Trend analysis of climate change compound indices in Iran

Roshani, Ahmad; Parak, Fatemeh; Esmaili, Hossein

doi:10.2166/wcc.2020.213

Cited by 8 publications

(6 citation statements)

References 37 publications

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“…The increasing temperature was expected to increase evaporation rates, leading to higher humidity during the summer in this climate zone. Moreover, the significant increase in MDSL and its temperature, coupled with rainfall reduction, has resulted in drier and warmer climate conditions in the last 30 years compared to the past 60 years, consistent with the previous studies 79 .…”

Section: Resultssupporting

confidence: 91%

Three-decade assessment of dry and wet spells change across Iran, a fingerprint of climate change

Motamedi

Gohari

Haghighi

2023

Sci Rep

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Extended periods of hydro-climate extremes with excessive or scarce rainfall associated with high or low temperatures have resulted in an imbalanced water cycle and inefficient socio-economic systems in several regions of Iran. However, there is a lack of comprehensive investigations on short-term to long-term variations in timing, duration, and temperature of wet/dry spells. This study bridges the current gap through a comprehensive statistical analysis of historical climatic data (1959–2018). Results indicated that the negative tendency of the accumulated rainfall (− 0.16/ − 0.35 mm/year during the past 60/30 years) in 2- to 6-day wet spells had made significant contributions to the ongoing downward trend in annual rainfall (− 0.5/ − 1.5 mm/year during the past 60/30 years) owing to a warmer climate condition. Warmer wet spells are likely responsible for precipitation patterns changes in snow-dominated stations since their wet spells temperature has more than threefold growth with increasing distance to coasts. The most detected trends in climatic patterns have started in the last two decades and become more severe from 2009 to 2018. Our results confirm the alteration of precipitation features across Iran due to anthropogenic climatic change, and suggest expected increase in air temperature would likely result in further dry and warm conditions over the coming decades.

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Section: Resultssupporting

confidence: 91%

Three-decade assessment of dry and wet spells change across Iran, a fingerprint of climate change

Motamedi

Gohari

Haghighi

2023

Sci Rep

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“…The analysis of the standard normal homogeneity test for temperature shows that among the examined 139 stations, 126 of the stations have breakpoints (Figure 2a), while for precipitation, only 33 stations have break points (Figure 2b). The results of many recent studies have shown that Iran has become warmer and drier in recent decades (e.g., Alizadeh-Choobari & Najafi, 2018;Roshani et al, 2021;Sotoudeheian et al, 2022), and we argue that the heterogeneity of the data could be caused by climate change.…”

Section: Homogeneity Testmentioning

confidence: 69%

Climate zones in Iran

Najafi,

Alizadeh

2023

Meteorological Applications

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Climate classification provides a framework for a better understanding of the dominant weather patterns in different regions of the Earth. This study aims at identifying climate zones in Iran based on the analysis of monthly temperature and precipitation over 139 synoptic stations across Iran during the period 1991–2020. Based on the application of the principal component analysis, we identified six distinct climate zones in Iran: mild and humid, cool and sub‐humid, cold and temperate semi‐arid, warm and semi‐arid, cool and arid, and warm and hyperarid. The highest precipitation occurs in the southern coastal plains of the Caspian Sea, characterized by a mild and humid climate. The climate of western Iran is identified as cool and sub‐humid, while northwestern Iran is characterized by a cold and temperate semi‐arid climate. Southwestern Iran is identified as a region with a warm and semi‐arid climate, while northeastern Iran has a cool and arid climate. Southeastern and central Iran are both characterized by a warm and hyperarid climate. The highest monthly and seasonal precipitation values over Iran occur in March (48.6 mm) and winter (134.2 mm), respectively, while the highest monthly and seasonal mean temperature values occur in July (29.1°C) and summer (28.0°C), respectively. In terms of seasonal variation, the maximum precipitation occurs in the southern coastal plains of the Caspian Sea in autumn, while the minimum occurs in southwestern Iran in summer. Our results have important implications for better understanding and analysing the climatic characteristics across Iran.

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“…The trees in this complex have been planted in two time periods in 2004 and 2010 with a distance of about 3 meters from each other. The region is cold semi-arid according to the Koppen climate classification system (Roshani et al, 2021) and has a relatively high slope in terms of topography (altitude from 1037 m to 1112 m) with average rainfall and temperature of 260 mm and 15 °C in a 10-year period (2010-2020) according to Bojnord Airport Meteorological Station (The station closest to the study area).. The main soil type of this park is silty clay and silty loam.…”

Section: Study Areamentioning

confidence: 99%

Tree Crown Delineation on Uav Imagery Using Combination of Machine Learning Algorithms With Majority Voting

Hosingholizade

Erfanifard²,

Alavipanah³

et al. 2023

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Crown area is one of the key parameters in determining tree growth and an important basis for estimation of biophysical characteristics at single-tree levels in natural and man-made forests. Therefore, the present study was aimed to improve the estimation of crown area on unmanned aerial vehicle (UAV) data using a novel method in a Pinus eldarica man-made forest. The UAV-based RGB images with spatial resolution of 2 cm were acquired from the study area and then resampled to four pixel sizes of 10, 30, 50 and 70 cm. The resampled images were classified by three methods, i.e., Support vector machine (SVM), Random forest (RF), and Artificial neural network (ANN), which are all ensemble (bagging) classification methods. In the next step, the maps of three classification methods for each pixel size were combined by majority voting algorithm at pixel level. The results showed the robustness of ANN in all pixel sizes compared to RF and SVM. Additionally, the combination of the machine learning method by majority voting algorithms had significantly improved the accuracy of P. eldarica crown delineation and its area estimation on the UAV orthoimages with the investigated pixel sizes.

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Trend analysis of climate change compound indices in Iran

Cited by 8 publications

References 37 publications

Three-decade assessment of dry and wet spells change across Iran, a fingerprint of climate change

Three-decade assessment of dry and wet spells change across Iran, a fingerprint of climate change

Climate zones in Iran

Tree Crown Delineation on Uav Imagery Using Combination of Machine Learning Algorithms With Majority Voting

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