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

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

dc.contributor.advisor	Parsons, David
dc.contributor.author	Lillo, Samuel
dc.contributor.committeeMember	Cavallo, Steven
dc.contributor.committeeMember	Furtado, Jason
dc.contributor.committeeMember	Martin, Elinor
dc.contributor.committeeMember	Petrov, Nikola
dc.date.accessioned	2022-01-25T15:07:00Z
dc.date.available	2022-01-25T15:07:00Z
dc.date.issued	2021-12
dc.date.manuscript	2021-12-17
dc.description.abstract	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. Applying the PV error tendency equation allows for a detailed examination of contributions to initial upscale error growth that transitions to synoptic-scale error wave activity. The complete framework of PV error tendency and wave dynamics provides insight into preferred modes of error growth and propagation, and atmospheric configurations that are susceptible to forecast busts. Two recent extreme weather events; a winter storm over Mexico in 2016 and a cold air outbreak over the Midwest in 2019; are investigated from the context of multiple scales. The Mexico winter storm occurred during an historic El Niño while the internal mid-latitude variability disagreed with canonical Niño climatology. An unprecedented surge of mid-latitude Rossby wave activity played a major role in the severity and predictability of this and other events that winter. The 2019 cold air outbreak was the result of a tropopause polar vortex (TPV) transported out of the Arctic into the United States. Here we look at the sensitivity of the forecast to the initial strength of the TPV by using perturbed simulations with MPAS. The evolution of the structure of the TPV is explained through different sources of diabatic heating, and we find high sensitivity of the cold air outbreak severity and position to the TPV strength. A full climatology of TPV tracks is compared against cold air outbreaks in the United States to establish their connection.	en_US
dc.identifier.uri	https://hdl.handle.net/11244/334410
dc.language	en	en_US
dc.subject	Predictability	en_US
dc.subject	Synoptic	en_US
dc.subject	Error growth	en_US
dc.subject	Extremes	en_US
dc.thesis.degree	Ph.D.	en_US
dc.title	Development and Application of a Unified Framework for Meso to Synoptic Scale Error Growth Diagnosis and Weather Extremes in Global Numerical Weather Prediction	en_US
ou.group	College of Atmospheric and Geographic Sciences::School of Meteorology	en_US
shareok.orcid	0000-0001-6050-6466	en_US