
Level 2b Cloudnet product:Cloud fraction on RACMO model gridData Home  Overview of Cloudnet products  Product list  Quicklooks  Conditions of useSummary
Dataset contentsSample NetCDF file: 20031001_chilbolton_cloudfractionracmogrid.nc The following is a description of the variables in this product, produced automatically from the metadata in the sample file (using the nc2html unix utility): Dataset title: Cloud fractions by area and volume, as observed at Chilbolton, averaged to the KNMI Regional Atmospheric Climate Model (RACMO) grid.This dataset contains cloud fraction both from a forecast model and derived from the highresolution observations on the grid of that model. There are a number of different cloud fraction variables. In the case of the observations, cloud fraction has been calculated "by volume" (i.e. the volume of a gridbox containing cloud) and "by area" (i.e. the area of the gridbox when viewed from above that is obscured by cloud). It has also been calculated both from the time taken for the wind to advect 1 model gridbox of cloud across the site, and using a constant 1hour sample window. In the case of the model, the "model_Cv" variable contains cloud fraction taken directly from the model, while "model_Cv_filtered" contains cloud fraction after filtering to remove tenuous ice clouds that are not believed to be likely to be detected by the radar. Generally the observed values should be compared to "model_Cv_filtered", with "model_Cv_filtered_min" and "model_Cv_filtered_max" providing an estimate of the range of uncertainty in the filtering procedure. Note that the problem of some ice cloud not being detected is limited to above around 8 km. The filtering has been performed as discussed in Hogan et al. (2001, J. Appl. Meteorol., 40, 513525), but accounting for subgrid variability as described by Hogan and Illingworth (2003, J. Atmos. Sci., 60, 756767).
Software version:1.3 Dimensions and coordinate variablestimeHours UTC
Type:singleprecision floatingpoint vector Height above ground
Type:singleprecision floatingpoint array Variableshorizontal_resolutionHorizontal resolution of model
Type:singleprecision floatingpoint scalar Height of radar above mean sea level
Type:singleprecision floatingpoint scalar Time since initialization of forecast For each profile in the file this variable contains the time elapsed since the initialization time of the forecast from which it was taken. Note that the profiles in this file may be taken from more than one forecast. Units:hoursType:singleprecision floatingpoint vector Rain rate threshold Measurements above a surface rain rate of greater than this value were excluded due to the possibility of strong attenuation leading to an underestimate of cloud fraction. Units:mm hr1Type:singleprecision floatingpoint scalar Height above ground The heights have been calculated using pressure, temperature and specific humidity. Units:mType:singleprecision floatingpoint array Latitude of site
Type:singleprecision floatingpoint scalar Longitude of site
Type:singleprecision floatingpoint scalar Observed cloud fraction by volume, 1 hour sampling This variable is the observed cloud fraction, by volume, averaged onto the model grid with height, and 1 hour in time. Units:dimensionlessType:singleprecision floatingpoint array Observed cloud fraction by area, 1 hour sampling This variable is the observed cloud fraction, by area, averaged onto the model grid with height, and 1 hour in time. Units:dimensionlessType:singleprecision floatingpoint array Observed cloud fraction by volume, 18km sampling This variable is the observed cloud fraction, by volume, averaged onto the model grid with height, and over the time taken to advect the model's horizontal resolution (max 1 hour, min 10 minutes). Units:dimensionlessType:singleprecision floatingpoint array Observed cloud fraction by area, 18km sampling This variable is the observed cloud fraction, by area, averaged onto the model grid with height, and over the time taken to advect the model's horizontal resolution (max 1 hour, min 10 minutes). Units:dimensionlessType:singleprecision floatingpoint array Total column cloud cover, 1 hour sampling This variable is the total column cloud cover (by area), averaged over 1 hour. Units:dimensionlessType:singleprecision floatingpoint vector Total column cloud cover, 18km sampling This variable is the total column cloud cover (by area), averaged over the time taken to advect the model's horizontal resolution (max 1 hour, min 10 minutes). Units:dimensionlessType:singleprecision floatingpoint vector Number of radar pixels, 1 hour sampling This variable is the number of radar pixels used to derive the cloud fractions by area and volume, for 1 hour sampling. Units:dimensionlessType:singleprecision floatingpoint array Number of radar pixels, 18km sampling This variable is the number of radar pixels used to make the cloud fractions by area and volume, averaging over the time taken to advect 1 model grid box, using model winds. Units:dimensionlessType:singleprecision floatingpoint array Model cloud fraction
Type:singleprecision floatingpoint array Model ice water content
Type:singleprecision floatingpoint array Model liquid water content
Type:singleprecision floatingpoint array Model cloud fraction by volume with undetectable cirrus removed using best guess of radar sensitivity This variable is model cloud fraction by volume, filtered to remove ice cloud deemed to be too tenuous to be detected by the radar. The best guess of the radar sensitivity has been used, and the spread of IWC across the grid box assumed to be described by a gamma distribution (Hogan and Illingworth 2003). Units:dimensionlessType:singleprecision floatingpoint array Model cloud fraction by volume with undetectable cirrus removed assuming radar 3 dB more sensitive than best guess This variable is the same as "model_Cv_filtered" except that the sensitivity of the radar is taken to be 3 dB better. It therefore provides an approximate estimate of the uncertainty associated with the removal of undetectable ice clouds from the model. Units:dimensionlessType:singleprecision floatingpoint array Model cloud fraction by volume with undetectable cirrus removed assuming radar 3 dB less sensitive than best guess This variable is the same as "model_Cv_filtered" except that the sensitivity of the radar is taken to be 3 dB worse. It therefore provides an approximate estimate of the uncertainty associated with the removal of undetectable ice clouds from the model. Units:dimensionlessType:singleprecision floatingpoint array Model ice water content with undetectable cirrus removed using best guess of radar sensitivity This variable is model ice water content, filtered to remove ice cloud deemed to be too tenuous to be detected by the radar. The best guess of the radar sensitivity has been used, and the spread of IWC across the grid box assumed to be described by a gamma distribution (Hogan and Illingworth 2003). Units:kg m^{3}Type:singleprecision floatingpoint array Model ice water content with undetectable cirrus removed assuming radar 3 dB more sensitive than best guess This variable is the same as "model_iwc_filtered" except that the sensitivity of the radar is taken to be 3 dB better. It therefore provides an approximate estimate of the uncertainty associated with the removal of undetectable ice clouds from the model. Units:kg m^{3}Type:singleprecision floatingpoint array Model ice water content with undetectable cirrus removed assuming radar 3 dB less sensitive than best guess This variable is the same as "model_iwc_filtered" except that the sensitivity of the radar is taken to be 3 dB worse. It therefore provides an approximate estimate of the uncertainty associated with the removal of undetectable ice clouds from the model. Units:kg m^{3}Type:singleprecision floatingpoint array These pages are maintained by . 