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- Author or Editor: Robert R. Hoffman x
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Abstract
Advanced Meteorological Processing (AMP) systems will provide a workstation environment to support the activities of operational forecasters and research meteorologists. AMP system research and development projects are underway at laboratories of the National Weather Service, the U.S. Air Force, and a number of universities and private corporations. AMP systems will integrate artificial intelligence techniques with forecasting procedures, and will support the interpretation and integration of data from new remote sensing satellites and new ground-based radars. This article illustrates human factors research aimed at generating specifications for prototype AMP systems. A task analysis of forecasting deliberations and structured interviews with research meteorologists lead to a number of recommendations about the design of AMP systems, and to some ideas about needed research on graphics displays and the reasoning of expert meteorologists.
Abstract
Advanced Meteorological Processing (AMP) systems will provide a workstation environment to support the activities of operational forecasters and research meteorologists. AMP system research and development projects are underway at laboratories of the National Weather Service, the U.S. Air Force, and a number of universities and private corporations. AMP systems will integrate artificial intelligence techniques with forecasting procedures, and will support the interpretation and integration of data from new remote sensing satellites and new ground-based radars. This article illustrates human factors research aimed at generating specifications for prototype AMP systems. A task analysis of forecasting deliberations and structured interviews with research meteorologists lead to a number of recommendations about the design of AMP systems, and to some ideas about needed research on graphics displays and the reasoning of expert meteorologists.
Abstract
This article is intended to facilitate discussion of issues related to the use of color in new meteorological displays. Given the proliferation of new graphics display capabilities (e.g., overlays, animation, the combination of statistical models or numerical fields with satellite images, etc.) and new information sources (e.g., Doppler radar, wind profilers, etc.), the challenge of using color effectively without interfering with users’ abilities to interact with these systems has never been greater. Psychological and ergonomic research on the perception and interpretation of colored graphical displays is reviewed not only to ferret out recommendations but to disclose the design issues raised for meteorology. In addition to relying on tradition and consensus on meteorological symbology and the use of color, an iterative empirical strategy is recommended to help establish whether candidate color schemes could result in interpretation problems when applied to actual meteorological data.
Abstract
This article is intended to facilitate discussion of issues related to the use of color in new meteorological displays. Given the proliferation of new graphics display capabilities (e.g., overlays, animation, the combination of statistical models or numerical fields with satellite images, etc.) and new information sources (e.g., Doppler radar, wind profilers, etc.), the challenge of using color effectively without interfering with users’ abilities to interact with these systems has never been greater. Psychological and ergonomic research on the perception and interpretation of colored graphical displays is reviewed not only to ferret out recommendations but to disclose the design issues raised for meteorology. In addition to relying on tradition and consensus on meteorological symbology and the use of color, an iterative empirical strategy is recommended to help establish whether candidate color schemes could result in interpretation problems when applied to actual meteorological data.
Abstract
As in many domains of modern work, a concern in weather forecasting is the loss of expertise, due either to reassignment or retirement. This note reports upon a project that demonstrates a procedure that can be used to capture forecasters' knowledge of weather concepts. The System To Organize Representations in Meteorology-Local Knowledge (STORM-LK) focuses on weather phenomena in the Gulf Coast region. Forecasters and aerographers at Whiting Field, Naval Air Station, in Pensacola, Florida, participated in a knowledge elicitation procedure that yielded diagrammatic models of their knowledge in the form of “concept maps.” The demonstration suggests the following: 1) the feasibility of using the approach to elicit knowledge so that it might be preserved and shared and 2) the use of concept maps to integrate and navigate through the various instructional and data resources that are used in forecasting. It is envisioned that a knowledge model patterned after STORM-LK could be created for other regions, and for many other topics. Throughout the weather forecasting community, the approach presented here could support the processes of knowledge capture and preservation at the organizational level, with the ultimate goal of fostering active learning and the achievement of local expertise.
Abstract
As in many domains of modern work, a concern in weather forecasting is the loss of expertise, due either to reassignment or retirement. This note reports upon a project that demonstrates a procedure that can be used to capture forecasters' knowledge of weather concepts. The System To Organize Representations in Meteorology-Local Knowledge (STORM-LK) focuses on weather phenomena in the Gulf Coast region. Forecasters and aerographers at Whiting Field, Naval Air Station, in Pensacola, Florida, participated in a knowledge elicitation procedure that yielded diagrammatic models of their knowledge in the form of “concept maps.” The demonstration suggests the following: 1) the feasibility of using the approach to elicit knowledge so that it might be preserved and shared and 2) the use of concept maps to integrate and navigate through the various instructional and data resources that are used in forecasting. It is envisioned that a knowledge model patterned after STORM-LK could be created for other regions, and for many other topics. Throughout the weather forecasting community, the approach presented here could support the processes of knowledge capture and preservation at the organizational level, with the ultimate goal of fostering active learning and the achievement of local expertise.
