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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types ATT_METHOD : float. Dataset keyword The attenuation estimation method used. One of the following: ZPhi, Philin. Default ZPhi fzl : float. 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. sounding : str. 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 `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement angle : float or None. Dataset keyword The center angle to average. If not set or set to -1 all available azimuth angles will be used delta_azi : float. Dataset keyword The angle span to average. If not set or set to -1 all the available azimuth angles will be used avg_type : str. Dataset keyword Average type. Can be mean or median. Default mean nvalid_min : int. Dataset keyword the minimum number of valid points to consdier the average valid. Default 1 lin_trans : dict 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 `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement delta_azi : float. Dataset keyword The angle span to average. Default 20 avg_type : str. Dataset keyword Average type. Can be mean or median. Default mean nvalid_min : int. Dataset keyword the minimum number of valid points to consdier the average valid. Default 1 lin_trans : dict 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 `[Source] `_ parameters datatype : string. Dataset keyword The data type to correct for bias bias : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types BIRD_DENSITY """""""""""""""""""""""""""""" description Computes the bird density from the volumetric reflectivity `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types sigma_bird : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types CDF """""""""""""""""""""""""""""" description Collects the fields necessary to compute the Cumulative Distribution Function `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types CDR """""""""""""""""""""""""""""" description Computes Circular Depolarization Ratio `[Source] `_ parameters datatype : string. Dataset keyword The input data type CLT_TO_SAN """""""""""""""""""""""""""""" description Converts clutter exit code from rad4alp into pyrad echo ID `[Source] `_ parameters datatype : list 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 `[Source] `_ parameters datatype : string. Dataset keyword arbitrary data type lookup_table : int. 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_grid : int. 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_type : str. Dataset keyword name of the icon field to process. Default TEMP icon_variables : list of strings. Dataset keyword Py-art name of the icon fields. Default temperature DEM """""""""""""""""""""""""""""" description Gets DEM data and put it in radar coordinates `[Source] `_ parameters datatype : string. Dataset keyword arbitrary data type keep_in_memory : int. 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_grid : int. 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_field : str. Dataset keyword name of the DEM field to process demfile : str. 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 `[Source] `_ parameters datatype : string. Dataset keyword The input data type filt : int. Dataset keyword Flag controlling Bergen and Albers filter, 1 = yes, 0 = no. sign : int. 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 `[Source] `_ parameters datatype : string. Dataset keyword The input data type interval_splits : int, 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_ray : int, 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. centered : bool, 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_vel : float, 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 `[Source] `_ parameters datatype : string. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types DOPPLER_VELOCITY_IQ """""""""""""""""""""""""""""" description Compute the Doppler velocity from the spectral reflectivity `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types direction : str 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types DOPPLER_WIDTH_IQ """""""""""""""""""""""""""""" description Compute the Doppler spectrum width from the spectral reflectivity `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types subtract_noise : Bool If True noise will be subtracted from the signals lag : int 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types echo_type : int 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types FIXED_RNG """""""""""""""""""""""""""""" description Obtains radar data at a fixed range `[Source] `_ parameters datatype : list of strings. Dataset keyword The fields we want to extract rng : float. Dataset keyword The fixed range [m] RngTol : float. Dataset keyword The tolerance between the nominal range and the radar range ele_min, ele_max, azi_min, azi_max : floats. 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 `[Source] `_ parameters datatype : list of strings. Dataset keyword The fields we want to extract rmin, rmax : float. Dataset keyword The range limits [m] ele_min, ele_max, azi_min, azi_max : floats. 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. `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types lower_bounds : list of float The list of lower bounds for every input data type upper_bounds : list 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types range_discretization : float. Dataset keyword Range discretization used when computing the Cartesian visibility field the larger the better but the slower the processing will be az_discretization : float. Dataset keyword Azimuth discretization used when computing the Cartesian visibility field, the larger the better but the slower the processing will be ke : float. Dataset keyword Equivalent earth-radius factor used in the computation of the radar beam refraction atm_att : float. Dataset keyword One-way atmospheric refraction in db / km mosotti_kw : float. Dataset keyword Clausius-Mosotti factor K, depends on material (water) and wavelength for water = sqrt(0.93) raster_oversampling : int. 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_method : string. Dataset keyword Which estimation method to use, either 'Gabella' or 'Delrieu' clip : int. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types HYDRO_METHOD : string. Dataset keyword The hydrometeor classification method. One of the following: SEMISUPERVISED, UKMO centroids_file : string 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_entropy : bool. Dataset keyword Used with HYDRO_METHOD SEMISUPERVISED. If true the entropy is computed and the field hydroclass_entropy is output output_distances : bool. 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 vectorize : bool. Dataset keyword Used with HYDRO_METHOD SEMISUPERVISED. If true a vectorized version of the algorithm is used weights : array of floats. Dataset keyword Used with HYDRO_METHOD SEMISUPERVISED. The list of weights given to each variable hydropath : string. Dataset keyword Used with HYDRO_METHOD UKMO. Directory of the UK MetOffice hydrometeor classification code mf_dir : string. 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. sounding : str. 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 `[Source] `_ parameters metranet_read_lib : str. Global keyword Type of METRANET reader library used to read the data. Can be 'C' or 'python' datatype : string. Dataset keyword arbitrary data type keep_in_memory : int. Dataset keyword if set keeps the icon data dict, the icon coordinates dict and the icon field in radar coordinates in memory regular_grid : int. 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_type : str. Dataset keyword name of the icon field to process. Default TEMP icon_variables : list 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 `[Source] `_ parameters metranet_read_lib : str. Global keyword Type of METRANET reader library used to read the data. Can be 'C' or 'python' datatype : string. Dataset keyword arbitrary data type lookup_table : int. 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_grid : int. 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 `[Source] `_ parameters datatype : string. Dataset keyword arbitrary data type time_interp : bool. 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. `[Source] `_ parameters datatype : string. Dataset keyword arbitrary data type iso0_statistic : str. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rwind : float. Dataset keyword The length of the segment for the least square method [m]. Default 6000. vectorize : bool. Dataset keyword Whether to vectorize the KDP processing. Default false KDP_LEASTSQUARE_2W """""""""""""""""""""""""""""" description Computes specific differential phase using a piecewise least square method `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rwinds : float. Dataset keyword The length of the short segment for the least square method [m]. Default 2000. rwindl : float. Dataset keyword The length of the long segment for the least square method [m]. Default 6000. Zthr : float. Dataset keyword The threshold defining which estimated data to use [dBZ] vectorize : Bool. 