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Severe Weather Events over Southeastern Brazil during the 2016 Dry Season

Severe Weather Events over Southeastern Brazil during the 2016 Dry Season Hindawi Advances in Meteorology Volume 2018, Article ID 4878503, 15 pages https://doi.org/10.1155/2018/4878503 Research Article Severe Weather Events over Southeastern Brazil during the 2016 Dry Season 1 1 1 Amanda Rehbein, L´ıvia Ma ´ rcia Mosso Dutra, Tercio Ambrizzi , 1 2 Rosmeri Porfı ´rio da Rocha, Michelle Simões Reboita, 3 4 Gyrlene Aparecida Mendes da Silva , Luiz Felippe Gozzo, 1 1 Ana Carolina No ´ bile Tomaziello, Jose ´ Leandro Pereira Silveira Campos, 1 1 1 Victor Raul Chavez Mayta, Nata ´ lia Machado Crespo, Paola Gimenes Bueno , 1 1 1 Vannia Jaqueline Aliaga Nestares, La´ıs Tabosa Machado, Eduardo Marcos De Jesus, 5 4 6 Luana Albertani Pampuch, Maria de Souza Custo ´ dio, and Camila Bertoletti Carpenedo Departamento de Ciˆencias Atmosf´ericas, Instituto de Astronomia, Geof´ısica e Cieˆncias Atmosfe´ricas da Universidade de São Paulo, São Paulo, SP, Brazil Instituto de Recursos Naturais da Universidade Federal de Itajuba´, Itajuba´, MG, Brazil Departamento de Ciˆencias do Mar da Universidade Federal de São Paulo, São Paulo, SP, Brazil Departamento de F´ısica da Universidade Estadual Paulista Ju´lio de Mesquita Filho, Campus de Bauru, SP, Brazil Instituto de Ciˆencia e Tecnologia da Universidade Estadual Paulista Ju´lio de Mesquita Filho, Campus de São Jos´e dos Campos, São Paulo, SP, Brazil Instituto de Geografia da Universidade Federal de Uberlaˆndia, Uberlaˆndia, MG, Brazil Correspondence should be addressed to Tercio Ambrizzi; ambrizzi@model.iag.usp.br Received 27 December 2017; Revised 3 April 2018; Accepted 18 April 2018; Published 10 June 2018 Academic Editor: Anthony R. Lupo Copyright © 2018 Amanda Rehbein et al. 'is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Southeastern Brazil is the most populated and economically developed region of this country. Its climate consists of two distinct seasons: the dry season, extending from April to September, the precipitation is significantly reduced in comparison to that of the wet season, which extends from October to March. However, during nine days of the 2016 dry season, successive convective systems were associated with atypical precipitation events, tornadoes and at least one microburst over the southern part of this region. 'ese events led to flooding, damages to buildings, shortages of electricity and water in several places, many injuries, and two documented deaths. 'e present study investigates the synoptic and dynamical features related to these anomalous events. 'e convective systems were embedded in an unstable environment with intense low-level jet flow and strong wind shear and were supported by a sequence of extratropical cyclones occurring over the Southwest Atlantic Ocean. 'ese features were intensified by the Madden–Julian oscillation (MJO) in its phase 8 and by intense negative values of the Pacific South America (PSA) 2 mode. summer (Dec-Jan-Feb), there is a predominance of intense 1. Introduction convective precipitation due to the availability of plentiful Climate and weather components that affect directly the heat and moisture over the tropical region [3]. 'is intense population and economy of Southeastern Brazil [1, 2] have convective precipitation delineates a cloud corridor known as been widely studied in recent years, as well as the large-scale the South Atlantic Convergence Zone (SACZ), which extends forcings from tropical and extratropical origins. It is well from the southwest Amazon Basin and through Southeast known that the climate of Southeastern Brazil is influenced Brazil, reaching the Atlantic Ocean [4]. From the beginning of by the South America monsoon system, where during the autumn until midspring, the frequency of SACZ episodes 2 Advances in Meteorology decreases, initiating the dry period over Southeastern Brazil Precipitation (mm) and 850 hPa wind (m/s) anomaly 30/May/2016 – 07/Jun/2016 Climatology: 1981–2010 [5]. Moreover, it is during this period that the South Atlantic 5N Subtropical Anticyclone (SASA) reaches its most westerly position, extending over Southeastern Brazil, which impedes the passage of frontal systems [6]. �erefore, during this EQ period, the precipitation events are normally quick, isolated, and not intense. 5S During the dry season of 2016, there were 9 consecutive atypical days (May 30 to June 07, 2016) with thunderstorms, tornadoes, and at least one microburst over Southeastern 10S Brazil. �ese phenomena caused ˆoods, smashed houses, personal injuries, and two documented deaths (http:// 15S g1.globo.com/sao-paulo/sorocaba-jundiai/noticia/2016/06/ meteorologistas-analisam-se-tornado-causou-destruicao- em-jarinu.html and http://www.saoroquenoticias.com.br/ 20S noticia.asp?idnoticia16053). �ese atypical weather events a‘ected mainly the southern part of Southeastern Brazil, with 25S the most severe conditions occurring over the cities of Campinas, Jarinu, and São Roque, which are close to city of São Paulo in São Paulo State. In Campinas, a probable mi- 30S croburst occurred on June 05 between 00:00 and 00:30 Local Time (LT; Rachel Ifanger Albrecht, personal communication, 35S 2016). At Jarinu on June 05 at about 21 LT and at São Roque 75W 70W 65W 60W 55W 50W 45W 40W 35W 30W on June 06 in the late afternoon, the occurrences of tornadoes were conšrmed by analysis of damage by local meteorological –150 –100 –50 –25 0 25 50 100 150 institutes and civil defense, besides being observed in the meteorological radar data (Rachel Ifanger Albrecht, personal 10 m/s communication, 2018). Precipitation anomalies from May 30 to Figure 1: Precipitation anomalies (mm) and 850 hPa wind com- June 07 reached values of around 200 mm in Southeastern −1 posite (m·s ) for May 30 to June 07, 2016. �e blue (brown) colors Brazil, in a region comprising São Paulo State and parts of other indicate the positive (negative) rain anomalies, and the red box surrounding states (Figure 1). For instance, at the meteoro- indicates the area of study. �e anomalies were calculated using the logical station of the Institute of Astronomy, Geophysics 30-year period, 1981 to 2010. and Atmospheric Science of the University of Sao Paulo (IAG/USP), located in the southern part of the city of São Paulo, the climatological precipitation for the period of 1981 to 2010 is reanalysis [7] from the European Centre for Medium-Range 55.5 mm for the entire month of June. In the šrst 7 days of June Weather Forecasts (ECMWF). �ese data are available every 2016, at this station, the total precipitation was 175.4 mm (316% six hours (0000, 0006, 1200, and 1800 UTC) with spatial of the climatological value for the entire month). resolution of 0.75 , for various pressure levels [7]. We an- �e aims of the present study are (a) to investigate the alyzed the synoptic šelds at low, middle, and upper levels at dynamic forcings associated with those severe weather and each available time; however, for brevity, only the 1200 UTC extreme rainfall events over Southeastern Brazil in the dry šelds are presented here. season of 2016 and (b) to verify whether or not the most- Infrared satellite images (about 10.7 μm) with 4 km and 30 used forecast models in Brazil predicted this period of in- minutes of spatial and temporal resolution, respectively, are tense precipitation. �e datasets and methodology used are from the Geostationary Operational Environmental Satellite described in Section 2; Section 3 presents the synoptic (GOES-13; Janowiak et al. [8]) and were made available by discussion, low-frequency analysis, and the model forecasts the CPC/NCEP/NWS (Climate Prediction Center/National results; and the concluding remarks are given in Section 4. Centers for Environmental Prediction/National Weather Service) via ftp://ftp.cpc.ncep.noaa.gov/precip/global_full_ res_IR/. 2. Data and Methods Five thermodynamic indices (Convective Available Po- tential Energy—CAPE, Convective Inhibition—CIN, K index, �e period of analysis is May 30 to June 07, 2016, and Total Totals—TT, and Showalter) are used to characterize the the region of interest covers the area between latitudes 25 S ° ° ° environmental instability. Moreover, two kinematic indices to 19 S and longitudes 53 W to 42 W (red box in Figure 1), (sweat and vertical shear of horizontal wind—here termed where the most intense precipitation and severe weather “wind shear”) are also presented because when their values are events were registered. strong, the environment is favorable to severe weather events [9, 10] and to the formation of stronger convective supercells 2.1. Synoptic and ermodynamic Analysis. �e synoptic [11]. �e instability and kinematic indices were obtained for ° ° šelds were constructed using data from the ERA-Interim a point (23 S/47 W) representative of the severe storm Advances in Meteorology 3 convection) over tropical South America, is shown in Fig- sites—Campinas, Jarinu, and São Roque. 'is point is located less than 60 km from these sites. In the literature, a distance of ure 8. RMM amplitude in phase 8 reaches its maximum value at “day 0,” which means that the association between rainfall up to 180 km is used for the representativeness of such surveys [12, 13]. 'e Convective Available Potential Energy (CAPE) anomalies and MJO passage over Southeastern Brazil was and Convective Inhibition (CIN) were obtained from the strong. Global Forecast System (GFS) model analysis with spatial 'e PSA modes are teleconnection patterns extending resolution of 0.5 and available for 0000, 0600, 1200, and 1800 poleward and eastward over the Pacific Ocean [31], mod- UTC. 'e K index [14], Total Totals (TT; Miller [15]), ulating the circulation and precipitation anomalies over Showalter [16], wind shear, and Sweat index were calculated South America [32]. PSA teleconnection patterns consist of using the GFS analysis data. 