Spatial and temporal variability of dryness characteristics in Turkey

Abstract

Drought may occur in almost every climatic region on Earth at any time. Understanding the nature and magnitude of the dryness and drought events are crucial mainly in semi‐arid regions characterized by water shortage and warm/hot and dry Mediterranean type climate. The present article analyses the major patterns of the spatial and temporal characteristics of the climatological dryness in Turkey. This study adopts a relatively new approach for characterizing the dryness over a certain region; dry days since last rain (DDSLR). The DDSLR in a certain place can be evaluated using three different metrics; its severity, consistency and temporal uncertainty enabling to present intra‐ and inter‐annual variations of the dryness. The DDSLR is also coupled with the Mediterranean Climate Index (MCI) approach, measuring the seasonality of rainfall. Analyses were based on daily precipitation data recorded at 69 principal climatological and synoptic meteorological stations of the Turkish Meteorological Service network during the period 1970–2011. The spatial distributions of the MCI and the various DDSLR metrics are presented and analysed. Overall, the three metrics of the DDSLR show their highest values in southern parts of Turkey along the Mediterranean and the borders with Syria and Iraq. These dryness indices are even larger than in central Turkey which receives less annual rainfall. On the other hand, dryness is at its minimum along the Black Sea in northern Turkey. Logarithmic equations of the type f(DDSLR) = a × ln(MCI) + b were fitted to describe the dependence of these metrics on the MCI. All regressions are highly significant and enable to evaluate these metrics even in regions without daily data. Finally, linear trends of the longest DDSLR in each year were calculated and reveal trends toward more severe dry conditions in north‐western Turkey and less severe dry conditions in east Turkey.

Climatic Uncertainty in the Mediterranean Basin and Its Possible Relevance to Important Economic Sectors

“…These examples illustrate the great variability of the rainfall regime between Serbia and Montenegro as revealed for example, by [33]. However, such large variability exists almost everywhere around the Mediterranean for example, in Spain [34], in Israel [25] and in Turkey [32]. Table 1.…”

“…The results presented above are not the most extreme within the Mediterranean Basin and therefore should be regarded as representing average conditions. Furthermore, in many cases, such as for example dryness in Turkey [32] trends towards increasing uncertainties were detected, even if not always statistically significant.…”

“…However, ref. [29][30][31][32] and many others, pointed out the advantage of the DDSLR (dry days since last rain) approach upon the dry-spell approach. According to the DDSLR approach each calendar day is attributed a number that represents its distance (in days) since the last rainy day (above any selected daily rainfall threshold-DRT).…”

“…Detailed information regarding how these metrics are calculated can be found in [32]. It should be made clear that each of these three metrics are calculated independently without high correlation among them.…”

Simulation of precipitation variations in Iran using Kriging interpolation methods

“…Some of these aspects include: (1) does require the spatial variability of precipitation series using geostatistical methods (Cecinati et al, 2017) (Kriging method), (2) compare methods rather than temporal method, and (4) larger control is completed for the precipitation spatial distributions variability (Zeleke and Damtie, 2017). In spite of mentioned aspects, the effectiveness of the spatial variability in the precipitation series (Kutiel and Türkeş, 2017) on the results of trend spatial method has been E-mail: majid_javari@yahoo.com. analyzed using kriging interpolation methods.…”