Global Precipitations and Climate Change 1994
DOI: 10.1007/978-3-642-79268-7_14
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The Effect of Dimensions and Shape of Precipitation Gauges on the Wind-Induced Error

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Cited by 17 publications
(15 citation statements)
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“…It is well-known that precipitation analysis is also hampered by systematic errors, which can attain underestimations of up to 15 per cent for rain and up to 40 per cent for episodes of snow fall (Sevruk, 1989;Groisman and Legates, 1994;Sevruk and Nespor, 1994). The principal error source is the wind®eld deformation above the gauge, and hence these errors depend on the local wind speed, on the fall speed of hydrometeors, as well as the rain-gauge type.…”
Section: Datamentioning
confidence: 99%
“…It is well-known that precipitation analysis is also hampered by systematic errors, which can attain underestimations of up to 15 per cent for rain and up to 40 per cent for episodes of snow fall (Sevruk, 1989;Groisman and Legates, 1994;Sevruk and Nespor, 1994). The principal error source is the wind®eld deformation above the gauge, and hence these errors depend on the local wind speed, on the fall speed of hydrometeors, as well as the rain-gauge type.…”
Section: Datamentioning
confidence: 99%
“…All but snow depth are predominantly measured with precipitation gauges (rain gauge if only liquid precipitation is measured). Precipitation measurements represent point measurements and are representative to a limited area, accompanied by errors and are very sensitive to exposure, and in particular to wind (Sevruk and Nespor, 1994;Groisman et al, 1999;WMO, 2010;Wolff et al, 2015;Kochendorfer et al, 2017a,b). Fog, dew, throughfall and stemflow are facultative measurements within ICOS at the moment, and therefore only briefly outlined in the section dealing with potential improvements in the future.…”
Section: Methodsmentioning
confidence: 99%
“…All types of precipitation measurements at ICOS ecosystem stations are done with the aim to provide long-term high-quality continuous data. Precipitation gauges are accompanied by errors induced due to wind effects (systematic wind field deformation above the gauge orifice) (Wolff et al, 2013;Colli, 2014) and the inhomogeneity introduced by the design of the measuring device (Sevruk and Nespor, 1994). Further errors include wetting losses (Sevruk, 1974a) and evaporation losses (Sevruk, 1974b;Leeper and Kochendorfer, 2015) inside the collection funnel, sampling errors due to weighing and tipping mechanisms (Sevruk and Chvíla, 2005) and in-and out-splashing effects due to device location, as well as random observational and instrumental errors.…”
Section: Sources Of Error For Precipitation Gaugesmentioning
confidence: 99%
“…A wide range of differences are evident. Apart from the well-known errors in rain gauge estimates (reviewed in Legates and Willmott 1990;Sevruk 1994;Sevruk and Nespor 1994;Strangeways 1996a, b), there are also errors due to the dearth of point-scale measurements of precipitation over mountainous areas (where rain gauges are scarce to non-existent) and also over oceans. Consequently even the baseline precipitation data sets remain flawed but they still are the best available benchmarks for comparison with GCM outputs.…”
Section: Examples Of Uncertainties Linked With Gcms In Se Asiamentioning
confidence: 98%