'e Sweat index is adapted from two distinct modes: PSA 1, related to the El Niño Southern Miller [15] to Southern Hemisphere wind conditions fol- Oscillation (ENSO; Karoly [31]) and PSA 2, associated with the MJO during the winter [18]. Both of them have impacts lowing Nascimento [10]. on the climate of South America, and consequently on the rainfall intensity and distribution over São Paulo state. 'e 2.2. Climate Analysis. 'e weather and climate in South PSA modes are defined as the first and second leading ro- America are influenced by relatively well-known telecon- tated principal component modes of the 200 hPa stream nection patterns of tropical and extratropical origins that we function anomaly, respectively [18, 32]; these patterns are can observe and measure through indices and statistical also presented in other time scales such as pentads and annual analysis. In this study, we investigated the influence of the [32–34]. In this study, both PSA modes were computed using most important atmospheric and oceanic phenomena that can ERA-Interim reanalysis for the 200 hPa pentad stream affect the weather over the Southeastern Brazil: Madden Julian function anomaly data. 'e covariance matrix was obtained Oscillation [17], Pacific South America pattern, first and through the extraction of the annual cycle computed with the climatology of 1981–2010 as a basis period. second modes [18, 19]; Indian Ocean Dipole (IOD; [20–22]); Southern Annular Mode [23]; and blocking events [24, 25]. Saji et al. [35] showed that the anomalous warming of the tropical Indian Ocean due to low level evaporation can lead 'e MJO is triggered in the Indian and Pacific Oceans and propagates eastward over the tropical region with to divergence in the upper troposphere, sourcing Rossby a cycle of about 30 to 60 days [26]. During its propagation, wave trains propagating from the Indo-Pacific region to- it comprises regions with enhanced and suppressed con- wards the South Atlantic Ocean in an arch-like trajectory. vection. In São Paulo, the most favorable conditions for Taschetto and Ambrizzi [22] showed that anomalous convection occur with suppression of convection over warming throughout the Indian Ocean Basin can excite Indonesia, when the MJO is in its phases 8 and 1, as shown Rossby wave trains moving towards the South Atlantic, and also amplifying El Niño patterns in the precipitation over the by Jones and Carvalho [17]. Here, to better understand the influence on the extreme rainfall variability over South- South American continent, for the austral autumn season (March–May). In order to explore the effects of the Indian eastern Brazil by the eastward-propagating MJO-related large-scale convective and circulation envelope, we have Ocean on South American precipitation, the Indian Ocean Dipole (IOD; Saji et al. [36]; Webster et al. [37]), that is, the constructed lagged/lead composites for the 0.21 sigma-level (approximately 200 hPa) velocity potential and outgoing difference between the Eastern and Western Basin sea longwave radiation (OLR) anomalies. surface temperature anomaly (SSTa), is computed through 'e velocity potential was obtained from National the extraction of the annual cycle based on the 1981–2010 Centers for Environmental Prediction/National Center for climatology, for 36 years (1980–2016) of ERA-Interim data. Atmospheric Research (NCEP/NCAR; Kalnay et al. [27]) 'e SAM, also known as Antarctic Oscillation (AAO), is and the OLR field from the High Resolution Infrared Ra- the main mode of extratropical circulation variability in the Southern Hemisphere. It consists of zonally symmetric diation Sounder (HIRS; Lee et al. [28]). Daily anomalies of OLR and velocity potential were calculated at every grid structures, with geopotential height perturbations of op- posing signs in Antarctica and in the surrounding zonal ring point by subtracting the long-term average (1979–2015) in order to remove the seasonal cycle. 'e intraseasonal signals centered near 45 latitude [38]. Reboita et al. [23] observed are isolated from the OLR daily anomalies by applying that during negative SAM phases, the cyclone trajectories Lanczos bandpass filter [29] using cutoff frequencies at 20 are northward of their positions during the positive phase, and 96 days. To assemble the composites, we considered the and in the South America and South Atlantic sectors, there Wheeler and Hendon [30] real-time multivariate MJO is intense frontogenetic activity and a positive precipita- (RMM) index for our period of analysis. 'is index is tion anomaly over southeastern South America, which in- available at the Centre for Australian Weather and Climate fluences the weather in São Paulo. To monitor SAM, we used Research website (see: http://www.bom.gov.au/climate/mjo/) the daily AAO index available on the Climate Prediction and is based on a pair of empirical orthogonal functions Center/National Oceanic and Atmospheric Administra- (EOFs) of the combined fields of near-equator averaged tion (CPC/NOAA) website (http://www.cpc.ncep.noaa.gov/ 850 hPa zonal wind, 200 hPa zonal wind, and satellite- products/precip/CWlink/daily_ao_index/aao/aao.shtml). observed outgoing longwave radiation (OLR) data [30]. 'is index is constructed using 700 hPa geopotential height 'e evolution of these anomalies from “day−12” to “day +9”, anomalies projected onto the leading EOF mode [39]. To where “day 0” represents the active phase (enhanced define the phase of the SAM, we use a methodology similar 4 Advances in Meteorology 15S 15S 15S 15S 20S 20S 20S 20S 25S 25S 25S 25S 30S 30S 30S 30S 60W 50W 40W 60W 50W 40W 60W 50W 40W 60W 50W 40W (a) (b) (c) (d) 15S 15S 15S 15S 20S 20S 20S 20S 25S 25S 25S 25S 30S 30S 30S 30S 60W 50W 40W 60W 50W 40W 60W 50W 40W 60W 50W 40W (e) (f) (g) (h) Figure 2: GOES-13 enhanced infrared images on June 04, 2016, at (a) 1200 UTC, (b) 1500 UTC, (c) 1800 UTC, and (d) 2100 UTC; and on June 05, 2016, at (e) 0000 UTC, (f) 0300 UTC, (g) 0600 UTC, and (h) 0900 UTC. to Reboita et al. [23], in which values above (below) one America (including northern/northeastern Brazil; Grimm standard deviation indicate the positive (negative) phase. and Ambrizzi [46]; da Rocha et al. [47]). Given its location, �e standard deviation value of the daily SAM time series the SP region is considered to be a transition region where from 1979 to 2015 is equal to 1.4, and thus values between the e‘ect of ENSO could be either to increase or reduce ±1.4 indicate the neutral phase. precipitation [48]. Atmospheric blocking episodes are due to quasi- stationary planetary waves of large amplitude [40], persist- 3. Results and Discussions ing from days to a few weeks, leading to episodes of prolonged extreme weather conditions over some areas. Over the 3.1. Synoptic Analysis. A rainfall anomaly averaging 47 mm Southeastern Pacišc, Southern Atlantic and Oceania, the low- occurred over the SP region (red box in Figure 1) during the pressure anomalies occurring on the equatorial ˆank of the period May 30 to June 07, 2016. Figure 1 shows that in specišc blocking pattern favor the development of transient systems regions, rainfall anomalies reached more than 100 mm over that may cause precipitation as they move eastward (Mendes these 9 days. �e satellite images show convective systems et al. [41]). �e resulting impacts on temperature and pre- forming in the western SP region and moving eastward cipitation are most frequently observed over Southern Brazil, throughout their life cycle (see, e.g., Figure 2). In addition, but they can also inˆuence our region of interest (South- some convective systems were generated northwest of the SP eastern Brazil; Mendes et al. [41]). In the latter case, Mendes region propagating along the low-level mean ˆow and et al. [41] observed that southeastern Pacišc blocking has growing as they moved into the region. Each system had its higher impact on precipitation in austral summer and spring own lifetime, starting, and developing preferentially during (wet season), while the Atlantic blocking a‘ects precipitation early afternoon (1200 to 1500 LT). Figure 1 also shows that the in austral autumn and winter (dry season). predominant wind at 850 hPa ˆowed from the southern For the identišcation of blocking events over the Amazon Basin into the SP region. �is is the same as the Southern Hemisphere, we used the objective method of conšguration observed by Morales et al. [49] on days with Tibaldi et al. [42], modišed from Lejeñas [43]. �is method thunderstorms in the city of São Paulo. was adapted to a smaller horizontal spacing of the ERA- Figures 3(a)–3(d) show vertical prošles of horizontal ° ° Interim reanalysis (1.5 ×1.5 of horizontal resolution) in- temperature advection, divergence of the horizontal wind, ° ° stead of 3.75 × 3.75 used by Tibaldi et al. [42] and stratišed pressure vertical velocity (omega), and moisture conver- into šve bands of latitudes, according to Oliveira et al. [25]. gence averaged over the SP region, from May 30 to June 07, For an episode to be characterized as a blocking event, it 2016, every 6 hours. Overall, warm-air advection occurred at all levels of the troposphere, peaking on June 05 (Figure 3(a)) must persist for at least 3 days [25, 44, 45]. �e ENSO signal was not evaluated in this work because when two of the most severe events were reported (mi- the São Paulo (SP) region is located in between the two croburst at Campinas, SP, and tornado at Jarinu, SP). �is sectors of South America in El Niño (EN), and La Niña (LN) warm advection contributes to increased instability over the episodes usually a‘ect the observed precipitation with op- SP region and is associated with a northerly mean ˆow, as posing contributions. For instance, during EN conditions, further discussed in