Introduction
Motivation
Chilbolton Observatory is a world-class radar facility for
meteorological research. However, a substantial barrier to more
widespread use of Chilbolton radar data is the fact that it is not
routinely available in a standard data format with all of the
processing issues, about which the the average meteorological user
knows nothing, taken care of. This is particularly true in the case of
cloud radar data, for which it is essential to perform accurate `noise
subtraction' if anything like the maximum sensitivity of the
instrument is to be realised. This collection of utilities provides
the ability to convert data stored in the in-house Chilbolton radar
format to a form that is easy to read using standard data-analysis
packages (such as matlab and IDL), while also doing all the necessary
processing. It is also possible to produce quicklooks of the processed
data.
Features
The processing options available to the programs chil2a,
chil2nc, chilplot and loadchil are as follows:
General
- Averaging over gates and rays; this is particularly useful for
cloud radar data which is recorded at a much higher temporal
resolution (around 1 second) than is often required (around 1 minute),
and affords greater sensitivity. Z is averaged in a true linear sense.
- Correction of the various parameters using specified calibration
values.
- (Re)calculation of range calibration using a different range
offset. This is typically used with cloud radar data for which the
recording starts before the pulse has gone out, and is now not range
calibrated at all.
- Ability to read raw (little endian) data files. This enables near
real-time radar images to be created for use on the web.
Scanning data
- Subtraction of the noise contributions from Z, ZDR and LDR using
the noise figures of the H, V and cross-polar channels. This is
essential if these parameters are to be used at low signal to noise
ratios, and also sets the `clear-sky' regions to no signal.
- Simple rejection of ground clutter using LDR.
Cloud data
- Output of data by day rather than by raster.
- Noise subtraction using gates from the top of the ray to
characterise the magnitude of the noise.
- Noise subtraction but taking account of interference by an
oscillator in the received rays by using the gates at the top of the
ray to characterise the shape of the oscillation. If this is not done
for data from the Galileo radar then anomalous lines of pixel-width
cloud are apparent in the processed data.
- Removal of vertically-isolated pixels: cleans up most remaining
anomalous lines.
- Simple ground clutter removal using v and sigma_v to find a
stationary signal with a narrow spectral width.
- Rejection of `range-glitched' rays, which sometimes occur with the
Galileo radar when the transmitter and receiver get out of sync.
- Rejection of rays when the radar is recording in cloud mode but is
not vertically pointing.