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The kasacr PCM process executed by the sacr3 binary reads in kasacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The kasacr PCM process executed by the sacr3 binary reads in kasacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The kasacr PCM process executed by the sacr3 binary reads in kasacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The kasacr PCM process executed by the sacr3 binary reads in kasacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
The wsacr PCM process executed by the sacr3 binary reads in wsacr.00 data and produces CF/Radial compliant NetCDF files for each of the radar operational scanning modes. This incorporates raw data from the radar, as well as scientifically important base derived parameters that affect interpretation of the data.
SACR-ADV-QVP provides a quasi-vertical representation of azimuthally averaged polarimetric variables to reveal important signatures in ice and mixed-phase clouds. SACR-ADV-QVP is produced using a sequence of plan-position-indicator (PPI) scans, which typically covers 3 different elevation angles and is repeated every 30 minutes. The scientific basis of the algorithm is described in Ryzhkov et al. (2016). The SACR2CORR VAP generates the main inputs of this VAP. They include corrected reflectivity, differential reflectivity, spectrum width, differential phase, linear depolarization ratio, and correlation coefficient. This VAP outputs a daily NetCDF file containing quasi-vertical profiles of all aforementioned polarimetric variables every time the PPI scan strategy is performed (this could result an irregular time stamp).
SACR-ADV-3D3C remaps the outputs of SACRCORR for cross-wind range-height indicator (CW-RHI) scans to a Cartesian grid and reports reflectivity CFAD and best estimate domain averaged cloud fraction. The final output is a single NetCDF file containing all aforementioned corrected radar moments remapped on a 3-D Cartesian grid, the SACR reflectivity CFAD, a profile of best estimate cloud fraction, a profile of maximum observable x-domain size (xmax), a profile time to horizontal distance estimate and a profile of minimum observable reflectivity (dBZmin).
SACR-ADV-QVP provides a quasi-vertical representation of azimuthally-averaged polarimetric variables. These profiles may be useful to reveal important signatures in ice and mixed-phase clouds. The SACR-ADV-QVP is produced using a sequence of plan-position-indicator (PPI) scans, which typically covers 3 different elevation angles and is repeated every 30 minutes. The scientific basis and description of the algorithm is described by Ryzhkov et al. (2016). The primary inputs for the current quick-look form of this VAP are those from the uncalibrated SACR reflectivity factor and differential reflectivity fields, whereas spectrum width, differential phase, linear depolarization ratio, and correlation coefficient fields are not biased by radar miscalibration. Processing includes a light filtering procedure using polarimetric measureands to mitigate the most pronounced contamination from ground clutter and insects. This VAP outputs a daily NetCDF file containing quasi-vertical profiles of all aforementioned polarimetric variables every time the PPI scan strategy is performed (this could result an irregular time stamp).
The data set contains physical retrievals of PWV and cloud LWP retrieved from MWR3C measurements during the MAGIC campaign. Additional data used in the retrieval process include radiosondes and ceilometer. The retrieval is based on an optimal estimation technique that starts from a first guess and iteratively repeats the forward model calculations until a predefined convergence criterion is satisfied. The first guess is a vector of [PWV,LWP] from the neural network retrieval fields in the netcdf file. When convergence is achieved the 'a posteriori' covariance is computed and its square root is expressed in the file as the retrieval 1-sigma uncertainty. The closest radiosonde profile is used for the radiative transfer calculations and ceilometer data are used to constrain the cloud base height. The RMS error between the brightness temperatures is computed at the last iterations as a consistency check and is written in the last column of the output file.
ACSM instrument measure mass loading (ug/m3) of non-refractory aerosol particles particularly organics, sulfate, chlorides, ammonium, and nitrates in real-time. The instrument is run autonomously at various ARM sites at time resolution equal to 30 minutes. Different data products are developed. The raw data (.itx and .asc) files are ingested to produce the.a0 product - the first netCDF file. These raw files are used by the mentor to calculate the mentor processed mass loadings. The .a0 files are used to develop the .b1 level product. The .b1 level data is further integrated with mentor processed data to produce .c0 level data product.