this section. On June 07, the last day of there is increased precipitation over the southeastern sector the observed anomalous precipitation over the SP region, of South America (including Southern Brazil) and reduced intense cold advection occurred in the lower troposphere precipitation over the northern/northeastern sector of South (Figure 3(a)), associated with a change in the direction of the Advances in Meteorology 5 –1 –3 –5 30 May 31 May 1 Jun 2 Jun 3 Jun 4 Jun 5 Jun 6 Jun 7 Jun (a) 0.6 0.2 –0.2 –0.6 –1 30 May 31 May 1 Jun 2 Jun 3 Jun 4 Jun 5 Jun 6 Jun 7 Jun (b) 0.25 0.15 0.05 –0.05 –0.15 –0.25 30 May 31 May 1 Jun 2 Jun 3 Jun 4 Jun 5 Jun 6 Jun 7 Jun (c) –2 –6 –10 30 May 31 May 1 Jun 2 Jun 3 Jun 4 Jun 5 Jun 6 Jun 7 Jun (d) −1 −5 −1 Figure 3: Vertical prošles of (a) horizontal temperature advection (K·day ), (b) divergence of the horizontal wind (10 ·s ), (c) pressure −1 −5 −1 −1 vertical velocity (or omega; Pa·s ), and (d) moisture divergence (10 ·g·kg ·s ) averaged over the SP region, from May 30 to June 07, 2016, every 6 hours. mean ˆow over the region at these levels. Convergence in the which comes from tropical latitudes over the south Amazon lower troposphere and divergence in the upper troposphere Basin towards the subtropics, exiting over the SP region. �is occurred during all days analyzed (Figure 3(b)), favoring SALLJ developed around 0600 UTC on May 30 (not shown) upward motion over the SP region (Figure 3(c)). At lower and was sustained until 0000 UTC on 07 June. It can be seen and middle levels (up to 600 hPa), moisture convergence as a northwesterly band of maximum wind intensity at 850 hPa in association with a poleward transport of warm and occurred on all days (except June 07; Figure 3(d)), indicating favorable conditions for the formation of convective systems moist air (Figure 4). Commonly, days with thunderstorms in the SP region. �e general pattern described above was the over the city of São Paulo (about 100 km away from where the reverse of that of the week prior to May 30 and after June 07 severe events occurred) are accompanied by strong northerly (not shown), when there was no anomalous precipitation winds [49]. over the SP region. �e SALLJs are observed throughout the year but are �e lower-level moisture convergence and warm-air more frequent and intense during the warm season (NDJF) advection over the SP region occurred in association with when the northeast trade winds in the equatorial western the South American low-level jet (SALLJ) (east of the Andes), Atlantic ˆow towards the Amazon Basin [50]. �e trade 6 Advances in Meteorology EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (a) (b) (c) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (d) (e) (f ) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (g) (h) (i) –15 –12 –9 –6 –3 –1.5 1.5 3 6 9 12 15 20 (m/s) −1 −5 −1 −1 Figure 4: Horizontal temperature advection (shaded; K·day ), moisture ˆux convergence (purple contours every 10 ×10 g·kg ·s −5 −5 −1 −1 −1 from 5 ×10 to 55 ×10 g·kg ·s ), and horizontal wind (vectors; m·s ) at 850 hPa at 1200 UTC on (a) 30 May, (b) 31 May, (c) 01 June, (d) 02 June, (e) 03 June, (f) 04 June, (g) 05 June, (h) 06 June, and (i) 07 June, 2016. Advances in Meteorology 7 winds are deflected toward the southeast as they approach streams on those days (Figure (6)). 'e Sweat index in- the mountain barriers and then converge with the flow from creased from May 30 to June 6; however, it did not reach the western branch of the South Atlantic Subtropical High the thresholds for the development of severe storms in the (SASH), producing strong wind speeds at low levels and United States (above 300; Figure 7(g)). Other studies in convective development over the exit region of the jet (see, Brazil have also found that some thermodynamic and ki- conceptual model presented in Marengo et al. [51] and their nematic indices are indicative of the instability of a given Figure 1). 'is exit region is located typically over Southern region; however, they may not reach established thresholds Brazil-Northern Argentina as described in Marengo et al. of severity even when severe weather occurs [53, 54]. [51]. During May 30 to June 06, 2016, however, the SALLJ was active northeastward of its typical position, such that its 3.2. Low-Frequency Analysis. 'e following analysis and exit was located over the SP region instead of Southern Brazil discussions cover the contribution of climate indices (Figure 4). 'is displacement in the jet direction was likely (Table 1) and planetary-scale influence on the severe rain driven by the intense extratropical cyclonic activity over the event studied in the present paper. Atlantic Ocean adjacent to the South American coast during the days analyzed (Figure 5). 'is activity consisted of two main extratropical cyclones plus three secondary cyclones 3.2.1. 5e Influence of the Madden–Julian Oscillation. forming and acting along the southeastern coast of South Anomalous upper-level velocity divergence (represented by America. 'e cyclonic (clockwise) circulation predomi- negative velocity potential anomalies—dashed lines in nant over the southwestern Atlantic Oceanfavored the Figure 8—had been established over tropical South America blocking—by the northwesterly SALLJ—of the advection of by “day −9” (May 28) and persisted to “day +3” (June 09), cold and dry air from higher latitudes into eastern Argentina favoring upward motion mainly between “day−3” (June 03) and Southern Brazil (Figure 4). At 0000 UTC on June 07, and “day 0” (June 06), the period of the most intense rainfall a cold front finally penetrates the continent (figure not events over the state of Sao Paulo. 'us, the OLR pattern shown), reaching the southern Amazon region and weak- showed enhanced convection over southeastern South ening the SALLJ, by means of advection from a colder and America and the adjacent Atlantic Ocean toward the dryer air mass into the rear of the frontal zone (Figure 4(i)). southern Amazon basin, resembling the austral winter sit- 'ese persistent low-level patterns (Figures 4 and 5) all seem uation with the active MJO phase over South America to be unrelated to a persistent subtropical jet at high-levels (e.g., [55]). In addition, “day 0” was when the RMM reached (Figure 6). phase 8 and its amplitude began to increase. As pointed During the period of interest, atmospheric instability was out in previous studies (e.g., Jones and Carvalho 2012 calculated in terms of various thermodynamic (Figures 7(a)–7(e)) [17, 56, 57]), phase 8 and phase 1 favor convection over and kinematic (Figure 7(f) and 7(g)) indices. 'e K index tropical South America. Even though phase 1 favors con- indicates high probability (above 80%) of storm occurrence vection over tropical South America and the following days from 1200 UTC on May 31 to 0000 UTC on June 07 (except were in that phase, it was not sufficient to favor convection at 1200 UTC on June 02 and 03; Figure 7(a)). After this over the SP region because, as shown by the synoptic period, the K index decreased substantially. 'e Total analysis, and on June 07, the atmospheric environment over Totals index was high (above 46 C) during most of our this region began to stabilize, after the cold front passage, period of interest (Figure 7(b)), indicating some scattered with cold and dry air being advected from the south. storms. From 0000 UTC on June 04 to 1200 UTC on June Upper-level tropical convergence (represented by posi- 06, the warm air advection at middle levels was greater than tive velocity potential anomalies (Figure 8)) progresses on other days (Figure 3(a)), decreasing the values of the eastward from the western tropical Pacific from “day −12” Total Totals during this period. 'e Showalter index in- (May 25) and arrives in tropical South America by “day +9” dicated the possibility of storms, remaining most of the (June 15), indicating the end of the active MJO period over time below 1 C (Figure 7(c)). However, it did not match the tropical South America. It is noteworthy that the evolution thresholds for tornados (below −6 C) in the days in which of the MJO influence (onset-peak-demise) has a period of this phenomenon happened (June 05 and 06). 'is is approximately 10 days (from “day−6” to “day +3”), average possibly due to the strong midlevel warm advection over duration of the MJO passage over South America [58]. the SP region during these days (Figure 3(a)), which contributed to raising the temperature at 500 hPa. It is interesting to note that the CAPE was relatively low 3.2.2. Pacific South America Mode. 'e dominant mode (Figure 7(d)), CIN was relatively intense (Figure 7(e)), and of low-frequency climate variability for the last pentad of the wind shear was above the traditional threshold to favor May and first pentad of June 2016 was the PSA 2 mode, −1 rotating supercells (15 m·s ; Figure 7(f) [10]). 'e severe presenting negative values below 2 standard deviations weather observed during these days is the characteristic of (Table 1); this possibly results from a combination of ENSO the cold season, where there is usually low thermodynamic influence in the interannual band [31] and tropical con- convective potential but strong wind shear (an example of vection associated with the MJO in the intraseasonal band such a type of event in the United States is presented in [18]. 'is strongly negative value of PSA 2 during late May/early June 2016 likely contributed to the persistent Markowski and Straka [52]). 