• Allerup, P., , Madsen H. , , and Vejen F. , 1997: A comprehensive model for correcting point precipitation. Nordic Hydrol., 28 , 120.

  • Bogdanova, E. G., , Ilyin B. M. , , and Dragomilova I. V. , 2002: Application of a comprehensive bias-correction model to precipitation measured at Russian North Pole drifting stations. J. Hydrometeor., 3 , 700713.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clagett, G. P., 1991: Artificial windshielding of precipitation gauges in the Arctic. Climate Monitoring and Diagnostics Laboratory Summary Rep. 15 1989–1990, 92 pp.

  • Clagett, G. P., 1992: Artificial windshielding of precipitation gauges in the Arctic. Climate Monitoring and Diagnostics Laboratory Summary Rep. 16 1990–1991, 87 pp.

  • Clagett, G. P., 1993: Artificial windshielding of precipitation gauges in the Arctic. Climate Monitoring and Diagnostics Laboratory Summary Rep. 17 1991–1992, 92 pp.

  • Golubev, V., 1985: On the problem of standard conditions for precipitation gauge installation. Proc. Int. Workshop on the Correction of Precipitation Measurements, WMO/Tech. Doc. 104, Zurich, Switzerland, World Meteorological Organization, 57–59.

  • Goodison, B. E., , and Metcalfe J. R. D. , 1989: Canadian participation in the WMO solid precipitation measurements intercomparison: Preliminary results. Proc. Int. Workshop on Precipitation Measurement, WMO/Tech. Doc. 328, St. Moritz, Switzerland, Department of Geography, Swiss Federal Institute of Technology, ETH Zurich, 121–125.

  • Goodison, B. E., , Louie P. Y. T. , , and Yang D. , 1998: WMO solid precipitation measurement intercomparison final report. WMO/Tech. Doc. 872, World Meteorological Organization, 212 pp.

  • Hosler, C. L., , Jensen D. C. , , and Goldshlak L. , 1957: On the aggregation of ice crystals to form snow. J. Meteor., 14 , 415420.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mekis, E., , and Hogg W. D. , 1999: Rehabilitation and analysis of Canadian daily precipitation time series. Atmos.–Ocean, 37 , 5385.

  • Nespor, V., , and Sevruk B. , 1999: Estimation of wind-induced error of rainfall gauge measurements using a numerical simulation. J. Atmos. Oceanic Technol., 16 , 450464.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ohtake, T., , Jayaweera K. , , and Sakurai K-I. , 1982: Observation of ice crystal formation in lower Arctic atmosphere. J. Atmos. Sci., 39 , 28982904.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Poncelet, L., 1959: Sur le comportement des pluviometres. Inst. Meteor. Belg. Publ. Ser. A, 10 , 358.

  • Rechard, P. A., , and Larson L. W. , 1971: The use of snow fences for shielding precipitation gauges. Proc. 39th Western Snow Conf., Billings, MT, Western Snow Conference, 56–62.

  • Sevruk, B., 2004: Precipitation as a Water Cycle Element: Theory and Practice of Precipitation Measurements. (in German). Zurich-Nitra, 300 pp.

    • Search Google Scholar
    • Export Citation
  • Sevruk, B., , and Hamon W. R. , 1984: International comparison of national precipitation gauges with a reference pit gauge. WMO Instrument and Observing Methods Rep. 17, 111 pp.

  • Sevruk, B., , and Klemm S. , 1989: Types of standard precipitation gauges. Proc. Int. Workshop on Precipitation Measurement, WMO/Tech. Doc. 328, St. Moritz, Switzerland, Department of Geography, Swiss Federal Institute of Technology, ETH Zurich, 227–236.

  • Sevruk, B., , and Nespor V. , 1998: Empirical and theoretical assessment of the wind-induced error of rain measurement. Water Sci. Technol., 37 , 171178.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Struzer, L. R., 1971a: On the ways of account of precipitation gauge errors caused by falling of false precipitation into precipitation gauges during blizzards (in Russian). Trans. Voyeykov Main Geophys. Observ., 260 , 3560.

    • Search Google Scholar
    • Export Citation
  • Struzer, L. R., 1971b: Practicability analysis of rain gauge international comparison test results (in Russian). Trans. Voyeykov Main Geophys. Observ., 260 , 7794.

    • Search Google Scholar
    • Export Citation
  • Sugiura, K., , and Ohata T. , 2004: Hydrometeorological study in Barrow, Alaska, 2000–2001. FORSGC Research Rep. 1, IORGC/JAMSTEC, 111–116.

  • Sugiura, K., , Yang D. , , and Ohata T. , 2003: Systematic error aspects of gauge-measured solid precipitation in the Arctic, Barrow, Alaska. Geophys. Res. Lett., 30 .1192, doi:10.1029/2002GL015547.

    • Search Google Scholar
    • Export Citation
  • UNESCO, 1978: World Water Balance and Water Resources of the Earth. Studies and Reports in Hydrology, No. 25, UNESCO, 663 pp.

  • Yang, D., 1999: An improved precipitation climatology for the Arctic Ocean. Geophys. Res. Lett., 26 , 16251628.

  • Yang, D., , and Ohata T. , 2001: A bias-corrected Siberian regional precipitation climatology. J. Hydrometeor., 2 , 122139.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, D., , Metcalfe J. R. , , Goodison B. E. , , and Mekis E. , 1993: An evaluation of the double fence intercomparison reference gauge. Proc. Eastern Snow Conf., Quebec City, QC, Canada, Eastern Snow Conference, 105–111.

  • Yang, D., , Goodison B. E. , , and Ishida S. , 1998a: Adjustment of daily precipitation data at 10 climate stations in Alaska: Application of World Meteorological Organization intercomparison results. Water Resour. Res., 34 , 241256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, D., , Goodison B. E. , , Metcalfe J. R. , , Golubev V. S. , , Bates R. , , Pangburn T. , , and Hanson C. L. , 1998b: Accuracy of NWS 8″ standard nonrecording precipitation gauge: Results and application of WMO intercomparison. J. Atmos. Oceanic Technol., 15 , 5468.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, D., , Ishida S. , , Goodison B. E. , , and Gunther T. , 1999: Bias correction of daily precipitation measurements for Greenland. J. Geophys. Res., 104D , 61716181.

