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Travis Griggs
,
James Flynn
,
Yuxuan Wang
,
Sergio Alvarez
,
Michael Comas
, and
Paul Walter

Abstract

Photochemical modeling outputs showing high ozone concentrations over the Gulf of Mexico and Galveston Bay during ozone episodes in the Houston–Galveston–Brazoria (HGB) region have not been previously verified using in situ observations. Such data were collected systematically, for the first time, from July to October 2021 from three boats deployed for the Galveston Offshore Ozone Observations (GO3) and Tracking Aerosol Convection Interactions Experiment—Air Quality (TRACER-AQ) field campaigns. A pontoon boat and a commercial vessel operated in Galveston Bay, while another commercial vessel operated in the Gulf of Mexico offshore of Galveston. All three boats had continuously operating sampling systems that included ozone analyzers and weather stations, and the two boats operating in Galveston Bay had a ceilometer. The sampling systems operated autonomously on the two commercial boats as they traveled their daily routes. Thirty-seven ozonesondes were launched over water on forecast high ozone days in Galveston Bay and the Gulf of Mexico. During the campaigns, multiple periods of ozone exceeding 100 ppbv were observed over water in Galveston Bay and the Gulf of Mexico. These events included previously identified conditions for high ozone events in the HGB region, such as the bay/sea-breeze recirculation and postfrontal environments, as well as a localized coastal high ozone event after the passing of a tropical system (Hurricane Nicholas) that was not well forecast.

Open access
Morgan E O’Neill
and
Daniel R. Chavas
Open access
Teryn J. Mueller
,
Christina M. Patricola
, and
Emily Bercos-Hickey

Abstract

The El Niño–Southern Oscillation (ENSO) influences seasonal Atlantic tropical cyclone (TC) activity by impacting environmental conditions important for TC genesis. However, the influence of future climate change on the teleconnection between ENSO and Atlantic TCs is uncertain, as climate change is expected to impact both ENSO and the mean climate state. We used the Weather Research and Forecasting model on a tropical channel domain to simulate 5-member ensembles of Atlantic TC seasons in historical and future climates under different ENSO conditions. Experiments were forced with idealized sea-surface temperature configurations based on the Community Earth System Model (CESM) Large Ensemble representing: a monthly-varying climatology, Eastern Pacific El Niño, Central Pacific El Niño, and La Niña. The historical simulations produced fewer Atlantic TCs during Eastern Pacific El Niño compared to Central Pacific El Niño, consistent with observations and other modeling studies. For each ENSO state, the future simulations produced a similar teleconnection with Atlantic TCs as in the historical simulations. Specifically, La Niña continues to enhance Atlantic TC activity, and El Niño continues to suppress Atlantic TCs, with greater suppression during Eastern Pacific El Niño compared to Central Pacific El Niño. In addition, we found a decrease in Atlantic TC frequency in the future relative to historical regardless of ENSO state, which was associated with a future increase in northern tropical Atlantic vertical wind shear and a future decrease in the zonal tropical Pacific SST gradient, corresponding to a more El Niño-like mean climate state. Our results indicate that ENSO will remain useful for seasonal Atlantic TC prediction in the future.

Restricted access
Jingjie Yu
,
Bolan Gan
,
Haiyuan Yang
,
Zhaohui Chen
,
Lixiao Xu
, and
Lixin Wu

Abstract

Subtropical mode water (STMW) is a thick layer of water mass characterized by homogeneous properties within the main pycnocline, important for oceanic oxygen utilization, carbon sequestration, and climate regulation. North Pacific STMW is formed in the Kuroshio Extension region, where vigorous mesoscale eddies strongly interact with the atmosphere. However, it remains unknown how such mesoscale ocean-atmosphere (MOA) coupling affects the STMW formation. By conducting twin simulations with an eddy-resolving global climate model, we find that approximately 25% more STMW is formed with the MOA coupling than without it. This is attributable to a significant increase in ocean latent heat release primarily driven by higher wind speed over the STMW formation region, which is associated with the southward deflection of storm tracks in response to oceanic mesoscale imprints. Such enhanced surface latent heat loss overwhelms the stronger upper-ocean restratification induced by vertical eddy and turbulent heat transport, leading to the formation of colder and denser STMW in the presence of MOA coupling. Further investigation of a multi-model and multi-resolution ensemble of global coupled models reveals that the agreement between the STMW simulation in eddy-present/rich coupled models and observations is superior to that of eddy-free ones, likely due to more realistic representation of MOA coupling. However, the ocean-alone model simulations show significant limitations in improving STMW production, even with refined model resolution. This indicates the importance of incorporating the MOA coupling into Earth system models to alleviate biases in STMW and associated climatic and biogeochemical impacts.

Restricted access
Jannick Fischer
,
Johannes M. L. Dahl
,
Brice E. Coffer
,
Jana Lesak Houser
,
Paul M. Markowski
,
Matthew D. Parker
,
Christopher C. Weiss
, and
Alex Schueth

Abstract

Over the last decade, supercell simulations and observations with ever increasing resolution have provided new insights into the vortex-scale processes of tornado formation. This article incorporates these and other recent findings into the existing three-step model by adding an additional fourth stage. The goal is to provide an updated and clear picture of the physical processes occurring during tornadogenesis. Specifically, we emphasize the importance of the low-level wind shear and mesocyclone for tornado potential, the organization and interaction of relatively small-scale pre-tornadic vertical vorticity maxima, and the transition to a tornado-characteristic flow. Based on these insights, guiding research questions are formulated for the decade ahead.

