List of pyrad datasets separated by dataset type#
VOL#
ATTENUATION#
- description
Computes specific attenuation and specific differential attenuation using the Z-Phi method and corrects reflectivity and differential reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
- ATT_METHODfloat. Dataset keyword
The attenuation estimation method used. One of the following: ZPhi, Philin. Default ZPhi
- fzlfloat. Dataset keyword
The default freezing level height. It will be used if no temperature field name is specified or the temperature field is not in the radar object. Default 2000.
- soundingstr. Dataset keyword
The nearest radiosounding WMO code (5 int digits). It will be used to compute the freezing level, if no temperature field name is specified, if the temperature field is in the radar object or if no freezing_level is explicitely defined.
AZI_AVG#
- description
Averages radar data in azimuth obtaining and RHI as a result
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- anglefloat or None. Dataset keyword
The center angle to average. If not set or set to -1 all available azimuth angles will be used
- delta_azifloat. Dataset keyword
The angle span to average. If not set or set to -1 all the available azimuth angles will be used
- avg_typestr. Dataset keyword
Average type. Can be mean or median. Default mean
- nvalid_minint. Dataset keyword
the minimum number of valid points to consdier the average valid. Default 1
- lin_transdict or None
A dictionary specifying which data types have to be transformed in linear units before averaging
MOVING_AZI_AVG#
- description
Applies a moving azimuthal average to the radar data
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- delta_azifloat. Dataset keyword
The angle span to average. Default 20
- avg_typestr. Dataset keyword
Average type. Can be mean or median. Default mean
- nvalid_minint. Dataset keyword
the minimum number of valid points to consdier the average valid. Default 1
- lin_transdict or None
A dictionary specifying which data types have to be transformed in linear units before averaging
BIAS_CORRECTION#
- description
Corrects a bias on the data
- parameters
- datatypestring. Dataset keyword
The data type to correct for bias
- biasfloat. Dataset keyword
The bias to be corrected [dB]. Default 0
BIRDS_ID#
- description
identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Birds
- parameters
- datatypelist of string. Dataset keyword
The input data types
BIRD_DENSITY#
- description
Computes the bird density from the volumetric reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
- sigma_birdfloat. Dataset keyword
The bird radar cross section
CCOR#
- description
Computes the Clutter Correction Ratio, i.e. the ratio between the signal without Doppler filtering and the signal with Doppler filtering
- parameters
- datatypelist of string. Dataset keyword
The input data types
CDF#
- description
Collects the fields necessary to compute the Cumulative Distribution Function
- parameters
- datatypelist of string. Dataset keyword
The input data types
CDR#
- description
Computes Circular Depolarization Ratio
- parameters
- datatypestring. Dataset keyword
The input data type
CLT_TO_SAN#
- description
Converts clutter exit code from rad4alp into pyrad echo ID
- parameters
- datatypelist of string. Dataset keyword
The input data types
ICON_LOOKUP#
- description
Gets icon data and put it in radar coordinates using look up tables computed or loaded when initializing
- parameters
- datatypestring. Dataset keyword
arbitrary data type
- lookup_tableint. Dataset keyword
if set a pre-computed look up table for the icon coordinates is loaded. Otherwise the look up table is computed taking the first radar object as reference
- regular_gridint. Dataset keyword
if set it is assume that the radar has a grid constant in time and therefore there is no need to interpolate the icon field in memory to the current radar grid
- icon_typestr. Dataset keyword
name of the icon field to process. Default TEMP
- icon_variableslist of strings. Dataset keyword
Py-art name of the icon fields. Default temperature
DEM#
- description
Gets DEM data and put it in radar coordinates
- parameters
- datatypestring. Dataset keyword
arbitrary data type
- keep_in_memoryint. Dataset keyword
if set keeps the COSMO data dict, the COSMO coordinates dict and the COSMO field in radar coordinates in memory. Default False
- regular_gridint. Dataset keyword
if set it is assume that the radar has a grid constant in time and there is no need to compute a new COSMO field if the COSMO data has not changed. Default False
- dem_fieldstr. Dataset keyword
name of the DEM field to process
- demfilestr. Dataset keyword
Name of the file containing the DEM data
DEALIAS_FOURDD#
- description
Dealiases the Doppler velocity field using the 4DD technique from Curtis and Houze, 2001
- parameters
- datatypestring. Dataset keyword
The input data type
- filtint. Dataset keyword
Flag controlling Bergen and Albers filter, 1 = yes, 0 = no.
- signint. Dataset keyword
Sign convention which the radial velocities in the volume created from the sounding data will will. This should match the convention used in the radar data. A value of 1 represents when positive values velocities are towards the radar, -1 represents when negative velocities are towards the radar.
DEALIAS_REGION#
- description
Dealiases the Doppler velocity field using a region based algorithm
- parameters
- datatypestring. Dataset keyword
The input data type
- interval_splitsint, optional
Number of segments to split the nyquist interval into when finding regions of similar velocity. More splits creates a larger number of initial regions which takes longer to process but may result in better dealiasing. The default value of 3 seems to be a good compromise between performance and artifact free dealiasing. This value is not used if the interval_limits parameter is not None.
- skip_between_rays, skip_along_rayint, optional
Maximum number of filtered gates to skip over when joining regions, gaps between region larger than this will not be connected. Parameters specify the maximum number of filtered gates between and along a ray. Set these parameters to 0 to disable unfolding across filtered gates.
- centeredbool, optional
True to apply centering to each sweep after the dealiasing algorithm so that the average number of unfolding is near 0. False does not apply centering which may results in individual sweeps under or over folded by the nyquist interval.
- nyquist_velfloat, optional
Nyquist velocity of the aquired radar velocity. Usually this parameter is provided in the Radar object intrument_parameters. If it is not available it can be provided as a keyword here.
DEALIAS_UNWRAP#
- description
Dealiases the Doppler velocity field using multi-dimensional phase unwrapping
- parameters
- datatypestring. Dataset keyword
The input data type
- unwrap_unit{‘ray’, ‘sweep’, ‘volume’}, optional
Unit to unwrap independently. ‘ray’ will unwrap each ray individually, ‘sweep’ each sweep, and ‘volume’ will unwrap the entire volume in a single pass. ‘sweep’, the default, often gives superior results when the lower sweeps of the radar volume are contaminated by clutter. ‘ray’ does not use the gatefilter parameter and rays where gates ared masked will result in poor dealiasing for that ray.
DOPPLER_VELOCITY#
- description
Compute the Doppler velocity from the spectral reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
DOPPLER_VELOCITY_IQ#
- description
Compute the Doppler velocity from the spectral reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
- directionstr
The convention used in the Doppler mean field. Can be negative_away or negative_towards
DOPPLER_WIDTH#
- description
Compute the Doppler spectrum width from the spectral reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
DOPPLER_WIDTH_IQ#
- description
Compute the Doppler spectrum width from the spectral reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
- subtract_noiseBool
If True noise will be subtracted from the signals
- lagint
Time lag used in the denominator of the computation
ECHO_FILTER#
- description
Masks all echo types that are not of the class specified in keyword echo_type
- parameters
- datatypelist of string. Dataset keyword
The input data types
- echo_typeint or list of ints
The type of echoes to keep: 1 noise, 2 clutter, 3 precipitation. Default 3
FIELDS_DIFF#
- description
Computes the field difference between RADAR001 and radar002, i.e. RADAR001-RADAR002. Assumes both radars have the same geometry
- parameters
- datatypelist of string. Dataset keyword
The input data types
FIXED_RNG#
- description
Obtains radar data at a fixed range
- parameters
- datatypelist of strings. Dataset keyword
The fields we want to extract
- rngfloat. Dataset keyword
The fixed range [m]
- RngTolfloat. Dataset keyword
The tolerance between the nominal range and the radar range
- ele_min, ele_max, azi_min, azi_maxfloats. Dataset keyword
The azimuth and elevation limits of the data [deg]
FIXED_RNG_SPAN#
- description
For each azimuth-elevation gets the data within a fixed range span and computes a user-defined statistic: mean, min, max, mode, median
- parameters
- datatypelist of strings. Dataset keyword
The fields we want to extract
- rmin, rmaxfloat. Dataset keyword
The range limits [m]
- ele_min, ele_max, azi_min, azi_maxfloats. Dataset keyword
The azimuth and elevation limits of the data [deg]
GATEFILTER#
- description
filters out all available moments based on specified upper/lower bounds for moments based on the Py-ART gatefilter. Every value below upper bound or above upper bound will be filtered. To ignore lower/upper bound enter an impossible value such as -9999 or 9999.
- parameters
- datatypelist of string. Dataset keyword
The input data types
- lower_boundslist of float
The list of lower bounds for every input data type
- upper_boundslist of float
The list of upper bounds for every input data type
GECSX#
- description
Computes ground clutter RCS, radar visibility and many others using the GECSX algorithmn translated from IDL into python
- parameters
- datatypelist of string. Dataset keyword
The input data types
- range_discretizationfloat. Dataset keyword
Range discretization used when computing the Cartesian visibility field the larger the better but the slower the processing will be
- az_discretizationfloat. Dataset keyword
Azimuth discretization used when computing the Cartesian visibility field, the larger the better but the slower the processing will be
- kefloat. Dataset keyword
Equivalent earth-radius factor used in the computation of the radar beam refraction
- atm_attfloat. Dataset keyword
One-way atmospheric refraction in db / km
- mosotti_kwfloat. Dataset keyword
Clausius-Mosotti factor K, depends on material (water) and wavelength for water = sqrt(0.93)
- raster_oversamplingint. Dataset keyword
The raster resolution of the DEM should be smaller than the range resolution of the radar (defined by the pulse length). If this is not the case, this keyword can be set to increase the raster resolution. The values for the elevation, sigma naught, visibility are repeated. The other values are recalculated. Values for raster_oversampling: 0 or undefined: No oversampling is done 1: Oversampling is done. The factor N is automatically calculated such that 2*dx/N < pulse length 2 or larger: Oversampling is done with this value as N
- sigma0_methodstring. Dataset keyword
Which estimation method to use, either ‘Gabella’ or ‘Delrieu’
- clipint. Dataset keyword
If set to true, the provided DEM will be clipped to the extent of the polar radar domain. Increases computation speed a lot but Cartesian output fields will be available only over radar domain
HYDROCLASS#
- description
Classifies precipitation echoes
- parameters
- datatypelist of string. Dataset keyword
The input data types
- HYDRO_METHODstring. Dataset keyword
The hydrometeor classification method. One of the following: SEMISUPERVISED, UKMO
- centroids_filestring or None. Dataset keyword
Used with HYDRO_METHOD SEMISUPERVISED. The name of the .csv file that stores the centroids. The path is given by [configpath]/centroids_hydroclass/ If None is provided default centroids are going to be used
- compute_entropybool. Dataset keyword
Used with HYDRO_METHOD SEMISUPERVISED. If true the entropy is computed and the field hydroclass_entropy is output
- output_distancesbool. Dataset keyword
Used with HYDRO_METHOD SEMISUPERVISED. If true the de-mixing algorithm based on the distances to the centroids is computed and the field proportions of each hydrometeor in the radar range gate is output
- vectorizebool. Dataset keyword
Used with HYDRO_METHOD SEMISUPERVISED. If true a vectorized version of the algorithm is used
- weightsarray of floats. Dataset keyword
Used with HYDRO_METHOD SEMISUPERVISED. The list of weights given to each variable
- hydropathstring. Dataset keyword
Used with HYDRO_METHOD UKMO. Directory of the UK MetOffice hydrometeor classification code
- mf_dirstring. Dataset keyword
Used with HYDRO_METHOD UKMO. Directory where the UK MetOffice hydrometeor classification membership functions are stored
- ml_depth: float. Dataset keyword
Used with HYDRO_METHOD UKMO. Depth of the melting layer [km]. Default 500.
- perturb_ml_depth: float. Dataset keyword
Used with HYDRO_METHOD UKMO. if specified, the depth of the melting layer can be varied by +/- this value [km], allowing a less-rigidly defined melting layer. Default 0.
- fzl: float or None. Dataset keyword
If desired, a single freezing level height can be specified for the entire PPI domain. This will be used only if no temperature field is available.
- soundingstr. Dataset keyword
The nearest radiosounding WMO code (5 int digits). It will be used to compute the freezing level, if no temperature field name is specified, if the temperature field is not in the radar object or if no fzl is explicitely defined.
