Preprints
https://doi.org/10.5194/egusphere-2022-391
https://doi.org/10.5194/egusphere-2022-391
 
13 Jun 2022
13 Jun 2022

A Storm-centered Multivariate Modeling of Extreme Precipitation Frequency Based on Atmospheric Water Balance

Yuan Liu and Daniel Benjamin Wright Yuan Liu and Daniel Benjamin Wright
  • Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, 53706, USA

Abstract. Conventional rainfall frequency analysis faces several limitations. These include difficulty incorporating relevant atmospheric variables beyond precipitation and limited ability to depict the frequency of rainfall over large areas that is relevant for flooding. This study proposes a storm-based model of extreme precipitation frequency based on the atmospheric water balance equation. We developed a storm tracking and regional characterization (STARCH) method to identify precipitation systems in space and time from hourly ERA5 precipitation fields over the contiguous United States from 1951 to 2020. Extreme “storm catalogs” were created by selecting annual maximum storms with specific areas and durations over a chosen region. The annual maximum storm precipitation was then modeled via multivariate distributions of atmospheric water balance components using vine copula models. We applied this approach to estimate precipitation average recurrence intervals for storm areas from 5,000 to 100,000 km2 and durations from 2 to 72 hours in the Mississippi Basin and its five major subbasins. The estimated precipitation distributions show a good fit to the reference data from the original storm catalogs and are close to the estimates from conventional univariate GEV distributions. Our approach explicitly represents the contributions of water balance components in extreme precipitation. Of these, water vapor flux convergence is the main contributor, while precipitable water and a mass residual term can also be important, particularly for short durations and small storm footprints. We also found that ERA5 shows relatively good water balance closure for extreme storms, with a mass residual on average 10 % of precipitation. The approach can incorporate nonstationarities in water balance components and their dependence structures and can benefit from further advancements in reanalysis products and storm tracking techniques.

Journal article(s) based on this preprint

20 Oct 2022
A storm-centered multivariate modeling of extreme precipitation frequency based on atmospheric water balance
Yuan Liu and Daniel B. Wright
Hydrol. Earth Syst. Sci., 26, 5241–5267, https://doi.org/10.5194/hess-26-5241-2022,https://doi.org/10.5194/hess-26-5241-2022, 2022
Short summary

Yuan Liu and Daniel Benjamin Wright

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-391', Geoff Pegram, 04 Jul 2022
    • AC1: 'Reply on RC1', Yuan Liu, 17 Aug 2022
  • RC2: 'Comment on egusphere-2022-391', Anonymous Referee #2, 19 Jul 2022
    • AC2: 'Reply on RC2', Yuan Liu, 17 Aug 2022

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-391', Geoff Pegram, 04 Jul 2022
    • AC1: 'Reply on RC1', Yuan Liu, 17 Aug 2022
  • RC2: 'Comment on egusphere-2022-391', Anonymous Referee #2, 19 Jul 2022
    • AC2: 'Reply on RC2', Yuan Liu, 17 Aug 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (28 Aug 2022) by Efrat Morin
AR by Yuan Liu on behalf of the Authors (01 Sep 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (03 Sep 2022) by Efrat Morin
RR by Anonymous Referee #2 (15 Sep 2022)
ED: Publish as is (18 Sep 2022) by Efrat Morin

Journal article(s) based on this preprint

20 Oct 2022
A storm-centered multivariate modeling of extreme precipitation frequency based on atmospheric water balance
Yuan Liu and Daniel B. Wright
Hydrol. Earth Syst. Sci., 26, 5241–5267, https://doi.org/10.5194/hess-26-5241-2022,https://doi.org/10.5194/hess-26-5241-2022, 2022
Short summary

Yuan Liu and Daniel Benjamin Wright

Yuan Liu and Daniel Benjamin Wright

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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Short summary
We present a new approach to estimate extreme rainfall probability and severity using the atmospheric water balance, where precipitation is the sum of water vapor components moving in and out of a storm. We apply our method to the Mississippi Basin and its five major subbasins. Our approach achieves a good fit to reference precipitation, indicating that the rainfall probability estimation can benefit from additional information from physical processes that control rainfall.