Estimation of wind-induced losses from a precipitation gauge network in the Australian Snowy Mountains

Thomas Chubb, Michael J Manton, Steven T Siems, Andrew D Peace, Shane P Bilish

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17 Citations (Scopus)

Abstract

Wind-induced losses, or undercatch, can have a substantial impact on precipitation gauge observations, especially in alpine environments that receive a substantial amount of frozen precipitation and may be exposed to high winds. A network of NOAH II all-weather gauges installed in the Snowy Mountains since 2006 provides an opportunity to evaluate the magnitude of undercatch in an Australian alpine environment. Data from two intercomparison sites were used with NOAH II gauges with different configurations of wind fences installed: unfenced, WMO standard double fence intercomparison reference (full DFIR) fences, and an experimental half-sized double fence (half DFIR). It was found that average ambient temperature over 6-h periods was sufficient to classify the precipitation phase as snow, mixed precipitation, or rain in a statistically robust way. Empirical catch ratio relationships (i.e., the quotient of observations from two gauges), based on wind speed, ambient temperature, and measured precipitation amount, were established for snow and mixed precipitation. An adjustment scheme to correct the unfenced NOAH II gauge data using the catch ratio relationships was cross validated with independent data from two additional sites, as well as from the intercomparison sites themselves. The adjustment scheme was applied to the observed precipitation amounts at the other sites with unfenced NOAH II gauges. In the worst-case scenario, it was found that the observed precipitation amount would need to be increased by 52% to match what would have been recorded had adequate shielding been installed. However, gauges that were naturally well protected, and those below about 1400 m, required very little adjustment. Spatial analysis showed that the average seasonal undercatch was between 6% and 15% for gauges above 1000 m MSL.
Original languageEnglish
Pages (from-to)2619-2638
Number of pages20
JournalJournal of Hydrometeorology
Volume16
Issue number6
DOIs
Publication statusPublished - 2015

Keywords

  • Algorithms
  • Applications
  • Automatic weather stations
  • Mathematical and statistical techniques
  • Mountain meteorology
  • Observational techniques and algorithms
  • Quality assurance/control
  • Regression analysis
  • Surface observations

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