- use_dualpol: Bool. Dataset keyword
Used with HYDRO_METHOD UKMO. If false no radar data is used and the classification is performed using temperature information only. Default True
- use_temperature: Bool. Dataset keyword
Used with HYDRO_METHOD UKMO. If false no temperature information is used and the classification is performed using radar data only. Default True
- use_interpolation: Bool. Dataset keyword
Used with HYDRO_METHOD UKMO. If True gaps in the classification are filled using a nearest-neighbour interpolation. Default False
- map_to_semisupervised: Bool. Dataset keyword
Used with HYDRO_METHOD UKMO. If True the output is map to the same categories as the semi-supervised classification. Default True
- append_all_fields: Bool. Dataset keyword
Used with HYDRO_METHOD UKMO. If True auxiliary fields such as confidence and probability for each class are going to be added to the output
HZT#
- description
Gets iso0 degree data in HZT format and put it in radar coordinates
- parameters
- metranet_read_libstr. Global keyword
Type of METRANET reader library used to read the data. Can be ‘C’ or ‘python’
- datatypestring. Dataset keyword
arbitrary data type
- keep_in_memoryint. Dataset keyword
if set keeps the icon data dict, the icon coordinates dict and the icon field in radar coordinates in memory
- regular_gridint. Dataset keyword
if set it is assume that the radar has a grid constant in time and there is no need to compute a new icon field if the icon data has not changed
- icon_typestr. Dataset keyword
name of the icon field to process. Default TEMP
- icon_variableslist of strings. Dataset keyword
Py-art name of the icon fields. Default temperature
HZT_LOOKUP#
- description
Gets HZT data and put it in radar coordinates using look up tables computed or loaded when initializing
- parameters
- metranet_read_libstr. Global keyword
Type of METRANET reader library used to read the data. Can be ‘C’ or ‘python’
- datatypestring. Dataset keyword
arbitrary data type
- lookup_tableint. Dataset keyword
if set a pre-computed look up table for the icon coordinates is loaded. Otherwise the look up table is computed taking the first radar object as reference
- regular_gridint. Dataset keyword
if set it is assume that the radar has a grid constant in time and therefore there is no need to interpolate the icon field in memory to the current radar grid
ISO0_GRIB#
- description
Gets iso0 degree data in GRIB format and put it in radar coordinates. This function is meant to process data received from the MeteoFrance NWP model. It can output the height over the iso0 of each gate or the iso0 height at each gate
- parameters
- datatypestring. Dataset keyword
arbitrary data type
- time_interpbool. Dataset keyword
whether to perform an interpolation in time between consecutive model outputs. Default True
- voltype: str. Dataset keyword
The type of data to output. Can be H_ISO0 or HZT. Default H_ISO0
ISO0_MF#
- description
Gets iso0 degree data in text format and put it in radar coordinates. This function is meant to process data received from the MeteoFrance NWP model. The model provides a maximum of 9 points at 0.5 degree lat/lon spacing surrounding a given radar. If a point is not provided it means that the iso0 for that point is at or below the ground level. Out of these points a single reference iso-0 is obtained according to the user defined iso0 statistic.
- parameters
- datatypestring. Dataset keyword
arbitrary data type
- iso0_statisticstr. Dataset keyword
The statistic used to weight the iso0 points. Can be avg_by_dist, avg, min, max
KDP_LEASTSQUARE_1W#
- description
Computes specific differential phase using a piecewise least square method
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rwindfloat. Dataset keyword
The length of the segment for the least square method [m]. Default 6000.
- vectorizebool. Dataset keyword
Whether to vectorize the KDP processing. Default false
KDP_LEASTSQUARE_2W#
- description
Computes specific differential phase using a piecewise least square method
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rwindsfloat. Dataset keyword
The length of the short segment for the least square method [m]. Default 2000.
- rwindlfloat. Dataset keyword
The length of the long segment for the least square method [m]. Default 6000.
- Zthrfloat. Dataset keyword
The threshold defining which estimated data to use [dBZ]
- vectorizeBool. Dataset keyword
Whether to vectorize the KDP processing. Default false
KEEP_ROI#
- description
keep only data within a region of interest and mask anything else
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- trtfilestr. Dataset keyword
TRT file from which to extract the region of interest
- time_tolfloat. Dataset keyword
Time tolerance between the TRT file date and the nominal radar volume time
- lon_roi, lat_roifloat array. Dataset keyword
latitude and longitude positions defining a region of interest
- alt_min, alt_maxfloat. Dataset keyword
Minimum and maximum altitude of the region of interest. Can be None
- cercleboolean. Dataset keyword
If True the region of interest is going to be defined as a cercle centered at a particular point. Default False
- lon_centre, lat_centreFloat. Dataset keyword
The position of the centre of the cercle. If None, that of the radar will be used
- rad_cercleFloat. Dataset keyword
The radius of the cercle in m. Default 1000.
- res_cercleint. Dataset keyword
Number of points used to define a quarter of cercle. Default 16
- boxboolean. Dataset keyword
If True the region of interest is going to be defined by a rectangle
- lon_point, lat pointFloat
The position of the point of rotation of the box. If None the position of the radar is going to be used
- rotationfloat
The angle of rotation. Positive is counterclockwise from North in deg. Default 0.
- we_offset, sn_offsetfloat
west-east and south-north offset from rotation position in m. Default 0
- we_length, sn_lengthfloat
west-east and south-north rectangle lengths in m. Default 1000.
- originstr
origin of rotation. Can be center: center of the rectangle or mid_south. East-west mid-point at the south of the rectangle. Default center
- use_latlonBool. Dataset keyword
If True the coordinates used to find the radar gates within the ROI will be lat/lon. If false it will use Cartesian Coordinates with origin the radar position. Default True
L#
- description
Computes L parameter
- parameters
- datatypestring. Dataset keyword
The input data type
MEAN_PHASE_IQ#
- description
Computes the mean phase from the horizontal or vertical IQ data
- parameters
- datatypelist of string. Dataset keyword
The input data types
NCVOL#
- description
Dummy function that allows to save the entire radar object
parameters
NOISE_POWER#
- description
Computes the noise power from the spectra
- parameters
- datatypelist of string. Dataset keyword
The input data types
- unitsstr
The units of the returned signal. Can be ‘ADU’, ‘dBADU’ or ‘dBm’
- navgint
Number of spectra averaged
- rminint
Range from which the data is used to estimate the noise
- nnoise_minint
Minimum number of samples to consider the estimated noise power valid
OUTLIER_FILTER#
- description
filters out gates which are outliers respect to the surrounding
- parameters
- datatypelist of string. Dataset keyword
The input data types
- thresholdfloat. Dataset keyword
The distance between the value of the examined range gate and the median of the surrounding gates to consider the gate an outlier
- nbint. Dataset keyword
The number of neighbours (to one side) to analyse. i.e. 2 would correspond to 24 gates
- nb_minint. Dataset keyword
Minimum number of neighbouring gates to consider the examined gate valid
- percentile_min, percentile_maxfloat. Dataset keyword
gates below (above) these percentiles (computed over the sweep) are considered potential outliers and further examined
PHIDP0_CORRECTION#
- description
corrects phidp of the system phase
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rminfloat. Dataset keyword
The minimum range where to look for valid data [m]. Default 1000.
- rmaxfloat. Dataset keyword
The maximum range where to look for valid data [m]. Default 50000.
- rcellfloat. Dataset keyword
The length of a continuous cell to consider it valid precip [m]. Default 1000.
- Zminfloat. Dataset keyword
The minimum reflectivity [dBZ]. Default 20.
- Zmaxfloat. Dataset keyword
The maximum reflectivity [dBZ]. Default 40.
PHIDP0_ESTIMATE#
- description
estimates the system differential phase offset at each ray
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rminfloat. Dataset keyword
The minimum range where to look for valid data [m]
- rmaxfloat. Dataset keyword
The maximum range where to look for valid data [m]
- rcellfloat. Dataset keyword
The length of a continuous cell to consider it valid precip [m]
- Zminfloat. Dataset keyword
The minimum reflectivity [dBZ]
- Zmaxfloat. Dataset keyword
The maximum reflectivity [dBZ]
PHIDP_KDP_KALMAN#
- description
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
- parameters
- datatypelist of string. Dataset keyword
The input data types
- parallelboolean. Dataset keyword
if set use parallel computing
- get_phidpboolean. Datset keyword
if set the PhiDP computed by integrating the resultant KDP is added to the radar field
- frequencyfloat. Dataset keyword
the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present it will be assumed that the radar is C band
PHIDP_KDP_LP#
- description
Estimates PhiDP and KDP using a linear programming algorithm. This method only retrieves data in rain (i.e. below the melting layer). The method has 3 steps: PhiDP unfolding (including clutter suppression), Processing PhiDP using the LP algorithm, Obtaining KDP by convoluting PhiDP with a Sobel window. Required inputs for the LP algorithm are PsiDP and reflectivity. RhoHV and SNR are used for the clutter suppression in the PhiDP unfolding step (note that SNR is used instead of Normalized Coherent Power used by the original algorithm). If they are not provided a gate_filter based on the values of reflectivity is used instead. Freezing level height can be retrieved from iso-0 or temperature fields, from radio sounding or set by the user.
- parameters
- datatypelist of string. Dataset keyword
The input data types
- fzlfloat. Dataset keyword
The freezing level height [m]. Default 2000.
- soundingstr. Dataset keyword
The nearest radiosounding WMO code (5 int digits). It will be used to compute the freezing level, if no temperature field name is specified, if the temperature field is not in the radar object or if no freezing_level is explicitely defined.
- ml_thicknessfloat. Dataset keyword
The melting layer thickness in meters. Default 700.
- beamwidthfloat. Dataset keyword
the antenna beamwidth [deg]. If None that of the keys radar_beam_width_h or radar_beam_width_v in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the beamwidth will be set to None
- LP_solverstr.
The LP solver to use. Can be pyglpk, cvxopt, cylp, cylp_mp. Default cvxopt
- procint
Number of worker processes. Only used when LP_solver is cylp_mp. Default 1
- min_snr, min_rhvfloat
Minimum SNR and RhoHV. Used to filter out non-meteorological echoes when performing the unfolding of the differential phase. Default 10 and 0.6
- sys_phasefloat
Default system differential phase offset in deg. Default 0.
- overide_sys_phasebool
If True the dynamic sys_phase not computed and the default sys_phase is used. If false a dynamic sys_phase is computed. If no dynamic value is found the default sys_phase is used. Default False
- first_gate_syspint
First gate to use when determining the system differential phase offset. Default 0
- nowrapint or None
Gate number where to begin the phase unwrapping. None will unwrap from gate 0. Default None
- ncptsint
Minimum number of continuous valid PhiDP points. Segments below this number or starting at a gate below this number are going to be excluded from the unfolding. Default 2.
- z_biasfloat
reflectivity bias. Default 0 dBZ
- low_z, high_zfloat
mininum and maximum reflectivity values. Values beyond this range are going to be set to this range limits. The modified reflectivity is used in the LP algorithm. Default 10 and 53 dBZ
- min_phidpfloat
minimum differential phase. PhiDP values below this threshold are going to be set to the threshold values. The modified PhiDP is used in the LP algorithm. Default 0.1 deg
- docint
Number of gates to doc at the end of the ray. Used in the LP algorithm. Default 0
- self_constfloat
selfconsistency factor. Used in the LP algorithm. Default 60000
- coeffloat
Exponent linking Z to KDP in selfconsistency. Used in the LP algorithm. kdp = (10**(0.1z))**coef. Default 0.914
- window_lenint
Length of Sobel Window applied to PhiDP field before computing KDP. Default 35
PHIDP_KDP_VULPIANI#
- description
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
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rwindfloat. Dataset keyword
The length of the segment [m]. Default 2000.
- n_iterint. Dataset keyword
number of iterations. Default 3.
- interpboolean. Dataset keyword
if set non valid values are interpolated using neighbouring valid values. Default 0 (False)
- parallelboolean. Dataset keyword
if set use parallel computing. Default 1 (True)
- get_phidpboolean. Datset keyword
if set the PhiDP computed by integrating the resultant KDP is added to the radar field. Default 0 (False)
- frequencyfloat. Dataset keyword
the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present it will be assumed that the radar is C band
PHIDP_KDP_MAESAKA#
- description
Estimates PhiDP and KDP using the method by Maesaka. This method only retrieves data in rain (i.e. below the melting layer)
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rminfloat. Dataset keyword
The minimum range where to look for valid data [m]. Default 1000.
- rmaxfloat. Dataset keyword
The maximum range where to look for valid data [m]. Default 50000.
- rcellfloat. Dataset keyword
The length of a continuous cell to consider it valid precip [m]. Default 1000.
- Zminfloat. Dataset keyword
The minimum reflectivity [dBZ]. Default 20
- Zmaxfloat. Dataset keyword
The maximum reflectivity [dBZ]. Default 40
- fzlfloat. Dataset keyword
The freezing level height [m]. Default 2000.
- soundingstr. Dataset keyword
The nearest radiosounding WMO code (5 int digits). It will be used to compute the freezing level, if no temperature field name is specified, if the temperature field isin the radar object or if no freezing_level is explicitely defined.
