UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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Author: search.filters.author.Chen, RuiyueSubject: search.filters.subject.effective radius profile

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    ENHANCEMENT OF ATMOSPHERIC LIQUID WATER ESTIMATION USING SPACE-BORNE REMOTE SENSING DATA
    (2009) Chen, Ruiyue; Li, Zhanqing; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Clouds strongly affect the energy balance and water cycle, two dominant processes in the climate system. Low-level liquid clouds have the most significant influence on cloud radiative forcing due to their areal extent and frequency. Estimation of atmospheric liquid water contained in low-level clouds and the precipitation underneath them is very important in meteorology, hydrology, and climatology. Space-borne remote sensing data are widely used for global estimation of atmospheric liquid water, given that they have a wider spatial coverage than other data sources and are spanning many years. However, previous space-borne remote sensing techniques have some limitations for estimation of atmospheric liquid water in low-level liquid clouds, namely, the vertical variation of droplet effective radius (DER) is neglected in the calculation of cloud liquid water path (LWP) and the rain underneath low-level liquid clouds can be overlooked. Comprising many state-of-art passive and active instruments, the recently launched NASA A-Train series of satellites provides comprehensive simultaneous information about cloud and precipitation processes. Utilizing A-Train satellite data and ship-borne data from the East Pacific Investigation of Climate (EPIC) campaign, in this study investigated is the estimation of liquid water in low-level liquid clouds, and assessed is the potential of cloud microphysical parameters in the estimation of rain from low-level liquid clouds. This study demonstrates that assuming a constant cloud DER can cause biases in the calculation of LWP. It is also shown that accounting for the vertical variation of DER can reduce the mean biases. This study shows that DER generally increases with height in non-drizzling clouds, consistent with aircraft observations. It is found that in drizzling clouds, the vertical gradient of DER is significantly smaller than that in non-drizzling clouds, and it can become negative when the drizzle is heavier than approximately 0.1 mm hr-1. It is shown that the warm rain underneath low-level liquid clouds accounts for 45.0% of occurrences of rain and 27.5% of the rainfall amount over the global ocean areas. Passive microwave techniques underestimate the warm rain over oceans by nearly 48%. Among the cloud microphysical parameters, LWP calculated with DER profile shows the best potential for estimating warm rain, which is neglected by traditional techniques of precipitation estimation.