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The 2009 Atlanta flood was a historic event that resulted in catastrophic damage throughout the metropolitan area. The flood was the product of several hydrometeorological processes, including moist antecedent conditions, ample atmospheric moisture, and mesoscale training. Additionally, previous studies hypothesized that the urban environment of Atlanta altered the location and/or overall quantities of precipitation and runoff that ultimately produced the flood. This hypothesis was quantitatively evaluated by conducting a modeling case study that utilized the Weather Research and Forecasting Model. Two model runs were performed: 1) an urban run designed to accurately depict the flood event and 2) a nonurban simulation where the urban footprint of Atlanta was replaced with natural vegetation. Comparing the output from the two simulations revealed that interactions with the urban environment enhanced the precipitation and runoff associated with the flood. Specifically, the nonurban model underestimated the cumulative precipitation by approximately 100 mm in the area downwind of Atlanta where urban rainfall enhancement was hypothesized. This notable difference was due to the increased surface convergence observed in the urban simulation, which was likely attributable to the enhanced surface roughness and thermal properties of the urban environment. The findings expand upon previous research focused on urban rainfall effects since they demonstrate that urban interactions can influence mesoscale hydrometeorological characteristics during events with prominent synoptic-scale forcing. Finally, from an urban planning perspective, the results highlight a potential two-pronged vulnerability of urban environments to extreme rainfall, as they may enhance both the initial precipitation and subsequent runoff.

Atmospheric rivers (ARs) are narrow and elongated bands of anomalous water vapour transport that have been widely studied due to their notable influence on regional weather patterns, surface hydrology, and the global water cycle. Although ARs produce a relatively large proportion of the annual precipitation in the southeastern quadrant of the United States, a detailed climatological analysis of Southeastern atmospheric rivers (SE-ARs) has not been conducted. In this study, a climatology of SE-AR coastal interactions from 1979 to 2014 was constructed from a global AR data set to examine the spatiotemporal characteristics of SE-ARs as well as the importance of synoptic-scale and low-frequency modes of climate variability in modulating their frequency. The climatology revealed that SE-ARs were most prevalent during the cold season, with the majority of these wintertime coastal interactions occurring predominately in the Gulf of Mexico. The synoptic-scale and low-frequency modes of climate variability favourable for SE-AR development differed depending on the season and sub-region of the Southeast considered. More specifically, a dipole effect was discovered, as conditions conducive for SE-AR coastal interactions along the western Gulf generally inhibited SE-AR interactions with the Florida Peninsula and vice versa. Overall, a better understanding of the seasonality of SE-ARs as well as the synoptic-scale and low-frequency modes of climate variability that encourage their development could lead to improved forecasting and community awareness of the devastating AR-related flood events that occur throughout the Southeast.

The human population on Earth has increased by a factor of 4.6 in the last 100 years and has become more centered in urban environments. This expansion and migration pattern has resulted in stresses on the environment. Meteorological applications have helped to understand and mitigate those stresses. This chapter describes several applications that enable the population to interact with the environment in more sustainable ways. The first topic treated is urbanization itself and the types of stresses exerted by population growth and its attendant growth in urban landscapes—buildings and pavement—and how they modify airflow and create a local climate. We describe environmental impacts of these changes and implications for the future. The growing population uses increasing amounts of energy. Traditional sources of energy have taxed the environment, but the increase in renewable energy has used the atmosphere and hydrosphere as its fuel. Utilizing these variable renewable resources requires meteorological information to operate electric systems efficiently and economically while providing reliable power and minimizing environmental impacts. The growing human population also pollutes the environment. Thus, understanding and modeling the transport and dispersion of atmospheric contaminants are important steps toward regulating the pollution and mitigating impacts. This chapter describes how weather information can help to make surface transportation more safe and efficient. It is explained how these applications naturally require transdisciplinary collaboration to address these challenges caused by the expanding population.