'e wind shear was high even after the period of interest because of the influence of the jet cyclogenetic activity over the Atlantic near the South 8 Advances in Meteorology EQ EQ EQ 10S 10S 10S 20S 20S 20S 1016 1016 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (a) (b) (c) EQ EQ EQ 10S 10S 10S 1020 1020 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (d) (e) (f ) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 1020 30S 1020 1024 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (g) (h) (i) –22 –18 –14 –10 –6 –2 Figure 5: Mean sea level pressure (black contours; hPa), geopotential height (red-dashed contours; gpm), and relative vorticity −5 −1 (shaded; 10 ·s ) at 850 hPa at 12 UTC on (a) 30 May, (b) 31 May, (c) 01 June, (d) 02 June, (e) 03 June, (f) 04 June, (g) 05 June, (h) 06 June, and (i) 07 June, 2016. Advances in Meteorology 9 EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 60W 40W 80W 60W 40W 80W 60W 40W (a) (b) (c) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 60W 40W 80W 60W 40W 80W 60W 40W (d) (e) (f ) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 60W 40W 80W 60W 40W 80W 60W 40W (g) (h) (i) 20 30 40 50 60 70 −1 Figure 6: 200 hPa streamlines and isotachs (shaded; m·s ) at 12 UTC on (a) 30 May, (b) 31 May, (c) 01 June, (d) 02 June, (e) 03 June, (f) 04 June, (g) 05 June, (h) 06 June, and (i) 07 June, 2016. 10 Advances in Meteorology 40 50 –20 (a) (b) –50 –100 –150 –200 –250 (c) (d) 250 20 (e) (f ) 20°S 21°S 22°S Campinas 23°S Jarinu São Roque 24°S 52°W 50°W 48°W 46°W 44°W (g) (h) 0000 UTC 1200 UTC ° ° Figure 7: Temporal evolution of the instability indices at 0000 UTC (red) and 1200 UTC (blue): (a) K index ( C), (b) Total Totals ( C), −1 −1 −1 (c) Showalter index ( C), (d) CAPE (J·kg ), (e) CIN (J·kg ), (f) Wind shear (m·s ), (g) Sweat index, and (h) Map of São Paulo state, with the location of where these indices were calculated (red dot) and the three cities where the most severe thunderstorms occurred (black crosses). �e shaded areas from (a) to (g) indicate the values for instability. –1 Showalter (°C) K index (°C) Sweat CAPE (J∙kg ) 25–May 25–May 25–May 25–May 26–May 26–May 26–May 26–May 27–May 27–May 27–May 27–May 28–May 28–May 28–May 28–May 29–May 29–May 29–May 29–May 30–May 30–May 30–May 30–May 31–May 31–May 31–May 31–May 01–Jun 01–Jun 01–Jun 01–Jun 02–Jun 02–Jun 02–Jun 02–Jun 03–Jun 03–Jun 03–Jun 03–Jun 04–Jun 04–Jun 04–Jun 04–Jun 05–Jun 05–Jun 05–Jun 05–Jun 06–Jun 06–Jun 06–Jun 06–Jun 07–Jun 07–Jun 07–Jun 07–Jun 08–Jun 08–Jun 08–Jun 08–Jun 09–Jun 09–Jun 09–Jun 09–Jun 10–Jun 10–Jun 10–Jun 10–Jun –1 CIN (J∙kg ) –1 Wind shear (m∙s ) Total Totals (°C) 25–May 25–May 25–May 26–May 26–May 26–May 27–May 27–May 27–May 28–May 28–May 28–May 29–May 29–May 29–May 30–May 30–May 30–May 31–May 31–May 31–May 01–Jun 01–Jun 01–Jun 02–Jun 02–Jun 02–Jun 03–Jun 03–Jun 03–Jun 04–Jun 04–Jun 04–Jun 05–Jun 05–Jun 05–Jun 06–Jun 06–Jun 06–Jun 07–Jun 07–Jun 07–Jun 08–Jun 08–Jun 08–Jun 09–Jun 09–Jun 09–Jun 10–Jun 10–Jun 10–Jun Advances in Meteorology 11 Table 1: Values of the climate indices analyzed. σ is the standard deviation. Index Values Period PSA 1 +4.0 June 01–05, 2016 PSA 2 −59.0 (−2.3σ) June 01–05, 2016 IOD −0.61 June 2016 AAO +1.759 May 30 to June 07, 2016 20°N 20°N EQ EQ 20°S 20°S 40°S 40°S 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° (a) (e) 20°N 20°N EQ EQ 20°S 20°S 40°S 40°S 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° (b) (f ) 20°N 20°N EQ EQ 20°S 20°S 40°S 40°S 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° (c) (g) 20°N 20°N EQ EQ 20°S 20°S 40°S 40°S 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° (d) (h) –50 –40 –30 –20 –10 0 10 20 30 40 50 −2 Figure 8: Lagged composite maps of šltered OLR anomaly (W·m ; shaded) and sigma-level 0.21 velocity potential (black contours every 6 2 −1 0.75 ×10 ·m ·s ; negative values are dashed) for a frequency band of 20 to 96 days. Composites are centered on day −12 to day +9 in which day 0 represents the most intense precipitation events over SP region (June 06). (a) Day −12 (May 25), (b) Day −9 (May 28), (c) Day −6 (May 31), (d) Day −3 (Jun 03), (e) Day 0 (Jun 06), (f) Day +3 (Jun 09), (g) Day +6 (Jun 12), and (h) Day +9 (Jun 15). American coast that inˆuenced the weather in the SP region 3.2.4. Southern Annular Mode. �e AAO index, which during the period analyzed. measures the phase of the SAM, was positive during �e PSA 1 mode in June 2016 was not signišcant, staying the period of study, with an average of +1.759 (Table 1), between ±1 standard deviation (Table 1). indicating the predominance of negative anomalies of geo- potential height at southern high latitudes and positive anomalies in the middle latitudes [38, 60, 61]. Reboita et al. 3.2.3. Indian Ocean Dipole and Wave Source Analysis. [23] showed that the low-pressure circumpolar belt is shifted For May/June 2016, the IOD presents negative values, south during the positive phase of the AAO in relation to conšguring a negative dipole event (western basin colder that in the negative phase, which is unfavorable for the and eastern basin warmer). �rough the analysis of the wave propagation of cyclonic systems to the north that could activity ˆux divergence (Figure 9) for the May-June 2016 propagate to Southeastern Brazil. �erefore, the AAO did basic state [59], a wave like pattern coming from the Indian not interfere in the analyzed extreme event. Ocean eastern basin (Indo-Pacišc region) is not found; thus, this region is probably not a Rossby wave train source inˆuencing the South America—even though it is found to 3.2.5. Blocking Events. No blocking events a‘ecting the be an upper-level divergence source (see the red shaded area weather over South America were found during the period over the eastern basin). evaluated (šgure not shown). 12 Advances in Meteorology Wave activity flux (W ,W ) for May-Jun 2016 x y 30°N 15°N 0° 15°S 30°S 0 45°S –2 60°S –4 0° 30°E 60°E 90°E 120°E 150°E 180° 150°W 120°W 90°W 60°W 30°W 0° Figure 9: Wave activity ˆux (×10 ) for May-Jun 2016. �e arrows represent the wave ˆux W and W , and the shading represents the wave x y ˆux divergence, wave ˆux divergence indicates Rossby wave sources and convergence indicates Rossby wave sinks. Following Takaya and Nakamura [59], the wave ˆux is parallel to the phase velocity of the Rossby wave packages. 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 Date Date CHIRPS BRAMS 36 h CHIRPS WRF 72 h BRAMS 24 h BRAMS 48 h WRF 24 h WRF 96 h WRF 48 h (a) (b) 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 Date Date CHIRPS ETA 60 h ETA 108 h CHIRPS GFS 60 h GFS 108 h ETA 24 h ETA 72 h ETA 120 h GFS 24 h GFS 72 h GFS 120 h ETA 36 h ETA 84 h ETA 132 h GFS 36 h GFS 84 h GFS 132 h ETA 48 h ETA 96 h ETA 144 h GFS 48 h GFS 96 h GFS 144 h (c) (d) −1 Figure 10: Temporal evolution of the percentage of the SP region area with precipitation above the threshold of 5 mm·day (%) for CHIRPS and for di‘erent forecast times of the models (a) BRAMS, (b) WRF, (c) Eta, and (d) GFS, from 29 May to 9 June 2016. Dotted lines indicate the start (30 May 2016) and end (07 June 2016) of the period of interest. Area with precipitation (%) Area with precipitation (%) 28 May 28 May 29 May 29 May 30 May 30 May 31 May 31 May 1 Jun 1 Jun 2 Jun 2 Jun 3 Jun 3 Jun 4 Jun 4 Jun 5 Jun 5 Jun 6 Jun 6 Jun 7 Jun 7 Jun 8 Jun 8 Jun 9 Jun 9 Jun Area with precipitation (%) Area with precipitation (%) 28 May 28 May 29 May 29 May 30 May 30 May 31 May 31 May 1 Jun 1 Jun 2 Jun 2 Jun 3 Jun 3 Jun 4 Jun 4 Jun 5 Jun 5 Jun Sink←▽·W→source 6 Jun 6 Jun 7 Jun 7 Jun 8 Jun 8 Jun 9 Jun 9 Jun Advances in Meteorology 13 of a detailed verification will be presented and discussed in 4. Conclusions a future paper. A sequence of successive convective systems favoring Atypical precipitation events like the one analyzed in the atypical precipitation events, with high volumes of rain, present paper can happen again in the future, causing occurrences of tornadoes, and a microburst over South- further significant impacts for society and the economy. eastern Brazil took place during the dry season of 2016, more Studies to detect and evaluate the mechanisms contributing specifically, from May 30 to June 07, 2016 (9 days). 'ese to these anomalous events are important for the improve- anomalous events caused flooding, damages to houses and ment of the forecasts and mitigation of the associated buildings, and shortages of electricity and water in several consequences. Suggestions for future studies include in- places, with many injuries and two deaths documented. vestigating why the models did not predict the beginning of 'ese severe weather events were associated with a daily the precipitation period and whether this type of severe sequence of convective systems that formed preferentially weather will be frequent in the coming warmer climate. during early afternoon in the western part of SP state (red box in Figure 1) and also northwest of the SP region, Conflicts of Interest propagating along the low-level mean flow and growing as they moved into the region. 'e convective systems were 'e authors declare that there are no conflicts of interest embedded in an instable environment (high K index, high regarding the publication of this paper. Total Totals, low Showalter, and high wind shear) with an intense and persistent South American low-level jet (SALLJ) Acknowledgments (east of the Andes) advecting heat and moisture from the 'e authors are grateful to Dr. Jose´ Roberto Rozante, Amazon Basin into Southeastern Brazil. 'e exit region of the SALLJ was located over the SP region instead of Southern Dr. Jorge Lu´ıs Gomes, and Vinicius Matoso Silva from CPTEC/INPE for providing BRAMS and Eta datasets and to Brazil-northern Argentina (which is its typical exit location according to climatological studies). 'is displacement the Universidade Federal de Itajuba (UNIFEI) for providing WRF datasets. Tercio Ambrizzi was supported by CNPq and along the direction of the jet was likely driven by a sequence of extratropical cyclones that formed to the south of the FAPESP. region of interest over the Southwest Atlantic Ocean during the 9-day rainy period. 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Severe Weather Events over Southeastern Brazil during the 2016 Dry Season

