Context. The most primitive metal-poor stars are important for studying the conditions of the early galaxy and are also relevant to big bang nucleosynthesis. Aims. Our objective is to find the brightest (V < 14) most metal-poor stars. Methods. Candidates were selected using a new method, which is based on the mismatch between spectral types derived from colors and observed spectral types. They were observed first at low resolution with EFOSC2 at the NTT to obtain an initial set of stellar parameters. The most promising candidate, 2MASS J18082002−5104378 (V = 11.9), was observed at high resolution (R = 50 000) with UVES at the VLT, and a standard abundance analysis was performed. Results. We found that 2MASS J18082002−5104378 is an ultra metal-poor star with stellar parameters T eff = 5440 K, log g = 3.0 dex, v t = 1.5 km s −1 , [Fe/H] = −4.1 dex. The star has [C/Fe] < +0.9 in a 1D analysis, or [C/Fe] +0.5 if 3D effects are considered; its abundance pattern is typical of normal (non-CEMP) ultra metal-poor stars. Interestingly, the star has a binary companion. Conclusions. 2MASS J1808−5104 is the brightest (V = 11.9) metal-poor star of its category, and it could be studied further with even higher S/N spectroscopy to determine additional chemical abundances, thus providing important constraints to the early chemical evolution of our Galaxy.

Abstract. Organised cloud bands are important features of tropical and subtropical rainfall. These structures are often regarded as convergence zones, alluding to an association with coherent atmospheric flow. However, the flow kinematics is not usually taken into account in classification methods for this type of event, as large-scale lines are rarely evident in instantaneous diagnostics such as Eulerian convergence. Instead, existing convergence zone definitions rely on heuristic rules of shape, duration and size of cloudiness fields. Here we investigate the role of large-scale turbulence in shaping atmospheric moisture in South America. We employ the finite-time Lyapunov exponent (FTLE), a metric of deformation among neighbouring trajectories, to define convergence zones as attracting Lagrangian coherent structures (LCSs). Attracting LCSs frequent tropical and subtropical South America, with climatologies consistent with the South Atlantic Convergence Zone (SACZ), the South American Low-Level Jet (SALLJ) and the Intertropical Convergence Zone (ITCZ). In regions under the direct influence of the ITCZ and the SACZ, rainfall is significantly positively correlated with large-scale mixing measured by the FTLE. Attracting LCSs in south and southeast Brazil are associated with significant positive rainfall and moisture flux anomalies. Geopotential height composites suggest that the occurrence of attracting LCSs in these regions is related with teleconnection mechanisms such as the Pacific–South Atlantic. We believe that this kinematical approach can be used as an alternative to region-specific convergence zone classification algorithms; it may help advance the understanding of underlying mechanisms of tropical and subtropical rain bands and their role in the hydrological cycle.

This paper presents a simple methodology to identify sea breeze frontal passage in the city of São Paulo, Brazil, based in hourly wind direction data. Fifty‐year time series of annual frequency of sea breeze frontal passage and of its time of arrival in São Paulo are generated and related to global climate indicators and local variables. The frequency of occurrence and time of arrival of sea breeze shows long‐term oscillations in the interannual and decadal time scales. Multiple regression is used to identify the variables that explain the observed variance of both frequency of occurrence and timing of the sea breeze in São Paulo. Local variables such as air temperature in São Paulo and sea surface temperature (SST) in the vicinity of the coast explain more than 95% of the total R2 (R2 = 51%) in a multiple regression model of the frequency of sea breeze frontal passage. Global climate indices such as the Atlantic Multidecadal Oscillation, the Southern Oscillation Index (SOI) and the Pacific Decadal Oscillation explain about 85% of the total R2 (R2 = 52%) in a multiple regression model of the time of arrival of the sea breeze in São Paulo. The sea breeze circulation is shown to impact the rainfall in São Paulo and vicinity and to be associated with extreme rainfall events.

Precipitation often happens along organised filaments or bands of moisture such as convergence zones. Recent regional studies have shown that these moisture filaments arise from synoptic-scale mixing features known as attracting “Lagrangian Coherent Structures” (LCSs). In this study, we present a climatology of synoptic-scale mixing and investigate its co-variability with precipitation on temporal scales ranging from weekly to interannual. We characterise mixing with the Finite-time Lyapunov Exponent (FTLE), a measure of parcel deformation, in ERA5 reanalysis data between 1980 and 2009. Attracting LCSs are identified as ridges of the FTLE. At the interannual time scale, we compare El Niño and La Niña events and find that composites of precipitation and mixing anomalies share similar spatial patterns. We also compare summer and winter seasons and find that composites of seasonal-mean precipitation and mixing anomalies present similar characteristics; i.e., precipitation is particularly intense (weak) where mixing is strong (weak). In particular, these patterns closely match the typical signatures of the Intertropical Convergence Zone (ITCZ) and monsoon systems and the migrations of extratropical cyclone tracks. At the subseasonal scale, we employ daily composites to investigate the influence of the Madden-Julian Oscillation and the North Atlantic Oscillation on the mixing regimes of the Atlantic and East Pacific; our results indicate that these oscillations control the synoptic-scale horizontal mixing and the occurrence of LCSs as to suppress or enhance precipitating systems like the ITCZ and the South Atlantic Convergence Zone. The results presented in this first climatology of synoptic-scale mixing and LCSs indicate that these are powerful diagnostics to identify circulation mechanisms underlying precipitation variability.

The role of particulate matter (PM) in the COVID-19 pandemic is currently being discussed by the scientific community. Long-term (years) exposure to PM is known to affect human health by increasing susceptibility to viral infections as well as to the development of respiratory and cardiovascular symptoms. In the short-term (days to months), PM has been suggested to assist airborne viral transmission. However, confounding factors such as urban mobility prevent causal conclusions. In this study, we explore short-term relationships between PM concentrations and the evolution of COVID-19 cases in a number of cities in the United States of America. We focus on the role of PM in facilitating viral transmission in early stages of the pandemic. We analyzed PM concentrations in two particle size ranges, <2.5 μm, and between 10 and 2.5 μm (PM2.5 and PM10 respectively) as well as carbon monoxide (CO) and nitrogen dioxide (NO2). Granger causality analysis was employed to evaluate instantaneous and lagged effects of pollution in peaks of COVID-19 new daily cases in each location. The effect of pollution in shaping the disease spread was evaluated by correlating the logistic growth rate of accumulated cases with pollutants concentrations for a range of time lags and accumulation windows. PM2.5 shows the most significant results in Granger causality tests in comparison with the other pollutants. We found a strong and significant association between PM2.5 concentrations and the growth rate of accumulated cases between the 1st and 18th days after the report of the infection, peaking at the 8th day. By comparing results of PM2.5 with PM10, CO and NO2 we rule out confounding effects associated with mobility. We conclude that PM2.5 is not a first order effect in the cities considered; however, it plays a significant role in facilitating the COVID-19 transmission.