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 `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement trtfile : str. Dataset keyword TRT file from which to extract the region of interest time_tol : float. Dataset keyword Time tolerance between the TRT file date and the nominal radar volume time lon_roi, lat_roi : float array. Dataset keyword latitude and longitude positions defining a region of interest alt_min, alt_max : float. Dataset keyword Minimum and maximum altitude of the region of interest. Can be None cercle : boolean. 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_centre : Float. Dataset keyword The position of the centre of the cercle. If None, that of the radar will be used rad_cercle : Float. Dataset keyword The radius of the cercle in m. Default 1000. res_cercle : int. Dataset keyword Number of points used to define a quarter of cercle. Default 16 box : boolean. Dataset keyword If True the region of interest is going to be defined by a rectangle lon_point, lat point : Float The position of the point of rotation of the box. If None the position of the radar is going to be used rotation : float The angle of rotation. Positive is counterclockwise from North in deg. Default 0. we_offset, sn_offset : float west-east and south-north offset from rotation position in m. Default 0 we_length, sn_length : float west-east and south-north rectangle lengths in m. Default 1000. origin : str 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_latlon : Bool. 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 `[Source] `_ parameters datatype : string. Dataset keyword The input data type MEAN_PHASE_IQ """""""""""""""""""""""""""""" description Computes the mean phase from the horizontal or vertical IQ data `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types NCVOL """""""""""""""""""""""""""""" description Dummy function that allows to save the entire radar object `[Source] `_ parameters NOISE_POWER """""""""""""""""""""""""""""" description Computes the noise power from the spectra `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types units : str The units of the returned signal. Can be 'ADU', 'dBADU' or 'dBm' navg : int Number of spectra averaged rmin : int Range from which the data is used to estimate the noise nnoise_min : int Minimum number of samples to consider the estimated noise power valid OUTLIER_FILTER """""""""""""""""""""""""""""" description filters out gates which are outliers respect to the surrounding `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types threshold : float. 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 nb : int. Dataset keyword The number of neighbours (to one side) to analyse. i.e. 2 would correspond to 24 gates nb_min : int. Dataset keyword Minimum number of neighbouring gates to consider the examined gate valid percentile_min, percentile_max : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rmin : float. Dataset keyword The minimum range where to look for valid data [m]. Default 1000. rmax : float. Dataset keyword The maximum range where to look for valid data [m]. Default 50000. rcell : float. Dataset keyword The length of a continuous cell to consider it valid precip [m]. Default 1000. Zmin : float. Dataset keyword The minimum reflectivity [dBZ]. Default 20. Zmax : float. Dataset keyword The maximum reflectivity [dBZ]. Default 40. PHIDP0_ESTIMATE """""""""""""""""""""""""""""" description estimates the system differential phase offset at each ray `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rmin : float. Dataset keyword The minimum range where to look for valid data [m] rmax : float. Dataset keyword The maximum range where to look for valid data [m] rcell : float. Dataset keyword The length of a continuous cell to consider it valid precip [m] Zmin : float. Dataset keyword The minimum reflectivity [dBZ] Zmax : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types parallel : boolean. Dataset keyword if set use parallel computing get_phidp : boolean. Datset keyword if set the PhiDP computed by integrating the resultant KDP is added to the radar field frequency : float. 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. `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types fzl : float. Dataset keyword The freezing level height [m]. Default 2000. sounding : str. 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_thickness : float. Dataset keyword The melting layer thickness in meters. Default 700. beamwidth : float. 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_solver : str. The LP solver to use. Can be pyglpk, cvxopt, cylp, cylp_mp. Default cvxopt proc : int Number of worker processes. Only used when LP_solver is cylp_mp. Default 1 min_snr, min_rhv : float 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_phase : float Default system differential phase offset in deg. Default 0. overide_sys_phase : bool 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_sysp : int First gate to use when determining the system differential phase offset. Default 0 nowrap : int or None Gate number where to begin the phase unwrapping. None will unwrap from gate 0. Default None ncpts : int 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_bias : float reflectivity bias. Default 0 dBZ low_z, high_z : float 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_phidp : float 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 doc : int Number of gates to doc at the end of the ray. Used in the LP algorithm. Default 0 self_const : float selfconsistency factor. Used in the LP algorithm. Default 60000 coef : float Exponent linking Z to KDP in selfconsistency. Used in the LP algorithm. kdp = (10**(0.1z))**coef. Default 0.914 window_len : int 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rwind : float. Dataset keyword The length of the segment [m]. Default 2000. n_iter : int. Dataset keyword number of iterations. Default 3. interp : boolean. Dataset keyword if set non valid values are interpolated using neighbouring valid values. Default 0 (False) parallel : boolean. Dataset keyword if set use parallel computing. Default 1 (True) get_phidp : boolean. Datset keyword if set the PhiDP computed by integrating the resultant KDP is added to the radar field. Default 0 (False) frequency : float. 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) `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rmin : float. Dataset keyword The minimum range where to look for valid data [m]. Default 1000. rmax : float. Dataset keyword The maximum range where to look for valid data [m]. Default 50000. rcell : float. Dataset keyword The length of a continuous cell to consider it valid precip [m]. Default 1000. Zmin : float. Dataset keyword The minimum reflectivity [dBZ]. Default 20 Zmax : float. Dataset keyword The maximum reflectivity [dBZ]. Default 40 fzl : float. Dataset keyword The freezing level height [m]. Default 2000. sounding : str. 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_thickness : float. Dataset keyword The melting layer thickness in meters. Default 700. beamwidth : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rmin : float. Dataset keyword The minimum range where to look for valid data [m]. Default 1000. rmax : float. Dataset keyword The maximum range where to look for valid data [m]. Default 50000. rcell : float. Dataset keyword The length of a continuous cell to consider it valid precip [m]. Default 1000. rwind : float. Dataset keyword The length of the smoothing window [m]. Default 6000. Zmin : float. Dataset keyword The minimum reflectivity [dBZ]. Default 20. Zmax : float. Dataset keyword The maximum reflectivity [dBZ]. Default 40. PHIDP_SMOOTH_2W """""""""""""""""""""""""""""" description corrects phidp of the system phase and smoothes it using one window `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rmin : float. Dataset keyword The minimum range where to look for valid data [m] rmax : float. Dataset keyword The maximum range where to look for valid data [m] rcell : float. Dataset keyword The length of a continuous cell to consider it valid precip [m] rwinds : float. Dataset keyword The length of the short smoothing window [m] rwindl : float. Dataset keyword The length of the long smoothing window [m] Zmin : float. Dataset keyword The minimum reflectivity [dBZ] Zmax : float. Dataset keyword The maximum reflectivity [dBZ] Zthr : float. Dataset keyword The threshold defining wich smoothed data to used [dBZ] POL_VARIABLES """""""""""""""""""""""""""""" description Computes the polarimetric variables from the complex spectra `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types subtract_noise : Bool If True noise will be subtracted from the signal. Default False smooth_window : int or None Size of the moving Gaussian smoothing window. If none no smoothing will be applied. Default None variables : list of str list of variables to compute. Default dBZ POL_VARIABLES_IQ """""""""""""""""""""""""""""" description Computes the polarimetric variables from the IQ data `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types subtract_noise : Bool If True noise will be subtracted from the signal lag : int The time lag to use in the estimators direction : str The convention used in the Doppler mean field. Can be negative_away or negative_towards variables : list of str list of variables to compute. Default dBZ phase_offset : float. Dataset keyword The system differential phase offset to remove PWR """""""""""""""""""""""""""""" description Computes the signal power in dBm `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types mflossh, mflossv : float. 