pyrad.proc#
Description
Dataset processing (pyrad.proc)#
Initiate the dataset processing.
Auxiliary functions#
|
Maps the dataset type into its processing function and data set format associated. |
|
Dummy function that returns the initial input data set |
|
Dummy function that allows to save the entire radar object |
|
Obtains radar data at a fixed range |
|
For each azimuth-elevation gets the data within a fixed range span and computes a user-defined statistic: mean, min, max, mode, median |
|
Obtains the radar data at a region of interest defined by a TRT file or by the user. |
|
keep only data within a region of interest and mask anything else |
|
Obtains the radar data at a region of interest defined by a TRT file or by the user. |
|
Averages radar data in azimuth obtaining and RHI as a result |
|
Applies a moving azimuthal average to the radar data |
|
Resamples the radar data to mimic another radar with different geometry and antenna pattern |
|
Function to convert polar data into a Cartesian grid |
Gridded data functions#
|
Dummy function that returns the initial input data set |
|
Puts the radar data in a regular grid |
|
Obtains the grid data at a point location. |
|
Obtains the grid data at a point location. |
|
computes the temporal statistics of a field |
|
computes temporal statistics of a field |
|
computes rainfall accumulation fields |
|
Computes the 2D texture of a gridded field |
|
Computes grid field differences |
|
Mask data. |
|
Normalize the data by the sinus of the sun elevation. |
|
Masks all pixels that are not of the class specified in keyword pixel_type |
Spectral data functions#
|
Dummy function that returns the initial input data set |
|
Obtains the spectra or IQ data at a point location. |
|
Function to filter the 0-Doppler line bin and neighbours of the Doppler spectra |
|
Filter the noise of the Doppler spectra by clipping any data below the noise level plus a margin |
|
Filter Doppler spectra as a function of spectral RhoHV |
|
Function to average the spectra over the rays. |
|
Computes the spectral power |
|
Computes the spectral noise |
|
Computes the spectral phase |
|
Computes spectral reflectivity |
Computes spectral differential reflectivity |
|
|
Computes the spectral differential phase |
|
Computes the spectral RhoHV |
|
Processing of automatic sun scans for monitoring purposes of the radar system. |
|
Computes the polarimetric variables from the complex spectra |
|
Computes the noise power from the spectra |
|
Computes reflectivity from the spectral reflectivity |
|
Computes differential reflectivity from the horizontal and vertical spectral reflectivity |
|
Computes the differential phase from the spectral differential phase and the spectral reflectivity |
|
Computes RhoHV from the complex spectras |
|
Compute the Doppler velocity from the spectral reflectivity |
|
Compute the Doppler spectrum width from the spectral reflectivity |
|
Compute the Doppler spectrum width from the spectral reflectivity |
IQ data functions#
|
Dummy function that returns the initial input data set |
|
Computes the polarimetric variables from the IQ data |
|
Computes reflectivity from the IQ data |
|
Computes the statistical test one lag fluctuation from the horizontal or vertical IQ data |
|
Computes the statistical test two lag fluctuation from the horizontal or vertical IQ data |
|
Computes the wide band noise from the horizontal or vertical IQ data |
|
Computes differential reflectivity from the horizontal and vertical IQ data |
|
Computes the mean phase from the horizontal or vertical IQ data |
|
Computes the differential phase from the horizontal and vertical IQ data |
|
Computes RhoHV from the horizontal and vertical IQ data |
|
Compute the Doppler velocity from the spectral reflectivity |
|
Compute the Doppler spectrum width from the spectral reflectivity |
|
Compute the Doppler spectra form the IQ data with a Fourier transform |
Echo classification and filtering#
|
identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Precipitation |
|
identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Birds |
|
Converts clutter exit code from rad4alp into pyrad echo ID |
|
Converts velocity status from lidar data into pyrad echo ID |
|
Converts MF hydrometeor classification into pyrad echo ID |
|
Converts the hydrometeor classification from Météo France to that of MeteoSwiss |
|
Masks all echo types that are not of the class specified in keyword echo_type |
|
Collects the fields necessary to compute the Cumulative Distribution Function |
|
filters out low SNR echoes |
|
filters out rays gates with low visibility and corrects the reflectivity |
|