    • Search Google Scholar
    • Export Citation
  • Yang, D., and Coauthors, 2000: An evaluation of the Wyoming gauge system for snowfall measurement. Water Resour. Res., 36 , 26652677.

  • Yang, D., , Kane D. L. , , Zhang Z. , , Legates D. , , and Goodison B. E. , 2005: Bias corrections of long-term (1973–2004) daily precipitation data over the northern regions. Geophys. Res. Lett., 32 .L19501, doi:10.1029/2005GL024057.

    • Search Google Scholar
    • Export Citation
  • View in gallery

    Double fence intercomparison reference.

  • View in gallery

    Canadian Nipher gauge.

  • View in gallery

    Hellmann gauge.

  • View in gallery

    Russian Tretyakov gauge.

  • View in gallery

    U.S. 8-in. gauge.

  • View in gallery

    Wyoming gauge.

  • View in gallery

    Climatology of precipitation at Barrow (Barrow W Post—W Rogers Airport) based on monthly precipitation data for the period from 1971 to 2000. The bars represent 1 std dev.

  • View in gallery

    DFIR vs various gauges: (a) Canadian Nipher gauge, (b) Hellmann gauge, (c) Russian Tretyakov gauge, (d) U.S. 8-in. gauge, and (e) Wyoming gauge.

  • View in gallery

    Mean catch ratio of snow for various gauges collected up to the end of March 2004 at the Barrow intercomparison site. Mean catch ratio of the gauges is ΣPgPdfir, where Pg is the precipitation measured by the various gauges (the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, and the Wyoming gauge), and Pdfir is the precipitation measured by the DFIR.

  • View in gallery

    Mean catch ratios of snow for various gauges obtained by the WMO intercomparison at midlatitudes. Values inside the bars are mean wind speeds (m s−1): (a) is the mean catch ratio of the Canadian Nipher gauge for snow (= ΣPcgPdfir), (b) is the mean catch ratio of the Russian Tretyakov gauge for snow (= ΣPrgPdfir), (c) is the mean catch ratio of the Hellmann gauge for snow (= ΣPhgPdfir), and (d) is the mean catch ratio of the U.S. 8-in. gauge for snow (= ΣPugPdfir); Pcg, Phg, Prg, Pug, Pwg, and Pdfir are the solid precipitation measured by the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, the Wyoming gauge, and the DFIR, respectively.

  • View in gallery

    Daily catch ratios of (a) the Canadian Nipher gauge (CRcg_d = Pcg_d/Pdfir_d), (b) the Hellmann gauge (CRhg_d = Phg_d/Pdfir_d), (c) the Russian Tretyakov gauge (CRrg_d = Prg_d/Pdfir_d), (d) the U.S. 8-in. gauge (CRug_d = Pug_d/Pdfir_d), and (e) the Wyoming gauge (CRwg_d = Pwg_d/Pdfir_d) for snow with Pdfir_d greater than or equal to 0.3 mm; Pcg_d, Phg_d, Prg_d, Pug_d, Pwg_d, and Pdfir_d are the daily solid precipitations measured by the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, the Wyoming gauge, and the DFIR, respectively. The lines in the graphs represent correction equations obtained in the WMO third intercomparison at middle latitudes: 100.00–0.44 W2 − 1.98W in (a), 100.00 + 1.13W2 − 19.45W in (b), 103.11 − 8.67W + 0.30Tmax in (c), and exp(4.61 − 0.16W1.28) in (d), where W is the wind speed at gauge height, and Tmax is the daily maximum air temperature. Since CRrg_d is a function of wind speed and maximum air temperature, the line in (c) was obtained using a maximum air temperature of −15°C. Here ○: 0° to −8°C, □: −8° to −27°C, and ♦: ≤−27°C.

  • View in gallery

    Zero-catch frequency of snow for various gauges.

  • View in gallery

    Daily catch ratio of the Russian Tretyakov gauge, CRrg_d, as a function of daily wind speed at gauge height and the amount of precipitation measured by the Russian Tretyakov gauge, Prg_d.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 44 44 16
PDF Downloads 38 38 11

Catch Characteristics of Precipitation Gauges in High-Latitude Regions with High Winds

View More View Less
  • 1 Institute of Observational Research for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokosuka, Japan
  • 2 Water and Environmental Research Center, University of Alaska Fairbanks, Fairbanks, Alaska
© Get Permissions
Full access

Abstract

Intercomparison of solid precipitation measurement at Barrow, Alaska, has been carried out to examine the catch characteristics of various precipitation gauges in high-latitude regions with high winds and to evaluate the applicability of the WMO precipitation correction procedures. Five manual precipitation gauges (Canadian Nipher, Hellmann, Russian Tretyakov, U.S. 8-in., and Wyoming gauges) and a double fence intercomparison reference (DFIR) as an international reference standard have been installed. The data collected in the last three winters indicates that the amount of solid precipitation is characteristically low, and the zero-catch frequency of the nonshielded gauges is considerably high, 60%–80% of precipitation occurrences. The zero catch in high-latitude high-wind regions becomes a significant fraction of the total precipitation. At low wind speeds, the catch characteristics of the gauges are roughly similar to the DFIR, although it is noteworthy that the daily catch ratios decreased more rapidly with increasing wind speed compared to the WMO correction equations. The dependency of the daily catch ratios on air temperature was confirmed, and the rapid decrease in the daily catch ratios is due to small snow particles caused by the cold climate. The daily catch ratio of the Wyoming gauge clearly shows wind-induced losses. In addition, the daily catch ratios are considerably scattered under strong wind conditions due to the influence of blowing snow. This result suggests that it is not appropriate to extrapolate the WMO correction equations for the shielded gauges in high-latitude regions for high wind speed of over 6 m s−1.

