@article { author = {Pourasghar, F and Ghaemi, H and Jahanbakhsh, S. and Sari Sarraf, B.}, title = {Studying of moisture flux during wet and dry periods over southern part of Iran from adjacent Seas}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {2-16}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction        The ocean has an important role on climate variability. Most of the water that evaporates from oceans is precipitated back into them and continents. Because of its low annual mean precipitation, Iran is commonly regarded as an arid country. So it is important to understand the processes that govern on the moisture transport in atmosphere and how they are related to precipitation over Iran. Therefore the goal of the study is identifying the role of the adjacent Seas on the winter precipitation over the southern part of Iran. Materials and Methods        Monthly precipitation data from 183 stations in the southern part of Iran were made available by the Iranian Meteorological Organization and Iranian water resource institute. The SST data used in the present study is obtained from the Hadley centre sea ice and sea surface temperature. It is monthly data with 1ºx1º horizontal resolution. The NCEP/NCAR reanalysis data is used for wind, specific humidity, geopotential height and sea level pressure. For all data, we adopted the period from December 1974 to February 2005. To capture the dominant mode of interannual variability, we have applied the EOF analysis to deterended monthly precipitation anomaly data from 183 stations. To characterize the dynamical features related to each precipitation regime composites of sea surface temperature, moisture flux and SLP were computed for wet and dry years. Wet (dry) years correspond to those years with the principle component of the first EOF mode for each month above 0.8 (below -0.8) standard deviation. Results and discussion        Regional spatial precipitation on variability was identified by Empirical Orthogonal Function (EOF). The first 2 components represent more than 66% of total variance. In the first mode of EOF which represent 50% of total variance the positive (negative) sea surface temperature anomaly is in the Arabian Sea during wet (dry) years. The southeasterly moisture flux anomaly over the Arabian Sea turns anti-cyclonically and transport more moisture to the southern part of Iran from Arabian Sea, Red Sea, and Persian Gulf during wet years. On the other hand, the moisture flux has northerly anomaly over Iran during the dry years, which results in reduced moisture supply from the south. In the second mode of EOF the sea surface temperature anomaly over the Arabian Sea is positive in the wet years but it is not dominant for dry years. The displacement of Arabian anticyclone to eastward (westward) in wet (dry) years transport more moisture from Arabian Sea, Red Sea to south and east (west) part of Iran. Conclusion        The results of this study showed that the Sea surface temperature variation over adjacent Seas causes the precipitation variation over southern part of Iran. The main source for the winter precipitation in the south part of Iran is Arabian Sea at the lower level and Red Sea at the middle level. In almost all precipitation regimes the trough and Arabian anticyclone have an important role to transfer moisture from southern water bodies to the southern part of Iran.    }, keywords = {Precipitation,Moisture flux,Southern Iran}, title_fa = {بررسی شار رطوبت از دریاهای مجاور در دوره‌های مرطوب و خشک فصل زمستان نیمه جنوبی کشور}, abstract_fa = {در این پژوهش، نقش منابع آبی مجاور روی بارش فصل زمستان نیمه جنوبی کشور با استفاده از داده‌های ماهانه بارش 183 ایستگاه سینوپتیک ، اقلیمی و باران سنجی سازمان هواشناسی کشور و سازمان آب برای دوره 2005-1974 مورد بررسی قرار گرفت. توزیع مکانی نابهنجاری بارش برای ماه‌های دسامبر، ژانویه و فوریه با استفاده از روش تابع متعامد تجربیEOF شناسایی شده و مؤلفه‌های اول و دوم که بیش از 66 درصد واریانس بارش را تعیین می‌کنند برای مطالعه تعیین شدند. برای شناسایی الگوهای همدیدی و دینامیکی رژیم بارش هر منطقه نقشه‌های ترکیبی نابهنجاری دمای سطح آب، شار رطوبت و فشار سطح دریا برای دوره‌های مرطوب و خشک محاسبه و ترسیم شد. الگوی نابهنجاری دمای سطح آب پهنه‌های آبی نیمه جنوبی کشور در دوره مرطوب و خشک نشان داد که تغییرات دمای سطح آب نقش مهمی در نوسانات بارش دارد به طوری که نابهنجاری دمای سطح آب برای مؤلفه‌های اول EOF که بیش از 50 درصد واریانس کل بارش را در نیمه جنوبی کشور تبیین می‌کند در دوره مرطوب (خشک) مثبت (منفی) است از آنجائیکه گردش جو حاکم در منطقه نقش مهمی در انتقال رطوبت به جنوب ایران دارد در دوره مرطوب رطوبت از دریای عرب، دریای سرخ و خلیج عدن به جنوب ایران منتقل می‌شود و در دوره خشک از جنوب ایران خارج می‌گردد. نابهنجاری دمای سطح آب دریای عرب برای مد دوم EOF  مثبت می‌باشد اما تغییرات دمایی در دوره خشک برجسته نیست. جابه جایی پر فشار عربستان به سمت راست (چپ) در دوره‌های مرطوب (خشک) رطوبت بیشتری را از دریای عرب به نواحی جنوبی – شرقی (غربی) کشور انتقال می‌دهد.}, keywords_fa = {بارندگی,شار رطوبت,جنوب ایران}, url = {https://clima.irimo.ir/article_14934.html}, eprint = {https://clima.irimo.ir/article_14934_ec0775ab80519d0899776ace7c74b129.pdf} } @article { author = {Seyyed Nezhad Golkhatmi, N. and Sanaeinejad, H. and Ghahraman, B. and Rezaee Pazhand, H.}, title = {Daily rainfall interpolation of Mashhad Drainage basin}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {17-30}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {  1-Introduction     Daily Rainfall estimation usually performed with classical interpolation methods (Dingman,2002).To have a responsible accuracy in using new geostatistical methods, and neural networks methods we need a dense distributed stations (Goovaerts,2000؛ Rahimi-BondarAbadi and Saghafian, 2007). However, Modified Inverse Distance Method(MIDW) can be used in mountainous areas with low density (LO,1992(.Elevation to the distance ratio (with equal power) appears in MIDW. MIDW-F is the advanced version of MIDW that considers the elevation and distance as the inverse with unequal power (m and n). It is analyzed with fuzzy mathematics and is optimized with Genetic Algorithm (GA) (Chang et al, 2005). The purpose and innovation of this paper is to provide MIDW-F with a new alignment of MIDW-F which named GMIDW-F.   2 - Materials and Methods 2.1 Study area and data     The study  area is Mashhad Drainage basin (dry and semi-dry climate) with longitude  58° ,20´ to 60°,8' Easting and Latitude  36°-0' to 37°-5' Northing(North East of Iran) with total area of ​​9909.4 km2. Number of rain gauges within and adjacent the area are 49 with over a period of 16 years combined(1993-2009). 215daily rainfall (at least 50% of the stations have rainy day at the same time) was used for modeling in this study. 2-2 Modified inverse distance method Based on Fuzzy Mathematics    MIDW method considers the ratio of elevation(h) to distance(d) with equal power (LO, 1992). Advanced version of this is MIDW-F (Eq.8) that powers are unequal (Chang et al, 2005. The weights of elevation and distance(Eqs.1 and 2) are fuzzy.  and  are the Fuzzy membership functions d,and.  and  are the membership degrees. They can be integrated with the fuzzy operators, minimum, maximum, multiplied and sum of squares (Eqs.3 to 7) (Vahidian-Kamyad and Tarqyan, 2002). The phrase  is integrated weight. We can consider the role of elevation directly in these area . We applied two different alignments to MIDW-F which named GMIDW-F method (Eq.8). If weights(h and d) appear in reverse (as), it was named GMIDW-F(1). The caseis named GMIDW-F(2). (1)                                                                           (2)                                                                                  (3)                                                                                                        (4)                                                                                                    (5)                                                                                             (6)                                                                                                   (7)                                                                                              (8)         GMIDW-F equation                                            2.3 Genetic Algorithms    The GA is useful to estimate and optimize the parameters m and n of equation 8. The error function is regional sum of absolute errors(RSAE).   