سامانه مدیریت نشریات علمی دانشگاه شهید بهشتی

برخورداری, زهرا, شمس الدینی, علی. (1404). ارزیابی زمانی‌ـ مکانی بارش ماهیانه مبتنی‌بر داده‌های CHIRPS، TRMM و MERRA در ایران. , 17(2), 55-78. doi: 10.48308/gisj.2024.234268.1194
زهرا برخورداری; علی شمس الدینی. "ارزیابی زمانی‌ـ مکانی بارش ماهیانه مبتنی‌بر داده‌های CHIRPS، TRMM و MERRA در ایران". , 17, 2, 1404, 55-78. doi: 10.48308/gisj.2024.234268.1194
برخورداری, زهرا, شمس الدینی, علی. (1404). 'ارزیابی زمانی‌ـ مکانی بارش ماهیانه مبتنی‌بر داده‌های CHIRPS، TRMM و MERRA در ایران', , 17(2), pp. 55-78. doi: 10.48308/gisj.2024.234268.1194
برخورداری, زهرا, شمس الدینی, علی. ارزیابی زمانی‌ـ مکانی بارش ماهیانه مبتنی‌بر داده‌های CHIRPS، TRMM و MERRA در ایران. , 1404; 17(2): 55-78. doi: 10.48308/gisj.2024.234268.1194

ارزیابی زمانی‌ـ مکانی بارش ماهیانه مبتنی‌بر داده‌های CHIRPS، TRMM و MERRA در ایران

نشریه سنجش از دور و GIS ایران
مقاله 4، دوره 17، شماره 2 - شماره پیاپی 66، 1404، صفحه 55-78    اصل مقاله (2.93 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.48308/gisj.2024.234268.1194
نویسندگان
زهرا برخورداری؛ علی شمس الدینی*
گروه سنجش از دور و سیستم اطلاعات جغرافیایی، دانشکدۀ علوم انسانی، دانشگاه تربیت مدرس، تهران، ایران
چکیده
سابقه و هدف: بارش، به‌منزلۀ یکی از اصلی‏ترین مؤلفه‌های بیلان آب، نقش مهمی در توزیع مکانی و زمانی آب در دسترس دارد و مهم‌ترین عاملی است که در چرخۀ هیدرولوژی، دخالت مستقیم دارد. به‌دلیل فقدان داده‏های بارش به‌روز و طولانی‌مدت با صحت مناسب و تغییر‌پذیری زیاد این کمّیت در مکان و زمان، پایش آن در وسعت‏های زیاد، بسیار دشوار است. همچنین هزینه‏بر بودن ایجاد ایستگاه اندازه‏گیری بارش، کمبود ایستگاه، مستقر نبودن دستگاه‏های ثبت‏کننده در مناطق صعب‏العبور، برداشت‏های نقطه‏ای و تعمیم‌پذیر نبودن اندازه‏گیری‏ها در نواحی وسیع و نیز نبودِ توانایی مطلوب در ثبت بارندگی‏های رگباری و سنگین همرفتی، همواره پژوهشگران حوزه‏های جوّی و هیدرولوژی را در اندازه‏گیری بارش، با چالش مواجه کرده است؛ ازاین‏رو استفاده از محصولات ماهواره‏ای جایگزین مناسبی برای دستیابی به داده‏های بارش، به‌ویژه در مناطق فاقد آمار و مناطق با تراکم ایستگاه‌های زمینی پایین است. اما محصولات ماهواره‏ای نیز خطاهای متعددی دارند؛ به همین دلیل، ارزیابی و بررسی دقت این محصولات قبل‌از استفاده، ضروری است. بنابراین، در تحقیق حاضر، محصولات بارش سه ماهوارۀ CHIRPS، MERRA و TRMM در مقیاس ماهیانه، در سطح کشور ایران، ارزیابی شده است.
مواد و روش‌ها: در این مطالعه، داده‏های 222 ایستگاه سینوپتیک کشور ایران، از ژانویۀ 2005 تا دسامبر 2019، در مقیاس زمانی ماهیانه از سازمان هواشناسی کل کشور دریافت شد. محصولات بارش ماهواره‏هایCHIRPS ، TRMM و MERRA نیز از سایت ناسا دانلود و پس‌از همسان‌سازی فرمت داده‏ها، به داده‏های عددی هم‏واحد تبدیل شدند. دراِدامه، داده‏های ماهواره‏ای و داده‏های ایستگاه‌های سینوپتیک زمینی به‌صورت یکپارچه درکنار هم قرار گرفتند و درنَهایت، داده‏های تخمینی و مشاهده‏ای اعتبارسنجی شدند تا میزان خطای پیش‌بینی ماهواره‏ها، با استفاده از شاخص‏های آماری شامل Bias، MAE، RMSE، R و R^2 به دست آید و موفقیت سنجنده‏ها، با استفاده از شاخص‏های مطابقت شامل POD، FAR و CSI، صحت‏سنجی و بررسی شود.
نتایج و بحث: با توجه به نتایج، TRMM با 84/23 = RMSE و 69/0 = R^2، درمقایسه با ماهواره‏های دیگر، عملکرد خوبی داشته است. سایر شاخص‏ها نیز حاکی از برتری این ماهواره بر دیگر ماهواره‏هاست. ماهوارۀ MERRA، با 57/30 = RMSE و 56/0 =R^2، درمقایسه با TRMM عملکردی ضعیف و درقیاس با CHIRPS عملکردی بهتر داشته است و از این لحاظ، در رتبۀ دوم قرار دارد. ماهوارۀ CHRIPS نیز تقریباً در همۀ شاخص‏ها عملکردی ضعیف‌تر از دو ماهوارۀ دیگر نشان داده است. با توجه به این اطلاعات و مقدار Bias حاصل‌شده، هر سه ماهواره بارندگی را کمتر از مقدار واقعی برآورد کرده‏اند اما ماهوارۀ TRMM، درمقایسه با دو ماهوارۀ دیگر، کم‏برآوردتر بوده و در این شاخص نیز، برتر از دو ماهوارۀ دیگر عمل کرده است.
نتیجه‌گیری: صحت‌سنجی تک‌تک ایستگاه‌ها نشان داد که داده‏های هر سه ماهواره، طبق شاخص POD، دامنۀ تغییرات اندک و نزدیک به صفر دارند و طبق شاخص‏های FAR و CSI، این اختلاف حدود 5/0 است؛ بیشترین آن به محصولات ماهوارۀ MERRA، با دامنۀ تغییرات 148/0، تعلق دارد که نشان می‏دهد طبق این شاخص‏ها، می‌توان به داده‏های این ماهواره‏ها تاحد بسیاری اعتماد داشت. نتایج FAR و CSI بیان می‌کند که هرچند محصولات MERRA در تمامی ایستگاه‌ها، با اختلاف بسیار جزئی، کمترین میزان خطا و اشتباه را در تشخیص روزهای غیربارانی و بارانی داشته‌اند، براساس نتایج این تحقیق می‏توان گفت که درمجموع، محصولات ماهوارۀ TRMM دارای صحت مناسب، تشخیص و مطابقت مطلوب در تمامی ارزیابی‌هاست.
 
