Evaluation and application of hydrometeor classification algorithm outputs inferred from multi‐frequency dual‐polarimetric radar observations collected during HyMeX. (14th July 2015)
- Record Type:
- Journal Article
- Title:
- Evaluation and application of hydrometeor classification algorithm outputs inferred from multi‐frequency dual‐polarimetric radar observations collected during HyMeX. (14th July 2015)
- Main Title:
- Evaluation and application of hydrometeor classification algorithm outputs inferred from multi‐frequency dual‐polarimetric radar observations collected during HyMeX
- Authors:
- Ribaud, J.‐F.
Bousquet, O.
Coquillat, S.
Al‐Sakka, H.
Lambert, D.
Ducrocq, V.
Fontaine, E. - Abstract:
- Abstract : A fuzzy logic hydrometeor classification algorithm (HCA), allowing discrimination between six microphysical species regardless of the radar wavelength is presented and evaluated. The proposed method is based upon combination sets of dual‐polarimetric observables (reflectivity at horizontal polarization Z H, differential reflectivity Z DR, specific differential phase K DP, correlation coefficient ρ HV ) along with temperature data inferred from a numerical weather prediction model output. The performance of the HCA is evaluated using 20 h of multi‐frequency dual‐polarimetric radar data collected during the first Special Observation Period (SOP1) of the Hydrological Cycle in the Mediterranean Experiment (HyMeX). A new method based upon intercomparisons of retrieved hydrometeor data deduced from pairs of neighbouring radars (S‐band vs. S‐band and S‐band vs. C‐band) over a common sampling area is proposed to evaluate the consistency of hydrometor classification outputs. S‐/C‐band radar comparisons generally show better consistency than S‐/S‐band radar comparisons due to issues with the identification of the 0°C isotherm on one of the two S‐band radars. Imperfect attenuation correction at C‐band may also lead into differences in hydrometeor fields retrieved from the C‐ and S‐band radars in convective situations, but retrieved hydrometeor data are globally very consistent from one radar to another. Comparisons against in situ airborne data also confirm the overall goodAbstract : A fuzzy logic hydrometeor classification algorithm (HCA), allowing discrimination between six microphysical species regardless of the radar wavelength is presented and evaluated. The proposed method is based upon combination sets of dual‐polarimetric observables (reflectivity at horizontal polarization Z H, differential reflectivity Z DR, specific differential phase K DP, correlation coefficient ρ HV ) along with temperature data inferred from a numerical weather prediction model output. The performance of the HCA is evaluated using 20 h of multi‐frequency dual‐polarimetric radar data collected during the first Special Observation Period (SOP1) of the Hydrological Cycle in the Mediterranean Experiment (HyMeX). A new method based upon intercomparisons of retrieved hydrometeor data deduced from pairs of neighbouring radars (S‐band vs. S‐band and S‐band vs. C‐band) over a common sampling area is proposed to evaluate the consistency of hydrometor classification outputs. S‐/C‐band radar comparisons generally show better consistency than S‐/S‐band radar comparisons due to issues with the identification of the 0°C isotherm on one of the two S‐band radars. Imperfect attenuation correction at C‐band may also lead into differences in hydrometeor fields retrieved from the C‐ and S‐band radars in convective situations, but retrieved hydrometeor data are globally very consistent from one radar to another. Comparisons against in situ airborne data also confirm the overall good performance of the HCA. In a second experiment, an original method allowing the production of multi‐radar three‐dimensional (3D) hydrometeor fields from single‐radar 2D hydrometeor data is tested on a bow‐echo convective system observed with C‐ and S‐band radars. The resulting 3D hydrometeor fields provide a detailed view of the bow‐echo microphysical structure and confirm the good performance of both the HCA and interpolation technique. … (more)
- Is Part Of:
- Quarterly journal of the Royal Meteorological Society. Volume 142(2016)Supplement 1
- Journal:
- Quarterly journal of the Royal Meteorological Society
- Issue:
- Volume 142(2016)Supplement 1
- Issue Display:
- Volume 142, Issue 1 (2016)
- Year:
- 2016
- Volume:
- 142
- Issue:
- 1
- Issue Sort Value:
- 2016-0142-0001-0000
- Page Start:
- 95
- Page End:
- 107
- Publication Date:
- 2015-07-14
- Subjects:
- dual‐polarization radar -- hydrometeor identification -- convective systems
Meteorology -- Periodicals
551.5 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1477-870X/issues ↗
http://onlinelibrary.wiley.com/ ↗
http://www.ingentaselect.com/rpsv/cw/rms/00359009/contp1.htm ↗ - DOI:
- 10.1002/qj.2589 ↗
- Languages:
- English
- ISSNs:
- 0035-9009
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7186.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 300.xml