- ml_thicknessfloat. Dataset keyword
The melting layer thickness in meters. Default 700.
- beamwidthfloat. Dataset keyword
the antenna beamwidth [deg]. If None that of the keys radar_beam_width_h or radar_beam_width_v in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the beamwidth will be set to None
PHIDP_SMOOTH_1W#
- description
corrects phidp of the system phase and smoothes it using one window
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rminfloat. Dataset keyword
The minimum range where to look for valid data [m]. Default 1000.
- rmaxfloat. Dataset keyword
The maximum range where to look for valid data [m]. Default 50000.
- rcellfloat. Dataset keyword
The length of a continuous cell to consider it valid precip [m]. Default 1000.
- rwindfloat. Dataset keyword
The length of the smoothing window [m]. Default 6000.
- Zminfloat. Dataset keyword
The minimum reflectivity [dBZ]. Default 20.
- Zmaxfloat. Dataset keyword
The maximum reflectivity [dBZ]. Default 40.
PHIDP_SMOOTH_2W#
- description
corrects phidp of the system phase and smoothes it using one window
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rminfloat. Dataset keyword
The minimum range where to look for valid data [m]
- rmaxfloat. Dataset keyword
The maximum range where to look for valid data [m]
- rcellfloat. Dataset keyword
The length of a continuous cell to consider it valid precip [m]
- rwindsfloat. Dataset keyword
The length of the short smoothing window [m]
- rwindlfloat. Dataset keyword
The length of the long smoothing window [m]
- Zminfloat. Dataset keyword
The minimum reflectivity [dBZ]
- Zmaxfloat. Dataset keyword
The maximum reflectivity [dBZ]
- Zthrfloat. Dataset keyword
The threshold defining wich smoothed data to used [dBZ]
POL_VARIABLES#
- description
Computes the polarimetric variables from the complex spectra
- parameters
- datatypelist of string. Dataset keyword
The input data types
- subtract_noiseBool
If True noise will be subtracted from the signal. Default False
- smooth_windowint or None
Size of the moving Gaussian smoothing window. If none no smoothing will be applied. Default None
- variableslist of str
list of variables to compute. Default dBZ
POL_VARIABLES_IQ#
- description
Computes the polarimetric variables from the IQ data
- parameters
- datatypelist of string. Dataset keyword
The input data types
- subtract_noiseBool
If True noise will be subtracted from the signal
- lagint
The time lag to use in the estimators
- directionstr
The convention used in the Doppler mean field. Can be negative_away or negative_towards
- variableslist of str
list of variables to compute. Default dBZ
- phase_offsetfloat. Dataset keyword
The system differential phase offset to remove
PWR#
- description
Computes the signal power in dBm
- parameters
- datatypelist of string. Dataset keyword
The input data types
- mflossh, mflossvfloat. Dataset keyword
The matching filter losses of the horizontal (vertical) channel [dB]. If None it will be obtained from the attribute radar_calibration of the radar object. Defaults to 0
- radconsth, radconstvfloat. Dataset keyword
The horizontal (vertical) channel radar constant. If None it will be obtained from the attribute radar_calibration of the radar object
- lrxh, lrxvfloat. Global keyword
The horizontal (vertical) receiver losses from the antenna feed to the reference point. [dB] positive value. Default 0
- lradomeh, lradomevfloat. Global keyword
The 1-way dry radome horizontal (vertical) channel losses. [dB] positive value. Default 0.
- attgfloat. Dataset keyword
The gas attenuation [dB/km]. If none it will be obtained from the attribute radar_calibration of the radar object or assigned according to the radar frequency. Defaults to 0.
RADAR_RESAMPLING#
- description
Resamples the radar data to mimic another radar with different geometry and antenna pattern
parameters
RADIAL_NOISE_HS#
- description
Computes the radial noise from the signal power using the Hildebrand and Sekhon 1974 method
- parameters
- datatypestring. Dataset keyword
The input data type
- rminfloat. Dataset keyword
The minimum range from which to start the computation
- nbins_minint. Dataset keyword
The minimum number of noisy gates to consider the estimation valid
- max_std_pwrfloat. Dataset keyword
The maximum standard deviation of the noise power to consider the estimation valid
- get_noise_posbool. Dataset keyword
If True a field flagging the position of the noisy gets will be returned
RADIAL_NOISE_IVIC#
- description
Computes the radial noise from the signal power using the Ivic 2013 method
- parameters
- datatypestring. Dataset keyword
The input data type
- npulses_rayint
Default number of pulses used in the computation of the ray. If the number of pulses is not in radar.instrument_parameters this will be used instead. Default 30
- ngates_min: int
minimum number of gates with noise to consider the retrieval valid. Default 800
- iterations: int
number of iterations in step 7. Default 10.
- get_noise_posbool
If true an additional field with gates containing noise according to the algorithm is produced
RADIAL_VELOCITY#
- description
Estimates the radial velocity respect to the radar from the wind velocity
- parameters
- datatypestring. Dataset keyword
The input data type
- latitude, longitudefloat
arbitrary coordinates [deg] from where to compute the radial velocity. If any of them is None it will be the radar position
- altitudefloat
arbitrary altitude [m MSL] from where to compute the radial velocity. If None it will be the radar altitude
RAINRATE#
- description
Estimates rainfall rate from polarimetric moments
- parameters
- datatypestring. Dataset keyword
The input data type
- RR_METHODstring. Dataset keyword
The rainfall rate estimation method. One of the following: Z, ZPoly, KDP, A, ZKDP, ZA, hydro
- alpha, betafloat
factor and exponent of the R-Var power law R = alpha*Var^Beta. Default value depending on RR_METHOD. Z (0.0376, 0.6112), KDP (None, None), A (None, None)
- alphaz, betazfloat
factor and exponent of the R-Z power law R = alpha*Z^Beta. Default value (0.0376, 0.6112)
- alphazr, betazrfloat
factor and exponent of the R-Z power law R = alpha*Z^Beta applied to rain in method hydro. Default value (0.0376, 0.6112)
- alphazs, betazsfloat
factor and exponent of the R-Z power law R = alpha*Z^Beta applied to solid precipitation in method hydro. Default value (0.1, 0.5)
- alphakdp, betakdpfloat
factor and exponent of the R-KDP power law R = alpha*KDP^Beta. Default value (None, None)
- alphaa, betaafloat
factor and exponent of the R-Ah power law R = alpha*Ah^Beta. Default value (None, None)
- threshfloat
In hybrid methods, Rainfall rate threshold at which the retrieval method used changes [mm/h]. Default value depending on RR_METHOD. ZKDP 10, ZA 10, hydro 10
- mp_factorfloat
Factor by which the Z-R relation is multiplied in the melting layer in method hydro. Default 0.6
RAW#
- description
Dummy function that returns the initial input data set
parameters
REFLECTIVITY#
- description
Computes reflectivity from the spectral reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
REFLECTIVITY_IQ#
- description
Computes reflectivity from the IQ data
- parameters
- datatypelist of string. Dataset keyword
The input data types
- subtract_noiseBool
If True noise will be subtracted from the signal
RCS#
- description
Computes the radar cross-section (assuming a point target) from radar reflectivity.
- parameters
- datatypelist of string. Dataset keyword
The input data types
- kw2float. Dataset keyowrd
The water constant
- pulse_widthfloat. Dataset keyowrd
The pulse width [s]
- beamwidthvfloat. Global keyword
The vertical polarization antenna beamwidth [deg]. Used if input is vertical reflectivity
- beamwidthhfloat. Global keyword
The horizontal polarization antenna beamwidth [deg]. Used if input is horizontal reflectivity
RCS_PR#
- description
Computes the radar cross-section (assuming a point target) from radar reflectivity by first computing the received power and then the RCS from it.
- parameters
- datatypelist of string. Dataset keyword
The input data types
- AntennaGainH, AntennaGainVfloat. Dataset keyword
The horizontal (vertical) polarization antenna gain [dB]. If None it will be obtained from the attribute instrument_parameters of the radar object
- txpwrh, txpwrvfloat. Dataset keyword
The transmitted power of the horizontal (vertical) channel [dBm]. If None it will be obtained from the attribute radar_calibration of the radar object
- mflossh, mflossvfloat. Dataset keyword
The matching filter losses of the horizontal (vertical) channel [dB]. If None it will be obtained from the attribute radar_calibration of the radar object. Defaults to 0
- radconsth, radconstvfloat. Dataset keyword
The horizontal (vertical) channel radar constant. If None it will be obtained from the attribute radar_calibration of the radar object
- lrxh, lrxvfloat. Global keyword
The horizontal (vertical) receiver losses from the antenna feed to the reference point. [dB] positive value. Default 0
- ltxh, ltxvfloat. Global keyword
The horizontal (vertical) transmitter losses from the output of the high power amplifier to the antenna feed. [dB] positive value. Default 0
- lradomeh, lradomevfloat. Global keyword
The 1-way dry radome horizontal (vertical) channel losses. [dB] positive value. Default 0.
- attgfloat. Dataset keyword
The gas attenuation [dB/km]. If none it will be obtained from the attribute radar_calibration of the radar object or assigned according to the radar frequency. Defaults to 0.
RHOHV_CORRECTION#
- description
identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Precipitation
- parameters
- datatypelist of string. Dataset keyword
The data types used in the correction
RHOHV_RAIN#
- description
Keeps only suitable data to evaluate the 80 percentile of RhoHV in rain
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rminfloat. Dataset keyword
minimum range where to look for rain [m]. Default 1000.
- rmaxfloat. Dataset keyword
maximum range where to look for rain [m]. Default 50000.
- Zminfloat. Dataset keyword
minimum reflectivity to consider the bin as precipitation [dBZ]. Default 20.
- Zmaxfloat. Dataset keyword
maximum reflectivity to consider the bin as precipitation [dBZ] Default 40.
- ml_thicknessfloat. Dataset keyword
assumed thickness of the melting layer. Default 700.
- fzlfloat. Dataset keyword
The default freezing level height. It will be used if no temperature field name is specified or the temperature field is not in the radar object. Default 2000.
- soundingstr. Dataset keyword
The nearest radiosounding WMO code (5 int digits). It will be used to compute the freezing level, if no temperature field name is specified, if the temperature field isin the radar object or if no freezing_level is explicitely defined.
ROI#
- description
Obtains the radar data at a region of interest defined by a TRT file or by the user.
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- trtfilestr. Dataset keyword
TRT file from which to extract the region of interest
- time_tolfloat. Dataset keyword
Time tolerance between the TRT file date and the nominal radar volume time
- lon_roi, lat_roifloat array. Dataset keyword
latitude and longitude positions defining a region of interest
- alt_min, alt_maxfloat. Dataset keyword
Minimum and maximum altitude of the region of interest. Can be None
- cercleboolean. Dataset keyword
If True the region of interest is going to be defined as a cercle centered at a particular point. Default False
- lon_centre, lat_centreFloat. Dataset keyword
The position of the centre of the cercle
- rad_cercleFloat. Dataset keyword
The radius of the cercle in m. Default 1000.
- res_cercleint. Dataset keyword
Number of points used to define a quarter of cercle. Default 16
- lon_point, lat pointFloat
The position of the point of rotation of the box. If None the position of the radar is going to be used
- rotationfloat
The angle of rotation. Positive is counterclockwise from North in deg. Default 0.
- we_offset, sn_offsetfloat
west-east and south-north offset from rotation position in m. Default 0
- we_length, sn_lengthfloat
west-east and south-north rectangle lengths in m. Default 1000.
- originstr
origin of rotation. Can be center: center of the rectangle or mid_south. East-west mid-point at the south of the rectangle. Default center
- use_latlonBool. Dataset keyword
If True the coordinates used to find the radar gates within the ROI will be lat/lon. If false it will use Cartesian Coordinates with origin the radar position. Default True
ROI2#
- description
Obtains the radar data at a region of interest defined by a TRT file or by the user. More information is kept
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- trtfilestr. Dataset keyword
TRT file from which to extract the region of interest
- time_tolfloat. Dataset keyword
Time tolerance between the TRT file date and the nominal radar volume time
- lon_roi, lat_roifloat array. Dataset keyword
latitude and longitude positions defining a region of interest
- alt_min, alt_maxfloat. Dataset keyword
Minimum and maximum altitude of the region of interest. Can be None
- cercleboolean. Dataset keyword
If True the region of interest is going to be defined as a cercle centered at a particular point. Default False
- lon_centre, lat_centreFloat. Dataset keyword
The position of the centre of the cercle
- rad_cercleFloat. Dataset keyword
The radius of the cercle in m. Default 1000.
- res_cercleint. Dataset keyword
Number of points used to define a quarter of cercle. Default 16
- boxboolean. Dataset keyword
If True the region of interest is going to be defined by a rectangle
- lon_point, lat pointFloat
The position of the point of rotation of the box. If None the position of the radar is going to be used
- rotationfloat
The angle of rotation. Positive is counterclockwise from North in deg. Default 0.
