Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Stratospheric temperature is an important climatic factor regionally and globally. This paper investigates temperature trends in the lower stratosphere at 50 hPa (T50), the mid-stratosphere at 30 hPa (T30), and the upper stratosphere at 10 hPa (T10), as well as their impacts on Atlantic Ocean sea surface temperature (SST) and Saudi Arabian surface air temperature (SAT) during the entire winter seasons of 1979-2019. The results show significant cooling for the T50 linear trend, progressive cooling for the T30 linear trend, and cooling for the T10 linear trend during the study period over Saudi Arabia. The results also indicate a significant nonlinear cooling trend for stratospheric temperature at T50 and T30, while a weak cooling at T10 is observed. Abrupt climatic changes towards warmth exist at all three levels of stratospheric temperature, which occur in 1992 for T50 and T30 and in 1983 for T10. These abrupt climate changes may be related to volcanic eruptions. Our results also indicate that a strong negative relationship exists between T50 and the SST of the tropical South Atlantic (TSA) and the Atlantic Multi-Decadal Oscillation (AMO), while T30 indicates a statistically negative relationship with the AMO. The lead-lag cross-correlation suggests that the SST of the Atlantic Ocean (tropical North Atlantic [TNA], TSA, and AMO) are linked to stratospheric temperatures at three lead winters. As a result of the teleconnection between SAT and stratospheric temperature over Saudi Arabia, the coupling of these two features occurs in winter, especially in the lower to mid-stratosphere layers.

Friction velocity (u*) is an important velocity scale used in the study of engineering and geophysical flows. The widespread use of 2D sonic anemometers in modern meteorological stations makes the estimation of u* from just the horizontal components of the velocity a very attractive possibility. The presence of different wind regimes (such as sea breezes in or near coastal zones) causes the turbulent parameters to be dependent on the wind direction. Additionally, u* depends on atmospheric stability, whch makes the estimation of u* from 2D measurements very difficult. A simple expression is proposed, and then tested with data from six independent experiments located in coastal zones. The results show that it is possible to estimate friction velocity from 2D measurements using the turbulence intensity as a proxy for u*, reducing substantially the sensitivity to the wind direction or atmospheric stability, with small root mean squared errors (0.06 < RMSE < 0.097) and high correlation coefficients (0.77 < r2 < 0.95).

This work aimed to identify and quantify greenhouse gases (GHG) emissions of a steel factory, considering the importance of these data in the context of large global GHG emissions. As a result, Scope 1 emissions were identified as the highest in the industry, representing more than 89% of total emissions in CO2eq. This scenario is mainly identified a result of the Brazilian energy matrix configuration, which contributes to reduce Scope 2 emissions. The used methodology (GHG Protocol v. 2018.1.4) proved to be appropriate for calculating emissions within a broader report (annual amount). However, in order to develop an indicator for the organization, with monthly detailed data, it was necessary to adapt the tool, which is the differential of this work.

This study simulates an unusual extreme rainfall event that occurred in Salvador city, Bahia, Brazil, on December 9, 2017, which was named subtropical storm Guará and had precipitation of approximately 24 mm within less than 1 h. Numerical simulations were conducted using the Weather Research and Forecasting (WRF) model over three domains with horizontal resolutions of 9, 3, and 1 km. Different combinations of seven microphysics, three cumulus, and three planetary boundary layer schemes were evaluated based on their ability to simulate the hourly precipitation during this rainfall event. Statistical indices (MB = –0.69; RMSE = 4.11; MAGE = 1.74; r = 0.55; IOA = 0.66; FAC2 = 0.58) and time series plots showed that the most suitable configurations for this weather event were the Mellor-Yamada-Janjić, Grell-Freitas, and Lin formulations for the planetary boundary layer, cumulus, and microphysics schemes, respectively. The results were compared with the data measured at meteorological stations located in Salvador city. The WRF model simulated well the arrival and occurrence of this extreme weather event in a tropical and coastal region, considering that the region already has intense convective characteristics and is constantly influenced by sea breezes, which could interfere in the model results and compromise the performance of the simulations.