Corresponding author address: Konosuke Sugiura, Institute of Observational Research for Global Change, Japan Agency for Marine-Earth Science and Technology, 2-15, Natsushima-cho, Yokosuka 237-0061, Japan. Email: sugiura@jamstec.go.jp

Abstract

Intercomparison of solid precipitation measurement at Barrow, Alaska, has been carried out to examine the catch characteristics of various precipitation gauges in high-latitude regions with high winds and to evaluate the applicability of the WMO precipitation correction procedures. Five manual precipitation gauges (Canadian Nipher, Hellmann, Russian Tretyakov, U.S. 8-in., and Wyoming gauges) and a double fence intercomparison reference (DFIR) as an international reference standard have been installed. The data collected in the last three winters indicates that the amount of solid precipitation is characteristically low, and the zero-catch frequency of the nonshielded gauges is considerably high, 60%–80% of precipitation occurrences. The zero catch in high-latitude high-wind regions becomes a significant fraction of the total precipitation. At low wind speeds, the catch characteristics of the gauges are roughly similar to the DFIR, although it is noteworthy that the daily catch ratios decreased more rapidly with increasing wind speed compared to the WMO correction equations. The dependency of the daily catch ratios on air temperature was confirmed, and the rapid decrease in the daily catch ratios is due to small snow particles caused by the cold climate. The daily catch ratio of the Wyoming gauge clearly shows wind-induced losses. In addition, the daily catch ratios are considerably scattered under strong wind conditions due to the influence of blowing snow. This result suggests that it is not appropriate to extrapolate the WMO correction equations for the shielded gauges in high-latitude regions for high wind speed of over 6 m s−1.

Corresponding author address: Konosuke Sugiura, Institute of Observational Research for Global Change, Japan Agency for Marine-Earth Science and Technology, 2-15, Natsushima-cho, Yokosuka 237-0061, Japan. Email: sugiura@jamstec.go.jp

1. Introduction

It has been widely recognized that gauge-measured precipitation has systematic errors that are mainly caused by wind-induced gauge undercatch and the errors in snowfall observations are very large at high wind speeds. The World Meteorological Organization (WMO) has carried out intercomparison projects of precipitation measurement. The first international intercomparison was carried out from 1960 to 1975, with the purpose of the reduction coefficients between catches of various gauges (Poncelet 1959; Struzer 1971b). The subject of the second international intercomparison, conducted from 1972 to 1976, was rain. The purpose of this intercomparison was to obtain a quantitative assessment of the average differences between the semidaily amounts of rain, as measured by various elevated gauges and a ground-level pit gauge, and to determine these differences as a function of meteorological factors, when wetting and evaporation corrections are included. Wind-induced loss was on average to 3% (up to 20%), or to 4%–6% if wetting and evaporation losses were accounted for (Sevruk and Hamon 1984). This error depends on wind speed, rain intensity, and the type of gauge. The subject of the third international intercomparison during 1986 to 1993 was snow, and its purpose was to determine the wind-induced error and to derive standard correction procedures for wind-induced undercatch and wetting and evaporation losses. The results of this intercomparison show that wind-induced loss depends on wind speed, temperature, and type of gauge, and that nonshielded gauges showed greater losses compared to the shielded gauges (up to 80%, compared to 40%, for a wind speed of 5 m s−1 and a temperature greater than −8°C) (Goodison et al. 1998). The third WMO intercomparison sites were carried out at middle latitudes. There are strong winds in Arctic regions, with tundra arresting the growth of forests, and blowing snow occurs frequently. The catch efficiency of precipitation gauges in strong winds has been noted by Struser (1971a) and Goodison et al. (1998). Sugiura et al. (2003) provided insight into systematic errors of gauge-measured precipitation in the Arctic, and suggested that the systematic errors of gauge-measured precipitation for the Arctic conditions must take into account not only wind-induced undercatch, wetting, and evaporation losses, but also the influence of blowing snow and trace precipitation. In addition to empirical methods for deriving the wind-induced losses of precipitation measurement, Nespor and Sevruk (1999) used numerical simulation, with good results (Sevruk and Nespor 1998; Sevruk 2004). Although the corrected global precipitation map was developed (UNESCO 1978) and adjustment procedures and reference measurements have been developed for the Arctic regions (Mekis and Hogg 1999; Yang 1999; Yang et al. 1998a, 1999, 2005; Yang and Ohata 2001, Bogdanova et al. 2002), further intercomparison experiments based on the WMO precipitation procedures should be conducted in order to test and assess the various precipitation gauges in the Arctic regions.

Intercomparison was carried out at Barrow, Alaska, a high-latitude region with high winds, since 2000, in accordance with the WMO precipitation procedures (Sugiura and Ohata 2004). The purpose of the present paper is to test various precipitation gauges in the Arctic region, and to investigate the catch ratios as a function of daily mean wind speed. Furthermore, based on field data and analysis, an attempt is made to examine the catch characteristics of various precipitation gauges in high-latitude, high-wind regions and to evaluate the applicability of the WMO correction equations for Arctic windy environment with possible blowing-snow conditions.

2. Observation site and equipment

The observation site is located in the Point Barrow Observatory, National Oceanic and Atmospheric Administration/Climate Modeling and Diagnostics Laboratory (NOAA/CMDL) (71°19′N/156°36′W), near the sea level, 550 km north of the Arctic Circle. Five types of precipitation gauges (Canadian Nipher, Hellmann, Russian Tretyakov, U.S. 8-in., and Wyoming gauges) that are commonly used around the world were installed.

To measure true precipitation, a double fence intercomparison reference (DFIR) was installed near the precipitation gauges (Fig. 1). Golubev (1985) tested various designs of the double fence for snowfall measurement at the Valdai Hydrological Research Station, and the WMO uses the DFIR as an international reference standard (Goodison et al. 1998). The DFIR is a combination of two concentric octagonal lath fences. The diameters of the fences are 4 and 12 m, and the heights are 3 and 3.5 m above the ground, respectively. The lath fences are 1.5 m in length and have a density of 50%. A Russian Tretyakov gauge with a windshield is placed in the center of the fences. The orifice height of the Russian Tretyakov gauge is 3 m above the ground.

A Canadian Nipher gauge with a windshield is used as a standard gauge in Canada for snowfall observations, as shown in Fig. 2. The shield is an inverted bell-shaped spun piece that houses a cylindrical bucket. The diameter of the windshield is 610 mm for the upper part and 229 mm for the lower part, and the shield length is 508 mm. The inside diameter of the bucket is 127 mm. The bucket orifice height is 2 m above the ground.