- we_offset, sn_offsetfloat
west-east and south-north offset from rotation position in m. Default 0
- we_length, sn_lengthfloat
west-east and south-north rectangle lengths in m. Default 1000.
- originstr
origin of rotation. Can be center: center of the rectangle or mid_south. East-west mid-point at the south of the rectangle. Default center
- use_latlonBool. Dataset keyword
If True the coordinates used to find the radar gates within the ROI will be lat/lon. If false it will use Cartesian Coordinates with origin the radar position. Default True
SAN#
- description
identifies echoes as 0: No data, 1: Noise, 2: Clutter, 3: Precipitation
- parameters
- datatypelist of string. Dataset keyword
The input data types
- wind_sizeint
Size of the moving window used to compute the ray texture (number of gates). Default 7
- max_textphi, max_textrhv, max_textzdr, max_textreflfloat
Maximum value for the texture of the differential phase, texture of RhoHV, texture of Zdr and texture of reflectivity. Gates in these. Default 20, 0.3, 2.85, 8
- min_rhvfloat
Minimum value for the RhoHV. Default 0.6
SELFCONSISTENCY_BIAS#
- description
Estimates the reflectivity bias by means of the selfconsistency algorithm by Gourley
- parameters
- datatypelist of string. Dataset keyword
The input data types
- parametrizationstr
The type of parametrization for the self-consistency curves. Can be ‘None’, ‘Gourley’, ‘Wolfensberger’, ‘Louf’, ‘Gorgucci’ or ‘Vaccarono’ ‘None’ will use tables from config files. Default ‘None’.
- fzlfloat. Dataset keyword
Default freezing level height. Default 2000.
- soundingstr. Dataset keyword
The nearest radiosounding WMO code (5 int digits). It will be used to compute the freezing level, if no temperature field name is specified, if the temperature field isin the radar object or if no freezing_level is explicitely defined.
- rsmoothfloat. Dataset keyword
length of the smoothing window [m]. Default 2000.
- min_rhohvfloat. Dataset keyword
minimum valid RhoHV. Default 0.92
- filter_rainBool. Dataset keyword
If True the hydrometeor classification is used to filter out gates that are not rain. Default True
- max_phidpfloat. Dataset keyword
maximum valid PhiDP [deg]. Default 20.
- ml_thicknessfloat. Dataset keyword
Melting layer thickness [m]. Default 700.
- rcellfloat. Dataset keyword
length of continuous precipitation to consider the precipitation cell a valid phidp segment [m]. Default 15000.
- dphidp_minfloat. Dataset keyword
minimum phase shift [deg]. Default 2.
- dphidp_maxfloat. Dataset keyword
maximum phase shift [deg]. Default 16.
- frequencyfloat. Dataset keyword
the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the selfconsistency will not be computed
- check_wet_radomeBool. Dataset keyword
if True the average reflectivity of the closest gates to the radar is going to be check to find out whether there is rain over the radome. If there is rain no bias will be computed. Default True.
- wet_radome_reflFloat. Dataset keyword
Average reflectivity [dBZ] of the gates close to the radar to consider the radome as wet. Default 25.
- wet_radome_rng_min, wet_radome_rng_maxFloat. Dataset keyword
Min and max range [m] of the disk around the radar used to compute the average reflectivity to determine whether the radome is wet. Default 2000 and 4000.
- wet_radome_ngates_minint
Minimum number of valid gates to consider that the radome is wet. Default 180
- valid_gates_onlyBool
If True the reflectivity bias obtained for each valid ray is going to be assigned only to gates of the segment used. That will give more weight to longer segments when computing the total bias. Default False
- keep_pointsBool
If True the ZDR, ZH and KDP of the gates used in the self- consistency algorithm are going to be stored for further analysis. Default False
- rkdpfloat
The length of the window used to compute KDP with the single window least square method [m]. Default 6000.
SELFCONSISTENCY_BIAS2#
- description
Estimates the reflectivity bias by means of the selfconsistency algorithm by Gourley
- parameters
- datatypelist of string. Dataset keyword
The input data types
- parametrizationstr
The type of parametrization for the self-consistency curves. Can be ‘None’, ‘Gourley’, ‘Wolfensberger’, ‘Louf’, ‘Gorgucci’ or ‘Vaccarono’ ‘None’ will use tables from config files. Default ‘None’.
- fzlfloat. Dataset keyword
Default freezing level height. Default 2000.
- soundingstr. Dataset keyword
The nearest radiosounding WMO code (5 int digits). It will be used to compute the freezing level, if no temperature field name is specified, if the temperature field isin the radar object or if no freezing_level is explicitely defined.
- rsmoothfloat. Dataset keyword
length of the smoothing window [m]. Default 2000.
- min_rhohvfloat. Dataset keyword
minimum valid RhoHV. Default 0.92
- filter_rainBool. Dataset keyword
If True the hydrometeor classification is used to filter out gates that are not rain. Default True
- max_phidpfloat. Dataset keyword
maximum valid PhiDP [deg]. Default 20.
- ml_thicknessfloat. Dataset keyword
Melting layer thickness [m]. Default 700.
- rcellfloat. Dataset keyword
length of continuous precipitation to consider the precipitation cell a valid phidp segment [m]. Default 15000.
- frequencyfloat. Dataset keyword
the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the selfconsistency will not be computed
- check_wet_radomeBool. Dataset keyword
if True the average reflectivity of the closest gates to the radar is going to be check to find out whether there is rain over the radome. If there is rain no bias will be computed. Default True.
- wet_radome_reflFloat. Dataset keyword
Average reflectivity [dBZ] of the gates close to the radar to consider the radome as wet. Default 25.
- wet_radome_rng_min, wet_radome_rng_maxFloat. Dataset keyword
Min and max range [m] of the disk around the radar used to compute the average reflectivity to determine whether the radome is wet. Default 2000 and 4000.
- wet_radome_ngates_minint
Minimum number of valid gates to consider that the radome is wet. Default 180
- keep_pointsBool
If True the ZDR, ZH and KDP of the gates used in the self- consistency algorithm are going to be stored for further analysis. Default False
- bias_per_gateBool
If True the bias per gate will be computed
SELFCONSISTENCY_KDP_PHIDP#
- description
Computes specific differential phase and differential phase in rain using the selfconsistency between Zdr, Zh and KDP
- parameters
- datatypelist of strings. Dataset keyword
The input data types
- parametrizationstr
The type of parametrization for the self-consistency curves. Can be ‘None’, ‘Gourley’, ‘Wolfensberger’, ‘Louf’, ‘Gorgucci’ or ‘Vaccarono’ ‘None’ will use tables from config files. Default ‘None’.
- rsmoothfloat. Dataset keyword
length of the smoothing window [m]. Default 2000.
- min_rhohvfloat. Dataset keyword
minimum valid RhoHV. Default 0.92
- filter_rainBool. Dataset keyword
If True the hydrometeor classification is used to filter out gates that are not rain. Default True
- max_phidpfloat. Dataset keyword
maximum valid PhiDP [deg]. Default 20.
- ml_thicknessfloat. Dataset keyword
assumed melting layer thickness [m]. Default 700.
- fzlfloat. Dataset keyword
The default freezing level height. It will be used if no temperature field name is specified or the temperature field is not in the radar object. Default 2000.
- soundingstr. Dataset keyword
The nearest radiosounding WMO code (5 int digits). It will be used to compute the freezing level, if no temperature field name is specified, if the temperature field isin the radar object or if no freezing_level is explicitely defined.
- frequencyfloat. Dataset keyword
the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the selfconsistency will not be computed
SNR#
- description
Computes SNR
- parameters
- datatypestring. Dataset keyword
The input data type
- output_typestring. Dataset keyword
The output data type. Either SNRh or SNRv
SNR_FILTER#
- description
filters out low SNR echoes
- parameters
- datatypelist of string. Dataset keyword
The input data types
- SNRminfloat. Dataset keyword
The minimum SNR to keep the data.
ST1_IQ#
- description
Computes the statistical test one lag fluctuation from the horizontal or vertical IQ data
- parameters
- datatypelist of string. Dataset keyword
The input data types
ST2_IQ#
- description
Computes the statistical test two lag fluctuation from the horizontal or vertical IQ data
- parameters
- datatypelist of string. Dataset keyword
The input data types
TRAJ_TRT#
- description
Processes data according to TRT trajectory
- parameters
- datatypelist of string. Dataset keyword
The input data types
- time_tolfloat. Dataset keyword
tolerance between reference time of the radar volume and that of the TRT cell [s]. Default 100.
- alt_min, alt_maxfloat. Dataset keyword
Minimum and maximum altitude of the data inside the TRT cell to retrieve [m MSL]. Default None
- cell_centerBool. Dataset keyword
If True only the range gate closest to the center of the cell is extracted. Default False
- latlon_tolFloat. Dataset keyword
Tolerance in lat/lon when extracting data only from the center of the TRT cell. Default 0.01
TRAJ_TRT_CONTOUR#
- description
Gets the TRT cell contour corresponding to each radar volume
- parameters
- datatypelist of string. Dataset keyword
The input data types
- time_tolfloat. Dataset keyword
tolerance between reference time of the radar volume and that of the TRT cell [s]. Default 100.
TURBULENCE#
- description
Computes turbulence from the Doppler spectrum width and reflectivity using the PyTDA package
- parameters
- datatypestring. Dataset keyword
The input data type
- radiusfloat. Dataset keyword
Search radius for calculating Eddy Dissipation Rate (EDR). Default 2
- split_cutBool. Dataset keyword
Set to True for split-cut volumes. Default False
- max_split_cutInt. Dataset keyword
Total number of tilts that are affected by split cuts. Only relevant if split_cut=True. Default 2
- xran, yranfloat array. Dataset keyword
Spatial range in X,Y to consider. Default [-100, 100] for both X and Y
- use_ntdaBool. Dataset keyword
Wether to use NCAR Turbulence Detection Algorithm (NTDA). Default True
- beamwidthFloat. Dataset keyword
Radar beamwidth. Default None. If None it will be obtained from the radar object metadata. If cannot be obtained defaults to 1 deg.
- compute_gate_posBool. Dataset keyword
If True the gate position is going to be computed in PyTDA. Otherwise the position from the radar object is used. Default False
- verboseBool. Dataset keyword
True for verbose output. Default False
VAD#
- description
Estimates vertical wind profile using the VAD (velocity Azimuth Display) technique
- parameters
- datatypestring. Dataset keyword
The input data type
VEL_FILTER#
- description
filters out range gates that could not be used for Doppler velocity estimation
- parameters
- datatypelist of string. Dataset keyword
The input data types
VIS#
- description
Gets the visibility in percentage from the minimum visible elevation. Anything with elevation lower than the minimum visible elevation plus and offset is set to 0 while above is set to 100.
- parameters
- datatypestring. Dataset keyword
arbitrary data type
- offsetfloat. Dataset keyword
The offset above the minimum visibility that must be filtered
VIS_FILTER#
- description
filters out rays gates with low visibility and corrects the reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
- VISminfloat. Dataset keyword
The minimum visibility to keep the data.
VOL_REFL#
- description
Computes the volumetric reflectivity in 10log10(cm^2 km^-3)
- parameters
- datatypelist of string. Dataset keyword
The input data types
- freqfloat. Dataset keyword
The radar frequency
- kwfloat. Dataset keyword
The water constant
VOL2BIRD_FILTER#
- description
Masks all echo types that have been identified as non-biological by vol2bird
- parameters
- datatypelist of string. Dataset keyword
The input data types
VOL2BIRD_GATE_FILTER#
- description
Adds filter on range gate values to the vol2bird filter
- parameters
- datatypelist of string. Dataset keyword
The input data types
- dBZ_maxfloat
Maximum reflectivity of biological scatterers
- V_minfloat
Minimum Doppler velocity of biological scatterers
VSTATUS_TO_SAN#
- description
Converts velocity status from lidar data into pyrad echo ID
- parameters
- datatypelist of string. Dataset keyword
The input data types
WBN#
- description
Computes the wide band noise from the horizontal or vertical IQ data
- parameters
- datatypelist of string. Dataset keyword
The input data types
WIND_VEL#
- description
Estimates the horizontal or vertical component of the wind from the radial velocity
- parameters
- datatypestring. Dataset keyword
The input data type
- vert_projBoolean
If true the vertical projection is computed. Otherwise the horizontal projection is computed
WINDSHEAR#
- description
Estimates the wind shear from the wind velocity
- parameters
- datatypestring. Dataset keyword
The input data type
- az_tolfloat
The tolerance in azimuth when looking for gates on top of the gate when computation is performed
WINDSHEAR_LIDAR#
- description
Estimates the wind shear from the wind velocity of lidar scans
- parameters
- datatypestring. Dataset keyword
The input data type
- az_tolfloat
The tolerance in azimuth when looking for gates on top of the gate when computation is performed
ZDR#
- description
Computes differential reflectivity from the horizontal and vertical spectral reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
ZDR_IQ#
- description
Computes differential reflectivity from the horizontal and vertical IQ data
- parameters
- datatypelist of string. Dataset keyword
The input data types
- subtract_noiseBool
If True noise will be subtracted from the signal
- lagint
The time lag to use in the estimators
ZDR_PREC#
- description
Keeps only suitable data to evaluate the differential reflectivity in moderate rain or precipitation (for vertical scans)
- parameters
- datatypelist of string. Dataset keyword
The input data types
- ml_filterboolean. Dataset keyword
indicates if a filter on data in and above the melting layer is applied. Default True.
