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Ke Xu
and
Riyu Lu

Abstract

The break events of the western North Pacific summer monsoon vary significantly in duration, ranging from a few days to more than two weeks. In this study, we classify the monsoon break events into short-lived (≤8 days) and long-lived (>8 days) events, which account for 78% and 22% of the total events during 1979–2020, respectively. The results show that convection suppression is stronger and broader for long-lived events than for short-lived events. In addition, the temporal distributions of the two break categories are distinct: short-lived events present a roughly even distribution from late July to late September, while long-lived events are highly concentrated, with a striking frequency peak around early September.

The mechanisms responsible for break events are investigated. Results indicate that both break categories are co-contributed by 10–25-day and 30–60-day oscillations. Short-lived events result from a phase lock of the two oscillations, which explain 54% and 35% of the convection suppression, respectively. By contrast, long-lived events are initiated by both oscillations but maintained only by 30–60-day oscillations. In addition, 30–60-day oscillations reach the peak intensity after the monsoon onset due to seasonal background changes, which is critical for forming the frequency peak of long-lived events around early September. Furthermore, it is found that long-lived events prefer to occur in the developing phase of positive SST anomalies in the tropical central Pacific, when 30–60-day oscillations are abnormally enhanced over the western North Pacific.

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Vincent-Henri Peuch
,
Richard Engelen
,
Michel Rixen
,
Dick Dee
,
Johannes Flemming
,
Martin Suttie
,
Melanie Ades
,
Anna Agustí-Panareda
,
Cristina Ananasso
,
Erik Andersson
,
David Armstrong
,
Jérôme Barré
,
Nicolas Bousserez
,
Juan Jose Dominguez
,
Sébastien Garrigues
,
Antje Inness
,
Luke Jones
,
Zak Kipling
,
Julie Letertre-Danczak
,
Mark Parrington
,
Miha Razinger
,
Roberto Ribas
,
Stijn Vermoote
,
Xiaobo Yang
,
Adrian Simmons
,
Juan Garcés de Marcilla
, and
Jean-Noël Thépaut

Abstract

The Copernicus Atmosphere Monitoring Service (CAMS), part of the European Union’s Earth observation program Copernicus, entered operations in July 2015. Implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) as a truly European effort with over 23,500 direct data users and well over 200 million end users worldwide as of March 2022, CAMS delivers numerous global and regional information products about air quality, inventory-based emissions and observation-based surface fluxes of greenhouse gases and from biomass burning, solar energy, ozone and UV radiation, and climate forcings. Access to CAMS products is open and free of charge via the Atmosphere Data Store. The CAMS global atmospheric composition analyses, forecasts, and reanalyses build on ECMWF’s Integrated Forecasting System (IFS) and exploit over 90 different satellite data streams. The global products are complemented by coherent higher-resolution regional air quality products over Europe derived from multisystem analyses and forecasts. CAMS information products also include policy support such as quantitative impact assessment of short- and long-term pollutant-emission mitigation scenarios, source apportionment information, and annual European air quality assessment reports. Relevant CAMS products are cited and used for instance in IPCC Assessment Reports. Providing dedicated support for users operating smartphone applications, websites, or TV bulletins in Europe and worldwide is also integral to the service. This paper presents key achievements of the CAMS initial phase (2014–21) and outlines some of its new components for the second phase (2021–28), e.g., the new Copernicus anthropogenic CO2 emissions Monitoring and Verification Support capacity that will monitor global anthropogenic emissions of key greenhouse gases.

Free access
Carlo Buontempo
,
Samantha N. Burgess
,
Dick Dee
,
Bernard Pinty
,
Jean-Noël Thépaut
,
Michel Rixen
,
Samuel Almond
,
David Armstrong
,
Anca Brookshaw
,
Angel Lopez Alos
,
Bill Bell
,
Cedric Bergeron
,
Chiara Cagnazzo
,
Edward Comyn-Platt
,
Eduardo Damasio-Da-Costa
,
Anabelle Guillory
,
Hans Hersbach
,
András Horányi
,
Julien Nicolas
,
Andre Obregon
,
Eduardo Penabad Ramos
,
Baudouin Raoult
,
Joaquín Muñoz-Sabater
,
Adrian Simmons
,
Cornel Soci
,
Martin Suttie
,
Freja Vamborg
,
James Varndell
,
Stijn Vermoote
,
Xiaobo Yang
, and
Juan Garcés de Marcilla

Abstract

The Copernicus Climate Change Service (C3S) provides open and free access to state-of-the-art climate data and tools for use by governments, public authorities, and private entities around the world. It is fully funded by the European Union and implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) together with public and private entities in Europe and elsewhere. With over 120,000 registered users worldwide, C3S has rapidly become an authoritative climate service in Europe and beyond, delivering quality-assured climate data and information based on the latest science. Established in 2014, C3S became fully operational in 2018 with the launch of its Climate Data Store, a powerful cloud-based infrastructure providing access to a vast range of global and regional information, including climate data records derived from observations, the latest ECMWF reanalyses, seasonal forecast data from multiple providers, and a large collection of climate projections. The system has been designed to be accessible to nonspecialists, offering a uniform interface to all data and documentation as well as a Python-based toolbox that can be used to process and use the data online. C3S publishes European State of the Climate reports annually for policy-makers, as well as monthly and annual summaries that are widely disseminated in the international press. Together with users, C3S develops customized indicators of climate impacts in economic sectors such as energy, water management, agriculture, insurance, health, and urban planning. C3S works closely with national climate service providers, satellite agencies, and other stakeholders on the improvement of its data and services.

