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<Article>
<Journal>
				<PublisherName>انجمن جغرافیایی ایران</PublisherName>
				<JournalTitle>جغرافیا  (نشریۀ انجمن جغرافیایی ایران)</JournalTitle>
				<Issn>2783-3739</Issn>
				<Volume>24</Volume>
				<Issue>89</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>08</Month>
					<Day>23</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Analysis of Temperature and Precipitation Trends in Northeastern Iran and their Association with Global CO₂ Concentration</ArticleTitle>
<VernacularTitle>بررسی روند تغییرات دما و بارش در شمال‌شرق ایران و ارتباط آن با غلظت جهانی CO₂</VernacularTitle>
			<FirstPage>79</FirstPage>
			<LastPage>103</LastPage>
			<ELocationID EIdType="pii">740755</ELocationID>
			
<ELocationID EIdType="doi">10.22034/jiga.2026.2076947.1459</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>قربان</FirstName>
					<LastName>جعفری</LastName>
<Affiliation>گروه آب و هواشناشی و ژئومورفولوژی ، دانشکده جغرافیا و علوم محیطی ، دانشگاه حکیم سبزواری، ایران.</Affiliation>
<Identifier Source="ORCID">0009-0000-3806-5254</Identifier>

</Author>
<Author>
					<FirstName>عبدالرضا</FirstName>
					<LastName>کاشکی</LastName>
<Affiliation>گروه آموزشی آب و هواشناسی و ژئومورفولوژی ، دانشکده جغرافیا و علوم محیطی، دانشگاه حکیم سبزواری ، سبزوار ، ایران</Affiliation>
<Identifier Source="ORCID">0000-0002-8888-1097</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2026</Year>
					<Month>03</Month>
					<Day>20</Day>
				</PubDate>
			</History>
		<Abstract>&lt;strong style=&quot;mso-bidi-font-weight: normal;&quot;&gt;&lt;span lang=&quot;NL&quot;&gt;Extended Abstract&lt;/span&gt;&lt;/strong&gt;&lt;br&gt;&lt;strong style=&quot;mso-bidi-font-weight: normal;&quot;&gt;&lt;span lang=&quot;NL&quot;&gt;Introduction&lt;/span&gt;&lt;/strong&gt;&lt;br&gt;&lt;span lang=&quot;NL&quot;&gt;Climate change is one of the most important environmental challenges of the twenty-first century and is mainly driven by anthropogenic greenhouse gas emissions. Its impacts are reflected in rising air temperatures, changes in precipitation regimes, and increasing hydro-climatic extremes (IPCC, 2023). Arid and semi-arid regions are especially vulnerable because they depend on scarce and highly variable water resources and climate-sensitive agriculture. Northeast Iran, including Khorasan Razavi, North Khorasan, and South Khorasan provinces, is a representative dryland region exposed to these pressures. It is characterized by hot dry summers, cold winters, low and irregular precipitation, and growing stress on groundwater resources. Previous studies have reported warming tendencies, declining humidity, and hydro-climatic instability in parts of this region. However, many of those studies were conducted either at broader national scales, over shorter periods, or without a systematic assessment of data homogeneity before trend analysis. This study addresses these gaps by examining long-term annual and seasonal changes in temperature and precipitation in Northeast Iran during 1995–2024 and by evaluating their statistical relationship with globally averaged atmospheric CO₂ concentration.