EGU21-3575
https://doi.org/10.5194/egusphere-egu21-3575
EGU General Assembly 2021
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

The effect of different contributing sensors in IMERG-Final precipitation estimates

Hooman Ayat1, Jason Evans1, and Ali Behrangi2,3
Hooman Ayat et al.
  • 1Climate Change Research Centre and ARC Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, New South Wales, Australia
  • 2University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, Arizona, USA
  • 3University of Arizona, Department of Geosciences, Tucson, Arizona, USA

Ground observation absence in many parts of the world highlights the importance of merged satellite precipitation products. In this study, we aim to evaluate the effect of different sources of data in the uncertainties of a merged satellite product, by comparing the Integrated Multi-satellitE Retrievals for GPM (IMERG) final-product V06B with a ground-radar product, Multi-Radar Multi-Sensor (MRMS), over eastern United-States during the hurricane days that occurred in 2016-2018 using both pixel-based and object-based approaches. The results showed that IMERG had better agreement in terms of the average precipitation intensity and area when the passive microwave (PMW) sensor overpass is matched instantaneously with MRMS in comparison with the temporally averaged MRMS data (MRMS-Averaged) with a bias reduction of 75% and 65%, respectively. PMW observations tend to show storms with smaller areas in the IMERG final product in comparison with MRMS, possibly due to the effect of light precipitation not detected properly by PMW sensors. However, by removing the light precipitation (less than 1mm/hr) in the object-based approach, hurricane objects in the IMERG final product tend to be larger during the PMW observations, which might be related to different viewing angles of sensors contributing to MRMS and IMERG products. Precipitation estimates in the IMERG final product have smaller areas with higher average intensity during the PMW observations compared to data estimated by Morph or IR (morph/IR) observations. It is probably related to the effect of morphing technique, leading to homogenization of the varying rainstorm characteristics. The quality of IMERG data changes with the longer absence of the PMW observations. IMERG data estimated by morph/IR observations, with a 30-minute time-distance to the nearest PMW observation, showed the best agreement with MRMS-Averaged even in comparison with PMW estimates, possibly due to the time-lag in recording the precipitation between satellites and ground-radars. It is also possible to be related to the homogenizing nature of morphing technique in IMERG and averaging MRMS data in time in MRMS-Averaged, relaxing the differences between PMW observations and MRMS. However, the morph/IR data quality deteriorates with the longer absence of PMW sensors. The inter-comparison of PMW sensors showed the priority of imagers over sounders with GMI as the best among imagers and MHS as the best among sounders in terms of correlation and average intensity compared to MRMS; however, SSMIS was the best in capturing the precipitation area.

How to cite: Ayat, H., Evans, J., and Behrangi, A.: The effect of different contributing sensors in IMERG-Final precipitation estimates, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3575, https://doi.org/10.5194/egusphere-egu21-3575, 2021.