The climatological characterization of variables, allows us to understand the average behavior of atmospheric conditions, detect extremes and fluctuations, relationships of variables with geographic physical factors and is presented as another alliance for weather forecasting. The aim of this research is characterize the behavior of the meteorological variables at the Antonio Maceo International Airport in Santiago de Cuba, in the period 2017-2021. Antonio Maceo International Airport has the particularity of being located in a complex relief, exposed to marked breeze influences, and a significant number of wind shear pilot reports. The characterization was based on the concepts and graphs of descriptive statistics. The mean monthly distribution of the variables: temperature, relative humidity, atmospheric pressure, and wind speed and direction was obtained and represented. The distributions of the maximum monthly and annual accumulations, the cloud cover and the ranges of the reduction of the horizontal and vertical visibility were analyzed.

The city of Tampico has one of the main ports on the east coast of Mexico, on the Gulf of Mexico. The city is considered part of five human settlement nuclei metropolitan areas. It has a significant industrial, port, petrochemical, commercial, tourist, and residential zone, causing a significant positive economic impact in the region. These activities directly impact air quality with the presence of anthropogenic emission sources. Air pollution is one of the most investigated causes of health risk; early warnings protect the population and create public policies to avoid exposure and identify control measures to reduce atmospheric emissions. Therefore, the objective of this study is to analyze the effect of maritime traffic on air quality through a multiple regression effect using an artificial neural network (ANN), allowing to forecast the daily concentration of particulate matter (PM₁₀, PM_2.5, and PM₁) and ozone (O₃). The data set used the hourly average of the pollutant concentration levels and meteorological factors from May 1^st, 2021, to January 31^st, 2022, and the entry and exit of ships to the port area in the same range of dates. The regression model based on the ANN reaches an acceptable precision with a root- mean-squared error (RMSE) of 5.9554 and a mean absolute error (MAE) of 4.5732.

The objective of the present study is to estimate the duration of extreme thermal bioclimate conditions in and around Kolkata, one of the highly densely populated cities in India. The biometeorological conditions have been calculated by Physiologically Equivalent Temperature (PET) using RayMan model at 0530 h and 1430 h (IST) based on meteorological data for the stations Kolkata (Alipore), Dum Dum and Diamond Harbour for the period January, 2020 to December, 2021. Dum Dum is located to the north of Kolkata and Diamond Harbour is situated to the south of Kolkata. The meteorological data have been retrieved from the station data measured by Indian Meteorological Department (IMD). The atmospheric variables required to calculate the PET index are air temperature, relative humidity, cloud cover and wind speed. A recent study reported that stations outside Kolkata suffer warmer human thermal stress conditions. To account for the prolonged thermal stress periods, PET with greater than 40 ° C is categorized as an episode if it turns up consecutively for more than 5 days. The results from this analysis computes no such event in any of the investigated stations at 0530 h (IST). At 1430 h, the frequency of occurrences of PET with > 40 ° C for the period between 5 to 10 days is 12 for Diamond Harbour followed by Dum Dum (5) and Kolkata (3). Similar pattern is observed when the frequency is calculated for the duration between 11-20 days. The frequency of such duration is 6, 3, 2 for Diamond Harbour, Dum Dum, Kolkata respectively.

Monitoring clouds is necessary for many applications, such as aircraft navigation, astronomical observations and others. The height of the top and the bottom of the clouds can be retrieved from satellites and ground-based stations, respectively, by measuring their brightness temperature. In this context, ground-based infrared cameras offer interesting information about the spatial distribution of clouds and the height of their bases. Some atmospheric gases interact significantly with the radiation emitted by clouds, aerosols, atmospheric gases and the Earth’s surface, so an atmospheric correction is needed to obtain reliable estimates of a cloud base. In this study, the influence of water vapour and carbon dioxide on the downward radiance measured by a FLIR infrared camera on a height variable cloudy scenario is analyzed. The FLIR A325SC camera spectral response function is considered, and standard atmospheric profiles are used. The infrared absorption and emission of the profiles of water vapour and carbon dioxide is estimated by the Python package ‘RADIS’. The results show a positive net atmospheric effect on the downward radiance for all the standard atmospheric profiles considered, which indicates a higher emission contribution of the atmospheric gases compared to the absorption. However, the magnitude of the atmospheric effect significantly depends on the specific atmospheric profile. For example, the atmospheric net emission effect on the downward radiation for high clouds with a Tropical atmospheric profile is around 30 W/m²·sr, whereas for a Subarctic-Winter atmospheric profile is less than 8 W/ m²·sr. Main results show that the atmospheric effect notably depends also on the vertical gradient, being particularly high for the Tropical profile. Moreover, regarding a specific profile, the atmospheric correction becomes more important for high clouds than for medium or low clouds. Therefore, the atmospheric correction should not be neglected if accurate estimations of the cloud height are to be obtained.