Free access
Cory L. Armstrong
and
Anna Grace Usery

Abstract

When a tornado hits, there is little time to think through mental checklists for needed items. This study attempted to understand what information sources those in the path of tornados utilized for preparation and how those sources influence people to act. Results from the study indicate that television and radio are the top two information sources, and that some visual graphics—gauged via heat maps to understand higher levels of severe weather preparation—were reported as useful. Contrary to meteorological intentions, results showed that participants were less likely to prepare for impending weather when radar displayed tornado locations and intensity. In addition, those who identified as having more interest in weather-related information in the study were significantly more likely to prepare, along with those who fear future tornadoes. Each variable explored is underpinned by the theory of planned behavior and the risk information seeking and processing (RISP) model to better understand behavioral intentions and actions. This study offers two new concepts of general weather that have not previously been explored: interest and general versus specific storm preparation.

Significance Statement

The purpose of this work is to learn more about how individuals gather information and obtain weather warnings, primarily during tornado events. In particular, the study seeks to understand how individuals view and interpret visual graphics with information about the location and details about the event. Further, results suggest some differences between those who generally prepare for storm season versus those who only prepare for a specific event. Researchers may also be interested to know how weather enthusiasts may differ in their preparatory activities in comparison with nonweather enthusiasts. All of this information will help meteorologists and media professionals to better target their messages during severe weather.

Restricted access
Zeng-Zhen Hu
,
Yan Xue
,
Boyin Huang
,
Arun Kumar
,
Caihong Wen
,
Pingping Xie
,
Jieshun Zhu
,
Philip J. Pegion
,
Li Ren
, and
Wanqiu Wang

Abstract

Climate variability on subseasonal to interannual time scales has significant impacts on our economy, society, and Earth’s environment. Predictability for these time scales is largely due to the influence of the slowly varying climate anomalies in the oceans. The importance of the global oceans in governing climate variability demonstrates the need to monitor and forecast the global oceans in addition to El Niño–Southern Oscillation in the tropical Pacific. To meet this need, the Climate Prediction Center (CPC) of the National Centers for Environmental Prediction (NCEP) initiated real-time global ocean monitoring and a monthly briefing in 2007. The monitoring covers observations as well as forecasts for each ocean basin. In this paper, we introduce the monitoring and forecast products. CPC’s efforts bridge the gap between the ocean observing system and the delivery of the analyzed products to the community. We also discuss the challenges involved in ocean monitoring and forecasting, as well as the future directions for these efforts.

Free access
Zoey Rosen

Abstract

The narratives of emerging adults, such as university students, can reveal aspects of their professional and academic identities that explain their career paths. While narrative has been studied as a tool in the meteorological classroom, narrative has not been used to study why students choose to become meteorologists. This study aims to identify the narrative features about what draws students to pursue meteorology as a career, and reflect upon how the telling of these narratives can help career counselors and other stakeholders, like universities, to understand this discipline of students. This study is a qualitative textual analysis of N = 34 video clips of meteorology students from around the United States submitted for the 2020 AMS Student Conference welcome video, #MyFieldMyStory campaign. The findings show that formative experiences like early childhood memories, mediated experiences with the weather, and family interactions were major life themes in the students’ stories. Other reasons students chose this career path were concerns over local climatic effects, a desire to control their course of study, curiosity stemming from internships and research opportunities, confidence from their personal math/science propensity in school, and a commitment to do work that can mitigate the effects of severe weather or inform people of impending threats. The students’ narratives also showed optimism around future jobs and graduate school, as well as an exploration of their identity through finding their passion in this career path. This study is an interesting initial delve into narratively analyzing stories from emerging meteorologists.

Full access
Hong-Li Ren
,
Yuntao Wei
, and
Shuo Zhao

Abstract

The real-time multivariate Madden-Julian Oscillation (MJO) (RMM) index has now been widely applied as a standard in operational sub-seasonal prediction and monitoring. Its calculation procedures involve the extraction of major intraseasonal variability (ISV) by subtracting the prior 120-day mean. However, this study uncovers that such a real-time strategy artificially creates unwanted low-frequency variability (LFVartificial) that might cause non-negligible influences on the RMM amplitude and phase. Compared to the real LFV, the LFVartificial explains more (~70% in boreal summer) of the residual LFV (LFVresidual) in the RMM index. It occupies 33% of all days that the LFVresidual explains more than one-half of total RMM amplitude, 19% that the LFV contribution exceeds ISV, and 10% that the LFVartificial-associated RMM amplitude surpasses 0.8. The RMM-defined “MJO” is obscured by the LFVresidual in such a way that the eastward-propagating mode is stronger and bigger with a slower phase speed, as compared with the “true” MJO derived from the 20–100-day filtered data. The interference effects of LFVresidual on the MJO might be particularly strong when the background state is changing rapidly with time. However, these issues can be well avoided when one chooses to remove the centered 120-day mean, as evidenced by the largely reduced three percentages (17%, 8%, and 1%) mentioned above in the so-derived index. These results give us a reminder that more attention should be paid to monitoring or predicting an MJO using the RMM index in a rapidly changing low-frequency background or the boreal summer.