Figure 3 shows a Hellmann gauge, which is used in Argentina, Austria, Chile, Croatia, Denmark, Germany, Greenland, Hungary, Poland, Portugal, Romania, Spain, Switzerland, and Turkey (Sevruk and Klemm 1989). This gauge consists of an upper part with a funnel-shaped base and a lower collecting part. The bucket orifice area is 0.02 m2. The bucket orifice height is 2 m above the ground.

Figure 4 shows a Russian Tretyakov gauge with a wind shield, which is used as a standard precipitation gauge in Russia. This type of gauge is also commonly used in Afghanistan, Finland, Mongolia, North Korea, and Vietnam (Sevruk and Klemm 1989). The diameter of the upper part of the wind shield is 1050 mm, and the shield length is 400 mm. The gauge bucket is placed inside the wind shield, which consists of 15 plates bent into a specific pattern. The bucket orifice area is 0.02 m2. The gauge orifice height is 2 m above the ground.

Figure 5 shows a U.S. 8-in. gauge, which is used as a standard gauge in the United States and has no wind shield. This gauge is also used in the Bahamas, Bangladesh, the Philippines, Saudi Arabia, and Thailand (Sevruk and Klemm 1989). The inner diameter of the cylindrical bucket is 203 mm. The bucket orifice height is 2 m above the ground.

Figure 6 shows a Wyoming gauge, which is used as a reference gauge for snowfall observations and has been widely used in the United States, particularly in Alaska. The Wyoming shield was developed by the University of Wyoming, and was empirically determined in a wind tunnel (Rechard and Larson 1971). The Wyoming gauge installed at the observation site is encircled by two octagonal wind shields that have a density of 50% and that are inclined at angles of 45° and 60°, respectively, from the horizontal. A Russian Tretyakov gauge without a wind shield is mounted within the Wyoming shields. The orifice height of the Russian Tretyakov gauge is the same as the height of the top of the inner shield, 2.3 m above the ground, and the height of the outer shield is 2.6 m above the ground.

Four wind speed sensors and thermometers were installed near the gauges at heights of 3.0, 2.0, 1.0, and 0.5 m above the ground.

3. Climatology of the site and observation methods

Figure 7 shows the precipitation climatology of Barrow based on data from the National Climatic Data Center [Global Historical Climatology Network (GHCN) version 2; raw monthly precipitation data] for the past 30 yr, from 1971 to 2000. The data were collected by Barrow Station (Barrow W Post—W Rogers Airport, 71°18′N/156°47′W from 1971 to 1998 and 71°17′N/156°46′W from 1998 to 2000). It is clear that the amount of precipitation is small, which is characteristic of high latitudes. Seasonal variation of monthly precipitation is clear, with a peak occurring during the summer season. Interannual variation of precipitation is large. The amount of monthly precipitation in winter season is less than 5 mm (approximately 3 mm on average), with a standard deviation of 2–3 mm. This means that measurements of solid precipitation at Barrow must be precise. Application of the correction procedures for wind, wetting loss, and trace amounts on a daily basis at Barrow for 1982 and 1983 increased snow precipitation by 90% on average (Yang et al. 1998b). Daily totals when the DFIR measurement was greater than 3.0 mm were used for the statistical analyses for the third WMO international intercomparison (Goodison et al. 1998). Since, for example, the resolution of the Russian Tretyakov gauge is 0.1 mm, the error for the gauge is estimated as 3% per 3.0 mm of precipitation and as 20% per 0.5 mm of precipitation. Low precipitation produces large errors, and therefore requires high-precision precipitation measurements. The following considerations are of particular note in this precipitation measurement. The orifice of all gauges is horizontally level, because a gauge that is off-level by only 3° can lead to errors of ±5% (Goodison et al. 1998). All of the gauges are manual gauges, and the collectors are dry before being placed in the gauges. The collectors are covered with their lids during transport. When the amount of precipitation in the collectors is measured using the measuring glass of the collector, the collectors are overturned so as to collect every drop.

Extensive testing and assessment of the DFIR performance concluded that the DFIR gives the best estimate of true solid precipitation, even though it slightly undercatches solid precipitation by 5%–10% at high wind speeds (Golubev 1985; Yang et al. 1993). In the present study, the measured solid precipitation is analyzed without correction.

4. Results and discussion

a. Comparison of DFIR and various gauges

Table 1 shows the number of precipitation events collected from March 2001 to March 2004. These precipitation events were sometimes the total accumulation of several precipitation events.

Based on the data in Table 1, the relationship between the gauge catch and the DFIR is shown in Fig. 8. Higher solid precipitation sometimes indicates the total accumulation of several weeks. Although most gauge catches increase with the DFIR catch, each gauge has its own slope. All of the slopes are less than unity on a 1:1 scale. The physical meaning of these slopes corresponds to the mean catch ratio for each gauge. Various data points show dispersion. The relationship between the solid precipitation catches of the various gauges and the DFIR, that is, the ratio of precipitation catches of the DFIR, correspond to the catch ratio for each gauge.

b. Mean catch ratios of various gauges

Allerup et al. (1997) presented a comprehensive model for correcting point precipitation, and the general model for the correction of systematic errors in precipitation measurements is
i1525-7541-7-5-984-e1
where Pc is the corrected or “true” amount of precipitation, Pm is the measured amount, ΣPim is the sum of various error sources, and k is the correction factor due to wind-induced undercatch. Assuming that Pc corresponds to the true amount of precipitation measured by the DFIR and Pim is neglected, 1/k is the ratio of the gauge to the DFIR; that is, 100/k is the catch ratio of the gauge (%). Figure 9 shows one result for the mean snow catch ratios of various gauges to the DFIR:
i1525-7541-7-5-984-e2
i1525-7541-7-5-984-e3
i1525-7541-7-5-984-e4
i1525-7541-7-5-984-e5
i1525-7541-7-5-984-e6
where , , , , and are the mean catch ratios (%) of the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, and the Wyoming gauge, respectively, to the DFIR for snow, and Pcg, Phg, Prg, Pug, Pwg, and Pdfir are the solid precipitation measured by the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, the Wyoming gauge, and the DFIR, respectively. These event data were sometimes the total accumulation of several precipitation events. The mean catch ratios of the Canadian Nipher gauge, the Russian Tretyakov gauge, and the Wyoming gauge with a wind shield were 68.1%, 53.9%, and 67.6%, respectively. On the other hand, those of the Hellmann gauge and the U.S. 8-in. gauge without a wind shield were only 6.6% and 10.2%, respectively. The shielded gauges caught more snow, and nonshielded gauges showed a greater loss of snow. This result clarified that wind shields are effective under windy conditions, such as those at Barrow, Alaska.

