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Elizabeth Tirone
,
Subrata Pal
,
William A Gallus Jr.
,
Somak Dutta
,
Ranjan Maitra
,
Jennifer Newman
,
Eric Weber
, and
Israel Jirak

Abstract

Many concerns are known to exist with thunderstorm wind reports in the National Center for Environmental Information Storm Events Database, including the overestimation of wind speed, changes in report frequency due to population density, and differences in reporting due to damage tracers. These concerns are especially pronounced with reports that are not associated with a wind speed measurement, but are estimated, which make up almost 90% of the database. We have used machine learning to predict the probability that a severe wind report was caused by severe intensity wind, or wind ≥ 50 kt. A total of six machine learning models were trained on 11 years of measured thunderstorm wind reports, along with meteorological parameters, population density, and elevation. Objective skill metrics such as the area under the ROC curve (AUC), Brier score, and reliability curves suggest that the best performing model is the stacked generalized linear model, which has an AUC around 0.9 and a Brier score around 0.1. The outputs from these models have many potential uses such as forecast verification and quality control for implementation in forecast tools. Our tool was evaluated favorably at the Hazardous Weather Testbed Spring Forecasting Experiments in 2020, 2021, and 2022.

Open access
Cyrille Flamant
,
Jean-Pierre Chaboureau
,
Julien Delanoë
,
Marco Gaetani
,
Cédric Jamet
,
Christophe Lavaysse
,
Olivier Bock
,
Maurus Borne
,
Quitterie Cazenave
,
Pierre Coutris
,
Juan Cuesta
,
Laurent Menut
,
Clémantyne Aubry
,
Angela Benedetti
,
Pierre Bosser
,
Sophie Bounissou
,
Christophe Caudoux
,
Hélène Collomb
,
Thomas Donal
,
Guy Febvre
,
Thorsten Fehr
,
Andreas H. Fink
,
Paola Formenti
,
Nicolau Gomes Araujo
,
Peter Knippertz
,
Eric Lecuyer
,
Mateus Neves Andrade
,
Cédric Gacial Ngoungué Langué
,
Tanguy Jonville
,
Alfons Schwarzenboeck
, and
Azusa Takeishi

Abstract

During the boreal summer, mesoscale convective systems generated over West Africa propagate westward and interact with African easterly waves, and dust plumes transported from the Sahel and Sahara by the African easterly jet. Once off West Africa, the vortices in the wake of these mesoscale convective systems evolve in a complex environment sometimes leading to the development of tropical storms and hurricanes, especially in September when sea surface temperatures are high. Numerical weather predictions of cyclogenesis downstream of West Africa remains a key challenge due to the incomplete understanding of the clouds–atmospheric dynamics–dust interactions that limit predictability. The primary objective of the Clouds–Atmospheric Dynamics–Dust Interactions in West Africa (CADDIWA) project is to improve our understanding of the relative contributions of the direct, semidirect, and indirect radiative effects of dust on the dynamics of tropical waves as well as the intensification of vortices in the wake of offshore mesoscale convective systems and their evolution into tropical storms over the North Atlantic. Airborne observations relevant to the assessment of such interactions (active remote sensing, in situ microphysics probes, among others) were made from 8 to 21 September 2021 in the tropical environment of Sal Island, Cape Verde. The environments of several tropical cyclones, including Tropical Storm Rose, were monitored and probed. The airborne measurements also serve the purpose of regional model evaluation and the validation of spaceborne wind, aerosol and cloud products pertaining to satellite missions of the European Space Agency and EUMETSAT (including the Aeolus, EarthCARE, and IASI missions).