&lt;/span&gt;&lt;br&gt;&lt;br&gt;&lt;strong style=&quot;mso-bidi-font-weight: normal;&quot;&gt;&lt;span lang=&quot;NL&quot;&gt;Methodology&lt;/span&gt;&lt;/strong&gt;&lt;br&gt;&lt;span lang=&quot;NL&quot;&gt;Monthly, seasonal, and annual mean temperature and total precipitation data from 16 synoptic stations of the Iran Meteorological Organization were analyzed for the period 1995–2024. Stations were selected based on balanced spatial distribution, continuity of records, and low rates of missing data. Missing values, which did not exceed 0.5 percent, were completed using multiple imputation in SPSS. Global atmospheric CO₂ data were obtained from the NOAA Global Monitoring Laboratory. Before trend detection, annual temperature and precipitation series were tested for homogeneity using three complementary methods: Pettitt, SNHT, and Buishand. Temporal trends were identified using the non-parametric Mann–Kendall test, and their magnitude was estimated by Sen’s slope estimator. A paired t-test was applied to compare climatic conditions between the two sub-periods 1995–2009 and 2010–2024. P-values between 0.05 and 0.10 were interpreted as marginally significant because weak precipitation declines may still be hydrologically important in dry environments. The relationship between global CO₂ concentration and regional climatic variables was examined through simple linear regression. Spatial patterns of trend magnitude were mapped using the Inverse Distance Weighting method in ArcGIS Pro. Finally, hierarchical clustering based on Ward’s method and squared Euclidean distance was performed using four standardized variables: annual temperature trend slope, annual precipitation trend slope, mean annual temperature, and mean annual precipitation.&lt;/span&gt;&lt;br&gt;&lt;br&gt;&lt;strong style=&quot;mso-bidi-font-weight: normal;&quot;&gt;&lt;span lang=&quot;NL&quot;&gt;Results and&lt;/span&gt;&lt;/strong&gt; &lt;strong style=&quot;mso-bidi-font-weight: normal;&quot;&gt;&lt;span lang=&quot;NL&quot;&gt;Discussion&lt;/span&gt;&lt;/strong&gt;&lt;br&gt;&lt;span lang=&quot;NL&quot;&gt;The homogeneity assessment showed that annual temperature series at all 16 stations were non-homogeneous. This was interpreted as a statistical signal of strong and persistent warming rather than a data-quality problem. In contrast, annual precipitation series were homogeneous at all stations and therefore suitable for direct trend analysis. The Mann–Kendall test revealed a clear regional warming pattern. Fifteen of the sixteen stations, equivalent to 93.75 percent, exhibited statistically significant positive annual temperature trends. The strongest warming rates were observed at Qaen (0.069°C year⁻¹), Tabas (0.068°C year⁻¹), Torbat-e Jam (0.066°C year⁻¹), and Sarakhs (0.064°C year⁻¹). Quchan was the only station with a negative slope, but this trend was not statistically significant. Seasonal analysis showed that spring had the strongest and most spatially consistent warming signal across the region, while summer also displayed mainly positive trends.Precipitation trends were more heterogeneous and generally weaker than temperature trends. Significant annual precipitation declines were detected only at Tabas and Torbat-e Heydarieh, while Torbat-e Jam and Birjand showed marginally significant decreases. Several northern stations, including Quchan, Mashhad, and Sarakhs, displayed weak positive or near-zero precipitation slopes. Seasonal analysis indicated that the most persistent declines occurred in winter and spring, the two seasons most critical for groundwater recharge and rainfed agriculture. This pattern points to increasing pressure on regional water resources and agricultural stability, especially in the southern and central sectors of the study area.The paired t-test confirmed that the second sub-period was significantly warmer than the first at all stations except Quchan. In Qaen, Tabas, and Torbat-e Jam, the increase &lt;/span&gt;&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;span lang=&quot;NL&quot;&gt;exceeded 1°C, indicating a structural shift in the regional thermal regime. Regression analysis further showed a positive and