2.4 Data screening and normalization           Reforming data due to wrong registration, incorrect transmission, system failure, etc. is called screening. The normalization is for unification the scales of elevation and distance (Eqs 9 and 11). If the role of elevation is assumed to be negative, normalized by Eq.(10) and in direct mode can be done with Eq.(11) (Chang et al, 2006).                                                                                         (9)                                                                                       (10)                                                                                                           (11)       3 - Results and Discussion    The MIDW-F considers elevation and distance inversely with unequal powers (m and n) in MIDW. We added a new alignment elevation to the distance ratio (GMIDW-F). Optimization of m and n was conducted for 215 daily rainfalls. Rainfalls were classified into 5-10, 10- 20, 30-40, 40-50 etc (in mm). Screening and normalization were also performed. Integration was examined with five fuzzy functions(Eqs. 4 to 8). GA is applied to optimize the parameters.    RSAE for each equation and for each category was calculated(Eq. 10, Tables 1 and 2). This classification did not show any specific results. Contribution of minimum and multiply operators is more frequenty (Table 2). Some statistical features of RSAE increase with rainfall classification(Table 3). Without classification the optimum function was obtained in 66% of cases with and 34% of cases with. The Best operator was minimized (57%) and then multiplied (31%) (Tables 1, 2 and 4). The multiplication operator showed that in 76% of cases the effect of elevation and distance are inversed when  and in 24% of the cases the effect of distance is direct while elevation effect is inverse when   (Tables 2 and 4). The zoning of a daily precipitation (11/04/2009) by GMIDW-F and IDW methods were compared in a graph with RSAE values of 213 and 252 (in mm) respectively. By using IDW method, precipitation was estimated zero when it was at least 7(in mm), so it is overestimate, while it was estimated 1.5 mm by at the same values. It could be concluded that zoning by GMIDW-F provides better results than IDW method. 4 - Conclusion      The results of analysis showed that the minimum and multiplication operators are the best (Table1). Type of alignment is effective. Function improved in 66% of cases by applying GMIDW-F(1) and 44% of cases by applying GMIDW-F(2). The best function and alignment is determined by h and d. The classification does not affect for choosing the Fuzzy operator (Table1). It can be concluded that there is no restriction for parameters, classification is ineffective, the minimum and multiplication operators have priority and the alignment of h and d should be considered.   Table 1 - ratio of optimal operation of various categories All rains 50-70 40-50 30-40 20-30 10-20 5-10 Operator 215 6 11 39 64 90 5 No. days 31% 33% 9% 49% 28% 27% 60% Multiply 57% 67% 73% 41% 59% 60% 40% Minimum 7% 0% 9% 5% 6% 9% 0% Maximum 4% 0% 9% 5% 5% 1% 0% Sum 1% 0% 0% 0% 2% 0% 0% Sum of Sqrt.   Table 2 - Effect of different signs of  m and n in some clasification Operator Sign(m , n) 10-20 20-30 30-40 40-50 Total   Multiply   67% 89% 74% 100% 76%   33% 11% 26% 0% 24% Minimum   65% 66% 75% 88% 67%   35% 34% 25% 12% 33%                     Table 3 – Statistics of RSAE in categories categories 5-10 10-20 20-30 30-40 40-50 50-70 Mean(RSAE) 84 138.7 201 242.5 340.3 314.2 Max(RSAE) 93.5 295.8 320.4 426.6 426.8 407.7 min(RSAE) 72.6 64.1 106.8 129.3 238.5 236 range(RSAE) 20.9 231.7 213.6 297.3 143.3 169.7 Table 4 –  The alignments ratio at fuzzy operators and domain of m&n Range m Range n model operator percent total     GMIDW-F(1) multiply 76% 100%     GMIDW-F(2) multiply 24%     GMIDW-F(1) minimum 67% 100%     GMIDW-F(2) minimum 33%     GMIDW-F(1) maximum 60% 100%     GMIDW-F(2) maximum 40%     GMIDW-F(1) sum 22% 100%     GMIDW-F(2) sum 78%}, keywords = {regionally interpolation,GMIDW-F,Fuzzy theory,Genetic Algorithms,daily rainfall}, title_fa = {درونیابی بارش روزانه حوضه آبریز دشت مشهد}, abstract_fa = {    تخمین روزانه بارش در ایستگاه ‌ها یا نقاط خاص یک ناحیه نیاز اساسی برای پژوهش‌های آب و هواشناسی است. فاصله، تنها وزن روش کلاسیک درونیابی فاصله‌معکوس (IDW) است. اضافه کردن وزن ارتفاع به‌آن منجر به‌روش اصلاحی MIDW می‌شود. چیدمان دو وزن فوق به‌دو صورت قابل انجام است. هدف این مقاله بررسی تاثیر دو چیدمان وزن‌های ارتفاع و فاصله در MIDW و باتلفیق عملگرهای فازی (بیشینه، کمینه، جمع، ضرب و مجذورمربعات) و الگوریتم‌ژنتیک است (GMIDW-F). عملگرهای فازی برای یکپارچه‌سازی و الگوریتم ژنتیک برای بهینه‌سازی وزن‌ها است. تحلیل‌ها روی 215 بارش‌روزانه مربوط ‌به 49 ایستگاه باران‌سنج حوضه‌آبریز دشت مشهد واسنجی شد. خطای درونیابی بارش‌روزانه باGMIDW-F به‌صورت منطقه‌ای تحلیل شد. عملگرکمینه بهترین (سهم 57%) و سپس ضرب (سهم 31%) در بهینه‌سازی دارد. سهم سه عملگر دیگر بیشینه(7%)، جمع (4%) و مجذورمربعات (1%) است. تابعGMIDW-F بهینه 66% از موارد با چیدمان معکوس ارتفاع و فاصله و 34% از موارد با نسبت ارتفاع به فاصله حاصل شد. به‌منظور رفتارشناسی بارش، اطلاعات براساس شدت بارش رده‌بندی شد (حداقل یک بارش بین 10-5، 20-10 ، ... و بیش از 50 میلی متر تفکیک شد) و مشخص شد که رده‌بندی تاثیری در انتخاب عملگرهای فازی ندارد. تعداد حالت‌هائی که تاثیر فاصله صفر باشد، یک مورد و 17مورد تاثیر ارتفاع صفر بود. لذا وجود حداقل یک‌کدام از آنها در معادله ضرورت دارد. استفاده از چیدمان‌ها و عملگرهای مختلف فازی امکان رسیدن به پاسخ بهتررا فراهم می‌کند. پهنه‌بندی بارش (22/1/1388) با دو روش GMIDW-F و IDW مقایسه نموداری شد. آماره‌ی خطا (RSAE) به‌ترتیب  213 و 252 میلی‌متراست. روش IDW بارش صفر را حداقل 7 میلی‌متر (فرا برآورد) و در یک نوار افقی برآورد کرد. حداقل برآورد روش GMIDW-F؛ 5/1 میلی‌متر و نقاط اطراف نیمساز ناحیه اول قرار گرفتند که برآورد بهتری توسط این روش است. پهنه‌بندی روش GMIDW-F نیز رفتار مناسب‌تری  ارائه کرد.    }, keywords_fa = {درونیابی­ منطقه­ ای,MIDW,نظریه ­فازی,الگوریتم­ ژنتیک,مشهد}, url = {https://clima.irimo.ir/article_14935.html}, eprint = {https://clima.irimo.ir/article_14935_fe134051a25b794d564fae93aec82690.pdf} } @article { author = {Farajzadeh, M. and Ahmadi, M. and Alijani, B. and Qavidel Rahimi, Y. and Mofidi, A. and Babaeian, I.}, title = {Study on Variation of Major Teleconnection Patterns (MTP) associated with Iran’s Precipitatio}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {31-45}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction: In this study, the effects of some leading Teleconnection Patterns of atmospheric circulation, on regional-scale for Middle East, along with precipitation over Iran have been investigated. Different types of data including Teleconnection Indices and monthly precipitation data weather stations have been used. One of important parameters is Precipitation that has change from a year to other year. Teleconnection Patterns and Indices are remote controller of precipitation amount variation in Iran and the entire world. So in this paper on of main goal is relationship between teleconnection patterns and precipitation data in main meteorological station of IRAN that have long term data base. Material and Methods: By using Statistical analysis (Correlation and linear regression) over Precipitation data via 25 Weather Station from 1951-2005 in whole Country and Teleconnection Indices from NOAA, we analysis and notice to archive component that have up most impact on Precipitation variation in Iran. Results and Discussion: According to the relationship between major teleconnection indices and Iran's rainfall, we investigate to recognition of their effects and phenomena on climate of Iran. As a results the Sum of 24 stations, the precipitation of Iran have decrease trend. Eventually changes in some Teleconnection indices cause decreasing rainfall as SCAND index, GlobLandTA, NH ssta+Land, NH ta Land, NTA and EA in spite of intensifying of some indices that increasing rainfall as SST4, MEI, PDO, NOI. Conclusion: In resent decade, Global increasing temperature causes change over most atmospheric parameters in whole world and the other hand these atmospheric parameters themselves have impact as feedback over other branches of Climate and weather machine. One of important results in current paper is showing effect of Global Warming that cause decreasing in average of Iran's precipitation by means of change in some teleconnection pattern in time series. Also the results indicate that ENSO is the most effective factor and it can influence on variation of precipitation, temporally and spatially, on all type of climate regimes in Iran.    }, keywords = {Iran,climatic indices,Teleconnection patterns,Variation}, title_fa = {بررسی وردایی الگوهای پیوند از دور و اثر آن‌ها بر بارش ایران}, abstract_fa = {    این تحقیق با هدف درک تغییرات یا نوسان های شاخص های بارز پیوند از دور و اثرات آن ها روی بارش سالانه کشور ایران صورت کرفته است.داده‌های مورد استفاده بارش ماهانه بیست و چهار ایستگاه هواشناسی در سطح کشور از سازمان هواشناسی کشور و داده های ماهانه شاخص ها و الگوهای بارز پیوند از دور از مرکز اقیانوس شناسی و جوشناسی ملی نوآ (NOAA ) در دوره آماری 2005-1951 دریافت گردید. در ادامه با استفاده از روش های آماری مانند همبستگی پیرسن و رگرسیون، تجزیه و تحلیل داده ها انجام شد. یافته های تحقیق نشان دهنده تغییر الگوی بارشی کشور زیر تاثیر تغییر برخی از الگوهای پیوند از دور می باشد؛ به طوری که تغییر در برخی شاخص ها نظیر الگوهای پیوند از دور در اقیانوس اطلس و اسکاندیناوی سبب کاهش بارش و افزایش نمایه های اقیانوس آرام در جهت بهبود بارش میانگین کشور شده است. به عنوان نتیجه مهم دیگر این تحقیق، گرمایش جهانی به عنوان یکی از اصلی ترین عوامل کاهش و نوسان بارش کشور طی ده های جدید شناسایی شد.}, keywords_fa = {بارش ایران,شاخص ها و الگوهای دورپیوندی,نمایه های اقلیمی,وردایی}, url = {https://clima.irimo.ir/article_14936.html}, eprint = {https://clima.irimo.ir/article_14936_058e1cb6f74ae3439e6dd107faf059c6.pdf} } @article { author = {Khodadi, M.M. and Azadi, Majid and Ghaemi, H.}, title = {Role of transient synoptic systems on seasonal moisture transport over Iran}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {47-62}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Materials and Methods An attempt is made to examine the moisture sources and transport over Iran and its relation to other influencing factors during different seasons for a 30 years period (1981-2010. Using National Center for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) data with 0.5 degree horizontal resolution, described by Saha et al., 2010, several fields including geopotential height, horizontal wind and temperature at several vertical levels along with sea level pressure, precipitable water and rotational and divergent components of the moisture flux vector are presented and analyzed.   Results and discussion Results show that, during the autumn, the subtropical high is located over south of Iran and west of Indian Ocean and there is anticyclonic curvature of moisture flux vector and moisture transport from over Oman sea to south of Iran. Examination of the anomaly of rotational component of moisture flux vector indicates that formation of thermal low over south of Iran causes moisture transport form over Oman sea to southeast of Iran and intensification of eastern Mediterranean low causes moisture transport from over east of Mediterranean to northwest of Iran. During winter, subtropical anticyclone located over east of Saudi Arabia causes anticyclonic curvature of moisture flux vector over west of Indian ocean, south of Red sea and east of Saudi Arabia and consequently moisture transport to west and southwest of Iran. Examining the anomaly of rotational component of moisture flux vector indicates that intensification of eastern African low causes moisture transport from over Red Sea to southwest of Iran and eastward migration of high pressure system from eastern Europe to Mediterranean causes moisture transport to northwest and southern coast of the Caspian sea. During Spring, eastward expansion of subtropical anticyclone over west of Indian ocean and also general circulation of Indian Ocean due to Indian Ocean Dipole (IOD) at 10-20 N, anticyclonic curvature of moisture flux vector over west of Indian ocean is formed and moisture transport to Indian subcontinent and southeast of Iran is significant. Also, formation of thermal low over southeast of Iran causes cyclonic curvature of moisture flux vector anomaly and moisture transport from over Oman sea to southeast of Iran. Anticyclonic curvature of moisture flux vector anomaly due to expansion of high pressure to east of Mediterranean and northwest of Iran, causes moisture transport from over east of Mediterranean to northwest of Iran. During summer, northward migration of subtropical high to higher latitudes 25-35N over Indian subcontinent and Monsoon intensification and Indian ocean general circulation associated with IOD, moisture transport from over west of Indian ocean to Indian subcontinent and then to east of Iran are observed. It is to be noted that during summer, a thermal low pressure region is formed over east of Iran and extended up to south of Alborz and east of Zagross mountain ranges. Coexistence of the thermal low with transported moisture from Indian subcontinent, causes a moisture flux vector anomaly is observed. Moreover, formation of thermal low pressure over this region causes anomaly of moisture transport from over Oman Sea to southeast and east of Iran.   Conclusion   In this research, the important role of the subtropical high pressure in combination with passing synoptic systems on the moisture transport over Iran during different seasons is investigated. It is concluded that during winter the subtropical high pressure has its prominent role in moisture transport from over Arab and Red Seas toward west and south-west of Iran. Moreover western synoptic systems are associated with moisture advection over west and south west of Iran. As such, a moisture convergence is formed over west of Iran During summer the subtropical high pressure is extended over Iran and Indian subcontinent. As such there is a moisture transport towards Indian subcontinent and from there toward south east and east of Iran. And thermal low pressure systems cause moisture convergence and subsequently summer time monsoonal rain fall over south of Iran.  }, keywords = {Moisture flux vector,stream function,subtropical high}, title_fa = {نقش سامانه‌های همدیدی گذرا در ترابرد فصلی رطوبت روی ایران}, abstract_fa = {در این پژوهش منابع رطوبت و چگونگی ترابرد رطوبت روی ایران و عوامل موثر بر آنها در فصل‌های مختلف در یک دوره 30 ساله (1981-2010) بررسی شده است. به این منظور از داده های میانگین ماهانه cfsr با تفکیک افقی 5/0 درجه برای محاسبه و تحلیل کمیت‌های ارتفاع ژئو پتانسیل، باد، دما، فشار سطح دریا، آب‌بارش‌شو، مولفه‌های چرخشی و واگرای بردار شار رطوبت و توابع جریان و پتانسیل بردار شار رطوبت استفاده شده است.نتایج نشان می دهد که در فصل پاییز با استقرار واچرخند جنب حاره روی نوار جنوبی ایران و غرب اقیانوس هند خمش واچرخندی بردار شار رطوبتو ترابری رطوبت از دریایعمان به جنوب ایران وجود دارد. همچنینبررسی بی‌هنجاری مولفه چرخشی بردار شار رطوبت نشان‌ دهنده ترابرد رطوبت از دریای عمان به جنوب شرق ایران در اثر شکل گیری چرخند گرمایی روی جنوب ایران و ترابرد رطوبت از شرق مدیترانه به شمال غرب ایران ناشی از تقویت چرخند شرق مدیترانه است. در فصل زمستان، واچرخند جنب حاره روی شرق عربستان موجب خمش واچرخندی بردار شار رطوبت روی دریای عرب، جنوب دریای سرخ و شرق عربستان و در نتیجه ترابرد رطوبت به نواحی غرب و جنوب غرب ایران است. بررسی بی‌هنجاری مولفه چرخشی بردار شار رطوبت نشان دهنده ترابرد رطوبت از دریای سرخ به جنوب غرب ایرانبراثر تقویت چرخند شرق آفریقا و ترابرد رطوبت به شمال غرب و سواحل جنوبی دریای خزر ناشی از نفوذ پرفشار از شرق اروپا به دریای مدیترانه است. در فصل بهار به علت نفوذ واچرخند جنب حاره روی غرب اقیانوس هند و گردش کلی آب اقیانوس وابسته به نوسان دو قطبی اقیانوس هند (IOD) در عرض‌هایN20-15 خمش واچرخندی بردار شار رطوبت روی غرب اقیانوس هند شکل می‌گیرد و ترابرد رطوبت به شبه قاره هند و جنوب شرق ایران قابل توجه است. همچنین خمش چرخندی بی‌هنجاری بردار شار رطوبت ناشی از شکل‌گیری‌ چرخند گرمایی روی جنوب شرق ایران، موجب ترابرد رطوبت از دریای عمان به جنوب شرق ایران می‌شود و خمش واچرخندی بی هنجاری بردار شار رطوبت ناشی از نفوذ واچرخند روی شرق مدیترانه و شمال غرب ایران، موجب ترابرد رطوبت از شرق مدیترانه به شمال غرب ایران می شود. در فصل تابستان با نفوذ واچرخند جنب حاره به عرض‌هایN35-25 و تقویت مونسون هند و گردش کلی آب اقیانوس هند ناشی از دو قطبی اقیانوس هند، ترابرد رطوبت از غرب اقیانوس هند به شبه قاره هند و جنوب شرق ایران مشاهده می‌شود. همچنین بر اثر شکل گیری چرخند گرمایی در این ناحیه بی هنجاری ترابرد رطوبت از دریای عمان به جنوب شرق و شرق ایران مشاهده می‌شود.