Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 1163–1167, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-1163-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 1163–1167, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-1163-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  31 Oct 2019

31 Oct 2019

EVALUATION OF TRMM-3B42V7 AND PERSIANN-CDR DAILY-PRECIPITATION PRODUCTS FOR THE SOUTHERN SLOPES OF ALBORZ MOUNTAINS, IRAN

S. Khalighi-Sigaroodi1, E. Ghaljaee1, A. Moghaddam Nia1, A. Malekian1, and F. Zhang2 S. Khalighi-Sigaroodi et al.
  • 1Faculty of Natural Resources, University of Tehran, Karaj, Iran
  • 2Institute of Tibetan Plateau Research, Chinese Academy of Sciences, China

Keywords: Precipitation, Error assessment, TRMM-3B42 V7, PERSIANN-CDR, Southern slopes of Alborz mountains of Iran

Abstract. The density of rain gauges in many regions is lower than standard. Therefore, there are no precise estimates of precipitation in such regions. Today the use of satellite data to overcome this deficiency is increasing day to day. Unfortunately, the results from different satellite products also show a significant difference. Hence, their evaluation and validation are very important. The main objective of this study is to investigate the accuracy of the daily precipitation data of TRMM-3B42 V7 and PERSIANN-CDR satellites under a case study in the southern slopes of Alborz mountains, Iran. For this purpose, satellite precipitation data were compared with ground measured precipitation data of 12 synoptic stations over a 15- year period. The statistical criteria of MAE, RMSE, and Bias were used to assess error and the statistical indices of POD, FAR, and CSI was used to evaluate the recognition rate of occurrence or non-occurrence of precipitation. The results showed that there is a low correlation between satellite precipitation data and ground measured precipitation data, and the lowest and the highest values of correlation coefficient are from 0.228 to 0.402 for TRMM and from 0.047 to 0.427 for PERSIANN, respectively. However, there is a theoretical consensus on other assessment parameters, so that TRMM data is preferable in terms of the amount of data bias and the False Alarm Ratio (FAR) and PERSIANN data is superior in terms of RMSE, POD, and CSI. Also, it seems that in the study region, both of TRMM and PERSIANN have overestimated the number of daily precipitation events, so that the number of daily precipitation events was estimated about 125% and 200% of ground stations by TRMM and PERSIANN, respectively.