- rminfloat. Dataset keyword
minimum range where to look for rain [m]. Default 1000.
- rmaxfloat. Dataset keyword
maximum range where to look for rain [m]. Default 50000.
- Zminfloat. Dataset keyword
minimum reflectivity to consider the bin as precipitation [dBZ]. Default 20.
- Zmaxfloat. Dataset keyword
maximum reflectivity to consider the bin as precipitation [dBZ] Default 22.
- RhoHVminfloat. Dataset keyword
minimum RhoHV to consider the bin as precipitation Default 0.97
- PhiDPmaxfloat. Dataset keyword
maximum PhiDP to consider the bin as precipitation [deg] Default 10.
- elmaxfloat. Dataset keyword
maximum elevation angle where to look for precipitation [deg] Default None.
- ml_thicknessfloat. Dataset keyword
assumed thickness of the melting layer. Default 700.
- fzlfloat. Dataset keyword
The default freezing level height. It will be used if no temperature field name is specified or the temperature field is not in the radar object. Default 2000.
- soundingstr. Dataset keyword
The nearest radiosounding WMO code (5 int digits). It will be used to compute the freezing level, if no temperature field name is specified, if the temperature field isin the radar object or if no freezing_level is explicitely defined.
ZDR_SNOW#
- description
Keeps only suitable data to evaluate the differential reflectivity in snow
- parameters
- datatypelist of string. Dataset keyword
The input data types
- rminfloat. Dataset keyword
minimum range where to look for rain [m]. Default 1000.
- rmaxfloat. Dataset keyword
maximum range where to look for rain [m]. Default 50000.
- Zminfloat. Dataset keyword
minimum reflectivity to consider the bin as snow [dBZ]. Default 0.
- Zmaxfloat. Dataset keyword
maximum reflectivity to consider the bin as snow [dBZ] Default 30.
- SNRminfloat. Dataset keyword
minimum SNR to consider the bin as snow [dB]. Default 10.
- SNRmaxfloat. Dataset keyword
maximum SNR to consider the bin as snow [dB] Default 50.
- RhoHVminfloat. Dataset keyword
minimum RhoHV to consider the bin as snow Default 0.97
- PhiDPmaxfloat. Dataset keyword
maximum PhiDP to consider the bin as snow [deg] Default 10.
- elmaxfloat. Dataset keyword
maximum elevation angle where to look for snow [deg] Default None.
- KDPmaxfloat. Dataset keyword
maximum KDP to consider the bin as snow [deg] Default None
- TEMPminfloat. Dataset keyword
minimum temperature to consider the bin as snow [deg C]. Default None
- TEMPmaxfloat. Dataset keyword
maximum temperature to consider the bin as snow [deg C] Default None
- hydroclasslist of ints. Dataset keyword
list of hydrometeor classes to keep for the analysis Default [2] (dry snow)
SPECTRA#
FFT#
- description
Compute the Doppler spectra form the IQ data with a Fourier transform
- parameters
- datatypelist of string. Dataset keyword
The input data types
- windowlist of str
Parameters of the window used to obtain the spectra. The parameters are the ones corresponding to function scipy.signal.windows.get_window. It can also be [‘None’].
FILTER_0DOPPLER#
- description
Function to filter the 0-Doppler line bin and neighbours of the Doppler spectra
- parameters
- datatypelist of string. Dataset keyword
The input data types
- filter_widthfloat
The Doppler filter width. Default 0.
- filter_unitsstr
Can be ‘m/s’ or ‘Hz’. Default ‘m/s’
FILTER_SPECTRA_NOISE#
- description
Filter the noise of the Doppler spectra by clipping any data below the noise level plus a margin
- parameters
- datatypelist of string. Dataset keyword
The input data types
- clipping_levelfloat
The clipping level [dB above noise level]. Default 10.
IFFT#
- description
Compute the Doppler spectrum width from the spectral reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
RAW_IQ#
- description
Dummy function that returns the initial input data set
parameters
RAW_SPECTRA#
- description
Dummy function that returns the initial input data set
parameters
SPECTRA_ANGULAR_AVERAGE#
- description
Function to average the spectra over the rays. This function is intended mainly for vertically pointing scans. The function assumes the volume is composed of a single sweep, it averages over the number of rays specified by the user and produces a single ray output.
- parameters
- datatypelist of string. Dataset keyword
The input data types
- navgint
Number of spectra to average. If -1 all spectra will be averaged. Default -1.
SPECTRA_POINT#
- description
Obtains the spectra or IQ data at a point location.
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- single_pointboolean. Dataset keyword
if True only one gate per radar volume is going to be kept. Otherwise all gates within the azimuth and elevation tolerance are going to be kept. This is useful to extract all data from fixed pointing scans. Default True
- latlonboolean. Dataset keyword
if True position is obtained from latitude, longitude information, otherwise position is obtained from antenna coordinates (range, azimuth, elevation). Default False
- truealtboolean. Dataset keyword
if True the user input altitude is used to determine the point of interest. if False use the altitude at a given radar elevation ele over the point of interest. Default True
- lonfloat. Dataset keyword
the longitude [deg]. Use when latlon is True.
- latfloat. Dataset keyword
the latitude [deg]. Use when latlon is True.
- altfloat. Dataset keyword
altitude [m MSL]. Use when latlon is True. Default 0.
- elefloat. Dataset keyword
radar elevation [deg]. Use when latlon is False or when latlon is True and truealt is False
- azifloat. Dataset keyword
radar azimuth [deg]. Use when latlon is False
- rngfloat. Dataset keyword
range from radar [m]. Use when latlon is False
- AziTolfloat. Dataset keyword
azimuthal tolerance to determine which radar azimuth to use [deg]. Default 0.5
- EleTolfloat. Dataset keyword
elevation tolerance to determine which radar elevation to use [deg]. Default 0.5
- RngTolfloat. Dataset keyword
range tolerance to determine which radar bin to use [m]. Default 50.
SPECTRAL_NOISE#
- description
Computes the spectral noise
- parameters
- datatypelist of string. Dataset keyword
The input data types
- unitsstr
The units of the returned signal. Can be ‘ADU’, ‘dBADU’ or ‘dBm’
- navgint
Number of spectra averaged
- rminint
Range from which the data is used to estimate the noise
- nnoise_minint
Minimum number of samples to consider the estimated noise power valid
SPECTRAL_PHASE#
- description
Computes the spectral phase
- parameters
- datatypelist of string. Dataset keyword
The input data types
SPECTRAL_POWER#
- description
Computes the spectral power
- parameters
- datatypelist of string. Dataset keyword
The input data types
- unitsstr
The units of the returned signal. Can be ‘ADU’, ‘dBADU’ or ‘dBm’
- subtract_noiseBool
If True noise will be subtracted from the signal
- smooth_windowint or None
Size of the moving Gaussian smoothing window. If none no smoothing will be applied
SPECTRAL_REFLECTIVITY#
- description
Computes spectral reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
- subtract_noiseBool
If True noise will be subtracted from the signal
- smooth_windowint or None
Size of the moving Gaussian smoothing window. If none no smoothing will be applied
SRHOHV_FILTER#
- description
Filter Doppler spectra as a function of spectral RhoHV
- parameters
- datatypelist of string. Dataset keyword
The input data types
- sRhoHV_thresholdfloat
Data with sRhoHV module above this threshold will be filtered. Default 1.
CENTROIDS#
CENTROIDS#
- description
Computes centroids for the semi-supervised hydrometeor classification
- parameters
- datatypelist of string. Dataset keyword
The input data types
- samples_per_volint. Dataset keyword
Maximum number of samples per volume kept for further analysis. Default 20000
- nbinsint.
Number of bins of the histogram used to make the data platykurtic. Default 110
- pdf_zh_maxint
Multiplicative factor to the Guassian function used to make the distribution of the reflectivity platykurtic that determines the number of samples for each bin. Default 10000
- pdf_relh_maxint
Multiplicative factor to the Guassian function used to make the distribution of the height relative to the iso-0 platykurtic that determines the number of samples for each bin. Default 20000
- sigma_zh, sigma_relhfloat
sigma of the respective Gaussian functions. Defaults 0.75 and 1.5
- randomizebool
If True the data is randomized to avoid the effects of the quantization. Default True
- platykurtic_dBZbool
If True makes the reflectivity distribution platykurtic. Default True
- platykurtic_H_ISO0bool
If True makes the height respect to the iso-0 distribution platykurtic. Default True
- relh_slopefloat. Dataset keyword
The slope used to transform the height relative to the iso0 into a sigmoid function. Default 0.001
- external_iterationsint. Dataset keywords
Number of iterations of the external loop. This number will determine how many medoids are computed for each hydrometeor class. Default 30
- internal_iterationsint. Dataset keyword
Maximum number of iterations of the internal loop. Default 10
- sample_dataBool.
If True the data is going to be sampled prior to each external iteration. Default False
- nsamples_iterint.
Number of samples per iteration. Default 20000
- alphafloat
Minimum value to accept the cluster according to p. Default 0.01
- cv_approachBool
If true it is used a critical value approach to reject or accept similarity between observations and reference. If false it is used a p-value approach. Default True
- n_samples_synint
Number of samples drawn from reference to compare it with observations in the KS test. Default 50
- num_samples_arrarray of int
Number of observation samples used in the KS test to choose from. Default (30, 35, 40)
- acceptance_thresholdfloat. Dataset keyword
Threshold on the inter-quantile coefficient of dispersion of the medoids above which the medoid of the class is not acceptable. Default 0.5
- nmedoids_minint
Minimum number of intermediate medoids to compute the final result. Default 1
- var_namestupple
The names of the features. Default (‘dBZ’, ‘ZDR’, ‘KDP’, ‘RhoHV’, ‘H_ISO0’)
- hydro_names: tupple
The name of the hydrometeor types. Default (‘AG’, ‘CR’, ‘LR’, ‘RP’, ‘RN’, ‘VI’, ‘WS’, ‘MH’, ‘IH/HDG’)
- weighttupple
The weight given to each feature when comparing to the reference. It is in the same order as var_names. Default (1., 1., 1., 1., 0.75)
- parallelizedbool
If True the centroids search is going to be parallelized. Default False
- kmax_iterint
Maximum number of iterations of the k-medoids algorithm. Default 100
- nsamples_smallint
Maximum number before using the k-medoids CLARA algorithm. If this number is exceeded the CLARA algorithm will be used. Default 40000
- sampling_size_claraint
Number of samples used in each iteration of the k-medoids CLARA algorithm. Default 10000
- niter_claraint
Number of iterations performed by the k-medoids CLARA algorithm. Default 5
- keep_labeled_databool
If True the labeled data is going to be kept for storage. Default True
- use_medianbool
If True the intermediate centroids are computed as the median of the observation variables and the final centroids are computed as the median of the intermediate centroids. If false they are computed using the kmedoids algorithm. Default false
- allow_label_duplicatesbool
If True allow to label multiple clusters with the same label. Default True
COLOCATED_GATES#
COLOCATED_GATES#
- description
Find colocated gates within two radars
- parameters
- datatypelist of string. Dataset keyword
The input data types
- h_tolfloat. Dataset keyword
Tolerance in altitude difference between radar gates [m]. Default 100.
- latlon_tolfloat. Dataset keyword
Tolerance in latitude and longitude position between radar gates [deg]. Default 0.0005
- vol_d_tolfloat. Dataset keyword
Tolerance in pulse volume diameter [m]. Default 100.
- visminfloat. Dataset keyword
Minimum visibility [percent]. Default None.
- hminfloat. Dataset keyword
Minimum altitude [m MSL]. Default None.
- hmaxfloat. Dataset keyword
Maximum altitude [m MSL]. Default None.
- rminfloat. Dataset keyword
Minimum range [m]. Default None.
- rmaxfloat. Dataset keyword
Maximum range [m]. Default None.
- elminfloat. Dataset keyword
Minimum elevation angle [deg]. Default None.
- elmaxfloat. Dataset keyword
Maximum elevation angle [deg]. Default None.