}, keywords_fa = {بردار شار رطوبت,تابع جریان,واچرخند جنب‌حاره}, url = {https://clima.irimo.ir/article_14954.html}, eprint = {https://clima.irimo.ir/article_14954_993e0239289e738ed0d996c0277d149f.pdf} } @article { author = {Mohammadi, H. and Yolmeh, I.}, title = {Statistical and Synoptic Analysis of Forest Fire in Golestan Province (Case Study: 16 December 2005 and 9 March 2006)}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {63-80}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction When temperature increases and relative humidity decreases, especially if this condition is associated with the warm wind, the condition is prepared for forest fires. In seasons that branches and leaves have less moisture, fire events will happen more likely. Forest fires takes a lot of damage to the country's natural resources each year. In recent years effects of temperature is rising and changing of precipitation pattern on forest fires risk had been different on various regions of Alps (wastl et al, 2012). At Australian Alps the foehn winds suddenly changed climatic parameters and increased risk of forest fires (sharples et al, 2010). Climate change is an important factor in causing forest fires in northern Europe and Asia (Groisman et al, 2007). During the period 1980-2000 the mean burnt area by wildfires in Portugal was higher than 90000 ha per year (Pereira et al, 2005). Large forest fires in Portugal occur when the atmospheric circulation forms a prominent ridge over the Iberian Peninsula with the flow being dominated by a strong meridional component. These days are associated with south-easterly winds that led to warm advection from North Africa to the Iberian Peninsula (Pereira et al, 2005). Several forest fires also occur each year in Iran, especially in the northern forests. During the 1998-2005 periods, 1258 forest fires occurred in the northern forest area, where about 7623.29 hectares were burned (azizi & yusefi, 2009). In golestan province averagely occur 82 forest fires every year and forests with area of 740 hectares were destroyed (Department of Natural Resources, Golestan Province, 2006). Given the importance of forests and the role of Atmospheric Condition in causing forest fires, the relationship between fire event and Atmospheric Condition should be considered. Materials and methods Data used in this study includes meteorological and forest fire data. First, spatial and temporal distributions of forest fires were determined. Then in the fire occurrence days, meteorological data that consist of temperature, relative humidity, wind and pressure were surveyed. Precipitation and cloudiness were investigated in south slope of Alborz Mountains to ensure the formation of foehn wind. Finally synoptic patterns during fire event using sea level and upper level maps, along with vector wind and thickness maps were analyzed. Results and Discussion In temporal distributions, most of fire cases occurred in cold seasons.  Considering the spatial distributions, most fire cases were in the southeast of province. In fire occurrence time the temperature had a remarkable rise and the relative humidity had a remarkable decrease. Also there were high speed winds in all stations. Moreover rainfall had been occurred over southern slopes of Alborz Mountain. The synoptic pattern of weather maps showed that a low pressure was formed over Caspian Sea and a high pressure over Zagros mountain at sea level map. At 500 geopotential height, there was a deep trough over Eastern Europe and was formed a ridge over Iran. Vector wind maps ​​shows that, wind direction is south west - North East at upper levels. In fire occurrence days, thickness of atmosphere was high in studying region. Conclusion High number of fire occurrence in cold seasons showed that, there was no relationship between warm season and fire occurrence. Remarkable increase of temperature and remarkable decrease of relative humidity during the fire times along with high speed wind showed that, foehn had been occurred. In addition, foehn occurrence was confirmed by existence of precipitation and cloudiness in Alborz southern slopes. At sea level map, a low pressure tongue over Caspian Sea is stretched. If this tongue accompanied with deep trough at 500 geopotential height, a low pressure over Caspian Sea is formed. With the formation of a high pressure over the Zagros Mountains, the pressure gradient is created between the center of Iran and the Caspian Sea. At 500 geopotential height, placement of a ridge over Iran, along with southwestern wind in upper level, forms warm advection from low latitudes to northern area of Iran. Also high thickness of atmosphere in studying region confirms warm advection from Arabian Peninsula and north of Africa. Existence of Alborz Mountains in front of low-level air makes up the foehn in northern coast of Iran.  }, keywords = {Advection,foehn,Forest Fire,Golestan,Synoptic Analysis}, title_fa = {تحلیل آماری - همدیدی آتش سوزی جنگل در استان گلستان (مطالعه موردی :روزهای 25 آذر و 18 بهمن سال 1384)}, abstract_fa = {آتش‌سوزی جنگل‌ها یکی از مخاطراتی می‌باشد که با شرایط جوی مرتبط است. با مطالعه شرایط جوی در مواقع رخداد آتش‌سوزی می‌توان به این ارتباط پی برد. داده‌های استفاده شده در این تحقیق شامل داده‌های هواشناسی در دوره آماری 1386-1377 به همراه گزارش‌های وقوع آتش‌سوزی جنگل‌ها در همین دوره می‌باشد. در این تحقیق تعداد و مساحت آتش‌سوزی ها به همراه روند و پراکندگی زمانی و مکانی آنها مورد بررسی قرار گرفت. سپس داده‌های هواشناسی و نقشه‌های سطح زمین تا 500 هکتوپاسکال به همـراه نقشه‌های دمای سطوح بالا و نقشه‌های ضخامت و بردار باد تحلیل شد. بررسی‌ها نشان می‌دهد که در دوره آماری تعداد و وسعت آتش‌سـوزی‌ها روند افزایشی دارد. از نظر پراکندگی زمانی، بیشترین فراوانی آتش‌سوزی مربوط به دوره‌ی سرد سال است. از نظر مکانی نیز بیشتر آتش‌سوزی‌ها در جنوب‌شرق استان متمرکز است. آرایش همدیدی نقشه‌های هوا نشان می‌دهد که در سطح زمین با شکل گیری یک مرکز کم فشار بر روی خزر و یک مرکز پر‌فشار بر روی زاگرس بین مرکز و شمال ایران گرادیان فشار ایجاد می‌شود.قرارگیری پشته بر روی ایران و در جلوی ناوه عمیق شرق اروپا در سطح 500 هکتوپاسکال، به همراه جهت و سرعت باد در سطوح مختلف جو باعث ایجاد جریانات جنوب‌غرب به شمال‌شرق و فرارفت هوای گرم عرض‌های پایین‌تر (به ویژه شمال آفریقا و شبه‌جزیره عربستان) به نواحی مرکزی و شمال کشور می‌شود. نقشه‌های ضخامت نیز مؤید فرارفت گرم در روزهای وقوع آتش‌سوزی می‌باشد. علاوه بر این کوهستان البرز باعث رخداد گرمباد در دامنه بادپناه خود می‌شود.  }, keywords_fa = {آتش‌سوزی جنگل,تحلیل همدید,فرارفت,گرمباد,گلستان}, url = {https://clima.irimo.ir/article_14955.html}, eprint = {https://clima.irimo.ir/article_14955_fee89959312e9275f24f96d63523c20e.pdf} } @article { author = {Siabi, N. and Sanaeinejad, H.}, title = {An investigation into using of combined geostatistical methods to increase precision in climatological classification and climatic parameters zoning in great Khorasan}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {81-32}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction: Climatic parameters’ modeling is very important in environmental data processing. This is a consequence that climatic parameters vary dramatically in time and space. Moreover, the climate variables are dependent to each other and also to earth surface conditions such as height. The other problem is that climatic parameters are measured as a point based variables in weather stations. However, for environmental studies it is crucial to have continues spatial and temporal perception for these parameters. There are different methods to provide such perceptions from climatic variables. Some geo-statistical models are used to interpolate the data. The ability of these models for spatial interpolation increases significantly, if co-variables are used (Daly et al. 1994). In Kriging methods the sparsely sampled variables can be completed by secondary attributes that are more densely sampled. Topography and weather-radar observations could be used as secondary information in these models. Material and methods: The study area is Khorasan province (Northeast of Iran, longitude 55◦W to 61◦E and latitude 38◦S to 30◦N). The area is approximately 248,000 km2 in a semiarid climate.  