been gained about the production and effective use of high-resolution model products for satisfying a variety of needs. This paper serves as a foundation for the rest of the papers in the series by describing the operational requirements for the system, the data assimilation and forecasting system characteristics, and the forecaster training that is required for the finescale products to be used effectively.
Abstract
Given the rapid increase in the use of operational mesoscale models to satisfy different specialized needs, it is important for the community to share ideas and solutions for meeting the many associated challenges that encompass science, technology, education, and training. As a contribution toward this objective, this paper begins a series that reports on the characteristics and performance of an operational mesogamma-scale weather analysis and forecasting system that has been developed for use by the U.S. Army Test and Evaluation Command. During the more than five years that this four-dimensional weather system has been in use at seven U.S. Army test ranges, valuable experience has been gained about the production and effective use of high-resolution model products for satisfying a variety of needs. This paper serves as a foundation for the rest of the papers in the series by describing the operational requirements for the system, the data assimilation and forecasting system characteristics, and the forecaster training that is required for the finescale products to be used effectively.
