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پژوهش های اقلیم شناسی، جلد ۱۴۰۳، شماره ۵۸، صفحات ۳۳-۴۹

عنوان فارسی برآورد تعداد روزهای گرد و غباری سالیانه درجنوب شرق ایران با استفاده از روش کرجینگ فضایی - زمانی
چکیده فارسی مقاله سرعت باد یکی از عوامل تعیین کننده در تولید گرد و غبار در و جنوب شرق ایران است، که با قرار گیری حوزه سیستان در این دراین منطقه بر شدت آن می افزاید. لذا برای پیش بینی فضایی- زمانی تعداد روزهای گرد و غباری سالیانه ، از آمار روزانه سرعت باد و دید افقی 43 ایستگاه هواشناسی سینوپتیک منطقه مورد مطالعه استفاده شد. سپس با به کارگیری طرح شبکه کامل فضایی - زمانی ، داده ها به صورت آرایه SP Data ، ترکیبی از ماتریس و بردار به طور مجزا در دو کلاسSTFDF و STF به صور ت ماتریس کامل n×m تعریف شدند. در نهایت با استفاده از نرم افزار R و روش کرجینگ فضایی- زمانی 144 مدل نظری به مدل تجربی داده ها، برازش داده شدند که مدل مَترن به عنوان بهترین مدل انتخاب شد و تغییرنگار فضایی-زمانی متریک با کمترین میانگین مربعات خطا، بهترین برازش را داشت . خروجی مدل نشان داد که داده ها می توانند تا 5 سال تعداد روزهای گرد و غباری را پیش بینی کنند. محاسبه حدود اطمینان در سطح 95% نشان داد که در سال 2022 ایستگاه زابل با 106 روز بیشترین و ایستگاه بیرجند با 23 روز کمترین تعداد روزگرد و غباری را خواهند داشت. همچنین پیش بینی ها نشان می دهند که تعداد روز های گرد وغباری در جنوب شرق ایران از 41 روز به 46 روز در سال 2022 می رسد که روند آن افزایش می یابد.
کلیدواژه‌های فارسی مقاله کرجینگ فضایی-زمانی،تعداد روزهای گرد و غباری،جنوب شرق ایران،SDS،

عنوان انگلیسی Numerical Prediction of annual dust days in east and southeast of Iran Using geospatial -Temporal Statistics
چکیده انگلیسی مقاله Introduction:

Wind speed is one of the determining factors in dust production in the east and southeast of Iran, this issue increases with the location of Sistan basin in the east .Therefore, forspatio-temporal prediction, the number of annual dust days, wind speed of 15 meters per second and more and horizontal visibility of less than 1000 meters were considered as dust days, which by using the space-time layout algorithm, Data were defined in two classes of space-time, horizontal visibility and wind speed as SP Data array as a combination of matrix and vector in STFDFandSTF classes.

For this purpose, in this study, with the help of the packages gstat(Pebesma et al. 2022), Space time(Pebesma et al., 2022) and SP (Pebesma et al, 2017), Raster (Robert J. 2017), spdep (Bivand et al , 2022) and R Google Maps (Climbarda, 2013 andLochter, 2016) of the software environment R, using Kriging Method, the spatio-temporal changes of the number of annual dust days and its prediction in the coming years were examined.

Materials and methods:

In this study using all synoptic stations in the study area, a completespatio-temporal network design was used. This design is most used in spatio-temporal analysis of data in which data with a special feature is collected in a regular network design were collected. then in long formats by specifying each record, the spatio-temporal composition of the data was obtained. The data were then adjusted to a complete n × m matrix. And was considered for records without NA statistics.After that, the empirical Spatial –Temporal variogram were calculated using the Kriging method (Mohammadzadeh, 2012) Used to predict the number of dusty days .

Then 144 separable and non-separable models were fitted to the experimental data model The spatio-temporal metric model with Mattern marginal variable with the lowest mean square error was selected as the best model for predicting the number of annual dust days.