The monthly and annual precipitation has been averaged for the climate normal period of 1993 – 2009. We were very strict in data selection, only keeping weather stations with complete years. After assuring the raw data quality, monthly and annual climate data averages were calculated. This information was loaded to the spatial database and used as the source of input data for the gridding process. We used geostatistic algorithms for assessment, interpolation and preparing spatial and temporal maps for climatic parameters in North East of Iran. Different interpolation methods including ordinary Kriging (OK), Inverse Distance Weighted (IDW), Co-Kriging (COK) and Kriging with External Drift (KED) were examined. The dependence of the variables (including solar radiation, evaporation, air temperature and precipitation) to height as ancillary variable was also investigated in different monthly and annual time scales. Thornthwaite climate classification method was used for climate zoning. Then the effect order of each climatic variable in the climate zoning precision was assessed by using multivariate methods such as COK and KED. Mean Squared Error (MSE) was used to compare the models results. Different results were obtained for different variables. Results and discussion: According to MSE values, COK and IDW had the highest and lowest accuracy among the methods for temperature respectively. The pattern of MSE changes were also similar for all of the four methods when MSE values increased from January to June showing that the accuracy of the models decreased from cold to warm season. OK and IDW showed more errors in the warm months than in cold months for precipitation, while KED and COK with elevation as ancillary variable showed better results. Considering all of the variables, KED provided the most accurate spatial interpolation among all of the applied models. However, COK was more accurate for evapotranspiration interpolation with the minimum MSE with increasing toward warm months as other variables. There is only one exception in applying COK method for evapotranspiration and temperature where MSE is almost the same in cold and warm seasons. For interpolating of relative humidity, there was not a substantial difference between K and KED, while COK and IDW showed smaller values of MSE. In this case MSE values decreased from clod to warm months. All of the four interpolation methods were used for climatological zoning based on Thornthwaite Climatological Index values. MSE values decreased in order of IDW, K, KED and OCK respectively. Using meteorological parameters such as temperature and evapotranspiration as ancillary variables in multivariable methods such as COK and KED showed a substantial improvement in the accuracy of climatological zoning. COK model provided better results for air temperature, while KED method showed more precision for precipitation. For example the resulted MSE from K, COK and KED methods for temperature in January was 2.19, 0.004 and 1, in February was, 2.63, 0.005 and 1.27 in March was 2.51, 0.004 and 1.33 respectively. The results also showed that MSE values substantially increased from March to July which means that using elevation in this model for estimating temperature during these months provides less precision. Conclusion: It was concluded that temporal and spatial distribution of precipitation is affected more by elevation among all of the climatic parameters, followed by air temperature, evaporation and relative humidity respectively. It should be noticed that evaporation is affected by elevation during cold season (from October to March). Among the environmental parameters, evaporation, elevation, relative humidity and precipitation had the most effect on spatial and temporal climate variability in the area of study respectively. Temperature provided different results depending on the climate index that was used for classification and zoning.  }, keywords = {evaluation of accuracy,spatial analysis,climatic parameters,Classification of Climate}, title_fa = {بررسی روش های ترکیبی زمین آمار در افزایش دقت طبقه بندی اقلیمی و نیز پهنه بندی عناصر اقلیمی شمال شرق ایران}, abstract_fa = {      متغیر های اقلیمی به یکدیگر و نیز به وضعیت سطح زمین مانند ارتفاع و پوشش گیاهی وابسته اند. این در حالی است که این متغیر ها به صورت نقطه ای در ایستگاه های هواشناسی اندازه گیری می شوند. برای انجام مطالعات محیطی و تحقیقات کشاورزی، داشتن درک صحیحی از تغییرات پیوسته مکانی و زمانی این متغیر ها از اهمیت بسزایی برخوردار است. از طرفی طبقه بندی های اقلیمی به دلیل استفاده از روابط ساده و متغیر های کم از دقت بالایی برخوردار نیستند، از این رو در این تحقیق دو هدف دنبال شده است: اول اینکه از الگوریتم های زمین آمار برای درون یابی، ارزیابی و تهیه نقشه های تغییرات مکانی و زمانی متغیر های اقلیمی در شمال شرق ایران استفاده شد و آنگاه روش تورنت وایت[1] برای طبقه بندی اقلیمی انتخاب و درجه تاثیر هر متغیر اقلیمی در افزایش دقت طبقه بندی اقلیمی با استفاده از روش های چند متغیره بررسی شد. روش ها ی درون یابی در این تحقیق کریجینگ معمولی ([2]OK) ، کو کریجنگ ([3]COK)، روش وزن دهی عکس فاصله ([4]IDW) و روش ([5]KED) بود. با استفاده از روش های چند متغیره (COK,KED)، وابستگی متغیر هایی مانند (تبخیر، دمای هوا، بارندگی و رطوبت نسبی) به ارتفاع به عنوان متغیر ثانویه با گام های زمانی ماهانه و سالانه مورد بررسی قرار گرفت. مقدار MSE برای مقایسه نتایج مدل ها استفاده شد و نتایج متفاوتی برای هر متغیر به دست آمد. روش COK برای دمای هوا نتایج بهتری را نشان داد، در حالی که روش KED برای بارندگی نتایج دقیق تری را حاصل کرد. به عنوان مثال MSE برای برای دما از روش های K، COK و KED در ماه ژانویه به ترتیب مقادیر 19/2، 004/0 و 1 ، در ماه فوریه 63/2، 005/0 و 27/1 و در ماه مارس 51/2، 004/0 و 33/1 به دست آمد. همچنین نتایج نشان داد که مقادیر MSE از ماه مارس تا جولای افزایش می یابد، بدین معنی که استفاده از ارتفاع در این مدل برای تخمین دما در این ماه ها دقت کمتری دارد. همچنین مشاهده شد که توزیع زمانی و مکانی بارندگی نسبت به سایر متغیر های مورد مطالعه، بیشترین تاثیر پذیری را از تغییرات ارتفاع دارد. قابل ذکر است که بر اساس این تحقیق تبخیر در طول ماه های سرد از ارتفاع تاثیر می پذیرد( اکتبر تا مارس). و از میان متغیر های محیطی به ترتیب تبخیر، ارتفاع، رطوبت نسبی و بارندگی در تغییر پذیری زمانی و مکانی اقلیم در منطقه مورد مطالعه بیشترین تاثیر را دارند. دما نتایج متفاوتی بسته به شاخص اقلیمی مورد استفاده برای پهنه بندی اقلیمی حاصل کرد. Email: negarsiabi63@gmail.com [1]. Thornthwaite [2]. Ordinary kriging [3] .Co-Kriging [4] .Inverse Distance Weighted [5] .Kriging with an External Drift}, keywords_fa = {ارزیابی دقت,تحلیل مکانی,عناصر اقلیمی,زمین آمار,طبقه بندی اقلیمی}, url = {https://clima.irimo.ir/article_14957.html}, eprint = {https://clima.irimo.ir/article_14957_a2f66ae403f7010630fb057d73ccd10b.pdf} } @article { author = {Hajrasouliha, O. and Hassanzadeh, S. and Latifi, A. R.}, title = {The Role of Physical Processes on Oil Pollutants Distribution in the Persian Gulf}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {93-106}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction   Persian Gulf for having the world's major oil and gas fields exposed to contaminants such as oil pollution and the pollutants are associated with them. In this study the distribution of pollution in various conditions is simulated by a hydrodynamic model to determine the behavior of the oil pollutants spill into the sea and the effect of the physical processes such as wind, heat fluxes and wind stress on the distribution of these contaminants. The COHERENS model was used to simulate the oil pollutants distribution which coupled with biological and contaminant modules and has the ability to solve transport equation using sigma coordinate in the vertical direction and Cartesian coordinate in horizontal. The Persian Gulf ecosystem is facing a variety of stresses due to its location within the richest oil province in the world that hosts more than 67% of the world oil reserve. In recent years, researchers have studied the pollution diffusion in the Persian Gulf using different approaches, but nobody have done a complete work in the Persian Gulf that contain both oil pollution modelling, and the effect of physical processes on it.  There is no published research about the effect of wind forces and heat fluxes on oil pollution distribution in the Persian Gulf. In fact the main idea of this study is to notify the role of wind, heat fluxes and wind stress in oil pollution diffusion which accomplished by set up an Eulerian model, i.e. COHERENS.   