Using Ensemble Sensitivity to Diagnose Environmental Modulation of Mesocyclone Intensity in the Warn-on-Forecast System.

Saved in:

Bibliographic Details
Title:	Using Ensemble Sensitivity to Diagnose Environmental Modulation of Mesocyclone Intensity in the Warn-on-Forecast System.
Authors:	Faletti, William L.¹ (AUTHOR) wfaletti@ou.edu, Weiss, Christopher C.¹ (AUTHOR), Skinner, Patrick S.^2,3,4 (AUTHOR), Ancell, Brian C.¹ (AUTHOR)
Source:	Monthly Weather Review. Jun2026, Vol. 154 Issue 6, p1-25. 25p.
Subjects:	Sensitivity analysis, Weather forecasting, Environmental sciences, Thermal instability, Thunderstorm forecasting, Atmospheric boundary layer
Abstract:	Ensemble sensitivity analysis (ESA) is a computationally inexpensive technique to diagnose how the initial atmospheric state affects a later forecast metric. Recent study has found success applying this method to convective phenomena from the meso-alpha scale to the storm-scale. Some of these works have analyzed short-term, ensemble predictions of thunderstorms and their near-storm environments within the Warn-on-Forecast System (WoFS). However, several challenges remain largely unexplored that may complicate ESA usage within the system, including a multiphysics configuration and relatively small ensemble size. As such, this study applies ESA to forecasts of individual mesocyclones to 1) better understand its utility within the WoFS framework and 2) uncover near-storm controls on predicted mesocyclone strength. Storm-relative sensitivities to many diagnostic variables are calculated at short (30-90 minute) lead times for an updraft helicity response function. Their spatial and statistical distributions are analyzed as they relate to near-storm dynamics and member-to-member planetary boundary layer (PBL) scheme stratification. ESA is found to provide useful insight into sources of short-term uncertainty of predicted mesocyclone strength. These sources also differed notably case-to-case, ranging from environmental differences to storm interactions, and were often induced by PBL multiphysics. Further, ESA illuminates how WoFS models storm-induced kinematic feedbacks, finding patterns similar to previous supercell dynamics research. These results indicate that ESA is an effective metric to identify sources of uncertainty in future WoFS case studies. Additionally, the utility of ESA-based forecast improvement techniques like ensemble subsetting should be explored within WoFS. [ABSTRACT FROM AUTHOR]
	Copyright of Monthly Weather Review is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database:	Engineering Source

Description
Abstract:	Ensemble sensitivity analysis (ESA) is a computationally inexpensive technique to diagnose how the initial atmospheric state affects a later forecast metric. Recent study has found success applying this method to convective phenomena from the meso-alpha scale to the storm-scale. Some of these works have analyzed short-term, ensemble predictions of thunderstorms and their near-storm environments within the Warn-on-Forecast System (WoFS). However, several challenges remain largely unexplored that may complicate ESA usage within the system, including a multiphysics configuration and relatively small ensemble size. As such, this study applies ESA to forecasts of individual mesocyclones to 1) better understand its utility within the WoFS framework and 2) uncover near-storm controls on predicted mesocyclone strength. Storm-relative sensitivities to many diagnostic variables are calculated at short (30-90 minute) lead times for an updraft helicity response function. Their spatial and statistical distributions are analyzed as they relate to near-storm dynamics and member-to-member planetary boundary layer (PBL) scheme stratification. ESA is found to provide useful insight into sources of short-term uncertainty of predicted mesocyclone strength. These sources also differed notably case-to-case, ranging from environmental differences to storm interactions, and were often induced by PBL multiphysics. Further, ESA illuminates how WoFS models storm-induced kinematic feedbacks, finding patterns similar to previous supercell dynamics research. These results indicate that ESA is an effective metric to identify sources of uncertainty in future WoFS case studies. Additionally, the utility of ESA-based forecast improvement techniques like ensemble subsetting should be explored within WoFS. [ABSTRACT FROM AUTHOR]
ISSN:	00270644
DOI:	10.1175/MWR-D-25-0123.1