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Land use and land cover (LULC) changes have some implications on land–atmosphere interactions, surface energy budget, and hydrological cycle. The understanding of LULC changes and their interactions with the environment provide better management of agriculture, forests, and water resources. LULC changes are frequently observed in developing countries such as Türkiye and much research has been conducted in this field. However, few studies investigated the countrywide LULC changes and their interactions with energy fluxes and precipitation. In this paper, LULC changes in Türkiye over the last two decades have been evaluated by utilizing an Enhanced Vegetation Index (EVI) derived from the Terra satellite. The latent and sensible heat fluxes were obtained from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis datasets. Precipitation data were acquired from the Tropical Rainfall Measuring Mission (TRMM) satellite. The results showed that EVI has an increasing trend over Türkiye between 2000 and 2021, while climate change–induced desertification, droughts, and forest fires have threatened the vegetative cover in some portions of the country. The latent heat flux has a rising trend due to increasing vegetative cover and irrigated areas. A slight reduction was observed in sensible heat flux, while a sharp increase was witnessed in specific humidity. EVI represented a high positive correlation (R = 0.84) with sensible heat flux and a moderate positive correlation (R = 0.69) with latent heat flux. No significant relation was determined between EVI and precipitation on a monthly basis. [ABSTRACT FROM AUTHOR]

The climate change impact appears as a decreasing or increasing monotonic trend in hydro-meteorology time series records due to greenhouse gas (GHG) emissions causing to global warming and climate change impacts. On the other hand, there may be abrupt changes in the form of jumps in these series due to natural and engineering activities. Although trend identification methods are rather common in the literature, jump determination conventional methodologies are rather rare and their applications present some restrictive asumptions like the serial independence and normal (Gaussian) probability distribution function (PDF). The methodology presented in this paper is away from each of such assumptions and it depicts the minimum number of upcrossing along horizontal truncation levels within the time series variation domain. The applications of the methodology are given for annual Danube River discharge records, Romania; New Jersey rainfall and temperature records, USA; monthly rainfall records and Van Lake level fluctuations, Turkey. [ABSTRACT FROM AUTHOR]

Trend analyses are the necessary tools for depicting possible general increase or decrease in a given time series. There are many versions of trend identification methodologies such as the Mann-Kendall trend test, Spearman's tau, Sen's slope, regression line, and Şen's innovative trend analysis. The literature has many papers about the use, cons and pros, and comparisons of these methodologies. In this paper, a completely new approach is proposed based on the crossing properties of a time series. It is suggested that the suitable trend from the centroid of the given time series should have the maximum number of crossings (total number of up-crossings or down-crossings). This approach is applicable whether the time series has dependent or independent structure and also without any dependence on the type of the probability distribution function. The validity of this method is presented through extensive Monte Carlo simulation technique and its comparison with other existing trend identification methodologies. The application of the methodology is presented for a set of annual daily extreme rainfall time series from different parts of Turkey and they have physically independent structure. [ABSTRACT FROM AUTHOR]

This paper focuses on spatiotemporal characteristics of precipitation indices of Turkey's precipitation data for the periods 1966–2014. Seven precipitation indices include the number of extremely wet days, very wet days, heavy precipitation days (10 mm and 20 mm), simple daily intensity days, and consecutive dry and wet days. The indices are based on homogenized precipitation data. Besides, long-term changes and trends in the time series of precipitation indices in terms of climatic variability were investigated using nonparametric time series analysis methods. The results obtained are summarized as follows. Extremely wet and very wet day indices include significant decreasing trends in most stations. The trend is statistically significant at some stations in the Mediterranean region and southeastern Anatolia region. The number of heavy precipitation day indices tend to decrease in most of the stations in the Mediterranean precipitation zone, throughout Turkey. Simple daily intensity index generally displays an increasing trend. Consecutive dry days include an overall upward trend throughout Turkey. The inner and in the west of southeastern Anatolia regions have displayed a statistically significant increasing trend. Consecutive humid days tend to decrease overall outside of Turkey's internal parts. The study also examined the relationships between atmospheric oscillation indices and precipitation indices. Accordingly, the atmospheric oscillation index that has the most decisive effect on the Turkish precipitation indices is NAO. [ABSTRACT FROM AUTHOR]

Trend identification procedures are used to identify systematic monotonic trendlines in a given hydro-meteorological time series recording to represent time-dependent variations as increases or decreases. Different methodologies have been proposed for such descriptions, but most of them require restrictive assumptions such as normal (Gaussian) probability distribution function (PDF), serial independence, and long sample sizes. In particular, pre-whitening and over-whitening are recommended to meet the need for serial independence, but they cannot transform a serially dependent series into a completely independent one. In this paper, a new trend methodology is proposed based on the characteristics of crossings along any given straight line within the given time series, and the sought-after trend component is the one with the maximum number of crossings. This approach does not require any restrictive assumptions. Unlike previous trend algorithms, the proposed cross-empirical trend analysis (CETA) does not give a single trend, but a series of trends at different levels within the variation range of hydro-meteorological time series records. For the sake of brevity, only three levels are considered in this article, at 10%, 50%, and 90% risk levels. The comparison of the CETA approach is presented with the classical and frequently used Mann–Kendall (MK) trend determination procedure method based on Sen's slope calculation. For very small series correlation coefficients and normal PDF function cases, CETA and the classical technique give almost the same trendline within the ± 5% error band. The application of this methodology is presented for monthly and annual discharge records of the Danube River and annual precipitation records from seven geographical regions of Turkey. [ABSTRACT FROM AUTHOR]

The rising temperatures and decreasing rainfall are expected to have negative effects on ecosystem services by causing significant shrinkage or shift of forest distribution particularly in Mediterranean basin. In this study, it was aimed to determine the distribution of oriental beech (Fagus orientalis Lipsky.) by modelling the current and future potential locations of the habitats. With Maximum Entropy (MaxEnt) approach, we predicted its distribution under current and future conditions (RCP 4.5 and RCP 8.5) in Turkey. Modelling was performed by using eight bioclimatic variables that show significant relationship to the current distribution of oriental beech and were widely used in the literature. The fitted model had high quality (93.5% AUC) and is biological meaningful. The prediction of warmer condition in future showed that the populations on the southern slopes of the North Anatolian Mountains were expected to shrink and that there would be reduction in the populations found in the main distribution area in the Istranca Mountains and the Northern Anatolia, especially in populations in the transition zone of Central Anatolia. Also, oriental beech would lose its isolated-marginal populations in the southeast of Turkey. The results highlight the importance of a genetic conservation programme for beech population in Turkey. Otherwise, the genetic pools seem to extinct under climate change. Furthermore, the paper is intended to provide a starting point for a monitoring of oriental beech at the edge of its distribution, to observe its climatic migration. [ABSTRACT FROM AUTHOR]