Materials and methods COHERENS is a three-dimensional, multi-purpose numerical model for coastal and shelf seas. The hydrodynamic model is coupled with biological, re-suspension and contaminant models, and resolves mesoscale to seasonal processes. The code has been developed over the period 1990 to 1998 by a multinational group as part of the MAST projects. The numerical model calculates in Cartesian coordinates, with the vertical axis representing sigma coordinates, the horizontal axis representing Arakawa C grid. The model domain includes the Persian Gulf with one open boundary in the Gulf of Oman, covering the area of 47°–58° E; 24°–31°N, five sigma layers are used in the vertical direction. As the input data, the meteorological parameters (wind components at 10 meters above ground, air temperature relative humidity, cloud cover and precipitation) are needed. All these data were derived from the National Oceanic and Atmospheric Administration (NOAA) and applied in the model as monthly mean values.  The model equations are derived with the following assumptions: The Boussinesq approximation is applied which means that the density is constant except for the Earth’s gravity force.  The vertical component of the momentum equations reduces to the hydrostatic balance between the vertical pressure gradient and the gravity force. The horizontal component of the Earth’s rotation vector is set to zero. The assumption becomes invalid for non-hydrostatic water masses or near the equator. The equations for the three-dimensional mode consist of the momentum equations, the continuity equation and the equations of temperature and salinity. Results and discussion The winter winds are predominantly from northwest, along the axis of the Gulf basin. During summer the northwesterly winds of the Gulf are affected by the cooler winds of the southwest monsoon. Changes in energy stored in the upper ocean are the results of an imbalance between input and output of heat through the sea surface. The heat transfer across or through a surface is called a heat flux. The wind stress is the shear stress exerted by the wind on the surface of large bodies of water such as oceans or seas—in other words, it is the vertical transfer of horizontal momentum from the atmosphere to the ocean. Model results show that oil spill in the northern Persian Gulf moves toward the northern Persian Gulf and Bushehr coast along the Iranian coast. Afterwards, due to the counterclockwise currents of that region it moves toward southwest of Gulf along the Arabian coast. The results of simulation indicate that the wind speed and its effect on heat fluxes component is the main reason how the oil pollution is distributed. The results of numerical simulation are in good agreement with what has been observed regarding oil pollution distribution and its circulation patterns in the region. Conclusion The influence of forces of wind, heat flux, and wind stress on oil pollution distribution was studied separately. The effect of wind on the distribution of oil pollution is more significant than the heat fluxes and the wind stress. The results of numerical simulation show that the wind stress mainly affects surface diffusion of oil pollution. In summary, the wind speed and its effect on heat flux component are the main factors influencing the distribution of oil pollution.  }, keywords = {COHERENS model,heat fluxes,oil pollutants,Persian Gulf,wind,wind stress}, title_fa = {نقش فرآیندهای فیزیکی بر نحوه توزیع آلاینده‏های نفتی در خلیج فارس}, abstract_fa = {   خلیج فارس به خاطر دارا بودن عمده میادین نفتی و گازی جهان در معرض آلودگی‏هایی مانند آلودگی‏های نفتی و گسترش آلاینده‏های مرتبط با آن می‏باشد. از آنجا که در صورت نشت آلاینده‏های نفتی به دریا، تشخیص رفتار آن‏ها بر روی آب و دانستن تأثیر فرآیندهای فیزیکی از قبیل باد، شارهای گرما و تنش باد بر نحوۀ پخش این آلاینده‏ها، ما را در امر جمع‏آوری آن‏ها کمک می‏کند، در این تحقیق قصد داریم نحوه توزیع این آلودگی‏ها را در شرایط مختلف توسط مدل عددی سه‏بعدی هیدرودینامیکی شبیه‏سازی کنیم،  به این منظور از مدل کوهرنس که با مدول آلودگی و بیولوژیکی جفت شده و قابلیت حل معادلات انتقال و پخش آلودگی را با به‏کارگیری مختصات سیگما در جهت قائم و مختصات دکارتی در جهت افقی دارد، برای شبیه‏سازی انتقال و پخش آلودگی‏های نفتی استفاده شده است.  نتایج مدل نشان می‏دهدکه آلودگی نفتی نشت یافته در بخش شمالی خلیج فارس، تحت تأثیر تمامی نیروهای اعمال شده در مدل دارای حرکتی به سمت شمال خلیج فارس و سواحل بوشهر در امتداد سواحل ایرانی بوده و سپس تحت تأثیر جریانات پادساعتگرد آن منطقه قرار گرفته و در امتداد سواحل عربی دارای حرکتی متمایل به بخش جنوب غربی خلیج فارس می‏گردد، همچنین  نتایج شبیه سازی مدل بیانگر این نکته بود که تأثیر نیروی باد بر نحوه پخش آلودگی و کاهش غلظت آلاینده‏ها نه به خاطر تنش باد ایجاد کرده، بلکه به خاطر سرعت باد و تأثیری که باد بر مولفه‏های شار گرما می‏گذارد، می‏باشد.  نتایج حاصل از شبیه‏سازی مدل در مورد نحوه توزیع و پخش آلودگی های نفتی توافق خوبی با شواهد مشاهداتی و همچنین الگوی جریانات موجود در منطقه دارد. }, keywords_fa = {آلاینده ‏های نفتی,خلیج فارس,مدل کوهرنس,باد,شارهای گرما,تنش باد}, url = {https://clima.irimo.ir/article_14958.html}, eprint = {https://clima.irimo.ir/article_14958_2bc6a18308b5978b8ee0a7e8e8dc7edc.pdf} } @article { author = {Arvin, A.A. and Shaemi, A. and Shojaeizadeh, K.}, title = {Tourism Calendar of Fars Province}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {107-116}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction Certainly, tourism is an important factor in the development of countries. Growth of this section is faster than that of the global trade in wealth production. Climate, as a geographical factor forming geographical space, can influence tourism. On the other hand, unpleasant climatic conditions have seriously negative effects on tourism. Most tourists, when choosing the destinations, take climatic conditions into consideration. On the other hand, unfavorable climatic conditions can reduce the positive aspects of a regional tourist attraction, imposing a considerably adverse impact on tourism. In this paper, this issue was investigated in the Iranian province of Fars, one of the most important tourist destinations because of its cultural attractions. The main purpose of this research was identifying appropriate conditions and suggesting a tourism temporal calendar that can improve quality and quantity of services offered to the tourists. For this purpose, a method was employed to calculate Man Ray physiological equivalent temperature (PET) and mean survey forecast (PMV) so that tourism and climate could be evaluated in the province. Another objective of this paper was to identify place and time conditions of tourism in the province to propose a calendar. Hopefully, this would lead to improving the quality of tourism services offered in the province. Material and Methods In this research, we used meteorological data in synoptic and climatologic stations at a period extending from 1990 to 2005. Meteorological indices included: temperature, humidity, wind speed, vapor pressure and cloudy cover. Personal variables were: stature, weight, age, coverage and thermal value based on human activity. Assessment Method used for measuring climate comfort for tourism was based on the physiological equivalent temperature index and the average of polls predicted. The index combines indicators of temperature, body's physiological balance with the environment, based on the known efficiency evaluation of climate comfort and tourism. However, one of the most widely accepted and commonly used physiological parameters of temperature is heat index, which is the physiological equivalent of the energy balance equation and is derived from human’s body. In the first step, climatic comfort method assessment was used to calculate Physiological Equivalent Temperature (PET) and Predicted Mean Vote (PMV). Then comfort isopleths were drawn based on PMV and PET index. PMV and PET showed similar results, but we drew PET method isopleths maps because PET method indicated temporal and spatial bio-climatic conditions much better than PMV and presented bioclimatic zone more clearly than PMV.   