Adjustment of tipping-bucket precipitation gauge measurements

Sevruk, Boris

doi:10.1016/0169-8095(95)00066-6

Cited by 137 publications

(92 citation statements)

References 2 publications

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“…To appreciate the challenge of providing a reliable flood forecast it is sufficient to realize that precipitation is the most difficult of the atmospheric parameters to forecast and observe (Sevruk, 1996;. Quantitative precipitation estimation (QPE, Germann et al, 2006) and quantitative precipitation forecasting (QPF, Richard et al, 2007) are key tools for quantifying the potential for flooding, especially on short time scales and for relatively small river and urban catchments.…”

Section: Review Of Recent Interest In Dealing With Uncertaintiesmentioning

confidence: 99%

The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems

Rossa¹,

Liechti

Zappa

et al. 2011

Atmospheric Research

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Publication informationAtmospheric Research, 100 (2-3): 150-167Publisher Elsevier This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT AbstractQuantifying uncertainty in flood forecasting is a difficult task, given the multiple and strongly nonlinear model components involved in such a system. Much effort has been and is being invested in the quest of dealing with uncertain precipitation observations and forecasts and the propagation of such uncertainties through hydrological and hydraulic models predicting river discharges and risk for inundation. The COST 731 Action is one of these and constitutes a European initiative which deals with the quantification of forecast uncertainty in hydro-meteorological forecast systems.COST 731 addresses three major lines of development: (1) combining meteorological and hydrological models to form a forecast chain, (2) propagating uncertainty information through this chain and make it available to end users in a suitable form, (3)

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Section: Review Of Recent Interest In Dealing With Uncertaintiesmentioning

confidence: 99%

The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems

Rossa¹,

Liechti

Zappa

et al. 2011

Atmospheric Research

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“…The determined precipitation differences could in theory be explained by undercatch related to wind (Sevruk, 1981(Sevruk, , 1996. It was checked whether correcting the tipping bucket data (TB corr ) according to the method of Richter (1995) could reduce the precipitation difference between lysimeter and TB.…”

Section: Precipitation Measurementsmentioning

confidence: 99%

“…Undercatch is larger in case of snowfall and larger wind speeds. Wind-induced loss is seen as the main source of error (Sevruk, 1981(Sevruk, , 1996Yang et al, 1998;Chvíla et al, 2005;Brutsaert, 2010). Precipitation gauges are commonly installed above ground to avoid negative impact on the measurements by splash water, hail, and snow drift.…”

Section: Introductionmentioning

confidence: 99%

Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket

Gebler¹,

Franssen²,

Pütz³

et al. 2015

Hydrol. Earth Syst. Sci.

153

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Abstract. This study compares actual evapotranspiration (ET a ) measurements by a set of six weighable lysimeters, ET a estimates obtained with the eddy covariance (EC) method, and evapotranspiration calculated with the full-form Penman-Monteith equation (ET PM ) for the Rollesbroich site in the Eifel (western Germany). The comparison of ET a measured by EC (including correction of the energy balance deficit) and by lysimeters is rarely reported in the literature and allows more insight into the performance of both methods. An evaluation of ET a for the two methods for the year 2012 shows a good agreement with a total difference of 3.8 % (19 mm) between the ET a estimates. The highest agreement and smallest relative differences (< 8 %) on a monthly basis between both methods are found in summer. ET a was close to ET PM , indicating that ET was energy limited and not limited by water availability. ET a differences between lysimeter and EC were mainly related to differences in grass height caused by harvest and the EC footprint. The lysimeter data were also used to estimate precipitation amounts in combination with a filter algorithm for the high-precision lysimeters recently introduced by Peters et al. (2014). The estimated precipitation amounts from the lysimeter data differ significantly from precipitation amounts recorded with a standard rain gauge at the Rollesbroich test site. For the complete year 2012 the lysimeter records show a 16 % higher precipitation amount than the tipping bucket. After a correction of the tipping bucket measurements by the method of Richter (1995) this amount was reduced to 3 %. With the help of an onsite camera the precipitation measurements of the lysimeters were analyzed in more detail. It was found that the lysimeters record more precipitation than the tipping bucket, in part related to the detection of rime and dew, which contribute 17 % to the yearly difference between both methods. In addition, fog and drizzle explain an additional 5.5 % of the total difference. Larger differences are also recorded for snow and sleet situations. During snowfall, the tipping bucket device underestimated precipitation severely, and these situations contributed also 7.9 % to the total difference. However, 36 % of the total yearly difference was associated with snow cover without apparent snowfall, and under these conditions snow bridges and snow drift seem to explain the strong overestimation of precipitation by the lysimeter. The remaining precipitation difference (about 33 %) could not be explained and did not show a clear relation to wind speed. The variation of the individual lysimeters devices compared to the lysimeter mean are small, showing variations up to 3 % for precipitation and 8 % for evapotranspiration.

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“…This is possibly most pronounced in the precipitation observations. There are many sources of error in the estimation of rainfall volumes and intensities for both the tipping bucket rain gauge (Sevruk, 1996) and weather radar (Germann et al, 2006;Villarini and Krajewski, 2008). The reduction of such errors would make weather radar QPE much more appealing for hydrology in the future (Collier, 2009a;Germann et al, 2009).…”

Section: Qpe/qpf Uncertainties and Verificationmentioning

confidence: 99%

Propagation of uncertainty from observing systems and NWP into hydrological models: COST‐731 Working Group 2

Zappa

Beven

Bruen³

et al. 2010

Atmospheric Science Letters

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The COST-731 action is focused on uncertainty propagation in hydrometeorological forecasting chains. Goals and activities of the action Working Group 2 are presented. Five foci for discussion and research have been identified: (1) understand uncertainties, (2) exploring, designing and comparing methodologies for the use of uncertainty in hydrological models, (3) providing feedback on sensitivity to data and forecast providers, (4) transferring methodologies among the different communities involved and (5) setting up test-beds and perform proof-of-concepts. Current examples of different perspectives on uncertainty propagation are presented.

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Adjustment of tipping-bucket precipitation gauge measurements

Cited by 137 publications

References 2 publications

The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems

The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems

Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket

Propagation of uncertainty from observing systems and NWP into hydrological models: COST‐731 Working Group 2

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