Since soil temperature (ST) is one of the most critical determinants affecting the soil's physical and chemical properties, the studies on soil temperature estimation increase with the widespread use of deep learning and machine learning algorithms. This study estimates soil temperature at four depths for Giresun and Bayburt stations in Turkey employing the Bayesian Tuned Gaussian Process Regression (BT-GPR), Bayesian Tuned Support Vector Regression (BT-SVR), and Long Short Term Memory (LSTM) models. The stations were selected from semiarid (Bayburt station) and very humid (Giresun station) climates to compare the models' performance and measure their applicability in different climate classes. Common meteorological indicators were determined as input parameters in the developed models, and a five-and-a-half-year daily dataset was used for all models. This paper represents a novel scheme to optimize the hyperparameters of kernel functions for GPR and SVR models using the Bayesian optimization method to expand predictive efficiency. The developed GPR and SVR models' outputs are compared with LSTM via three statistical metrics comprising the root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). The results show that the BT-GPR model has a superior estimation ability than other developed models for the two stations. The daily ST estimation with the highest accuracy was obtained at a 5-cm depth using BT-GPR at Giresun station (RMSE = 0.0439, R2 = 0.9535, MAE = 0.0344 in the testing phase) and Bayburt station (RMSE = 0.0525, R2 = 0.9438, MAE = 0.0412 in the testing phase). These outcomes provide helpful benchmarking guidance for future soil temperature investigation at various depths across the selected regions. [ABSTRACT FROM AUTHOR]

This paper studies the Upper Tigris River (UTR) drainage basin in Turkey for climate change impacted runoff estimations. Statistical downscaling method (SDM) is used by taking into consideration spatial dependence function (SDF) for the scenario precipitation projections at a set of available meteorology stations. Temporal adjustment between the climate scenarios and precipitation record time series is achieved by the white Markov (WM) stochastic process. Although various climate research center scenario data are considered, herein, only the general circulation model (GCM) A2 scenario data are adapted from the Hadley Center, England. The precipitation and runoff results are presented in decadal groups starting from 2001 to 2050 as cumulative monthly precipitation (CMP) and cumulative monthly runoff (CMR) graphs. It is observed that after 2021, precipitation decreases at about 12.5% and after 2030, it is 26%. Runoff projections indicate that they may decrease at about 30% especial after 2040. [ABSTRACT FROM AUTHOR]

Trend identification analyses in any hydrometeorological data are necessary and critical for predictions and planning in many disciplines such as atmospheric, environmental, and oceanographic sciences; water engineering; global warming; and climate change applications. In the literature, many researches have employed trend analyses by Mann-Kendall (MK) and innovative trend analysis (ITA) methods. Especially in recent years, the ITA method is preferred in trend identification methodological applications, because it can present trend graphs with visual inspection, verbal inferences, and objective quantitative calculations. In this paper, the trends of sea surface temperature (SST) data are identified by the MK and ITA methods on double logarithmic graphs, which provide fractal geometrical appearances with power law features. The SST data trends are evaluated at 22 coastal area stations of Turkey with monthly records from 1969 to 2014. According to the MK trend test, only 6 of the 22 stations had a significant upward trend at 5% significant level and 4 of these stations are in the Mediterranean Sea coastal area. At 10% significance level increasing trend numbers become 14 stations. According to the MK test results, the data records have been grouped into two parts as warming and cooling periods considering the physical conditions of the SST data. On the other hand, the results of ITA application provide average behavioral form according to the mathematical power law equations. [ABSTRACT FROM AUTHOR]

This paper studied hydrological drought identified by the Streamflow Drought Index (SDI) at eight river-gauging stations in the Eastern Mediterranean part of Turkey for a roughly 43-year period covering from 1972 to 2014 (4 stations), from 1973 to 2015 (2 stations), and from 1969 to 2011 (2 stations). Results of SDI analyses indicate that the number of drought years was highest during the 3-month October–December period. A considerable part of the drought years was determined to be mild drought. Although moderate drought conditions were observed in all stations, moderate drought conditions were determined especially at Göksu-H in the Seyhan River Basin and Söğütlü and Savrun in the Ceyhan River Basin. Short-term fluctuations of dry and wet conditions are the dominant pattern for most of the stations; however, long-term persistent drought conditions are also prominent, especially at Tacin and Körkün in Seyhan Basin and Göksun in Ceyhan Basin. The starting point for the negative trend in the 12-month series was the years 1996, 1999, and 2000. [ABSTRACT FROM AUTHOR]

The principal objectives of this paper are to develop and validate an optimum interpolation method for the spatial analysis of monthly precipitation in Turkey. A two-dimensional optimum interpolation objective analysis scheme has been developed for the spatial analysis of precipitation. The model is developed for generating statistically optimum interpolation based on the irregular distribution of meteorological stations. One question that affects the optimum interpolation method and, indeed, all such techniques, is how many observations should be allowed to influence a given grid point? The method developed in this paper addresses this question. For the implementation of the method, 52 stations are considered for Turkey, with 30 years of monthly data at each point. It is observed that each monthly average spatial correlation function shows a monotonically decreasing pattern based on 15 km interval averages. The method provides high estimation accuracy in dense station locations such as in northwestern Turkey. Precipitation contour maps obtained by the optimum interpolation method indicate two spatial trends over Turkey which have not been identified in any previous study. [ABSTRACT FROM AUTHOR]

Contour maps of any meteorological variable cannot give radius or area of influences around the measurement station by considering the records at surrounding sites. The main purpose of this paper is to propose a trigonometric point cumulative semivariogram (TPCSV) concept for deciding on a spatial dependence function and then its use for regional prediction. The TPCSV provides a unique opportunity for the establishment of a regional objective prediction method whereby the radius of influence helps to predict wind velocity at any site by using the weighted averages. The spatial correlations and weightings are obtained through the TPCSV provided that the distance between two sites is known. If the slope of TPCSV is greater than 80° after some distance, then beyond this distance the regional correlation is considered as negligible. The implementation of the proposed methodology is presented for 68 wind velocity measurement stations in Turkey. The proposed method yields the least prediction error compared with other objective methodologies. It is seen that areas of influence at Central Anatolia are generally bigger than coastal areas of Turkey. [ABSTRACT FROM AUTHOR]

When the regional and sectoral impacts caused by climate change are evaluated with different levels of vulnerability, the climate change risks that each region and sector may be exposed also vary. It can be expected that the risk posed by climate change on human comfort, especially due to heat stress, may significantly affect coastal tourism, one of Turkey's priority sectors. In the study, human comfort changes due to climate change in the 10 most important coastal tourism destinations of Turkey (i.e., Manavgat, Çeşme, Alanya, Kemer, Serik, Bodrum, Marmaris, Kuşadası, Aksu, and Fethiye) in the period of May–October were examined. For this purpose, changes in human comfort in the tourism season were projected in these destinations in the near (2026–2050) and mid-future (2051–2075) by using the Discomfort Index (DI), which is one of the most useful indicators of human comfort. In the study, high-resolution climate data, i.e., temperature and relative humidity produced for Turkey under optimistic (RCP4.5) and pessimistic (RCP8.5) scenarios using the regional climate model RegCM4.4, was used to calculate DI. Within the scope of both scenarios in examined destinations, it is predicted that DI values will increase in the near and mid-future. It shows that the thresholds of discomfort may be exceeded in these destinations. [ABSTRACT FROM AUTHOR]

This study aims to analyze drought using precipitation data from 6 meteorological stations located in the Aras Basin, one of Turkey's 25 river basins. The precipitation data of the meteorological stations between 1969 and 2020 were used. Drought analysis were performed using the actual precipitation index (API), a new method, and the standardized precipitation index (SPI) based on the gamma distribution. The Kolmogorov–Smirnov test was used to determine the best distribution that fits the observed data. Three-, 6-, and 12-month periods are preferred. For Ardahan, Iğdır, and Kars stations, 3-, 6-, and 12-month API and SPI values are shown comparatively with graphics. Drought frequency values for all meteorological stations were obtained for 3-, 6-, and 12-month periods. Relative drought frequency values for both SPI and API are depicted in tables. According to the findings of this study, the driest station is Iğdır, while the wettest station is Ardahan. While extreme wet incidents are occasionally in the basin, extreme drought situations are observed. It has been determined that the climate of the basin is slightly arid. [ABSTRACT FROM AUTHOR]