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, radconstv : float. Dataset keyword The horizontal (vertical) channel radar constant. If None it will be obtained from the attribute radar_calibration of the radar object lrxh, lrxv : float. Global keyword The horizontal (vertical) receiver losses from the antenna feed to the reference point. [dB] positive value. Default 0 lradomeh, lradomev : float. Global keyword The 1-way dry radome horizontal (vertical) channel losses. [dB] positive value. Default 0. attg : float. 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 `[Source] `_ parameters RADIAL_NOISE_HS """""""""""""""""""""""""""""" description Computes the radial noise from the signal power using the Hildebrand and Sekhon 1974 method `[Source] `_ parameters datatype : string. Dataset keyword The input data type rmin : float. Dataset keyword The minimum range from which to start the computation nbins_min : int. Dataset keyword The minimum number of noisy gates to consider the estimation valid max_std_pwr : float. Dataset keyword The maximum standard deviation of the noise power to consider the estimation valid get_noise_pos : bool. 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 `[Source] `_ parameters datatype : string. Dataset keyword The input data type npulses_ray : int 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_pos : bool 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 `[Source] `_ parameters datatype : string. Dataset keyword The input data type latitude, longitude : float arbitrary coordinates [deg] from where to compute the radial velocity. If any of them is None it will be the radar position altitude : float 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 `[Source] `_ parameters datatype : string. Dataset keyword The input data type RR_METHOD : string. Dataset keyword The rainfall rate estimation method. One of the following: Z, ZPoly, KDP, A, ZKDP, ZA, hydro alpha, beta : float 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, betaz : float factor and exponent of the R-Z power law R = alpha*Z^Beta. Default value (0.0376, 0.6112) alphazr, betazr : float 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, betazs : float 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, betakdp : float factor and exponent of the R-KDP power law R = alpha*KDP^Beta. Default value (None, None) alphaa, betaa : float factor and exponent of the R-Ah power law R = alpha*Ah^Beta. Default value (None, None) thresh : float 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_factor : float 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 `[Source] `_ parameters REFLECTIVITY """""""""""""""""""""""""""""" description Computes reflectivity from the spectral reflectivity `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types REFLECTIVITY_IQ """""""""""""""""""""""""""""" description Computes reflectivity from the IQ data `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types subtract_noise : Bool If True noise will be subtracted from the signal RCS """""""""""""""""""""""""""""" description Computes the radar cross-section (assuming a point target) from radar reflectivity. `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types kw2 : float. Dataset keyowrd The water constant pulse_width : float. Dataset keyowrd The pulse width [s] beamwidthv : float. Global keyword The vertical polarization antenna beamwidth [deg]. Used if input is vertical reflectivity beamwidthh : float. 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. `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types AntennaGainH, AntennaGainV : float. 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, txpwrv : float. 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, mflossv : float. 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, radconstv : float. Dataset keyword The horizontal (vertical) channel radar constant. If None it will be obtained from the attribute radar_calibration of the radar object lrxh, lrxv : float. Global keyword The horizontal (vertical) receiver losses from the antenna feed to the reference point. [dB] positive value. Default 0 ltxh, ltxv : float. 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, lradomev : float. Global keyword The 1-way dry radome horizontal (vertical) channel losses. [dB] positive value. Default 0. attg : float. 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 `[Source] `_ parameters datatype : list 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rmin : float. Dataset keyword minimum range where to look for rain [m]. Default 1000. rmax : float. Dataset keyword maximum range where to look for rain [m]. Default 50000. Zmin : float. Dataset keyword minimum reflectivity to consider the bin as precipitation [dBZ]. Default 20. Zmax : float. Dataset keyword maximum reflectivity to consider the bin as precipitation [dBZ] Default 40. ml_thickness : float. Dataset keyword assumed thickness of the melting layer. Default 700. fzl : float. 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. sounding : str. 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. `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement trtfile : str. Dataset keyword TRT file from which to extract the region of interest time_tol : float. Dataset keyword Time tolerance between the TRT file date and the nominal radar volume time lon_roi, lat_roi : float array. Dataset keyword latitude and longitude positions defining a region of interest alt_min, alt_max : float. Dataset keyword Minimum and maximum altitude of the region of interest. Can be None cercle : boolean. 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_centre : Float. Dataset keyword The position of the centre of the cercle rad_cercle : Float. Dataset keyword The radius of the cercle in m. Default 1000. res_cercle : int. Dataset keyword Number of points used to define a quarter of cercle. Default 16 lon_point, lat point : Float The position of the point of rotation of the box. If None the position of the radar is going to be used rotation : float The angle of rotation. Positive is counterclockwise from North in deg. Default 0. we_offset, sn_offset : float west-east and south-north offset from rotation position in m. Default 0 we_length, sn_length : float west-east and south-north rectangle lengths in m. Default 1000. origin : str 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_latlon : Bool. 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 `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement trtfile : str. Dataset keyword TRT file from which to extract the region of interest time_tol : float. Dataset keyword Time tolerance between the TRT file date and the nominal radar volume time lon_roi, lat_roi : float array. Dataset keyword latitude and longitude positions defining a region of interest alt_min, alt_max : float. Dataset keyword Minimum and maximum altitude of the region of interest. Can be None cercle : boolean. 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_centre : Float. Dataset keyword The position of the centre of the cercle rad_cercle : Float. Dataset keyword The radius of the cercle in m. Default 1000. res_cercle : int. Dataset keyword Number of points used to define a quarter of cercle. Default 16 box : boolean. Dataset keyword If True the region of interest is going to be defined by a rectangle lon_point, lat point : Float The position of the point of rotation of the box. If None the position of the radar is going to be used rotation : float The angle of rotation. Positive is counterclockwise from North in deg. Default 0. we_offset, sn_offset : float west-east and south-north offset from rotation position in m. Default 0 we_length, sn_length : float west-east and south-north rectangle lengths in m. Default 1000. origin : str 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_latlon : Bool. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types wind_size : int Size of the moving window used to compute the ray texture (number of gates). Default 7 max_textphi, max_textrhv, max_textzdr, max_textrefl : float 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_rhv : float Minimum value for the RhoHV. Default 0.6 SELFCONSISTENCY_BIAS """""""""""""""""""""""""""""" description Estimates the reflectivity bias by means of the selfconsistency algorithm by Gourley `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types parametrization : str 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'. fzl : float. Dataset keyword Default freezing level height. Default 2000. sounding : str. 