Sevinc Asilhan Sirdas

Tornadoes are the most violent and destructive of all the severe weather phenomena that localized convective storms produce. There is a requirement in operational meteorology increasing nowadays that an indicator index which allows to reduce the uncertainty of severe convective storms and tornadoes in the scope of climate change adaptation strategies. The main intention is not to replace or substitute mesoscale modeling approaches, or composite indexes, but to warn operationally to draw attention to the Eastern Mediterranean and Türkiye in particular a few days in advance. The development of some indicators using atmospheric variables can undertake a crucial role by enabling such numerical models to be run only at certain time intervals, thus enduring lower computational costs. In this study, Eastern Mediterranean oscillation index (EMEDOi) has been developed in order to be able to detect the presence of ULLs (upper-level low) and frontogenesis approach is employed for selected tornadic storm events in Türkiye. EMEDOi has 7 different its variations (members) which these members have been developed to detect differences depending on the entry directions of cyclones and storms influencing Türkiye from the west of the country. In line with the GDAS data analysis, values of geopotential height are derived for the requirement of EMEDOi in a limited area. A few of the results from the study are as in the following: 86% of the trained tornado events revealed that the EMEDO-Oper index was in negative phase at the time a tornado was reported, regardless of whether the events featured a supercell mesoscale convective storm or a frontal movement. The hourly period until the local minimum is obtained can be described and characterized as the process by which the EMEDO-Oper index value decreases continuously. The time required to reach the local minimum varies based on the tornado occurrence. Based on the tornadic storm scenario in the test cluster in 2022 and the train cluster, this timeframe is predicted to be roughly 33.2 h on average. In western Türkiye, there is a 79% chance of a tornado occurring between six and forty-two hours after the EMEDO-Oper index reaches its local minimum. In particular, the projected chance for this period is 63% between 12 and 30 h after the local minimum is obtained. Besides, the majority of the tornado incidents with EMEDO-Oper values below − 0.75 were evaluated. After an EMEDO-Oper index value falls below that threshold, it is likely to forecast the risk period of a tornado in Türkiye with a probability of 79% and the local minimum point must be identified.

Tornadoes are the most violent and destructive of all the severe weather phenomena that localized convective storms produce. There is a requirement in operational meteorology increasing nowadays that an indicator index which allows to reduce the uncertainty of severe convective storms and tornadoes in the scope of climate change adaptation strategies. The main intention is not to replace or substitute modeling approaches, or composite indexes, but to warn operationally to draw attention to the Eastern Mediterranean and in particular a few days in advance. The development of some indicators using atmospheric variables can undertake a crucial role by enabling such numerical models to be run only at certain time intervals, thus enduring lower computational costs. In this study, Eastern Mediterranean Oscillation Index () has been developed in order to be able to detect the presence of (Upper Level Low) and approach is employed for selected storm events in . has 7 different its variations (members) which these members have been developed to detect differences depending on the entry directions of cyclones and storms influencing from the west of the country. In line with the GDAS data analysis, values of height are derived for the requirement of in a limited area. A few of the results from the study are as in the following: 86% of the trained tornado events revealed that the index was in negative phase at the time a tornado was reported, regardless of whether the events featured a convective storm or a frontal movement. The hourly period until the local minimum is obtained can be described and characterized as the process by which the index value decreases continuously. The time required to reach the local minimum varies based on the tornado occurrence. Based on the storm scenario in the test cluster in 2022 and the train cluster, this is predicted to be roughly 33,2 hours on average. In western , there is a 79% chance of a tornado occurring between six and forty-two hours after the index reaches its local minimum. In particular, the projected chance for this period is 63% between 12 and 30 hours after the local minimum is obtained. Besides, the majority of the tornado incidents with values below -0.75 were evaluated. After an index value falls below that threshold, it is likely to forecast the risk period of a tornado in with a probability of 79% and the local minimum point must be identified.

The prediction and understanding of the extreme weather events became one of the top priorities of the forecasting centers. To analyze the heavy rainfall events, the data from reanalysis and station datasets are utilized. The linear regression analysis and principle component analysis (PCA) are applied on precipitation, temperature, Arctic Oscillation Indices (AO) and North Atlantic Oscillation Indices (NAO) datasets. The results indicate that the relationship between these variables can be expressed neither by linear regression nor by PCA, which falls in short in capturing the complexity of the problem. The results indicate the importance of low-level jet in two cases out of three cases considered here.

This technical note presents a combination of isohyetal map, kinematic wave, and rational methods for estimating flash flood synthetic hydrographs in arid regions. They are combined in a logical sequence for the calculations of time of concentration and synthetic flood hydrograph. This empirical approach relates flood peaks to the average temporal and areal intensities of storm rainfalls. The application of the methodology is presented for two arid region wadis in the central western part of the Arabian Peninsula. Hydrograph peaks yield practically reliable estimations of the observed flood magnitudes from individual storms.