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Browsing by Author "Barlow, Stephen J., author"

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    Exploratory study for detecting low clouds (base < 10,000 feet) over the southwestern United States using Tropical Rainfall Measuring Mission Microwave (TRMM) Imager 85.5 GHz data and coincident 10.8 micron infrared data
    (Colorado State University. Libraries, 2001) Barlow, Stephen J., author; Vonder Haar, Thomas H., author; Cooperative Institute for Research in the Atmosphere (Fort Collins, Colo.), publisher
    Recent research in retrieving cloud liquid water over land using the 85.5 GHz microwave channel has shown limited success. This work usually requires extensive manipulation of the data to correct for atmospheric effects, and to eliminate rain events Even with these corrections, the over-land methods must still address the complex spatial variability of soil and vegetation characteristics, which have a profound affect on surface emissivity, e.g., a non-uniform background. This work uses the Normalized Polarization Difference (NPD) method in an attempt to identify low cloud signature over the Southwestern United States from 1 June to 31 August 1998. This will provide nighttime capability in identifying low-cloud areas over data-sparse, data-denied regions with relatively uniform terrain characteristics. The development of a simplified method for use in data-sparse, data-denied regions was of prime importance In order to identify low clouds, effective surface emittance calculations were made using co-located Tropical Rainfall Measuring Mission Microwave 85.5 GHz data and coincident 10.8 μm infrared data for clear-sky conditions. Based on previous work, the Southwestern United States, in general, should have the large polarization differences (> 0.015) as well as uniform skin temperatures, which could provide a suitable background to detect low cloud signal above the background noise. Eleven sites were chosen based on varying degrees of polarization difference, as well as having available surface and upper air data. In situ surface observations were used to identify the low cloud base, while the infrared brightness temperature at 10. 8 μm was used to estimated the cloud top height using the nearest upper air sounding. The estimated cloud thickness was calculated from this data. Extensive efforts were made to eliminate multiple cloud layers, which would have a negative impact on brightness temperatures. A scattering index, the Grody algorithm, and surface observations were used to filter precipitating clouds. The results using a linear regression best fit indicated poor correlation (R2) between the NPD and the 2 estimated low-cloud thickness with values of R2 ranging from 0.002 to 0.345. Four primary error mechanisms were identified, and quantified. The uncorrected atmosphere accounted for about a 0.7-1.7 K error; horizontal variations in infrared temperature on the scale of 2.0-7.3 K; instrument noise of about 1.5K; and effective surface emissivity relative uncertainties ranging from 0.22- 1.16%. Future improvements in sensor noise characteristics and resolution, as well as the ability to perform instantaneous atmospheric corrections using coincident sounder and microwave imager data should lead to a viable NPD method over land.