Precipitation with high spatio-temporal resolution is essential for hydro-meteorological studies on global and regional scales. In recent decades, the scarcity and infrequent distribution of gauge networks have been a great challenge for precipitation observation over different climate zones in Turkey. Conversely, precipitation products (PPs) from various sources can be an alternative to fulfill this shortcoming. In this study, the spatio-temporal consistency of five precipitation products, including MSWXv100, MERRA-2, CFSR, SM2RAIN-ASCAT, and PDIR-Now, is evaluated over the variable climate of Turkey, considering two distinct temporal windows as daily and monthly. The Kling-Gupta efficiency (KGE), including its three components (Pearson correlation coefficient, ratio of bias, and variability ratio), is exploited to assess the consistency of PPs over seven climate zones. Moreover, the True Skill Statistic (TSS) is utilized to evaluate the detectability strength of each PP for different precipitation intensities during five hydrologic years (2015–2019). The results indicate that five PPs differed in their behavior over the variable climate of Turkey and different time steps, while showing higher performance in monthly terms compared to daily. Overall, MSWXv100 is able to present a reliable precipitation estimate over time and space and display the highest performance (median KGE; 0.75) for the entire region, where MERRA-2 comes with the second-best performance (median KGE; 0.64) followed by CFSR (median KGE; 0.61), SM2RAIN-ASCAT (median KGE; 56), and PDIR-Now (median KGE; 53). All PPs show diverse performance over each climate zone, and their best performance (except CFSR) is obtained over Southeastern Anatolia (SAN) for the monthly time step, while CFSR showed its best performance (median KGE; 0.70) over the Mediterranean (MED) climate zone. [ABSTRACT FROM AUTHOR]

Drought has devastating effects, and its frequency has increased due to climate change. Therefore, it is important to specifically identify and evaluate the drought-sensitive areas for taking early measures against drought and controlling its effects. The purpose of this study is to evaluate the hydrological drought of the Orontes River Basin within the borders of Turkey in the Eastern Mediterranean using streamflow drought index (SDI) method. The historical droughts of the region are examined in three periods: first period (1954–1976), second period (1976–1998), and third period (1998–2020). The return periods of the drought parameters (duration, severity, peak) are evaluated by univariate and bivariate analysis (duration-severity and duration-peak) using copula functions. Among Ali-Mikhail-Haq, Clayton, Frank, Gumbel-Hougaard, Joe, and Galambos copulas, the Galambos copula function is found to be the best to represent the drought parameters according to the Akaike's information criterion (AIC) and Bayesian information criterion (BIC). As a result of the study, it is found that all parameters of drought (duration, severity, and peak) are considerably higher in the third period than in other periods. The severity of drought in the region is found to increase significantly in the third period. Moreover, the univariate return periods of the drought parameters and their bivariate return periods calculated using the Galambos copula are compared. [ABSTRACT FROM AUTHOR]

Extreme rainfall has enormous importance in hazard management as well as the design of critical infrastructures for urban and rural areas. Also, complex terrain has a vast influence on spatial and temporal patterns of extreme rainfall. In this study, therefore, many different properties such as spatial similarity (regionalization) and temporal variability (trends and seasonality) of extreme rainfall were quantified over Turkey in which topography heavily influences meteorological parameters in short distances due to orientation and height of mountain chains. Moreover, spatial and temporal extreme rainfall characteristics are poorly quantified and investigated in Turkey. Principal component analyses (PCA) were used in order to reveal the parameters that have influence on rainfall, and three components were observed based on Kaiser Rule. The three PC explain the effect of topography, large-scale weather systems, and seasonality on extreme rainfall. Model-based clustering via retained component scores were used to generate the extreme rainfall regions. Eight different extreme rainfall regions have been obtained with different return periods and growth curves calculated based on regional frequency analysis via generalized extreme values distribution (GEV) distribution based on the goodness-of-fit measure. SWM (Southwest Mediterranean) and HEBS (Humid Eastern Black Sea) are remarkable regions than other extreme rainfall regions in terms of the magnitude of extreme rainfall because of the interaction of topography with tracks of weather systems. The circular statistic shows a strong gradient in terms of extreme rainfall seasonality between the coastal and interior parts of Anatolia. Moreover, positive trends and persistence in extreme rainfall have been detected in all regions as a signal of the increase in natural hazards. In general, orographic barriers and their interaction with large-scale weather systems shape the spatiotemporal variability of extreme rainfall and creating a negative gradient between interior and frontal parts of the Anatolian plateau. [ABSTRACT FROM AUTHOR]

In this study, the historical droughts at eight meteorological observation stations in the Tigris basin of Turkey are evaluated between 1965 and 2020. The drought indices are calculated using the Standardized Precipitation Index (SPI) method for 3-, 6-, and 12-month time scales. In order to examine the change of droughts from the past to the present, three different periods designated as the first period (FP), second period (SP), and third period (TP), which correspond respectively to the time intervals of 1965–1983, 1983–2001, and 2001–2020, are taken into consideration. The trend of the drought index values is determined by innovative trend analysis (ITA). It is concluded that the mean value of the peak drought indices in the basin increased significantly from FP to TP for all time scales. The percentages of extreme and severe drought occurrences in SPI-3 and SPI-6 have increased from the past to the present. In SPI-12, although there is a significant decrease in the mean percentage of extreme drought occurrence at FP and SP, it increased considerably at TP. The trend analysis results of the SPI-3 values indicate that the number of decreasing trend stations in the basin increased from the past to the present. There is also a considerable increase in the number of stations with a decreasing trend in almost all drought classes (drought or wet) in SPI-6 and SPI-12. [ABSTRACT FROM AUTHOR]

This study aimed to provide broad insight into the long-term trends and periodicity of monthly and seasonal precipitation in Turkey and to evaluate their implications for sectoral water availability. Overall, Turkey's monthly precipitation declined over the last five decades. While decreasing precipitation trends were dominant in the wet season, consistently increasing trends prevailed in the dry season. The monthly monotonic trends were marked by larger downward trends, especially in early winter and spring. The trend magnitudes in annual and wet season precipitation decreased from north to south and west to east, reaching a maximum value of 7.5 mm/year increase in the eastern Black Sea. The magnitude of dry season trends was much smaller but consistent across the country, varying by 1–5 mm/year. Monthly changes in the trend magnitudes varied between − 2.2 and 3.4 mm, reflecting both decrease and increase, respectively. The magnitude of the downward precipitation trends was higher in inland regions than in other regions. Spatial patterns in the trends evidenced that wet season precipitation variability largely governs annual precipitation variability. The wavelet spectrum indicated a strong annual signal for the monthly precipitation. The inland regions experienced the periodicity of wet years at much longer durations. An average 8-year periodicity was dominant for the annual precipitation, underlining its inter-annual variability and coincided well with the NAO spectrum. Assuming the identified trends persist in the future, a further increase in the magnitude of precipitation trends in coastal areas can enhance the flood risk. However, the precipitation decreases during the wet season are bound to have adverse consequences on sectoral-dependent water availability. [ABSTRACT FROM AUTHOR]

