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Artur Surowiecki
,
Natalia Pilguj
,
Mateusz Taszarek
,
Krzysztof Piasecki
,
Tomáš Púčik
, and
Harold E. Brooks

Abstract

In this work, we use 8 years (2014–2021) of OPERA radar data, ESWD severe weather reports, and ATDnet lightning detection data to create a climatology of quasi-linear convective systems (QLCS) across Europe. In the first step, 15-minute radar scans were used to identify 1475 QLCS polygons. Severe weather reports, lightning data, and morphological properties were used to classify QLCSs according to their intensity into 1151 marginal (78.0%), 272 moderate (18.5%), and 52 derecho (3.5%) events. Manual evaluation led to the recognition of QLCS morphological and precipitation archetypes, areal extent, duration, speed, forward motion, width, length, accompanying hazards, injuries and fatalities. Results indicate that QLCSs are the most frequent during summer in central Europe, while in southern Europe their occurrence is extended to late autumn. A bow echo feature occurred in around 29% of QLCS cases, while a mesoscale convective vortex in almost 9%. Among precipitation modes, trailing and embedded stratiform types accounted for around 50% of QLCSs. The most frequent hazard accompanying QLCSs was lightning (taking up on average 94.4% of the area impacted by QLCS), followed by severe winds gusts (7.9%), excessive precipitation (6.1%), large hail (2.9%), and tornadoes (0.5%). Derechoes had the largest coverage of severe wind reports (49.8%), while back-building QLCSs were the most prone for excessive precipitation events (13.5%). QLCSs caused 104 fatalities and 886 injuries. Severe wind gusts were responsible for 87.6% of fatalities and 73.6% of injuries. Nearly half of all fatalities and injuries were associated with only the 10 most impactful QLCS events, mostly warm-season derechoes.

Open access
William Rudisill
,
Alan Rhoades
,
Zexuan Xu
, and
Daniel R. Feldman

Abstract

Mountains play an outsized role in water resource availability, and the amount and timing of water they provide depend strongly on temperature. To that end, we ask the question: How well are atmospheric models capturing mountain temperatures? We synthesize results showing that high-resolution, regionally relevant climate models produce 2-m air temperature (T2m) measurements colder than what is observed (a “cold bias”), particularly in snow-covered midlatitude mountain ranges during winter. We find common cold biases in 44 studies across global mountain ranges, including single-model and multimodel ensembles. We explore the factors driving these biases and examine the physical mechanisms, data limitations, and observational uncertainties behind T2m. Our analysis suggests that the biases are genuine and not due to observation sparsity or resolution mismatches. Cold biases occur primarily on mountain peaks and ridges, whereas valleys are often warm biased. Our literature review suggests that increasing model resolution does not clearly mitigate the bias. By analyzing data from the Surface Atmosphere Integrated Field Laboratory (SAIL) field campaign in the Colorado Rocky Mountains, we test various hypotheses related to cold biases and find that local wind circulations, longwave (LW) radiation, and surface-layer parameterizations contribute to the T2m biases in this particular location. We conclude by emphasizing the value of coordinated model evaluation and development efforts in heavily instrumented mountain locations for addressing the root cause(s) of T2m biases and improving predictive understanding of mountain climates.

Open access
Sharanya J. Majumdar
,
David Hoffmann
,
Elizabeth E. Ebert
, and
Brian W. Golding

Abstract

University students can learn about weather warnings and contribute to a database for the World Meteorological Organization (WMO) project on Value Chain Approaches to Evaluate the End-to-End Warning Chain. The project offers students a way to understand how information about high-impact weather is created, shared, and used within a complete warning system for a selected event. Their contributions are intended to inform researchers and practitioners on what has and what has not worked well in the warning process. The students use a structured questionnaire designed to collect information on observations, forecasting, hazards, impacts, warning communications, and responses.

Two institutions took contrasting approaches to using the questionnaire. At the University of Miami, teams of meteorology undergraduates evaluated the value chain for three hurricanes. Among the issues identified were the dynamic nature of the forecasts, misinterpretations of the products, social media influences, demographic factors, and disparities in responses. The Australian Bureau of Meteorology engaged student interns in different disciplines and experience levels to evaluate and contrast the warning value chains for domestic and international events.

