شناسایی توزیع زمانی و مکانی نمایه‏های جوی فرین در استان مازندران

نوع مقاله: مقاله پژوهشی

نویسندگان

1 استاد یار- پژوهشکده هواشناسی

2 کارشناس ارشد ریاضی کاربردی ، اداره کل هواشناسی مازندران، ساری، ایران

3 دکتری اقلیم‌شناسی، اداره کل هواشناسی مازندران، ساری، ایران

چکیده

دیدبانی جهانی در سال­های اخیر تغییرات قابل ملاحظه­ای را در رفتار و ویژگی­های پدیده­های جوی فرین نشان می­دهد. موقعیت خاص جغرافیایی، توپوگرافی و تنوع در رخداد سامانه‏های جوی در استان مازندران هر ساله سبب وقوع تعدادی از پدیده‏های فرین می­شود. در سال‏های اخیر تعداد و شدت آن­ها در استان افزایش یافته است. در این تحقیق از آمار روزانه دما و بارش در 15 ایستگاه همدیدی استان به منظور شناسایی توزیع زمانی و مکانی رخداد فراسنج­های فرین استفاده شد. از ایستگاه­های بابلسر و رامسر با دارابودن آمار بلندمدت (2017 1971)، جهت بررسی روند تغییرات نمایه­های فرین دما و بارش استفاده شد. روند نمایه­های دمایی نشان داد که طول مدت گرما، تعداد روزهای تابستانی و شب­های حاره­ای به طور خیلی چشمگیر افزایش و اختلاف دمای بیشینه و کمینه روزانه به طور چشمگیری کاهش یافته است و تغییر معنی­داری در روند نمایه­های بارش در هیچ یک از این دو ایستگاه مشاهده نشد. بررسی نمایه­های فرین فراسنج دما روشن کرد که فراوانی روزهای یخبندان در نواحی مرتفع بیشتر است و روزهای یخی در نواحی ساحلی- جلگه­ای به­ندرت روی می­دهد. نمایه­های حداقل دمای روزانه، روزها و شب­های سرد با افزایش ارتفاع در استان رابطه­ی مستقیمی دارند. میانگین دماهای بیشینه و تعداد روزها و شب­های گرم در نواحی ساحلی- جلگه­ای شرق استان بیشترین مقدار را دارد و به سوی نواحی مرتفع و غربی استان کاهش می­یابد. دامنه تغییرات شبانه­روزی دما در نواحی کوهستانی بیشترین مقدار را داراست. بنابراین نمایه­های دمای بیشینه در مناطق شرقی استان و نمایه­های دمای کمینه در ارتفاعات استان سهم بیشتری دارند و توزیع دما در استان مازندران با توپوگرافی منطقه همخوانی مناسبی دارد.بررسی نمایه­های بارندگی روشن کرد که از نواحی ساحلی- جلگه­ای غرب استان به سمت ارتفاعات و شرق استان، از میزان و شدت بارش­ها کاسته می­شود.در بررسی نمایه­های فصلی کمترین دمای کمینه در تمام فصول ایستگاه بلده می­باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Identification of temporal and spatial distribution of extreme atmospheric indices in Mazandaran province

نویسندگان [English]

  • Zahra Ghassabi 1
  • Mohammad Ali Malaki 2
  • Azita Amiri 3
  • Mehdi Pashaeian
  • Rahim Yoseefi Zadeh
1 Faculty member- ASMERC
چکیده [English]

Introduction
Global observation in recent years has shown remarkable changes in the behavior and characteristics of extreme atmospheric phenomena. Geographic location, topography and variety in the occurrence of atmospheric systems causes a number of these phenomena in the Mazandaran province every year. In recent years, the number and severity of extreme events in the province has increased. Therefore, it is necessary to identify temporal and spatial distributions of the mentioned hazards in order to adapt to these hazards and reduce the effects of extreme phenomena.
 