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. rsmooth : float. Dataset keyword length of the smoothing window [m]. Default 2000. min_rhohv : float. Dataset keyword minimum valid RhoHV. Default 0.92 filter_rain : Bool. Dataset keyword If True the hydrometeor classification is used to filter out gates that are not rain. Default True max_phidp : float. Dataset keyword maximum valid PhiDP [deg]. Default 20. ml_thickness : float. Dataset keyword Melting layer thickness [m]. Default 700. rcell : float. Dataset keyword length of continuous precipitation to consider the precipitation cell a valid phidp segment [m]. Default 15000. dphidp_min : float. Dataset keyword minimum phase shift [deg]. Default 2. dphidp_max : float. Dataset keyword maximum phase shift [deg]. Default 16. frequency : float. 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_radome : Bool. 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_refl : Float. 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_max : Float. 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_min : int Minimum number of valid gates to consider that the radome is wet. Default 180 valid_gates_only : Bool 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_points : Bool 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 rkdp : float 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types parametrization : str 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'. fzl : float. Dataset keyword Default freezing level height. Default 2000. sounding : str. 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. rsmooth : float. Dataset keyword length of the smoothing window [m]. Default 2000. min_rhohv : float. Dataset keyword minimum valid RhoHV. Default 0.92 filter_rain : Bool. Dataset keyword If True the hydrometeor classification is used to filter out gates that are not rain. Default True max_phidp : float. Dataset keyword maximum valid PhiDP [deg]. Default 20. ml_thickness : float. Dataset keyword Melting layer thickness [m]. Default 700. rcell : float. Dataset keyword length of continuous precipitation to consider the precipitation cell a valid phidp segment [m]. Default 15000. frequency : float. 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_radome : Bool. 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_refl : Float. 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_max : Float. 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_min : int Minimum number of valid gates to consider that the radome is wet. Default 180 keep_points : Bool 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_gate : Bool 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 `[Source] `_ parameters datatype : list of strings. Dataset keyword The input data types parametrization : str 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'. rsmooth : float. Dataset keyword length of the smoothing window [m]. Default 2000. min_rhohv : float. Dataset keyword minimum valid RhoHV. Default 0.92 filter_rain : Bool. Dataset keyword If True the hydrometeor classification is used to filter out gates that are not rain. Default True max_phidp : float. Dataset keyword maximum valid PhiDP [deg]. Default 20. ml_thickness : float. Dataset keyword assumed melting layer thickness [m]. Default 700. fzl : float. 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. sounding : str. 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. frequency : float. 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 `[Source] `_ parameters datatype : string. Dataset keyword The input data type output_type : string. Dataset keyword The output data type. Either SNRh or SNRv SNR_FILTER """""""""""""""""""""""""""""" description filters out low SNR echoes `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types SNRmin : float. 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 `[Source] `_ parameters datatype : list 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types TRAJ_TRT """""""""""""""""""""""""""""" description Processes data according to TRT trajectory `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types time_tol : float. Dataset keyword tolerance between reference time of the radar volume and that of the TRT cell [s]. Default 100. alt_min, alt_max : float. Dataset keyword Minimum and maximum altitude of the data inside the TRT cell to retrieve [m MSL]. Default None cell_center : Bool. Dataset keyword If True only the range gate closest to the center of the cell is extracted. Default False latlon_tol : Float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types time_tol : float. 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 `[Source] `_ parameters datatype : string. Dataset keyword The input data type radius : float. Dataset keyword Search radius for calculating Eddy Dissipation Rate (EDR). Default 2 split_cut : Bool. Dataset keyword Set to True for split-cut volumes. Default False max_split_cut : Int. Dataset keyword Total number of tilts that are affected by split cuts. Only relevant if split_cut=True. Default 2 xran, yran : float array. Dataset keyword Spatial range in X,Y to consider. Default [-100, 100] for both X and Y use_ntda : Bool. Dataset keyword Wether to use NCAR Turbulence Detection Algorithm (NTDA). Default True beamwidth : Float. 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_pos : Bool. 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 verbose : Bool. Dataset keyword True for verbose output. Default False VAD """""""""""""""""""""""""""""" description Estimates vertical wind profile using the VAD (velocity Azimuth Display) technique `[Source] `_ parameters datatype : string. Dataset keyword The input data type VEL_FILTER """""""""""""""""""""""""""""" description filters out range gates that could not be used for Doppler velocity estimation `[Source] `_ parameters datatype : list 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. `[Source] `_ parameters datatype : string. Dataset keyword arbitrary data type offset : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types VISmin : float. Dataset keyword The minimum visibility to keep the data. VOL_REFL """""""""""""""""""""""""""""" description Computes the volumetric reflectivity in 10log10(cm^2 km^-3) `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types freq : float. Dataset keyword The radar frequency kw : float. Dataset keyword The water constant VOL2BIRD_FILTER """""""""""""""""""""""""""""" description Masks all echo types that have been identified as non-biological by vol2bird `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types VOL2BIRD_GATE_FILTER """""""""""""""""""""""""""""" description Adds filter on range gate values to the vol2bird filter `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types dBZ_max : float Maximum reflectivity of biological scatterers V_min : float Minimum Doppler velocity of biological scatterers VSTATUS_TO_SAN """""""""""""""""""""""""""""" description Converts velocity status from lidar data into pyrad echo ID `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types WBN """""""""""""""""""""""""""""" description Computes the wide band noise from the horizontal or vertical IQ data `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types WIND_VEL """""""""""""""""""""""""""""" description Estimates the horizontal or vertical component of the wind from the radial velocity `[Source] `_ parameters datatype : string. Dataset keyword The input data type vert_proj : Boolean If true the vertical projection is computed. Otherwise the horizontal projection is computed WINDSHEAR """""""""""""""""""""""""""""" description Estimates the wind shear from the wind velocity `[Source] `_ parameters datatype : string. Dataset keyword The input data type az_tol : float 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 `[Source] `_ parameters datatype : string. Dataset keyword The input data type az_tol : float 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types ZDR_IQ """""""""""""""""""""""""""""" description Computes differential reflectivity from the horizontal and vertical IQ data `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types subtract_noise : Bool If True noise will be subtracted from the signal lag : int 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) `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types ml_filter : boolean. Dataset keyword indicates if a filter on data in and above the melting layer is applied. Default True. rmin : float. Dataset keyword minimum range where to look for rain [m]. Default 1000. rmax : float. Dataset keyword maximum range where to look for rain [m]. Default 50000. Zmin : float. Dataset keyword minimum reflectivity to consider the bin as precipitation [dBZ]. Default 20. Zmax : float. Dataset keyword maximum reflectivity to consider the bin as precipitation [dBZ] Default 22. RhoHVmin : float. Dataset keyword minimum RhoHV to consider the bin as precipitation Default 0.97 PhiDPmax : float. Dataset keyword maximum PhiDP to consider the bin as precipitation [deg] Default 10. elmax : float. Dataset keyword maximum elevation angle where to look for precipitation [deg] Default None. ml_thickness : float. Dataset keyword assumed thickness of the melting layer. Default 700. fzl : float. 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. sounding : str. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types rmin : float. Dataset keyword minimum range where to look for rain [m]. Default 1000. rmax : float. Dataset keyword maximum range where to look for rain [m]. Default 50000. Zmin : float. Dataset keyword minimum reflectivity to consider the bin as snow [dBZ]. Default 0. Zmax : float. Dataset keyword maximum reflectivity to consider the bin as snow [dBZ] Default 30. SNRmin : float. Dataset keyword minimum SNR to consider the bin as snow [dB]. Default 10. SNRmax : float. Dataset keyword maximum SNR to consider the bin as snow [dB] Default 50. RhoHVmin : float. Dataset keyword minimum RhoHV to consider the bin as snow Default 0.97 PhiDPmax : float. Dataset keyword maximum PhiDP to consider the bin as snow [deg] Default 10. elmax : float. Dataset keyword maximum elevation angle where to look for snow [deg] Default None. KDPmax : float. Dataset keyword maximum KDP to consider the bin as snow [deg] Default None TEMPmin : float. Dataset keyword minimum temperature to consider the bin as snow [deg C]. Default None TEMPmax : float. Dataset keyword maximum temperature to consider the bin as snow [deg C] Default None hydroclass : list 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types window : list 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types filter_width : float The Doppler filter width. Default 0. filter_units : str 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types clipping_level : float The clipping level [dB above noise level]. Default 10. IFFT """""""""""""""""""""""""""""" description Compute the Doppler spectrum width from the spectral reflectivity `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types RAW_IQ """""""""""""""""""""""""""""" description Dummy function that returns the initial input data set `[Source] `_ parameters RAW_SPECTRA """""""""""""""""""""""""""""" description Dummy function that returns the initial input data set `[Source] `_ 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. `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types navg : int 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. `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement single_point : boolean. 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 latlon : boolean. Dataset keyword if True position is obtained from latitude, longitude information, otherwise position is obtained from antenna coordinates (range, azimuth, elevation). Default False truealt : boolean. 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 lon : float. Dataset keyword the longitude [deg]. Use when latlon is True. lat : float. Dataset keyword the latitude [deg]. Use when latlon is True. alt : float. Dataset keyword altitude [m MSL]. Use when latlon is True. Default 0. ele : float. Dataset keyword radar elevation [deg]. Use when latlon is False or when latlon is True and truealt is False azi : float. Dataset keyword radar azimuth [deg]. Use when latlon is False rng : float. Dataset keyword range from radar [m]. Use when latlon is False AziTol : float. Dataset keyword azimuthal tolerance to determine which radar azimuth to use [deg]. Default 0.5 EleTol : float. Dataset keyword elevation tolerance to determine which radar elevation to use [deg]. Default 0.5 RngTol : float. Dataset keyword range tolerance to determine which radar bin to use [m]. Default 50. SPECTRAL_NOISE """""""""""""""""""""""""""""" description Computes the spectral noise `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types units : str The units of the returned signal. Can be 'ADU', 'dBADU' or 'dBm' navg : int Number of spectra averaged rmin : int Range from which the data is used to estimate the noise nnoise_min : int Minimum number of samples to consider the estimated noise power valid SPECTRAL_PHASE """""""""""""""""""""""""""""" description Computes the spectral phase `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types SPECTRAL_POWER """""""""""""""""""""""""""""" description Computes the spectral power `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types units : str The units of the returned signal. Can be 'ADU', 'dBADU' or 'dBm' subtract_noise : Bool If True noise will be subtracted from the signal smooth_window : int or None Size of the moving Gaussian smoothing window. If none no smoothing will be applied SPECTRAL_REFLECTIVITY """""""""""""""""""""""""""""" description Computes spectral reflectivity `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types subtract_noise : Bool If True noise will be subtracted from the signal smooth_window : int 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types sRhoHV_threshold : float Data with sRhoHV module above this threshold will be filtered. Default 1. CENTROIDS ----------------------------- CENTROIDS """""""""""""""""""""""""""""" description Computes centroids for the semi-supervised hydrometeor classification `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types samples_per_vol : int. Dataset keyword Maximum number of samples per volume kept for further analysis. Default 20000 nbins : int. Number of bins of the histogram used to make the data platykurtic. Default 110 pdf_zh_max : int 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_max : int 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_relh : float sigma of the respective Gaussian functions. Defaults 0.75 and 1.5 randomize : bool If True the data is randomized to avoid the effects of the quantization. Default True platykurtic_dBZ : bool If True makes the reflectivity distribution platykurtic. Default True platykurtic_H_ISO0 : bool If True makes the height respect to the iso-0 distribution platykurtic. Default True relh_slope : float. Dataset keyword The slope used to transform the height relative to the iso0 into a sigmoid function. Default 0.001 external_iterations : int. 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_iterations : int. Dataset keyword Maximum number of iterations of the internal loop. Default 10 sample_data : Bool. If True the data is going to be sampled prior to each external iteration. Default False nsamples_iter : int. Number of samples per iteration. Default 20000 alpha : float Minimum value to accept the cluster according to p. Default 0.01 cv_approach : Bool 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_syn : int Number of samples drawn from reference to compare it with observations in the KS test. Default 50 num_samples_arr : array of int Number of observation samples used in the KS test to choose from. Default (30, 35, 40) acceptance_threshold : float. 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_min : int Minimum number of intermediate medoids to compute the final result. Default 1 var_names : tupple 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') weight : tupple 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) parallelized : bool If True the centroids search is going to be parallelized. Default False kmax_iter : int Maximum number of iterations of the k-medoids algorithm. Default 100 nsamples_small : int Maximum number before using the k-medoids CLARA algorithm. If this number is exceeded the CLARA algorithm will be used. Default 40000 sampling_size_clara : int Number of samples used in each iteration of the k-medoids CLARA algorithm. Default 10000 niter_clara : int Number of iterations performed by the k-medoids CLARA algorithm. Default 5 keep_labeled_data : bool If True the labeled data is going to be kept for storage. Default True use_median : bool 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_duplicates : bool If True allow to label multiple clusters with the same label. Default True COLOCATED_GATES ----------------------------- COLOCATED_GATES """""""""""""""""""""""""""""" description Find colocated gates within two radars `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types h_tol : float. Dataset keyword Tolerance in altitude difference between radar gates [m]. Default 100. latlon_tol : float. Dataset keyword Tolerance in latitude and longitude position between radar gates [deg]. Default 0.0005 vol_d_tol : float. Dataset keyword Tolerance in pulse volume diameter [m]. Default 100. vismin : float. Dataset keyword Minimum visibility [percent]. Default None. hmin : float. Dataset keyword Minimum altitude [m MSL]. Default None. hmax : float. Dataset keyword Maximum altitude [m MSL]. Default None. rmin : float. Dataset keyword Minimum range [m]. Default None. rmax : float. Dataset keyword Maximum range [m]. Default None. elmin : float. Dataset keyword Minimum elevation angle [deg]. Default None. elmax : float. Dataset keyword Maximum elevation angle [deg]. Default None. azrad1min : float. Dataset keyword Minimum azimuth angle [deg] for radar 1. Default None. azrad1max : float. Dataset keyword Maximum azimuth angle [deg] for radar 1. Default None. azrad2min : float. Dataset keyword Minimum azimuth angle [deg] for radar 2. Default None. azrad2max : float. 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 `[Source] `_ parameters datatype : string. Dataset keyword arbitrary data type iconpath : string. General keyword path where to store the look up table model : string. 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 `[Source] `_ parameters metranet_read_lib : str. Global keyword Type of METRANET reader library used to read the data. Can be 'C' or 'python' datatype : string. Dataset keyword arbitrary data type iconpath : string. 