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Martin Janssens
,
Jordi Vilà-Guerau de Arellano
,
Chiel C. van Heerwaarden
,
Stephan R. de Roode
,
A. Pier Siebesma
, and
Franziska Glassmeier

Abstract

Condensation in cumulus clouds plays a key role in structuring the mean, non-precipitating trade-wind boundary layer. Here, we summarise how this role also explains the spontaneous growth of mesoscale (> О(10) km) fluctuations in clouds and moisture around the mean state in a minimal-physics, large-eddy simulation of the undisturbed period during BOMEX on a large (О(100) km) domain. Small, spatial anomalies in latent heating in cumulus clouds, which form on top of small moisture fluctuations, give rise to circulations that transport moisture, but not heat, from dry to moist regions, and thus reinforce the latent heating anomaly. We frame this positive feedback as a linear instability in mesoscale moisture fluctuations, whose time scale depends only on i) a vertical velocity scale and ii) the mean environment’s vertical structure. In our minimal-physics setting, we show both ingredients are provided by the shallow cumulus convection itself: It is intrinsically unstable to length scale growth. The upshot is that energy released by clouds at kilometre scales may play a more profound and direct role in shaping the mesoscale trade-wind environment than is generally appreciated, motivating further research into the mechanism’s relevance.

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Rosimar Rios-Berrios
,
Naoko Sakaeda
,
Héctor J. Jimenez-González
,
Angelie Nieves-Jimenez
,
Yidiana Zayas
,
Elinor Martin
,
Shun-Nan Wu
,
Cameron R. Homeyer
, and
Ernesto Rodríguez

Abstract

The diurnal cycle of coastal rainfall over western Puerto Rico was studied with high-frequency radiosondes launched by undergraduate students at the University of Puerto Rico at Mayagüez (UPRM). Thirty radiosondes were launched during a three-week period as part of NASA’s Convective Processes Experiment—Aerosols and Winds (CPEX-AW) field project. The objective of the radiosonde launches over Puerto Rico was to understand the evolution of coastal convective systems that are often challenging to predict. Four different events were sampled: (1) a short-lived rainfall event during a Saharan-air dust outbreak, (2) a two-day period of limited rainfall activity under northeasterly wind conditions, (3) a two-day period of heavy rainfall over land, and (4) a two-day period of long-lived rainfall events that initiated over land and propagated offshore during the evening hours. The radiosondes captured the sea-breeze onset during the mid-morning hours, an erosion of lower-tropospheric inversions, and substantial differences in column humidity between the four events. All radiosondes were launched by volunteer undergraduate students who were able to participate in-person, while the coordination was done virtually with lead scientists located in Puerto Rico, Oklahoma, and St. Croix. Overall, this initiative highlighted the importance of student-scientist collaboration in collecting critical observations to better understand complex atmospheric processes.

Full access
Xiaomin Chen
,
Andrew Hazelton
,
Frank D. Marks
,
Ghassan J. Alaka Jr
, and
Chunxi Zhang

Abstract

Continuous development and evaluation of planetary boundary layer (PBL) parameterizations in hurricane conditions are crucial for improving tropical cyclone (TC) forecasts. A turbulence kinetic energy (TKE)-based eddy-diffusivity mass-flux (EDMF-TKE) PBL scheme, implemented in NOAA’s Hurricane Analysis and Forecast System (HAFS), was recently improved in hurricane conditions using large-eddy simulations. This study evaluates the performance of HAFS TC forecasts with the original (experiment HAFA) and modified EDMF-TKE (experiment HAFY) based on a large sample of cases during the 2021 North Atlantic hurricane season. Results indicate that intensity and structure forecast skill was better overall in HAFY than in HAFA, including during rapid intensification. Composite analyses demonstrate that HAFY produces shallower and stronger boundary layer inflow, especially within 1–3 times the radius of maximum wind (RMW). Stronger inflow and more moisture in the boundary layer contribute to stronger moisture convergence near the RMW. These boundary layer characteristics are consistent with stronger, deeper, and more compact TC vortices in HAFY than in HAFA. Nevertheless, track skill in HAFY is slightly reduced, which is in part attributable to the cross-track error from a few early cycles of Hurricane Henri that exhibited ~400 n mi track error at longer lead times. Sensitivity experiments based on HAFY demonstrate that turning off cumulus schemes notably reduces the track errors of Henri while turning off the deep cumulus scheme reduces the intensity errors. This finding hints at the necessity of unifying the mass fluxes in PBL and cumulus schemes in future model physics development.

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