How Well Do Multisatellite Products Capture the Space–Time Dynamics of Precipitation? Part I: Five Products Assessed via a Wavenumber–Frequency Decomposition.

As more global satellite-derived precipitation products become available, it is imperative to evaluate them more carefully for providing guidance as to how well precipitation space–time features are captured for use in hydrologic modeling, climate studies, and other applications. Here we propose a space–time Fourier spectral analysis and define a suite of metrics that evaluate the spatial organization of storm systems, the propagation speed and direction of precipitation features, and the space–time scales at which a satellite product reproduces the variability of a reference "ground-truth" product ("effective resolution"). We demonstrate how the methodology relates to our physical intuition using the case study of a storm system with rich space–time structure. We then evaluate five high-resolution multisatellite products (CMORPH, GSMaP, IMERG-Early, IMERG-Final, and PERSIANN-CCS) over a period of 2 years over the southeastern United States. All five satellite products show generally consistent space–time power spectral density when compared to a reference ground gauge–radar dataset (GV-MRMS), revealing agreement in terms of average morphology and dynamics of precipitation systems. However, a deficit of spectral power at wavelengths shorter than 200 km and periods shorter than 4 h reveals that all satellite products are excessively "smooth." The products also show low levels of spectral coherence with the gauge–radar reference at these fine scales, revealing discrepancies in capturing the location and timing of precipitation features. From the space–time spectral coherence, the IMERG-Final product shows superior ability in resolving the space–time dynamics of precipitation down to 200-km and 4-h scales compared to the other products. Significance Statement: Precipitation estimation products are essential for understanding water cycle dynamics and climate change, and for decision support in regions lacking ground observations. Several global products exist from multiple satellites orbiting Earth, but the challenge remains that of evaluating these products for accuracy and for improving the retrieval algorithms. Here we posit that the classical "pixel-to-pixel" comparison is not adequate and propose an approach that focuses on comparing space–time dynamics through a Fourier spectral analysis, which provides information about the size, shape, and orientation of precipitation systems, as well as their motion speed and direction. We evaluate five state-of-the-art multisatellite products and identify shortcomings, in particular in their ability to capture the submesoscale variability of precipitation. [ABSTRACT FROM AUTHOR]