Comparisons with other studies are necessary to better understand our data. Clagett (1991, 1992, 1993) measured the sum total of precipitation using a gauge protected by a Wyoming shield, two gauges with a Nipher shield and an Alter shield, and nonshielded gauges during three winters (1989–90, 1990–91, 1991–92) at Barrow, Alaska. Clagett’s results showed that the Wyoming and Nipher wind shields yielded similar catches, whereas that of the Alter shielded gauge recorded less than half of the snowfall caught by the Wyoming-shielded gauge, and a nonshielded gauge caught only around 20% of the Wyoming or Nipher shield catches. Since the Wyoming, Canadian Nipher, and Russian Tretyakov gauges used for our observations had wind shields and the Hellmann and U.S. 8-in. gauges were nonshielded, the tendency of the sum total of precipitation was similar to our results.

Figure 10 shows the results for the mean catch ratios of various gauges tested during the third WMO intercomparison at middle-latitude sites (Goodison et al. 1998). The values inside the bars indicate mean wind speeds in meters per second. The figure shows that the same type of gauge was used at several other sites in the WMO intercomparison. In addition, even though the same types of gauges are compared, each mean catch ratio has difference. While and are high, that is, 78.6%–103.3% and 59.4%–91.6%, and are low, that is, 42.7%–84.9% and 43.8%–86.3%, respectively. Namely, the mean catch ratios of the nonshielded gauges decrease steadily with wind speed compared with those of the shielded gauges, and the nonshielded gauges are strongly affected by wind conditions at the site. Therefore, the tendency of the mean catch ratios shown in Fig. 9 was similar to the results of the WMO intercomparison. The mean catch ratio is a function of wind speed and air temperature, and is mainly affected by wind speed. Therefore, the unevenness of the mean catch ratio of the Russian Tretyakov gauge in Fig. 10c, for example, is due to the difference in the wind speed conditions at the sites.

c. Daily catch ratio as a function of daily wind speed

Figure 11 shows the results for the daily catch ratios (%) of the Canadian Nipher gauge, CRcg_d, the Hellmann gauge, CRhg_d, the Russian Tretyakov gauge, CRrg_d, the U.S. 8-in. gauge, CRug_d, and the Wyoming gauge, CRwg_d, for snow with a daily solid precipitation, measured by the DFIR, greater than or equal to 0.3 mm:
i1525-7541-7-5-984-e7
i1525-7541-7-5-984-e8
i1525-7541-7-5-984-e9
i1525-7541-7-5-984-e10
i1525-7541-7-5-984-e11
where Pcg_d, Phg_d, Prg_d, Pug_d, Pwg_d, and Pdfir_d are the daily solid precipitation measured by the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, the Wyoming gauge, and the DFIR, respectively. The daily mean wind speed at 2- and 3-m gauge heights (for the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, and the DFIR) was estimated using 2- and 3-m wind speed sensors, respectively, that were installed near the gauges. To estimate the daily mean wind speed at the Wyoming gauge height, the logarithmic wind profile was applied using four-height wind speed sensors installed near the gauges. The daily mean air temperature at gauge heights was estimated using a 2-m thermometer. A small number of data are two-day catch ratios. Zero catch in Fig. 11 indicates that the daily solid precipitation measured by the gauge—that is, Pcg_d, Phg_d, Prg_d, Pug_d, or Pwg_d—is equal to 0 mm and Pdfir_d is greater than or equal to 0.3 mm. Since the daily solid precipitation measured by the DFIR was characteristically low, the WMO precipitation correction procedure of using daily totals when the DFIR measurement was greater than 3 mm was unsuitable for Barrow and similar conditions. In the present study, 0.3 mm was determined for the analyses. When precipitation was below the measurable amount, it was recorded as trace precipitation and was calculated as 0 mm. In addition, when the gauge did not measure solid precipitation at all, precipitation was recorded as —, and was calculated as 0 mm. The zero catch in Fig. 11 indicates trace precipitation or no precipitation recorded by the gauges.

Generally, at low wind speeds, the catch characteristics of all of the gauges were roughly similar to the DFIR; that is, the daily catch ratios were roughly 100%. However, the daily catch ratios decrease rapidly with increasing wind speed, as shown in Fig. 11. Figure 12 shows that the zero-catch frequencies of nonshielded gauges (the Hellmann gauge and the U.S. 8-in. gauge) are 79.7% and 57.8%, and those of shielded gauges (the Canadian Nipher gauge, the Russian gauge, and the Wyoming gauge) are 10.9%, 7.8%, and 1.9%, respectively. When the wind speed is 6 m s−1 or higher, it is clear that the zero catch is very frequent. The zero catch is not uncommon for of the nonshielded gauges, such as the Hellmann and U.S. 8-in. gauges, particularly under high wind speeds. A high frequency of the zero catch for the nonshielded gauges was confirmed. In addition, the zero-catch frequencies of the nonshielded gauges for no precipitation are 14.1% and 1.6%, and for trace precipitation are 65.6% and 56.3%, respectively. When the DFIR measures the solid precipitation, no precipitation recorded by the nonshielded gauges should be considered as a nonzero value. It is noteworthy that no precipitation recorded by the nonshielded gauges is including the uncertainty with respect to solid precipitation estimates.

Figure 11 shows that overcatches of the Canadian Nipher gauge and the Russian Tretyakov gauge are eight and one snowfall events, respectively. Although in the present study the wind shield was cleaned daily, this overcatch may indicate that snow collected on the wind shield and may have occasionally been blown into the gauge. Such an overcatch of the Canadian Nipher gauge was observed by Goodison and Metcalfe (1989).

