Tourism activities are highly dependent on climatological conditions. The climatological suitability of tourism destinations is investigated by using a Tourism Climate Index (TCI) that is frequently used by researchers. The TCI varies between 0 and 100 and is created by using temperature, relative humidity, sunshine duration, wind and precipitation data. For TCI, 100 is for ideal and 0 is for extremely unfavorable conditions for tourism. In this study, the meteorological data covering the period of 1981–2020 for 98 stations is used to calculate the TCI of each station for all seasons and months. The Mann-Kendall trend test is used for TCI behavior of the entire country and Sen Innovative Trend Analysis method is used for four famous tourism destinations. For summer, coastal regions have smaller TCI values than inland regions due to the high amount of relative humidity. Most stations have TCI values in the “Very Good” category or better. In spring and autumn, the TCI values fall into the “Acceptable” category or better. The winter is the season with smallest TCI values. For summer, 54 of 98 stations have a decreasing trend at different levels of significance and four of them have an increasing trend. In autumn, 30 stations have an increasing trend and two stations have a decreasing trend at standard levels of significance. Similarly, for spring, 20 stations have an increasing trend and one has a decreasing trend. During winter, 14 stations have an increasing trend while one has decreasing trend. The Sen Innovative Trend test shows an increasing trend on average for four famous tourism destinations during May–September months.

Two major earthquakes of 7.7 and 7.6 magnitudes hit a large region of east south of Türkiye on the same day. The first 7.7 MW earthquake occurred in Pazarcık, Kahramanmaraş on the 6th of Feb 2023 followed by an earthquake of 7.6 MW in Elbistan, Kahramanmaraş after 9 hours. Thousands of buildings collapsed in ten provinces in Türkiye and caused thousands of life losses and injuries. More than 14 million people were affected, and a lot of people lost their homes which makes the two major events the worst natural disaster of the century. This paper presents site observations on the seismic performance of the buildings in Hatay province that is the most affected city by these earthquakes. Site observations indicate that most of the collapsed buildings are old building stocks constructed before 1999 and collapsed in a pancake failure mode which increases life losses. In general, newly constructed buildings that were designed according to the new Turkish earthquake design code show good seismic performance. Reasons for failures and failure modes of old and new buildings were investigated.

Yağış, hidrolojik döngüde kritik bir rol oynar ve günlük hayatımızı çeşitli şekillerde etkiler. Ayrıca iklim değişikliğinin bir göstergesi olarak görülür ve yağış eğilimini tespit etmek, geleceğin yağış rejimi hakkında öngörüler yapmak için çok önemlidir. Bu amaçla, bu çalışmada Doğu ve Orta Karadeniz’de yer alan altı ilin meteoroloji istasyonlarından alınan yağış verileri trend analizine tabi tutulmuştur. Yağış eğilimini belirlemek için lineer trend testi ile parametrik olmayan Mann-Kendall testi kullanılmıştır. Trend analizi, altı il için aylık, mevsimlik ve yıllık dönemler bazında yapılmıştır. Çalışmanın sonucunda, Karadeniz havzasındaki altı ilin 1977-2016 arasındaki yağış verilerinde istatistiksel olarak anlamlı eğilimler saptanmıştır. Yıllık toplam yağışlarda üç ilde anlamlı artışlar tespit edilmiştir. Genel olarak yağışta artış eğilimi gözlenmiştir.

Renewable energy sources have gained great popularity due to the increasing importance given to a sustainable environment and economic development. Because of the environmental friendliness of renewable energy compared to fossil fuels, the tendency and investments in this field have increased. Wind energy comes into prominence among renewable energy sources because of its potential power that is used in various areas currently. Wind energy having stochastic nature is more sensitive to the extreme values of wind speed. Therefore, in order to create wind energy effectively, an accurate wind speed forecast is needed. In this study, nonlinear dynamical system approaches have been implemented by using reconstructing of phase space based on specifying minimum embedded dimension and delay time. In order to find out performance, different error metrics (MSE, RMSE, MAE, and MAPE) have been implemented. According to results, RMSE has been found 0.47 and 0.85 in hourly and daily dataset, respectively. Also, the correlation coefficient between the measurement and the obtained data set was as high as 0.92 in the hourly wind variable. In addition, a lesser correlation coefficient of 0.62 was found in the daily wind speed.