Fog event affects air, land and sea transportation adversely by reducing visibility, thus causes economic loss. Besides, it has an important role in construction planning. For this reason, it is very important to predict visibility before and during fog events. In this study, fog visibility prediction was made with artificial neural networks and validations were made for Esenboğa Airport. Temperature, dew point temperature, pressure, wind speed and relative humidity, which are considered to be the most important parameters for fog occurrence, were used for 2013-2015 years to train an artificial neural network. We selected only January, February, November and December months, as those are the foggiest months for Esenboğa airport. Correlation of test part was evaluated after training. Then, whole data for 2016-2017 years (regardless of fog existence) were used for validation of the output again. As a result, we found a correlation value (R) of 0.80 for the test part of 2013-2015 years; R=0.41 and root mean square error (RMSE) of 2652m for all data of the 2016 year; and R = 0.53 and RMSE = 2464m for all data of the 2017 year. The error rate (R = 0.80) for the test part (2013-2015) was found acceptable. However, consistencies for the years 2016 and 2017, when all data were tested regardless of fog existence were found below expectations.

ÖZETMeteorolojik kuraklık, küresel bir doğal afet olarak bilinmekle birlikte, ekonomik ve çevresel olarak önemli etkileri bulunmaktadır. Türkiye'nin de içerisinde bulunduğu Doğu Akdeniz Havzası, yağış azlığının beraberinde getirdiği kuraklık olayları ile baş başa kalmakta ve çeşitli problemler yaşamaktadır. Tüm bu problemler yağış ölçümünün olmadığı alanlarda daha sıkıntılı hale gelmektedir. Bu nedenle, kuraklık şiddetinin eksiksiz takibi ve gözlemi özellikle insan sağlığının korunması ve ekonomik kayıpların önlenmesi açısından çok önemlidir.

Forest fires are one of the natural disasters that concern all countries in the globalizing world in terms of their effects and consequences. Fires are a vital threat that causes the burning of millions of hectares of forest areas worldwide every year, causing loss of life and property. An early warning system helps people respond to dangers promptly and appropriately. In the scope of this study, the forest fires in Antalya-Manavgat (starting on 28 July 2021 and ending on 6 August 2021) analyzed using the meteorological early warning system (MEUS), which is developed by the employees of the Turkish State Meteorology Service, and the performance of the model products was assessed. Concordantly, the association between the weather conditions in the region and the forest fire was analyzed. Besides, the analysis of the model output products is also considered. By examining the synoptic models, hourly meteorological data and MEUS warnings taken two days before the forest fire selected in the Antalya-Manavgat region, the probabilities created by the meteorological variables that may be effective in the preparation of fire conditions in the region were evaluated.

The objective of this study is to investigate the meteorological, agricultural and hydrological drought of Muğla city for the period of 1960-2018 as well as to analyse precipitation trend. Monthly total precipitation data for the period of 1960-2018 belonging to Muğla meteorological station obtained from the Turkish State Meteorological Service were used in this study. Run (Swed-Eisenhart) homogeneity test, Mann-Kendall method and Standardized Precipitation Index method were applied to precipitation data. In addition, the severity and duration of droughts were examined. As a result, long years' precipitation and drought trend were demonstrated for Muğla city. The annual total precipitation for Muğla city in the period 1960-2018 was found to be 1180.2 mm. The lowest amount of precipitation in the study period was 564.6 mm in 2008 and the highest amount of rainfall was 1805 mm in 1969. In the province of Muğla, the number of the humid months was slightly higher than the other classes. In the province of Muğla, the numbers of the mildly humid and moderately dry months were slightly higher than the other classes. It was seen that the numbers of humid and dry months in Muğla province were mostly clustered in mildly humid, moderately humid, mildly dry and moderately dry classes. In addition, analyzes show that drought is less repetitive as the time period increases, but has a longer duration effect. Total drought severity and total drought duration of Muğla station on scales basis coincided with almost similar years. However, in the 3-monthly Standardized

Turkey is one of the most sensitive regions to climate change. Drought events triggered by climate change occur frequently in the region and cause important environmental problems. The agricultural sector and crop yield are among the areas that are adversely affected. In this study, meteorological and hydrological drought situation and precipitation trend is studied with SPI and SPEI methods by using Nevşehir Center and Ürgüp stations. Besides, the severity and duration of long-lasting strong droughts in the region are studied. The most important negative effects of drought events are seen in the agricultural sector on crop production. In order to analyze this effect, the yield values of agricultural products grown in the region were obtained from Turkish Statistical Institute (TUIK) and standardized with Z-Score method. Afterwards, the impact of drought events on the yield of agricultural products grown in the region are examined