Preprints
https://doi.org/10.5194/nhess-2021-373
https://doi.org/10.5194/nhess-2021-373
10 Dec 2021
 | 10 Dec 2021
Status: this preprint was under review for the journal NHESS. A revision for further review has not been submitted.

How well are hazards associated with derechos reproduced in regional climate simulations?

Tristan J. Shepherd, Frederick L. Letson, Rebecca J. Barthelmie, and Sara C. Pryor

Abstract. An 11-member ensemble of convection-permitting regional simulations of the fast-moving and destructive derecho of June 29 – 30, 2012 that impacted the northeastern urban corridor of the US is presented. This event generated 1100 reports of damaging winds, significant wind gusts over an extensive area of up to 500,000 km2, caused several fatalities and resulted in widespread loss of electrical power. Extreme events such as this are increasingly being used within pseudo-global warming experiments that seek to examine the sensitivity of historical, societally-important events to global climate non-stationarity and how they may evolve as a result of changing thermodynamic and dynamic context. As such it is important to examine the fidelity with which such events are described in hindcast experiments. The regional simulations presented herein are performed using the Weather Research and Forecasting (WRF) model. The resulting ensemble is used to explore simulation fidelity relative to observations for wind gust magnitudes, spatial scales of convection (as manifest in high composite reflectivity), and both rainfall and hail production as a function of model configuration (microphysics parameterization, lateral boundary conditions (LBC), start date, and use of nudging). We also examine the degree to which each ensemble member differs with respect to key mesoscale drivers of convective systems (e.g. convective available potential energy and vertical wind shear) and critical manifestations of deep convection; e.g. vertical velocities, cold pool generation, and how those properties relate to correct characterization of the associated atmospheric hazards (wind gusts and hail). Here, we show that the use of a double-moment, 7-class scheme with number concentrations for all species (including hail and graupel) results in the greatest fidelity of model simulated wind gusts and convective structure against the observations of this event. We further show very high sensitivity to the LBC employed and specifically that simulation fidelity is higher for simulations nested within ERA-Interim than ERA5.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Tristan J. Shepherd, Frederick L. Letson, Rebecca J. Barthelmie, and Sara C. Pryor

Status: closed (peer review stopped)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-373', Anonymous Referee #1, 23 Jan 2022
  • RC2: 'Comment on nhess-2021-373', Anonymous Referee #2, 19 Apr 2022

Status: closed (peer review stopped)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-373', Anonymous Referee #1, 23 Jan 2022
  • RC2: 'Comment on nhess-2021-373', Anonymous Referee #2, 19 Apr 2022
Tristan J. Shepherd, Frederick L. Letson, Rebecca J. Barthelmie, and Sara C. Pryor
Tristan J. Shepherd, Frederick L. Letson, Rebecca J. Barthelmie, and Sara C. Pryor

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Latest update: 18 May 2024
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Short summary
An historic derecho in the US is presented. The 29 June 2012 derecho caused more than 20 deaths and millions of dollars in damage. We use a regional climate model to understand how model fidelity changes under different initial conditions. We find changes drive different convective conditions resulting in a large variation in the simulated hazards. The variation from using different reanalysis data shows that framing these results in the context of contemporary and future climate is a challenge.
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