کلیدواژه‌ها
تخمین بارش؛ اعتبار سنجی؛ صحت سنجی؛ محصولات ماهواره ای بارش؛ CHIRPS
عنوان مقاله [English]
Temporal-Spatial Assessment of Monthly Precipitation Based on CHIRPS, TRMM and MERRA Data in Iran
نویسندگان [English]
Zahra Barkhordari؛ Ali Shamsoddini
Dep. of Remote Sensing and GIS, Humanities Faculty, Tarbiat Modarres University, Tehran, Iran
چکیده [English]
Introduction: Precipitation, as one of the main components of the water balance, plays an important role in the spatial and temporal distribution of available water and is the most important factor that directly interferes with the hydrological cycle. Due to the lack of up-to-date and long-term precipitation data with appropriate accuracy and the high spatially and temporally variability of this quantity, it is very difficult to monitor it over large areas; also, the cost of establishing a precipitation measuring station, the shortage of stations, the lack of installation of recording devices in undulating areas, point-based measurements and the inability to generalize measurements over large areas, as well as the lack of the desired ability to record torrential and heavy convective rainfall, have always faced researchers in the fields of atmospheric and hydrology with challenges in measuring precipitation; therefore, the use of satellite products is a suitable alternative to obtain precipitation data, especially in areas without statistics and areas with a low density of ground stations. However, satellite products also have numerous errors; For this reason, it is essential to evaluate and verify the accuracy of these products before use. Therefore, in the present study, the precipitation products of the three satellites including CHIRPS, MERRA, and TRMM were evaluated on a monthly scale in the country of Iran.
Materials and Methods: In this study, data from 222 synoptic stations in Iran were received from the National Meteorological Organization on a monthly time scale from January 2005 to December 2019, and precipitation products from CHIRPS, TRMM, and MERRA satellites were downloaded from the NASA website and converted into uniform numerical data after data format was standardized; then, satellite data and data from ground-based synoptic stations were integrated together, and finally, the estimated and observed data were validated to obtain the satellite forecast error rate using statistical indices including Bias, MAE, RMSE, R, and R2, and the accuracy and success rate of the sensors were verified using conformity indices including POD, FAR, and CSI.
Results and Discussion: According to the results, TRMM has shown good performance compared to other satellites with RMSE = 23.84 and R2 = 0.69. Other indicators also indicate the superiority of this satellite compared to other satellites. MERRA satellite with RMSE = 30.57 and R2 = 0.56 has shown poor performance compared to TRMM and stronger performance compared to CHIRPS and is in second place in this respect. CHRIPS satellite also shows poorer performance compared to the other two satellites in almost all indicators. According to this table and the resulting Bias value, all three satellites have underestimated the rainfall compared to the actual value; however, TRMM satellite has less underestimation compared to the other two satellites and has performed better than the other two satellites in this indicator.
Conclusion: The accuracy of each station showed that the data of all three satellites, according to the POD index, have a low and close to zero variation range, and according to the FAR and CSI indices, this difference is around 0.5; so that the largest of them is related to the MERRA satellite products with a variation range of 0.148, which shows that according to these indices, the data of these satellites have a high reliability. Based on the FAR and CSI results, it can be seen that, although, in all stations, the MERRA products had the lowest error and mistake rate in detecting non-rainy days and rainy days with a very slight difference, but, based on the results of this study, it can be said that overall, the TRMM satellite products have appropriate accuracy, detection, and desirable consistency in all assessments.
کلیدواژه‌ها [English]
Precipitation estimation, Validation, Satellite precipitation products, CHIRPS
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