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Copyright © 2018 Amanda Rehbein et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Hindawi Advances in Meteorology Volume 2018, Article ID 4878503, 15 pages https://doi.org/10.1155/2018/4878503 Research Article Severe Weather Events over Southeastern Brazil during the 2016 Dry Season 1 1 1 Amanda Rehbein, L´ıvia Ma ´ rcia Mosso Dutra, Tercio Ambrizzi , 1 2 Rosmeri Porfı ´rio da Rocha, Michelle Simões Reboita, 3 4 Gyrlene Aparecida Mendes da Silva , Luiz Felippe Gozzo, 1 1 Ana Carolina No ´ bile Tomaziello, Jose ´ Leandro Pereira Silveira Campos, 1 1 1 Victor Raul Chavez Mayta, Nata ´ lia Machado Crespo, Paola Gimenes Bueno , 1 1 1 Vannia Jaqueline Aliaga Nestares, La´ıs Tabosa Machado, Eduardo Marcos De Jesus, 5 4 6 Luana Albertani Pampuch, Maria de Souza Custo ´ dio, and Camila Bertoletti Carpenedo Departamento de Ciˆencias Atmosf´ericas, Instituto de Astronomia, Geof´ısica e Cieˆncias Atmosfe´ricas da Universidade de São Paulo, São Paulo, SP, Brazil Instituto de Recursos Naturais da Universidade Federal de Itajuba´, Itajuba´, MG, Brazil Departamento de Ciˆencias do Mar da Universidade Federal de São Paulo, São Paulo, SP, Brazil Departamento de F´ısica da Universidade Estadual Paulista Ju´lio de Mesquita Filho, Campus de Bauru, SP, Brazil Instituto de Ciˆencia e Tecnologia da Universidade Estadual Paulista Ju´lio de Mesquita Filho, Campus de São Jos´e dos Campos, São Paulo, SP, Brazil Instituto de Geografia da Universidade Federal de Uberlaˆndia, Uberlaˆndia, MG, Brazil Correspondence should be addressed to Tercio Ambrizzi; ambrizzi@model.iag.usp.br Received 27 December 2017; Revised 3 April 2018; Accepted 18 April 2018; Published 10 June 2018 Academic Editor: Anthony R. Lupo Copyright © 2018 Amanda Rehbein et al. 'is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Southeastern Brazil is the most populated and economically developed region of this country. Its climate consists of two distinct seasons: the dry season, extending from April to September, the precipitation is significantly reduced in comparison to that of the wet season, which extends from October to March. However, during nine days of the 2016 dry season, successive convective systems were associated with atypical precipitation events, tornadoes and at least one microburst over the southern part of this region. 'ese events led to flooding, damages to buildings, shortages of electricity and water in several places, many injuries, and two documented deaths. 'e present study investigates the synoptic and dynamical features related to these anomalous events. 'e convective systems were embedded in an unstable environment with intense low-level jet flow and strong wind shear and were supported by a sequence of extratropical cyclones occurring over the Southwest Atlantic Ocean. 'ese features were intensified by the Madden–Julian oscillation (MJO) in its phase 8 and by intense negative values of the Pacific South America (PSA) 2 mode. summer (Dec-Jan-Feb), there is a predominance of intense 1. Introduction convective precipitation due to the availability of plentiful Climate and weather components that affect directly the heat and moisture over the tropical region [3]. 'is intense population and economy of Southeastern Brazil [1, 2] have convective precipitation delineates a cloud corridor known as been widely studied in recent years, as well as the large-scale the South Atlantic Convergence Zone (SACZ), which extends forcings from tropical and extratropical origins. It is well from the southwest Amazon Basin and through Southeast known that the climate of Southeastern Brazil is influenced Brazil, reaching the Atlantic Ocean [4]. From the beginning of by the South America monsoon system, where during the autumn until midspring, the frequency of SACZ episodes 2 Advances in Meteorology decreases, initiating the dry period over Southeastern Brazil Precipitation (mm) and 850 hPa wind (m/s) anomaly 30/May/2016 – 07/Jun/2016 Climatology: 1981–2010 [5]. Moreover, it is during this period that the South Atlantic 5N Subtropical Anticyclone (SASA) reaches its most westerly position, extending over Southeastern Brazil, which impedes the passage of frontal systems [6]. �erefore, during this EQ period, the precipitation events are normally quick, isolated, and not intense. 5S During the dry season of 2016, there were 9 consecutive atypical days (May 30 to June 07, 2016) with thunderstorms, tornadoes, and at least one microburst over Southeastern 10S Brazil. �ese phenomena caused ˆoods, smashed houses, personal injuries, and two documented deaths (http:// 15S g1.globo.com/sao-paulo/sorocaba-jundiai/noticia/2016/06/ meteorologistas-analisam-se-tornado-causou-destruicao- em-jarinu.html and http://www.saoroquenoticias.com.br/ 20S noticia.asp?idnoticia16053). �ese atypical weather events a‘ected mainly the southern part of Southeastern Brazil, with 25S the most severe conditions occurring over the cities of Campinas, Jarinu, and São Roque, which are close to city of São Paulo in São Paulo State. In Campinas, a probable mi- 30S croburst occurred on June 05 between 00:00 and 00:30 Local Time (LT; Rachel Ifanger Albrecht, personal communication, 35S 2016). At Jarinu on June 05 at about 21 LT and at São Roque 75W 70W 65W 60W 55W 50W 45W 40W 35W 30W on June 06 in the late afternoon, the occurrences of tornadoes were conšrmed by analysis of damage by local meteorological –150 –100 –50 –25 0 25 50 100 150 institutes and civil defense, besides being observed in the meteorological radar data (Rachel Ifanger Albrecht, personal 10 m/s communication, 2018). Precipitation anomalies from May 30 to Figure 1: Precipitation anomalies (mm) and 850 hPa wind com- June 07 reached values of around 200 mm in Southeastern −1 posite (m·s ) for May 30 to June 07, 2016. �e blue (brown) colors Brazil, in a region comprising São Paulo State and parts of other indicate the positive (negative) rain anomalies, and the red box surrounding states (Figure 1). For instance, at the meteoro- indicates the area of study. �e anomalies were calculated using the logical station of the Institute of Astronomy, Geophysics 30-year period, 1981 to 2010. and Atmospheric Science of the University of Sao Paulo (IAG/USP), located in the southern part of the city of São Paulo, the climatological precipitation for the period of 1981 to 2010 is reanalysis [7] from the European Centre for Medium-Range 55.5 mm for the entire month of June. In the šrst 7 days of June Weather Forecasts (ECMWF). �ese data are available every 2016, at this station, the total precipitation was 175.4 mm (316% six hours (0000, 0006, 1200, and 1800 UTC) with spatial of the climatological value for the entire month). resolution of 0.75 , for various pressure levels [7]. We an- �e aims of the present study are (a) to investigate the alyzed the synoptic šelds at low, middle, and upper levels at dynamic forcings associated with those severe weather and each available time; however, for brevity, only the 1200 UTC extreme rainfall events over Southeastern Brazil in the dry šelds are presented here. season of 2016 and (b) to verify whether or not the most- Infrared satellite images (about 10.7 μm) with 4 km and 30 used forecast models in Brazil predicted this period of in- minutes of spatial and temporal resolution, respectively, are tense precipitation. �e datasets and methodology used are from the Geostationary Operational Environmental Satellite described in Section 2; Section 3 presents the synoptic (GOES-13; Janowiak et al. [8]) and were made available by discussion, low-frequency analysis, and the model forecasts the CPC/NCEP/NWS (Climate Prediction Center/National results; and the concluding remarks are given in Section 4. Centers for Environmental Prediction/National Weather Service) via ftp://ftp.cpc.ncep.noaa.gov/precip/global_full_ res_IR/. 2. Data and Methods Five thermodynamic indices (Convective Available Po- tential Energy—CAPE, Convective Inhibition—CIN, K index, �e period of analysis is May 30 to June 07, 2016, and Total Totals—TT, and Showalter) are used to characterize the the region of interest covers the area between latitudes 25 S ° ° ° environmental instability. Moreover, two kinematic indices to 19 S and longitudes 53 W to 42 W (red box in Figure 1), (sweat and vertical shear of horizontal wind—here termed where the most intense precipitation and severe weather “wind shear”) are also presented because when their values are events were registered. strong, the environment is favorable to severe weather events [9, 10] and to the formation of stronger convective supercells 2.1. Synoptic and ermodynamic Analysis. �e synoptic [11]. �e instability and kinematic indices were obtained for ° ° šelds were constructed using data from the ERA-Interim a point (23 S/47 W) representative of the severe storm Advances in Meteorology 3 convection) over tropical South America, is shown in Fig- sites—Campinas, Jarinu, and São Roque. 'is point is located less than 60 km from these sites. In the literature, a distance of ure 8. RMM amplitude in phase 8 reaches its maximum value at “day 0,” which means that the association between rainfall up to 180 km is used for the representativeness of such surveys [12, 13]. 'e Convective Available Potential Energy (CAPE) anomalies and MJO passage over Southeastern Brazil was and Convective Inhibition (CIN) were obtained from the strong. Global Forecast System (GFS) model analysis with spatial 'e PSA modes are teleconnection patterns extending resolution of 0.5 and available for 0000, 0600, 1200, and 1800 poleward and eastward over the Pacific Ocean [31], mod- UTC. 'e K index [14], Total Totals (TT; Miller [15]), ulating the circulation and precipitation anomalies over Showalter [16], wind shear, and Sweat index were calculated South America [32]. PSA teleconnection patterns consist of using the GFS analysis data. 