Open access
Xuelong Chen
,
Xiangde Xu
,
Yaoming Ma
,
Gaili Wang
,
Deliang Chen
,
Dianbin Cao
,
Xin Xu
,
Qiang Zhang
,
Luhan Li
,
Yajing Liu
,
Liping Liu
,
Maoshan Li
,
Siqiong Luo
,
Xin Wang
, and
Xie Hu

Abstract

The Yarlung Zsangbo Grand Canyon (YGC) is an important pathway for water vapor transport from southern Asia to the Tibetan Plateau (TP). This area exhibits one of the highest frequencies of convective activity in China, and precipitation often induces natural disasters in local communities, which can dramatically affect their livelihoods. In addition, the produced precipitation gives rise to vast glaciers and large rivers around the YGC. In 2018, the Second Tibetan Plateau Scientific Expedition and Research Program tasked a research team to conduct an “investigation of the precipitation process in the water vapor channel of the Yarlung Zsangbo Grand Canyon” (INVC) in the southeastern TP. This team subsequently established a comprehensive observation system of land–air interaction, water vapor, clouds, and rainfall activity in the YGC. This paper introduces the developed observation system and summarizes the preliminary results obtained during the first two years of the project. Using this INVC observation network, herein, we focus on the development of rainfall events on the southeastern TP. This project also helps to monitor geohazards in the key area of the Sichuan–Tibet railway, which traverses the northern YGC. The observation datasets will benefit future research on mountain meteorology.

Open access
Machiel Lamers
,
Gita Ljubicic
,
Rick Thoman
,
Jorge Carrasco
,
Jackie Dawson
,
Victoria J. Heinrich
,
Jelmer Jeuring
,
Daniela Liggett
, and
Emma J. Stewart

Abstract

The Polar Prediction Project (PPP), one of the flagship programmes of the World Meteorological Organisation’s (WMO) World Weather Research Programme (WWRP), has come to an end after a decade of intensive and coordinated international observing, modelling, verification, user engagement, and education activities. While PPP facilitated many advancements in modelling and forecasting, critical investment is now required to turn prediction science into salient environmental services for the Polar Regions. In this commentary, the members of the Societal and Economic Research and Applications task team of PPP, a group of social scientists and service delivery specialists, identify a number of insights and lessons that are critical for the implementation of the follow up programme Polar Coupled Analysis and Prediction for Services (PCAPS). We argue that in order to raise the societal value of polar environmental services we need: to better understand the diversity of highly specific user contexts; to tailor the actionability of weather, water, ice and climate (WWIC) service development in the Polar Regions through inclusive transdisciplinary approaches to co-production; to assess the societal impact of improved environmental services in the Polar Regions; and to invest and provide dedicated funding for involving the social sciences in research and tailoring processes across all the Polar Regions.

Open access
Xubin Zeng
,
Hui Su
,
Svetla Hristova-Veleva
,
Derek J. Posselt
,
Robert Atlas
,
Shannon T. Brown
,
Ross D. Dixon
,
Eric Fetzer
,
Thomas J. Galarneau Jr.
,
Michael Hardesty
,
Jonathan H. Jiang
,
Pekka P. Kangaslahti
,
Amir Ouyed
,
Thomas S. Pagano
,
Oliver Reitebuch
,
Remy Roca
,
Ad Stoffelen
,
Sara Tucker
,
Anna Wilson
,
Longtao Wu
, and
Igor Yanovsky

Abstract

It is challenging to accurately characterize the three-dimensional distribution of horizontal wind vectors (known as 3D winds). Feature-matching satellite cloud top or water vapor fields have been used for decades to retrieve atmospheric motion vectors, but this approach is mostly limited to a single and uncertain pressure level at a given time. Satellite wind lidar measurements are expected to provide more accurate data and capture the line-of-sight wind for clear skies, within cirrus clouds, and above thick clouds, but only along a curtain parallel to the satellite track. Here we propose Vientos—a new satellite mission concept that combines two or more passive water vapor sounders with Doppler wind lidar to measure 3D winds. The need for 3D wind observations is highlighted by inconsistencies in reanalysis estimates, particularly under precipitating conditions. Recent studies have shown that 3D winds can be retrieved using water vapor observations from two polar-orbiting satellites separated by 50 min, with the help of advanced optical flow algorithms. These winds can be improved through the incorporation of a small number of collocated higher-accuracy measurements via machine learning. The Vientos concept would enable simultaneous measurements of 3D winds, temperature, and humidity, and is expected to have a significant impact on scientific research, weather prediction, and other applications. For example, it can help better understand and predict the preconditions for organized convection. This article summarizes recent results, presents the Vientos mission architecture, and discusses implementation scenarios for a 3D wind mission under current budget constraints.

