Performance evaluation of satellite- and model-based precipitation products over varying climate and complex topography

Accuracy assessment of precipitation retrievals is a pre-requisite for many hydrological studies as it helps to understand the source and the magnitude of the uncertainty in hydrological response variables, particularly over regions with complex topography. This study evaluates GPM IMERGv05, TMPA 3B42V7, ERA-Interim, and ERA5 precipitation products using 256 ground-based gauge stations between 2014 and 2018 over Turkey known to have complex topography and varying climate. Error statistics, categorical performance indices, and intensity-frequency distribution of the precipitation products are investigated over varying wetness and terrain slope classes. Results show that while the monthly correlation coefficient averaged over all the products is 0.79 for regions having slopes between 5 and 10%, this value drops to 0.74 when the slope is above 15%. IMERG, TMPA and ERA-Interim products underestimate the observed precipitation over relatively wetter regions, while they overestimate over relatively drier regions and relatively higher slopes. ERA5 consistently overestimates the observed precipitation over all the wetness and slope classes. Overall, TMPA shows the smallest wet bias (0.1 mm/day), while ERA5 has the largest wet bias (0.5 mm/day). IMERG has the highest monthly correlation (i.e., 0.82 when averaged for all 256 stations) and ERA-Interim has the lowest correlation (0.77) against the ground-based observations. The successors (IMERG and ERA5) show smaller ErrSD and higher CC compared to their predecessors (TMPA and ERA-Interim) at both daily and monthly time scales. The results also show that the studied satellite-based products perform better in matching the frequency of daily precipitation intensities, whereas the studied model-based products perform better in terms of categorical performance indices for lighter precipitation events.


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The determination of periodic stationarity conditions for periodic autoregressive moving average (PARMA) processes is a prerequisite to their analysis. Means of obtaining these conditions in analytically simple forms are sought. It is shown that periodic stationarity conditions for univariate and multivariate PARMA processes can always be reduced to eigenvalue problems, which are computationally and analytically easier to deal with. Two different lumpings of the periodic process are considered along this li...
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Citation Formats
M. Amjad, M. T. Yılmaz, İ. Yücel, and K. K. Yılmaz, “Performance evaluation of satellite- and model-based precipitation products over varying climate and complex topography,” JOURNAL OF HYDROLOGY, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: