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

Accurate observations of rain and snow fall in mountain catchments are essential in the management of water resources for agricultural purposes and hydroelectric generation, amongst other activities. It has long been known that wind-induced losses, or “under-catch” can have a substantial impact on precipitation gauge observations during snow or mixed phase precipitation (e.g. Alter, 1937), and seminal (Goodison et al., 1998) and ongoing (the WMO Solid Precipitation Inter-Comparison Experiment, or SPICE) work attempts to quantify these impacts. In Australia, the accurate measurement of rain and snow fall in alpine regions, including the Snowy Mountains has not received due attention for a number of reasons, yet these mountains form the catchments for a number of major rivers, including the economically and ecologically critical Murray-Darling system.

Since 2005, an independent network of all-weather ETI NOAH-II precipitation gauges has been progressively installed in the Snowy Mountains region. A number of these gauges have been installed inside special double-fenced structures to reduce the effect of wind-induced losses. Intercomparison sites at 1586 m and 1741 m elevation provide an ideal opportunity to compare the performance the NOAH-II gauges in different wind-fence configurations during wintertime precipitation. We found that average ambient temperature over six hour periods was sufficient to classify the precipitation type as “snow”, “mixed” or “rain” in a statistically robust way, and separate “catch ratio” (the quotient of observations from two gauges) relationships, based on wind speed and ambient temperature, were established for different precipitation types.

Using wind speed and temperature observed at the other sites with unfenced NOAH-II gauges, the catch ratio relationships were applied to adjust the observed precipitation amounts, and the impact of wind-induced losses over the winter seasons from 2006 to 2012 was assessed. The resulting dataset was also compared to the Australian Bureau of Meteorology's Water Availability Project (AWAP) dataset, which uses interpolating splines to estimate precipitation amounts in alpine regions from sparse daily precipitation observations.

REFERENCES

Alter, J. C., 1937: Shielded Storage Precipitation Gages. Monthly Weather Review, 65, 262.

Goodison, B., P. Louie, and D. Yang, 1997: The WMO Solid Precipitation Measurement Intercomparison. Tech. rep., World Meteorological Organization.