- azrad1minfloat. Dataset keyword
Minimum azimuth angle [deg] for radar 1. Default None.
- azrad1maxfloat. Dataset keyword
Maximum azimuth angle [deg] for radar 1. Default None.
- azrad2minfloat. Dataset keyword
Minimum azimuth angle [deg] for radar 2. Default None.
- azrad2maxfloat. Dataset keyword
Maximum azimuth angle [deg] for radar 2. Default None.
ICON_COORD#
ICON_COORD#
- description
Gets the icon indices corresponding to each icon coordinates
- parameters
- datatypestring. Dataset keyword
arbitrary data type
- iconpathstring. General keyword
path where to store the look up table
- modelstring. Dataset keyword
The icon model to use. Can be icon-1, icon-1e, icon-2, icon-7
HZT_COORD#
- description
Gets the HZT indices corresponding to each HZT coordinates
- parameters
- metranet_read_libstr. Global keyword
Type of METRANET reader library used to read the data. Can be ‘C’ or ‘python’
- datatypestring. Dataset keyword
arbitrary data type
- iconpathstring. General keyword
path where to store the look up table
ICON2RADAR#
ICON2RADAR#
- description
Gets icon data and put it in radar coordinates using look up tables
- parameters
- datatypestring. Dataset keyword
arbitrary data type
- icon_typestr. Dataset keyword
name of the icon field to process. Default TEMP
- icon_variableslist of strings. Dataset keyword
Py-art name of the icon fields. Default temperature
- icon_time_index_min, icon_time_index_maxint
minimum and maximum indices of the icon data to retrieve. If a value is provided only data corresponding to the time indices within the interval will be used. If None all data will be used. Default None
GRID#
RAW_GRID#
- description
Dummy function that returns the initial input data set
parameters
GECSX#
- description
Computes ground clutter RCS, radar visibility and many others using the GECSX algorithmn translated from IDL into python
- parameters
- datatypelist of string. Dataset keyword
The input data types
- range_discretizationfloat. Dataset keyword
Range discretization used when computing the Cartesian visibility field the larger the better but the slower the processing will be
- az_discretizationfloat. Dataset keyword
Azimuth discretization used when computing the Cartesian visibility field, the larger the better but the slower the processing will be
- kefloat. Dataset keyword
Equivalent earth-radius factor used in the computation of the radar beam refraction
- atm_attfloat. Dataset keyword
One-way atmospheric refraction in db / km
- mosotti_kwfloat. Dataset keyword
Clausius-Mosotti factor K, depends on material (water) and wavelength for water = sqrt(0.93)
- raster_oversamplingint. Dataset keyword
The raster resolution of the DEM should be smaller than the range resolution of the radar (defined by the pulse length). If this is not the case, this keyword can be set to increase the raster resolution. The values for the elevation, sigma naught, visibility are repeated. The other values are recalculated. Values for raster_oversampling: 0 or undefined: No oversampling is done 1: Oversampling is done. The factor N is automatically calculated such that 2*dx/N < pulse length 2 or larger: Oversampling is done with this value as N
- sigma0_methodstring. Dataset keyword
Which estimation method to use, either ‘Gabella’ or ‘Delrieu’
- clipint. Dataset keyword
If set to true, the provided DEM will be clipped to the extent of the polar radar domain. Increases computation speed a lot but Cartesian output fields will be available only over radar domain
GRID#
- description
Puts the radar data in a regular grid
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- gridconfigdictionary. Dataset keyword
Dictionary containing some or all of this keywords: xmin, xmax, ymin, ymax, zmin, zmax : floats minimum and maximum horizontal distance from grid origin [km] and minimum and maximum vertical distance from grid origin [m] Defaults -40, 40, -40, 40, 0., 10000. latmin, latmax, lonmin, lonmax : floats minimum and maximum latitude and longitude [deg], if specified xmin, xmax, ymin, ymax, latorig, lonorig will be ignored hres, vres : floats horizontal and vertical grid resolution [m] Defaults 1000., 500. latorig, lonorig, altorig : floats latitude and longitude of grid origin [deg] and altitude of grid origin [m MSL] Defaults the latitude, longitude and altitude of the radar
- wfuncstr. Dataset keyword
the weighting function used to combine the radar gates close to a grid point. Possible values BARNES, BARNES2, CRESSMAN, NEAREST Default NEAREST
- roif_funcstr. Dataset keyword
the function used to compute the region of interest. Possible values: dist_beam, constant
- roifloat. Dataset keyword
the (minimum) radius of the region of interest in m. Default half the largest resolution
- beamwidthfloat. Dataset keyword
the radar antenna beamwidth [deg]. If None that of the key radar_beam_width_h in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present a default 1 deg value will be used
- beam_spacingfloat. Dataset keyword
the beam spacing, i.e. the ray angle resolution [deg]. If None, that of the attribute ray_angle_res of the radar object will be used. If the attribute is None a default 1 deg value will be used
GRID_FIELDS_DIFF#
- description
Computes grid field differences
- parameters
- datatypelist of string. Dataset keyword
The input data types
GRID_MASK#
- description
Mask data. Puts True if data is within thresholds, False if it is not. Thresholds can be min, max or both min and max
parameters
GRID_TEXTURE#
- description
Computes the 2D texture of a gridded field
- parameters
- datatypelist of string. Dataset keyword
The input data types
- xwind, ywindint
The size of the local window in the x and y axis. Default 7
- fill_valuefloat
The value with which to fill masked data. Default np.NaN
NORMALIZE_LUMINOSITY#
- description
Normalize the data by the sinus of the sun elevation. The sun elevation is computed at the central pixel.
parameters
PIXEL_FILTER#
- description
Masks all pixels that are not of the class specified in keyword pixel_type
- parameters
- pixel_typeint or list of ints
The type of pixels to keep: 0 No data, 1 Below threshold, 2 Above threshold. Default 2
VOL2GRID#
- description
Function to convert polar data into a Cartesian grid
- parameters
- xmin, xmax, ymin, ymaxfloat
Horizontal limits of the grid [m from origin]. Default +-20000.
- zmin, zmaxfloat
vertical limits of the grid [masl]. Default 1000.
- hres, vresfloat
horizontal and vertical resolution [m]. Default 1000.
- lat0, lon0float
Grid origin [deg]. The default will be the radar position
- alt0float
Grid origin altitude [masl]. Default is 0
- wfuncstr
Weighting function. Default NEAREST
DDA#
- description
Estimates horizontal wind speed and direction with a multi-doppler approach This method uses the python package pyDDA
- parameters
- datatypestring. Dataset keyword
The input data type
- gridconfigdictionary. Dataset keyword
Dictionary containing some or all of this keywords: xmin, xmax, ymin, ymax, zmin, zmax : floats minimum and maximum horizontal distance from grid origin [km] and minimum and maximum vertical distance from grid origin [m] Defaults -40, 40, -40, 40, 0., 10000. latmin, latmax, lonmin, lonmax : floats minimum and maximum latitude and longitude [deg], if specified xmin, xmax, ymin, ymax will be ignored hres, vres : floats horizontal and vertical grid resolution [m] Defaults 1000., 500. latorig, lonorig, altorig : floats latitude and longitude of grid origin [deg] and altitude of grid origin [m MSL] Defaults the latitude, longitude and altitude of the radar
- wfuncstr. Dataset keyword
the weighting function used to combine the radar gates close to a grid point. Possible values BARNES, BARNES2, CRESSMAN, NEAREST Default NEAREST
- roif_funcstr. Dataset keyword
the function used to compute the region of interest. Possible values: dist_beam, constant
- roifloat. Dataset keyword
the (minimum) radius of the region of interest in m. Default half the largest resolution
- beamwidthfloat. Dataset keyword
the radar antenna beamwidth [deg]. If None that of the key radar_beam_width_h in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present a default 1 deg value will be used
- beam_spacingfloat. Dataset keyword
the beam spacing, i.e. the ray angle resolution [deg]. If None, that of the attribute ray_angle_res of the radar object will be used. If the attribute is None a default 1 deg value will be used
- signslist of integers
The sign of the velocity field for every radar object. A value of 1 represents when positive values velocities are towards the radar, -1 represents when negative velocities are towards the radar.
- Cofloat
Weight for cost function related to observed radial velocities. Default: 1.
- Cmfloat
Weight for cost function related to the mass continuity equation. Default: 1500.
- Cx: float
Smoothing coefficient for x-direction
- Cy: float
Smoothing coefficient for y-direction
- Cz: float
Smoothing coefficient for z-direction
- Cb: float
Coefficient for sounding constraint
- Cv: float
Weight for cost function related to vertical vorticity equation.
- Cmod: float
Coefficient for model constraint
- Cpoint: float
Coefficient for point constraint
- wind_tol: float
Stop iterations after maximum change in winds is less than this value.
- frzfloat
The freezing level in meters. This is to tell PyDDA where to use ice particle fall speeds in the wind retrieval verus liquid.
GRID_TIMEAVG#
GRID_TIME_STATS#
- description
computes the temporal statistics of a field
- parameters
- datatypelist of string. Dataset keyword
The input data types
- periodfloat. Dataset keyword
the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600.
- start_averagefloat. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- lin_trans: int. Dataset keyword
If 1 apply linear transformation before averaging
- use_nanbool. Dataset keyword
If true non valid data will be used
- nan_valuefloat. Dataset keyword
The value of the non valid data. Default 0
- stat: string. Dataset keyword
Statistic to compute: Can be mean, std, cov, min, max. Default mean
GRID_TIME_STATS2#
- description
computes temporal statistics of a field
- parameters
- datatypelist of string. Dataset keyword
The input data types
- periodfloat. Dataset keyword
the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600.
- start_averagefloat. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- stat: string. Dataset keyword
Statistic to compute: Can be median, mode, percentileXX
- use_nanbool. Dataset keyword
If true non valid data will be used
- nan_valuefloat. Dataset keyword
The value of the non valid data. Default 0
GRID_RAIN_ACCU#
- description
computes rainfall accumulation fields
- parameters
- datatypelist of string. Dataset keyword
The input data types
- periodfloat. Dataset keyword
the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600.
- start_averagefloat. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- use_nanbool. Dataset keyword
If true non valid data will be used
- nan_valuefloat. Dataset keyword
The value of the non valid data. Default 0
INTERCOMP#
INTERCOMP#
- description
intercomparison between two radars at co-located gates. The variables compared must be of the same type.
- parameters
- datatypelist of string. Dataset keyword
The input data types
- colocgatespathstring.
base path to the file containing the coordinates of the co-located gates
- coloc_radars_namestring. Dataset keyword
string identifying the radar names
- rays_are_indexedbool. Dataset keyword
If True it is considered that the rays are indexed and that the data can be selected simply looking at the ray number. Default false
- azi_tolfloat. Dataset keyword
azimuth tolerance between the two radars. Default 0.5 deg
- ele_tolfloat. Dataset keyword
elevation tolerance between the two radars. Default 0.5 deg
- rng_tolfloat. Dataset keyword
range tolerance between the two radars. Default 50 m
- coloc_data_dirstring. Dataset keyword
name of the directory containing the csv file with colocated data
INTERCOMP_FIELDS#
- description
intercomparison between two radars
- parameters
- datatypelist of string. Dataset keyword
The input data types
INTERCOMP_TIME_AVG#
- description
intercomparison between the average reflectivity of two radars
- parameters
- datatypelist of string. Dataset keyword
The input data types
- colocgatespathstring.
base path to the file containing the coordinates of the co-located gates
- coloc_data_dirstring. Dataset keyword
name of the directory containing the csv file with colocated data
- coloc_radars_namestring. Dataset keyword
string identifying the radar names
- rays_are_indexedbool. Dataset keyword
If True it is considered that the rays are indexed and that the data can be selected simply looking at the ray number. Default false
- azi_tolfloat. Dataset keyword
azimuth tolerance between the two radars. Default 0.5 deg
- ele_tolfloat. Dataset keyword
elevation tolerance between the two radars. Default 0.5 deg
- rng_tolfloat. Dataset keyword
range tolerance between the two radars. Default 50 m
- clt_maxint. Dataset keyword
maximum number of samples that can be clutter contaminated. Default 100 i.e. all
- phi_excess_maxint. Dataset keyword
maximum number of samples that can have excess instantaneous PhiDP. Default 100 i.e. all
- non_rain_maxint. Dataset keyword
maximum number of samples that can be no rain. Default 100 i.e. all
- phi_avg_maxfloat. Dataset keyword
maximum average PhiDP allowed. Default 600 deg i.e. any
ML#
ML_DETECTION#
- description
Detects the melting layer
- parameters
- datatypelist of string. Dataset keyword
The input data types
VPR#
VPR#
- description
Computes the vertical profile of reflectivity using the Meteo-France operational algorithm
- parameters
- datatypestring. Dataset keyword
The input data type
- nvalid_minint
Minimum number of rays with data to consider the azimuthal average valid. Default 20.
- angle_min, angle_maxfloat
Minimum and maximum elevation angles used to compute the ratios of reflectivity. Default 0. and 4.
- ml_thickness_min, ml_thickness_max, ml_thickness_stepfloat
Minimum, maximum and step of the melting layer thickness of the models to explore [m]. Default 200., 800. and 200.
- iso0_maxfloat
maximum iso0 altitude of the profile. Default 5000.
- ml_top_diff_max, ml_top_stepfloat
maximum difference +- between iso-0 and top of the melting layer [m] of the models to explore. Step. Default 200. and 200.
- ml_peak_min, ml_peak_max, ml_peak_step: float
min, max and step of the value at the peak of the melting layer of the models to explore. Default 1., 6. and 1.
- dr_min, dr_max, dr_stepfloat
min, max and step of the decreasing ratio above the melting layer. Default -6., -1.5 and 1.5
- dr_defaultfloat
default decreasing ratio to use if a proper model could not be found. Default -4.5
- dr_altfloat
altitude above the melting layer top (m) where theoretical profile needs to be defined to be able to compute DR. If the theoretical profile is not defined up to the resulting altitude a default DR is used. Default 800.
- h_maxfloat
maximum altitude [masl] where to compute the model profile. Default 6000.
- h_corr_maxfloat
maximum altitude [masl] considered for the VPR correction
- h_resfloat
resolution of the model profile (m). Default 1.
- max_weightfloat
Maximum weight of the antenna pattern. Default 9.
- rmin_obs, rmax_obsfloat
minimum and maximum range (m) of the observations that are compared with the model. Default 5000. and 150000.
- use_mlbool
If True the retrieved ML will be used to select the range of variability the meltin layer top and thickness
- vpr_memory_maxfloat
The maximum time range to average reflectivity (min)
- filter_vpr_memory_maxfloat
The maximum time range where to look for previous VPR retrievals
- ml_datatypestr
Melting layer data type descriptor
- z_datatypestr
descriptor used get the linear reflectivity information
- vpr_theo_datatypestr
descriptor used to get the retrieved theoretical VPR
- filter_paramsbool
If True the current theoretical VPR profile is averaged with the past VPR profile by averaging the 4 parameters that define the profile, otherwise the shape of the profiles is averaged. Default false. Used only in non-spatialised VPR correction
- weight_memfloat
Weight given to past VPR when filtering the current VPR
- spatializedbool
If True the VPR correction is spatialized
- correct_iso0bool
If True the iso0 field is corrected by a bias constant computed as the difference between the retrieved melting layer top and the average iso0 and areas with precipitation. Default True. Used only in the spatialised VPR correction
MONITORING#
GC_MONITORING#
- description
computes ground clutter monitoring statistics
- parameters
- excessgatespathstr. Config keyword
The path to the gates in excess of quantile location
- excessgates_fnamestr. Dataset keyword
The name of the gates in excess of quantile file
- datatypelist of string. Dataset keyword
The input data types
- stepfloat. Dataset keyword
The width of the histogram bin. Default is None. In that case the default step in function get_histogram_bins is used
- regular_gridBoolean. Dataset keyword
Whether the radar has a Boolean grid or not. Default False
- val_minFloat. Dataset keyword
Minimum value to consider that the gate has signal. Default None
- filter_precstr. Dataset keyword
Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes.
- rmax_precfloat. Dataset keyword
Maximum range to consider when looking for wet gates [m]
- percent_prec_maxfloat. Dataset keyword
Maxim percentage of wet gates to consider the volume dry
MONITORING#
- description
computes monitoring statistics
- parameters
- datatypelist of string. Dataset keyword
The input data types
- stepfloat. Dataset keyword
The width of the histogram bin. Default is None. In that case the default step in function get_histogram_bins is used
- max_raysint. Dataset keyword
The maximum number of rays per sweep used when computing the histogram. If set above 0 the number of rays per sweep will be checked and if above max_rays the last rays of the sweep will be removed
OCCURRENCE#
OCCURRENCE#
- description
computes the frequency of occurrence of data. It looks only for gates where data is present.
- parameters
- datatypelist of string. Dataset keyword
The input data types
- regular_gridBoolean. Dataset keyword
Whether the radar has a Boolean grid or not. Default False
- rmin, rmaxfloat. Dataset keyword
minimum and maximum ranges where the computation takes place. If -1 the whole range is considered. Default is -1
- val_minFloat. Dataset keyword
Minimum value to consider that the gate has signal. Default None
- filter_precstr. Dataset keyword
Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes.
- rmax_precfloat. Dataset keyword
Maximum range to consider when looking for wet gates [m]
- percent_prec_maxfloat. Dataset keyword
Maxim percentage of wet gates to consider the volume dry
OCCURRENCE_PERIOD#
- description
computes the frequency of occurrence over a long period of time by adding together shorter periods
- parameters
- datatypelist of string. Dataset keyword
The input data types
- regular_gridBoolean. Dataset keyword
Whether the radar has a Boolean grid or not. Default False
- rmin, rmaxfloat. Dataset keyword
minimum and maximum ranges where the computation takes place. If -1 the whole range is considered. Default is -1
TIMEAVG_STD#
- description
computes the average and standard deviation of data. It looks only for gates where data is present.
- parameters
- datatypelist of string. Dataset keyword
The input data types
- regular_gridBoolean. Dataset keyword
Whether the radar has a Boolean grid or not. Default False
- rmin, rmaxfloat. Dataset keyword
minimum and maximum ranges where the computation takes place. If -1 the whole range is considered. Default is -1
- val_minFloat. Dataset keyword
Minimum reflectivity value to consider that the gate has signal. Default None
- filter_precstr. Dataset keyword
Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes.
- rmax_precfloat. Dataset keyword
Maximum range to consider when looking for wet gates [m]
- percent_prec_maxfloat. Dataset keyword
Maxim percentage of wet gates to consider the volume dry
- lin_transBoolean. Dataset keyword
If True the data will be transformed into linear units. Default False
QVP#
EVP#
- description
Computes enhanced vertical profiles, by averaging over height levels PPI data.
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- lat, lonfloat
latitude and longitude of the point of interest [deg]
- latlon_tolfloat
tolerance in latitude and longitude in deg. Default 0.0005
- delta_rng, delta_azifloat
maximum range distance [m] and azimuth distance [degree] from the central point of the evp containing data to average. Default 5000. and 10.
- hmaxfloat
The maximum height to plot [m]. Default 10000.
- hresfloat
The height resolution [m]. Default 250.
- avg_typestr
The type of averaging to perform. Can be either “mean” or “median” Default “mean”
- nvalid_minint
Minimum number of valid points to consider the data valid when performing the averaging. Default 1
- interp_kindstr
type of interpolation when projecting to vertical grid: ‘none’, or ‘nearest’, etc. Default ‘none’. ‘none’ will select from all data points within the regular grid height bin the closest to the center of the bin. ‘nearest’ will select the closest data point to the center of the height bin regardless if it is within the height bin or not. Data points can be masked values If another type of interpolation is selected masked values will be eliminated from the data points before the interpolation
QVP#
- description
Computes quasi vertical profiles, by averaging over height levels PPI data.
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- angleint or float
If the radar object contains a PPI volume, the sweep number to use, if it contains an RHI volume the elevation angle. Default 0.
- ang_tolfloat
If the radar object contains an RHI volume, the tolerance in the elevation angle for the conversion into PPI
- hmaxfloat
The maximum height to plot [m]. Default 10000.
- hresfloat
The height resolution [m]. Default 50
- avg_typestr
The type of averaging to perform. Can be either “mean” or “median” Default “mean”
- nvalid_minint
Minimum number of valid points to accept average. Default 30.
- interp_kindstr
type of interpolation when projecting to vertical grid: ‘none’, or ‘nearest’, etc. Default ‘none’ ‘none’ will select from all data points within the regular grid height bin the closest to the center of the bin. ‘nearest’ will select the closest data point to the center of the height bin regardless if it is within the height bin or not. Data points can be masked values If another type of interpolation is selected masked values will be eliminated from the data points before the interpolation
SVP#
- description
Computes slanted vertical profiles, by averaging over height levels PPI data.
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- angleint or float
If the radar object contains a PPI volume, the sweep number to use, if it contains an RHI volume the elevation angle. Default 0.
- ang_tolfloat
If the radar object contains an RHI volume, the tolerance in the elevation angle for the conversion into PPI. Default 1.
- lat, lonfloat
latitude and longitude of the point of interest [deg]
- latlon_tolfloat
tolerance in latitude and longitude in deg. Default 0.0005
- delta_rng, delta_azifloat
maximum range distance [m] and azimuth distance [degree] from the central point of the svp containing data to average. Default 5000. and 10.
- hmaxfloat
The maximum height to plot [m]. Default 10000.
- hresfloat
The height resolution [m]. Default 250.
- avg_typestr
The type of averaging to perform. Can be either “mean” or “median” Default “mean”
- nvalid_minint
Minimum number of valid points to consider the data valid when performing the averaging. Default 1
- interp_kindstr
type of interpolation when projecting to vertical grid: ‘none’, or ‘nearest’, etc. Default ‘none’ ‘none’ will select from all data points within the regular grid height bin the closest to the center of the bin. ‘nearest’ will select the closest data point to the center of the height bin regardless if it is within the height bin or not. Data points can be masked values If another type of interpolation is selected masked values will be eliminated from the data points before the interpolation
TIME_HEIGHT#
- description
Produces time height radar objects at a point of interest defined by latitude and longitude. A time-height contains the evolution of the vertical structure of radar measurements above the location of interest.
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- lat, lonfloat
latitude and longitude of the point of interest [deg]
- latlon_tolfloat
tolerance in latitude and longitude in deg. Default 0.0005
- hmaxfloat
The maximum height to plot [m]. Default 10000.
- hresfloat
The height resolution [m]. Default 50
- interp_kindstr
type of interpolation when projecting to vertical grid: ‘none’, or ‘nearest’, etc. Default ‘none’ ‘none’ will select from all data points within the regular grid height bin the closest to the center of the bin. ‘nearest’ will select the closest data point to the center of the height bin regardless if it is within the height bin or not. Data points can be masked values If another type of interpolation is selected masked values will be eliminated from the data points before the interpolation
TIME_ALONG_COORD#
- description
Produces time series along a particular antenna coordinate
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the time series
- modestr
coordinate to extract data along. Can be ALONG_AZI, ALONG_ELE or ALONG_RNG
- fixed_range, fixed_azimuth, fixed_elevationfloat
The fixed range [m], azimuth [deg] or elevation [deg] to extract. In each mode two of these parameters have to be defined. If they are not defined they default to 0.
- ang_tol, rng_tolfloat
The angle tolerance [deg] and range tolerance [m] around the fixed range or azimuth/elevation
- value_start, value_stopfloat
The minimum and maximum value at which the data along a coordinate start and stop
SPARSE_GRID#
ZDR_COLUMN#
- description
Detects ZDR columns
- parameters
- datatypelist of string. Dataset keyword
The input data types
SUN_HITS#
SUN_HITS#
- description
monitoring of the radar using sun hits
- parameters
- datatypelist of string. Dataset keyword
The input data types
- delev_maxfloat. Dataset keyword
maximum elevation distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5
- dazim_maxfloat. Dataset keyword
maximum azimuth distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5
- elminfloat. Dataset keyword
minimum radar elevation where to look for sun hits [deg]. Default 1.
- attgfloat. Dataset keyword
gaseous attenuation. Default None
- sun_positionstring. Datset keyword
The function to compute the sun position to use. Can be ‘MF’ or ‘pysolar’
- sun_hit_methodstr. Dataset keyword
Method used to estimate the power of the sun hit. Can be HS (Hildebrand and Sekhon 1974) or Ivic (Ivic 2013)
- rminfloat. Dataset keyword
minimum range where to look for a sun hit signal [m]. Used in HS method. Default 50000.
- hminfloat. Dataset keyword
minimum altitude where to look for a sun hit signal [m MSL]. Default 10000. The actual range from which a sun hit signal will be search will be the minimum between rmin and the range from which the altitude is higher than hmin. Used in HS method. Default 10000.
- nbins_minint. Dataset keyword.
minimum number of range bins that have to contain signal to consider the ray a potential sun hit. Default 20 for HS and 8000 for Ivic.
- npulses_rayint
Default number of pulses used in the computation of the ray. If the number of pulses is not in radar.instrument_parameters this will be used instead. Used in Ivic method. Default 30
- iterations: int
number of iterations in step 7 of Ivic method. Default 10.
- max_std_pwrfloat. Dataset keyword
maximum standard deviation of the signal power to consider the data a sun hit [dB]. Default 2. Used in HS method
- max_std_zdrfloat. Dataset keyword
maximum standard deviation of the ZDR to consider the data a sun hit [dB]. Default 2.
