Development and Application of a Unified Framework for Meso to Synoptic Scale Error Growth Diagnosis and Weather Extremes in Global Numerical Weather Prediction

While the average skill of medium-range numerical weather prediction (NWP) has steadily improved over the last three decades, there is still considerable variance in day-to-day forecast performance. Much of this variance is contained within a long tail in the distribution that is skewed toward cases...

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Main Author: Lillo, Samuel
Other Authors: Parsons, David, Cavallo, Steven, Furtado, Jason, Martin, Elinor, Petrov, Nikola
Language:English
Published: 2021
Subjects:
Online Access:https://hdl.handle.net/11244/334410
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spelling ftoklahomaunivs:oai:shareok.org:11244/334410 2023-05-15T17:36:40+02:00 Development and Application of a Unified Framework for Meso to Synoptic Scale Error Growth Diagnosis and Weather Extremes in Global Numerical Weather Prediction Lillo, Samuel Parsons, David Cavallo, Steven Furtado, Jason Martin, Elinor Petrov, Nikola 2021-12 application/pdf application/x-latex https://hdl.handle.net/11244/334410 en eng OU Thesis and Dissertation Collections https://hdl.handle.net/11244/334410 Predictability Synoptic Error growth Extremes 2021 ftoklahomaunivs 2023-01-25T21:28:24Z While the average skill of medium-range numerical weather prediction (NWP) has steadily improved over the last three decades, there is still considerable variance in day-to-day forecast performance. Much of this variance is contained within a long tail in the distribution that is skewed toward cases with very low skill, often referred to as forecast busts or dropouts. These forecast busts in global models are typically focused on sub-continental scales and can be associated with poorly-predicted high-impact weather events, motivating efforts to understand why these busts occur, how they could be anticipated, and how forecast systems could be improved to reduce their occurrence. This study is a systematic investigation of the variability in both upscale error growth and error propagation in global NWP. Our approach utilizes a framework for diagnosing error growth that begins with a prognostic equation for potential vorticity (PV) error in which non-linear terms have been mathematically eliminated. Following adiabatic flow, a wave equation is derived for the wind and PV error from which diagnostics for wave amplitude, wave activity flux (WAF), and Rossby wave source are defined. These diagnostics are then applied to ten years of deterministic ECMWF forecasts. Our results show that in the first 24 hours the largest rotational errors at the tropopause are over the central US, and to a lesser extent eastern Asia, during the spring and summer. These errors subsequently expand downstream within the respective waveguides. During the winter, initial error growth shifts to the eastern Pacific. The difference between good an bad medium range deterministic forecasts for Europe is associated with error growth over North Atlantic. To further investigate this issue, MPAS forecast runs are presented for cases during increased MCS activity over the central US during June 2015. This period coincided with the PECAN (Plains Elevated Convection at Night) field campaign and also included multiple forecast busts in the ECMWF model. ... Other/Unknown Material North Atlantic University of Oklahoma/Oklahoma State University: SHAREOK Repository Pacific
institution Open Polar
collection University of Oklahoma/Oklahoma State University: SHAREOK Repository
op_collection_id ftoklahomaunivs
language English
topic Predictability
Synoptic
Error growth
Extremes
spellingShingle Predictability
Synoptic
Error growth
Extremes
Lillo, Samuel
Development and Application of a Unified Framework for Meso to Synoptic Scale Error Growth Diagnosis and Weather Extremes in Global Numerical Weather Prediction
topic_facet Predictability
Synoptic
Error growth
Extremes
description While the average skill of medium-range numerical weather prediction (NWP) has steadily improved over the last three decades, there is still considerable variance in day-to-day forecast performance. Much of this variance is contained within a long tail in the distribution that is skewed toward cases with very low skill, often referred to as forecast busts or dropouts. These forecast busts in global models are typically focused on sub-continental scales and can be associated with poorly-predicted high-impact weather events, motivating efforts to understand why these busts occur, how they could be anticipated, and how forecast systems could be improved to reduce their occurrence. This study is a systematic investigation of the variability in both upscale error growth and error propagation in global NWP. Our approach utilizes a framework for diagnosing error growth that begins with a prognostic equation for potential vorticity (PV) error in which non-linear terms have been mathematically eliminated. Following adiabatic flow, a wave equation is derived for the wind and PV error from which diagnostics for wave amplitude, wave activity flux (WAF), and Rossby wave source are defined. These diagnostics are then applied to ten years of deterministic ECMWF forecasts. Our results show that in the first 24 hours the largest rotational errors at the tropopause are over the central US, and to a lesser extent eastern Asia, during the spring and summer. These errors subsequently expand downstream within the respective waveguides. During the winter, initial error growth shifts to the eastern Pacific. The difference between good an bad medium range deterministic forecasts for Europe is associated with error growth over North Atlantic. To further investigate this issue, MPAS forecast runs are presented for cases during increased MCS activity over the central US during June 2015. This period coincided with the PECAN (Plains Elevated Convection at Night) field campaign and also included multiple forecast busts in the ECMWF model. ...
author2 Parsons, David
Cavallo, Steven
Furtado, Jason
Martin, Elinor
Petrov, Nikola
author Lillo, Samuel
author_facet Lillo, Samuel
author_sort Lillo, Samuel
title Development and Application of a Unified Framework for Meso to Synoptic Scale Error Growth Diagnosis and Weather Extremes in Global Numerical Weather Prediction
title_short Development and Application of a Unified Framework for Meso to Synoptic Scale Error Growth Diagnosis and Weather Extremes in Global Numerical Weather Prediction
title_full Development and Application of a Unified Framework for Meso to Synoptic Scale Error Growth Diagnosis and Weather Extremes in Global Numerical Weather Prediction
title_fullStr Development and Application of a Unified Framework for Meso to Synoptic Scale Error Growth Diagnosis and Weather Extremes in Global Numerical Weather Prediction
title_full_unstemmed Development and Application of a Unified Framework for Meso to Synoptic Scale Error Growth Diagnosis and Weather Extremes in Global Numerical Weather Prediction
title_sort development and application of a unified framework for meso to synoptic scale error growth diagnosis and weather extremes in global numerical weather prediction
publishDate 2021
url https://hdl.handle.net/11244/334410
geographic Pacific
geographic_facet Pacific
genre North Atlantic
genre_facet North Atlantic
op_relation OU Thesis and Dissertation Collections
https://hdl.handle.net/11244/334410
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