26111

حساسيت‌‌سنجي سرعت باد حاصل از شبيه‌‌سازي‌هاي مدل WRF به پارامترهاي فيزيكي در محدوده سواحل جنوبي درياي خزر

كارشناسي ارشد

مهندسي عمران- مهندسي سواحل، بنادر و سازه‌هاي دريايي

1397

1400/8/2

سيد مصطفي سيادت موسوي

مهندسي عمران

ﺑﺎد ﻋﺎﻣﻞ ﻣﻬﻤﯽ در ﻓﺮارﻓﺖ ﮐﻤﯿﺖ‌ﻫﺎي ﻫﻮاﺷﻨﺎﺳﯽ اﺳﺖ. تخمين ﻗﺎﺑﻞ اﻋﺘﻤﺎد و ﺑﺎ ﺗﻔﮑﯿﮏ ﻣﻨﺎﺳﺐ از ﺑﺎد ﺳﻄﺤﯽ در درﯾﺎﻫﺎ در ﺑﺴﯿﺎري از ﻓﻌﺎﻟﯿﺖ‌ﻫﺎي ﻋﻠﻤﯽ و اﻗﺘﺼﺎدي ﻣﻮرد ﻧﯿﺎز اﺳﺖ. در ﭘﮋوﻫﺶ ﺣﺎﺿﺮ ﺷﺒﯿﻪ‌ﺳﺎزي و ارزﯾﺎﺑﯽ ﻣﯿﺪان‌ﻫﺎي ﺑﺎد ﺳﻄﺤﯽ ﺣﺎﺻﻞ از ﭘﯿﺶ‌ﯾﺎﺑﯽ ﻧﺴﺨﻪ 4.2 ﻣﺪل ﻣﯿﺎن‌ﻣﻘﯿﺎسWRF در ﻣﻨﻄﻘﻪ درﯾﺎي خزر اﻧﺠﺎم ﺷﺪه اﺳﺖ. ﺗﻤﺎﻣﯽ ﺷﺒﯿﻪ‌ﺳﺎزي‌ﻫﺎ ﺑﺮاي 9 ﭘﯿﮑﺮﺑﻨﺪي ﻣﺘﻔﺎوت از دﯾﺪﮔﺎه ﭘﺎراﻣﺘﺮﺳﺎزي ﻓﯿﺰﯾﮑﯽ اﻧﺠﺎم ﺷﺪ. ارزﯾﺎﺑﯽ ﻧﺘﺎﯾﺞ ﺷﺒﯿﻪ‌ﺳﺎزي ﺑﺎ اﺳﺘﻔﺎده از داده‌ﻫﺎي اﯾﺴﺘﮕﺎه‌ﻫﺎي ﻫﻤﺪﯾﺪي در دﺳﺘﺮس و ﻫﻢ‌ﭼﻨﯿﻦ داده‌ﻫﺎي يك بويه در آب‌هاي عميق درياي خزر در دو بازه 10 روزه به نمايندگي از دو فصل زمستان و تابستان و براي شرايط تندباد و طوفان اﻧﺠﺎم ﺷﺪه اﺳﺖ. ﺑﺮاي ﺑﺮرﺳﯽ ﻋﻤﻠﮑﺮد ﻣﺪل ﻋﺪدي از ﺳﻨﺠﻪ‌ﻫﺎي آﻣﺎري ﻣﺜﻞ شاخص توافق ويلموت، رﯾﺸﻪ ﻣﯿﺎﻧﮕﯿﻦ ﻣﺮﺑﻌﺎت ﺧﻄﺎﻫﺎ و خطاي اريبي اﺳﺘﻔﺎده ﺷﺪ. ﻧﺘﺎﯾﺞ ﻧﺸﺎن ﻣﯽ‌دﻫﻨﺪ ﮐﻪ در ﺑﺨﺶ ارزﯾﺎﺑﯽ ﺑﺎ داده‌ﻫﺎي بويه، ﻧﺘﺎﯾﺞ ﻋﻤﻠﮑﺮد ﻣﺪل، ﻗﺎﺑﻞ ﻗﺒﻮل و ﻣﻨﺎﺳﺐ ﺑﻮده اﺳﺖ. ﺷﺒﯿﻪ‌ﺳﺎزي‌ﻫﺎ ﺑﺮاي ﻣﻨﺎﻃﻖ دور از ﺳﺎﺣﻞ ﮐﻪ ﺑﻪ ﮐﻤﮏ داده‌ﻫﺎي اندازهگيري بويه ارزﯾﺎﺑﯽ ﺷﺪه‌اﻧﺪ، ﻧﺴﺒﺖ ﺑﻪ داده‌ﻫﺎي ﻫﻤﺪﯾﺪي ﺑﻪ ﻣﻘﺎدﯾﺮ ﻣﺸﺎﻫﺪات ﻧﺰدﯾﮑﺘﺮ هستند. ﻧﺘﺎﯾﺞ ﻋﻤﻠﮑﺮد ﻣﺪل در نزديكي ﻧﻮار ﺳﺎﺣﻠﯽ نيز از ﮐﯿﻔﯿﺖ ﻗﺎﺑﻞ ﻗﺒﻮﻟﯽ ﺑﺮﺧﻮردار است اﻣﺎ ﮐﯿﻔﯿﺖ ﮐﻤﺘﺮي ﻧﺴﺒﺖ ﺑﻪ ﻧﺘﺎﯾﺞ در آب‌ﻫﺎي آزاد و ﻣﻨﺎﻃﻖ دور از ﺳﺎﺣﻞ دارﻧﺪ. ﻣﯿﺰان ﺗﻔﮑﯿﮏ اﻓﻘﯽ ﻧﯿﺰ ﻣﯽ‌ﺗﻮاﻧﺪ در ﺑه دﺳﺖ آﻣﺪن اﯾﻦ ﻧﺘﺎﯾﺞ ﻣﻮﺛﺮ ﺑﺎﺷﺪ و انتظار ﻣﯽ‌رود ﺑﺎ افزايش ﺗﻔﮑﯿﮏ اﻓﻘﯽ، ﻧﺘﺎﯾﺞ ﺑﺮاي ﻣﻨﺎﻃﻖ ﻧﺰدﯾﮏ ﺳﺎﺣﻞ ﻧﯿﺰ ﺑﻬﺒﻮد ﭘﯿﺪا ﮐﻨﺪ. ﻧﺘﺎﯾﺞ طرحواره فيزيكي شماره 5 كه طرحوارهاي مبتني بر فيزيك لايه مرزي سيارهاي و فيزيك لايه سطحي با رويكرد محلي و غيرمحلي Mellor-Yamada Nakanishi Niino (MYNN) و همچنين مدل سطح زمين Noah-mp است، در اﻏﻠﺐ بازههاي زماني و ﺧﺼﻮﺻﺎ ﺑﺮاي زمستان از باقي طرحوارهها بهتر بودهاست. ﻧﺘﺎﯾﺞ ﻋﻤﻮﻣﺎ براي فصل زمستان همبستگي بيشتري در پارامترهاي سرعت و جهت باد اندازهگيري شده نسبت به فصل تابستان دارد كه احتمالا ناشي از دقت بيشتر دادههاي ورودي مدل در فصل زمستان نسبت به فصل تابستان باشد. دادههاي ورودي مدل از خروجي مدل جهاني ECMWF گرفته شده، و تفاوت ميزان خطا در اين دو فصل مربوط به دقت دادههاي شرايط اوليه ورودي به مدل است كه طبيعتا خطاي دادههاي ورودي، در خروجي مدل محلي هم با وجود بهبود نسبي نتايج بر اساس اعمال تاثيرگذاري پارامترهاي محلي، خود را نشان داده است.

