@article{fdi:010084617,
  title = {{A}n inverse method for drop size distribution retrieval from polarimetric radar at attenuating frequency},
  author = {{A}lcoba, {M}atias and {A}ndrieu, {H}. and {G}osset, {M}arielle},
  editor = {},
  language = {{ENG}},
  abstract = {{A} method that formulates the retrieval of drop size distribution ({DSD}) parameters from polarimetric radar variables at attenuating frequency as the solution of an inverse problem is presented. {T}he {DSD} in each radar bin is represented by a normalized {G}amma distribution defined by three parameters ({D}-m,{N}-0*,mu). {T}he direct problem that describes polarimetric radar observables-scattering and propagation terms-and their dependency on {DSD} parameters is analyzed based on {T}-matrix scattering simulations. {T}he inverse algorithm and its application to the {DSD} retrieval are then presented. {T}he inverse method is applied to an {A}frican {M}onsoon {M}ultidisciplinary {A}nalysis ({AMMA}) field campaign that deployed an {X}-band dual-polarization {D}oppler radar and optical disdrometers in {B}enin, {W}est {A}frica, in 2006 and 2007. {T}he dataset is composed of {X}-band polarimetric radar {PPI}s and disdrometer data for 15 organized convective systems observed in 2006. {A} priori information on {DSD} parameters (benchmark method) is derived from the polarimetric radar observables by applying power law relationships. {T}he proposed retrieval method of {DSD} parameters leads to the following results as compared to the benchmark: (i) we found a better spatial consistency of the retrieved parameters, (ii) the reconstructed polarimetric radar observables are closer to the observations, (iii) {T}he validation with disdrometer data confirms an improved estimation of the {DSD} parameters.},
  keywords = {radar polarimetry ; drop size distribution retrieval ; inverse problem ; attenuation correction ; {X}-band radar ; tropical rainfall ; convective ; rainfall},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {14},
  numero = {5},
  pages = {1116 [24 ]},
  year = {2022},
  DOI = {10.3390/rs14051116},
  URL = {https://www.documentation.ird.fr/hor/fdi:010084617},
}