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 `[Source] `_ parameters datatype : string. Dataset keyword arbitrary data type icon_type : str. Dataset keyword name of the icon field to process. Default TEMP icon_variables : list of strings. Dataset keyword Py-art name of the icon fields. Default temperature icon_time_index_min, icon_time_index_max : int 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 `[Source] `_ parameters GECSX """""""""""""""""""""""""""""" description Computes ground clutter RCS, radar visibility and many others using the GECSX algorithmn translated from IDL into python `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types range_discretization : float. Dataset keyword Range discretization used when computing the Cartesian visibility field the larger the better but the slower the processing will be az_discretization : float. Dataset keyword Azimuth discretization used when computing the Cartesian visibility field, the larger the better but the slower the processing will be ke : float. Dataset keyword Equivalent earth-radius factor used in the computation of the radar beam refraction atm_att : float. Dataset keyword One-way atmospheric refraction in db / km mosotti_kw : float. Dataset keyword Clausius-Mosotti factor K, depends on material (water) and wavelength for water = sqrt(0.93) raster_oversampling : int. 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_method : string. Dataset keyword Which estimation method to use, either 'Gabella' or 'Delrieu' clip : int. 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 `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement gridconfig : dictionary. 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 wfunc : str. 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_func : str. Dataset keyword the function used to compute the region of interest. Possible values: dist_beam, constant roi : float. Dataset keyword the (minimum) radius of the region of interest in m. Default half the largest resolution beamwidth : float. 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_spacing : float. 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 `[Source] `_ parameters datatype : list 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 `[Source] `_ parameters GRID_TEXTURE """""""""""""""""""""""""""""" description Computes the 2D texture of a gridded field `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types xwind, ywind : int The size of the local window in the x and y axis. Default 7 fill_value : float 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. `[Source] `_ parameters PIXEL_FILTER """""""""""""""""""""""""""""" description Masks all pixels that are not of the class specified in keyword pixel_type `[Source] `_ parameters pixel_type : int 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 `[Source] `_ parameters xmin, xmax, ymin, ymax : float Horizontal limits of the grid [m from origin]. Default +-20000. zmin, zmax : float vertical limits of the grid [masl]. Default 1000. hres, vres : float horizontal and vertical resolution [m]. Default 1000. lat0, lon0 : float Grid origin [deg]. The default will be the radar position alt0 : float Grid origin altitude [masl]. Default is 0 wfunc : str Weighting function. Default NEAREST DDA """""""""""""""""""""""""""""" description Estimates horizontal wind speed and direction with a multi-doppler approach This method uses the python package pyDDA `[Source] `_ parameters datatype : string. Dataset keyword The input data type gridconfig : dictionary. 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 wfunc : str. 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_func : str. Dataset keyword the function used to compute the region of interest. Possible values: dist_beam, constant roi : float. Dataset keyword the (minimum) radius of the region of interest in m. Default half the largest resolution beamwidth : float. 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_spacing : float. 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 signs : list 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. Co : float Weight for cost function related to observed radial velocities. Default: 1. Cm : float 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. frz : float 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types period : float. Dataset keyword the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600. start_average : float. 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_nan : bool. Dataset keyword If true non valid data will be used nan_value : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types period : float. Dataset keyword the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600. start_average : float. 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_nan : bool. Dataset keyword If true non valid data will be used nan_value : float. Dataset keyword The value of the non valid data. Default 0 GRID_RAIN_ACCU """""""""""""""""""""""""""""" description computes rainfall accumulation fields `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types period : float. Dataset keyword the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600. start_average : float. Dataset keyword when to start the average [s from midnight UTC]. Default 0. use_nan : bool. Dataset keyword If true non valid data will be used nan_value : float. 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. `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types colocgatespath : string. base path to the file containing the coordinates of the co-located gates coloc_radars_name : string. Dataset keyword string identifying the radar names rays_are_indexed : bool. 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_tol : float. Dataset keyword azimuth tolerance between the two radars. Default 0.5 deg ele_tol : float. Dataset keyword elevation tolerance between the two radars. Default 0.5 deg rng_tol : float. Dataset keyword range tolerance between the two radars. Default 50 m coloc_data_dir : string. Dataset keyword name of the directory containing the csv file with colocated data INTERCOMP_FIELDS """""""""""""""""""""""""""""" description intercomparison between two radars `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types INTERCOMP_TIME_AVG """""""""""""""""""""""""""""" description intercomparison between the average reflectivity of two radars `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types colocgatespath : string. base path to the file containing the coordinates of the co-located gates coloc_data_dir : string. Dataset keyword name of the directory containing the csv file with colocated data coloc_radars_name : string. Dataset keyword string identifying the radar names rays_are_indexed : bool. 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_tol : float. Dataset keyword azimuth tolerance between the two radars. Default 0.5 deg ele_tol : float. Dataset keyword elevation tolerance between the two radars. Default 0.5 deg rng_tol : float. Dataset keyword range tolerance between the two radars. Default 50 m clt_max : int. Dataset keyword maximum number of samples that can be clutter contaminated. Default 100 i.e. all phi_excess_max : int. Dataset keyword maximum number of samples that can have excess instantaneous PhiDP. Default 100 i.e. all non_rain_max : int. Dataset keyword maximum number of samples that can be no rain. Default 100 i.e. all phi_avg_max : float. Dataset keyword maximum average PhiDP allowed. Default 600 deg i.e. any ML ----------------------------- ML_DETECTION """""""""""""""""""""""""""""" description Detects the melting layer `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types VPR ----------------------------- VPR """""""""""""""""""""""""""""" description Computes the vertical profile of reflectivity using the Meteo-France operational algorithm `[Source] `_ parameters datatype : string. Dataset keyword The input data type nvalid_min : int Minimum number of rays with data to consider the azimuthal average valid. Default 20. angle_min, angle_max : float Minimum and maximum elevation angles used to compute the ratios of reflectivity. Default 0. and 4. ml_thickness_min, ml_thickness_max, ml_thickness_step : float Minimum, maximum and step of the melting layer thickness of the models to explore [m]. Default 200., 800. and 200. iso0_max : float maximum iso0 altitude of the profile. Default 5000. ml_top_diff_max, ml_top_step : float 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_step : float min, max and step of the decreasing ratio above the melting layer. Default -6., -1.5 and 1.5 dr_default : float default decreasing ratio to use if a proper model could not be found. Default -4.5 dr_alt : float 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_max : float maximum altitude [masl] where to compute the model profile. Default 6000. h_corr_max : float maximum altitude [masl] considered for the VPR correction h_res : float resolution of the model profile (m). Default 1. max_weight : float Maximum weight of the antenna pattern. Default 9. rmin_obs, rmax_obs : float minimum and maximum range (m) of the observations that are compared with the model. Default 5000. and 150000. use_ml : bool If True the retrieved ML will be used to select the range of variability the meltin layer top and thickness vpr_memory_max : float The maximum time range to average reflectivity (min) filter_vpr_memory_max : float The maximum time range where to look for previous VPR retrievals ml_datatype : str Melting layer data type descriptor z_datatype : str descriptor used get the linear reflectivity information vpr_theo_datatype : str descriptor used to get the retrieved theoretical VPR filter_params : bool 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_mem : float Weight given to past VPR when filtering the current VPR spatialized : bool If True the VPR correction is spatialized correct_iso0 : bool 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 `[Source] `_ parameters excessgatespath : str. Config keyword The path to the gates in excess of quantile location excessgates_fname : str. Dataset keyword The name of the gates in excess of quantile file datatype : list of string. Dataset keyword The input data types step : float. 