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ارزیابی دقت پایگاه داده ECMWF در پیشبینی دادههای اقلیمی و پایش خشکسالی حوزه آبریز قره چای استان مرکزی | ||
| تحقیقات آب و خاک ایران | ||
| دوره 53، شماره 4، تیر 1401، صفحه 715-732 اصل مقاله (2.7 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2022.340295.669227 | ||
| نویسندگان | ||
| زهرا سادات حسینی1؛ مه نوش مقدسی* 2؛ شهلا پایمزد3 | ||
| 1گروه علوم و مهندسی آب- دانشکده کشاورزی و محیط زیست- دانشگاه اراک-اراک- ایران | ||
| 2گروه علوم ومهندسی آب- دانشکده کشاورزی و محیط زیست- دانشگاه اراک- اراک-ایران | ||
| 3گروه علوم و مهندسی آب- دانشکده کشاورزی و محیط زیست-دانشگاه اراک- اراک-ایران | ||
| چکیده | ||
| در دهههای اخیر توسعه روزافزون تکنولوژیهای ماهوارهای، امکان دسترسی به دادههای اقلیمی در کل جهان با توان تفکیک مکانی و زمانی متفاوتی را فراهم نموده است. لذا در تحقیق حاضر، هدف ارزیابی مدلهای پایگاه ECMWF در پیشبینی دادههای اقلیمی و پایش خشکسالی در حوزه آبریز قرهچای استان مرکزی میباشد. بدین منظور ابتدا داده های بارش و دمای ماهانه ایستگاههای سینوپتیک همدان ، قم و شازند در سطح سه استان طی دوره آماری 2018-1987 جمع آوری گردید. سپس از دو مدل باز تحلیل شدهERA-Interim و ERA5 پایگاه ECMWF دادههای دما و بارش با قدرت تفکیک مکانی 125/0 × 125/0 درجه طی دوره 1979-2020 استخراج شده است. از آمارههایی مانند ضریب تعیین (2R)، ضریب نش-ساتکلیف (NS)، مجذور میانگین مربع خطا استاندارد شده (NRMSE) و میانگین خطای اریبی(MBE) و شاخصهای جدول توافقی که متشکل از POD ،FAR وCSI میباشد، برای مقایسه دادههای مدلها با دادههای مشاهداتی استفاده شده است. نتایج نشان داد که دادههای ERA5 نسبت به دادههای ERA-Interim همخوانی بهتری با دادههای مشاهداتی دارد. بطوریکه مقادیر ضریب همبستگی در اکثر مناطق بالای 5/0، خطا در 70 درصد مناطق بسیارکم و خطای اریبی نیز در بیشتر مناطق مقدار مثبت و کمی است. مقادیر شاخصهای جدول توافقی نیز همخوانی بیشتر مدل ERA5 را تائید مینماید. سپس بر اساس دادههای مدل منتخب و مشاهداتی شاخصهای خشکسالی SPEI و SPI در ایستگاههای منتخب محاسبه گردید. نتایج نشان داد که شاخص SPEI نسبت به SPI با دادههای مشاهداتی همبستگی بالاتر و خطای کمتری دارد. در نهایت بررسی روند بر اساس شاخص منتخب نشان داد که شدت خشکسالی در منطقه غرب نسبت به بقیه مناطق، دارای روند افزایشی در سطح 5 درصد میباشد. | ||
| کلیدواژه‌ها | ||
| داده های اقلیمی؛ شاخص بارندگی استاندارد شده؛ شاخص بارندگی و تبخیر و تعرق استاندارد شده؛ ERA5؛ ERA Interim | ||
| عنوان مقاله [English] | ||
| Accuracy Assessment of ECMWF Datasets in Prediction of Climate Data and Drought Monitoring of Garechai Basin of Markazi Province | ||
| نویسندگان [English] | ||
| Zahra Sadat Hoseeni1؛ mahnoosh Moghaddasi2؛ Shahla Paimozd3 | ||
| 1Department of Water Science and Engineering, Faculty of Agriculture and Environment, -Arak University-Arak, -Iran | ||
| 2Department of Water Science and Engineering, -Faculty of Agriculture and Environment, -Arak University,- Arak,-Iran | ||
| 3Department of Water Science and Engineering,- Faculty of Agriculture and Environment-, Arak University,- Arak,-Iran | ||
| چکیده [English] | ||
| In recent decades, the increasing development of satellite technologies has provided access to climate data around the world with different spatial and temporal resolution. Therefore, in the present study, the goal of evaluating ECMWF datasets models is to predict climate data and drought monitoring in Qarechai basin of Markazi province. To this end, first monthly precipitation and temperature data of synoptic stations of Hamedan, Qom and Shazand in three provinces during the period of 1987-2018 were collected. Then, the mentioned data with spatial resolution of 0.125 * 0.125 degrees during 1979-2020 were extracted from the reanalysis models including ERA-Interim and ERA5 of ECMWF datasets. Statistics criteria's such as coefficient of determination (R2), nash-sutcliffe (NS), normalized square root mean square error (NRMSE) and mean oblique error (MBE) and contingency table indices consisting of POD, FAR and CSI were used to compare the data of reanalysis models with observational data. The results showed that ERA5 data were more consistent with observational data than ERA-Interim data. As the values of correlation coefficient in most areas above 0.5, mean square error in 70% of areas is very low and mean oblique error in most areas is positive and small. The values of the agreement table indices also confirm the greater compatibility of the ERA5 model. Afterward, based on data of the selected model and observational, SPEI and SPI drought indices in selected stations were calculated. The results showed that SPEI index had higher correlation and less error with SPI than SPI. Finally, the trend based on the selected index showed that the severity of drought in the western region compared to other regions, has an increasing trend at the level of 5%. | ||
