Accuracy of NWS 8" Standard Nonrecording Precipitation Gauge: Results and Application of WMO Intercomparison

Yang, Daqing; Goodison, B.; Metcalfe, John R.; Golubev, Valentin S.; Bates, Roy E.; Pangburn, Timothy; Hanson, Clayton L.

doi:10.1175/1520-0426(1998)015<0054:aonsnp>2.0.co;2

Cited by 227 publications

(240 citation statements)

References 9 publications

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“…Additionally, two basins lie to the right of the curved line (Y = 1-1/aridity) indicating a surplus of water. These basins may also require modifications to input precipitation, but it is less clear in this case as observations of precipitation are generally underestimates, especially for snowfall (e.g., Yang et al, 1998). Examining the basin set using model output terms in the Budyko framework, there are many energy-limited basins with dryness ratios as small as 0.2 and many water-limited basins with model estimated dryness ratios as large as 4.5 (Fig.…”

Section: Forcing and Streamflow Datamentioning

confidence: 99%

Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance

Newman

Clark

Sampson

et al. 2015

Hydrol. Earth Syst. Sci.

444

455

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Abstract. We present a community data set of daily forcing and hydrologic response data for 671 small-to mediumsized basins across the contiguous United States (median basin size of 336 km 2 ) that spans a very wide range of hydroclimatic conditions. Area-averaged forcing data for the period 1980-2010 was generated for three basin spatial configurations -basin mean, hydrologic response units (HRUs) and elevation bands -by mapping daily, gridded meteorological data sets to the subbasin (Daymet) and basin polygons (Daymet, Maurer and NLDAS). Daily streamflow data was compiled from the United States Geological Survey National Water Information System. The focus of this paper is to (1) present the data set for community use and (2) provide a model performance benchmark using the coupled Snow-17 snow model and the Sacramento Soil Moisture Accounting Model, calibrated using the shuffled complex evolution global optimization routine. After optimization minimizing daily root mean squared error, 90 % of the basins have NashSutcliffe efficiency scores ≥ 0.55 for the calibration period and 34 % ≥ 0.8. This benchmark provides a reference level of hydrologic model performance for a commonly used model and calibration system, and highlights some regional variations in model performance. For example, basins with a more pronounced seasonal cycle generally have a negative low flow bias, while basins with a smaller seasonal cycle have a positive low flow bias. Finally, we find that data points with extreme error (defined as individual days with a high fraction of total error) are more common in arid basins with limited snow and, for a given aridity, fewer extreme error days are present as the basin snow water equivalent increases.

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Section: Forcing and Streamflow Datamentioning

confidence: 99%

Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance

Newman

Clark

Sampson

et al. 2015

Hydrol. Earth Syst. Sci.

444

455

View full text Add to dashboard Cite

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“…The once per day assumption may, therefore result in an underestimation of the wetting losses for these countries. Many previous bias adjustment efforts [e.g., Groisman, 1998;Mekis and Hogg, 1999 for Canada;Yang et al, 1998aYang et al, , 1998b for Alaska] have added a constant wetting loss for every precipitation measurement. Recent studies have shown that this practice may be in error.…”

Section: Wetting Lossesmentioning

confidence: 99%

“…[33] Yang and others performed adjustments on the precipitation measurements from several stations in the USA [Yang et al, 1998a[Yang et al, , 1998b, Greenland , the Arctic Ocean [Yang, 1999], and Siberia [Yang and Ohata, 2001]. Hereafter we refer to all of these studies by the first author, Yang.…”

Section: Comparisons With Yang Et Al's Crsmentioning

confidence: 99%

Adjustment of global gridded precipitation for systematic bias

2003

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[1] Systematic biases in gauge-based measurement of precipitation can be substantial. Of the sources of bias, wind-induced undercatch of solid precipitation is by far the largest. A methodology for producing gridded mean monthly catch ratios (CRs) for the adjustment of wind-induced undercatch and wetting losses is developed, which is suitable for application to continental or global gridded precipitation products. The adjustments for wind-induced solid precipitation were estimated using gauge type-specific regression equations from the recent World Meteorological Organization Solid Precipitation Measurement Intercomparison. Wind-induced undercatch of liquid precipitation and wetting losses were estimated using methods employed in previous global bias adjustment efforts. Due to the unique nature of Canada's precipitation measurement network, the Canadian adjustments were determined using more detailed information than for the rest of the domain, and are therefore expected to be more reliable. The gridded gauge adjustment products are designed to be applicable both to climatological estimates and to individual years during the 1979 through 1998 reference period. Application of the CRs to an existing precipitation product yielded an increase in mean annual global terrestrial precipitation of 11.7%. As compared with recent (but more localized) studies that used a similar method to account for wind-induced catch deficiencies, our estimates of wind-induced undercatch are 1.6-7.9% higher on a mean annual basis. Compared to a previous global precipitation bias adjustment effort, our adjusted data set results on average in slightly greater warm season and lower cold season precipitation increases, greater precipitation increases over North America, and lower precipitation increases over Eurasia.

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“…The need to correct these biases especially for solid precipitation measurement has now been more widely acknowledged, as the magnitude of the errors and their variation among gauges became known and their potential effects on regional, national and global climatological, hydrological, and climate change studies were recognized [Goodison and Yang, 1995 [Sevruk, 1981;Sevruk and Hamon, 1984] and applied to the archived precipitation data in Switzerland [Sevruk, 1993]. The WMO Solid Precipitation Measurement Intercomparison provided the opportunity to develop and evaluate the improved correction procedures on a daily or 6 hourly timescale for a number of precipitation gauges commonly used around the world Goodison and Yang, 1995;Yang et al, 1998a]. This paper presents a summary of the methodology of correcting Hellmann gaugemeasured daily precipitation for biases of wind-induced undercatch, wetting loss, and trace amount of precipitation.…”

Section: Introductionmentioning

confidence: 99%

Bias correction of daily precipitation measurements for Greenland

Yang¹,

Ishida²,

Goodison³

et al. 1999

J. Geophys. Res.

Self Cite

119

105

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Abstract. A methodology for correcting the Hellmann gauge-measured daily precipitation for wind-induced undercatch, wetting loss, and trace amount of precipitation was presented and applied at 12 climate stations in Greenland for years 1994-1997. The results show the following: (1) daily corrections of the biases increase the gauge-measured annual precipitation by 35-280 mm for the 4 years (about 25-90% of the gauge-measured yearly total) in Greenland; (2) of the biases, wind-induced undercatch is the source of greatest error; wetting loss and trace amount of precipitation are also significant biases in the northern Greenland regions of low precipitation; (3) monthly correction factors (corrected/measured precipitation) differ by station and, at an individual station, by type of precipitation; (4) considerable intra-annual variation of the yearly corrections has been found in Greenland due to the fluctuation of wind speed, air temperature, and frequency of snowfall. These results suggest that annual precipitation in Greenland is much higher than previously reported, particularly in the southern regions of high precipitation; and the latitudinal precipitation gradient may also be greater over Greenland. These results will have a significant impact to water budget and glacier mass balance studies in Greenland.

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Accuracy of NWS 8" Standard Nonrecording Precipitation Gauge: Results and Application of WMO Intercomparison

Cited by 227 publications

References 9 publications

Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance

Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance

Adjustment of global gridded precipitation for systematic bias

Bias correction of daily precipitation measurements for Greenland

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