Last modified 6 years ago Last modified on 03/04/13 14:37:37

1. Algorithm name

Removal of measurement noise and quality characterization (as a part of RADVOL-QC package) – RADVOL-QC: SPECK

2. Basic description

a) Physical basis of the algorithm

Investigation of echo patterns to detect non-meteorological echoes such as specks and reverse specks.

b) Amount of validation performed so far

Works operationally in IMGW since 2011 to correct data before using for Meteo Flight system (for air traffic control).

c) References (names and contact information of all developers during the evolutionary history, scientific papers)

  • Operational work: IMGW, Department of Ground Based Remote Sensing.
  • Scientific paper: Ośródka, K., Szturc, J., and Jurczyk, A., 2012. Chain of data quality algorithms for 3-D single-polarization radar reflectivity (RADVOL-QC system). Meteorol. Appl. (Early View).

3. ODIM metadata requirements for I/O

  • Dataset-specific “what”: gain, offset, nodata, undetect.
  • Dataset-specific “where”: elangle, nbins, nrays, rscale.

4. Input data

a) What kind of radar data (including the list of previous algorithms and quality flags applied)

object=PVOL or SCAN; quantity=DBZH, otherwise TH.

b) Other data (optional and mandatory, applying “universally” agreed formats, geometry)


5. Logical steps, using any of: text, flow charts, graphics, equations (or references to equations), conditional branches in “all possible cases”.

Generally, the specks are isolated radar gates with or without echo.

Set of the algorithm parameters

Description Denotation Default value
QISPECK value for speck SPECK_QI 0.9
QISPECK value for uncorrected speck SPECK_QIUn 0.5
A. Reverse speck vicinity SPECK_AGrid 1
A. Maximum of non-rainy gates SPECK_ANum 2
A. Number of reverse speck removal subalgorithm cycles SPECK_AStep 1
B. Speck vicinity SPECK_BGrid 1
B. Maximum of rainy gates SPECK_BNum 2
B. Number of speck removal subalgorithm cycles SPECK_BStep 2

At first the XML file is checked whether there exists group for a considered radar (based on the radar name read from "what"/source(NOD)), which contains the algorithm parameters. If "yes", then parameters are read from that XML group, but if it is impossible for a particular parameter, then default value from source code is taken. If the group does not exist, parameters are read from <default> group in XML file in analogous way.

If the algorithm is run by means of BALTRAD toolbox then all the algorirthm parameters for each specific radar should be placed in relevant XML file by the BALTRAD system admin. Default parameters are placed in the file by admin as well. Moreover, the algorithm default parameters are also included in software.

Reverse specks removal

So called reverse specks are isolated gates without radar echo (Z = –32 dBZ) surrounded by precipitation field. The introduced subalgorithm is employed to each elevation scan separately. A vicinity of a given gate (α, l) ±SPECK_AGrid gates is considered. Number of non-echo gates srspeck(α, l) in the grid is calculated from:

$  s_{rspeck}(\alpha ,l) = \sum_{m=\alpha -\text{SPECK}\_\text{AGrid}}^{\alpha +\text{SPECK}\_\text{AGrid}}  \sum_{n=l-\text{SPECK}\_\text{AGrid}}^{l+\text{SPECK}\_\text{AGrid}}  {f_{rspeck}(m,n)}  $


$ f_{rspeck}(m,n) = \begin{cases}
1                                 & \textrm{for\ } Z(m,n) = -32 \textrm{dBZ\ }  \\
0                                 & \textrm{for\ } Z(m,n) > -32 \textrm{dBZ\ }  
\end{cases} $

where m, n are the polar coordinates of gates inside the considered vicinity; Z(m, n) is the radar reflectivity in the gate (m, n) (in dBZ).

Parameter of the algorithm is threshold SPECK_ANum for srspeck(α, l) value. If the threshold for (α, l) gate is not exceeded then the gate is classified as a reverse speck and its reflectivity is set to average from all precipitation gates inside the grid. This subalgorithm is launched SPECK_AStep times.

Specks removal

As opposed to reverse specks, the ordinary ones are gates in which isolated echoes are observed that can be considered as measurement noise. Subalgorithm of the speck removal is analogous to the one used for reverse specks. A vicinity of a given gate (α, l) ±SPECK_BGrid gates is considered. Number of echo gates sspeck(α, l) in the grid can be calculated from (Jurczyk et al., 2008):

$  s_{speck}(\alpha ,l) = \sum_{m=\alpha -\text{SPECK}\_\text{BGrid}}^{\alpha +\text{SPECK}\_\text{BGrid}}  \sum_{n=l-\text{SPECK}\_\text{BGrid}}^{l+\text{SPECK}\_\text{BGrid}}  {f_{speck}(m,n)}  $


$ f_{speck}(m,n) = \begin{cases}
1                                 & \textrm{for\ } Z(m,n) > -32 \textrm{dBZ\ }  \\
0                                 & \textrm{for\ } Z(m,n) = -32 \textrm{dBZ\ }  
\end{cases} $

where denotation is the same as for Equation above.

If threshold SPECK_BNum for number of surrounding precipitation gates sspeck(α, l) is not exceeded then (α, l) gate is classified as speck echo and the echo is removed, i.e. reflectivity Z = –32 dBZ is set for the gate. This subalgorithm is launched SPECK_BStep times to clean the data more thoroughly.

Quality index

Related quality index QISPECK depends on presence of removed speck or reverse speck in the given gate:

$ QI_{SPECK} = \begin{cases}
\text{SPECK}\_\text{QI}         & \textrm{for gate with speck\ } \\
1                               & \textrm{for gate without speck\ } 
\end{cases} $

6. Output

a) Data type using ODIM notation where possible, e.g. DBZH

Corrected DBZH, with "pl.imgw.radvolqc.speck" added to data-specific "how"/task, and the algorithm parameters added to "how"/task_args.

b) Quality index (QI) field

Quality index (QI = 0 for bad data, QI = 1 for excellent data) with "pl.imgw.radvolqc.speck" in quality-specific "how"/task, and the algorithm parameters in "how"/task_args.

7. Outline of a test concept exemplifying the algorithm, as a suggestion for checking that an implementation has been successful.