EGU23-10873, updated on 24 Oct 2023
https://doi.org/10.5194/egusphere-egu23-10873
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Spatial downscaling of IMERG precipitation estimates using statistical techniques

Stavros Stathopoulos and Alexandra Gemitzi
Stavros Stathopoulos and Alexandra Gemitzi
  • Democritus University of Thrace, XANTHI, Greece (sstathop@env.duth.gr)

The aim of this study was to spatially downscale the Precipitation Estimates (PEs) from the Global Precipitation Measurement (GPM) mission, using the Integrated Multi-satellite Retrievals for GPM (IMERG), over a complex region in Greece. For this purpose, the Multivariate Linear Regression (MLR) and the Residual Correction (RC) techniques were utilized, in conjunction with remote sensing cloud properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, onboard Aqua satellite, namely Cloud Optical Thickness (COT), Cloud Effective Radius (CER) and Cloud Water Path (CWP). The downscaled PEs were then validated using regional rain gauges’ measurements. According to our analysis, the 0.01o downscaled IMERG PEs were found to be more accurate than the original 0.1o IMERG data, over the region. In addition, the implementation of the RC technique to the 0.01o downscaled PEs was observed to improve the performance of the MLR downscaling method. This research was funded by the EU project titled: WATERLINE project id CHIST-ERA-19-CES-006.

How to cite: Stathopoulos, S. and Gemitzi, A.: Spatial downscaling of IMERG precipitation estimates using statistical techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10873, https://doi.org/10.5194/egusphere-egu23-10873, 2023.