| کلیدواژه‌ها [English] | ||
| Climate data, ERA5, ERA Interim, SPI, SPEI | ||
| مراجع | ||
|
AghaKouchak, A., Nasrollahi, N., & Habib, E. (2009). Accounting for uncertainties of the TRMM satellite estimates. Remote Sensing, 1(3), 606-619 Amjad, M., Yilmaz, M. T., Yucel, I., & Yilmaz, K. K. (2020). Performance evaluation of satellite-and model-based precipitation products over varying climate and complex topography. Journal of Hydrology, 584, 124707. Arabi Yazdi, A., Sanaei Nejad, S. H., & Mofidi, A. (2020). Evaluation of Grid reanalysis products of the European Centre for Medium Range Weather Forecasts (ECMWF datasets) in Different Climatic Regions of Iran. Journal of Climate Research, 1398(38), 63-76. (In Farsi) Azizi Mobaser, J., Rasoulzadeh, A., Rahmati, A., Shayeghi, A., & Bakhtar, A. (2021). Evaluating the Performance of Era-5 Re-Analysis Data in Estimating Daily and Monthly Precipitation, Case Study; Ardabil Province. Iranian. Journal of Soil and Water Research, 51(11), 2937-2951. (In Farsi) Benoit, A., Jolivet, R., & Pinel-Puysségur, B. (2019). Correction of tropospheric effects in SAR interferometry: a comparison of ERA-Interim, ERA-5 and HRES Global Atmospheric Models. Bosilovich, M.G., Chen, Robertson, J. F., & Adler, R.F. (2008). Evaluation of global precipitation in reanalysis. Journal of Applied Meteorology and Climatology, 47 (9), 2279-2299. Darand, M., & Zande Karimi, S. (2015). Evaluation of Spatio-Temporal Accuracy of Precipitation of European Center for Medium-Range Weather Forecasts (ECMWF) over Iran. Physical Geography Research Quarterly, 47(4), 651-675. (In Farsi) Dehban, H., Ebrahimi, K., Araghinejad, S., Bazrafshan, J., & Modaresi, F. (2020). Monthly Stream-flow forecasting using the ECMWF model, case study: Sefidrud Basin-Iran. Iran-Water Resources Research, 16(3), 272-281. (In Farsi) Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S. & Vitart, F. (2011). The ERA‐Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), 553-597. Donaldson, R., Dyer, R. & Krauss, M. (1975). Objective evaluator of techniques for predicting severe weather events. In Bulletin of the American Meteorological, 56, 755-755. Erfani, A., Babaeian, I., & Entezari, A. (2020). ERA-Interim. Journal of Climate Research, 1398(38), 77-92. Farzaneh, S., Sharifi, M. A., & Akbarzadeh, A. (2020). Investigation of short-term atmospheric mass variations and their effects on geoid height using meteorological data. Journal of the Earth and Space Physics, 46(3), 497-515. Hargreaves, G. H., & Samani, Z. A. (1985). Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture, 1(2), 96-99. Hayes, M. (2000). Drought indices. National Drought Mitigation Center, University of Nebraska. Hénin, R., Liberato, M. L., Ramos, A. M., & Gouveia, C. M. (2018). Assessing the use of satellite-based estimates and high-resolution precipitation datasets for the study of extreme precipitation events over the Iberian Peninsula. Water, 10(11), 1688. Hersbach, H., de Rosnay, P., Bell, B., Schepers, D., Simmons, A., Soci, C. & Zuo, H. (2018). Operational global reanalysis: progress, future directions and synergies with NWP, ERA Report Series 27, 63 pp. Hughes, D., Rodriguez, J., Smith, E. P., Johnson, D. J., Stevenson, H. C., & Spicer, P. (2006). Parents' ethnic-racial socialization practices: a review of research and directions for future study. Developmental Psychology, 42(5), 747. Hu, Z., & Mallorquí, J. J. (2019). An accurate method to correct atmospheric phase delay for instar with the era5 global atmospheric model. Remote Sensing, 11(17), 1969. Jiang, C., Xu, T., Wang, S., Nie, W., & Sun, Z. (2020). Evaluation of zenith tropospheric delay derived from ERA5 data over China using GNSS observations. Remote Sensing, 12(4), 663. Kendall, M. G. (1975). Rank Correlation Methods. New York, NY: Oxford University Press. Khosravi Dehkordi, A., Mirabbasi, R., Samadi Boroujeni, H., & Ghasemi Dastgerdi, A. R. (2019). Monitoring and forecasting of groundwater drought in Shahrekord plain using Groundwater Resource Index (GRI) and Markov chain model. Hydrogeology, 4(1), 111-125. (In Farsi) Lucatero, D., Madsen, H., Refsgaard, J. C., Kidmose, J., & Jensen, K. H. (2018). Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistency. Hydrology and Earth System Sciences, 22(7), 3601-3617. Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13, 245–259. McKee, T.B., Doesken, N.J. & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, 17:179-183. Mishra, A. K., Singh, V. P., & Jain, S. K. (2010). Impact of global warming and climate change on social development. Journal of Comparative Social Welfare, 26(2-3), 239-260. Moghbel, M. (2021). Evaluation of Accuracy of ECMWF Re-Analysis Data in Estimation of Soil Depths Temperature Changes (Case Study of Tehran). Journal of Range and Watershed Management, 74(2), 453-468. (In Farsi) Navidi, N. B., Zohrabi, N., Nikbakht, S. A., & Fathian, H. (2021). Evaluation of Global Gridded Precipitation Datasets for Drought Monitoring (Case Study: Great Karoon Watershed). Journal of Water and Soil Resources Conservation, 10(3), 79-96.( In Farsi) Pachauri, R. K., Allen, M. R., Barros, V. R., Broome, J., Cramer, W., Christ, R., & van Ypserle, J. P. (2014). Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change (p. 151). Pilpayeh, A., Najafian Ghojehbiglou, D., Saadi, T., & Rahmati, A. (2020). Analysis of drought situation in Iran using ECMWF precipitation product. Journal of Spatial Analysis Environmental Hazards, 7(3), 0-0.) In Farsi) Raziei, T., & Sotoudeh, F. (2017). Investigation of the accuracy of the European Center for Medium Range Weather Forecast (ECMWF) in forecasting observed precipitation in different climates of Iran. Journal of the Earth and Space Physics, 43(1), 133-147. (In Farsi) Schmidhuber, J., & Tubiello, F. N. (2007). Global food security under climate change. Proceedings of the National Academy of Sciences of the United States of America, 104(50), 19703-19708. Stanski H. R., Wilson, L. J.& Burrows, W. R. (1989). Survey of common verification methods in meteorology. World Meteorological Organization Geneva. Sue, D. W., Nadal, K. L., Capodilupo, C. M., Lin, A. I., Torino, G. C., & Rivera, D. P. (2008). Racial microaggressions against Black Americans: Implications for counseling. Journal of Counseling & Development, 86(3), 330-338. Tang, Y., Zhong, S., Luo, L., Bian, X., Heilman, W. E., & Winkler, J. (2015). The potential impact of regional climate change on fire weather in the United States. Annals of the Association of American Geographers, 105(1), 1-21. Van Hateren T C, Sutanto S J, Van Lanen H A (2019). Evaluating skill and robustness of seasonal meteorological and hydrological drought forecasts at the catchment Scale-Case Catalonia (Spain). Environment International, 133:105206 Wang Q J, Shao Y, Song Y, Schepen A, Robertson D E, Ryu D, & Pappenberger, F. (2019). An evaluation of ECMWF SEAS5 seasonal climate forecasts for Australia using a new forecast calibration algorithm. Environmental Modelling and Software, 122:104550 Worqlul, A. W., Jeong, J., Dile, Y. T., Osorio, J., Schmitter, P., Gerik, T., ... & Clark, N. (2017). Assessing potential land suitable for surface irrigation using groundwater in Ethiopia. Applied Geography, 85, 1-13 Woznicki, SA. Nejadhashemi, AP. Tang, Y. & Wang, L. (2016). Large-scale climate change vulnerability assessment of stream health. Ecological Indicators, 69,578–594. Xu, X., Frey, S. K., Boluwade, A., Erler, A. R., Khader, O., Lapen, D. R., & Sudicky, E. (2019). Evaluation of variability among different precipitation products in the Northern Great Plains. Journal of Hydrology: Regional Studies, 24, 100608. | ||
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