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_grid : Boolean. Dataset keyword Whether the radar has a Boolean grid or not. Default False val_min : Float. Dataset keyword Minimum value to consider that the gate has signal. Default None filter_prec : str. Dataset keyword Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes. rmax_prec : float. Dataset keyword Maximum range to consider when looking for wet gates [m] percent_prec_max : float. Dataset keyword Maxim percentage of wet gates to consider the volume dry MONITORING """""""""""""""""""""""""""""" description computes monitoring statistics `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types step : float. 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_rays : int. 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. `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types regular_grid : Boolean. Dataset keyword Whether the radar has a Boolean grid or not. Default False rmin, rmax : float. Dataset keyword minimum and maximum ranges where the computation takes place. If -1 the whole range is considered. Default is -1 val_min : Float. Dataset keyword Minimum value to consider that the gate has signal. Default None filter_prec : str. Dataset keyword Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes. rmax_prec : float. Dataset keyword Maximum range to consider when looking for wet gates [m] percent_prec_max : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types regular_grid : Boolean. Dataset keyword Whether the radar has a Boolean grid or not. Default False rmin, rmax : float. 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. `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types regular_grid : Boolean. Dataset keyword Whether the radar has a Boolean grid or not. Default False rmin, rmax : float. Dataset keyword minimum and maximum ranges where the computation takes place. If -1 the whole range is considered. Default is -1 val_min : Float. Dataset keyword Minimum reflectivity value to consider that the gate has signal. Default None filter_prec : str. Dataset keyword Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes. rmax_prec : float. Dataset keyword Maximum range to consider when looking for wet gates [m] percent_prec_max : float. Dataset keyword Maxim percentage of wet gates to consider the volume dry lin_trans : Boolean. 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. `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement lat, lon : float latitude and longitude of the point of interest [deg] latlon_tol : float tolerance in latitude and longitude in deg. Default 0.0005 delta_rng, delta_azi : float maximum range distance [m] and azimuth distance [degree] from the central point of the evp containing data to average. Default 5000. and 10. hmax : float The maximum height to plot [m]. Default 10000. hres : float The height resolution [m]. Default 250. avg_type : str The type of averaging to perform. Can be either "mean" or "median" Default "mean" nvalid_min : int Minimum number of valid points to consider the data valid when performing the averaging. Default 1 interp_kind : str 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. `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement angle : int 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_tol : float If the radar object contains an RHI volume, the tolerance in the elevation angle for the conversion into PPI hmax : float The maximum height to plot [m]. Default 10000. hres : float The height resolution [m]. Default 50 avg_type : str The type of averaging to perform. Can be either "mean" or "median" Default "mean" nvalid_min : int Minimum number of valid points to accept average. Default 30. interp_kind : str 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. `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement angle : int 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_tol : float If the radar object contains an RHI volume, the tolerance in the elevation angle for the conversion into PPI. Default 1. lat, lon : float latitude and longitude of the point of interest [deg] latlon_tol : float tolerance in latitude and longitude in deg. Default 0.0005 delta_rng, delta_azi : float maximum range distance [m] and azimuth distance [degree] from the central point of the svp containing data to average. Default 5000. and 10. hmax : float The maximum height to plot [m]. Default 10000. hres : float The height resolution [m]. Default 250. avg_type : str The type of averaging to perform. Can be either "mean" or "median" Default "mean" nvalid_min : int Minimum number of valid points to consider the data valid when performing the averaging. Default 1 interp_kind : str 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. `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement lat, lon : float latitude and longitude of the point of interest [deg] latlon_tol : float tolerance in latitude and longitude in deg. Default 0.0005 hmax : float The maximum height to plot [m]. Default 10000. hres : float The height resolution [m]. Default 50 interp_kind : str 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 `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the time series mode : str coordinate to extract data along. Can be ALONG_AZI, ALONG_ELE or ALONG_RNG fixed_range, fixed_azimuth, fixed_elevation : float 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_tol : float The angle tolerance [deg] and range tolerance [m] around the fixed range or azimuth/elevation value_start, value_stop : float The minimum and maximum value at which the data along a coordinate start and stop SPARSE_GRID ----------------------------- ZDR_COLUMN """""""""""""""""""""""""""""" description Detects ZDR columns `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types SUN_HITS ----------------------------- SUN_HITS """""""""""""""""""""""""""""" description monitoring of the radar using sun hits `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types delev_max : float. Dataset keyword maximum elevation distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5 dazim_max : float. Dataset keyword maximum azimuth distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5 elmin : float. Dataset keyword minimum radar elevation where to look for sun hits [deg]. Default 1. attg : float. Dataset keyword gaseous attenuation. Default None sun_position : string. Datset keyword The function to compute the sun position to use. Can be 'MF' or 'pysolar' sun_hit_method : str. Dataset keyword Method used to estimate the power of the sun hit. Can be HS (Hildebrand and Sekhon 1974) or Ivic (Ivic 2013) rmin : float. Dataset keyword minimum range where to look for a sun hit signal [m]. Used in HS method. Default 50000. hmin : float. 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_min : int. 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_ray : int 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_pwr : float. 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_zdr : float. Dataset keyword maximum standard deviation of the ZDR to consider the data a sun hit [dB]. Default 2. az_width_co : float. Dataset keyword co-polar antenna azimuth width (convoluted with sun width) [deg]. Default None el_width_co : float. Dataset keyword co-polar antenna elevation width (convoluted with sun width) [deg]. Default None az_width_cross : float. Dataset keyword cross-polar antenna azimuth width (convoluted with sun width) [deg]. Default None el_width_cross : float. Dataset keyword cross-polar antenna elevation width (convoluted with sun width) [deg]. Default None ndays : int. Dataset keyword number of days used in sun retrieval. Default 1 coeff_band : float. Dataset keyword multiplicate coefficient to transform pulse width into receiver bandwidth frequency : float. 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 beamwidth : float. 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_width : float. 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_res : float. 