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Yun Fan
,
Vladimir Krasnopolsky
,
Huug van den Dool
,
Chung-Yu Wu
, and
Jon Gottschalck

in initial and boundary conditions, and other reasons. Therefore, various dynamical model postprocessing strategies are developed to remove forecast biases and errors, and to nudge model predictions toward observations, before forecasts are issued to the public. Linear statistical postprocessing methods show some success in improving direct model prediction skill. One of those techniques is the model output statistics (MOS), which relates observed weather elements (predictands) to appropriate

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Eric D. Loken
,
Adam J. Clark
,
Amy McGovern
,
Montgomery Flora
, and
Kent Knopfmeier

, multiple-physics CAEs is an artificial inflation of ensemble spread due to the existence of systematic biases between ensemble members ( Eckel and Mass 2005 ; Clark et al. 2010b ; Loken et al. 2019 ). These shortcomings are typically resolved using one or more postprocessing techniques, including isotropic (e.g., Sobash et al. 2011 , 2016 ; Loken et al. 2017 , 2019 ; Roberts et al. 2019 ) or anisotropic (e.g., Marsh et al. 2012 ) spatial smoothing of the raw forecast probability field

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John L. Cintineo
,
Michael J. Pavolonis
,
Justin M. Sieglaff
,
Anthony Wimmers
,
Jason Brunner
, and
Willard Bellon

1. Introduction Since the advent of weather satellites, researchers have been investigating signatures of intense convection from satellite images (e.g., Purdom 1976 ; Adler and Fenn 1979 ; Menzel and Purdom 1994 ; Schmit et al. 2005 , 2015 ). Forecasters frequently scrutinize satellite imagery to help infer storm dynamics and diagnose and forecast the intensity of thunderstorms, which can generate a variety of hazards. Intense convective updrafts frequently penetrate the tropopause

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