filters out all available moments based on specified upper/lower bounds for moments based on the Py-ART gatefilter. |
|
filters out gates which are outliers respect to the surrounding |
|
Masks all echo types that have been identified as non-biological by vol2bird |
|
Adds filter on range gate values to the vol2bird filter |
|
Classifies precipitation echoes |
|
Computes centroids for the semi-supervised hydrometeor classification |
|
Detects the melting layer |
|
filters out range gates that could not be used for Doppler velocity estimation |
|
Detects ZDR columns |
Phase processing and attenuation correction#
|
corrects phidp of the system phase |
|
corrects phidp of the system phase and smoothes it using one window |
|
corrects phidp of the system phase and smoothes it using one window |
|
Computes specific differential phase using a piecewise least square method |
|
Computes specific differential phase using a piecewise least square method |
|
Computes specific differential phase and differential phase using the method developed by Vulpiani et al. The data is assumed to be clutter free and monotonous. |
|
Computes specific differential phase and differential phase using the Kalman filter as proposed by Schneebeli et al. The data is assumed to be clutter free and continous. |
|
Estimates PhiDP and KDP using the method by Maesaka. |
|
Estimates PhiDP and KDP using a linear programming algorithm. |
|
Computes specific attenuation and specific differential attenuation using the Z-Phi method and corrects reflectivity and differential reflectivity |
Monitoring, calibration and noise correction#
|
Corrects a bias on the data |
|
identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Precipitation |
|
Keeps only suitable data to evaluate the 80 percentile of RhoHV in rain |
|
Keeps only suitable data to evaluate the differential reflectivity in moderate rain or precipitation (for vertical scans) |
|
Keeps only suitable data to evaluate the differential reflectivity in snow |
|
estimates the system differential phase offset at each ray |
|
monitoring of the radar using sun hits |
|
Computes specific differential phase and differential phase in rain using the selfconsistency between Zdr, Zh and KDP |
|
Estimates the reflectivity bias by means of the selfconsistency algorithm by Gourley |
|
Estimates the reflectivity bias by means of the selfconsistency algorithm by Gourley |
|
computes the average and standard deviation of data. |
|
computes the frequency of occurrence of data. |
|
computes the frequency of occurrence over a long period of time by adding together shorter periods |
|
computes monitoring statistics |
|
computes ground clutter monitoring statistics |
|
computes the temporal mean of a field |
|
computes the temporal mean of a field weighted by the reflectivity |
|
computes a flag field describing the conditions of the data used while averaging |
|
computes the temporal statistics of a field |
|
computes the temporal mean of a field |
|
Find colocated gates within two radars |
|
intercomparison between two radars at co-located gates. |
|
intercomparison between the average reflectivity of two radars |
|
Computes the field difference between RADAR001 and radar002, i.e. RADAR001-RADAR002. |
|
intercomparison between two radars |
Retrievals#
|
Computes the Clutter Correction Ratio, i.e. the ratio between the signal without Doppler filtering and the signal with Doppler filtering. |
|
Computes the signal power in dBm |
|
Computes the radar cross-section (assuming a point target) from radar reflectivity. |
|
Computes the radar cross-section (assuming a point target) from radar reflectivity by first computing the received power and then the RCS from it. |
|
Computes the radial noise from the signal power using the Hildebrand and Sekhon 1974 method |
|
Computes the radial noise from the signal power using the Ivic 2013 method |
|
Computes SNR |
|
Computes L parameter (logarithmic cross-correlation ratio) |
|
Computes approximation of Circular Depolarization Ratio |
|
Computes the vertical or horizontal reflectivity from ZDR and the reflectivity at the orthogonal polarization |
|
Estimates rainfall rate from polarimetric moments |
|
Computes rainfall accumulation fields |
|
Computes the volumetric reflectivity eta in 10log10(cm^2 km^-3) |
|
Computes the bird density from the volumetric reflectivity |
|
Computes the vertical profile of reflectivity using the Meteo-France operational algorithm |
Doppler processing#
|
Computes turbulence from the Doppler spectrum width and reflectivity using the PyTDA package |
|
Dealiases the Doppler velocity field using the 4DD technique from Curtis and Houze, 2001 |
|
Dealiases the Doppler velocity field using a region based algorithm |
|
Dealiases the Doppler velocity field using multi-dimensional phase unwrapping |
|
Estimates the radial velocity respect to the radar from the wind velocity |
|
Estimates the horizontal or vertical component of the wind from the radial velocity |
|
Estimates the wind shear from the wind velocity |
|
Estimates the wind shear from the wind velocity of lidar scans |
|
Estimates vertical wind profile using the VAD (velocity Azimuth Display) technique |
|
Estimates horizontal wind speed and direction with a multi-doppler approach This method uses the python package pyDDA |
Time series functions#
|
Obtains the radar data at a point location. |
|
Obtains the radar data at multiple points. |
|
Computes quasi vertical profiles, by averaging over height levels PPI data. |
|
Computes range defined quasi vertical profiles, by averaging over height levels PPI data. |
|
Computes slanted vertical profiles, by averaging over height levels PPI data. |
|
Computes enhanced vertical profiles, by averaging over height levels PPI data. |
|
Produces time height radar objects at a point of interest defined by latitude and longitude. |
|
Produces time series along a particular antenna coordinate |
Trajectory functions#
|
Return trajectory |
|
Return time series according to trajectory |
|
Process a new array of data volumes considering a plane trajectory. |
|
Return time series according to lightning trajectory |
|
Processes data according to TRT trajectory |
|
Gets the TRT cell contour corresponding to each radar volume |
icon data#
|
Gets icon data and put it in radar coordinates |
|
Gets icon data and put it in radar coordinates using look up tables computed or loaded when initializing |
|
Gets the icon indices corresponding to each icon coordinates |
|
Gets iso0 degree data in HZT format and put it in radar coordinates |
|
Gets HZT data and put it in radar coordinates using look up tables computed or loaded when initializing |
|
Gets the HZT indices corresponding to each HZT coordinates |
|
Gets iso0 degree data in text format and put it in radar coordinates. |
|
Gets iso0 degree data in GRIB format and put it in radar coordinates. |
|
Gets icon data and put it in radar coordinates using look up tables |
DEM data#
|
Gets DEM data and put it in radar coordinates |
|
Gets the visibility in percentage from the minimum visible elevation. |
|
Computes ground clutter RCS, radar visibility and many others using the GECSX algorithmn translated from IDL into python |
Functions
|
Maps the dataset type into its processing function and data set format associated. |
|
Compute the Doppler velocity from the spectral reflectivity |
|
Compute the Doppler velocity from the spectral reflectivity |
|
Compute the Doppler spectrum width from the spectral reflectivity |
|
Compute the Doppler spectrum width from the spectral reflectivity |
|
Computes specific attenuation and specific differential attenuation using the Z-Phi method and corrects reflectivity and differential reflectivity |
|
Averages radar data in azimuth obtaining and RHI as a result |
|
Computes the bird density from the volumetric reflectivity |
|
identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Birds |
|
Computes the Clutter Correction Ratio, i.e. the ratio between the signal without Doppler filtering and the signal with Doppler filtering. |
|
Collects the fields necessary to compute the Cumulative Distribution Function |
|
Computes approximation of Circular Depolarization Ratio |
|
Computes centroids for the semi-supervised hydrometeor classification |
|
Converts clutter exit code from rad4alp into pyrad echo ID |
|
Find colocated gates within two radars |
|
Corrects a bias on the data |
|
identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Precipitation |
|
corrects phidp of the system phase |
|
Estimates horizontal wind speed and direction with a multi-doppler approach This method uses the python package pyDDA |
|
Dealiases the Doppler velocity field using the 4DD technique from Curtis and Houze, 2001 |
|
Dealiases the Doppler velocity field using a region based algorithm |
|
Dealiases the Doppler velocity field using multi-dimensional phase unwrapping |
|
Gets DEM data and put it in radar coordinates |
|
Computes the differential phase from the spectral differential phase and the spectral reflectivity |
|
Computes the differential phase from the horizontal and vertical IQ data |
|
Computes differential reflectivity from the horizontal and vertical spectral reflectivity |
|
Computes differential reflectivity from the horizontal and vertical IQ data |
|
Masks all echo types that are not of the class specified in keyword echo_type |