The curves of the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, and the U.S. 8-in. gauge are given by regression equations obtained in the third WMO intercomparison. These curves are restricted to mean wind speeds at the gauge height during precipitation of less than 6 m s−1. It is noteworthy that all of the catch ratio-wind slopes based on the data obtained at the Barrow site under low wind speeds are sharper than those of the WMO project, as shown in Fig. 11. Furthermore, Yang et al. (2000) evaluated the performance of the Wyoming gauge for the DFIR snow measurement greater than 3 mm and stated that the Wyoming gauge catch versus DFIR relationship did not change with wind speed at four WMO test sites in the midlatitude. However, our results based on lower snowfall data (DFIR greater than or equal to 0.3 mm) showed that the daily catch ratio of the Wyoming gauge at Barrow changed, decreasing with wind speed in the same way as the other gauges, such as the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, and the U.S. 8-in. gauge. This result suggests that the Wyoming gauge should be corrected for wind-induced losses for light snowfall events in order to estimate true precipitation.

An explanation of the difference between the catch ratio-wind slopes at the Barrow site and at the WMO intercomparison sites is given below. The dependency of catch efficiency on air temperature is shown by UNESCO (1978). The three classes of air temperatures from 0° to −8°C, from −8° to −27°C, and ≤−27°C, were taken as the parameter characterizing the structure of precipitation, and the catch efficiency clearly decreased with air temperature. As shown in Fig. 11, it is seen that the daily catch ratios at Barrow at lower air temperatures showed a weak tendency to be low. The WMO intercomparison was carried out at middle latitudes, whereas the Barrow site is located at high latitudes. Even though the type of precipitation recorded at each observation site is snow, the size of the snow particles is different. The observed snow particle sizes near Barrow were very small and were below 0.3 mm (Ohtake et al. 1982; Sugiura et al. 2003). The aggregation of ice crystals becomes weaker with decreasing air temperature based on a cold chamber experiment involving ice crystals (Hosler et al. 1957), and the formation from ice crystals to snowflakes is not dominant in high-latitude regions due to the cold climate. Wind-induced loss of precipitation is caused by the interaction between the precipitation gauge with the wind flow and snow particles falling through the air, depending on the falling particle speed, the wind speed, and the aerodynamic properties of gauge types. Since small particles are affected by viscosity more than by inertia, the wind-induced loss for small snow particles may be larger than that for large snow particles. Therefore, it is reasonable for the daily catch ratio to have decreased remarkably due to wind at the Barrow site.

Figure 11 shows that the daily catch ratios decrease gradually with increasing wind speed, and that the daily catch ratios—for example, CRcg_d, CRrg_d and CRwg_d— are considerably scattered under strong winds of over 6 m s−1, indicating that the daily catch ratios are not necessarily decreasing for speeds above 6 m s−1. To discuss this scatter under strong wind conditions, another axis is added, as shown in Fig. 13. The figure shows that the scatter has two parts: a constantly decreasing part and a high-catch-ratio part, which shows a large amount of precipitation under the strong wind conditions. The height of the gauges is 2 m, except for the 2.3-m-height for the Wyoming gauge and 3 m for the DFIR. If the snow particle concentration at the gauge heights, 2 or 2.3 m, is higher than at the DFIR, 3 m, then the catch ratios should increase. When blowing snow occurs, the concentration changes, and the concentration at 2 or 2.3 m is higher than that at 3 m. An example of the intensity of falling snow particles in blowing snow was reported by Sugiura et al. (2003). Therefore, this tendency of the catch ratio, whereby blowing-snow fluxes affect the daily catch ratios under strong wind conditions, is adequately explained. Similarly, the shielded gauges show this tendency, but not clearly, especially in the case of the Hellmann gauge, because the Hellmann gauge did not catch snow particles well and so a clear tendency is difficult to discern. Estimating corrected precipitation under high wind speeds of over 6 m s−1, it is important to note the extrapolation of the WMO regression equations, which are limited in application to wind conditions of less than 6 m s−1. Extrapolation alone is probably not necessarily suitable, because the catch ratios over 6 m s−1 are scattered greatly.

5. Summary and conclusions

Intercomparison data collected from March 2001 to March 2004 show that the mean catch ratios of the Canadian Nipher gauge, the Russian Tretyakov gauge, and the Wyoming gauge are 68.1%, 53.9%, and 67.6%, respectively. On the other hand, those of the Hellmann gauge and the U.S. 8-in. gauge are only 6.6% and 10.2%, respectively. The shielded gauges were more effective for catching snow, and nonshielded gauges showed greater undercatch.

The catch ratio was analyzed on a daily basis. The amount of daily solid precipitation measured by the DFIR is characteristically low. Therefore, the WMO precipitation procedure of using daily totals when the DFIR measurement was greater than 3 mm for the analyses is unsuitable. In addition, the high zero-catch frequency of the nonshielded gauges was observed to be 60%–80%, and the zero catch is very frequent under high wind speeds. Since the zero-catch frequency of the nonshielded gauges for no precipitation accounted for 14% of precipitation occurrences by the DFIR at Barrow, it is worth noting that no precipitation recorded by the nonshielded gauges is including the uncertainty in solid precipitation estimates.

At low wind speeds, the catch characteristics of the gauges were roughly similar to the DFIR, and it is found characteristically that, with increasing wind speed, the daily catch ratios decreased rapidly. Although an earlier study (Yang et al. 2000) revealed 10%–20% difference between the DFIR and the Wyoming gauge measurements of snow, the current results indicate that the daily catch ratio of the Wyoming gauge generally decreases with increasing wind speed. The dependency of the daily catch ratios on air temperature was confirmed, and the daily catch ratios at lower air temperature showed a weak tendency to be low. Snow particle sizes observed at Barrow were relatively small and were below 0.3 mm (Ohtake et al. 1982; Sugiura et al. 2003), and Hosler et al. (1957) showed that the aggregation of ice crystals to form snowflakes increases with temperature. Since wind-induced loss of precipitation depends on the falling particle speed, the wind speed and the aerodynamic properties of gauge types, the rapid decrease in the daily catch ratios is due to the small particle size caused by the cold climate in high-latitude regions.

In addition, the daily catch ratios of the gauges tested at Barrow are considerably scattered under strong wind conditions, especially for winds above 6 m s−1. Since the high-catch ratios for strong wind conditions show a large amount of precipitation, and since blowing-snow flux raises the amount of gauge catch, the catch ratio increases during blowing-snow conditions. Accordingly, the scattering of the daily catch ratios under strong wind conditions is due to the influence of blowing-snow flux.

