Errors in Climatological Variation of Mean Areal Precipitation based on Satellite Observations and Implications for Downscaling of Climate Model Outputs

Abstract:

This study compares the scale-dependent variation in hourly Mean Areal Precipitation (MAP) derived from a satellite (S) and a radar-gauge (R) quantitative precipitation estimate (QPE), and seeks to explain the S-R differences on the basis of errors in the satellite QPE. This study employs an analytical framework to estimate the coefficient of variation (CV) of MAP for window sizes ranging from 4 to 512 km, using the rainfall fields of the CPC Morphing (CMORPH) satellite QPE and a radar-gauge multisensor QPE (MQPE) over five domains centered in Texas, Oklahoma and New Mexico. Our analyses reveal that CMORPH-based CV tends to plateau at larger window sizes (referred to as critical window size, or CWS), and is broadly higher in magnitude than that based on MQPE. The mechanisms underlying the CV differences differ between winter and summer. Over the winter, CMORPH suffers from severe underdetection, which yields suppressed fractional coverage (FC) across window sizes. This underestimation of FC, together with the lack of resolution of internal rainfall structure by CMORPH, leads to an magnification of both CWS and the magnitude of CV. By contrast, over the summer, widespread false precipitation detections in CMORPH lead to inflated FC, which tends to suppress CWS but this effect is outweighed by the opposing impacts of inflated outer and inner scales (i.e., distance parameters of indicator and conditional correlograms). Synthetic experiment shows that downscaling using the CMORPH-based CV tends to produce overly suppressed variance at finer spatial scales.