Correction of synoptic precipitation observations due to systematic measuring errors with special regard to precipitation phases

Fuchs, Tobias A.; Rapp, Jörg; Rubel, Franz; Rudolf, B.

doi:10.1016/s1464-1909(01)00070-3

Cited by 70 publications

(79 citation statements)

References 6 publications

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“…The proximity of the Black Sea, with low roughness and strong winds can explain the record value registered at Sulina in August. underestimated at higher altitudes and during winter, consistent with the findings of other studies (Fuchs et al, 2001;Yang et al, 2005). The diverse topography and meteorological influences determine a considerable interannual variability of the correction in all regions.…”

Section: Results and Validationsupporting

confidence: 91%

Climatologic adjustments to monthly precipitation in Romania

Cheval

Baciu

Dumitrescu

et al. 2011

Intl Journal of Climatology

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This article contributes to better understanding of the precipitation data, analyzing several measurement errors in Romania. Based on the influence of wind speed, solid precipitation rate, and wetting losses, we adjusted the monthly amounts registered at 159 weather stations through 1961-2006. The results emphasize distinct temporal and spatial distributions of the adjustment magnitude. In general, the correction factors increase with altitude and they have high values in the cold season, as they highly depend on wind speed and solid precipitation percentage. In Romania, bias corrections increase monthly precipitation by less than 10% from June to September, by 10-20% in the transition months, and by higher values during the winter.

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Section: Results and Validationsupporting

confidence: 91%

Climatologic adjustments to monthly precipitation in Romania

Cheval

Baciu

Dumitrescu

et al. 2011

Intl Journal of Climatology

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“…Dew point temperature was derived from maximum and minimum temperature and shortwave radiation of H08 by an empirical equation. The method of Yamazaki (2001) using TW is potentially better for estimating snowfall than the method which uses surface temperature only, since snowfall is observed at temperatures above 0°C especially under dry conditions (Fuchs et al, 2001). Snow depth and temperature in eastern Siberia that were estimated by a one-dimensional land surface model using this method showed good correlation with observations (Yamazaki, 2001), even though Equation (1) was derived from observations at 30 stations in Japan.…”

Section: Methods To Distinguish Rainfall and Snowfallmentioning

confidence: 97%

“…The global 0.5°cor-rection coefficients of Ad03 were obtained by interpolating monthly correction values that were estimated for approximately 8000 daily meteorological station data from 1994 to 1998; the correction incorporated wetting losses and wind-induced precipitation undercatch based on the gauge type provided by the World Meteorological Organization (WMO; Goodison et al, 1998). The data also included an adjustment for orographic effects, as described in Adam et al (2006).…”

Section: Correction Factors For Gauge Undercatchmentioning

confidence: 99%

“…Since the a and b values for the Hellman type gauges by Motoya et al (2002), which were obtained from the Hungarian Hellmann gauge, lead to erroneously high correction amounts under high wind velocity, new a and b values for Hellmann type gauges were obtained from a correction equation of the German Hellmann gauge (Goodison et al, 1998). Supplement 3 summarizes the parameter values a and b.…”

Section: Correction Factors For Gauge Undercatchmentioning

confidence: 99%

“…Undercatch correction coefficients for rainfall and snowfall were obtained as 1/CRrain and 1/CRsnow . To avoid excessively large correction values, the maximum wind speed to estimate correction coefficients for rainfall and snowfall was subjectively set to 6 m s 1 as Goodison et al (1998) Based on a sensitivity test in which not the wind velocity of the same year was used to correct for undercatch but wind velocity data from other years, we conclude that total correction amount of snowfall on land is underestimated by up to 5% during the periods 1948 1956 and 2003 2006. This is related to the inconsistencies of wet days between the years with wind velocity and precipitation data, as wind velocities on wet days tend to be larger than on dry days.…”

Section: Correction Factors For Gauge Undercatchmentioning

confidence: 99%

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A 59-year (1948-2006) global meteorological forcing data set for land surface models. Part II: Global snowfall estimation

Hirabayashi

Kanae

Motoya

et al. 2008

Hydrological Research Letters

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Abstract:Global terrestrial snowfall was estimated for 59 years from 1948 to 2006 by applying gauge undercatch correction for snowfall and rainfall based on daily meteorological data and gauge type. Following gauge correction, global annual snowfall estimation increased from 9.4 to 12.3 × 10 3 km 3 , while annual terrestrial precipitation increased from 112.8 to 119.6 × 10 3 km 3 . Percentage of snowfall in total precipitation increased from 8.3 to 10.3% with gauge correction. The snowfall distinction method using wet-bulb temperature produced larger values for snowfall than those obtained using a 0°C threshold method and those from reanalysis-based products. In contrast, the increase in total precipitation was half of the increase obtained by using a climatology of correction coefficients from previous studies. The estimated 59-year time series of snowfall amount showed a downward trend after the mid-1980s, suggesting a decrease in snowfall associated with a warmer climate in recent decades.

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Status of high‐latitude precipitation estimates from observations and reanalyses

et al. 2016

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An intercomparison of high-latitude precipitation characteristics from observation-based and reanalysis products is performed. In particular the precipitation products from CloudSat provide an independent assessment to other widely used products, these being the observationally-based GPCP, GPCC and CMAP products and the ERA-Interim, MERRA and NCEP-DOE R2 reanalyses. Seasonal and annual total precipitation in both hemispheres poleward of 55° latitude is considered in all products, and CloudSat is used to assess intensity and frequency of precipitation occurrence by phase, defined as rain, snow or mixed phase. Furthermore, an independent estimate of snow accumulation during the cold season was calculated from the Gravity Recovery and Climate Experiment (GRACE). The intercomparison is performed for the 2007-2010 period when CloudSat was fully operational. It is found that ERA- Interim and MERRA are broadly similar, agreeing more closely with CloudSat over oceans. ERA-Interim also agrees well with CloudSat estimates of snowfall over Antarctica where total snowfall from GPCP and CloudSat is almost identical. A number of disagreements on regional or seasonal scales are identified: CMAP reports much lower ocean precipitation relative to other products, NCEP-DOE R2 reports much higher summer precipitation over northern hemisphere land, GPCP reports much higher snowfall over Eurasia, and CloudSat overestimates precipitation over Greenland, likely due to mischaracterization of rain and mixed-phase precipitation. These outliers are likely unrealistic for these specific regions and time periods. These estimates from observations and reanalyses provide useful insights for diagnostic assessment of precipitation products in high latitudes, quantifying the current uncertainties, improving the products, and establishing a benchmark for assessment of climate models.

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Correction of synoptic precipitation observations due to systematic measuring errors with special regard to precipitation phases

Cited by 70 publications

References 6 publications

Climatologic adjustments to monthly precipitation in Romania

Climatologic adjustments to monthly precipitation in Romania

A 59-year (1948-2006) global meteorological forcing data set for land surface models. Part II: Global snowfall estimation

Status of high‐latitude precipitation estimates from observations and reanalyses

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