The students expressed enthusiasm for the exercises. Educational benefits included team collaboration, critical thinking, research and composition skills, a comprehensive view of weather events, understanding information flow, learning about new tools, and identifying gaps in practices. We encourage educators to adopt similar exercises to enable students to develop these skills, adopt value chain ideas, and contribute meaningfully to the community. The level of maintenance is low, and there is flexibility in how the exercises can be developed.

Open access
Louise Crochemore
,
Stefano Materia
,
Elisa Delpiazzo
,
Stefano Bagli
,
Andrea Borrelli
,
Francesco Bosello
,
Eva Contreras
,
Francesco Dalla Valle
,
Silvio Gualdi
,
Javier Herrero
,
Francesca Larosa
,
Rafael Lopez
,
Valerio Luzzi
,
Paolo Mazzoli
,
Andrea Montani
,
Isabel Moreno
,
Valentina Pavan
,
Ilias Pechlivanidis
,
Fausto Tomei
,
Giulia Villani
,
Christiana Photiadou
,
María José Polo
, and
Jaroslav Mysiak

Abstract

Assessing the information provided by coproduced climate services is a timely challenge, given the continuously evolving scientific knowledge and its increasing translation to address societal needs. Here, we propose a joint evaluation and verification framework to assess prototype services that provide seasonal forecast information based on the experience from the Horizon 2020 (H2020) Climate forecasts enabled knowledge services (CLARA) project. The quality and value of the forecasts generated by CLARA services were first assessed for five climate services utilizing the Copernicus Climate Change Service seasonal forecasts and responding to knowledge needs from the water resources management, agriculture, and energy production sectors. This joint forecast verification and service evaluation highlights various skills and values across physical variables, services, and sectors, as well as a need to bridge the gap between verification and user-oriented evaluation. We provide lessons learned based on the service developers’ and users’ experience and recommendations to consortia that may want to deploy such verification and evaluation exercises. Last, we formalize a framework for joint verification and evaluation in service development, following a transdisciplinary (from data purveyors to service users) and interdisciplinary chain (climate, hydrology, economics, and decision analysis).

Open access
Garik Gutman
,
Roger Pielke Sr
,
Richard Anthes
,
Pinhas Alpert
,
Alexander Baklanov
,
Svante Bodin
,
Alexander Khain
, and
Simon Krichak

Abstract

On March 5, 2023, Professor Lev Gutman would have been 100 years old. This article describes Professor Gutman’s legacy in the field of dynamic mesoscale meteorology and numerical weather prediction. Gutman developed his career as a mathematician and meteorologist in the Soviet Union, where he built a school of specialists in mesoscale meteorology during the 1950s through the 1970s. He primarily worked on analytical methods to solve complex nonlinear problems, such as the structure of sea breezes, mountain-valley circulations, and thermal convection over heated terrain. Gutman pioneered the development of theories of cumulus clouds, tornados, and other atmospheric phenomena. In the 1960s, he carried out numerous research investigations on these topics with his doctoral students and collaborators at High-Altitude Geophysical Institute in Nalchik in the northern Caucasus and later at the Siberian scientific center near Novosibirsk. Gutman compiled the results from these studies into a monograph titled “Introduction to the Nonlinear Theory of Mesoscale Meteorological Processes”, which was published in Russian in 1969, and later translated into English, Chinese, and Japanese. This monograph became a major textbook for specialists in mesoscale meteorology, remaining relevant to this day. After Prof. Gutman immigrated to Israel in 1978, his collaborations expanded to include Israeli and western scientists from Europe and the United States. Gutman did not receive the recognition he deserved due to the political realities of the time. His book and his seminal analytical solutions should still be useful for early career scientists in mesoscale meteorology and atmospheric dynamics.