Carbonaceous species [organic carbon (OC), elemental carbon (EC), elemental matter (EM), primary organic carbon (POC), secondary organic carbon (SOC), total carbon (TC), and total carbonaceous matter (TCM)] of PM_2.5 were estimated to study the seasonal variability and annual variability of carbonaceous aerosols (CAs) in megacity Delhi, India from January 2012 to April 2021. The annual average concentrations (± standard deviation) of PM_2.5, OC, EC, TC, EM, TCM, POC, and SOC were estimated as 127±77, 15.7±11.6, 7.4±5.1, 23.1±16.5, 8.2±5.6, 33.3±23.9, 9.3±6.3 and 6.5±5.3 µg m^-3, respectively during the entire study period (10-year). During the entire sampling period of PM_2.5, the average CAs accounted for 26% of the PM_2.5 concentration. Significant seasonal variations in concentrations of PM_2.5, OC, EC, POC, SOC, and TCM were recorded with maxima in post-monsoon and minima in monsoon seasons. A linear relationship between OC and EC concentrations, and OC/EC, as well as EC/TC ratios, suggested that vehicular emissions (VE), fossil fuel combustion (FFC), and biomass burning (BB) could be major sources of CAs of PM_2.5 at megacity Delhi, India.

Aerosol Optical Depth (AOD) was observed at Surat, Gujarat (INDIA), Coastal region near the Tapi River at the Gulf of Khambhat. Using MODIS, Satellite data for Aerosol Optical Depth (AOD) have been collected from the Giovanni site developed by NASA. Results of the data for the 5 years (January to December 2015-2019) have been discussed here. Aerosol Optical Depth characteristics are related to changes in the regional meteorological conditions. The data collected from January to December 2015-2019 indicated annual average AOD variation. The mean annual variations of Aerosol Optical Depth (AOD) indicated maxima around the monsoon. The lowest values of the seasonal mean Aerosol Optical Depth (AOD) observed during the pre-monsoon and relatively moderate AOD were observed during the winter season. Variation of aerosol optical depth (AOD) in the post-monsoon season shows similar variation as of winter and pre-monsoon in 2016. Values increased afterward and reached maxima in both Aqua and Terra observations, which is mostly related to the changes in the local boundary layer.

In this work, a statistical correction of the distribution of solar radiation in Cuba is obtained, estimated by the Heliosat method, using the images collected from the GOES-13 satellite, for the period 2012-2017. The need arises for an improvement in the update of the distribution of solar radiation in the country, because taking into account that the last characterization for the national territory, of the distribution of this resource, refers to the research of the year 2018 and prior to this, to that of the 1986-1991 period; when the maps obtained are compared with the values ​​of the stations, a certain overestimation of the solar radiation values ​​is observed. An improvement in the estimation of said resource, is required as a result of the problem raised in question, given the importance of this information as a renewable source of energy and its use in the evaluation of the helioenergic potential of Cuba.

In the East European Plain, the Early 20th Century Warming (ETCW) was marked by an unprecedented rise and fall in the annual runoff of the Volga and Northern Dvina rivers in 1920-1940, recorded in the long-term, since 1882, hydrological time-series. Analysis of the temperature and precipitation anomalies and Palmer Drought Severity Index, basing on observational data (CRUTEM.5, GISS, CRU TS4.05, CRU-scPDSI) and 20th century reanalysis (ERA20C, CERA20C), proves the uniqueness of the period 1920-1940 associated with large-scale humidification extreme anomalies of both signs.

