عنوان مقاله [English]
Precipitation is considered to be the most important phenomenon because the precipitation process is associated with atmospheric synoptic systems, energy interactions between the Earth's surface and the oceans. Today, various methods are used to predict the phenomenon of precipitation. The traditional method or synoptic analysis is the most basic of the predictive methods Subsequently, with the expansion of atmospheric models, rainfall prediction numerical methods were used which due to the general and spatial extent, errors are sometimes found in their estimation. Meteorological radars were used to increase the precision of accuracy These radars were used to calculate cloudy precipitation water. The advantage of using rainfall sensing methods is to better understand the phenomenon of rainfall and its effective parameters in a wide spatial range. For this reason, researchers are now investigating the rainfall estimation using satellite imagery. This research was carried out to evaluate the data of TRMM satellite, GPM satellite and radar data of Kermanshah and compare the data recorded in the stations in the heavy rain November 2012 in the western part of the country and to verify the accuracy of estimated precipitation of the data The satellite is done.
area of study:
The area of study area is 89505 km2, which is about 5/5% of the total area of Iran. This region is located in western Iran, in the range of 45 degrees and 24 minutes to 49 degrees and 36 minutes east, and 31 degrees 58 minutes to 36 degrees and 30 minutes north. From northwest to western province of Azarbaijan, south of Khuzestan Province and east to Lorestan and Central provinces and west to Iraq. The study area is located in the western slopes of Zagros.
materials and methods:
The data sets used in this research are:
1- Doppler Meteorological Radar Information:
Iran's Meteorological Organization is developing a Doppler Meteorological Radar Matrix across Iran with the highest concentration of radars in the provinces of western, north and south of Iran. The data used in this study was collected using Kermanshah radar, one of three western weather radars of Iran.
2- Weather station info:
In this research, ten weather stations located in four provinces of Kermanshah, Ilam, Kordestan and Hamedan were used.
3- GPM Satellite Information:
The satellite's information is available on a daily basis and every two hours. Through NASA, data on wave activity days was extracted.
4-TRMM Satellite Information:
The satellite is available every day and every three hours. Through the GIOVANNI site, information about the days of wave activity was extracted.
There is a very good correlation between satellite-radar data and ground stations.
The Pearson correlation coefficient between the mean and maximum rainfall data of the Kermanshah meteorological radar with its corresponding data on GPM and TRMM satellites is equal to 0.813 and 0.888 for GPM 0.821 and 0.873 ** for TRMM And statistically significant at 1% level.
In general, it can be concluded that Kermanshah weather forecast radar data have a good correlation with satellite precipitation data in determining rainfall rainfall and location of rainfall. It was also discovered that the Kermanshah meteorological radar, between 225 and 360 degrees, around its antenna, in the position of the Ilam and Kermanshah provinces, And also between the angles of 90 to 135 degrees, the west of the Kurdistan province of Iran and parts of Iraq.
Discussion and Conclusion:
Rainfall as an input element is often considered climatic, atmospheric and hydrological. If you need to study macros, access to a large and homogeneous database is essential.
For this purpose, satellite data can be used as a relatively desirable source. In the present study, accuracy of precipitation data of GPM, TRMM and Droppler radar of Kermanshah was evaluated with ground station data. The determination coefficients at a significant level of 5% indicate that the equations between rainfall data recorded in the regional stations, satellite and radar are meaningful, so that the determination coefficient between the GPM satellite data and the Doppler radar and the radar with the TRMM satellite The stations of the region with GPM and TRMM satellites were 0.75, 0.73, 0.59 and 0.58, respectively. The above correlations indicate that satellite precipitation data is a linear regression between observed values and correctional satellite values and is applicable to meteorological and hydrologic studies. In general, the results of this research show that satellite data after applying the coefficient and simple corrections are well-considered and can be used in different fields.