In recent times, copula families have been mostly employed in bivariate drought duration and severity. Archimedean copulas are mainly used conveniently among various potential families for hydrologic design and water resource management. In this study, drought events are defined by standard precipitation index (SPI3 time series) series for 24-gauge stations in Ceyhan Basin Turkey considering different elevation levels (high, average, and low). Both duration and severity are tested for their dependence with Mann–Kendall and Spearman Rho trend test at a 0.05 significant level. While Gamma and Weibull perform better than the other distributions at average elevation, Log-normal and Weibull distributions are found to fit the DD and DS series better for most stations located in low and high elevations, respectively. The best fit copula is found to construct a joint distribution function. The influence of upper tail dependencies is tested to select the most appropriate copula function. Gumbel and BB1 copulas are often regarded as the best copulas for the DD and DS series, respectively. After acquiring the best fit copula, the joint return periods are modeled for each station. Finally, considering drought risk categories (mild, moderate, severe, and extreme drought), spatial distributions of drought risk-return period are constructed. High risks are observed in the middle part of the basin based on TDS and T′DS under mild drought categories. Apart from using univariate frequency analysis, bivariate frequency analysis is performed to model the joint return period based on copula theory which is great of importance for hydrology design and water resource management. [ABSTRACT FROM AUTHOR]

Knowledge of the historical changes in streamflow is essential for operating and planning water structures. Hence, the monthly mean streamflow trends of 20 streamflow gauge stations in Turkey's Mediterranean basins, which are sensitive to climate change, are examined using the Mann–Kendall test, and trend slopes are calculated using Sen's slope method. Furthermore, the innovative trend significance test (ITST) and recently proposed innovative polygon trend analysis (IPTA) method are used to analyse the historical changes in streamflow values at the stations. The trend analysis results of a total of 240-time series between 1977 and 2015 are evaluated and compared with three different trend methods. As a result of the study, the MK method determined significant trends in only 24% (3 increasing, 55 decreasing), ITST in 83% (41 increasing, 158 decreasing), and IPTA in 82% (38 increasing, 158 decreasing) of the 240-time series. The IPTA and ITST methods are more sensitive to determining significant monthly streamflow trends than the MK method. In addition, there is a more significant decrease in the streamflow values of the stations located east of the basin, and the trend slope value reaches − 26%/decade. Therefore, the results of the streamflow trend in the Mediterranean basins will benefit decision-makers in planning the efficient use of water resources in the region. [ABSTRACT FROM AUTHOR]

Temperature has a control on growth, development and yield of crops. Extreme high and low temperatures can be a limiting factor on crops. Extreme temperatures have accompanied global average temperature increase. Investigating the changes in indices derived using daily minimum and maximum temperatures may provide information about how extreme temperatures related to crop production have changed under global warming. In this sense, it is aimed in this study to investigate the climatology and monotonic temporal trends of a number of temperature-based agroclimatic indices across western Anatolia, Türkiye. The indices included number of frost days (NFD), first fall/winter frost (FFF), last winter/spring frost (LSF), frost period (FP), accumulated frost (AF), plant heat stress day (PHSD), plant heat stress accumulation (PHSA), growing season start (GSS), growing season end (GSE), growing season length (GSL) and growing degree-day (GDD). Significance of trends was assessed using Mann–Kendall test, and trend rates were quantified by Sen's slope estimator. The results firstly showed that southern low-elevation stations have the lowest frequency, intensity and duration of frost as a result of rarely occurring frost events. These stations are also characterized by the highest GDD, the earliest GSS, the latest GSE and hence the longest GSL, even with never-ending growing seasons in many years. They are also exposed to the highest heat stress in terms of frequency and intensity. On the other hand, northern high-elevation stations have completely opposite character for all indices in comparison to southern low-elevation stations. Trend analysis revealed that frequency of frost events had decreasing trends (i.e., decreased NFD), accompanied by later onset of FFF, earlier onset of LSF and hence shortened FP and decreased AF. As for growing season indices, in general, GSS occurred earlier, GSE occurred later and GSL extended. Growing degree-day and heat stress indices had substantial increasing trends, implying that, over the course of study period, the study area had more thermal accumulation and exposed to more heat stress that may hinder crop development. [ABSTRACT FROM AUTHOR]

In recent years, natural calamities like droughts have caused disruptive impacts on the environment and society. Drought monitoring and its relations with different climatic parameters have been analyzed with various indices. This study assessed the drought condition with the Standardized Precipitation and Evapotranspiration Index (SPEI) and self-calibrated Palmer Drought Severity Index (sc-PDSI), which were calculated with monthly meteorological measurements between 1971 and 2018 in the northwestern part of Turkey. In addition, the projected drought events of the region were analyzed with the Coordinated Regional Downscaling Experiment (CORDEX) data obtained from five climate models with multi-model ensemble (MME) and under optimistic (RCP 4.5) and pessimistic (RCP 8.5) greenhouse gas and aerosol concentrations for the periods 2019–2050 and 2051–2099. The bias correction of projection data was carried out using meteorological data from the reference period (1971–2000) measurements. Projected drought conditions were analyzed according to the innovative trend analysis (ITA) methods. As a result of the trend analysis of SPEI, it was determined that the drought in the region would increase. Trend analysis of sc-PDSI indicated that drought intensity was different between the stations in RCP 4.5 and 8.5. In addition, the rate of moderate and higher dryness (drought occurrence) in the region was 17.2–30.3% in the measurement period with SPEI and sc-PDSI, respectively. Drought occurrence would increase by 38.3–35.3% in RCP 4.5 and 47–41% in RCP 8.5 for the years 2051–2099, respectively. [ABSTRACT FROM AUTHOR]

In this study, minimum (i.e., outlier or extreme) total monthly rainfall data recorded in the East Anatolia region (EAR) in Turkey were examined. Trend cases of thirteen stations in the EAR were analyzed using the Mann–Kendall (MK) trend and Şen trend tests. The homogeneity test and autocorrelation functions of the data of the stations were considered to comment. The analyses in this study were based on approximately 60-year (1960–2019, except for 17203 (1961–2019), 17285 (1961–2019), and 17204 (1964–2019)) records at thirteen meteorological stations. Drought cases in the previous studies for the EAR were also compared with the trend results of this study. The findings showed that there was no statistically significant trend for twelve stations except for the 17285 according to the MK trend test. Although seven stations (17046, 17201, 17100, 17097, 17199, 17204, and 17165) had a statistically significant upward trend, four stations (17203, 17094, 17285, and 17172) had a statistically significant downward trend according to the Şen trend test. Two stations (17099 and 17096) had no statistically significant trend. In the light of these findings, the statistically significant trends in minimum total monthly rainfall reported above should be considered in water resources management, engineering structures, biological/chemical processes, atmospheric conditions, and social-economic issues. [ABSTRACT FROM AUTHOR]

The present research has been performed for the temporal-spatial reconstruction of an extreme cold episode (temperature anomaly − 15 °C) occurring over the northwest part of Iran for a 142-year period (1871–2012). In carrying out the following investigation, the NOAA Twentieth Century (V20) reanalysis data including mid-level and sea-surface-level data were used. In order to achieve the research goals and extract the sea-surface and mid-troposphere patterns, the methods of hierarchical clustering and factor analysis were utilized. The results showed that during the 142-year period, a total of 791 days were identified in which temperature of − 15 °C or lower occurred. For the synoptic analysis, 183 of these days during which the temperature anomaly was widely observed across the study area were used. The results demonstrated that for most of these days, a surface high pressure system over Asia Minor and northwest Iran contributed to extreme low temperature. These high-pressure systems, whether individually or as part of an extended episode of occurrences, affected the study area. Furthermore, the upper air level study demonstrated that the occurrence of atmospheric blocking or high latitude troughs located to the northwest of Iran (or upstream) and extending into the study area were the main causes for these low temperatures. [ABSTRACT FROM AUTHOR]

