Preprints
https://doi.org/10.5194/amt-2020-468
https://doi.org/10.5194/amt-2020-468

  04 Jan 2021

04 Jan 2021

Review status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

W-band Radar Observations for Fog Forecast Improvement: an Analysis of Model and Forward Operator Errors

Alistair Bell1, Pauline Martinet1, Olivier Caumont1, Benoît Vié1, Julien Delanoë2, Jean-Charles Dupont3, and Mary Borderies1 Alistair Bell et al.
  • 1CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
  • 2Laboratoire Atmosphères, Milieux, Observations Spatiales/UVSQ/CNRS/UPMC, Guyancourt, France
  • 3Institut Pierre Simon Laplace (IPSL), École Polytechnique, UVSQ, Université Paris-Saclay, 91128 Palaiseau Cedex, France

Abstract. The development of ground based cloud radars offers a new capability to continuously monitor the fog structure. Retrievals of fog microphysics is key for future process studies, data assimilation or model evaluation, and can be performed using a variational method. Both the one-dimensional variational retrieval method (1D-Var) or direct 3D/4D-Var data assimilation techniques rely on the combination of cloud radar measurements and a background profile weighted by their corresponding uncertainties to obtain the optimal solution for the atmospheric state. In order to prepare for the use of ground-based cloud radar measurements for future applications based on variational approaches, the different sources of uncertainty due to instrumental, background, and the forward operator errors need to be properly treated and accounted for. This paper aims at preparing 1D-Var retrievals by analysing the errors associated with a background profile and a forward operator during fog conditions. For this, the background was provided by a high-resolution numerical weather prediction model and the forward operator by a radar simulator. Firstly, an instrumental dataset was taken from the SIRTA observatory near Paris, France for winter 2018–19 during which 31 fog events were observed. Statistics were calculated comparing cloud radar observations to those simulated. It was found that the accuracy of simulations could be drastically improved by correcting for significant spatio-temporal background errors. This was achieved by implementing a most resembling profile method in which an optimal model background profile is selected from a domain and time window around the observation location and time. After selecting the best background profile a good agreement was found between observations and simulations. Moreover, observation minus simulation errors were found to satisfy the conditions needed for future 1D-var retrievals (un-biased and normally distributed).

Alistair Bell et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2020-468', Alain Protat, 01 Feb 2021
    • AC1: 'Reply on RC1', Alistair Bell, 29 Mar 2021
  • RC2: 'Comment on amt-2020-468', Anonymous Referee #2, 06 Feb 2021
    • AC2: 'Reply on RC2', Alistair Bell, 29 Mar 2021
  • RC3: 'Comment on amt-2020-468', Anonymous Referee #3, 18 Feb 2021
    • AC3: 'Reply on RC3', Alistair Bell, 29 Mar 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2020-468', Alain Protat, 01 Feb 2021
    • AC1: 'Reply on RC1', Alistair Bell, 29 Mar 2021
  • RC2: 'Comment on amt-2020-468', Anonymous Referee #2, 06 Feb 2021
    • AC2: 'Reply on RC2', Alistair Bell, 29 Mar 2021
  • RC3: 'Comment on amt-2020-468', Anonymous Referee #3, 18 Feb 2021
    • AC3: 'Reply on RC3', Alistair Bell, 29 Mar 2021

Alistair Bell et al.

Alistair Bell et al.

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