The WMO correction equations for catch ratio are compared with the obtained intercomparison precipitation data collected at Barrow, and the result shows that the extrapolation of the WMO correction equations to high wind speeds above 6 m s−1 is unsuitable for Barrow, because the Barrow site is windy and the measurement of solid precipitation is strongly affected by blowing snow. In addition, determination of false precipitation, that is, the amount of blowing-snow particles into a gauge, is necessary in order to best estimate the true precipitation. Application of vertical concentration profiles of blowing snow to turbulent diffusion theory would be effective, and this study enables us to quantify the gauge catch–wind relationship in high latitudes.

Precipitation is important to climate and hydrology everywhere. However, in polar regions, there are fewer precipitation stations. Therefore, the quality of the precipitation data is more important. The results of the present study will be useful for hydrologic studies conducted in the high-latitude regions, particularly for interpretation of point solid precipitation data over high latitudes. Since the Barrow site is a unique location in the Arctic, it is important to continue to collect precipitation data in order to better understand precipitation change, to reduce the uncertainty in solid precipitation estimates, and to perform quantitative studies to develop reliable precipitation datasets in the Arctic for climate change investigations.

Acknowledgments

The authors would like to express their gratitude to the NOAA/CMDL staff (Daniel J. Endres and others) and BASC (Glenn W. Sheehan and others) for their assistance and support. The authors would also like to thank Dr. Tetsuzo Yasunari of FRCGC/JAMSTEC and Dr. Syun-ichi Akasofu of IARC/UAF for their advice. In addition, special thanks are due to Dr. Barry E. Goodison of the Meteorological Service of Canada for providing the Canadian Nipher gauge. The authors are grateful for the helpful comments by Dr. Steve Burges and the anonymous referees.

REFERENCES

  • Allerup, P., , Madsen H. , , and Vejen F. , 1997: A comprehensive model for correcting point precipitation. Nordic Hydrol., 28 , 120.

  • Bogdanova, E. G., , Ilyin B. M. , , and Dragomilova I. V. , 2002: Application of a comprehensive bias-correction model to precipitation measured at Russian North Pole drifting stations. J. Hydrometeor., 3 , 700713.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clagett, G. P., 1991: Artificial windshielding of precipitation gauges in the Arctic. Climate Monitoring and Diagnostics Laboratory Summary Rep. 15 1989–1990, 92 pp.

  • Clagett, G. P., 1992: Artificial windshielding of precipitation gauges in the Arctic. Climate Monitoring and Diagnostics Laboratory Summary Rep. 16 1990–1991, 87 pp.

  • Clagett, G. P., 1993: Artificial windshielding of precipitation gauges in the Arctic. Climate Monitoring and Diagnostics Laboratory Summary Rep. 17 1991–1992, 92 pp.

  • Golubev, V., 1985: On the problem of standard conditions for precipitation gauge installation. Proc. Int. Workshop on the Correction of Precipitation Measurements, WMO/Tech. Doc. 104, Zurich, Switzerland, World Meteorological Organization, 57–59.

  • Goodison, B. E., , and Metcalfe J. R. D. , 1989: Canadian participation in the WMO solid precipitation measurements intercomparison: Preliminary results. Proc. Int. Workshop on Precipitation Measurement, WMO/Tech. Doc. 328, St. Moritz, Switzerland, Department of Geography, Swiss Federal Institute of Technology, ETH Zurich, 121–125.

  • Goodison, B. E., , Louie P. Y. T. , , and Yang D. , 1998: WMO solid precipitation measurement intercomparison final report. WMO/Tech. Doc. 872, World Meteorological Organization, 212 pp.

  • Hosler, C. L., , Jensen D. C. , , and Goldshlak L. , 1957: On the aggregation of ice crystals to form snow. J. Meteor., 14 , 415420.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mekis, E., , and Hogg W. D. , 1999: Rehabilitation and analysis of Canadian daily precipitation time series. Atmos.–Ocean, 37 , 5385.

  • Nespor, V., , and Sevruk B. , 1999: Estimation of wind-induced error of rainfall gauge measurements using a numerical simulation. J. Atmos. Oceanic Technol., 16 , 450464.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ohtake, T., , Jayaweera K. , , and Sakurai K-I. , 1982: Observation of ice crystal formation in lower Arctic atmosphere. J. Atmos. Sci., 39 , 28982904.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Poncelet, L., 1959: Sur le comportement des pluviometres. Inst. Meteor. Belg. Publ. Ser. A, 10 , 358.

  • Rechard, P. A., , and Larson L. W. , 1971: The use of snow fences for shielding precipitation gauges. Proc. 39th Western Snow Conf., Billings, MT, Western Snow Conference, 56–62.

  • Sevruk, B., 2004: Precipitation as a Water Cycle Element: Theory and Practice of Precipitation Measurements. (in German). Zurich-Nitra, 300 pp.

    • Search Google Scholar
    • Export Citation
  • Sevruk, B., , and Hamon W. R. , 1984: International comparison of national precipitation gauges with a reference pit gauge. WMO Instrument and Observing Methods Rep. 17, 111 pp.

  • Sevruk, B., , and Klemm S. , 1989: Types of standard precipitation gauges. Proc. Int. Workshop on Precipitation Measurement, WMO/Tech. Doc. 328, St. Moritz, Switzerland, Department of Geography, Swiss Federal Institute of Technology, ETH Zurich, 227–236.

  • Sevruk, B., , and Nespor V. , 1998: Empirical and theoretical assessment of the wind-induced error of rain measurement. Water Sci. Technol., 37 , 171178.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Struzer, L. R., 1971a: On the ways of account of precipitation gauge errors caused by falling of false precipitation into precipitation gauges during blizzards (in Russian). Trans. Voyeykov Main Geophys. Observ., 260 , 3560.

    • Search Google Scholar
    • Export Citation
  • Struzer, L. R., 1971b: Practicability analysis of rain gauge international comparison test results (in Russian). Trans. Voyeykov Main Geophys. Observ., 260 , 7794.

    • Search Google Scholar
    • Export Citation
  • Sugiura, K., , and Ohata T. , 2004: Hydrometeorological study in Barrow, Alaska, 2000–2001. FORSGC Research Rep. 1, IORGC/JAMSTEC, 111–116.