Results and discussion Drawing PET isopleths curves for different stations in all months showed temporal and spatial comfort conditions in Fars province. Investigations showed that in Abade, Eghlid, Bavanat and Neirise stations, severe cold tension was dominant in January, February and March. On the other hand, In Lar, Darab, Lamerd and Jahrom, severe hot tension was dominant in June, July and August. In warm regions of province, there were comfort conditions in February–March in spring and November-December in autumn. In the cool regions of province, there were comfortable conditions in February-June and September-October. In fact, appropriate climatic conditions were confirmed in 9 months, thereby showing excellent qualification. Results, which were based on regionalization comfort maps, showed that winter provided favorable tourism conditions in the southern area of Fars province. Conclusion Planning for tourism development needs to consider temporal and spatial analysis. This work employed comfort isopleths maps. Therefore, drawing the maps for each of the spatial distribution of tourism can help identify the vulnerable areas. The analysis of maps showed that at 8.8 percent of annual times, severe conditions were dominant. Hence, it can be concluded that heat stress limits province's tourism much more than cold stress. At 13.8 percent of annual times, climatic comfort was dominant. If low heat and cold were added to it, a total 45.3 percent could be appropriate for tourism. However, this province, in 45.3% of  time, with a little warm, cool and comfortable weather can be a great potential for tourism. My assessment showed that isopleths diagram were good tools for determining comfort condition.Based on these findings, determination of the appropriate time for tourism in the province, due to the intense heat conflict in the north and south, is different. But, in all zones of the province, April and November are the best months for tourists.  }, keywords = {Ray Man Method,Fars province,Isopleths Map,tourism}, title_fa = {تقویم توریستی استان فارس}, abstract_fa = {اکثر گردشگران برای انتخاب مقصد گردشگری ملاحظات اقلیمی را مورد توجه قرار می دهند.در این مقاله نیز این مهم برای استان فارس بعنوان یکی از مقاصد مهم گردشگری ایران بدلایل دارا بودن جاذبه های فرهنگی مورد تحلیل قرار گرفته است. برای این منظور با استفاده از روشMan  Ray به محاسبه شاخص دمای معادل فیزیولوژیک (PET) و متوسط نظرسنجی پیش بینی شده (PMV) پرداخته شد و اقلیم گردشگری استان فارس مورد ارزیابی قرار گرفت. شاخص مورد نظر برای 14ایستگاه هواشناسی استان که دارای آمار مشترک 16 ساله بودند محاسبه و نتایج آن بر روی نمودارهای ایزوپلت و نقشه های پهنه بندی استان تحلیل گردید. بررسی توزیع زمانی-مکانی شرایط آسایش استان فارس بر روی نقشه های ایزوپلت نشان می دهد تنش گرما با 8/20 درصد اوقات سال بیش از تنش سرما (8/8 درصد اوقات) محدودیت گردشگری را در پی دارد. با این حال در 3/45 درصد اوقات سال شرایط کمی خنک، راحت و کمی گرم حکمفرما است که پتانسیل اصلی این استان برای توسعه گردشگری است بررسی نقشه ها پهنه بندی استان نشان می دهد در 9 ماه از سال نقاط مختلف استان دارای جاذبه گردشگری از نظر اقلیمی می باشند. در ماههای فصل زمستان تنها قسمت های جنوبی استان دارای شرایط مطلوبی برای گردشگری می باشند بطوری که در لامرد بهترین شرایط اقلیم آسایشی در ماههای ژانویه و فوریه می باشد. بهترین شرایط بیوکلیمایی در این استان مربوط به فصل بهار؛ ماههای آوریل و می و در فصل پاییز ماه نوامبر است. }, keywords_fa = {استان فارس,روشMan Ray,نقشه ایزوپلت آسایش,گردشگری}, url = {https://clima.irimo.ir/article_14962.html}, eprint = {https://clima.irimo.ir/article_14962_d70b32f212a038325fb1cd1fdeaa076d.pdf} } @article { author = {Behyar, M. B. and Kheyrandish, M. and Zamanian, M.}, title = {Investigation of climate change effects on early autumn chilling and late spring chilling in Iran using SDSM}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {117-128}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction: Increasing the greenhouse gases change the global climate and lead to global warming. Global warming makes change in dates of early and late chilling. These dates are very important in agricultural meteorology. Recognizing these changes can help us managing and scheduling for future. Materials and methods: General Circulation Models (GCMs) indicate that rising concentrations of greenhouse gases will have significant implications for climate at global and regional scales. Unfortunately, GCMs are restricted in their usefulness for local impact studies by. Their coarse spatial resolution (typically of the order 50,000 km2) and inability to resolve important sub–grid scale features such as clouds and topography. Statistical downscaling methodologies have several practical advantages over dynamical downscaling approaches. In situations where low–cost, rapid assessments of localized climate change impacts are required, statistical downscaling (currently) represents the more promising option. In this manual we describe a software package, and accompanying statistical downscaling methodology, that enables the construction of climate change scenarios for individual sites at daily time–scales, using grid resolution GCM output. Stochastic downscaling approaches typically involve modifying the parameters of conventional weather generators such as WGEN or LARS–WG. The WGEN model simulates precipitation occurrence using two–state, first order Markov chains: precipitation amounts on wet days using a gamma distribution; temperature and radiation components using first–order trivariate autoregression that is conditional on precipitation occurrence. Climate change scenarios are generated stochastically using revised parameter sets scaled in direct proportion to the corresponding parameter changes in a GCM. The main advantage of the technique is that it can exactly reproduce many observed climate statistics and has been widely used, particularly for agricultural impact assessment. Furthermore, stochastic weather generators enable the efficient production of large ensembles of scenarios for risk analysis. The key disadvantages relate to the arbitrary manner in which precipitation parameters are adjusted for future climate conditions, and to the unanticipated effects that these changes may have on secondary variables such as temperature. Regression Regression–based downscaling methods rely on empirical relationships between local scale predictands and regional scale predictor(s). Individual downscaling schemes differ according to the choice of mathematical transfer function, predictor variables or statistical fitting procedure. To date, linear and non–linear regression, artificial neural networks, canonical correlation and principal components analyses have all been used to derive predictor–predictand relationships. The main strength of regression downscaling is the relative ease of application, coupled with their use of observable trans–scale relationships. The main weakness of regression–based methods is that the models often explain only a fraction of the observed climate variability (especially in precipitation series). In common with weather typing methods, regression methods also assume validity of the model parameters under future climate conditions, and regression–based downscaling is highly sensitive to the choice of predictor variables and statistical transfer function (see below). Furthermore, downscaling future extreme events using regression methods is problematic since these phenomena, by definition, tend to lie at the limits or beyond the range of the calibration data set. One of the methods to study of future climate is using the general circulation models, but these models have low temporal and spatial resolution and they can’t show local changes in climate of a region. One of the methods to downscale the output of these models is using SDSM model. This research was tried using this method to study future climate of 12 synoptic stations in Iran. First we took daily minimum temperature, maximum temperature and precipitation of these stations from 1961 to 2005. These data are inputs of SDSM and the outputs of GCMs were downscaled with these observed data.  