Open access
Hui Yu
,
Guomin Chen
,
Wai-Kin Wong
,
Jonathan L. Vigh
,
Chi-kin Pan
,
Xiaoqin Lu
,
Jun A. Zhang
,
Jie Tang
,
Kun Zhao
,
Peiyan Chen
,
Zifeng Yu
,
Mengqi Yang
,
Jason Dunion
,
Zheqing Fang
,
Xiaotu Lei
,
Ajit Tyagi
, and
Lianshou Chen

Abstract

The Typhoon Landfall Forecast Demonstration Project (TLFDP) (2010–2022) was an international cooperative scientific project conducted under the framework of the WMO. The primary objectives of the TLFDP were to enhance the capability of tropical cyclone (TC) forecasters, and support related decision-makers in effective utilization of the most advanced forecasting techniques for the ultimate purpose of reducing and preventing disasters associated with TC landfall. Forty agencies/organizations/projects globally participated in the activities of the TLFDP following its inception in 2010, although the primary focus was on landfalling TCs in the western North Pacific. The TLFDP facilitated collaborations and workshops that realized notable achievements in four key areas: 1) the collection, production, and sharing of TC data; 2) the development and application of TC forecast verification metrics; 3) research on TC forecast skill; and 4) development of new techniques for TC forecasting. An obvious outcome was the shift from prediction of TC features, including track and intensity, toward prediction of TC impacts with more probabilistic conception. The final years of the project also promoted increasing application of artificial intelligence and machine learning techniques in various techniques for analysis and forecasting of TCs. Although the TLFDP ended in 2022, its core activities have continued to be extended through new WMO projects and regional cooperative initiatives.

Open access
Christopher J. Schultz
,
Phillip M. Bitzer
,
Michael Antia
,
Jonathan L. Case
, and
Christopher R. Hain

Abstract

Twenty-six years of lightning data were paired with over 68 000 lightning-initiated wildfire (LIW) reports to understand lightning flash characteristics responsible for ignition in between 1995 and 2020. Results indicate that 92% of LIW were started by negative cloud-to-ground (CG) lightning flashes and 57% were single stroke flashes. Moreover, 62% of LIW reports did not have a positive CG within 10 km of the start location, contrary to the science literature’s suggestion that positive CG flashes are a dominant fire-starting mechanism. Nearly ⅓ of wildfire events were holdovers, meaning 1 or more days elapsed between lightning occurrence and fire report. However, fires that were reported less than a day after lightning occurrence statistically burned more acreage. Peak current was not found to be a statistically significant delineator between fire starters and non–fire starters for negative CGs but was for positive CGs. Results highlighted the need for reassessing the role of positive CG lightning and subsequently long-continuing current in wildfire ignition started by lightning. One potential outcome of this study’s results is the development of real-time tools to identify ignition potential during lightning events to aid in fire mitigation efforts.

Restricted access
Pieter B. Smit
,
Galen Egan
, and
Isabel A Houghton

Abstract

Peak periods estimated from finite resolution frequency spectra are necessarily discrete. For wind generated surface gravity waves, conflicting considerations of robust (quasi)-stationary statistics, and high spectral resolution, combined with the inverse relation between frequency and period, this typically implies that swell periods (above 10 s) are resolved at best at 𝒪(1) s intervals. Here we consider a method to improve peak period estimates for finite resolution spectra. Specifically, we propose to define the peak period based on continuous spectra derived from a spline-based interpolation of the discretely sampled monotone cumulative distribution function. The method may directly be applied to existing discrete spectra—the original time-domain data (which may not be available) are not required. We compare reconstructed spectra and derived peak periods to parametric shapes and field data. Peak estimates are markedly improved, allowing for better tracking of e.g., swells. The proposed method also marginally improves spectral levels and shape for a given discretely sampled estimate.

Open access
Eun-Pa Lim
,
Harry H. Hendon
,
Amy H. Butler
,
David W. J. Thompson
,
Zachary D. Lawrence
,
Adam A. Scaife
,
Theodore G. Shepherd
,
Inna Polichtchouk
,
Hisashi Nakamura
,
Chiaki Kobayashi
,
Ruth Comer
,
Lawrence Coy
,
Andrew Dowdy
,
Rene D. Garreaud
,
Paul A. Newman
, and
Guomin Wang
Open access
Matthew Patterson
,
Christopher O’Reilly
,
Jon Robson
, and
Tim Woollings

Abstract

The coupled nature of the ocean-atmosphere system frequently makes understanding the direction of causality difficult in ocean-atmosphere interactions. This study presents a method to decompose turbulent surface heat fluxes into a component which is directly forced by atmospheric circulation, and a residual which is assumed to be primarily ‘ocean-forced’. This method is applied to the North Atlantic in a 500-year pre-industrial control run using the Met Office’s HadGEM3-GC3.1-MM model. The method shows that atmospheric circulation dominates interannual to decadal heat flux variability in the Labrador Sea, in contrast to the Gulf Stream where the Ocean primarily drives the variability. An empirical orthogonal function analysis identifies several residual heat flux modes associated with variations in ocean circulation. The first of these modes is characterised by the ocean warming the atmosphere along the Gulf Stream and North Atlantic Current and the second by a dipole of cooling in the western subtropical North Atlantic and warming in the sub-polar North Atlantic. Lead-lag regression analysis suggests that atmospheric circulation anomalies in prior years partly drive the ocean heat flux modes, however there is no significant atmospheric circulation response in years following the peaks of the modes. Overall, the heat flux dynamical decomposition method provides a useful way to separate the effects of the ocean and atmosphere on heat flux and could be applied to other ocean basins and to either models or reanalysis datasets.

Open access