Meteorological drought analyses were conducted for Eastern Mediterranean, Seyhan, Ceyhan, and Asi Basins located in the south of Turkey. The gauged data of total precipitation, average temperature, relative humidity, number of sunny days, and number of overcast days, all in monthly steps, obtained from 35 meteorological stations were used as drought indicators. Aggregate drought index (ADI) was used as drought index calculator. Meteorological data series were arranged in accordance with the hydrological years starting on October 1st and ending on September 30th. The ADI results were organized in order to see the variation of the ADI values of the stations from year to year. ADI thresholds were determined individually for all stations. The ADI results obtained by using the principal component analysis (PCA) were presented in form of drought maps by using the inverse distance weighting (IDW) method. The regional drought frequency analysis by the L-moments method was performed to determine extreme ADI values corresponding to generally referred to specific average return periods. Using both the growth curves yielded by the most suitable probability distributions and the regression equations for the means, the extreme ADI values against these average return periods were computed and presented in tabular forms. According to the outcome of the ADI results, it can be concluded that a severe drought does not prevail over the study area as a whole, but some stations experience extreme droughts locally from time to time because of excessive irrigation water demand. [ABSTRACT FROM AUTHOR]

Examining historical variations of hydroclimatic variables can provide crucial information about changes of water resources in a water cycle. In this study, the Mann–Kendall (MK) and Innovative Polygon Trend Analysis (IPTA) methods were applied to 56-year precipitation data collected at 8 measuring stations. These stations are located in Eastern Black Sea Basin (EBSB), which has a significant amount of annual precipitation and hydroelectric potential in Turkey. This study has two objectives: (1) investigating possible changes in the monthly precipitation and (2) comparing the results achieved by a classical (MK) and one of the latest trend analysis methods presented in the literature (IPTA). Based on the results, MK achieved no trend for most of months, while it reached an increasing trend for March at most of the stations. Likewise, IPTA determined an increasing trend for March precipitation. However, an increasing/decreasing trend was obtained by IPTA for most of the months and stations. In other words, comparing the trend analysis results obtained by IPTA and MK indicates a significant discrepancy between the numbers of months with detected trends primarily because the former is relatively more sensitive in trend identification. To be more precise, IPTA and MK determined trends in approximately 81.25% and 12.5% of all months, respectively. Furthermore, the former identified quite the same trends in every month which the latter reported a trend. Moreover, the polygon of the mean and standard deviation graphs developed by IPTA provides a year cycle, which brings about useful information for water utility sectors and decision makers of the study area. Finally, the findings of this study contribute to a large amount of research that attempts to explore spatio-temporal variations of hydroclimatic variables around the globe not only to enhance humans' knowledge about changes in a water cycle but also assess climate change impacts. [ABSTRACT FROM AUTHOR]

In this study, variability and trends of surface humidity, and its relationship with meteorological parameters and sea surface temperatures (SSTs) are investigated for Turkey. Daily relative humidity (RH) and calculated specific humidity (SH) values of the 92 stations, which are homogenously distributed over Turkey, were used for the period 1965–2018. Land surface temperature and precipitation values of the stations and areal-average SST values of the adjacent seas, which are derived from NOAA High Resolution daily mean SST data, were used to find the impacts of physical mechanisms on the increasing or decreasing humidity values. RH values in the stations generally tend to decrease in all seasons, with the largest decrease are found in Mediterranean Region (MeR) during fall with 1.20% per decade, which implies a total decrease of 6.5% during the analysis period. Winter temperature and precipitation records in western/southern stations of Turkey are positively correlated with their RH values due to the transfer of humidity from relatively warm Aegean/Mediterranean SSTs by westerly/southerly winds. In SH, all regions show increasing tendencies; however, highest increments are shown during summer and the increasing trend is higher in the northern regions (i.e., Marmara and Black Sea) when compared to southern areas. The role of SSTs on SH changes is more remarkable during spring than the other seasons. Highest positive SST-SH correlations (p < 0.05) were found in Black Sea (Aegean Sea) regions during spring, summer, fall, and winter seasons with the Pearson's correlation coefficients (r) of 0.83 (0.69), 0.80 (0.48), 0.78 (0.58), and 0.59 (0.49), respectively. Additionally, northerly and southerly dominant wind regimes of the Marmara Region (NW Turkey) enable receiving significant amount of moisture from western Black Sea and northern Aegean Sea in all seasons. [ABSTRACT FROM AUTHOR]

In the current study, an ability of a novel regression-based method is evaluated in modeling daily reference evapotranspiration (ET0), which is an important issue in water resources management and planning. The method was developed by hybridizing radial basis function and M5 model tree and called as radial basis M5 model tree (RM5Tree). The new model results were compared with traditional M5 model tree (M5Tree), response surface method (RSM), and two neural networks (multi-layer perceptron neural networks, MLPNN & radial basis function neural network, RBFNN) with respect to several statistical indices. Daily climatic data (relative humidity, RH, solar radiation, SR, wind speed, air temperature, T) recorded at three stations in Turkey, Mediterranean Region, were used. The effect of each weather data on ET0 was also investigated by utilizing three different input scenarios with various combinations of input variables. On the whole, the RM5Tree provided the best results (Nash and Sutcliffe efficiency, NES > 0.997) followed by the MLPNN (NES > 0.990), and M5Tree (NES > 0.945) in modeling daily ET0. The SR was observed as the most effective input parameter on ET0 which was followed by the T and RH. However, the findings of the third modeling scenario revealed that taking into account of all variables would considerably increase models' accuracies for the three stations. [ABSTRACT FROM AUTHOR]

This study investigated the spatiotemporal changes, including long-term trends and abrupt changes in the heatwave (HW)-related climatic characteristics of Turkey, such as the heatwave number (HWN), duration (HWD), frequency (HWF), magnitude (HWM), and amplitude (HWA). Heatwave-related indices in Turkey based on 88 meteorological stations were calculated considering the 90th percentile of the daily minimum air temperature (Tn90p) and the 90th percentile of the daily maximum air temperature (Tx90p). Trend analysis of the heatwave characteristics indicated that Turkey has experienced more frequent, longer, and hotter heatwaves since 1950. The most significant increasing trends observed in the series of HWNs, HWFs, and HWDs and the Tn90p series were characterized generally with greater trend values. Geographically, the largest changes in the heatwave characteristics of Turkey were detected to occur after the middle of the 1990s in the Black Sea and the Mediterranean coasts, which are in agreement with previous studies performed for various regions of the Mediterranean basin. Long-term trends in almost all country-based heatwave indices of Turkey, except trends in the Tn90p series of HWM values, particularly the Tn90p and Tx90p time series of HWN, HWF, and HWD, and the Tn90p time series of HWA values are statistically significant at the 0.000 level. Statistical comparisons of the means and variances of the Tn90p and Tx90p time series of HWN, HWF, and HWD between the periods of 1950–1984 and 1985–2018 are statistically significant at the 0.005 level. These results indicate abrupt changes towards increased heatwave conditions after the year 1984. [ABSTRACT FROM AUTHOR]