Patterns of surface atmospheric pressure anomalies (Had SLP.2), obtained for the years of maxima (1936 and 1938) and minima (1926-1928) of the drought conditions during the summer months (July-August) averaged for the sector 20-60N, 45-70 E, as well as the difference between them, indicate the circulation factors of the drought conditions of the 1930s and the accompanying remote anomalies of SLP. Propagation of the northern tropical belt eastward, beyond the Ural Ridge, and northward, to the Arctic coast and the Barents Sea, which corresponds to the extensive anticyclonic anomaly SLP centered over the Middle Urals results to conditions for the advection of hot and dry air mass from North Africa toward high latitudes. The anticyclonic anomaly is accompanied by a cyclonic anomaly over the circumpolar zone, spreading to the northeast of the Atlantic and able to intensify advection of tropical air masses through the East European Plain to the Arctic coast and Barents Sea.

The positive phase of the Atlantic Multi-decadal Oscillation considered as one of the main cause of the ETCW, can impact the formation of the circulation dipole mentioned above, as well as the loss of sea ice in the Barents and Kara Seas. The spatial features of the differences of sea ice concentration indicates the influence of the variability in the warm Atlantic water inflow to the Barents and Kara Seas. In turn, sea ice decline in the Barents Sea in spring can lead to a formation of cyclonic vortex over Barents Sea. This atmosphere circulation response, in term, can increase oceanic inflow of warm and salty Atlantic water masses. This positive feedback causes to further sea ice loss.

The concentrations of nitrogen dioxide (NO₂) and ozone (O₃) were determined at five indoor environments (corridor, living area, bedroom, kitchen, bathroom) of two homes located in different regions of EskiÅŸehir, Türkiye. Home 1 is located in the city center and urban residential area while Home 2 is located in a suburban area. In order to determine the indoor and outdoor (I/O) ratios of the pollutants, outdoor sampling was also carried out simultaneously with indoor sampling. Sampling studies were performed in one-day periods in four seasons by using passive sampling method. The indoor NO₂ concentrations varied between 8.80 - 124.18 µg/m³ while O₃ concentrations varied between 3.69 – 169.00 µg/m³. The highest NO₂ concentrations were determined in the kitchens both in two homes. This can be due to the intensive cooking activities carried out in the kitchens. The variation of O₃ concentrations in the measured indoor environments varied in homes. When the outdoor concentrations were examined, it was seen that NO₂ concentrations were higher in Home 1 and O₃ concentrations were higher in Home 2 in all seasons. This result is related to the location of the homes. The I/O ratios for NO₂ were generally > 1 for the kitchens. Also, all I/O ratios for NO₂ in Home 2 were found > 1 in autumn season. The I/O ratios for O₃ were found < 1 in both homes, except for Home 1, in the autumn season. Seasonal variations of the pollutant concentration levels were also observed for indoor environments. Indoor NO₂ concentrations, especially in Home 1, and O₃ concentrations, especially in Home 2, were higher in spring and summer compared to other seasons. The reason for this is thought to be more active natural ventilation due to the warming of the weather in these seasons.

Results of studying the impact of solar activity on variations in the atmospheric electric field, thunderstorm activity and the lower ionosphere, obtained at the Tien- Shan high-mountain experimental complex (height 3340 m) and the Alma-Ata ionospheric station [43.25N, 76.92E]) in 2005-2015 are presented in this work. It has been established that a decrease in the intensity of galactic cosmic rays at low magnetic activity lowers the average level of the electric field by 40÷60 V/m. Large magnetic storms affect the average level of the electric field, and also cause its fluctuations in the minute range (10^-3 ÷10^-1) Hz. Tendency has been established for the appearance of thunderstorm activity with a delay of 1-2 days or more after the impact on the Earth's atmosphere and magnetosphere of geoeffective coronal mass ejections (CME), high-speed solar wind streams (HSS). Noticeable changes in the state of the lower ionosphere and geomagnetic field (fmin and Dst) are observed during these periods. Cases of increasing fmin values and critical frequencies of the sporadic Es layer were recorded under conditions of low geomagnetic activity during thunderstorms with powerful positive discharges or in combination with negative discharges. Long-term anomalous changes in the electric field are observed on the eve of and during significant earthquakes with a magnitude of more than 5.0, as well as before weak earthquakes, but with epicenters located in the immediate vicinity of the electric field detector.