Results and Discussion:

The results showed that the most important points that have more dust days in the eastern and southeastern regions of the country in the coming years, including: northern and central and southwestern regions of Sistan and Baluchestan province, where Zabol and surrounding areas are more intense. And limited points in the west and east of Yazd province. In South Khorasan province in 2022, the only Nehbandan station with 19 days, which will reach 41 days with 95% confidence, and other stations do not show much.In Sistan and Baluchestan province, Zabol, Zahak, Zahedan Mirjaveh, Nosratabad, Khash, Nikshahr, Konarak and Iranshahr stations with 19,10,14,38,26,41,46,59,85 days, respectively, the highest number of dusty days With 95% confidence, the forecast value at Zabul station will reach 106 days, which was a maximum of 116 days in 2018. This rate shows that by 2022, the number of dust days in this province will be reduced. However, it can still be said that this province has the highest number of dust days in the east and southeast of Iran And Zabol can be considered the center of dust in the east of the country, Saravan, Chabahar and Rusk stations are forecasted with 8, 3, 14 days with the lowest number of dust days in 2022, respectively. In Kerman province in 2022, Kerman, Zarand, Kahnooj and Shahdad stations with 10, 10, 23, 16 days, respectively and Bam and Sirjan stations with 4 and 6 days, the lowest number of dust days are forecasted.In Yazd province, Abarkooh, Meybod, Aghda, Bahabad, Herat and Bafgh stations have the highest number of dusty days with 43, 32, 42,60,63,64 days, respectively. And Robat Roof Station will have the lowest number of dusty days in 2022 with 25 days.Finally, the high and low limit of the number of annual dust days shows that in the Southeast Iran, the average number of dust days has increased significantly. In 2018, it will increase from 22 days to 24 days in 2022 Also in this region out of 43 stations, 13 stations are facing critical conditions, of which there are 7 stations in Sistan and Baluchestan province, 4 stations in Yazd province and one station in Kerman province. The only province that does not have a critical station is South Khorasan. In general, it can be said that South Khorasan province has the most standard air quality index in the study area.

Conclusion:

An analysis of the number of dusty days in the Southeast Iran shows that this region is experiencing a significant increase in the number of dusty days, from an average of 11 days in 1987 to 16 days in 2016. Which will increase to 24 days in 2022 by using the space-time forecasting model. The results show that out of 43 stations in the study area, 13 stations are in good condition, 12 stations are in normal condition and 19 stations are in critical condition. Calculations of the maximum probability of occurrence of dust days show that the lowest number of dust days in the east of the country in 2022 is related to Birjand station with 23 days and the highest number of dust days is related to Zabol station 106 days.Spatio-temporal studies of the data showed that in Sistan and Baluchestan province, the number of dusty days is gradually decreasing. For example, at Zabol station, the upper limit of the values predicted in 2018 is 116 days, which will reach 106 days in 2022. However, the most critical province in terms of the number of dusty days is Sistan and Baluchestan province Out of 12 stations studied, 7 stations are in critical condition and one station is at the beginning of entering critical conditions and only Rusk and Chabahar stations are in optimal condition. However, the Sistan region can be considered the center of dust in the east and southeast of Iran. The results also showed that in 2022, Birjand city with one day a year and 95% confidence level with a maximum of 23 days has the most desirable and cleanest air in terms of the number of dusty days in the coming years.
کلیدواژه‌های انگلیسی مقاله کرجینگ فضایی-زمانی,تعداد روزهای گرد و غباری,جنوب شرق ایران,SDS

نویسندگان مقاله احمد حسینی |
استادیار گروه آب و هواشناسی دانشگاه پیام نور ایران

الهه نخعی نژاد |
کارشناس ارشد دانشگاه پیام نور، ایران


نشانی اینترنتی https://clima.irimo.ir/article_197737_4d6dc643eba6fb4335e7a4242edab908.pdf
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