Degree-days as a measure of accumulated temperature deviations from a base temperature have many practical applications in various human related activities such as home cooling, heating, plant growth in agriculture and power generation in addition to energy requirement. Longtemperature records are necessary for their reliable estimations at given stations. In this paper, degree-day measure has been applied tomonthly temperature records for systematically changed base temperature values from - 25 deg. C to + 35 deg. C with 5 deg. C increments at 255 meteorology stations in Turkey. The results are represented in the form of spatial degree-day distribution maps, which are then related to various climatic, meteorological and topographic features of Turkey. For instance, free surface water bodies in forms of surrounding seas, lakes and rivers insert retardation in the expansion of heating degree-days over large regions. On the other hand, cold air penetration from polar regions in the northeastern Turkey originating from Siberia appears at moderate base temperature heating degree-days. [ABSTRACT FROM AUTHOR]

Energy consumption, agricultural activities and comfort in building design are all related to temporal temperature variations. Truncationof the temperature series at a constant base temperature level leadsto surpluses and deficits as deviations. Surpluses are instances forcooling and deficits for heating. In meteorology and heat engineering these are referred to as cooling and heating degree-days, respectively. Since the temperature records are random in character their future predictions are necessary through statistical and probabilistic methods. In this paper, the degree-days are assumed to have a normal probability distribution function and therefore, their averages and standard deviations are considered sufficient for modeling cooling and heating degree-day amounts. Theoretical derivations are presented for degree-day risk calculations in their general forms and a simple implementation is given for two cities in Turkey. [ABSTRACT FROM AUTHOR]

The principal objectives of this paper are to develop and validate an optimum interpolation method for the spatial analysis of monthly precipitation in Turkey. A two-dimensional optimum interpolation objective analysis scheme has been developed for the spatial analysis of precipitation. The model is developed for generating statistically optimum interpolation based on the irregular distribution of meteorological stations. One question that affects the optimum interpolation method and, indeed, all such techniques, is how many observations should be allowed to influence a given grid point? The method developed in this paper addresses this question. For the implementation of the method, 52 stations are considered for Turkey, with 30 years of monthly data at each point. It is observed that each monthly average spatial correlation function shows a monotonically decreasing pattern based on15 km interval averages. The method provides high estimation accuracy in dense station locations such as in northwestern Turkey. Precipitation contour maps obtained by the optimum interpolation method indicate two spatial trends over Turkey which have not been identified in any previous study. [ABSTRACT FROM AUTHOR]

Wet and dry spell properties of monthly rainfall series at five meteorology stations in Turkey are examined by plotting successive wet and dry month duration versus their number of occurrences on the double-logarithmic paper. Straight line relationships on such graphs show that power-laws govern the pattern of successive persistent wet and dry monthly spells. Functional power law relationships between the number of dry and wet spells for a given monthly period are derived from the available monthly precipitation data. The probability statements for wet and dry period spells are obtained from the power law expressions. Comparison of power-law behaviours at five distinct sites in Turkey provides useful interpretation about the temporal and spatial rainfall pattern. As in temperate areas such as Turkey the rainfall amounts change mostly due to one-month-long dry or wet spells. [ABSTRACT FROM AUTHOR]

Changes in precipitation events due to climate change might have significant influences on the characteristics of most hydrological events as well as its own related variables such as intensity, duration, and frequency. Since the intensity–duration–frequency (IDF) curve is an important tool to design infrastructures in water resources management, updating IDF curves under future climate projections nowadays becomes a necessary practice. Therefore, we intended to investigate potential changes in the IDF curves due to climate change using the equidistance quantile matching method in the wettest region of Turkey. We aimed to examine two critical issues: (i) the estimation of changes in IDF curves for three future periods (namely, 2013–2039, 2040–2069, and 2070–2099) and (ii) a comparison analysis between the outcomes based on the two worst-case climate change scenarios (namely, SRES A2 and RCP 8.5) released for the fourth and fifth assessment reports by the IPCC. Our analysis results showed that the outcomes based on SRES A2 revealed an increase in intensities during all the future periods for recurrence intervals under 50 years. According to the outcomes of recurrence interval above 50 years, there is an increase in intensities at the beginning period of the century; however, a decrease in intensities prevails at the ending period of the century. On the contrary, the results based on RCP 8.5 showed that there is a decrease in intensities at the beginning of the century while there is an increase in intensities at the end of the century for all return periods. Our results were discussed according to the indications of the IPCC 5th assessment report. Although conflicting indications were noted between the two worst-case scenarios, our study results may be an inspiration to call a need to update all former design storms based on IDF in any region all over the globe. [ABSTRACT FROM AUTHOR]

The Holdridge life zone (HLZ) method is applied to map potential vegetation types in Turkey. The HLZ map is compared to a map of actual vegetation in order to assess the degradation status of vegetation in Turkey. Data required to identify HLZ classes are provided by the General Directorate of Meteorology, while the current vegetation status is estimated with data provided by the General Directorate of Forestry. After weather data are cleaned and missing values are replaced, the HLZ type is estimated for each station, and then thematic maps are created using the ArcGIS software. The study reveals that there are 12 HLZ types in Turkey. The three dominant types are as follows: cool temperate steppe, warm temperate dry forest, and cool temperate moist forest. In regions where physical geographical controls change in short distances, the biodiversity is greater, and linked to this, the HLZ diversity also appears to be greater. Comparing the identified life zones to the actual vegetation, in some areas, remarkable mismatches can be found. Although, in some regions, the life zone type is consistent with the land cover type, in some narrow areas, the potential vegetation does not reflect features of the current vegetation cover. Considering limitations and capabilities of the assessment approach used in this study, we think that the incompatibility between actual and modelled vegetation types in the eastern region of Turkey is caused by the intensive landscape use. The goal of this research is to support future bioclimatic studies and land use management strategies. [ABSTRACT FROM AUTHOR]

Many ecological studies show that diversity of vegetation is generally sensitive to hydrometeorological variables such as temperature, precipitation, and evaporation. Furthermore, it is also known that there have been changes in the precipitation regimes due to climate change and/or land use (such as urbanization). This study investigates the temporal diversity of the precipitation along with the Holdridge life zones (HLZ) using the biodiversity indices of true Hill numbers and Rényi entropy. The results show that there are no statistically significant changes in the "biodiversity" with respect to the HLZ. However, it was found that, although the biodiversity has remained more or less stable through 45 years, the HLZ classes have widened toward much warmer and drier vegetation cover. One can propose that the water regime of the rivers of the country has also changed due to the early melting of snow and an increase in evapotranspiration as a result of warming. Furthermore, using the Gini-Simpson diversity index for daily rainfall types recorded in a spatially homogeneous manner over Turkey, one can show that there are no significant changes in rainfall diversity in the coastal regions, but significant changes are observed in the internal and relatively high-altitude areas of the country. [ABSTRACT FROM AUTHOR]

In this study, we model and forecast monthly average temperature and monthly average precipitation of Turkey by employing periodogram-based time series methodology. We compare autoregressive integrated moving average methodology and harmonic regression. We show that harmonic regression performs better than the classical methodology in both time series. Also, we find that the monthly average temperature and monthly average precipitation have two different periodic structures of 6 months and 12 months which coincide with the seasonal pattern of the time series. [ABSTRACT FROM AUTHOR]

