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- Author or Editor: Frank W. Gallagher III x
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Abstract
It has been suggested that green light often observed in association with severe thunderstorms is caused by sunlight being reflected onto the cloud by green vegetation. Colorimetric observations were recorded of green-colored and blue-colored thunderstorms in conjunction with spectral measurements of the light reflected by the ground beneath the storms. Simple numerical models were used to evaluate the likelihood of ground-reflected light causing the green color in storms. Both the observations and calculations indicate that the green light seen in severe thunderstorms is not caused by light reflected from green foliage.
Abstract
It has been suggested that green light often observed in association with severe thunderstorms is caused by sunlight being reflected onto the cloud by green vegetation. Colorimetric observations were recorded of green-colored and blue-colored thunderstorms in conjunction with spectral measurements of the light reflected by the ground beneath the storms. Simple numerical models were used to evaluate the likelihood of ground-reflected light causing the green color in storms. Both the observations and calculations indicate that the green light seen in severe thunderstorms is not caused by light reflected from green foliage.
Abstract
The theoretical development presented by Fraser can produce a spectrum of light that would be perceived as a faint green. The theory assumed a perfectly black background thunderstorm. Severe thunderstorms are certainly not black when observed from a distance of 30–40 km. Thus it is useful to compare the theory with some observed examples of severe thunderstorms that should have been green by the Fraser theory but were not. Therefore, some elementary modifications of the Fraser model such as using a nonblack background are suggested. The use of a nonblack cloud background tends to shift the resulting dominant wavelengths away from the green portion of the spectrum, suggesting a better match with observations.
Abstract
The theoretical development presented by Fraser can produce a spectrum of light that would be perceived as a faint green. The theory assumed a perfectly black background thunderstorm. Severe thunderstorms are certainly not black when observed from a distance of 30–40 km. Thus it is useful to compare the theory with some observed examples of severe thunderstorms that should have been green by the Fraser theory but were not. Therefore, some elementary modifications of the Fraser model such as using a nonblack background are suggested. The use of a nonblack cloud background tends to shift the resulting dominant wavelengths away from the green portion of the spectrum, suggesting a better match with observations.
Abstract
Between 2014 and 2018, the NOAA Office of Systems Architecture and Advanced Planning (OSAAP) conducted the NOAA Satellite Observing System Architecture (NSOSA) study to plan the long-term future of the NOAA constellation of operational environmental satellites. This constellation of satellites (which may include space capabilities acquired in lieu of U.S. government satellites) will follow the current GOES-R and JPSS satellite programs, beginning about 2030. This was an opportunity to design a modern architecture with no preconceived notions regarding instruments, platforms, orbits, etc., but driven by user needs, new technology, and exploiting emerging space business models. In this paper we describe how the study was structured, review major results, show how observation priorities and estimated costs drove next-generation choices, and discuss important challenges for implementing the next generation of U.S. civil environmental remote sensing satellites.
Abstract
Between 2014 and 2018, the NOAA Office of Systems Architecture and Advanced Planning (OSAAP) conducted the NOAA Satellite Observing System Architecture (NSOSA) study to plan the long-term future of the NOAA constellation of operational environmental satellites. This constellation of satellites (which may include space capabilities acquired in lieu of U.S. government satellites) will follow the current GOES-R and JPSS satellite programs, beginning about 2030. This was an opportunity to design a modern architecture with no preconceived notions regarding instruments, platforms, orbits, etc., but driven by user needs, new technology, and exploiting emerging space business models. In this paper we describe how the study was structured, review major results, show how observation priorities and estimated costs drove next-generation choices, and discuss important challenges for implementing the next generation of U.S. civil environmental remote sensing satellites.
Abstract
Since 2007, meteorologists of the U.S. Army Test and Evaluation Command (ATEC) at Dugway Proving Ground (DPG), Utah, have relied on a mesoscale ensemble prediction system (EPS) known as the Ensemble Four-Dimensional Weather System (E-4DWX). This article describes E-4DWX and the innovative way in which it is calibrated, how it performs, why it was developed, and how meteorologists at DPG use it. E-4DWX has 30 operational members, each configured to produce forecasts of 48 h every 6 h on a 272-processor high performance computer (HPC) at DPG. The ensemble’s members differ from one another in initial-, lateral-, and lower-boundary conditions; in methods of data assimilation; and in physical parameterizations. The predictive core of all members is the Advanced Research core of the Weather Research and Forecasting (WRF) Model. Numerical predictions of the most useful near-surface variables are dynamically calibrated through algorithms that combine logistic regression and quantile regression, generating statistically realistic probabilistic depictions of the atmosphere’s future state at DPG’s observing sites. Army meteorologists view E-4DWX’s output via customized figures posted to a restricted website. Some of these figures summarize collective results—for example, through means, standard deviations, or fractions of the ensemble exceeding thresholds. Other figures show each forecast, individually or grouped—for example, through spaghetti diagrams and time series. This article presents examples of each type of figure.
Abstract
Since 2007, meteorologists of the U.S. Army Test and Evaluation Command (ATEC) at Dugway Proving Ground (DPG), Utah, have relied on a mesoscale ensemble prediction system (EPS) known as the Ensemble Four-Dimensional Weather System (E-4DWX). This article describes E-4DWX and the innovative way in which it is calibrated, how it performs, why it was developed, and how meteorologists at DPG use it. E-4DWX has 30 operational members, each configured to produce forecasts of 48 h every 6 h on a 272-processor high performance computer (HPC) at DPG. The ensemble’s members differ from one another in initial-, lateral-, and lower-boundary conditions; in methods of data assimilation; and in physical parameterizations. The predictive core of all members is the Advanced Research core of the Weather Research and Forecasting (WRF) Model. Numerical predictions of the most useful near-surface variables are dynamically calibrated through algorithms that combine logistic regression and quantile regression, generating statistically realistic probabilistic depictions of the atmosphere’s future state at DPG’s observing sites. Army meteorologists view E-4DWX’s output via customized figures posted to a restricted website. Some of these figures summarize collective results—for example, through means, standard deviations, or fractions of the ensemble exceeding thresholds. Other figures show each forecast, individually or grouped—for example, through spaghetti diagrams and time series. This article presents examples of each type of figure.