  • Sugiura, K., , Yang D. , , and Ohata T. , 2003: Systematic error aspects of gauge-measured solid precipitation in the Arctic, Barrow, Alaska. Geophys. Res. Lett., 30 .1192, doi:10.1029/2002GL015547.

    • Search Google Scholar
    • Export Citation
  • UNESCO, 1978: World Water Balance and Water Resources of the Earth. Studies and Reports in Hydrology, No. 25, UNESCO, 663 pp.

  • Yang, D., 1999: An improved precipitation climatology for the Arctic Ocean. Geophys. Res. Lett., 26 , 16251628.

  • Yang, D., , and Ohata T. , 2001: A bias-corrected Siberian regional precipitation climatology. J. Hydrometeor., 2 , 122139.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, D., , Metcalfe J. R. , , Goodison B. E. , , and Mekis E. , 1993: An evaluation of the double fence intercomparison reference gauge. Proc. Eastern Snow Conf., Quebec City, QC, Canada, Eastern Snow Conference, 105–111.

  • Yang, D., , Goodison B. E. , , and Ishida S. , 1998a: Adjustment of daily precipitation data at 10 climate stations in Alaska: Application of World Meteorological Organization intercomparison results. Water Resour. Res., 34 , 241256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, D., , Goodison B. E. , , Metcalfe J. R. , , Golubev V. S. , , Bates R. , , Pangburn T. , , and Hanson C. L. , 1998b: Accuracy of NWS 8″ standard nonrecording precipitation gauge: Results and application of WMO intercomparison. J. Atmos. Oceanic Technol., 15 , 5468.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, D., , Ishida S. , , Goodison B. E. , , and Gunther T. , 1999: Bias correction of daily precipitation measurements for Greenland. J. Geophys. Res., 104D , 61716181.

    • Search Google Scholar
    • Export Citation
  • Yang, D., and Coauthors, 2000: An evaluation of the Wyoming gauge system for snowfall measurement. Water Resour. Res., 36 , 26652677.

  • Yang, D., , Kane D. L. , , Zhang Z. , , Legates D. , , and Goodison B. E. , 2005: Bias corrections of long-term (1973–2004) daily precipitation data over the northern regions. Geophys. Res. Lett., 32 .L19501, doi:10.1029/2005GL024057.

    • Search Google Scholar
    • Export Citation
Fig. 1.
Fig. 1.

Double fence intercomparison reference.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 2.
Fig. 2.

Canadian Nipher gauge.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 3.
Fig. 3.

Hellmann gauge.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 4.
Fig. 4.

Russian Tretyakov gauge.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 5.
Fig. 5.

U.S. 8-in. gauge.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 6.
Fig. 6.

Wyoming gauge.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 7.
Fig. 7.

Climatology of precipitation at Barrow (Barrow W Post—W Rogers Airport) based on monthly precipitation data for the period from 1971 to 2000. The bars represent 1 std dev.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 8.
Fig. 8.

DFIR vs various gauges: (a) Canadian Nipher gauge, (b) Hellmann gauge, (c) Russian Tretyakov gauge, (d) U.S. 8-in. gauge, and (e) Wyoming gauge.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 9.
Fig. 9.

Mean catch ratio of snow for various gauges collected up to the end of March 2004 at the Barrow intercomparison site. Mean catch ratio of the gauges is ΣPgPdfir, where Pg is the precipitation measured by the various gauges (the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, and the Wyoming gauge), and Pdfir is the precipitation measured by the DFIR.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 10.
Fig. 10.

Mean catch ratios of snow for various gauges obtained by the WMO intercomparison at midlatitudes. Values inside the bars are mean wind speeds (m s−1): (a) is the mean catch ratio of the Canadian Nipher gauge for snow (= ΣPcgPdfir), (b) is the mean catch ratio of the Russian Tretyakov gauge for snow (= ΣPrgPdfir), (c) is the mean catch ratio of the Hellmann gauge for snow (= ΣPhgPdfir), and (d) is the mean catch ratio of the U.S. 8-in. gauge for snow (= ΣPugPdfir); Pcg, Phg, Prg, Pug, Pwg, and Pdfir are the solid precipitation measured by the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, the Wyoming gauge, and the DFIR, respectively.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 11.
Fig. 11.

Daily catch ratios of (a) the Canadian Nipher gauge (CRcg_d = Pcg_d/Pdfir_d), (b) the Hellmann gauge (CRhg_d = Phg_d/Pdfir_d), (c) the Russian Tretyakov gauge (CRrg_d = Prg_d/Pdfir_d), (d) the U.S. 8-in. gauge (CRug_d = Pug_d/Pdfir_d), and (e) the Wyoming gauge (CRwg_d = Pwg_d/Pdfir_d) for snow with Pdfir_d greater than or equal to 0.3 mm; Pcg_d, Phg_d, Prg_d, Pug_d, Pwg_d, and Pdfir_d are the daily solid precipitations measured by the Canadian Nipher gauge, the Hellmann gauge, the Russian Tretyakov gauge, the U.S. 8-in. gauge, the Wyoming gauge, and the DFIR, respectively. The lines in the graphs represent correction equations obtained in the WMO third intercomparison at middle latitudes: 100.00–0.44 W2 − 1.98W in (a), 100.00 + 1.13W2 − 19.45W in (b), 103.11 − 8.67W + 0.30Tmax in (c), and exp(4.61 − 0.16W1.28) in (d), where W is the wind speed at gauge height, and Tmax is the daily maximum air temperature. Since CRrg_d is a function of wind speed and maximum air temperature, the line in (c) was obtained using a maximum air temperature of −15°C. Here ○: 0° to −8°C, □: −8° to −27°C, and ♦: ≤−27°C.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 12.
Fig. 12.

Zero-catch frequency of snow for various gauges.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Fig. 13.
Fig. 13.

Daily catch ratio of the Russian Tretyakov gauge, CRrg_d, as a function of daily wind speed at gauge height and the amount of precipitation measured by the Russian Tretyakov gauge, Prg_d.

Citation: Journal of Hydrometeorology 7, 5; 10.1175/JHM542.1

Table 1.

Collected precipitation events using manual gauges up to the end of March 2004.

Table 1.
Save