Open access
Hans Burchard
,
Matthew Alford
,
Manita Chouksey
,
Giovanni Dematteis
,
Carsten Eden
,
Isabelle Giddy
,
Knut Klingbeil
,
Arnaud Le Boyer
,
Dirk Olbers
,
Julie Pietrzak
,
Friederike Pollmann
,
Kurt Polzin
,
Fabien Roquet
,
Pablo Sebastia Saez
,
Sebastiaan Swart
,
Lars Umlauf
,
Gunnar Voet
, and
Bethan Wynne-Cattanach
Open access
Paola Salio
,
Hernán Bechis
,
Bruno Z. Ribeiro
,
Ernani de Lima Nascimento
,
Vito Galligani
,
Fernando Garcia
,
Lucas Alvarenga
,
Maria de los Milagros Alvarezs Imaz
,
Daiana Marlene Baissac
,
María Florencia Barle
,
Cristian Bastías-Curivil
,
Marcos Benedicto
,
Maite Cancelada
,
Izabelly Carvalho da Costa
,
Daniela D’Amen
,
Ramon de Elia
,
David Eduardo Diaz
,
Anthony Duarte Páez
,
Sergio González
,
Vitor Goede
,
Julián Goñi
,
Agustín Granato
,
Murilo Machado Lopes
,
Matias Mederos
,
Matias Menalled
,
Romina Mezher
,
Eduardo José Mingo Vega
,
María Gabriela Nicora
,
Lucía Pini
,
Roberto Rondanelli
,
Juan Jose Ruiz
,
Nestor Santayana
,
Laís Santos
,
Guilherme Schild
,
Inés Simone
,
Raul Valenzuela
,
Yasmin Romina Velazquez
,
Luciano Vidal
, and
Constanza Inés Villagrán Asiares

Abstract

Despite southern South America being recognized as a hotspot for deep convective storms, little is known about the socioenvironmental impacts of high-impact weather (HIW) events. Although there have been past efforts to collect severe weather reports in the region, they have been highly fragmented among and within countries, sharing no common protocol, and limited to a particular phenomenon, a very specific region, or a short period of time. There is a pressing need for a more comprehensive understanding of the present risks linked to HIW events, specifically deep convective storms, on a global scale as well as their variability and potential future evolution in the context of climate change. A database of high-quality and systematic HIW reports and associated socioenvironmental impacts is essential to understand the regional atmospheric conditions leading to hazardous weather, to quantify its predictability, and to build robust early warning systems. To tackle this problem and following successful initiatives in other regions of the world, researchers, national weather service members, and weather enthusiasts from Argentina, Brazil, Chile, Paraguay, and Uruguay have embarked on a multinational collaboration to generate a standardized database of reports of HIW events principally associated with convective storms and their socioenvironmental impacts in South America. The goal of this paper is to describe this unprecedented initiative over the region, to summarize first results, and to discuss the potential applications of this collaboration.

Open access
Philip J. Klotzbach
,
Jhordanne J. Jones
,
Kimberly M. Wood
,
Michael M. Bell
,
Eric S. Blake
,
Steven G. Bowen
,
Louis-Philippe Caron
,
Daniel R. Chavas
,
Jennifer M. Collins
,
Ethan J. Gibney
,
Carl J. Schreck III
, and
Ryan E. Truchelut

Abstract

The 2023 Atlantic hurricane season was above normal, producing 20 named storms, 7 hurricanes, 3 major hurricanes and seasonal Accumulated Cyclone Energy that exceeded the 1991–2020 average. Hurricane Idalia was the most damaging hurricane of the year, making landfall as a Category 3 hurricane in Florida, resulting in eight direct fatalities and $3.6 billion USD in damage.

The above-normal 2023 hurricane season occurred during a strong El Niño event. El Niño events tend to be associated with increased vertical wind shear across the Caribbean and tropical Atlantic, yet vertical wind shear during the peak hurricane season months of August–October was well below normal. The primary driver of the above-normal season was likely record warm tropical Atlantic sea surface temperatures (SSTs), which effectively counteracted some of the canonical impacts of El Niño. The extremely warm tropical Atlantic and Caribbean were associated with weaker-than-normal trade winds driven by an anomalously weak subtropical ridge, resulting in a positive wind-evaporation-SST feedback.

