Remote Sensing of Clouds and Precipitation: Event-based Characterization, Life Cycle Evolution, and Aerosol Influences

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dc.contributor.advisorZeng, Ningen_US
dc.contributor.authorEsmaili, Rebekahen_US
dc.contributor.departmentAtmospheric and Oceanic Sciencesen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2017-06-22T05:50:05Z
dc.date.available2017-06-22T05:50:05Z
dc.date.issued2016en_US
dc.description.abstractGlobal climate models, numerical weather prediction, and flood models rely on accurate satellite precipitation products, which are the only datasets that are continuous in time and space across the globe. While there are more earth observing satellites than ever before, gaps in precipitation retrievals exist due to sensor and orbital limitations of low-earth (LEO) satellites, which are overcome by merging data from different sensors in satellite precipitation products (SPPs). Using cloud tracking at higher resolutions than the spatio-temporal scales of LEO satellites, this thesis examines how clouds typically form in the atmosphere, the rate that cloud size and temperature evolve over the life cycle, and the time of day that cloud development take place. This thesis found that cloud evolution was non-linear, which disagrees with the linear interpolation schemes used in SPPs. Longer lasting clouds tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lasting clouds. Over the ocean, longer lasting clouds were found to occur more frequently at night, while shorter lasting clouds were more common during the daytime. This thesis also examines whether large-scale Saharan dust outbreaks can impact the trajectories and intensity of cloud clusters in the tropical Atlantic, which is predicted by modeling studies. The presented results show that proximity to Saharan dust outbreaks shifts Atlantic cloud development northward and intense storms becoming more common, whereas on days with low dust loading small-scale, warmer clouds are more common. A simplified view of cloud evolution in merged rainfall retrievals is a possible source of errors, which can propagate into higher level analysis. This thesis investigates the difference in the intensity, duration, and frequency of precipitation in IMERG, a next-generation satellite precipitation product with ground radar observations over the contiguous United States. There was agreement on seasonal totals, but closer examination shows that the average intensity and duration of events is too high, and too infrequent compared to events detected on the ground. Awareness of the strengths and limitations, particularly in context of high-resolution cloud development, can enhance SPPs and can complement climate model simulations.en_US
dc.identifierhttps://doi.org/10.13016/M2M85W
dc.identifier.urihttp://hdl.handle.net/1903/19340
dc.language.isoenen_US
dc.subject.pqcontrolledAtmospheric sciencesen_US
dc.subject.pqcontrolledRemote sensingen_US
dc.subject.pqcontrolledClimate changeen_US
dc.subject.pquncontrolledCloud life cycleen_US
dc.subject.pquncontrolledGPMen_US
dc.subject.pquncontrolledinfrareden_US
dc.subject.pquncontrolledPrecipitationen_US
dc.subject.pquncontrolledtrackingen_US
dc.titleRemote Sensing of Clouds and Precipitation: Event-based Characterization, Life Cycle Evolution, and Aerosol Influencesen_US
dc.typeDissertationen_US

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