Itabira has in its territory the largest complex of opencast mining in the world, located close to residential areas of the city. The air quality monitoring network installed in the city is the main source of particulate matter (PM) emission data. However, these air quality stations only cover the areas near the mines and do not measure fine particulate matter (PM2.5). Thus, a first field campaign was carried out to characterize PM in the city and to compare high volume data from air quality stations with the dichotomous air sampler data. Results of trajectories’ cluster analysis showed a long-range transport of aerosols during the sampling days from northeast (84% of the trajectories), east-southeast (12%), and south-southwest (3%) directions. Regarding the meteorological conditions during the sampling days, negative correlations were seen between coarse particulate matter (PM10) from mostly air quality stations and all meteorological parameters (but temperature). Results of the X-ray fluorescence and principal component analyses showed that the main trace elements in the coarse (PM2.5-10) and fine modes (PM2.5) are iron and sulfur, associated with emissions from mining activities, air mass transport from regional iron and steelmaking industry activities, vehicle emissions, local and regional biomass burning, and natural biogenic emissions. This work is the first assessment of source apportionment done in the city. Comparisons with other studies, for some large metropolitan areas, showed that Itabira has comparable contributions of sulfur, iron and elements such as copper, selenium, chromium, nickel, vanadium and lead.

Time and intensity-specific very short-term forecasting or nowcasting is the biggest challenge faced by an aviation meteorologist. Ground-based microwave radiometer (MWR) has been used for nowcasting convective activity and it was established that there is a good comparison between thermodynamic parameters derived from MWR and GPS radiosonde observations, indicating that MWR observations can be used to develop techniques for nowcasting severe convective activity. In this study, efforts have been made to bring out the efficacy of MWR in nowcasting thunderstorms and fog. Firstly, the observations of MWR located at Palam, New Delhi, India have been compared with the nearest radiosonde data to ascertain the variation in respective profiles. Large differences were found in relative humidity (RH), whereas temperatures from MWR were found to be close to radiosonde observed temperature up to 3.5 km. Subsequently, the scatter plots and correlation coefficients of thermodynamic indices/parameters indicated that most of the parameters are either not correlated or have moderate correlation only for 12:00 UTC profiles. The superepoch technique of lagged composite for various thermodynamic indices/parameters to obtain a combined picture of all the thunderstorm and dense fog cases on the time series could not determine any pattern to predict thunderstorm and dense fog with lead time of 2-4 hours. MWR profile for a case of occurrence of thunderstorm was analyzed. No significant variation was observed in most of the indices (as calculated from MWR observed parameters) prior to the occurrence of thunderstorm. RH at freezing level and between 950 and 700 hPa levels were the only parameters, which increased four hours prior to the occurrence.

The assessment of atmospheric corrosion is currently based on the study of atmospheric basins (AB). Modeling atmospheric corrosion in many cases involves the measurement of several meteorological and atmospheric pollution parameters, specifically temperature, relative humidity, chloride, and sulfur dioxide, making the estimation process more complex. However, for the Western Central Valley (WCV) in Costa Rica, a low-pollution AB, it is possible to develop simplified atmospheric corrosion models based on a small number of atmospheric parameters. In this paper, the meteorological variables of the study region were analyzed in terms of their dependency on altitude and their applicability in the development of a simplified model to predict the corrosion rate (Vcorr). The output of the predictive model was compared with the standard model of ISO 9223:2012, showing a higher skill and giving reliable results for a wide interval of altitudes. 