'e Sweat index is adapted from two distinct modes: PSA 1, related to the El Niño Southern Miller [15] to Southern Hemisphere wind conditions fol- Oscillation (ENSO; Karoly [31]) and PSA 2, associated with the MJO during the winter [18]. Both of them have impacts lowing Nascimento [10]. on the climate of South America, and consequently on the rainfall intensity and distribution over São Paulo state. 'e 2.2. Climate Analysis. 'e weather and climate in South PSA modes are defined as the first and second leading ro- America are influenced by relatively well-known telecon- tated principal component modes of the 200 hPa stream nection patterns of tropical and extratropical origins that we function anomaly, respectively [18, 32]; these patterns are can observe and measure through indices and statistical also presented in other time scales such as pentads and annual analysis. In this study, we investigated the influence of the [32–34]. In this study, both PSA modes were computed using most important atmospheric and oceanic phenomena that can ERA-Interim reanalysis for the 200 hPa pentad stream affect the weather over the Southeastern Brazil: Madden Julian function anomaly data. 'e covariance matrix was obtained Oscillation [17], Pacific South America pattern, first and through the extraction of the annual cycle computed with the climatology of 1981–2010 as a basis period. second modes [18, 19]; Indian Ocean Dipole (IOD; [20–22]); Southern Annular Mode [23]; and blocking events [24, 25]. Saji et al. [35] showed that the anomalous warming of the tropical Indian Ocean due to low level evaporation can lead 'e MJO is triggered in the Indian and Pacific Oceans and propagates eastward over the tropical region with to divergence in the upper troposphere, sourcing Rossby a cycle of about 30 to 60 days [26]. During its propagation, wave trains propagating from the Indo-Pacific region to- it comprises regions with enhanced and suppressed con- wards the South Atlantic Ocean in an arch-like trajectory. vection. In São Paulo, the most favorable conditions for Taschetto and Ambrizzi [22] showed that anomalous convection occur with suppression of convection over warming throughout the Indian Ocean Basin can excite Indonesia, when the MJO is in its phases 8 and 1, as shown Rossby wave trains moving towards the South Atlantic, and also amplifying El Niño patterns in the precipitation over the by Jones and Carvalho [17]. Here, to better understand the influence on the extreme rainfall variability over South- South American continent, for the austral autumn season (March–May). In order to explore the effects of the Indian eastern Brazil by the eastward-propagating MJO-related large-scale convective and circulation envelope, we have Ocean on South American precipitation, the Indian Ocean Dipole (IOD; Saji et al. [36]; Webster et al. [37]), that is, the constructed lagged/lead composites for the 0.21 sigma-level (approximately 200 hPa) velocity potential and outgoing difference between the Eastern and Western Basin sea longwave radiation (OLR) anomalies. surface temperature anomaly (SSTa), is computed through 'e velocity potential was obtained from National the extraction of the annual cycle based on the 1981–2010 Centers for Environmental Prediction/National Center for climatology, for 36 years (1980–2016) of ERA-Interim data. Atmospheric Research (NCEP/NCAR; Kalnay et al. [27]) 'e SAM, also known as Antarctic Oscillation (AAO), is and the OLR field from the High Resolution Infrared Ra- the main mode of extratropical circulation variability in the Southern Hemisphere. It consists of zonally symmetric diation Sounder (HIRS; Lee et al. [28]). Daily anomalies of OLR and velocity potential were calculated at every grid structures, with geopotential height perturbations of op- posing signs in Antarctica and in the surrounding zonal ring point by subtracting the long-term average (1979–2015) in order to remove the seasonal cycle. 'e intraseasonal signals centered near 45 latitude [38]. Reboita et al. [23] observed are isolated from the OLR daily anomalies by applying that during negative SAM phases, the cyclone trajectories Lanczos bandpass filter [29] using cutoff frequencies at 20 are northward of their positions during the positive phase, and 96 days. To assemble the composites, we considered the and in the South America and South Atlantic sectors, there Wheeler and Hendon [30] real-time multivariate MJO is intense frontogenetic activity and a positive precipita- (RMM) index for our period of analysis. 'is index is tion anomaly over southeastern South America, which in- available at the Centre for Australian Weather and Climate fluences the weather in São Paulo. To monitor SAM, we used Research website (see: http://www.bom.gov.au/climate/mjo/) the daily AAO index available on the Climate Prediction and is based on a pair of empirical orthogonal functions Center/National Oceanic and Atmospheric Administra- (EOFs) of the combined fields of near-equator averaged tion (CPC/NOAA) website (http://www.cpc.ncep.noaa.gov/ 850 hPa zonal wind, 200 hPa zonal wind, and satellite- products/precip/CWlink/daily_ao_index/aao/aao.shtml). observed outgoing longwave radiation (OLR) data [30]. 'is index is constructed using 700 hPa geopotential height 'e evolution of these anomalies from “day−12” to “day +9”, anomalies projected onto the leading EOF mode [39]. To where “day 0” represents the active phase (enhanced define the phase of the SAM, we use a methodology similar 4 Advances in Meteorology 15S 15S 15S 15S 20S 20S 20S 20S 25S 25S 25S 25S 30S 30S 30S 30S 60W 50W 40W 60W 50W 40W 60W 50W 40W 60W 50W 40W (a) (b) (c) (d) 15S 15S 15S 15S 20S 20S 20S 20S 25S 25S 25S 25S 30S 30S 30S 30S 60W 50W 40W 60W 50W 40W 60W 50W 40W 60W 50W 40W (e) (f) (g) (h) Figure 2: GOES-13 enhanced infrared images on June 04, 2016, at (a) 1200 UTC, (b) 1500 UTC, (c) 1800 UTC, and (d) 2100 UTC; and on June 05, 2016, at (e) 0000 UTC, (f) 0300 UTC, (g) 0600 UTC, and (h) 0900 UTC. to Reboita et al. [23], in which values above (below) one America (including northern/northeastern Brazil; Grimm standard deviation indicate the positive (negative) phase. and Ambrizzi [46]; da Rocha et al. [47]). Given its location, �e standard deviation value of the daily SAM time series the SP region is considered to be a transition region where from 1979 to 2015 is equal to 1.4, and thus values between the e‘ect of ENSO could be either to increase or reduce ±1.4 indicate the neutral phase. precipitation [48]. Atmospheric blocking episodes are due to quasi- stationary planetary waves of large amplitude [40], persist- 3. Results and Discussions ing from days to a few weeks, leading to episodes of prolonged extreme weather conditions over some areas. Over the 3.1. Synoptic Analysis. A rainfall anomaly averaging 47 mm Southeastern Pacišc, Southern Atlantic and Oceania, the low- occurred over the SP region (red box in Figure 1) during the pressure anomalies occurring on the equatorial ˆank of the period May 30 to June 07, 2016. Figure 1 shows that in specišc blocking pattern favor the development of transient systems regions, rainfall anomalies reached more than 100 mm over that may cause precipitation as they move eastward (Mendes these 9 days. �e satellite images show convective systems et al. [41]). �e resulting impacts on temperature and pre- forming in the western SP region and moving eastward cipitation are most frequently observed over Southern Brazil, throughout their life cycle (see, e.g., Figure 2). In addition, but they can also inˆuence our region of interest (South- some convective systems were generated northwest of the SP eastern Brazil; Mendes et al. [41]). In the latter case, Mendes region propagating along the low-level mean ˆow and et al. [41] observed that southeastern Pacišc blocking has growing as they moved into the region. Each system had its higher impact on precipitation in austral summer and spring own lifetime, starting, and developing preferentially during (wet season), while the Atlantic blocking a‘ects precipitation early afternoon (1200 to 1500 LT). Figure 1 also shows that the in austral autumn and winter (dry season). predominant wind at 850 hPa ˆowed from the southern For the identišcation of blocking events over the Amazon Basin into the SP region. �is is the same as the Southern Hemisphere, we used the objective method of conšguration observed by Morales et al. [49] on days with Tibaldi et al. [42], modišed from Lejeñas [43]. �is method thunderstorms in the city of São Paulo. was adapted to a smaller horizontal spacing of the ERA- Figures 3(a)–3(d) show vertical prošles of horizontal ° ° Interim reanalysis (1.5 ×1.5 of horizontal resolution) in- temperature advection, divergence of the horizontal wind, ° ° stead of 3.75 × 3.75 used by Tibaldi et al. [42] and stratišed pressure vertical velocity (omega), and moisture conver- into šve bands of latitudes, according to Oliveira et al. [25]. gence averaged over the SP region, from May 30 to June 07, For an episode to be characterized as a blocking event, it 2016, every 6 hours. Overall, warm-air advection occurred at all levels of the troposphere, peaking on June 05 (Figure 3(a)) must persist for at least 3 days [25, 44, 45]. �e ENSO signal was not evaluated in this work because when two of the most severe events were reported (mi- the São Paulo (SP) region is located in between the two croburst at Campinas, SP, and tornado at Jarinu, SP). �is sectors of South America in El Niño (EN), and La Niña (LN) warm advection contributes to increased instability over the episodes usually a‘ect the observed precipitation with op- SP region and is associated with a northerly mean ˆow, as posing contributions. For instance, during EN conditions, further discussed in this section. On June 07, the last day