VOCALS2008_WbandCloudHeight10min_1_0.readme.txt :: 2009 June 1 :: Simon de Szoeke README metadata for VOCALS2008_WbandCloudHeight10min_1_0.nc, VOCALS2008_WbandCloudHeight10min_1_0.txt Title: W-band 10-minute cloud fraction and cloud top height data for VOCALS 2008 Version: 1.0 Creation date: 2009-06-26 Author: Simon de Szoeke Data are provided by Simon de Szoeke (Oregon State University), Chris Fairall (NOAA/ESRL/PSD), and Sandra Yuter (North Carolina State University) with funding from the NOAA Climate Program Office. Find this metadata at ftp://ftp.coas.oregonstate.edu/dist/sdeszoek/vocals/VOCALS2008_WbandCloudHeight10min_1_0.readme.txt Data Set Variables # Name [units] Description 1 yday [day] Decimal year day of start of averaging interval; days since 2008 January 1 00:00 UTC. 2 cloudtop [m] Mean cloud top height (algorithm below) 3 cloudfrac [unitless] Cloud fraction (algorithm below) 4 numreturns [number] Number of 3.5-Hz vertical slices of moments in 10-min interval (see definition under Cloud Fraction below) 5 numcloud [number] Number of cloudy vertical slices of moments 6 numclear [number] Number of clear vertical slices of moments 7 numnonmet [number] Number of non-meteorological vertical moment slices Variables are summed or averaged over 10-minute intervals. In the formatted text(.txt) file the missing value for cloud top and cloud fraction is -999.000. In the netcdf(.nc) file, IEEE not-a-number (NaN) values denote missing values. Cloud Top Height Cloud top height is computed from the NOAA/ESRL/PSD vertically-pointing W-band (3.17-mm wavelength, 94.56 GHz) radar during leg 2 of VOCALS 2008. Moments from the radar in 25-m range gates are available at a frequency of 3.5 Hz. Clouds and Doppler velocities were detected from W-band data available after 2008 November 5 (year day 310). Before November 5 the radar was operated with insufficient sensitivity to detect clouds. The highest cloud top was computed from the cloud-sensitive 3.5-Hz mean reflectivity moments. The algorithm balances sensitivity to the highest clouds with elimination of non-meteorological high-reflectivity moments: 1. Cloud Detection from W-band Moments Reflectivity moments at (3.5 Hz) are compared with the range-dependent minimum detectable reflectivity. Reflectivity above this threshold is mostly from scattering by clouds or precipitation. Reflectivity above the threshold might also be due to non-meteorological targets (clutter). They also have a small probability of being noise. Noise and clutter returns have no reason to appear near the true cloud top, and taking the highest return is potentially sensitive to noise above the cloud. Clouds being nearly always vertically homogeneous, we eliminate most noise and clutter above the cloud by insisting that potential clouds have 3 adjacent range gates with reflectivity above the noise threshold, i.e. clouds are at least 75 m thick. 2. Finding Cloud Top Heights The potential cloud returns from step 1 are binned into 1-minute intervals. (There are usually 210 3.5-Hz time slices per minute.) Clouds are excluded above the maximum allowed cloud height, defined as the height of the highest range at which at least 3 clouds are found in the minute. This helps exclude noise above a cloud. Cloud top height is still computed if there is no level with 3 cloudy moments. Cloud top height for each 3.5-Hz vertical slice is computed as the highest remaining cloud top below the maximum allowed cloud height. These cloud top heights are mean-averaged over the minute. 3. Averaging to 10-minute Intervals One-minute cloud top heights are meaned into evenly-spaced 10-minute intervals. The first 10-minute interval in a day begins on midnight UTC. All 1-minute cloud top heights in which a cloud top was found are weighted equally in the 10-minute mean. Moments at 3.5-Hz are identified as cloudy, clear, or non-meteorological. While the cloud top algorithm takes care to exclude non-meteorological outlier returns, in practice most non-meteorological returns yield cloud tops consistent with those from cloudy moments. Cloud Fraction 1. Identifying Potential Clouds Potential clouds are identified the same as cloud top height step 1. Mean reflectivity moments exceeding the noise threshold are identified. Potential clouds must also have three vertically adjacent cloud levels. 2. Cloud Sorting The potential cloud returns from step 1 are binned into 1-minute intervals. (There are usually 210 3.5-Hz time slices per minute.) Clouds are deemed "non-meteorological" above the maximum allowed cloud height, defined as the height of the highest range at which at least 3 clouds are found in the minute. Thus each (3.5-Hz) time slice must be one of 3 designations: (1) clear: no clouds (of vertical extent >=75 m) found (2) cloud: clouds found at or below the maximum allowed cloud height (3) non-meteorological: clouds above the maximum allowed cloud height, or clouds vertically inhomogeneous for the whole minute 3. Cloud Fraction Computation The number of returns in each designation is counted. The cloud fraction is computed from the number of cloud counts over the sum of the clear and cloud counts, cloud fraction = cloud / ( clear + cloud ). Non-meteorological returns are not considered in the cloud fraction. The number of non-meteorological returns is relatively small. Even if cloud fraction is zero, for vertically inhomogeneous clouds cloud top height can be computed. 4. Averaging to 10-minute Intervals While step 3 can be computed on 1-minute or 10-minute intervals, we have chosen to compute it on 1-minute intervals and mean all 1-minute intervals with equal weight in the 10-minute interval. The total counts of cloud, clear, and non-meteorological returns for each 10-minute interval are also provided.