Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale
Abstract
:1. Introduction
2. Materials and Methods
2.1. Gauge Data
2.2. IMERG
2.3. ERA5
2.4. Sample Preparation
- (1)
- When the air temperature exceeded 10 °C or was lower than −10 °C, there was no difficulty in distinguishing between rainfall and snowfall. Therefore, the data with air temperatures below −10 °C and above 10 °C were deleted. This resulted in 46.3% of the dataset being eliminated.
- (2)
- Gauge observations with relative humidity (RH) lower than 10% or greater than 100% were excluded. This is because RH in nature rarely drops below 10% and cannot exceed 100%, as observed by Jennings et al. [2]. The excluded samples comprise about 0.1% of the dataset.
- (3)
- Almost all snowfall events occurred in the middle (60–90° NS) and high latitudes (30–60° NS), so the observation data for 23.5° N–23.5° S were deleted.
2.5. Statistical Metrics
3. Results and Discussion
3.1. Spatial Analysis
3.2. Seasonal and Regional Analysis
3.3. Sensitivity to Precipitation and Temperature
4. Discussion
4.1. Comparison between IMERG and ERA5
4.2. Performance over Mountainous Areas
5. Conclusions
- (1)
- The ERA5 results show better overall performance in distinguishing rainfall and snowfall events than the IMERG. The median CSI values of the IMERG and ERA5 are 0.78, and 0.82, respectively.
- (2)
- Both the IMERG and ERA5 perform well in winter, but worse in summer. The ERA5 shows good accuracy on all continents except for South America. Both products demonstrated poor performance in South America, likely due to complex terrain and warm temperature circumstances.
- (3)
- Compared with the IMERG, the ERA5 is more sensitive to snowfall events at high latitudes but shows worse performance at mid-low latitude regions. A possible reason for this phenomenon is that due to the ERA5 having a coarser resolution (0.25 × 0.25°) and a simulation based on physical mechanisms, it is more difficult for the ERA5 than the IMERG to accurately capture the complex precipitation phase in low- and medium-dimensional regions. Moreover, the IMERG performs better than the ERA5 at middle latitude regions. Both the IMERG and ERA5 have lower accuracy in rain–snow partitioning under heavy precipitation.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Xiong, W.; Tang, G.; Wang, T.; Ma, Z.; Wan, W. Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale. Water 2022, 14, 1122. https://doi.org/10.3390/w14071122
Xiong W, Tang G, Wang T, Ma Z, Wan W. Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale. Water. 2022; 14(7):1122. https://doi.org/10.3390/w14071122
Chicago/Turabian StyleXiong, Wentao, Guoqiang Tang, Tsechun Wang, Ziqiang Ma, and Wei Wan. 2022. "Evaluation of IMERG and ERA5 Precipitation-Phase Partitioning on the Global Scale" Water 14, no. 7: 1122. https://doi.org/10.3390/w14071122