Squall‐line initiation over the northern coast of Brazil in March: Observational features

Oliveira, Fernando Pereira de; Oyama, Marcos Daisuke

doi:10.1002/met.1799

Cited by 10 publications

(8 citation statements)

References 34 publications

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“…Since R6 has a large coastal strip, sea breezes in the region are frequent [1]. Under these conditions, the sea breeze transports moisture to the R6 inland, which interacts with the trade winds producing squall lines that enter the continent [1,[215][216][217]. Squall lines are MCSs that begin their formation north of the R6 in the late afternoon or early evening when convective cells agglomerate, forming a linear band of clouds parallel to the coast [216].…”

Section: Cluster 5-region 5 (R5)mentioning

confidence: 99%

“…Under these conditions, the sea breeze transports moisture to the R6 inland, which interacts with the trade winds producing squall lines that enter the continent [1,[215][216][217]. Squall lines are MCSs that begin their formation north of the R6 in the late afternoon or early evening when convective cells agglomerate, forming a linear band of clouds parallel to the coast [216]. Squall lines occur all year round but have a maximum frequency in the autumn when ITCZ reaches its southernmost position, directly affecting the instability conditions in the northern R6 [216].…”

Section: Cluster 5-region 5 (R5)mentioning

confidence: 99%

“…Squall lines are MCSs that begin their formation north of the R6 in the late afternoon or early evening when convective cells agglomerate, forming a linear band of clouds parallel to the coast [216]. Squall lines occur all year round but have a maximum frequency in the autumn when ITCZ reaches its southernmost position, directly affecting the instability conditions in the northern R6 [216]. In general, squall lines can contribute up to 45% of the precipitation during the rainy season in eastern Pará state (northern sector of the R6) [203].…”

Section: Cluster 5-region 5 (R5)mentioning

confidence: 99%

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A New Look into the South America Precipitation Regimes: Observation and Forecast

Ferreira

Reboita

2022

Atmosphere

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South America is a vast continent characterized by diverse atmospheric phenomena and climate regimes. In this context, seasonal climate predictions are helpful for decision-making in several relevant socioeconomic segments in this territory, such as agriculture and energy generation. Thus, the present work evaluates the performance of ECMWF-SEAS5 in simulating the South American precipitation regimes by applying a non-hierarchical clustering technique. In addition, the study describes the main atmospheric systems that cause precipitation in each cluster and updates a previous work performed in South America in 2010. As a result, ECMWF-SEAS5 simulates (with good correspondence) the eight climate regimes identified in the analysis of precipitation from the Climate Prediction Center (CPC). Moreover, ECMWF-SEAS5 has a satisfactory ability in representing the rainfall regime in low and medium climate predictability regions, such as central and southern South America. ECMWF-SEAS5 has good performance in the climate characterization of South America and it gives us confidence in using its seasonal climate predictions throughout the continent.

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Section: Cluster 5-region 5 (R5)mentioning

confidence: 99%

Section: Cluster 5-region 5 (R5)mentioning

confidence: 99%

Section: Cluster 5-region 5 (R5)mentioning

confidence: 99%

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A New Look into the South America Precipitation Regimes: Observation and Forecast

Ferreira

Reboita

2022

Atmosphere

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“…The variability of precipitation in NEB is influenced by the different systems which occur in the region, such as the Intertropical Convergence Zone (ITCZ; Uvo, 1989;Utida et al, 2019); South Atlantic Convergence Zone (SACZ; Kodama, 1992;Zilli et al, 2019); Easterly Wave Disturbances (EWD; Torres and Ferreira, 2011;Gomes et al, 2019); Upper Tropospheric Cyclonic Vortex (Kousky and Gan, 1981;Fedorova et al, 2016) and Squall Lines (Kousky, 1980;Oliveira and Oyama, 2019). In addition, it is influenced by the interannual variability of Pacific Ocean temperature, associated with the El Niño Southern Oscillation (Ropelewski and Halpert, 1987;Marengo et al, 2017), and to the interannual variability of Atlantic Ocean temperatures (Bombardi et al, 2014;Rodrigues et al, 2015).…”

Section: Study Areamentioning

confidence: 99%

Spatial distribution of the level of return of extreme precipitation events in Northeast Brazil