Open access
Janet Sprintall
,
Motoki Nagura
,
Juliet Hermes
,
M. K. Roxy
,
Michael J. McPhaden
,
E. Pattabhi Rama Rao
,
Srinivasa Kumar Tummala
,
Sidney Thurston
,
Jing Li
,
Mathieu Belbeoch
, and
Victor Turpin

Abstract

Observing and understanding the state of the Indian Ocean and its influence on climate and maritime resources is of critical importance to the populous nations that rim its border. Acute gaps have occurred in the Indian Ocean observing system, which underpins monitoring and forecasting of regional climate, since the start of the COVID pandemic. The pandemic disrupted the deployment and maintenance cruises for the observational array and also resulted in supply chain issues for procurement and refurbishment of equipment. In particular, the observational platforms that provide key measurements of upper ocean heat variability have experienced serious multi-year declines. There is now record-low data reporting and the platforms that are successfully reporting are old and quickly surpassing their expected period of reliable operation. The overall impact on the observing system will take a few years to fully comprehend. In the meantime, there is a critical need to document the gaps that have appeared over the past few years and how this will impact our ability to improve understanding and model representations of the real world that support regional weather and climate forecasts. The article outlines the expected slow road to recovery for the Indian Ocean observing system, documents case studies of successful international collaborative efforts that will revive the observing system and provides guidelines for resilience from unexpected external factors in the future.

Open access
Ali Sarhadi
,
Raphaël Rousseau-Rizzi
,
Kyle Mandli
,
Jeffrey Neal
,
Michael P. Wiper
,
Monika Feldmann
, and
Kerry Emanuel

Abstract

Efforts to meaningfully quantify the changes in coastal compound surge- and rainfall-driven flooding hazard associated with tropical cyclones (TCs) and extratropical cyclones (ETCs) in a warming climate have increased in recent years. Despite substantial progress, however, obtaining actionable details such as the spatially and temporally varying distribution and proximal causes of changing flooding hazard in cities remains a persistent challenge. Here, for the first time, physics-based hydrodynamic flood models driven by rainfall and storm surge simultaneously are used to estimate the magnitude and frequency of compound flooding events. We apply this to the particular case of New York City. We find that sea level rise (SLR) alone will increase the TC and ETC compound flooding hazard more significantly than changes in storm climatology as the climate warms. We also project that the probability of destructive Sandy-like compound flooding will increase by up to 5 times by the end of the century. Our results have strong implications for climate change adaptation in coastal communities.

Open access
Elizabeth M. Page
,
Samuel S. P. Shen
, and
Richard C. J. Somerville
Open access
Antje Weisheimer
,
Laura H. Baker
,
Jochen Bröcker
,
Chaim I. Garfinkel
,
Steven C. Hardiman
,
Dan L.R. Hodson
,
Tim N. Palmer
,
Jon I. Robson
,
Adam A. Scaife
,
James A. Screen
,
Theodore G. Shepherd
,
Doug M. Smith
, and
Rowan T. Sutton
Open access
D. D. Turner
,
L. Ott
,
P. F. Steblein
,
M. Stieglitz
,
O. Tweedy
,
J. Furman
, and
C. S. James

Abstract

The size, duration, impact, and cost of wildland fire is increasing over the last several decades. A recent Interagency Council for Advancing Meteorological Services (ICAMS)-sponsored workshop focused on the scientific questions and challenges associated with subseasonal-to-seasonal wildfire outlooks. Opinions from this workshop, including recommended cross-agency motivation and activities, are provided.

Open access