1400/12/09

Sensitivity of wind speed from WRF model simulations to physical parameters in the southern coast of the Caspian Sea

10/24/2022 12:00:00 AM

Weather is an important factor in quantities of wind advection. Reliable estimates and appropriate resolution of surface wind on the sea in many scientific and economic activities is required. In this study, simulation and evaluation of surface wind fields prediction of 4.2 WRF in the Caspian Sea region is done. All simulations were performed for 9 configured differently in terms of physical parameterization. Evaluation of simulation results using data from synoptic stations available as well as data from a buoy in deep waters of the Caspian Sea in two periods of 10 days on behalf of both winter and summer in a gust of wind and the storm is done. To evaluate the performance of numerical models of statistical measures such as Willmott agreement index, root mean square error and bias error was used. The results show that the assessment buoy data model performance results have been good and acceptable. Simulations for offshore areas that have been evaluated using measurement data buoy observations are closer to the values of the synoptic data. The results of performance of the model near the coastal strip also is of acceptable quality but lower quality results in open waters and offshore areas are. The horizontal resolution can also be effective in achieving the results. It's expected by increasing the horizontal resolution, the results also improved to areas near the coast. Results of Physical ensemble (5), which is based on the physics of planetary boundary layer physics and surface layer physics with the local approach and nonlocal - sample physics ( MYNN ) as well as the Noah - mp surface model , has been better than the other ensembles in most of the time periods , especially for the winter .Results for winter generally have greater solidarity in measured wind speed and direction parameters over the summer, likely due to more accurately input data model Weather is an important factor in quantities of wind advection. Reliable estimates and appropriate resolution of surface wind on the sea in many scientific and economic activities is required. In this study, simulation and evaluation of surface wind fields prediction of 4.2 WRF in the Caspian Sea region is done. All simulations were performed for 9 configured differently in terms of physical parameterization. Evaluation of simulation results using data from synoptic stations available as well as data from a buoy in deep waters of the Caspian Sea in two periods of 10 days on behalf of both winter and summer in a gust of wind and the storm is done. To evaluate the performance of numerical models of statistical measures such as Willmott agreement index, root mean square error and bias error was used. The results show that the assessment buoy data model performance results have been good and acceptable. Simulations for offshore areas that have been evaluated using measurement data buoy observations are closer to the values of the synoptic data. The results of performance of the model near the coastal strip also is of acceptable quality but lower quality results in open waters and offshore areas are. The horizontal resolution can also be effective in achieving the results. It's expected by increasing the horizontal resolution, the results also improved to areas near the coast. Results of Physical ensemble (5), which is based on the physics of planetary boundary layer physics and surface layer physics with the local approach and nonlocal - sample physics ( MYNN ) as well as the Noah - mp surface model , has been better than the other ensembles in most of the time periods , especially for the winter .Results for winter generally have greater solidarity in measured wind speed and direction parameters over the summer, likely due to more accurately input data model is in winter than in summer. The model input data is taken from the output of the global ECMWF model and the difference in the error rate in these two seasons is related to the accuracy of the initial input condition data to the model. The results are based on the influence of local parameters. is in winter than in summer. The model input data is taken from the output of the global ECMWF model and the difference in the error rate in these two seasons is related to the accuracy of the initial input condition data to the model. The results are based on the influence of local parameters.

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