Rodrigues

Gonçalves

Spyrides

et al. 2020

Intl Journal of Climatology

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This study aimed to estimate levels of return of extreme daily precipitation events, associating them with natural disasters in Northeast Brazil (NEB), a region characterized by different climatic conditions and low rates of social and economic development. For this, generalized Pareto distribution (GPD) models were adjusted to the daily extreme precipitation data estimated by the Tropical Rainfall Measuring Mission (TRMM) 3B42 product of the multisatellite precipitation analysis for a period of 16 years (2000-2015). In addition, the estimates of the GPD model were compared using two data sources, TRMM and pluviometer. The investigation showed that the results of the GPD model estimated by means of the extreme data from the rain gauge and the TRMM were statistically the same, with 95% confidence. Thus, using the data referring to the 2,082 grid points of the TRMM, it was possible to map the spatial distribution of the estimates of the levels of return of extreme precipitation to the return periods of 2, 5 and 10 years, per seasonal period. In general, the results indicated that the intensity of expected extreme precipitation depends on the seasonal period and the place of occurrence of precipitation. The eastern NEB stood out as the region where the highest intensities of extreme precipitation are expected. Extreme precipitation values of up to 178 mm are expected in 2 years. The areas where natural disasters occurred in the years 2016, 2017 and 2018 are similar to those in which the highest rainfall intensities are expected. The results of this study can allow the evaluation of the spatial distribution of risks related to extreme precipitation events, and therefore, support the planning of regional public policies and environmental management for the prevention of natural disasters in NEB. K E Y W O R D S diaries precipitation, generalized Pareto distribution, natural disaster, TRMM 1 | INTRODUCTION Extreme weather events are one of the main topics studied related to climate change. Future projections released by the Intergovernmental Panel on Climate Change (IPCC) show that these events will become increasingly frequent and intense in several regions of the world, including in areas of Northeast Brazil (NEB; Du et al., 2019). Extreme weather events can cause waves of heat and cold, floods, landslides, droughts and more.

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“…Later, French and Parker (2012) focused on 21 MFBE cases in North America from 2006 to 2010, and the analyses showed that the merged bow echoes normally produced more severe weather than the nonmerged ones. Oliveira and Oyama (2020) demonstrated squall line formation over the northern coast of Brazil and pointed out that the convective merging process was responsible for the long‐lasting and more intense convective systems, and the moisture at 700 hPa was crucial for system evolution.…”

Section: Introductionmentioning

confidence: 99%

A Climatological Study on the Two Types of Bow Echoes Over South China

Zhou,

Zhao,

et al. 2023

JGR Atmospheres

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Classical bow echoes (CBEs) normally develop due to rear‐inflow jets, while merger‐formation bow echoes (MFBEs) evolve from the merger between linear systems and preline convection. MFBEs are rarely documented before, and the key processes remain unclear because of the small‐scale and fast‐evolving merging processes. Using radar observations during 2015–2019, this study examines the characteristics of these two types of bow echoes over South China. Eighteen MFBEs and 11 CBEs are identified, accounting for 62% and 38% of the total 29 bow echoes, respectively. MFBEs commonly occur over coastal regions in the afternoon, where southerly sea breezes provide favorable thermodynamic conditions. About half CBEs develop over mountainous areas in the morning, and northerly winds enhance the local baroclinity and kinematic convergence. A new Merger‐Classical index is proposed to distinguish the environments for the development of two types of bow echoes, disclosing the more favorable near‐surface thermal conditions for MFBEs. In addition, more severe weather occurs in metropolitan area near the Pearl River Delta region during MFBEs, in which the accumulated precipitation is about 2.5 times higher than that during CBEs. This study reveals the discrepancies between MFBEs and CBEs over South China, emphasizing the MFBEs account for more than half of the total bow echoes and cause more high‐impact weather in the metropolitan area. This study proposes a new perspective on the environment in which bow echo forms by merger process over South China, urging for more research to explore the underlying processes.

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Squall‐line initiation over the northern coast of Brazil in March: Observational features

Cited by 10 publications

References 34 publications

A New Look into the South America Precipitation Regimes: Observation and Forecast

A New Look into the South America Precipitation Regimes: Observation and Forecast

Spatial distribution of the level of return of extreme precipitation events in Northeast Brazil

A Climatological Study on the Two Types of Bow Echoes Over South China

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