Decadal variability analysis of extreme precipitation in Turkey and its relationship with teleconnection patterns

Düzenli, Eren; Tabari, Hossein; Willems, Patrick; Yılmaz, M. Tuğrul

doi:10.1002/hyp.13275

Cited by 33 publications

(11 citation statements)

References 38 publications

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“…The BS coast gets the highest precipitation in Turkey. The eastern BS is the only region in the country that receives precipitation throughout the year [39]. BS region has wet and humid climate (winter and summer have about 4 • C and 22 • C).…”

Section: Study Area and Datamentioning

confidence: 99%

Combined Use of Graphical and Statistical Approaches for Analyzing Historical Precipitation Changes in the Black Sea Region of Turkey

Cengiz

Tabari

Onyutha

et al. 2020

Water

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Many statistical methods have been developed and used over time to analyze historical changes in hydrological time series, given the socioeconomic consequences of the changes in the water cycle components. The classical statistical methods, however, rely on many assumptions on the time series to be examined such as the normality, temporal and spatial independency and the constancy of the data distribution over time. When the assumptions are not fulfilled by the data, test results are not reliable. One way to relax these cumbersome assumptions and credibilize the results of statistical approaches is to make a combined use of graphical and statistical methods. To this end, two graphical methods of the refined cumulative sum of the difference between exceedance and non-exceedance counts of data points (CSD) and innovative trend analyses (ITA)-change boxes alongside the classical statistical Mann–Kendall (MK) method are used to analyze historical precipitation changes at 16 stations during 1960–2015 in the Black Sea region of Turkey. The results show a good match between the results of the graphical and statistical methods. The graphical CSD and ITA methods, however, are able to identify the hidden trends in the precipitation time series that cannot be detected using the statistical MK method.

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Section: Study Area and Datamentioning

confidence: 99%

Combined Use of Graphical and Statistical Approaches for Analyzing Historical Precipitation Changes in the Black Sea Region of Turkey

Cengiz

Tabari

Onyutha

et al. 2020

Water

Self Cite

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“…The variability of the climate across Turkey is large, hence, different climate zones [62] obtained from Köppen-Geiger Climate classification [63] are often used to investigate the impact of the climate as a part of sensitivity studies.…”

Section: Evaluation Categoriesmentioning

confidence: 99%

Evaluation of Remotely-Sensed and Model-Based Soil Moisture Products According to Different Soil Type, Vegetation Cover and Climate Regime Using Station-Based Observations over Turkey

et al. 2019

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This study evaluates the performance of widely-used remotely sensed-and model-based soil moisture products, including: The Advanced Scatterometer (ASCAT), the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), the European Space Agency Climate Change Initiative (ESA-CCI), the Antecedent Precipitation Index (API), and the Global Land Data Assimilation System (GLDAS-NOAH). Evaluations are performed between 2008 and 2011 against the calibrated station-based soil moisture observations collected by the General Directorate of Meteorology of Turkey. The calibration of soil moisture observing sensors with respect to the soil type, correction of the soil moisture for the soil temperature, and the quality control of the collected measurements are performed prior to the evaluation of the products. Evaluation of remotely sensedand model-based soil moisture products is performed considering different characteristics of the time series (i.e., seasonality and anomaly components) and the study region (i.e., soil type, vegetation cover, soil wetness and climate regime). The systematic bias between soil moisture products and in situ measurements is eliminated by using a linear rescaling method. Correlations between the soil moisture products and the in situ observations vary between 0.57 and 0.87, while the root mean square errors of the products versus the in situ observations vary between 0.028 and 0.043 m 3 m −3 . Overall, according to the correlation and root mean square error values obtained in all evaluation categories, NOAH and ESA-CCI soil moisture products perform better than all the other model-and remotely sensed-based soil moisture products. These results are valid for the entire study time period and all of the sub-categories under soil type, vegetation cover, soil wetness and climate regime.

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“…This is particularly important for regions such as the Black Sea region, which accommodate geophysical features such as various land-use and land-cover types, irregular terrain, and land-sea interaction dynamics [17,31]. It is also important to determine the spatial and temporal variations of extremes in regions with topography such as the Black Sea region, which is one of the regions exposed to meteorological hazards from extreme precipitation [17,32,33].…”

Section: Introductionmentioning

confidence: 99%

Non-stationary Investigation of Extreme Rainfall

Oruc

2021

Civ Eng J

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Natural or human-induced variability emerged from investigation of the traditional stationary assumption regarding extreme precipitation analyses. The frequency of extreme rainfall occurrence is expected to increase in the future and neglecting these changes will result in the underestimation of extreme events. However, applications of extremes accept the stationarity that assumes no change over time. Thus, non-stationarity of extreme precipitation of 5, 10, 15, and 30 minutes and 1-, 3-, 6-, and 24-hour data of 17 station in the Black Sea region were investigated in this study. Using one stationary and three non-stationary models for every station and storm duration, 136 stationary and 408 non-stationary models were constructed and compared. The results are presented as non-stationarity impact maps across the Black Sea Region to visualize the results, providing information about the spatial variability and the magnitude of impact as a percentage difference. Results revealed that nonstationary (NST) models outperformed the stationary model for almost all precipitation series at the 17 stations. The model in which time dependent location and scale parameter used (Model 1), performed better among the three different time variant non-stationary models (Model 1 as time variant location and scale parameters, Model 2 as time variant location parameter, and Model 3 as time variant scale parameter). Furthermore, non-stationary impacts exhibited site-specific behavior: Higher magnitudes of non-stationary impacts were observed for the eastern Black Sea region and the coastal line. Moreover, the non-stationary impacts were more explicit for the sub-hourly data, such as 5 minutes or 15 minutes, which can be one of the reasons for severe and frequent flooding events across the region. The results of this study indicate the importance of the selected covariate and the inclusion of it for the reliability of the model development. Spatial and temporal distribution of the nonstationary impacts and their magnitude also urges to further investigation of the impact on precipitation regime, intensification, severity. Doi: 10.28991/cej-2021-03091748 Full Text: PDF

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Decadal variability analysis of extreme precipitation in Turkey and its relationship with teleconnection patterns

Cited by 33 publications

References 38 publications

Combined Use of Graphical and Statistical Approaches for Analyzing Historical Precipitation Changes in the Black Sea Region of Turkey

Combined Use of Graphical and Statistical Approaches for Analyzing Historical Precipitation Changes in the Black Sea Region of Turkey

Evaluation of Remotely-Sensed and Model-Based Soil Moisture Products According to Different Soil Type, Vegetation Cover and Climate Regime Using Station-Based Observations over Turkey

Non-stationary Investigation of Extreme Rainfall

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