A split-window algorithm has been used in the Ilam dam watershed to determine the relationship between land surface temperature (LST) and types of land use. Landsat satellite images of the TM sensor for 1990, 1995, 2000, 2005 and 2010 and Landsat 8 (OLI Sensor) for 2015 and 2018 are used. After geometric and radiometric corrections of satellite images, land use maps are extracted by using the fuzzy ARTMAP method. An accuracy assessment showed that the highest value of the kappa coefficient was 94% with a total accuracy of 0.95 for 2015, and the lowest kappa coefficient value was 87% with a total accuracy of 0.9 for 1990. The high values of these coefficients indicate the acceptable accuracy of using Landsat’s remote sensing data for land use detection. The most important land use change is related to dense forest and sparse forest land uses, with decreases of 20.07 and 17.04%, respectively. The minimum LST measures in 1990, 2010, and 2018 in dense forest are 21.27, 30.55 and 33.82 ºC, respectively. The maximum LSTs for the sparse forest land use in 1990 and 2010 are 52.48 and 56.09, and 56.10 ºC for the dense forest land use in 2018. As a result, the average LST in agricultural lands was lower than in sparse forest and rangeland;, which is mainly due to the high moisture content and the greater evapotranspiration rate. Land use/land cover variations from 1990 to 2018 show that all land uses have experienced an increase in LST.

The COVID-19 pandemic introduced a significant decrease in industrial activities and other anthropogenic interventions on the environment, followed by a reduction of the emission of pollutant gases and aerosols. Monitoring of air quality is commonly performed through automatic stations, which can provide nearly real-time, accurate information. However, stations located in urban areas are subject to maintenance problems and extensive coverage for large areas is not feasible. As an alternative approach, data from orbital sensors can provide useful information for large areas at a low cost. Consequently, this study aimed to analyze the partial COVID-19 lockdown effect in atmospheric pollutants and its indirect impact in UV radiation in Rio Grande do Sul, Brazil. Data on concentrations of nitrogen dioxide (NO2), total ozone (O3), and ultraviolet index (UVI) acquired by the OMI sensor aboard the Aura satellite were accessed for May, for the entire period 2010 to 2018, 2019, and 2020. Differences between these time series were calculated. Results showed significant reductions in NO2 in most of the study area by as much as 33.9%, followed by increases in total ozone of up to 3.5% and the UVI by up to 4.8%. Although NO2 plays a fundamental role in stratospheric chemistry, our results suggest that its decrease in 2020 was not directly responsible for the increase in total O3; however, NO2 was partially the cause for the increase in UVI, which in turn led to the heating of the stratosphere, generating an increase in O3.

Changes to the tropical eastern North Pacific Intraseasonal Oscillation (ISO) at the end of the 21st century and implications for tropical cyclone (TC) genesis are examined in the Shared Socioeconomic Pathways (SSP585) scenario of the Coupled Model Intercomparison Project phase 6 (CMIP6) data set. Multimodel mean composite low-level wind and precipitation anomalies associated with the leading intraseasonal mode indicate that precipitation amplitude increases while wind amplitude weakens under global warming, consistent with previous studies for the Indo-Pacific warm pool. The eastern North Pacific intraseasonal precipitation/wind pattern also tends to shift southwestward in a warmer climate, associated with weaker positive precipitation anomalies near the coast of Mexico and Central America during the enhanced convection/westerly wind phase. Implications for the modulation of TC genesis by the leading intraseasonal mode are then explored using an empirical genesis potential index (GPI). In the historical simulation, GPI shows positive anomalies in the eastern North Pacific in the convectively enhanced phase of the ISO. The ISO’s modulation of GPI weakens near the coast of Mexico and Central America with warming, associated with a southward shift of GPI anomalies. Further examination of the contribution from individual environmental variables that enter the GPI shows that relative humidity and vorticity changes during ISO events weaken positive GPI anomalies near the Mexican coast with warming and make genesis more favorable to the southwest. The impact of vertical shear anomaly changes is also to favor genesis away from the coast. These results suggest a weaker modulation of TCs near the Mexican Coast by the ISO in a warmer climate.