Abstract
A global observing system simulation experiment (OSSE) was used to assess the potential impact of a proposed Global Navigation Satellite System (GNSS) radio occultation (RO) constellation on tropical cyclone (TC) track, maximum 10-m wind speed (V max), and integrated kinetic energy (IKE) forecasts. The OSSE system was based on the 7-km NASA nature run and simulated RO refractivity determined by the spatial distribution of observations from the original planned (i.e., including both equatorial and polar orbits) Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2). Data were assimilated using the NOAA operational weather analysis and forecasting system. Three experiments generated global TC track, V max, and IKE forecasts over 6 weeks of the North Atlantic hurricane season in the North Atlantic, east Pacific, and west Pacific basins. Confidence in our results was bolstered because track forecast errors were similar to those of official National Hurricane Center forecasts, and V max errors and IKE errors showed similar results. GNSS-RO assimilation did not significantly impact global track forecasts, but did slightly degrade V max and IKE forecasts in the first 30–60 h of lead time. Global forecast error statistics show adding or excluding explicit random errors to RO profiles made little difference to forecasts. There was large forecast-to-forecast variability in RO impact. For two cases studied in depth, track and V max improvements and degradations were traced backward through the previous 24 h of assimilation cycles. The largest V max degradation was traced to particularly good control analyses rather than poor analyses caused by GNSS-RO.
Abstract
A global observing system simulation experiment (OSSE) was used to assess the potential impact of a proposed Global Navigation Satellite System (GNSS) radio occultation (RO) constellation on tropical cyclone (TC) track, maximum 10-m wind speed (V max), and integrated kinetic energy (IKE) forecasts. The OSSE system was based on the 7-km NASA nature run and simulated RO refractivity determined by the spatial distribution of observations from the original planned (i.e., including both equatorial and polar orbits) Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2). Data were assimilated using the NOAA operational weather analysis and forecasting system. Three experiments generated global TC track, V max, and IKE forecasts over 6 weeks of the North Atlantic hurricane season in the North Atlantic, east Pacific, and west Pacific basins. Confidence in our results was bolstered because track forecast errors were similar to those of official National Hurricane Center forecasts, and V max errors and IKE errors showed similar results. GNSS-RO assimilation did not significantly impact global track forecasts, but did slightly degrade V max and IKE forecasts in the first 30–60 h of lead time. Global forecast error statistics show adding or excluding explicit random errors to RO profiles made little difference to forecasts. There was large forecast-to-forecast variability in RO impact. For two cases studied in depth, track and V max improvements and degradations were traced backward through the previous 24 h of assimilation cycles. The largest V max degradation was traced to particularly good control analyses rather than poor analyses caused by GNSS-RO.
Abstract
The potential impact of Doppler wind lidar (DWL) observations from a proposed optical autocovariance wind lidar (OAWL) instrument is quantified in observing system simulation experiments (OSSEs). The OAWL design would provide profiles of useful wind vectors along a ground track to the left of the International Space Station (ISS), which is in a 51.6° inclination low-Earth orbit (LEO). These observations are simulated realistically, accounting for cloud and aerosol distributions inferred from the OSSE nature runs (NRs), and measurement and sampling error sources. The impact of the simulated observations is determined in both global and regional OSSE frameworks. The global OSSE uses the ECMWF T511 NR and the NCEP operational Global Data Assimilation System at T382 resolution. The regional OSSE uses an embedded hurricane NR and the NCEP operational HWRF data assimilation system with outer and inner domains of 9- and 3-km resolution, respectively.
The global OSSE results show improved analyses and forecasts of tropical winds and extratropical geopotential heights. The tropical wind RMSEs are significantly reduced in the analyses and in short-term forecasts. The tropical wind improvement decays as the forecasts lengthen. The regional OSSEs are limited but show some improvements in hurricane track and intensity forecasts.
Abstract
The potential impact of Doppler wind lidar (DWL) observations from a proposed optical autocovariance wind lidar (OAWL) instrument is quantified in observing system simulation experiments (OSSEs). The OAWL design would provide profiles of useful wind vectors along a ground track to the left of the International Space Station (ISS), which is in a 51.6° inclination low-Earth orbit (LEO). These observations are simulated realistically, accounting for cloud and aerosol distributions inferred from the OSSE nature runs (NRs), and measurement and sampling error sources. The impact of the simulated observations is determined in both global and regional OSSE frameworks. The global OSSE uses the ECMWF T511 NR and the NCEP operational Global Data Assimilation System at T382 resolution. The regional OSSE uses an embedded hurricane NR and the NCEP operational HWRF data assimilation system with outer and inner domains of 9- and 3-km resolution, respectively.
The global OSSE results show improved analyses and forecasts of tropical winds and extratropical geopotential heights. The tropical wind RMSEs are significantly reduced in the analyses and in short-term forecasts. The tropical wind improvement decays as the forecasts lengthen. The regional OSSEs are limited but show some improvements in hurricane track and intensity forecasts.