Materials and methods
Daily temperature and precipitation data were used in the 15 stations of the Mazandaran province in order to identify the temporal and spatial distribution of the extreme parameters. To ensure the quality of them, homogeneity, adequacy of data and recovering and estimation of lost data implemented. Data homogeneity was investigated by Run-Test method. In this method, each of the series values is compared with the mean of the data. The parameter z is computed (relation 1). If its magnitude is greater than 1.96, the data is considered at 95% heterogeneous confidence level
here r, m and n are the total number of sequences, the number of values smaller than the mean and   the number of values greater than the mean, respectively.
In the study of sufficient number of years for stations, the Makus relationship (relation 2) was determined.





(2)

 




where y, t and R are the minimum number of required years, the Student’s t test value at the 90% confidence level and the ratio of y value based on 100 year return interval to y value based on a 2 year return interval. The minimum statistical years are 10 years old and a 15-year statistical period (2017-2003) selected in the present study.
To study the trend of changes in extreme indices, Spearman nonparametric test was used in the Babolsar and Ramsar stations with long-term data (1971-2017). This method uses data’s rank instead of the actual values. Data are arranged in increments and ranks from 1 to n. If the Spearman correlation coefficient () (Equation 3) was greater than 1.96, the assumption of the trend in the data series was accepted, otherwise, the data series would be considered without trend.
Here, for a sample of size n, i and  are the historical rankings in order of occurrence and the ordered historical rankings are in incremental order.
The temporal and spatial frequency of  twenty extreme indices from the expert team ETCCDM[1]  for temperature and precipitation were determined using Rclimdex software.
 
Results and discussion

Long-term trend of extreme indices

The number of cold nights and cold days as well as the number of frost days in recent years were dropped significantly. CSDI index was decreased only in Babolsar, while the WSDI was increased significantly at both stations. The number of summer days and tropical nights has increased. The max Tmax have been increasing in Ramsar. The min Tmin was increased at both stations. DTR index was dropped significantly. Rainfall indices at either of these two coastal stations do not show a meaningful change in recent years.
 

Daily temperature extreme indices

The maximum number of FD was in Baladeh and the maximum number of ID was in Siyahbisheh. The maximum number of SU was in Amol, Sari and Ramsar and the maximum number of TR20 was in Babolsar. The monthly max of Tmax was happened in Sari, Galougah in May, and the monthly min of Tmin was happened in Baladeh in the month January. Most of the cool days and nights and cold spell duration were in Alasht and most of the warm days and nights and warm spell duration were in Ramsar.
 

Precipitation indices

The highest and lowest total annual precipitations were observed in Ramsar (1915.4 mm) and Kojur (449 mm), respectively. The most RX1day and RX5day were in Ramsar. The highest number of days with heavy rainfall greater than 25 mm per year was in Ramsar (21 days) and the highest number of dry periods was happened at Amir Abad station (108 courses).
 

Seasonal indices

The max Tmax was in Sari, Galougah and Dasht-e-naz (42.6 ˚C) during spring, in Galougah (42.2 ˚C) during summer, in Galougah (42 ˚C) during autumn and in Gharakheil (34.6 ˚C) during winter. The min Tmin was in Baladeh every Season, it was 4.6 ˚C in spring, 12 ˚C in summer, 6.2 ˚C in autumn and -9.4 ˚C in winter.
Conclusion
In the study of trend, it was found that the warm duration index, number of summer days and tropical nights were increased significantly and the temperature difference between the daily maximum and minimum values was decreased significantly. No significant change was observed in rainfall indices at any of two stations in recent years. Investigating phenomena associated with extreme temperature indices showed that the frequency of frost days is higher in highlands, and ice days in the coastal-plain areas occur rarely. The minimum daily temperature, cold days and nights indices show a direct correlation with elevation in the province. The average of maximum temperatures and the number of warm days and nights in the east coastal zone of province are the highest and it goes down to the high and western regions of the province. Diurnal temperature range has the highest amount in the mountainous areas of the province. Therefore, the indices of maximum air temperature in the eastern parts of the province have higher values. the minimum temperature distribution is in a good agreement with topography of the region in Mazandaran province. The rainfall indices determine that the amount and severity of rainfall reduce from the west to the highlands and east of the province. So far, the largest number of days with a very heavy rainfall of more than 25 mm in the period 2003- 2017 belongs to Ramsar (351 millimeter).

کلیدواژه‌ها [English]

  • climate change
  • Extreme indices
  • temporal and spatial distribution
  • Mazandaran Province