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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 FROM AUTHOR]

Presents an article on studying the cause of the green sky that precedes threatening storms and often accompanied by tornadoes. Previous research on green sky phenomenon; Experience in tracking down the cause of green light; Importance of the spectrophotometer in studying the green sky.

Illustrates the problems and general scale of errors that can occur in the measurement of atmospheric pressure. Demonstration on the inaccuracies in atmospheric pressure measurement using an automobile; Methodology of the experiment; Discussion on the results of the experiment.

Discusses the theory behind the creation of distant green thunderstorms. Spectrum of light perceived as a faint green; Use of a nonblack cloud background; Shift in the dominant wavelengths from the green portion of the spectrum.

Reports on the development of a prototype instrument that measures haze in aircraft windscreens. Elimination of ambient light and compensation for the remaining illumination; Need for precise orientation of the collimator and the integrating sphere.

Observes green light in thunderstorms caused by sunlight reflected onto the cloud by green vegetation. Colorimetric observations of green-colored and blue-colored thunderstorms; Test on the validity of the importance of ground reflection; Use of numerical models to evaluate the likelihood of ground-reflected light causing green color in storms.

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 DPGuse 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 FROM AUTHOR]