Future climate was predicted for these stations. Then the dates of early and late chilling were extracted of predicted temperature for future climate in these stations. Results and discussion: The results show that the date of late spring chilling increases and the date of first autumn chilling decreases in all station but on Rasht station the both parameters for all scenarios decrease and in Gorgan station just for a2 scenario the dates of late chilling decrease. Conclusions: This research shows that in the major of stations growing season decreases. So we recommend that farmers and gardeners change their crops or they cultivate early crops. In the rest of stations they should cultivate late crops or alternatively.  }, keywords = {Climate change,first autumn chilling,last spring chilling,Downscaling,SDSM,Iran}, title_fa = {بررسی ﺗﺄثیرات تغییر اقلیم بر شماره روز اولین یخبندان پاییزه و آخرین یخبندان بهاره در ایران با استفاده از ریز مقیاس نمایی SDSM}, abstract_fa = {تغییر تاریخ اولین یخبندان زودرس پاییزه و آخرین یخبندان دیررس بهاره که به لحاظ کشاورزی بسیار حائز اهمیت است، می تواند یکی از پیامدهای پدیده گرمایش جهانی باشد. یکی از روش های مطالعه اقلیم آینده، استفاده از خروجی مدل های گردش عمومی جو است اما این مدل ها به دلیل قدرت تفکیک زمانی و مکانی پایین، گویای تغییر اقلیم منطقه ای نمی باشند. در این تحقیق از مدل آماریSDSM برای ریز مقیاس نمایی نتایج مدل های گردش عمومی جو تحت دو سناریو انتشار A2 و B2 در چند نمونه اقلیمی استفاده شده است. نتایج این تحقیق برای چشم انداز 2039-2020 نشان می دهد که دمای کمینه در اکثر ایستگاه های انتخابی افزایش و در مابقی ایستگاه ها تفاوتی نخواهد کرد. میانگین شماره روز آخرین یخبندان بهاره هم در ایستگاه های کرمانشاه، گرگان و رشت کاهش و در ایستگاه های اصفهان و زاهدان بدون تفاوت و در مابقی ایستگاه ها افزایش می یابد. میانگین شماره روز اولین یخبندان پاییزه در ایستگاه کرمانشاه افزایش، در ایستگاه رشت بدون تفاوت و در مابقی ایستگاه های مورد مطالعه کاهش خواهد یافت. با توجه به پیش بینی افزایش طول دوره یخبندان در اکثر ایستگاه های مورد مطالعه، فراوانی وقوع یخبندان در تمام ایستگاه ها در دوره 2020 تا 2039 در مقایسه با 1961 تا 1990کاهش خواهد یافت.همچنین نتایج بیانگر کاهش فراوانی وقوع دماهای کمینه کوچکتر از دهک اول یا یخبندان شدید و افزایش وقوع دماهای کمینه بزرگتر از دهک نهم  یا یخبندان ضعیف و افزایش دمای کمینه دهک اول و دهک نهم در ایستگاه های مورد مطالعه می باشد.    }, keywords_fa = {تغییر اقلیم,اولین یخبندان پاییزه,آخرین یخبندان بهاره,ریزمقیاس نمایی,SDSM,ایران}, url = {https://clima.irimo.ir/article_14963.html}, eprint = {https://clima.irimo.ir/article_14963_31c384bcd850ca0d41f87ae66f22fc39.pdf} } @article { author = {Ghafarian, P. and Barekati, S. M.}, title = {Verification of the Weather Research and Forecasting Model (WRF) for the Heavy Precipitation Forecasting in the Karun basin. A case study ( 8-9 February 2006)}, journal = {Journal of Climate Research}, volume = {1392}, number = {15}, pages = {129-140}, year = {2013}, publisher = {https://www.irimo.ir/}, issn = {2228-5040}, eissn = {2783-395X}, doi = {}, abstract = {Introduction Accurate weather forecasting plays a key role in people daily life and agriculture. By using of numerical weather forecasting models could predict meteorological parameters, but the model outputs have errors which should be verified. Model errors are due to the random and systematic errors. The eyeball and statistical verification methods help us to evaluate model outputs accuracy. In February 2006, a heavy precipitation occurred in Karun basin that had a lot of economic damages. The purpose of this study is evaluating WRF model for forecasting Heavy Precipitation in Karun Basin. Material and Methods In this study, the precipitation data from synoptic stations and TRMM satellite is used. The boundary and initial conditions of model are FNL data. The WRF model outputs for a case of rainfall, which has been caused the flooding in the Karun region, with observation precipitation data were verified. The model has been run for 24 and 48 hours predictions with two nested of network steps of 15 and 45 km. To evaluate the accuracy of WRF numerical prediction model, the model results, were investigated with the reality of the eyeball verification and statistical points of view. Results and discussion The results of eyeball verification indicated that the precipitation pattern and its amount in the area are correctly predicted. The statistical verification results in three thresholds, the occurrence or absence of rainfall, average and heavy precipitation in the first and second 24 hours were evaluated. The results show that the model in the first and second 24 hours prediction of occurrence or absence of the rainfall is very precise and the accuracy of results is close to 100 percent. For the second threshold, the model accuracy in rainfall prediction is high but the accuracy was higher in the second 24 hours, so that in the second threshold and the second 24 hours, the number of cases correctly predicted is high. Also, in the second threshold in the first 24 hours, the model has been dry, in other words the number of days when precipitation has occurred, has been less than anticipated value. In the second 24 hours, the model has been wet, the number of days that the precipitation has not happened, but the model has predicted, is high. In the third threshold, the prediction accuracy is higher in the first 24 hours and in two cases, the model has been wet. In other words, for the third threshold, the model accuracy in predicting heavy rainfall has been in average value in the region. Finally, the results show that in the occurrence of the flood forecasting in Karun basin, the model is reliable. Conclusion In February 2006, a heavy and unprecedented precipitation occurred in Karun basin that had a lot of economic damages. In this study, the WRF model outputs for a case of rainfall, which has been caused the flooding in the Karun basin, with observation precipitation data were verified. The model has been run for 24 and 48 hours predictions with two nested of 15 and 45 km. To evaluate the accuracy of the WRF numerical prediction model, the model results, were investigated with the reality of the eyeball verification and statistical points of view.  Finally, the results show that in the occurrence of the flood forecasting in Karun basin, the model is reliable. Iran has a complex topography and accurate predicting of meteorological parameters especially precipitation and 2 meter temperature is very difficult. Although the model output is reliable, but using of the best model configuration and ensemble forecasting could improve the model outputs.    }, keywords = {Verification,Flood Forecasting,Regional WRF Model,Precipitation Thresholds,Contingency table}, title_fa = {راستی آزمایی مدل پیش‌بینی و پژوهش وضع هوا (WRF) در پیش‌بینی بارشهای سنگین در حوضه کارون (مطالعه موردی: بارش 20 تا 21 بهمن 1384)}, abstract_fa = {در این پژوهش خروجی‌های مدل WRF برای بارشی که در منطقه‌ی کارون منجر به وقوع سیل شده است،  راستی‌آزمایی شدند.  داده‌های دیدبانی شده‌ی بارش و داده‌های ماهواره TRMM  برای راستی‌آزمایی و  داده‌های FNL به عنوان خروجی مدل استفاده شده‌اند. مدل با دو آشیانه با گام‌های شبکه‌ای 45 و15 کیلومتر، برای پیش بینی 24 و 48 ساعته اجرا شده است. به منظور بررسی صحت مدل پیش بینی عددی WRF، نتایج حاصل از آن با واقعیت از دو دیدگاه راستی آزمایی چشمی و آماری بررسی شدند. نتایج راستی آزمایی چشمی مدل، نشان داد که الگوی بارش و میزان آن در منطقه به درستی پیش‌بینی شده است. نتایج راستی‌آزمایی آماری در سه آستانه، وقوع یا عدم وقوع بارش؛ بارش متوسط و بارش سنگین در 24 ساعت اول و دوم ارزیابی شد. نتایج نشان می‌دهد که مدل در 24 ساعت اول و دوم در پیش بینی وقوع یا عدم وقوع بارش بسیار دقیق عمل کرده و نتایج نزدیک 100 درصد صحیح هستند.  برای آستانه‌ی دوم، دقت مدل در پیش بینی بارش بالا است ولی در 24 ساعت دوم دقت بالاتر بوده است، به گونه‌ای که در آستانه‌ی دوم و در 24 ساعت دوم تعداد مواردی که به درستی پیش‌بینی شده، بالا بوده است. همچنین، در آستانه‌ی دوم در 24 ساعت اول، مدل خشک بوده، بعبارت دیگر تعداد روزهایی که بارش اتفاق افتاده را کمتر پیش بینی نموده است. و در 24 ساعت دوم مدل تر بوده، یعنی تعداد روزهایی که بارش اتفاق رخ نداده، اما مدل پیش‌بینی نموده، بالا بوده است. و در آستانه‌ی سوم، در پیش بینی 24 ساعت اول دقت بالاتر است و در دو حالت، مدل تر بوده است. به عبارتی دیگر، برای آستانه‌ی سوم، دقت مدل در پیش بینی بارش‌های بسیار سنگین در منطقه متوسط بوده است. در نهایت نتایج نشان می‌دهند که در وقوع پیش بینی سیل در منطقه‌ی کارون نتایج مدل قابل اعتماد است.}, keywords_fa = {راستی‌آزمایی,پیش‌بینی سیل,مدل‌ منطقه‌ای WRF,آستانه‌های بارش,جدول توافقی}, url = {https://clima.irimo.ir/article_14964.html}, eprint = {https://clima.irimo.ir/article_14964_62341aa41173ffca78bb1ee85d3d208e.pdf} }