Meteorological drought is analyzed both in time and space by using drought indices based on site-specific precipitation and temperature data. Departure of precipitation from its normal called in this study as the Dimensionless Precipitation Anomaly Index (DPAI) is used at annual scale, while the Standardized Precipitation Index (SPI) using precipitation and the Standardized Precipitation Evapotranspiration Index (SPEI) using precipitation and temperature are considered at monthly time scale. Five meteorological stations over Kucuk Menderes River Basin in the western part of Turkey are selected for the case study. Results are presented in the forms of drought index time series, drought risk graphs, and drought severity maps. The prolonged severe historical dry periods of the river basin are correctly identified by the drought indices. It is seen that simple tools such as the drought indices used in this study based on easily available meteorological data could explain temporal variability at a site or spatial variability over a river basin. They are therefore important not only for the scientific community dealing with drought as a research problem but also for decision-makers, stakeholders, and end-users making practice about the drought through water allocation studies and drought management plans. [ABSTRACT FROM AUTHOR]

Accurate estimation of solar radiation both spatially and temporally is important for engineering studies related to climate and energy. The multi-gene genetic programming (MGGP) is proposed as a new compact method for this purpose, which is verified to yield more accurate solar radiation estimations in Turkey. Meteorological data such as extraterrestrial solar radiation, sunshine duration, mean of monthly maximum sunny hours, long-term mean of monthly maximum air temperatures, long-term mean of monthly minimum air temperatures, monthly mean air temperature, and monthly mean moisture data are selected as the MGGP model inputs. In the prediction models, the meteorological data measured from 163 stations in seven climate areas of Turkey over the period 1975–2015 are used. The MGGP model results for solar radiation prediction are found to be more accurate than the values given by some conventional empirical equations such as Abdalla, Angstrom, and Hargreaves–Samani. The performance of MGGP is also assessed for Turkey by single-data and multi-data models. The multi-data models of MGGP and the calibrated empirical equations are found to be more successful than the single-data models for solar radiation prediction. [ABSTRACT FROM AUTHOR]

Determining water level changes in lakes is significant for sustainable water supply planning, flood control, water resource management, and economic development with ecosystem sustainability. Trend analysis is a commonly used tool for detecting changes in hydrologic time series of quantities such as lake level, precipitation and temperature. Trend analysis of meteorological variables is very important for assessing the long-term changes in lake levels. This study examines long-term changes in the lakes in the Central Anatolia region of Turkey. Kızören and Timraş sinkhole lakes and Lakes Tuz and Beyşehir are some of the lakes located in this region. Changes in these lakes were examined along with changes in precipitation trends and human effects. The precipitation stations representing these lakes were determined using Thiessen polygons. In this study, the well-known nonparametric Mann–Kendall trend test (MK) was used. Before performing trend analysis, homogeneity and autocorrelation tests were applied for the time series. The standard normal homogeneity test (SNHT) was used to evaluate homogeneity. Trend analysis was performed before and after the change points the inhomogeneous series for the period of the homogeneous series. In addition, the modified Mann–Kendall method (MMK) was performed to examine the strong autocorrelations seen in the entire time series. The results showed that precipitation station data are homogeneous and lake levels are inhomogeneous. Trend analysis was performed by determining the change points for the inhomogeneous lakes. There were no significant trends after the change points for the Lake Tuz and Timraş sinkhole lake. These results are supported by the insignificant trends in precipitation stations. Contrary to the trend analysis results, the increase in the water level of Beyşehir Lake was determined to increment from the water transferred to the lake. The decrease in the water level of Kızören sinkhole was a result of anthropogenic effect rather than precipitation. The results confirm that lake levels have been affected by precipitation trends and anthropogenic effects. [ABSTRACT FROM AUTHOR]

The relationship between blocking events and mean precipitation frequency (MPF) was investigated in this work for Turkey during 1977–2016. The overall MPF for the examined stations during blocked days (nonblocked days) fluctuated between 0.15 and 0.43 (0.12 and 0.38). The ratio of MPF during the blocked days to nonblocked days ranges between 12 and 38%. During the winter season, the country has higher MPF values during blocked days. The greatest ratio of MPF values during blocked days to nonblocked days is observed in summer due to smaller values of MPF occurring during this season overall. Higher MPF occurs when the event center was located between 0o and 30o E (mean 0.27, range 0.17–0.51). There is no relationship between blocking duration and MPF for all seasons. There is a positive relationship between blocking intensity and MPF during summer (CC = 0.35, significant at the 95% level) and fall (CC = 0.43, significant at the 95% level). The relationship between blocking longitudinal extent and MPF is significant at the 95% confidence level during the summer and fall seasons with correlation coefficients of 0.29 and 0.25, respectively. A composite of the 10 blocking events associated with the largest MPF demonstrated that there is moist advection via westerly flow into Turkey in all seasons. During winter, a greater proportion of these events is observed during the La Niña phase of El Niño Southern Oscillation, but during El Niño in spring and summer. For the blocking case study (31 October to 5 November 2009) associated with the largest MPF, the mean value across the country was 0.73. The mean total precipitation during this period was 63.4 mm. [ABSTRACT FROM AUTHOR]

Climate change analysis includes the study of several types of variables such as temperature, precipitation, carbon emission, and streamflow. In this study, we focus on basin hydrology and, in particular, on streamflow values. They are geographic and climatologic indicators utilized in the study of basins. We analyze these values to better understand monthly and seasonal change over a 40-year period for all basins in Turkey. Our study differs from others by applying multivariate analysis into the streamflow data implementations rather than on trend, frequency, and/or distribution-based analysis. The characteristics of basins and climate change effects are visualized and examined with monthly data by using cluster analysis, multidimensional scaling, and gCLUTO (graphical Clustering Toolkit). As a result, we classify months as low-flow and high-flow periods. Multidimensional scaling proves that there is a clockwise movement of months from one decade to the next, which is the indicator of seasonal shift. Finally, the gCLUTO tool is utilized in a novel way in the hydrology field by revealing the seasonal change and visualizing the current changing structure of streamflow. [ABSTRACT FROM AUTHOR]

Soil temperature is a meteorological data directly affecting the formation and development of plants of all kinds. Soil temperatures are usually estimated with various models including the artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models. Soil temperatures along with other climate data are recorded by the Turkish State Meteorological Service (MGM) at specific locations all over Turkey. Soil temperatures are commonly measured at 5-, 10-, 20-, 50-, and 100-cm depths below the soil surface. In this study, the soil temperature data in monthly units measured at 261 stations in Turkey having records of at least 20 years were used to develop relevant models. Different input combinations were tested in the ANN and ANFIS models to estimate soil temperatures, and the best combination of significant explanatory variables turns out to be monthly minimum and maximum air temperatures, calendar month number, depth of soil, and monthly precipitation. Next, three standard error terms (mean absolute error (MAE, °C), root mean squared error (RMSE, °C), and determination coefficient ( R )) were employed to check the reliability of the test data results obtained through the ANN, ANFIS, and MLR models. ANFIS (RMSE 1.99; MAE 1.09; R 0.98) is found to outperform both ANN and MLR (RMSE 5.80, 8.89; MAE 1.89, 2.36; R 0.93, 0.91) in estimating soil temperature in Turkey. [ABSTRACT FROM AUTHOR]

