بررسی اعتبار و امکان استفاده از داده‌های شبکه‌بندی‌شده agmerra برای مطالعات اقلیمی-کشاورزی در استان خراسان شمالی

بررسی تاثیر تغییر اقلیم بر تولیدات کشاورزی در بعد زمانی مکانی، مطالعات هواشناسی کشاورزی، شبیه‌سازی عملکرد گیاهان زراعی و تولید سناریوهای اقلیمی، نیازمند مجموعه داده‌های هواشناسی دقیق و استاندارد است. این در حالی است که داده‌های مشاهداتی تاریخی در بسیاری از مناطق در دسترس نبوده و یا ناقص است؛ بنابراین، داده‌های شبکه‌بندی شده یا داده‌های آب و هوایی تولید شده به‌عنوان جایگزینی در این مناطق مورد استفاده قرار می‌گیرند. در پژوهش حاضر، امکان استفاده از مجموعه داده‌های agmerra برای پر کردن خلاء داده‌های تاریخی ناقص و گمشده در هفت ایستگاه هواشناسی سینوپتیک در استان خراسان شمالی در بازه زمانی 20101980 مورد بررسی قرار گرفت. نتایج واسنجی با استفاده از شاخص‌های ارزیابی کارایی مدل نظیر ضریب تبیین (r2)، شاخص توافق (d)، جذر میانگین مربعات خطا (rmse)، جذر میانگین مربعات خطای نرمال شده (nrmse)، میانگین خطای اریبی (mbe) نشان داد که در تمامی مناطق مورد مطالعه، داده‌های شبکه‌بندی شده agmerra برای تشعشع خورشیدی، دمای حداقل، دمای حداکثر، به استثنای بارندگی روزانه و رطوبت نسبی در دمای حداکثر، تطابق (0.92> d و 30%< nrmse)و همبستگی خوبی (0.96 ≥ r ≥ 0.81) با داده‌های ایستگاهی در مناطق خشک، نیمه‌خشک، معتدل و سرد و کوهستانی استان خراسان شمالی دارد. اگرچه زمانی که داده‌های روزانه بارندگی به‌صورت داده‌های ماهانه تجمیع شدند، همبستگی بهتری حاصل شد. به‌طور کلی نتایج حاصل از این پژوهش نشان داد که می‌توان از سری داده‌های agmerra برای مطالعات اقلیمی، تجزیه و تحلیل، برنامه‌ریزی و مدیریت بخش کشاورزی در حوزه استان خراسان شمالی استفاده نمود.

Investigation of Validity and Possibility of using AgMERRA Networked Dataset in North Khorasan Province

Introduction Investigating the effect of climate change on agricultural production in spatiotemporal dimension, development and use of crop management decisionsupport tools, supporting and target agronomic research and policy require a series of accurate and standard meteorological data. The weather station databases are often regional in coverage, and it can have extensive gaps in station coverage over time. It may also contain errors in climate records, station coordinates or elevation. While historical observational data are incomplete or not available in many areas; therefore, gridded weather data are used as an alternative in these areas. An issue is the agreement of gridded with measured weather data and the degree to which this agreement may influence the utility of gridded for agricultural research.  In this study, the possibility of using AgMERRA data series to fill the gap of incomplete and missing historical data in seven synoptic meteorological stations in North Khorasan province in the period (19802010) was investigated. Materials and Methods Historical daily measured weather data (maximum and minimum air temperature, sunshine hours, relative humidity, and precipitation) for the 1980 to 2010 period, were obtained from the 7 synoptic weather stations (Bojnord, Shirvan, Farooj, Esfarayen, ManeSemelghan, RazJargalan, Jajarm) across Northern Khorasan.  The robustness of AgMERRA dataset was investigated through statistical validation indices including RMSE (Root Mean Square Error), R2 (Coefficient of Determination), d (d Index of Agreement), NRMSE (Normalized Root Mean Square Error) and MBE (Mean Bias Error).  Result and Discussion Strong positive correlations were observed between simulated values ​​of maximum and minimum temperature with observational values (0.81 ≤ r ≤ 0.96). The NRMSE was excellent and good for all stations (7.76 ≤ NRMSE ≤ 15.81). Overall, the high agreement index (d ≥ 0.92), as well as the small values ​​of the MBE, indicated good agreement between the observed and predicted data for the maximum and minimum temperature variable. The solar radiation simulations correlated well with the observed values (0.86 ≤  r ≤ 0.93). The high values for agreement index were obtained in four stations (0.96 ≤ d ≤ 0.98). But the NRMSE for Bojnourd, Esfarayen, and Jajarm stations was ranked in moderate class (20 < NRMSE < 30), and weak class for Mane Semelghan station (NRMSE = 32.31). Other stations (Shirvan, Farooj, and RazJargalan) did not have station observation values for the radiation variable. AgMERRA had a relatively high ability to simulate the relative humidity variable at maximum temperature for Shirvan, Farooj, Esfarayen, and Jajarm stations. The agreement index for these stations was between 0.92 and 0.94, also those NRMSE was ranked in the good class. The coefficient of correlation (r) between the predicted values with the observational data of the relative humidity at maximum temperature )Rhstmax(  ranged from 0.40 to 0.70. The low r value can be related to the topographic conditions and low vegetation of these areas. AgMERRA daily precipitation data had excellent NRMSE. Due to the weak correlation between the predicted daily precipitation data and the observational data, the total monthly precipitation of each station was examined, which showed better correlation and NRMSE than of the daily precipitation. Considering the monthly time scale compared to the daily, NRMSE reduced from a high class to a good class, also a strong correlation was obtained especially for Raz Jarglan (0.88), Esfarayen (0.84), and Mane Semolghan (0.80) stations. Conclusions  AgMERRA gridded dataset for maximum and minimum temperature, solar radiation excluding daily precipitation and relative humidity at maximum temperature showed high accordance (d> 0.92 and NRMSE <30%) and strong correlation (0.81 ≤ r ≤ 0.96) with station data in arid, semiarid, temperate, cold and mountainous areas of North Khorasan province.  However, a more strong correlation was obtained when daily precipitation data were aggregated into monthly data. In general, the validation results of the AgMERRA simulated values with 7 synoptic stations indicated its robustness and power to produce meteorological data series. So AgMERRA data series can be used for climate studies, analysis, planning and decision making in agriculture section in North Khorasan province.