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, AntennaGainV : float. 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. `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types delev_max : float. Dataset keyword maximum elevation distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5 dazim_max : float. Dataset keyword maximum azimuth distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5 elmin : float. Dataset keyword minimum radar elevation where to look for sun hits [deg]. Default 1. attg : float. Dataset keyword gaseous attenuation. Default None sun_position : string. Datset keyword The function to compute the sun position to use. Can be 'MF' or 'pysolar' sun_hit_method : str. 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_bins : int. Dataset keyword Number of bins to use for noise estimation noise_threshold : float. Dataset keyword Distance over the noise level in [dBm] min_num_samples : int. Dataset keyword Minimal number of samples above the noise level max_fit_stddev : float. Dataset keyword Maximal allowed standard deviation for a valid sun fit [dBm] do_second_noise_est : string ('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_bins : int. Dataset keyword Number of samples most remote from the sun center az_width_co : float. Dataset keyword co-polar antenna azimuth width (convoluted with sun width) [deg]. Default None el_width_co : float. Dataset keyword co-polar antenna elevation width (convoluted with sun width) [deg]. Default None az_width_cross : float. Dataset keyword cross-polar antenna azimuth width (convoluted with sun width) [deg]. Default None el_width_cross : float. Dataset keyword cross-polar antenna elevation width (convoluted with sun width) [deg]. Default None rmin : float. Dataset keyword minimum range where to look for a sun hit signal [m]. Used in HS method. Default 50000. hmin : float. 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_min : int. 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_ray : int 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_wlen : int 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_pwr : float. 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_zdr : float. Dataset keyword maximum standard deviation of the ZDR to consider the data a sun hit [dB]. Default 2. ndays : int. Dataset keyword number of days used in sun retrieval. Default 1 coeff_band : float. Dataset keyword multiplicate coefficient to transform pulse width into receiver bandwidth frequency : float. 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 beamwidth : float. 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_width : float. 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_res : float. 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, AntennaGainV : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types period : float. Dataset keyword the period to average [s]. Default 3600. start_average : float. Dataset keyword when to start the average [s from midnight UTC]. Default 0. phidpmax: float. Dataset keyword maximum PhiDP beamwidth : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types period : float. Dataset keyword the period to average [s]. Default 3600. start_average : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types period : float. Dataset keyword the period to average [s]. Default 3600. start_average : float. Dataset keyword when to start the average [s from midnight UTC]. Default 0. TIME_STATS """""""""""""""""""""""""""""" description computes the temporal statistics of a field `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types period : float. Dataset keyword the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600. start_average : float. 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_nan : bool. Dataset keyword If true non valid data will be used nan_value : float. 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types period : float. Dataset keyword the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600. start_average : float. 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_nan : bool. Dataset keyword If true non valid data will be used nan_value : float. Dataset keyword The value of the non valid data. Default 0 RAIN_ACCU """""""""""""""""""""""""""""" description Computes rainfall accumulation fields `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types period : float. Dataset keyword the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600. start_average : float. Dataset keyword when to start the average [s from midnight UTC]. Default 0. use_nan : bool. Dataset keyword If true non valid data will be used nan_value : float. Dataset keyword The value of the non valid data. Default 0 TIMESERIES ----------------------------- GRID_POINT_MEASUREMENT """""""""""""""""""""""""""""" description Obtains the grid data at a point location. `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement latlon : boolean. Dataset keyword if True position is obtained from latitude, longitude information, otherwise position is obtained from grid index (iz, iy, ix). lon : float. Dataset keyword the longitude [deg]. Use when latlon is True. lat : float. Dataset keyword the latitude [deg]. Use when latlon is True. alt : float. Dataset keyword altitude [m MSL]. Use when latlon is True. iz, iy, ix : int. Dataset keyword The grid indices. Use when latlon is False latlonTol : float. Dataset keyword latitude-longitude tolerance to determine which grid point to use [deg] altTol : float. Dataset keyword Altitude tolerance to determine which grid point to use [deg] GRID_MULTIPLE_POINTS """""""""""""""""""""""""""""" description Obtains the grid data at a point location. `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement coord_fname : string File name containing the points coordinates latlonTol : float. 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 `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement truealt : boolean. 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_fname : string File name containing the points coordinates alt_points : float. Dataset keyword altitude [m MSL]. Use when latlon is True. ele_points : float. Dataset keyword radar elevation [deg]. Use when latlon is False or when latlon is True and truealt is False AziTol : float. Dataset keyword azimuthal tolerance to determine which radar azimuth to use [deg] EleTol : float. Dataset keyword elevation tolerance to determine which radar elevation to use [deg] RngTol : float. Dataset keyword range tolerance to determine which radar bin to use [m] POINT_MEASUREMENT """""""""""""""""""""""""""""" description Obtains the radar data at a point location. `[Source] `_ parameters datatype : string. Dataset keyword The data type where we want to extract the point measurement single_point : boolean. 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 latlon : boolean. Dataset keyword if True position is obtained from latitude, longitude information, otherwise position is obtained from antenna coordinates (range, azimuth, elevation). truealt : boolean. 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. lon : float. Dataset keyword the longitude [deg]. Use when latlon is True. lat : float. Dataset keyword the latitude [deg]. Use when latlon is True. alt : float. Dataset keyword altitude [m MSL]. Use when latlon is True and truealt is True ele : float. Dataset keyword radar elevation [deg]. Use when latlon is False or when latlon is True and truealt is False azi : float. Dataset keyword radar azimuth [deg]. Use when latlon is False rng : float. Dataset keyword range from radar [m]. Use when latlon is False AziTol : float. Dataset keyword azimuthal tolerance to determine which radar azimuth to use [deg] EleTol : float. Dataset keyword elevation tolerance to determine which radar elevation to use [deg] RngTol : float. Dataset keyword range tolerance to determine which radar bin to use [m] fill_value : float 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. `[Source] `_ parameters TRAJ_ATPLANE """""""""""""""""""""""""""""" description Return time series according to trajectory `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types data_is_log : dict. Dataset keyword Dictionary specifying for each field if it is in log (True) or linear units (False). Default False ang_tol : float. Dataset keyword Factor that multiplies the angle resolution. Used when determining the neighbouring rays. Default 1.2 az_tol, el_tol : float 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. timeformat : str or None time format of the time series output file TRAJ_LIGHTNING """""""""""""""""""""""""""""" description Return time series according to lightning trajectory `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types data_is_log : dict. Dataset keyword Dictionary specifying for each field if it is in log (True) or linear units (False). Default False ang_tol : float. Dataset keyword Factor that multiplies the angle resolution. Used when determining the neighbouring rays. Default 1.2 az_tol, el_tol : float 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 `[Source] `_ parameters datatype : list of string. Dataset keyword The input data types