A global blocking climatology published by this group for events that occurred during the late 20th century examined a comprehensive list of characteristics that included block intensity (BI). In addition to confirming the results of other published climatologies, they found that Northern Hemisphere (NH) blocking events (1968–1998) were stronger than Southern Hemisphere (SH) blocks and winter events are stronger than summer events in both hemispheres. This work also examined the interannual variability of blocking as related to El Niño and Southern Oscillation (ENSO). Since the late 20th century, there is evidence that the occurrence of blocking has increased globally. A comparison of blocking characteristics since 1998 (1998–2018 NH; 2000–2018 SH) shows that the number of blocking events and their duration have increased significantly in both hemispheres. The blocking BI has decreased by about six percent in the NH, but there was little change in the BI for the SH events. Additionally, there is little or no change in the primary genesis regions of blocking. An examination of variability related to ENSO reveals that the NH interannual-scale variations found in the earlier work has reversed in the early 21st century. This could either be the result of interdecadal variability or a change in the climate. Interdecadal variations are examined as well.

Precipitation is a particularly important part of the Earth’s hydrological cycle and, therefore, is a necessary variable for maintaining natural balance. This study investigated past, present, and future changes in precipitation in the Marmara region, and examined the effects of global warming on this variable. The study period was from 1960 to 2020, and the climate data of 15 synoptic stations in the Marmara region were used for this purpose. To achieve the objectives of the study, linear and 6th order polynomial regression, ombrothermic and hythergraph diagrams, geostatistical models, Mann-Kendall test, Pearson correlation, standard Z-scores, and multi-layer perceptron artificial neural network models (MLP-ANN) were used to model and predict precipitation. The results of the linear regression analysis showed that of the 15 stations, 6 stations had an increasing trend, 6 stations had a trendless pattern, and 3 stations had a decreasing trend. In terms of periodic analysis, the main downward trend started in 1964 and continued until 1992, while the main periodic upward trend started in 1992 and continued until 2016. The synoptic stations in the Marmara region showed a lack of precipitation over six to seven months of the year, and the precipitation changes in the region were stronger than the temperature changes. In addition, the highest precipitation was observed on the southeast coast of the Black Sea, and the lowest precipitation was observed in the eastern parts of the region. Moreover, except for the Bilecik and Kocaeli stations, the changes in the long-term trend of precipitation at the other stations were significant. Among the 15 stations, only the Kocaeli and Sarıyer stations showed a positive correlation with global temperature during the annual period. In addition, the developed ANN model was accurate in simulating and predicting precipitation and showed an upward trend over the next seven years.

The outbreak of the novel coronavirus SARS-CoV-2 (hereafter COVID-19) has changed the daily routines of people around the world. When the first case was confirmed on 11 March 2020 in Turkey, the number of cases reached 4500 per day by 10 April in Turkey. Afterwards, the government declared more restrictive lockdown measures for 31 metropolitan cities starting 10 April, and it was implemented for the following weekends, national, and religious holidays. The change in concentrations of PM₁₀, PM_2.5, and NO₂ during these measures with respect to the pre-lockdown period, the same period in the previous years and for different levels of measures for the cities in the Marmara Region of Turkey was investigated in this study. The daily mean concentrations of PM₁₀, PM_2.5, and NO₂ obtained from 11 stations operated by the Ministry of Environment and Urbanization and Google mobility data are used in this study. Average PM_2.5 and NO₂ concentrations during the lockdown period declined with respect to the pre-lockdown period and the previous year for all stations. Average PM₁₀ concentrations during the lockdown of 8 of 11 stations declined, while the rest of the stations increased with respect to the pre-lockdown period. In 9 of the 11 stations, the average concentration of PM₁₀ decreased compared to the previous four years. In 7 of the 11 stations, the number of days exceeding WHO limit for PM₁₀ was decreased during the lockdown period with respect to the pre-lockdown period. For PM_2.5, the number of days exceeding WHO limit was decreased during the lockdown period compared to the pre-lockdown period for all the stations. For NO₂, the number of days exceeding WHO limit was decreased during the lockdown period compared to the pre-lockdown period for 7 of the 8 stations. There is a significant relationship between mobility decrease and NO₂ concentrations in large cities. The correlation coefficients are generally lower in small cities in the study region.

The relationship between the character of atmospheric blocking and surface temperature has not been studied in depth for Turkey. Here, these relationships are investigated for the period 1977–2016. The seasonal mean temperature anomalies for all stations during blocked days varies between −2.1 and 0.8°C. There are four main patterns representing the mean seasonal temperature anomalies for all stations during blocked and non-blocked days. The annual cycle for each group is nearly opposite, and this indicates the impact of blocking on observed temperature, as blocked days comprised 30% of the study period. When focusing on the spatial distribution of mean seasonal anomalies, the winter and fall seasons show that, almost all stations have negative temperature anomalies although anomalies are close to zero during warm seasons (spring and summer). The composite analysis shows that the western part of the country is strongly affected by cold air advection during upstream blocking events and the eastern part of the country is affected by warm temperature advection for downstream blocking events. There is a statistically significant (95% confidence level) negative correlation between blocking intensity and temperature anomalies in all seasons except spring. There is no relationship between both blocking duration and longitudinal extent and the seasonal mean temperature anomaly except during winter, which has a significant negative correlation. The temperature anomaly distribution stratified by season shows that strong positive anomalies are rarely observed in all seasons. Only winter and spring were associated with very strong positive anomalies and only at a few stations. Rex-type atmospheric blocking events are observed during the period of not only the maximum temperature anomaly but also for minimum anomalies. However, the location of the blocking event differed from the typical situation above, with the cold and warm events being located downstream and upstream of Turkey, respectively.