TL;DR: In this paper, the authors describe the thermodynamic properties of dry air water vapor and its thermodynamic effects Parcel buoyancy and atmospheric stability Mixing and convection Observed properties of clouds Formation of cloud droplets Droplet growth by condensation Initiation of rain in nonfreezing clouds Formation and growth of ice crystals Rain and snow Weather radar Precipitation processes Severe storm and hail Weather modification Numerical cloud models References Appendix Answers to selected problems Index
Abstract: Thermodynamics of dry air Water vapor and its thermodynamic effects Parcel buoyancy and atmospheric stability Mixing and convection Observed properties of clouds Formation of cloud droplets Droplet growth by condensation Initiation of rain in nonfreezing clouds Formation and growth of ice crystals Rain and snow Weather radar Precipitation processes Severe storm and hail Weather modification Numerical cloud models References Appendix Answers to selected problems Index
TL;DR: In this article, the Regional Atmospheric Modeling System was integrated for July-August 1973 for south Florida, and three experiments were performed-one using the observed 1973 landscape, another the 1993 landscape, and the third the 1900 landscape, when the region was close to its natural state.
Abstract: Using identical observed meteorology for lateral boundary conditions, the Regional Atmospheric Modeling System was integrated for July-August 1973 for south Florida. Three experiments were performed-one using the observed 1973 landscape, another the 1993 landscape, and the third the 1900 landscape, when the region was close to its natural state. Over the 2-month period, there was a 9% decrease in rainfall averaged over south Florida with the 1973 landscape and an 11% decrease with the 1993 landscape, as compared with the model results when the 1900 landscape is used. The limited available observations of trends in summer rainfall over this region are consistent with these trends.
TL;DR: In this paper, the authors performed an analysis of the 500 most relevant scientific articles published since 2018, concerning machine learning methods in the field of climate and numerical weather prediction using the Google Scholar search engine.
Abstract: In this paper, we performed an analysis of the 500 most relevant scientific articles published since 2018, concerning machine learning methods in the field of climate and numerical weather prediction using the Google Scholar search engine. The most common topics of interest in the abstracts were identified, and some of them examined in detail: in numerical weather prediction research—photovoltaic and wind energy, atmospheric physics and processes; in climate research—parametrizations, extreme events, and climate change. With the created database, it was also possible to extract the most commonly examined meteorological fields (wind, precipitation, temperature, pressure, and radiation), methods (Deep Learning, Random Forest, Artificial Neural Networks, Support Vector Machine, and XGBoost), and countries (China, USA, Australia, India, and Germany) in these topics. Performing critical reviews of the literature, authors are trying to predict the future research direction of these fields, with the main conclusion being that machine learning methods will be a key feature in future weather forecasting.
TL;DR: Using synoptic weather categories in regression models does not meaningfully change the association between mortality and air pollution indexes, and there is little evidence that weather conditions modified the effect of pollution, regardless of the approach used to represent weather.
TL;DR: METROMEX as discussed by the authors, a field project designed and now in progress at St. Louis State University, involves 4 research groups planning and working cooperatively to study inadvertent weather modification by urban-industrial effects, and, in particular, man-made changes of precipitation.
Abstract: METROMEX, a field project designed and now in progress at St. Louis, involves 4 research groups planning and working cooperatively to study inadvertent weather modification by urban-industrial effects, and, in particular, man-made changes of precipitation. Urban areas affect most forms of weather and some, such as winds, temperature, and visibility, are obvious and their changes are easily measured. inadvertent precipitation changes are harder to measure, and except for the well-documented La Porte anomaly, urban-related rain changes have had only limited study. Examination of historical data at St. Louis has revealed summer increases in the immediate downwind area of. 1) rainfall (10–17%); 2) moderate rain days (11–23%); 3) heavy rainstorms (80%) 4) thunderstorms (21%); and 5) hailstorms (30%). METROMEX field measurements in the summer of 1971 involved 220 raingages and hailpads, 3 radar sets, 70 rainwater collectors, 14 pibal stations, 4 meteorological aircraft, unique atmospheric tracers, and ...