statistically significant relationship between global CO₂ concentration and annual temperature at 15 of the 16 stations. In contrast, no significant association was found between global CO₂ and annual precipitation, suggesting that precipitation in Northeast Iran is influenced more strongly by regional circulation patterns, topography, and moisture transport processes than by direct global radiative forcing. Hierarchical clustering identified three distinct climatic groups: a hot-arid cluster with high temperatures, low precipitation, and strong warming trends; a transitional semi-arid cluster with moderate thermal and moisture conditions; and a distinct cool-wet cluster represented only by Quchan.&lt;/span&gt;&lt;br&gt;&lt;br&gt;&lt;strong style=&quot;mso-bidi-font-weight: normal;&quot;&gt;&lt;span lang=&quot;NL&quot;&gt;Conclusion&lt;/span&gt;&lt;/strong&gt;&lt;br&gt;&lt;span lang=&quot;NL&quot;&gt;The findings show that Northeast Iran experienced substantial climatic change during 1995–2024, mainly in the form of widespread and statistically robust warming. In contrast, precipitation changes were spatially less uniform, although drying tendencies were evident in the southern and central sectors, particularly during winter and spring. The combined effect of increasing temperature and declining seasonal precipitation implies rising risks of hydrological and agricultural drought. The identification of three climatic clusters provides a practical basis for region-specific adaptation strategies. Priority actions should include improved water allocation, strengthened drought monitoring systems, and the promotion of drought-resistant agricultural practices, especially in the most vulnerable hot-arid areas&lt;/span&gt;&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;br&gt;</Abstract>
			<OtherAbstract Language="FA">مناطق خشک و نیمه‌خشک جهان، از جمله شمال‌شرق ایران، به دلیل محدودیت منابع آب و وابستگی شدید به فعالیت‌های کشاورزی، از آسیب‌پذیرترین نواحی در برابر تغییرات اقلیمی به شمار می‌آیند. از این‌رو، تحلیل علمی روند تغییرات هیدرواقلیمی و بررسی ارتباط آن با عوامل جهانی نظیر افزایش غلظت دی‌اکسیدکربن، برای تدوین راهبردهای سازگاری و مدیریت پایدار منابع طبیعی ضروری است. پژوهش حاضر با هدف تحلیل روند تغییرات دما و بارش و تبیین ارتباط آن با غلظت جهانی CO₂ در دوره سی‌ساله ۱۹۹۵ تا ۲۰۲۴ در شمال‌شرق ایران انجام شد.&lt;br&gt;در این پژوهش، داده‌های ماهانه، فصلی و سالانه ۱۶ ایستگاه همدید سازمان هواشناسی کشور مورد استفاده قرار گرفت. برای تحلیل روند، از آزمون ناپارامتریک من‌کندال، برآوردگر شیب سن و رگرسیون خطی بهره گرفته شد و به‌منظور مقایسه تغییرات، آزمون T زوجی نیز به کار رفت. همچنین، همگنی سری‌های زمانی با آزمون‌های Pettitt، SNHT و Buishand ارزیابی و تحلیل فضایی روندها با روش درون‌یابی وزنی معکوس فاصله (IDW) در محیط ArcGIS انجام شد. افزون بر این، برای شناسایی الگوهای فضایی-اقلیمی، تحلیل خوشه‌ای سلسله‌مراتبی بر پایه چهار متغیر اقلیمی اجرا گردید.&lt;br&gt;نتایج نشان داد که ۱۵ ایستگاه از ۱۶ ایستگاه (۹۳.۷۵ درصد) دارای روند افزایشی معنادار دما در سطح ۰.۰۵ هستند. بیشترین نرخ گرمایش در ایستگاه‌های قائن، طبس، تربت‌جام و سرخس مشاهده شد، در حالی‌که ایستگاه قوچان تنها ایستگاه با روند کاهشی و غیرمعنادار بود. بارش سالانه در اغلب ایستگاه‌ها روندی کاهشی داشت که در برخی ایستگاه‌ها معنادار بود. همچنین، بین دمای منطقه و غلظت جهانی CO₂ رابطه‌ای مثبت و معنادار مشاهده شد. نتایج خوشه‌بندی، ایستگاه‌ها را در سه خوشه اقلیمی متمایز قرار داد. رویکرد یکپارچه این پژوهش، چارچوبی مناسب برای شناسایی نواحی آسیب‌پذیر و پشتیبانی از برنامه‌ریزی سازگاری اقلیمی در شمال‌شرق ایران فراهم می‌سازد.</OtherAbstract>
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			<Param Name="value">روند دما و بارش</Param>
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