UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
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Item Interaction Between the Aerosol Direct Effect in the Lower Troposphere and the Planetary Boundary Layer(2015) Sawyer, Virginia Ruth; Li, Zhanqing; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The planetary boundary layer (PBL) limits the vertical mixing of aerosol emitted to the lower troposphere. The PBL depth and its change over time affect weather, surface air quality and radiative forcing. While model simulations have suggested that the column optical properties of aerosol are associated with changes in the PBL depth in turn, there are few long-term measurements of PBL depth with which to validate the theory. Of the existing methods to detect the PBL depth from atmospheric profiles, many require supporting information from multiple instruments or cannot adapt to changing atmospheric conditions. This study combines two common methods for PBL depth detection (wavelet covariance and iterative curve-fitting) in order to produce more reliable PBL depths for micropulse lidar backscatter (MPL). The combined algorithm is also flexible enough to use with radiosonde and atmospheric emitted radiance interferometer (AERI) data. PBL depth retrievals from these three instruments collected at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are compared to one another to show the robustness of the algorithm. The comparisons were made for different times of day, four seasons, and variable sky conditions. While considerable uncertainties exist in PBL detection using all three types of measurements, the agreement among the PBL products is promising, and the different measurements have complementary advantages. The best agreement in the seasonal cycle occurs in winter, and the best agreement in the diurnal cycle when the boundary-layer regime is mature and changes slowly. PBL depths from instruments with higher temporal resolution (MPL and AERI) are of comparable accuracy to radiosonde-derived PBL depths. The new PBL depth measurements for SGP are compared to MPL-derived PBL depths from a multiyear lidar deployment at the Hefei Radiation Observatory (HeRO), and the column aerosol optical depth (AOD) for each site is considered. A one-month period at SGP is also modeled to relate AOD to PBL depth. These comparisons show a weak inverse relationship between AOD and daytime PBL depth. This is consistent with predictions that aerosol suppresses surface convection and causes shallower PBLs.Item ESTIMATING LAND SURFACE ALBEDO FROM SATELLITE DATA(2012) He, Tao; Liang, Shunlin; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Land surface albedo, defined as the ratio of the surface reflected incoming and outgoing solar radiation, is one of the key geophysical variables controlling the surface radiation budget. Surface shortwave albedo is widely used to drive climate and hydrological models. During the last several decades, remotely sensed surface albedo products have been generated through satellite-acquired data. However, some problems exist in those products due to instrument measurement inaccuracies and the failure of current retrieving procedures, which have limited their applications. More significantly, it has been reported that some albedo products from different satellite sensors do not agree with each other and some even show the opposite long term trend regionally and globally. The emergence of some advanced sensors newly launched or planned in the near future will provide better capabilities for estimating land surface albedo with fine resolution spatially and/or temporally. Traditional methods for estimating the surface shortwave albedo from satellite data include three steps: first, the satellite observations are converted to surface directional reflectance using the atmospheric correction algorithms; second, the surface bidirectional reflectance distribution function (BRDF) models are inverted through the fitting of the surface reflectance composites; finally, the shortwave albedo is calculated from the BRDF through the angular and spectral integration. However, some problems exist in these algorithms, including: 1) "dark-object" based atmospheric correction methods which make it difficult to estimate albedo accurately over non-vegetated or sparsely vegetated area; 2) the long-time composite albedo products cannot satisfy the needs of weather forecasting or land surface modeling when rapid changes such as snow fall/melt, forest fire/clear-cut and crop harvesting occur; 3) the diurnal albedo signature cannot be estimated in the current algorithms due to the Lambertian approximation in some of the atmospheric correction algorithms; 4) prior knowledge has not been effectively incorporated in the current algorithms; and 5) current observation accumulation methods make it difficult to obtain sufficient observations when persistent clouds exist within the accumulation window. To address those issues and to improve the satellite surface albedo estimations, a method using an atmospheric radiative transfer procedure with surface bidirectional reflectance modeling will be applied to simultaneously retrieve land surface albedo and instantaneous aerosol optical depth (AOD). This study consists of three major components. The first focuses on the atmospheric radiative transfer procedure with surface reflectance modeling. Instead of executing atmospheric correction first and then fitting surface reflectance in the previous satellite albedo retrieving procedure, the atmospheric properties (e.g., AOD) and surface properties (e.g., BRDF) are estimated simultaneously to reduce the uncertainties produced in separating the entire radiative transfer process. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua are used to evaluate the performance of this albedo estimation algorithm. Good agreement is reached between the albedo estimates from the proposed algorithm and other validation datasets. The second part is to assess the effectiveness of the proposed algorithm, analyze the error sources, and further apply the algorithm on geostationary satellite - the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). Extensive validations on surface albedo estimations from MSG/SEVIRI observations are conducted based on the comparison with ground measurements and other satellite products. Diurnal changes and day-to-day changes in surface albedo are accurately captured by the proposed algorithm. The third part of this study is to develop a spatially and temporally complete, continuous, and consistent albedo maps through a data fusion method. Since the prior information (or climatology) of albedo/BRDF plays a vital role in controlling the retrieving accuracy in the optimization method, currently available multiple land surface albedo products will be integrated using the Multi-resolution Tree (MRT) models to mitigate problems such as data gaps, systematic bias or low information-noise ratio due to instrument failure, persistent clouds from the viewing direction and algorithm limitations. The major original contributions of this study are as follows: 1) this is the first algorithm for the simultaneous estimations of surface albedo/reflectance and instantaneous AOD by using the atmospheric radiative transfer with surface BRDF modeling for both polar-orbiting and geostationary satellite data; 2) a radiative transfer with surface BRDF models is used to derive surface albedo and directional reflectance from MODIS and SEVIRI observations respectively; 3) extensive validations are made on the comparison between the albedo and AOD retrievals, and the satellite products from other sensors; 4) the slightly modified algorithm has been adopted to be the operational algorithm of Advanced Baseline Imager (ABI) in the future Geostationary Operational Environmental Satellite-R Series (GOES-R) program for estimating land surface albedo; 5) a framework of using MRT is designed to integrate multiple satellite albedo products at different spatial scales to build the spatially and temporally complete, continuous, and consistent albedo maps as the prior knowledge in the retrieving procedure.