|
identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Precipitation |
|
estimates the system differential phase offset at each ray |
|
Computes enhanced vertical profiles, by averaging over height levels PPI data. |
|
Compute the Doppler spectra form the IQ data with a Fourier transform |
|
Computes the field difference between RADAR001 and radar002, i.e. RADAR001-RADAR002. |
|
Function to filter the 0-Doppler line bin and neighbours of the Doppler spectra |
|
filters out low SNR echoes |
|
Filter the noise of the Doppler spectra by clipping any data below the noise level plus a margin |
|
Filter Doppler spectra as a function of spectral RhoHV |
|
filters out range gates that could not be used for Doppler velocity estimation |
|
filters out rays gates with low visibility and corrects the reflectivity |
|
Masks all echo types that have been identified as non-biological by vol2bird |
|
Obtains radar data at a fixed range |
|
For each azimuth-elevation gets the data within a fixed range span and computes a user-defined statistic: mean, min, max, mode, median |
|
Adds filter on range gate values to the vol2bird filter |
|
filters out all available moments based on specified upper/lower bounds for moments based on the Py-ART gatefilter. |
|
computes ground clutter monitoring statistics |
|
Computes ground clutter RCS, radar visibility and many others using the GECSX algorithmn translated from IDL into python |
|
Puts the radar data in a regular grid |
|
Computes grid field differences |
|
Mask data. |
|
Obtains the grid data at a point location. |
|
Obtains the grid data at a point location. |
|
computes rainfall accumulation fields |
|
Computes the 2D texture of a gridded field |
|
computes the temporal statistics of a field |
|
computes temporal statistics of a field |
|
Converts MF hydrometeor classification into pyrad echo ID |
|
Converts the hydrometeor classification from Météo France to that of MeteoSwiss |
|
Classifies precipitation echoes |
|
Gets iso0 degree data in HZT format and put it in radar coordinates |
|
Gets the HZT indices corresponding to each HZT coordinates |
|
Gets HZT data and put it in radar coordinates using look up tables computed or loaded when initializing |
|
Gets icon data and put it in radar coordinates |
|
Gets the icon indices corresponding to each icon coordinates |
|
Gets icon data and put it in radar coordinates using look up tables computed or loaded when initializing |
|
Gets icon data and put it in radar coordinates using look up tables |
|
Compute the Doppler spectrum width from the spectral reflectivity |
|
intercomparison between two radars at co-located gates. |
|
intercomparison between two radars |
|
intercomparison between the average reflectivity of two radars |
|
Gets iso0 degree data in GRIB format and put it in radar coordinates. |
|
Gets iso0 degree data in text format and put it in radar coordinates. |
|
Computes specific differential phase using a piecewise least square method |
|
Computes specific differential phase using a piecewise least square method |
|
keep only data within a region of interest and mask anything else |
|
Computes L parameter (logarithmic cross-correlation ratio) |
|
Computes the mean phase from the horizontal or vertical IQ data |
|
Detects the melting layer |
|
computes monitoring statistics |
|
Applies a moving azimuthal average to the radar data |
|
Obtains the radar data at multiple points. |
|
Computes the noise power from the spectra |
|
Normalize the data by the sinus of the sun elevation. |
|
computes the frequency of occurrence of data. |
|
computes the frequency of occurrence over a long period of time by adding together shorter periods |
|
filters out gates which are outliers respect to the surrounding |
|
Computes specific differential phase and differential phase using the Kalman filter as proposed by Schneebeli et al. The data is assumed to be clutter free and continous. |
|
Estimates PhiDP and KDP using the method by Maesaka. |
|
Computes specific differential phase and differential phase using the method developed by Vulpiani et al. The data is assumed to be clutter free and monotonous. |
|
Estimates PhiDP and KDP using a linear programming algorithm. |
|
Masks all pixels that are not of the class specified in keyword pixel_type |
|
Obtains the radar data at a point location. |
|
Computes the polarimetric variables from the complex spectra |
|
Computes the polarimetric variables from the IQ data |
|
Computes quasi vertical profiles, by averaging over height levels PPI data. |
|
Resamples the radar data to mimic another radar with different geometry and antenna pattern |
