Now showing items 1-6 of 6
An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB
(American Meteorological Society (ACM), 2018-02-19)
This paper presents a satellite-observation-based evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmosphere Model, version 5 (CAM5), simulations, one with the standard parameterization ...
Quantifying the Impacts of Subpixel Reﬂectance Variability on Cloud Optical Thickness and Eﬀective Radius Retrievals Based On High-Resolution ASTER Observations
(American Geophysical Union, 2018-04-26)
Recently, Zhang et al. (2016, https://doi.org/10.1002/2016JD024837) presented a mathematical framework based on a second-order Taylor series expansion in order to quantify the plane-parallel homogeneous bias (PPHB) in cloud ...
Comparisons of bispectral and polarimetric retrievals of marine boundary layer cloud microphysics: case studies using a LES–satellite retrieval simulator
(Copernicus Publications, 2018-06-26)
Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These ...
The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models
(Copernicus Publications, 2018-08-03)
Satellite cloud observations have become an indispensable tool for evaluating general circulation models (GCMs). To facilitate the satellite and GCM comparisons, the CFMIP (Cloud Feedback Model Inter-comparison Project) ...
Assessing Water Budget Sensitivity to Precipitation Forcing Errors in Potomac River Basin Using the VIC Hydrologic Model CyberTraining: Big Data + High-Performance Computing + Atmospheric Sciences
The Potomac River Basin is a watershed located on the East Coast of the USA across West Virginia, Virginia, Pennsylvania, Maryland, and the District of Columbia. Inter-annual variations in precipitation makes it challenging ...
Dust Detection in Satellite Data using Convolutional Neural Networks
(HPCF UMBC, 2019)
Atmospheric dust is known to cause health ailments and impacts earth’s climate and weather patterns. Due to the many issues atmospheric dust contributes to, it is important to study dust patterns and how it enters the ...