Preprints
https://doi.org/10.5194/amt-2022-92
https://doi.org/10.5194/amt-2022-92
 
23 Mar 2022
23 Mar 2022
Status: a revised version of this preprint is currently under review for the journal AMT.

Sensitivity analysis of DSD retrievals from polarimetric radar in stratiform rain based on μ-Λ relationship

Christos Gatidis, Marc Schleiss, and Christine Unal Christos Gatidis et al.
  • Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, The Netherlands

Abstract. Raindrop size distributions (DSD) play a crucial role in quantitative rainfall estimation using weather radar. Thanks to dual-polarization capabilities, crucial information about the DSD in a given volume of air can be retrieved. One popular retrieval method assumes that the DSD can be modeled by a constrained gamma distribution in which the shape (μ) and rate (Λ) parameters are linked together by a deterministic relationship. In the literature, μ-Λ relationships are often taken for granted and applied without much critical discussion. In this study, we take another look at this important issue by conducting a detailed analysis of μ-Λ relations in stratiform rain and quantifying the accuracy of the associated DSD retrievals. Crucial aspects of our research include the sensitivity of μ-Λ relations to the temporal aggregation scale, drop concentration, inter-event variability and adequacy of the gamma distribution model. Our results show that μ-Λ relationships in stratiform rain are surprisingly robust to the choice of the sampling resolution, sample size and adequacy of the gamma model. Overall, the retrieved DSDs are in a rather decent agreement with ground observations (correlation coefficient of 0.57 and 0.74 for μ and Dm). The main sources of errors and uncertainty during the retrievals are calibration offsets in reflectivity (Zhh) and differential reflectivity (Zdr). Measurement noise and differences in scale between radar and disdrometers also play a minor role. The most problematic parameter remains the raindrop concentration (NT), which can be off by several orders of magnitude. By removing problematic Zhh/Zdr pairs, the correlation coefficient for the retrieved NT values increases from 0.12 to 0.24, however even after the careful data filtering the accuracy of the retrieved values remains low.

Christos Gatidis et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-92', Anonymous Referee #1, 07 Apr 2022
    • AC1: 'Reply on RC1', Christos Gatidis, 15 Jun 2022
  • RC2: 'Comment on amt-2022-92', Anonymous Referee #2, 15 May 2022
    • AC2: 'Reply on RC2', Christos Gatidis, 15 Jun 2022
  • RC3: 'Comment on amt-2022-92', Anonymous Referee #3, 18 May 2022
    • AC3: 'Reply on RC3', Christos Gatidis, 15 Jun 2022

Christos Gatidis et al.

Christos Gatidis et al.

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Short summary
Knowledge of the raindrop size distribution (DSD) is crucial for understanding rainfall microphysics and quantifying uncertainty in quantitative precipitation estimates. In this study a general overview of the DSD retrieval approach from a polarimetric radar is discussed, highlighting sensitivity to potential sources of errors, either directly linked to the radar measurements or indirectly through the critical modeling assumptions behind the method such as the shape (μ) – size (Λ) relationship.