|
Computes the radial noise from the signal power using the Hildebrand and Sekhon 1974 method |
|
Computes the radial noise from the signal power using the Ivic 2013 method |
|
Estimates the radial velocity respect to the radar from the wind velocity |
|
Computes rainfall accumulation fields |
|
Estimates rainfall rate from polarimetric moments |
|
Dummy function that returns the initial input data set |
|
Dummy function that returns the initial input data set |
|
Dummy function that returns the initial input data set |
|
Dummy function that returns the initial input data set |
|
Computes the radar cross-section (assuming a point target) from radar reflectivity. |
|
Computes the radar cross-section (assuming a point target) from radar reflectivity by first computing the received power and then the RCS from it. |
|
Computes the vertical or horizontal reflectivity from ZDR and the reflectivity at the orthogonal polarization |
|
Computes reflectivity from the spectral reflectivity |
|
Computes reflectivity from the IQ data |
|
Computes RhoHV from the complex spectras |
|
Computes RhoHV from the horizontal and vertical IQ data |
|
Keeps only suitable data to evaluate the 80 percentile of RhoHV in rain |
|
Obtains the radar data at a region of interest defined by a TRT file or by the user. |
|
Obtains the radar data at a region of interest defined by a TRT file or by the user. |
|
Computes range defined quasi vertical profiles, by averaging over height levels PPI data. |
|
Dummy function that allows to save the entire radar object |
|
Estimates the reflectivity bias by means of the selfconsistency algorithm by Gourley |
|
Estimates the reflectivity bias by means of the selfconsistency algorithm by Gourley |
|
Computes specific differential phase and differential phase in rain using the selfconsistency between Zdr, Zh and KDP |
|
Computes the signal power in dBm |
|
corrects phidp of the system phase and smoothes it using one window |
|
corrects phidp of the system phase and smoothes it using one window |
|
Computes SNR |
|
Function to average the spectra over the rays. |
|
Obtains the spectra or IQ data at a point location. |
|
Computes the spectral differential phase |
Computes spectral differential reflectivity |
|
|
Computes the spectral noise |
|
Computes the spectral phase |
|
Computes the spectral power |
|
Computes spectral reflectivity |
|
Computes the spectral RhoHV |
|
Computes the statistical test one lag fluctuation from the horizontal or vertical IQ data |
|
Computes the statistical test two lag fluctuation from the horizontal or vertical IQ data |
|
monitoring of the radar using sun hits |
|
Processing of automatic sun scans for monitoring purposes of the radar system. |
|
Computes slanted vertical profiles, by averaging over height levels PPI data. |
|
computes the temporal mean of a field |
|
computes a flag field describing the conditions of the data used while averaging |
|
computes the average and standard deviation of data. |
|
Produces time height radar objects at a point of interest defined by latitude and longitude. |
|
computes the temporal statistics of a field |
|
computes the temporal mean of a field |
|
Process a new array of data volumes considering a plane trajectory. |
|
Return time series according to trajectory |
|
Return time series according to lightning trajectory |
|
Processes data according to TRT trajectory |
|
Gets the TRT cell contour corresponding to each radar volume |
|
Return trajectory |
|
Produces time series along a particular antenna coordinate |
|
Computes turbulence from the Doppler spectrum width and reflectivity using the PyTDA package |
|
Estimates vertical wind profile using the VAD (velocity Azimuth Display) technique |
|
Gets the visibility in percentage from the minimum visible elevation. |
|
Computes the volumetric reflectivity eta in 10log10(cm^2 km^-3) |
|
Function to convert polar data into a Cartesian grid |
|
Computes the vertical profile of reflectivity using the Meteo-France operational algorithm |
|
Converts velocity status from lidar data into pyrad echo ID |
|
Computes the wide band noise from the horizontal or vertical IQ data |
|
computes the temporal mean of a field weighted by the reflectivity |
|
Estimates the horizontal or vertical component of the wind from the radial velocity |
|
Estimates the wind shear from the wind velocity |
|
Estimates the wind shear from the wind velocity of lidar scans |
|
Detects ZDR columns |
|
Keeps only suitable data to evaluate the differential reflectivity in moderate rain or precipitation (for vertical scans) |
|
Keeps only suitable data to evaluate the differential reflectivity in snow |