عنوان مقاله [English]
In climatic and environmental studies, we sometimes encounter data gap or deficiency, so using other sources for creating reliable meteorological data at different spatiotemporal scales, becomes crucially important. For this, various research groups around the world have been collecting multiple meteorological data from different terrestrial and satellite sources and combining them to provide regular global data at different scales. In this study, the applicability of AgMERRA as a gauge-satellite database was evaluated in order to fill meteorological data gap, using goodness of fit measures and probability distribution functions. This was completed with the ultimate goal of producing reliable climatic data to study Hamoun International Wetland.
We studied three major synoptic stations of Sistan plain in southeast of Iran: Zabol, Zahak and Zahedan. The observed daily maximum, minimum and average temperatures and precipitation data were collected through Iran meteorological Organization (IMO). AgMERRA Data was downloaded through NASA website and extracted with OPEN NCfile software. Then five goodness of fit were calculated at three spatiotemporal scales (daily, 14 days, monthly) to define correlation between the observed and simulated data.
We found that AgMERRA has good ability to fill temperature data deficiency in the three studied stations. RMSE, NRMSE, MBE and d showed good and high correlation between the observed and modeled temperature data. Also R2 was high for temperature data at three temporal scales. However, correlation coefficient for daily and 14-day precipitation was <0.5 and <0.6 respectively, which is low. At the three stations, R2 was higher than 0.7 for the monthly precipitation.
Results showed that AgMERRA has an acceptable potential to simulate meteorological data of the study area especially for temperature and could be used to fill the data gap. The generated data will be used to check the status of the Hamoon International Wetland.