Validating the intrinsic uncertainty: Implications for hydrologic applications

Abstract

The critical importance of accurate water flux estimates for science and applications explains the large body of verification analyses focusing on precipitation estimates. Very few are implemented at the relevant scales to address the intrinsic uncertainty of precipitation products. This endeavor requires the expert use of other precipitation sensors such as radar-gauge combinations. The intrinsic uncertainty structure of satellite-based quantitative precipitation estimates is still largely unknown at the spatiotemporal scales near the sensor measurement scale. Without relevant information on key uncertainty features, applications making use of satellite Level-3 precipitation products are impacted both in terms of outcomes and physical realism. Ultimately, it requires more than just one deterministic “best estimate” to adequately cope with the intermittent, highly-skewed distribution that characterizes precipitation. Advancing the use of uncertainty as an integral part of the relationship between sensor measurements and precipitation estimates has the potential to provide a framework for diagnosing intrinsic uncertainty.