Prior to hydrological assessment of climate change at catchment scale, an applied methodology is necessary to evaluate the performance of climate models available for a given catchment. This study presents a grid-based performance evaluation approach as well as an intercomparison framework to evaluate the uncertainty of climate models for rainfall reproduction. For this purpose, we used outputs of two general circulation models (GCMs), namely ECHAM5 and CCSM3, downscaled by a regional climate model (RCM), namely RegCM3, over ten small to mid-size catchments in Rize Province, Turkey. To this end, five rainfall-borne climatic statistics are computed from the outputs of ECHAM5-RegCM3 and CCSM3-RegCM3 combinations in order to compare with those of observations in the province for the reference period 1961-1990. Performance of each combination is tested by means of scatter diagram, bias, mean absolute bias, root mean squared error, and model performance index (MPI) measures. Our results indicated that ECHAM5-RegCM3 overestimates the total monthly rainfall observations whereas CCSM3-RegCM3 tends to underestimate. In terms of maximum monthly and annual maximum rainfall reproduction, ECHAM5-RegCM3 shows higher performance than CCSM3-RegCM3, particularly in the coastland areas. In contrast, CCSM3-RegCM3 outperforms ECHAM5-RegCM3 in reproducing the number of rainy days, especially in the inland areas. The results also revealed that if a GCM-RCM combination performs well for a portion (statistic) of a catchment, it is not necessarily appropriate for the other portions (statistics). Moreover, the MPI measure demonstrated the superiority of ECHAM5-RegCM3 to CCSM3-RegCM3 up to 33 % excelling for annual rainfall reproduction in Rize Province. [ABSTRACT FROM AUTHOR]

The purpose of this study is to revaluate the changing spatial and temporal trends of precipitation in Turkey. Turkey is located in one of the regions at greatest risk from the potential effects of climate change. Since the 1970s, a decreasing trend in annual precipitation has been observed, in addition to an increasing number of precipitation-related natural hazards such as floods, extreme precipitation, and droughts. An understanding of the temporal and spatial characteristics of precipitation is therefore crucial to hazard management as well as planning and managing water resources, which depend heavily on precipitation. The ordinary kriging method was employed to interpolate precipitation estimates using precipitation records from 228 meteorological stations across the country for the period 1976-2010. A decreasing trend was observed across the Central Anatolian region, except for 1996-2000 which saw an increase in precipitation. However, this same period is identified as the driest year in Eastern and South Eastern Anatolia. The Eastern Black Sea region has the highest precipitation in the country; after 1996, an increase in annual precipitation in this region is observed. An overall reduction is also seen in southwest Turkey, with less variation in precipitation. [ABSTRACT FROM AUTHOR]

In this study, meteorological time series from five meteorological stations in and around a watershed in Turkey were used in the statistical downscaling of global climate model results to be used for future projections. Two general circulation models (GCMs), Canadian Climate Center (CGCM3.1(T63)) and Met Office Hadley Centre (2012) (HadCM3) models, were used with three Special Report Emission Scenarios, A1B, A2, and B2. The statistical downscaling model SDSM was used for the downscaling. The downscaled ensembles were put to validation with GCM predictors against observations using nonparametric statistical tests. The two most important meteorological variables, temperature and precipitation, passed validation statistics, and partial validation was achieved with other time series relevant in hydrological studies, namely, cloudiness, relative humidity, and wind velocity. Heat waves, number of dry days, length of dry and wet spells, and maximum precipitation were derived from the primary time series as annual series. The change in monthly predictor sets used in constructing the multiple regression equations for downscaling was examined over the watershed and over the months in a year. Projections between 1962 and 2100 showed that temperatures and dryness indicators show increasing trends while precipitation, relative humidity, and cloudiness tend to decrease. The spatial changes over the watershed and monthly temporal changes revealed that the western parts of the watershed where water is produced for subsequent downstream use will get drier than the rest and the precipitation distribution over the year will shift. Temperatures showed increasing trends over the whole watershed unparalleled with another period in history. The results emphasize the necessity of mitigation efforts to combat climate change on local and global scales and the introduction of adaptation strategies for the region under study which was shown to be vulnerable to climate change. [ABSTRACT FROM AUTHOR]

Weather forecasting, especially for temperature, has always been a popular subject since it affects our daily life and always includes uncertainty as statistics does. The goals of this study are (a) to forecast monthly mean temperature by benefitting meteorological variables like temperature, humidity and rainfall; and (b) to improve the forecast ability by evaluating the forecasting errors depending upon the parameter changes and local or global forecasting methods. Approximately 100 years of meteorological data from 54 automatic meteorology observation stations of Istanbul that is the mega city of Turkey are analyzed to infer about the meteorological behaviour of the city. A new partial least square (PLS) forecasting technique based on chaotic analysis is also developed by using nonlinear time series and variable selection methods. The proposed model is also compared with artificial neural networks (ANNs), which model nonlinearly the relation between inputs and outputs by working neurons like human brain. Ordinary least square (OLS), PLS and ANN methods are used for nonlinear time series forecasting in this study. Major findings are the chaotic nature of the meteorological data of Istanbul and the best performance values of the proposed PLS model. [ABSTRACT FROM AUTHOR]

The presented study was concentrated on the trend analysis of the annual mean temperature series of 40 meteorological stations in all climatic zones of Turkey. The sensitivity of the parametric and nonparametric tests to the selected record periods was investigated in detail. Backward-shifted and forward-shifted trend analyses were accomplished by keeping either the beginning or the ending data period constant and varying the other period ending. This analysis resulted with a trend statistic direction turning point at the year 1992. Following this result, the trend tests were applied to three different records to distinguish the effect of 1992 on the trend direction. For the period 1950-1992, the downward trend was dominating several stations whereas only upward trend was observed for 1986-2006 period. Clearly, the trend direction change in 1992 dominated the trend behavior between 1986 and 2006. The opposite trend orientations on 1950-1992 and 1986-2006 periods seem to be neutralized on 1950-2006 period with the majority of the stations showing no trend as the result. This study displays the effect of different lengths of data record on the trend analysis results. It has been clear by this study that a sudden change on trend direction is obvious at the stations above 39°N in Turkey provinces in 1992. These results are conformed to the previous studies related with climate change like temperature, sea level, meteorological observations, and dominant climatic events as North Atlantic Oscillation and El-Niño and Southern Oscillation. [ABSTRACT FROM AUTHOR]

It is well-known that North Atlantic Oscillation (NAO), which is one of the large-scaled climate modes effective in the Northern Hemisphere, has a considerable affect on the water resources and climatic indicators especially in the Mediterranean basin. In recent years, also crucial studies about the sea level rise in relation to climate change have been accelerated. Turkey has about 20 modernized tide gauge stations equipped with permanent GPS receivers and targets to contribute to global sea level rise studies in the future. The aim of this study is to find out the effects of North Atlantic Oscillation on the national shores using the data of four tide-gauge stations located on the Aegean and Mediterranean coasts of Turkey. Implications from these four tide gauges would motivate researches to take into account the effect of NAO in calculating the true sea level rise at the national coasts. While studying the sea level changes, vertical crustal movement has been observed using the data of tide gauge GPS stations, and this situation has been taken into consideration in the evaluation of sea levels. Besides, in order to investigate the influences of thermal expansion on sea levels, sea surface temperature data of the meteorology stations near the tide gauges have been evaluated. The homogeneity of the data sets was analyzed using four statistical tests. As a result, all of the meteorology stations' temperature series and tide gauges' data are subjected to trend detection after the homogeneity analysis. Eventually, the effects of North Atlantic Oscillation on both sea levels and sea surface temperatures have been introduced. The study results indicate high correlation between North Atlantic Oscillation and the sea level and sea surface temperature events. It is seen that the linear correlation between the sea level trends of the considered stations and the sea surface temperature data of the related meteorology stations is considerably significant. [ABSTRACT FROM AUTHOR]