The importance of choosing precipitation datasets

Abstract

Precipitation data are important for hydrometeorological analyses, yet there are many ways to measure precipitation. The impact of station density analysed by the current study by comparing measurements from the Missouri Mesonet available via the Missouri Climate Center and Community Collaborative Rain, Hail, and Snow (CoCoRaHS) measurements archived at the program website. The CoCoRaHS data utilize citizen scientists to report precipitation data providing for much denser data resolution than available through the Mesonet. Although previous research has shown the reliability of CoCoRaHS data, the results here demonstrate important differences in details of the spatial and temporal distribution of annual precipitation across the state of Missouri using the two data sets. Furthermore, differences in the warm and cold season distributions are presented, some of which may be related to interannual variability such as that associated with the El Niño and Southern Oscillation. The contradictory results from two widely‐used datasets display the importance in properly choosing precipitation data that have vastly differing temporal and spatial resolutions. With significantly different yearly aggregated precipitation values, the authors stress caution in selecting 1 particular rainfall dataset as conclusions drawn could be unrepresentative of the actual values. This issue may be remediated by increased spatiotemporal coverage of precipitation data.

Performance of Three Reanalysis Precipitation Datasets over the Qinling-Daba Mountains, Eastern Fringe of Tibetan Plateau, China

“…Although both the meteorological stations are observed with the manually standard process in the standard field with grass land cover, the local factors such as terrain and wind are still different to considered and corrected. Many different studies [62][63][64], among many, have concluded that automated gauges have many errors associated with them, among which some errors as high as 80% under extremely detrimental conditions.…”

Dual-polarized quantitative precipitation estimation as a function of range

“…Furthermore, results demonstrate the issues with analyzing QPE from a single gauge, explaining why the Community Collaborative Rain, Hail, and Snow Network (Kelsch, 1998;Cifelli et al, 2005;Reges et al, 2016) or other densely gauged networks (e.g., the Hydrometeorological Automated Data System, HADS; and the Meteorological Assimilation Data Ingest System, MADIS) tend to be more utilized since results have shown that measurements or qualitycontrolled techniques made by these organizations, especially CoCoRaHS (Community Collaborative Rain, Hail and Snow Network), are significantly more accurate than rain gauges (Simpson et al, 2017), especially for convective events (Moon et al, 2009). …”

Validation of chirps gauge – satellite based rainfall dataset over Nicaragua, 2011 - 2021

“…Therefore, it is a primary input when developing different climate and weather numerical models. Long enough records of this variable are necessary to carry out a wide range of studies in many water-related disciplines, such as water resources management, extreme events analysis, climate change, among others (Simpson et al, 2017;Tabari, 2020).…”