BALTRAD

1. Algorithm name

Quality-based maximum of reflectivity (MAX) product generation – Product2D: MAX

2. Basic description

a) Physical basis of the algorithm

The algorithm generates maximum of reflectivity (MAX) 2-D product from radar reflectivity volume with quality information using product2D_PPI algorithm.

b) Amount of validation performed so far

Not performed yet.

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

IMGW, Department of Ground Based Remote Sensing.

3. ODIM metadata requirements for I/O

Input data: VOL

• General “what”: source(NOD).
• For particular SCANs:
  • Dataset-specific “where” for data and QI: nbins, nrays.
  • Data-specific “what” for data: gain, offset, nodata, undetect.
  • Data-specific “what” for QI: gain, offset, nodata, undetect.

Output data: Cartesian data

• Top-level “where”: lon, lat, xsize, ysize, xscale, yscale.
• Dataset-specific “what”: product.
• Data-specific “what” for data: gain, offset, nodata, undetect.
• Data-specific “what” for QI: gain, offset, nodata, undetect.

4. Input data

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

object=PVOL:

• quantity=DBZH, otherwise TH,
• quantity=QIND (generated e.g. by QI_TOTAL algorithm).

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

Defined projection and domain of Cartesian output.

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

The algorithm generates maximum of reflectivity (MAX) 2-D products in Cartesian coordinates from radar reflectivity volume and based on the data quality information.

Algorithm parameters

Set of the algorithm parameters:

Description	Denotation	Unit	Default value
Lower height limit for MAX product generation	MAX_hMin	km	1
Upper height limit for MAX product generation	MAX_hMax	km	20

Algorithm description

Maximum of reflectivity (MAX) product represents Cartesian image of highest measured value of radar reflectivity Z’’ (in dBZ) for each vertical column. The maximum is detected in a preset range of height (between ‘‘h’‘_min and ‘‘h_max) and generally is a search for the highest value among reflectivities in pixels in the column for all PPIs (Fig. 1).

Fig. 1. Scheme of generation of maximum of radar reflectivity product (MAX).

Data quality characterization

Quality of the MAX depends on the two factors:

• quality of reflectivity data taken as MAX’’, ‘‘QI,,source,,,
• how large fraction of investigated heights (between h’’,,min,, and ‘‘h’’,,max,,) was scanned, ‘‘QI,,scope,,, and the final quality index QI is taken as a product of the both factors:

The value of the first component QI,,source,,’’ is taken as the quality of the measurement defining ‘‘MAX’’. If ‘‘MAX’’ “nodata”, and if ‘‘MAX 1.

Fig. 2. Quality characterization for maximum of reflectivity product in terms of availability.

The second component QI_scope’’ is determined based on heights of the highest and lowest scans for considered Cartesian pixel (‘‘h_highest’’ and ‘‘h_lowest’’ respectively) in relation to ‘‘h’‘_min and ‘‘h_max (Fig. 2):

• if h_highest’’ < ‘‘h_min then

  QI_scope “nodata”.

• if h_highest’’ ≥ ‘‘h’‘_min and ‘‘h_lowest’’ <= ‘‘h’‘_max then ‘‘QI_scope’’ depends on what part of height range between ‘‘h’‘_min and ‘‘h_max was scanned:

• if h_lowest’’ > ‘‘h_max then

  QI_scope “nodata”.

6. Output

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

Input quantity as IMAGE object (in Cartesian coordinates) with:

• “how”: task - “pl.imgw.product2d.max”,
• “how”: task_args
  • parameters inherited from PPI algorithm (interpolation method and selected quality field name),
  • parameters of MAX algorithm,

b) Quality index (QI) field

Quality index field QIND as IMAGE object with:

• “how”: task - “pl.imgw.product2d.max”,
• “how”: task_args - parameters inherited from PPI algorithm (interpolation method and selected quality field name).

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

TBD