CAPS AVHRR Processing

See also the overview document.

Cognac CAPS Installation

• BWidget-1.8
• pv1.3 (parameter value language in tcl)
• tkcon-2.4
• tkimg-1.3
• libhdf-4.2
• libnetcdf-3.6.1
  

CAPS Quickstart on Cognac

$ module load caps  # This sets $CAPS to installation location, makes path adjustments, etc]
$ cp $CAPS/.[tw]* ~ # Do this once only - sets up .wishrc, .tclshrc etc in your $HOME
$ getcapsnav.sh     # Once a day before processing say.  Wait for update to complete
$ caps_l1b.tcl [input hrpt] [output L1B hdf]
$ caps_quicklook.tcl [input L1B hdf]

caps_amc.tcl runs the AllModCons modular processing layer that sites on top of CAPS and NAP. It currently pulls in the following AMC config:

$ cat amc_newhdf.cfg
#depend_dbg
#need_dbg
#hrpt_file ah15_20000101_095809_eoc.asda.784889
angle_step 1
delete_hdf Y
chunk_lines 4000
hdf_attributes {{reception_station  c8   "PERTH CURTIN"}}
hdf_avhrrattr
# X,Y are remapped coordinates, to subsample inputs use line_step,pixel_step
#step_x 0.05
#step_y 0.05
line_step 1
pixel_step 1
# For N < N15
#re_outputs {^(normalisedReflectance_avhrr_(1|2)|brightnessTemperature_avhrr_(3b|4|5)|Latitude|Longitude|(sun|satellite)(Azimuth|Zenith)Grid|cloud_mask)$}
# For N >= N15
re_outputs {^(normalisedReflectance_avhrr_(1|2|3a)|brightnessTemperature_avhrr_(3b|4|5)|Latitude|Longitude|(sun|satellite)(Azimuth|Zenith)Grid|cloud_mask)$}
@getAVHRR
@geonav
@angles
@calSol
@calTIR
@bt
@expandGrid
@isLand
@cloudAVHRR
# Leave this out to NOT apply cloud mask
#@mask_out_cloud
@putHDF

CAPS GUI

After installing you .wishrc startup files previously, you'll simply be able to run wish and it will start. This is extremely handy. You can read both raw HRPT and L1B HDF using this GUI.

CAPS Cloud Mask

The @cloudAVHRR uses the CLAVR algorithm by Stowe et al (1999):

An algorithm for the remote sensing of global cloud cover using multispectral radiance measurements from the Advanced Very High Resolution Radiometer (AVHRR) on board National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites has been developed. The CLAVR-1 (Clouds from AVHRR-Phase I) algorithm classifies 2 × 2 pixel arrays from the Global Area Coverage (GAC) 4-km-resolution archived database into CLEAR, MIXED, and CLOUDY categories. The algorithm uses a sequence of multispectral contrast, spectral, and spatial signature threshold tests to perform the classification. The various tests and the derivation of their thresholds are presented. CLAVR-1 has evolved through experience in applying it to real-time NOAA-11 data, and retrospectively through the NOAA AVHRR Pathfinder Atmosphere project, where 16 years of data have been reprocessed into cloud, radiation budget, and aerosol climatologies. The classifications are evaluated regionally with image analysis, and it is concluded that the algorithm does well at classifying perfectly clear pixel arrays, except at high latitudes in their winter seasons. It also has difficulties with classifications over some desert and mountainous regions and when viewing regions of ocean specular reflection. Generally, the CLAVR-1 fractional cloud amounts, when computed using a statistically equivalent spatial coherence method, agree to within about 0.05–0.10 of image/analyst estimates on average. There is a tendency for CLAVR-1 to underestimate cloud amount when it is large and to overestimate it when small.

How to interpret the CAPS CLAVR cloud mask.


All the little acronyms and test names come from

 Stowe, L.L, Davis, P.A. & McClain, E.P.
 Scientific Basis and Initial Evalation of the CLAVR-1
 Global Clear/Cloud Classification
 Algorithm for the Advanced Very High Resolution Radiometer
 J. Atmos. Oceanic Technol., vol 16, June 1999, pp 656-681.

The algorithm works in four phases depending on land/ocean and day/night.
You should not see any of the prestore or ptrestore flags in the
output as they are intermediate flags which are replaced by something
more definitive.

In general, values < 12 (ie 0-11) should be clear pixels.

Basic Starting Mask Values

    ocean/night = 0
    ocean/day   = 1
    land/night  = 2
    land/day    = 3


Land Day

    clear_land_day = 3
    rclear = 8              Restored - clear
    mcrgct = 100            Reflectance Gross Cloud Test (RGCT)
    mrut = 101              Reflectance Uniformity Test (RUT)
    mcrrct = 102            Reflectance Ratio Cloud Test (RRCT)
    mcfmft = 103            Four Minus Five Test  (FMFT)
    mctgct = 104            Thermal Gross Cloud Test (TGCT)
    mc3at = 105             Channel 3 Albedo Test  (C3AT)
    mtut = 106              Thermal Uniformity Test (TUT)
    prestore = 110          Potentially restorable
    ptrestore = 111         Potential Thermal Uniformity Restoral 

Land Night

    clear_land_night = 2
    rcIce = 9               Restored Clear (Ice)
    rcLand = 11             Restored Clear (Land)
    mcrgct = 130            Reflectance Gross Cloud Test (RGCT)
    mtut = 131              Thermal Uniformity Test (TUT)
    mcrrct = 132            Reflectance Ratio Cloud Test (RRCT)
    mcfmft = 133            Four Minus Five Test  (FMFT)
    mctgct = 134            Thermal Gross Cloud Test (TGCT)
    mculst = 135            Uniform Low Stratus Test
    prestore = 136          Potentially restorable
    mccirt = 139            Nightime cirrus test

Ocean Day

    clear_ocean_day = 1
    rcIce = 9               Restored Clear (Ice)
    rcOcean = 10            Restored Clear (Ocean)
    mcrgct = 120            Reflectance Gross Cloud Test (RGCT)
    mtut = 121              Thermal Uniformity Test (TUT)
    mcrrct = 122            Reflectance Ratio Test (RRCT)
    mcfmft = 123            Four Minus Five Test  (FMFT)
    mctgct = 124            Thermal Gross Cloud Test (TGCT)
    mc3at = 125             Channel 3 Albedo Test  (C3AT)
    mrut = 126              Reflectance Uniformity Test (RUT)
    prestore = 128          Potentially restorable
    prestore1 = 129         Another kind of potential restoration

Ocean Night

    clear_ocean_night = 0
    rcIce = 9               Restored Clear (Ice)
    rcOcean = 10            Restored Clear (Ocean)
    mcrgct = 140            Reflectance Gross Cloud Test (RGCT)
    mtut = 141              Thermal Uniformity Test (TUT)
    mcrrct = 142            Reflectance Ratio Test (RRCT)
    mcfmft = 143            Four Minus Five Test  (FMFT)
    mctgct = 144            Thermal Gross Cloud Test (TGCT)
    mculst = 145            Uniform Low Stratus
    mccirt = 149            Nightime cirrus test
    prestore = 128          Potentially restorable

Sourced from CAPS/AMC team.