We tested atmospheric circulation sensitivity to SSTs in both the tropical and subtropical Pacific and the Atlantic using the atmospheric component of the Community Earth System Model version 2.3. We found that the extremely warm Atlantic was the primary driver of the reduced vertical wind shear relative to other moderate/strong El Niño events. The concentrated warmth in the eastern tropical Pacific in August–October may have contributed to increased levels of vertical wind shear than if the warming had been more evenly spread across the eastern and central tropical Pacific.

Open access
David H. Bromwich
,
Irina V. Gorodetskaya
,
Scott Carpentier
,
Simon Alexander
,
Eric Bazile
,
Victoria J. Heinrich
,
Francois Massonnet
,
Jordan G. Powers
,
Jorge F. Carrasco
,
Arthur Cayette
,
Taejin Choi
,
Anastasia Chyhareva
,
Steven R. Colwell
,
Jason M. Cordeira
,
Raul R. Cordero
,
Alexis Doerenbecher
,
Claudio Durán-Alarcón
,
W. John R. French
,
Sergi Gonzalez-Herrero
,
Adrien Guyot
,
Thomas Haiden
,
Naohika Hirasawa
,
Paola Rodriguez Imazio
,
Brian Kawzenuk
,
Svitlana Krakovska
,
Matthew A. Lazzara
,
Mariana Fontolan Litell
,
Kevin W. Manning
,
Kimberley Norris
,
Sang-Jong Park
,
F. Martin Ralph
,
Penny M. Rowe
,
Qizhen Sun
,
Vito Vitale
,
Jonathan D. Wille
,
Zhenhai Zhang
, and
Xun Zou

Abstract

The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) held seven Targeted Observing Periods (TOPs) during the 2022 austral winter to enhance atmospheric predictability over the Southern Ocean and Antarctica. The TOPs of 5-10 days duration each featured the release of additional radiosonde balloons, more than doubling the routine sounding program at the 24 participating stations run by 14 nations, together with process-oriented observations at selected sites. These extra sounding data are evaluated for their impact on forecast skill via data denial experiments with the goal of refining the observing system to improve numerical weather prediction for winter conditions. Extensive observations focusing on clouds and precipitation primarily during atmospheric river (AR) events are being applied to refine model microphysical parameterizations for the ubiquitous mixed phase clouds that frequently impact coastal Antarctica. Process studies are being facilitated by high time resolution series of observations and forecast model output via the YOPP Model Intercomparison and Improvement Project (YOPPsiteMIIP). Parallel investigations are broadening the scope and impact of the YOPP-SH winter TOPs. Studies of the Antarctic tourist industry’s use of weather services show the scope for much greater awareness of the availability of forecast products and the skill they exhibit. The SIPN South analysis of predictions of the sea ice growth period reveals that the forecast skill is superior to the sea ice retreat phase.

Open access
Patrick C. Burke
,
Joshua Barnwell
,
Matthew Reagan
,
Mark A. Rose
,
Thomas J. Galarneau Jr.
,
Richard Otto
, and
Andrew Orrison

Abstract

On the morning of 21 August 2021, extreme rainfall spurred a flood wave on Trace Creek that ravaged Waverly, Tennessee, causing 19 fatalities. Peak 24-h rainfall of 526 mm was recorded just upstream at McEwen, setting the Tennessee 24-h state rainfall record.

A Slight Risk of excessive rainfall and a Flash Flood Watch were issued 16 and 8 hours, respectively, before rain began; however, predicting meso-beta scale extreme rainfall remains an elusive skill for models and humans alike. Operational convection allowing models suggested pockets of heavy rain, but also displayed 1) peak values generally less than half of those observed, 2) widely ranging solutions, and 3) erroneous similarly heavy rain elsewhere. Future use of storm-scale ensembles which use rapid data assimilation promises to help forecasters anticipate extrema that may only be predictable at shorter time scales. This work will examine compelling forecasts from a retrospective run of the experimental Warn-on-Forecast System (WoFS). The authors, who include National Weather Service forecasters who worked the event, discuss how WoFS and its probabilistic framework could influence services during low-predictability, high-impact flash floods.

Open access