عنوان مقاله [English]
Rainfall prediction at regional and global scales is mostly the principle component of hydro-meteorological studies in un-gauged regions. Ground-based measurements of precipitation are available with high accuracy in synoptic stations. Spatial distribution of operational stations is now as one of the biggest problems in the developing countries such as Iran, which the spatial distribution of the stations is not enough. In recent decades, remote sensing data have widely been used by many researchers in the world for drought monitoring and management of water resources. The satellites data can be used as compensation for temporal and spatial distribution of rainfall. The satellite-based rainfall estimates provided by the Tropical Rainfall Measuring Mission (TRMM) satellite at global scale, are now available freely as the only data source in the regions without in-situ measurements. Most regions of Iran have arid and semi-arid climates. The evaluation and calibration of TRMM data in different regions of Iran at daily and monthly time scales is very important before those data are used by researchers, experts, climate scientist, hydrologist, and etc. Therefore, a comprehensive evaluation and calibration of the TRMM 3B43 and 3B42 dataset at 87 synoptic stations in Iran including six climatic zones, is the main objective of this present research.
Materials and Methods
This research was carried out in Iran. It is located between 44˚14’ to 63˚20 E longitude and 25˚03’ to 39˚47 N latitude, with an area of more than 1.6 million Km2. Alijani et al. (2008) classified Iran climate according to climatological parameters to six separate climatic classes: desert, semi desert, mountainous, semi-mountainous, coastal wet, and coastal desert. This study aims to evaluate the accuracy of the Tropical Rainfall Measuring Mission (TRMM) satellite and its calibration on the daily, monthly, seasonal and annual scales at the synoptic stations located in climate zones of Iran. The daily TRMM-3B42 and monthly TRMM-3B43 collection data were downloaded from the NASA website. After early processing, a comparative analysis was carried out for satellite data and observed rainfall data at 87 synoptic stations during a 12-year data period of 2009-1998. The Desert, semi desert, mountain, semi-mountain, coastal desert and coastal wet climate zones are containing 22, 19, 19, 12, 8 and 7 stations, respectively. We utilized different error measures (R, ME, MAE and RMSE), and agreement indices (POD, FAR, CSI and TSS) for satellite data evaluation. Since there were noticeable errors, regional mean data were calibrated in the daily and monthly scales and finally two correction coefficients were introduced based on regression analysis.
Results and Discussion
Day-to-day rainfall comparisons showed that the TRMM rainfall estimates are very similar to the observed data values, even if a general overestimation in the satellite products must be highlighted. We found out a high similarity between two sources of rainfall data at 87 synoptic stations in most of climatic zones. Furthermore, The TRMM revealed the highest error at Ramsar, Bandar Anzali, Rasht and Babolsar stations, and the lowest errors at Zahedan, Bam and Esfahan stations. In other words, the TRMM revealed the highest error in coastal wet zone and the lowest error in desert zone. The False Alarm ratio (FAR) indicator has the lowest value in coastal wet zone that shows TRMM applicability to predict rainfall amount at these stations. The highest correlation coefficients on monthly and daily scales were 0.86 and 0.998 in the semi mountainous zone, respectively. The lowest values were 0.49 and 0.78 in the humid zone, respectively. After applying the calibration coefficients, The RMSE values were significantly reduced at monthly scale. This indicates that the calibrated TRMM data is mostly similar to the observed rainfall data at different time scales and climatic zones.
In the recent years, the accurate measurement of precipitation and its spatial and temporal distribution have been addressed frequently at un-gauged regions of the world. At present, the estimation of rainfall by the TRMM satellite is only data source, which is available freely at global scale. The main purpose of present study is to evaluate the TRMM rainfall data and to provide the correction coefficients in desert, semi-desert, mountainous, semi-mountainous, coastal wet and coastal desert climatic zones, on daily and monthly scale. The main advantage of this work is to apply various statistical error criteria and newly introduced agreement indicators to evaluate TRMM data. The results reveal that the TRMM overestimates rainfall on daily and monthly scales at 68% of stations. In general, The TRMM could detect most of rainy days in the climate zone and Iran during 1998-2009 period. The calibrated data were very similar to the measured values. Therefore, our research findings revealed that the calibration process could improve rainfall estimates at most of climatic zones, significantly.