Preprints
https://doi.org/10.5194/npg-2022-9
https://doi.org/10.5194/npg-2022-9
08 Mar 2022
 | 08 Mar 2022
Status: this preprint was under review for the journal NPG but the revision was not accepted.

Fortnight conditioning of historical data to improve short-term precipitation predictions

Yoshito Hirata and Yoshinori Yamada

Abstract. The effects of changes in weather variables, including precipitation dependence on the days-of-the-week, have known applications in weather predictions. However, the use of these effects to improve weather forecasting has not been determined. Here we investigate if conditioning past data somehow by considering the days-of-the-week helps us to obtain the better short-term time series prediction for precipitation. Especially, we demonstrate that short-term time series prediction of precipitation up to 2 h ahead can be improved using the data points of the days whose differences from the current day are multiples of 14. For short-term predictions, we employ infinite-dimensional delay coordinates (Hirata et al., Sci. Rep. 5, 15736, 2015) to reconstruct the underlying dynamics. Although the results demonstrate that the two-week periodicity seems to exist in the weather at Tokyo, and thus some anthropogenic activities could influence weather, the mechanism of the influence remains unclear.

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Yoshito Hirata and Yoshinori Yamada

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on npg-2022-9', Dmitri Kondrashov, 24 Mar 2022
    • AC1: 'Reply on CC1', Yoshito Hirata, 08 Apr 2022
  • RC1: 'Comment on npg-2022-9', Anonymous Referee #1, 28 Mar 2022
    • AC2: 'Reply on RC1', Yoshito Hirata, 08 Apr 2022
  • RC2: 'Comment on npg-2022-9', Anonymous Referee #2, 23 May 2022
    • AC3: 'Reply on RC2', Yoshito Hirata, 30 May 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on npg-2022-9', Dmitri Kondrashov, 24 Mar 2022
    • AC1: 'Reply on CC1', Yoshito Hirata, 08 Apr 2022
  • RC1: 'Comment on npg-2022-9', Anonymous Referee #1, 28 Mar 2022
    • AC2: 'Reply on RC1', Yoshito Hirata, 08 Apr 2022
  • RC2: 'Comment on npg-2022-9', Anonymous Referee #2, 23 May 2022
    • AC3: 'Reply on RC2', Yoshito Hirata, 30 May 2022
Yoshito Hirata and Yoshinori Yamada
Yoshito Hirata and Yoshinori Yamada

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Short summary
We show that there exists some complicated days-of-week effects in precipitation at Tokyo. By using the effects, we could improve short-term precipitation forecasts up to 2 hours ahead.