Litcius/Paper detail

Characterizing Uncertainties in Ground “Truth” of Precipitation Over Complex Terrain Through High‐Resolution Numerical Modeling

Lin Ouyang, Hui Lü, Kun Yang, L. Ruby Leung, Yan Wang, Long Zhao, Xu Zhou, Zhu La, Yingying Chen, Yaozhi Jiang, Xiangnan Yao

2021Geophysical Research Letters48 citationsDOI

Abstract

Abstract Ground observation of precipitation over complex terrain is subject to large uncertainties due to inadequate sampling. This study explores a method that combines limited gauge data and a high‐resolution numerical simulation to quantify the precipitation uncertainties in central Himalaya. Specifically, the Coefficient of spatial Variability (CV) of precipitation and the minimum Number of Required Stations (NRS) to obtain areal‐mean precipitation ground truth values within a 0.25° area are investigated using fine‐scale meteorological simulation at 1.5 km grid spacing. Evaluation over a densely‐gauged area demonstrates comparable CV and NRS values between station observations and simulations. The simulated CV and NRS values in a larger area show a strong and positive dependence on each other and an expected positive (negative) correlation with topographic complexity (temporal scale). The proposed method sheds lights on evaluating precipitation products and holds promise for informing the layout of rain gauge networks in complex terrain.

Topics & Concepts

TerrainPrecipitationGround truthEnvironmental scienceScale (ratio)Sampling (signal processing)Correlation coefficientRain gaugeMeteorologyGridGauge (firearms)Spatial correlationGeologyRemote sensingGeodesyComputer scienceMathematicsStatisticsPhysicsGeographyCartographyArchaeologyFilter (signal processing)Computer visionMachine learningPrecipitation Measurement and AnalysisMeteorological Phenomena and SimulationsCryospheric studies and observations