of there is increased precipitation over the southeastern sector the observed anomalous precipitation over the SP region, of South America (including Southern Brazil) and reduced intense cold advection occurred in the lower troposphere precipitation over the northern/northeastern sector of South (Figure 3(a)), associated with a change in the direction of the Advances in Meteorology 5 –1 –3 –5 30 May 31 May 1 Jun 2 Jun 3 Jun 4 Jun 5 Jun 6 Jun 7 Jun (a) 0.6 0.2 –0.2 –0.6 –1 30 May 31 May 1 Jun 2 Jun 3 Jun 4 Jun 5 Jun 6 Jun 7 Jun (b) 0.25 0.15 0.05 –0.05 –0.15 –0.25 30 May 31 May 1 Jun 2 Jun 3 Jun 4 Jun 5 Jun 6 Jun 7 Jun (c) –2 –6 –10 30 May 31 May 1 Jun 2 Jun 3 Jun 4 Jun 5 Jun 6 Jun 7 Jun (d) −1 −5 −1 Figure 3: Vertical prošles of (a) horizontal temperature advection (K·day ), (b) divergence of the horizontal wind (10 ·s ), (c) pressure −1 −5 −1 −1 vertical velocity (or omega; Pa·s ), and (d) moisture divergence (10 ·g·kg ·s ) averaged over the SP region, from May 30 to June 07, 2016, every 6 hours. mean ˆow over the region at these levels. Convergence in the which comes from tropical latitudes over the south Amazon lower troposphere and divergence in the upper troposphere Basin towards the subtropics, exiting over the SP region. �is occurred during all days analyzed (Figure 3(b)), favoring SALLJ developed around 0600 UTC on May 30 (not shown) upward motion over the SP region (Figure 3(c)). At lower and was sustained until 0000 UTC on 07 June. It can be seen and middle levels (up to 600 hPa), moisture convergence as a northwesterly band of maximum wind intensity at 850 hPa in association with a poleward transport of warm and occurred on all days (except June 07; Figure 3(d)), indicating favorable conditions for the formation of convective systems moist air (Figure 4). Commonly, days with thunderstorms in the SP region. �e general pattern described above was the over the city of São Paulo (about 100 km away from where the reverse of that of the week prior to May 30 and after June 07 severe events occurred) are accompanied by strong northerly (not shown), when there was no anomalous precipitation winds [49]. over the SP region. �e SALLJs are observed throughout the year but are �e lower-level moisture convergence and warm-air more frequent and intense during the warm season (NDJF) advection over the SP region occurred in association with when the northeast trade winds in the equatorial western the South American low-level jet (SALLJ) (east of the Andes), Atlantic ˆow towards the Amazon Basin [50]. �e trade 6 Advances in Meteorology EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (a) (b) (c) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (d) (e) (f ) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (g) (h) (i) –15 –12 –9 –6 –3 –1.5 1.5 3 6 9 12 15 20 (m/s) −1 −5 −1 −1 Figure 4: Horizontal temperature advection (shaded; K·day ), moisture ˆux convergence (purple contours every 10 ×10 g·kg ·s −5 −5 −1 −1 −1 from 5 ×10 to 55 ×10 g·kg ·s ), and horizontal wind (vectors; m·s ) at 850 hPa at 1200 UTC on (a) 30 May, (b) 31 May, (c) 01 June, (d) 02 June, (e) 03 June, (f) 04 June, (g) 05 June, (h) 06 June, and (i) 07 June, 2016. Advances in Meteorology 7 winds are deflected toward the southeast as they approach streams on those days (Figure (6)). 'e Sweat index in- the mountain barriers and then converge with the flow from creased from May 30 to June 6; however, it did not reach the western branch of the South Atlantic Subtropical High the thresholds for the development of severe storms in the (SASH), producing strong wind speeds at low levels and United States (above 300; Figure 7(g)). Other studies in convective development over the exit region of the jet (see, Brazil have also found that some thermodynamic and ki- conceptual model presented in Marengo et al. [51] and their nematic indices are indicative of the instability of a given Figure 1). 'is exit region is located typically over Southern region; however, they may not reach established thresholds Brazil-Northern Argentina as described in Marengo et al. of severity even when severe weather occurs [53, 54]. [51]. During May 30 to June 06, 2016, however, the SALLJ was active northeastward of its typical position, such that its 3.2. Low-Frequency Analysis. 'e following analysis and exit was located over the SP region instead of Southern Brazil discussions cover the contribution of climate indices (Figure 4). 'is displacement in the jet direction was likely (Table 1) and planetary-scale influence on the severe rain driven by the intense extratropical cyclonic activity over the event studied in the present paper. Atlantic Ocean adjacent to the South American coast during the days analyzed (Figure 5). 'is activity consisted of two main extratropical cyclones plus three secondary cyclones 3.2.1. 5e Influence of the Madden–Julian Oscillation. forming and acting along the southeastern coast of South Anomalous upper-level velocity divergence (represented by America. 'e cyclonic (clockwise) circulation predomi- negative velocity potential anomalies—dashed lines in nant over the southwestern Atlantic Oceanfavored the Figure 8—had been established over tropical South America blocking—by the northwesterly SALLJ—of the advection of by “day −9” (May 28) and persisted to “day +3” (June 09), cold and dry air from higher latitudes into eastern Argentina favoring upward motion mainly between “day−3” (June 03) and Southern Brazil (Figure 4). At 0000 UTC on June 07, and “day 0” (June 06), the period of the most intense rainfall a cold front finally penetrates the continent (figure not events over the state of Sao Paulo. 'us, the OLR pattern shown), reaching the southern Amazon region and weak- showed enhanced convection over southeastern South ening the SALLJ, by means of advection from a colder and America and the adjacent Atlantic Ocean toward the dryer air mass into the rear of the frontal zone (Figure 4(i)). southern Amazon basin, resembling the austral winter sit- 'ese persistent low-level patterns (Figures 4 and 5) all seem uation with the active MJO phase over South America to be unrelated to a persistent subtropical jet at high-levels (e.g., [55]). In addition, “day 0” was when the RMM reached (Figure 6). phase 8 and its amplitude began to increase. As pointed During the period of interest, atmospheric instability was out in previous studies (e.g., Jones and Carvalho 2012 calculated in terms of various thermodynamic (Figures 7(a)–7(e)) [17, 56, 57]), phase 8 and phase 1 favor convection over and kinematic (Figure 7(f) and 7(g)) indices. 'e K index tropical South America. Even though phase 1 favors con- indicates high probability (above 80%) of storm occurrence vection over tropical South America and the following days from 1200 UTC on May 31 to 0000 UTC on June 07 (except were in that phase, it was not sufficient to favor convection at 1200 UTC on June 02 and 03; Figure 7(a)). After this over the SP region because, as shown by the synoptic period, the K index decreased substantially. 'e Total analysis, and on June 07, the atmospheric environment over Totals index was high (above 46 C) during most of our this region began to stabilize, after the cold front passage, period of interest (Figure 7(b)), indicating some scattered with cold and dry air being advected from the south. storms. From 0000 UTC on June 04 to 1200 UTC on June Upper-level tropical convergence (represented by posi- 06, the warm air advection at middle levels was greater than tive velocity potential anomalies (Figure 8)) progresses on other days (Figure 3(a)), decreasing the values of the eastward from the western tropical Pacific from “day −12” Total Totals during this period. 'e Showalter index in- (May 25) and arrives in tropical South America by “day +9” dicated the possibility of storms, remaining most of the (June 15), indicating the end of the active MJO period over time below 1 C (Figure 7(c)). However, it did not match the tropical South America. It is noteworthy that the evolution thresholds for tornados (below −6 C) in the days in which of the MJO influence (onset-peak-demise) has a period of this phenomenon happened (June 05 and 06). 'is is approximately 10 days (from “day−6” to “day +3”), average possibly due to the strong midlevel warm advection over duration of the MJO passage over South America [58]. the SP region during these days (Figure 3(a)), which contributed to raising the temperature at 500 hPa. It is interesting to note that the CAPE was relatively low 3.2.2. Pacific South America Mode. 'e dominant mode (Figure 7(d)), CIN was relatively intense (Figure 7(e)), and of low-frequency climate variability for the last pentad of the wind shear was above the traditional threshold to favor May and first pentad of June 2016 was the PSA 2 mode, −1 rotating supercells (15 m·s ; Figure 7(f) [10]). 'e severe presenting negative values below 2 standard deviations weather observed during these days is the characteristic of (Table 1); this possibly results from a combination of ENSO the cold season, where there is usually low thermodynamic influence in the interannual band [31] and tropical con- convective potential but strong wind shear (an example of vection associated with the MJO in the intraseasonal band such a type of event in the United States is presented in [18]. 'is strongly negative value of PSA 2 during late May/early June 2016 likely contributed to the persistent Markowski and Straka [52]). 