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Estimation of rain kinetic energy from radar reflectivity and/or rain rate based on a scaling formulation of the raindrop size distribution
Author(s) -
Yu Nan,
Boudevillain Brice,
Delrieu Guy,
Uijlenhoet Remko
Publication year - 2012
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2011wr011437
Subject(s) - disdrometer , radar , kinetic energy , moment (physics) , dimensionless quantity , rain gauge , environmental science , scaling , mathematics , meteorology , statistics , physics , precipitation , geometry , computer science , mechanics , telecommunications , classical mechanics , quantum mechanics
This study offers an approach to estimate the rainfall kinetic energy (KE) by rain intensity ( R ) and radar reflectivity factor ( Z ) separately or jointly on the basis of a one‐ or two‐moment scaled raindrop size distribution (DSD) formulation, which contains (1) R and/or Z observations and (2) the dimensionless probability density function (pdf) of a scaled raindrop diameter. The key point is to explain all variability of the DSD by the evolution of the explaining moments ( R and Z ); hence the pdf is considered as constant. A robust method is proposed to estimate the climatological values of the parameters with a 28 month DSD data set collected in the Cévennes‐Vivarais region of France. Three relationships (KE‐ R , KE‐ Z , and KE‐ RZ ), which link the observations ( R and/or Z ) to rainfall kinetic energy (KE), are established. As expected, the assessment using the disdrometer data indicates that (1) because of the proximity of the moment orders, the KE‐ Z relationship exhibits less variability than the KE‐ R relationship and (2) the combination of R and Z yields a significant improvement of the estimation of KE compared to the single‐moment formulations. Subsequently, a first attempt to spatialize the kinetic energy using radar and rain gauge measurements is presented for a convective event, showing a promising potential for erosion process studies. Different from the application with the disdrometer data, the performance of the KE‐ Z relationship degrades compared to the KE‐ R relationship as a result of a bias and/or the sampling characteristics of the radar data.