- az_width_cofloat. Dataset keyword
co-polar antenna azimuth width (convoluted with sun width) [deg]. Default None
- el_width_cofloat. Dataset keyword
co-polar antenna elevation width (convoluted with sun width) [deg]. Default None
- az_width_crossfloat. Dataset keyword
cross-polar antenna azimuth width (convoluted with sun width) [deg]. Default None
- el_width_crossfloat. Dataset keyword
cross-polar antenna elevation width (convoluted with sun width) [deg]. Default None
- ndaysint. Dataset keyword
number of days used in sun retrieval. Default 1
- coeff_bandfloat. Dataset keyword
multiplicate coefficient to transform pulse width into receiver bandwidth
- frequencyfloat. Dataset keyword
the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present frequency dependent parameters will not be computed
- beamwidthfloat. Dataset keyword
the antenna beamwidth [deg]. If None that of the keys radar_beam_width_h or radar_beam_width_v in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the beamwidth dependent parameters will not be computed
- pulse_widthfloat. Dataset keyword
the pulse width [s]. If None that of the key pulse_width in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the pulse width dependent parameters will not be computed
- ray_angle_resfloat. Dataset keyword
the ray angle resolution [deg]. If None that of the key ray_angle_res in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed
- AntennaGainH, AntennaGainVfloat. Dataset keyword
the horizontal (vertical) polarization antenna gain [dB]. If None that of the attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed
SUNSCAN#
- description
Processing of automatic sun scans for monitoring purposes of the radar system.
- parameters
- datatypelist of string. Dataset keyword
The input data types
- delev_maxfloat. Dataset keyword
maximum elevation distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5
- dazim_maxfloat. Dataset keyword
maximum azimuth distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5
- elminfloat. Dataset keyword
minimum radar elevation where to look for sun hits [deg]. Default 1.
- attgfloat. Dataset keyword
gaseous attenuation. Default None
- sun_positionstring. Datset keyword
The function to compute the sun position to use. Can be ‘MF’ or ‘pysolar’
- sun_hit_methodstr. Dataset keyword
Method used to estimate the power of the sun hit. Should be PSR. HS (Hildebrand and Sekhon 1974) or Ivic (Ivic 2013) are implemented but not tested.
- n_noise_binsint. Dataset keyword
Number of bins to use for noise estimation
- noise_thresholdfloat. Dataset keyword
Distance over the noise level in [dBm]
- min_num_samplesint. Dataset keyword
Minimal number of samples above the noise level
- max_fit_stddevfloat. Dataset keyword
Maximal allowed standard deviation for a valid sun fit [dBm]
- do_second_noise_eststring (‘Yes’ or ‘No’). Dataset keyword
Used to trigger a second noise estimation based on the first fit Requires another dataset keyword: n_indfar_bins
- n_indfar_binsint. Dataset keyword
Number of samples most remote from the sun center
- az_width_cofloat. Dataset keyword
co-polar antenna azimuth width (convoluted with sun width) [deg]. Default None
- el_width_cofloat. Dataset keyword
co-polar antenna elevation width (convoluted with sun width) [deg]. Default None
- az_width_crossfloat. Dataset keyword
cross-polar antenna azimuth width (convoluted with sun width) [deg]. Default None
- el_width_crossfloat. Dataset keyword
cross-polar antenna elevation width (convoluted with sun width) [deg]. Default None
- rminfloat. Dataset keyword
minimum range where to look for a sun hit signal [m]. Used in HS method. Default 50000.
- hminfloat. Dataset keyword
minimum altitude where to look for a sun hit signal [m MSL]. Default 10000. The actual range from which a sun hit signal will be search will be the minimum between rmin and the range from which the altitude is higher than hmin. Used in HS method. Default 10000.
- nbins_minint. Dataset keyword.
minimum number of range bins that have to contain signal to consider the ray a potential sun hit. Default 20 for HS and 8000 for Ivic.
- npulses_rayint
Default number of pulses used in the computation of the ray. If the number of pulses is not in radar.instrument_parameters this will be used instead. Used in Ivic method. Default 30
- flat_reg_wlenint
Length of the flat region window [m]. Used in Ivic method. Default 8000.
- iterations: int
number of iterations in step 7 of Ivic method. Default 10.
- max_std_pwrfloat. Dataset keyword
maximum standard deviation of the signal power to consider the data a sun hit [dB]. Default 2. Used in HS method
- max_std_zdrfloat. Dataset keyword
maximum standard deviation of the ZDR to consider the data a sun hit [dB]. Default 2.
- ndaysint. Dataset keyword
number of days used in sun retrieval. Default 1
- coeff_bandfloat. Dataset keyword
multiplicate coefficient to transform pulse width into receiver bandwidth
- frequencyfloat. Dataset keyword
the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present frequency dependent parameters will not be computed
- beamwidthfloat. Dataset keyword
the antenna beamwidth [deg]. If None that of the keys radar_beam_width_h or radar_beam_width_v in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the beamwidth dependent parameters will not be computed
- pulse_widthfloat. Dataset keyword
the pulse width [s]. If None that of the key pulse_width in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the pulse width dependent parameters will not be computed
- ray_angle_resfloat. Dataset keyword
the ray angle resolution [deg]. If None that of the key ray_angle_res in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed
- AntennaGainH, AntennaGainVfloat. Dataset keyword
the horizontal (vertical) polarization antenna gain [dB]. If None that of the attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed
TIMEAVG#
FLAG_TIME_AVG#
- description
computes a flag field describing the conditions of the data used while averaging
- parameters
- datatypelist of string. Dataset keyword
The input data types
- periodfloat. Dataset keyword
the period to average [s]. Default 3600.
- start_averagefloat. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- phidpmax: float. Dataset keyword
maximum PhiDP
- beamwidthfloat. Dataset keyword
the antenna beamwidth [deg]. If None that of the keys radar_beam_width_h or radar_beam_width_v in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the beamwidth will be set to None
TIME_AVG#
- description
computes the temporal mean of a field
- parameters
- datatypelist of string. Dataset keyword
The input data types
- periodfloat. Dataset keyword
the period to average [s]. Default 3600.
- start_averagefloat. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- lin_trans: int. Dataset keyword
If 1 apply linear transformation before averaging
WEIGHTED_TIME_AVG#
- description
computes the temporal mean of a field weighted by the reflectivity
- parameters
- datatypelist of string. Dataset keyword
The input data types
- periodfloat. Dataset keyword
the period to average [s]. Default 3600.
- start_averagefloat. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
TIME_STATS#
- description
computes the temporal statistics of a field
- parameters
- datatypelist of string. Dataset keyword
The input data types
- periodfloat. Dataset keyword
the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600.
- start_averagefloat. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- lin_trans: int. Dataset keyword
If 1 apply linear transformation before averaging
- use_nanbool. Dataset keyword
If true non valid data will be used
- nan_valuefloat. Dataset keyword
The value of the non valid data. Default 0
- stat: string. Dataset keyword
Statistic to compute: Can be mean, std, cov, min, max. Default mean
TIME_STATS2#
- description
computes the temporal mean of a field
- parameters
- datatypelist of string. Dataset keyword
The input data types
- periodfloat. Dataset keyword
the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600.
- start_averagefloat. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- stat: string. Dataset keyword
Statistic to compute: Can be median, mode, percentileXX
- use_nanbool. Dataset keyword
If true non valid data will be used
- nan_valuefloat. Dataset keyword
The value of the non valid data. Default 0
RAIN_ACCU#
- description
Computes rainfall accumulation fields
- parameters
- datatypelist of string. Dataset keyword
The input data types
- periodfloat. Dataset keyword
the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600.
- start_averagefloat. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- use_nanbool. Dataset keyword
If true non valid data will be used
- nan_valuefloat. Dataset keyword
The value of the non valid data. Default 0
TIMESERIES#
GRID_POINT_MEASUREMENT#
- description
Obtains the grid data at a point location.
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- latlonboolean. Dataset keyword
if True position is obtained from latitude, longitude information, otherwise position is obtained from grid index (iz, iy, ix).
- lonfloat. Dataset keyword
the longitude [deg]. Use when latlon is True.
- latfloat. Dataset keyword
the latitude [deg]. Use when latlon is True.
- altfloat. Dataset keyword
altitude [m MSL]. Use when latlon is True.
- iz, iy, ixint. Dataset keyword
The grid indices. Use when latlon is False
- latlonTolfloat. Dataset keyword
latitude-longitude tolerance to determine which grid point to use [deg]
- altTolfloat. Dataset keyword
Altitude tolerance to determine which grid point to use [deg]
GRID_MULTIPLE_POINTS#
- description
Obtains the grid data at a point location.
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- coord_fnamestring
File name containing the points coordinates
- latlonTolfloat. Dataset keyword
latitude-longitude tolerance to determine which grid point to use [deg]
MULTIPLE_POINTS#
- description
Obtains the radar data at multiple points. The points are defined in a file
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- truealtboolean. Dataset keyword
if True the user input altitude is used to determine the point of interest. if False use the altitude at a given radar elevation ele over the point of interest.
- coord_fnamestring
File name containing the points coordinates
- alt_pointsfloat. Dataset keyword
altitude [m MSL]. Use when latlon is True.
- ele_pointsfloat. Dataset keyword
radar elevation [deg]. Use when latlon is False or when latlon is True and truealt is False
- AziTolfloat. Dataset keyword
azimuthal tolerance to determine which radar azimuth to use [deg]
- EleTolfloat. Dataset keyword
elevation tolerance to determine which radar elevation to use [deg]
- RngTolfloat. Dataset keyword
range tolerance to determine which radar bin to use [m]
POINT_MEASUREMENT#
- description
Obtains the radar data at a point location.
- parameters
- datatypestring. Dataset keyword
The data type where we want to extract the point measurement
- single_pointboolean. Dataset keyword
if True only one gate per radar volume is going to be kept. Otherwise all gates within the azimuth and elevation tolerance are going to be kept. This is useful to extract all data from fixed pointing scans. Default True
- latlonboolean. Dataset keyword
if True position is obtained from latitude, longitude information, otherwise position is obtained from antenna coordinates (range, azimuth, elevation).
- truealtboolean. Dataset keyword
if True the user input altitude is used to determine the point of interest. if False use the altitude at a given radar elevation ele over the point of interest.
- lonfloat. Dataset keyword
the longitude [deg]. Use when latlon is True.
- latfloat. Dataset keyword
the latitude [deg]. Use when latlon is True.
- altfloat. Dataset keyword
altitude [m MSL]. Use when latlon is True and truealt is True
- elefloat. Dataset keyword
radar elevation [deg]. Use when latlon is False or when latlon is True and truealt is False
- azifloat. Dataset keyword
radar azimuth [deg]. Use when latlon is False
- rngfloat. Dataset keyword
range from radar [m]. Use when latlon is False
- AziTolfloat. Dataset keyword
azimuthal tolerance to determine which radar azimuth to use [deg]
- EleTolfloat. Dataset keyword
elevation tolerance to determine which radar elevation to use [deg]
- RngTolfloat. Dataset keyword
range tolerance to determine which radar bin to use [m]
- fill_valuefloat or None
If not None masked values are going to be filled by this value
TRAJ_ANTENNA_PATTERN#
- description
Process a new array of data volumes considering a plane trajectory. As result a timeseries with the values transposed for a given antenna pattern is created. The result is created when the LAST flag is set.
parameters
TRAJ_ATPLANE#
- description
Return time series according to trajectory
- parameters
- datatypelist of string. Dataset keyword
The input data types
- data_is_logdict. Dataset keyword
Dictionary specifying for each field if it is in log (True) or linear units (False). Default False
- ang_tolfloat. Dataset keyword
Factor that multiplies the angle resolution. Used when determining the neighbouring rays. Default 1.2
- az_tol, el_tolfloat
azimuth and elevation tolerance (deg). Samples that have values beyond this tolerance from the limits in azimuth and elevation of the radar will be considered outside the sector. Default 3.
- timeformatstr or None
time format of the time series output file
TRAJ_LIGHTNING#
- description
Return time series according to lightning trajectory
- parameters
- datatypelist of string. Dataset keyword
The input data types
- data_is_logdict. Dataset keyword
Dictionary specifying for each field if it is in log (True) or linear units (False). Default False
- ang_tolfloat. Dataset keyword
Factor that multiplies the angle resolution. Used when determining the neighbouring rays. Default 1.2
- az_tol, el_tolfloat
azimuth and elevation tolerance (deg). Samples that have values beyond this tolerance from the limits in azimuth and elevation of the radar will be considered outside the sector. Default 3.
TRAJ_ONLY#
TRAJ#
- description
Return trajectory
- parameters
- datatypelist of string. Dataset keyword
The input data types