'e wind shear was high even after the period of interest because of the influence of the jet cyclogenetic activity over the Atlantic near the South 8 Advances in Meteorology EQ EQ EQ 10S 10S 10S 20S 20S 20S 1016 1016 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (a) (b) (c) EQ EQ EQ 10S 10S 10S 1020 1020 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (d) (e) (f ) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 1020 30S 1020 1024 40S 40S 40S 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W 80W 70W 60W 50W 40W (g) (h) (i) –22 –18 –14 –10 –6 –2 Figure 5: Mean sea level pressure (black contours; hPa), geopotential height (red-dashed contours; gpm), and relative vorticity −5 −1 (shaded; 10 ·s ) at 850 hPa at 12 UTC on (a) 30 May, (b) 31 May, (c) 01 June, (d) 02 June, (e) 03 June, (f) 04 June, (g) 05 June, (h) 06 June, and (i) 07 June, 2016. Advances in Meteorology 9 EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 60W 40W 80W 60W 40W 80W 60W 40W (a) (b) (c) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 60W 40W 80W 60W 40W 80W 60W 40W (d) (e) (f ) EQ EQ EQ 10S 10S 10S 20S 20S 20S 30S 30S 30S 40S 40S 40S 80W 60W 40W 80W 60W 40W 80W 60W 40W (g) (h) (i) 20 30 40 50 60 70 −1 Figure 6: 200 hPa streamlines and isotachs (shaded; m·s ) at 12 UTC on (a) 30 May, (b) 31 May, (c) 01 June, (d) 02 June, (e) 03 June, (f) 04 June, (g) 05 June, (h) 06 June, and (i) 07 June, 2016. 10 Advances in Meteorology 40 50 –20 (a) (b) –50 –100 –150 –200 –250 (c) (d) 250 20 (e) (f ) 20°S 21°S 22°S Campinas 23°S Jarinu São Roque 24°S 52°W 50°W 48°W 46°W 44°W (g) (h) 0000 UTC 1200 UTC ° ° Figure 7: Temporal evolution of the instability indices at 0000 UTC (red) and 1200 UTC (blue): (a) K index ( C), (b) Total Totals ( C), −1 −1 −1 (c) Showalter index ( C), (d) CAPE (J·kg ), (e) CIN (J·kg ), (f) Wind shear (m·s ), (g) Sweat index, and (h) Map of São Paulo state, with the location of where these indices were calculated (red dot) and the three cities where the most severe thunderstorms occurred (black crosses). �e shaded areas from (a) to (g) indicate the values for instability. –1 Showalter (°C) K index (°C) Sweat CAPE (J∙kg ) 25–May 25–May 25–May 25–May 26–May 26–May 26–May 26–May 27–May 27–May 27–May 27–May 28–May 28–May 28–May 28–May 29–May 29–May 29–May 29–May 30–May 30–May 30–May 30–May 31–May 31–May 31–May 31–May 01–Jun 01–Jun 01–Jun 01–Jun 02–Jun 02–Jun 02–Jun 02–Jun 03–Jun 03–Jun 03–Jun 03–Jun 04–Jun 04–Jun 04–Jun 04–Jun 05–Jun 05–Jun 05–Jun 05–Jun 06–Jun 06–Jun 06–Jun 06–Jun 07–Jun 07–Jun 07–Jun 07–Jun 08–Jun 08–Jun 08–Jun 08–Jun 09–Jun 09–Jun 09–Jun 09–Jun 10–Jun 10–Jun 10–Jun 10–Jun –1 CIN (J∙kg ) –1 Wind shear (m∙s ) Total Totals (°C) 25–May 25–May 25–May 26–May 26–May 26–May 27–May 27–May 27–May 28–May 28–May 28–May 29–May 29–May 29–May 30–May 30–May 30–May 31–May 31–May 31–May 01–Jun 01–Jun 01–Jun 02–Jun 02–Jun 02–Jun 03–Jun 03–Jun 03–Jun 04–Jun 04–Jun 04–Jun 05–Jun 05–Jun 05–Jun 06–Jun 06–Jun 06–Jun 07–Jun 07–Jun 07–Jun 08–Jun 08–Jun 08–Jun 09–Jun 09–Jun 09–Jun 10–Jun 10–Jun 10–Jun Advances in Meteorology 11 Table 1: Values of the climate indices analyzed. σ is the standard deviation. Index Values Period PSA 1 +4.0 June 01–05, 2016 PSA 2 −59.0 (−2.3σ) June 01–05, 2016 IOD −0.61 June 2016 AAO +1.759 May 30 to June 07, 2016 20°N 20°N EQ EQ 20°S 20°S 40°S 40°S 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° (a) (e) 20°N 20°N EQ EQ 20°S 20°S 40°S 40°S 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° (b) (f ) 20°N 20°N EQ EQ 20°S 20°S 40°S 40°S 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° (c) (g) 20°N 20°N EQ EQ 20°S 20°S 40°S 40°S 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° 0° 40°E 80°E 120°E 160°E 160°W 120°W 80°W 40°W 0° (d) (h) –50 –40 –30 –20 –10 0 10 20 30 40 50 −2 Figure 8: Lagged composite maps of šltered OLR anomaly (W·m ; shaded) and sigma-level 0.21 velocity potential (black contours every 6 2 −1 0.75 ×10 ·m ·s ; negative values are dashed) for a frequency band of 20 to 96 days. Composites are centered on day −12 to day +9 in which day 0 represents the most intense precipitation events over SP region (June 06). (a) Day −12 (May 25), (b) Day −9 (May 28), (c) Day −6 (May 31), (d) Day −3 (Jun 03), (e) Day 0 (Jun 06), (f) Day +3 (Jun 09), (g) Day +6 (Jun 12), and (h) Day +9 (Jun 15). American coast that inˆuenced the weather in the SP region 3.2.4. Southern Annular Mode. �e AAO index, which during the period analyzed. measures the phase of the SAM, was positive during �e PSA 1 mode in June 2016 was not signišcant, staying the period of study, with an average of +1.759 (Table 1), between ±1 standard deviation (Table 1). indicating the predominance of negative anomalies of geo- potential height at southern high latitudes and positive anomalies in the middle latitudes [38, 60, 61]. Reboita et al. 3.2.3. Indian Ocean Dipole and Wave Source Analysis. [23] showed that the low-pressure circumpolar belt is shifted For May/June 2016, the IOD presents negative values, south during the positive phase of the AAO in relation to conšguring a negative dipole event (western basin colder that in the negative phase, which is unfavorable for the and eastern basin warmer). �rough the analysis of the wave propagation of cyclonic systems to the north that could activity ˆux divergence (Figure 9) for the May-June 2016 propagate to Southeastern Brazil. �erefore, the AAO did basic state [59], a wave like pattern coming from the Indian not interfere in the analyzed extreme event. Ocean eastern basin (Indo-Pacišc region) is not found; thus, this region is probably not a Rossby wave train source inˆuencing the South America—even though it is found to 3.2.5. Blocking Events. No blocking events a‘ecting the be an upper-level divergence source (see the red shaded area weather over South America were found during the period over the eastern basin). evaluated (šgure not shown). 12 Advances in Meteorology Wave activity flux (W ,W ) for May-Jun 2016 x y 30°N 15°N 0° 15°S 30°S 0 45°S –2 60°S –4 0° 30°E 60°E 90°E 120°E 150°E 180° 150°W 120°W 90°W 60°W 30°W 0° Figure 9: Wave activity ˆux (×10 ) for May-Jun 2016. �e arrows represent the wave ˆux W and W , and the shading represents the wave x y ˆux divergence, wave ˆux divergence indicates Rossby wave sources and convergence indicates Rossby wave sinks. Following Takaya and Nakamura [59], the wave ˆux is parallel to the phase velocity of the Rossby wave packages. 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 Date Date CHIRPS BRAMS 36 h CHIRPS WRF 72 h BRAMS 24 h BRAMS 48 h WRF 24 h WRF 96 h WRF 48 h (a) (b) 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 Date Date CHIRPS ETA 60 h ETA 108 h CHIRPS GFS 60 h GFS 108 h ETA 24 h ETA 72 h ETA 120 h GFS 24 h GFS 72 h GFS 120 h ETA 36 h ETA 84 h ETA 132 h GFS 36 h GFS 84 h GFS 132 h ETA 48 h ETA 96 h ETA 144 h GFS 48 h GFS 96 h GFS 144 h (c) (d) −1 Figure 10: Temporal evolution of the percentage of the SP region area with precipitation above the threshold of 5 mm·day (%) for CHIRPS and for di‘erent forecast times of the models (a) BRAMS, (b) WRF, (c) Eta, and (d) GFS, from 29 May to 9 June 2016. Dotted lines indicate the start (30 May 2016) and end (07 June 2016) of the period of interest. Area with precipitation (%) Area with precipitation (%) 28 May 28 May 29 May 29 May 30 May 30 May 31 May 31 May 1 Jun 1 Jun 2 Jun 2 Jun 3 Jun 3 Jun 4 Jun 4 Jun 5 Jun 5 Jun 6 Jun 6 Jun 7 Jun 7 Jun 8 Jun 8 Jun 9 Jun 9 Jun Area with precipitation (%) Area with precipitation (%) 28 May 28 May 29 May 29 May 30 May 30 May 31 May 31 May 1 Jun 1 Jun 2 Jun 2 Jun 3 Jun 3 Jun 4 Jun 4 Jun 5 Jun 5 Jun Sink←▽·W→source 6 Jun 6 Jun 7 Jun 7 Jun 8 Jun 8 Jun 9 Jun 9 Jun Advances in Meteorology 13 of a detailed verification will be presented and discussed in 4. Conclusions a future paper. A sequence of successive convective systems favoring Atypical precipitation events like the one analyzed in the atypical precipitation events, with high volumes of rain, present paper can happen again in the future, causing occurrences of tornadoes, and a microburst over South- further significant impacts for society and the economy. eastern Brazil took place during the dry season of 2016, more Studies to detect and evaluate the mechanisms contributing specifically, from May 30 to June 07, 2016 (9 days). 'ese to these anomalous events are important for the improve- anomalous events caused flooding, damages to houses and ment of the forecasts and mitigation of the associated buildings, and shortages of electricity and water in several consequences. Suggestions for future studies include in- places, with many injuries and two deaths documented. vestigating why the models did not predict the beginning of 'ese severe weather events were associated with a daily the precipitation period and whether this type of severe sequence of convective systems that formed preferentially weather will be frequent in the coming warmer climate. during early afternoon in the western part of SP state (red box in Figure 1) and also northwest of the SP region, Conflicts of Interest propagating along the low-level mean flow and growing as they moved into the region. 'e convective systems were 'e authors declare that there are no conflicts of interest embedded in an instable environment (high K index, high regarding the publication of this paper. Total Totals, low Showalter, and high wind shear) with an intense and persistent South American low-level jet (SALLJ) Acknowledgments (east of the Andes) advecting heat and moisture from the 'e authors are grateful to Dr. Jose´ Roberto Rozante, Amazon Basin into Southeastern Brazil. 'e exit region of the SALLJ was located over the SP region instead of Southern Dr. Jorge Lu´ıs Gomes, and Vinicius Matoso Silva from CPTEC/INPE for providing BRAMS and Eta datasets and to Brazil-northern Argentina (which is its typical exit location according to climatological studies). 'is displacement the Universidade Federal de Itajuba (UNIFEI) for providing WRF datasets. Tercio Ambrizzi was supported by CNPq and along the direction of the jet was likely driven by a sequence of extratropical cyclones that formed to the south of the FAPESP. region of interest over the Southwest Atlantic Ocean during the 9-day rainy period. 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