Precipitation measurement intercomparison in the Qilian Mountains, north-eastern Tibetan Plateau

Abstract

Abstract. An experimental field study of wind-induced bias in precipitation measurements was conducted from September 2010 to April 2015 at a grassland site (99°52.9´ E, 38°16.1´ N; 2980 m) in the Hulu watershed in the Qilian Mountains, on the north-eastern Tibetan Plateau, in China. The experiment included (1) an unshielded Chinese standard precipitation gauge (CSPGUN; orifice diameter = 20 cm, height = 70 cm), (2) a single Alter shield around a CSPG (CSPGSA), (3) a CSPG in a pit (CSPGPIT) and (4) a Double-Fence International Reference (DFIR) with a Tretyakov-shielded CSPG (CSPGDFIR). The catch ratio (CR) used the CSPGDFIR as a reference (CR = CSPGX/CSPGDFIR, %; X denotes UN, SA or PIT). The results show that the CSPGSA, CSPGPIT and CSPGDIFR caught 0.9, 4.5 and 3.4 % more rainfall; 7.7, 15.6 and 14.2 % more mixed precipitation (snow with rain, rain with snow); 11.1, 16.0 and 20.6 % more snowfall and 2.0, 6.0 and 5.3 % more precipitation (of all types), respectively, than the CSPGUN from September 2012 to April 2015. The CSPGPIT and CSPGDFIR caught 3.6 and 2.5 % more rainfall; 7.3 and 6.0 % more mixed precipitation; 4.4 and 8.5 % more snowfall; and 3.9 and 3.2 % more total precipitation, respectively, than the CSPGSA. However, the CSPGDFIR caught 1.0 % less rainfall; 1.2 % less mixed precipitation; 3.9 % more snowfall and 0.6 % less total precipitation than the CSPGPIT. From most to least precipitation measured, the instruments ranked as follows: for rain and mixed precipitation, CSPGPIT > CSPGDFIR > CSPGSA > CSPGUN; for snowfall, CSPGDFIR > CSPGPIT > CSPGSA > CSPGUN. The CR vs. 10 m wind speed for the period of precipitation indicated that with increasing wind speed from 0 to 8.0 m s−1, the CRUN/DFIR and CRSA/DFIR for rainfall decreased slightly. For mixed precipitation, the wind speed showed no significant effect on CRUN/DFIR and CRSA/DFIR below 3.5 m s−1. For snowfall, the CRUN/DFIR and CRSA/DFIR vs. wind speed showed that CR decreased with increasing wind speed. The precipitation measured by the shielded gauges increased linearly relative to that of the unshielded gauges. However, the increase in the ratio of the linear correlation should depend on specific environmental conditions. A comparison of the wind-induced bias indicates that the CSPGPIT could be used as a reference gauge for rain, mixed and snow precipitation events at the experimental site. As both the PIT and DFIR effectively prevented wind from influencing the catch of the precipitation gauge, the CRPIT/DFIR had no relationship with wind speed. Cubic polynomials and exponential functions were used to quantify the relationship between catch ratio and wind speed. For snow, for both event and daily scales, the CRUN/DFIR and CRSA/DFIR were significantly related to wind speed; while for rain and mixed precipitation, only the event scale showed a significant relationship.

Effects of Cryospheric Change on Alpine Hydrology: Combining a Model With Observations in the Upper Reaches of the Hei River, China

“…It is widely recognized that snowfall observation errors can be large with high winds and that precipitation gauge measurements contain systematic errors caused mainly by wetting, evaporation loss, and wind‐induced undercatch (Sugiura et al, ; Yang et al, ). Because the precipitation gauges at the CMA and CMWR stations are unshielded Chinese standard precipitation gauges (CSPGs), an intercomparison of 5‐year precipitation measurements among CSPGs with different shielding was conducted in the Hulu watershed in the UHR (R. Chen et al, ) to provide the CSPG catch ratio versus wind speed equations for rainfall, snowfall, and sleet. Because wind speed data are rare, an accurate wind field is impossible in the WCRC, so these equations could not be used in the CBHM.…”

Adjustment of measurement errors to reconcile precipitation distribution in the high‐altitude Indus basin

“…The underestimated precipitation by Dahri et al . () is probably due to the use of net precipitation estimates from the glacier accumulation zones and the raw/uncorrected precipitation gauge observations which are subject to significant measurements errors (Sevruk and Hamon, ; Legates, ; Legates and Willmott, ; Goodison et al, ; Chen et al, ; Wolff et al, ).…”

Similarity and Error Intercomparison of the GPM and Its Predecessor-TRMM Multisatellite Precipitation Analysis Using the Best Available Hourly Gauge Network over the Tibetan Plateau

“…The gauge densities in the Yellow River, Yangtze River and Brahmaputra basins are 2.01 and 1.34, 1.78 per ten thousand square kilometers, respectively. Moreover, a field snowfall experiment from April 2014-February 2015 at a site (99°52′54″ E, 38°16′06″ N, 2980 m) of the northeastern TP ( Figure 1) was performed by [28], and the data are used for IMERG snowfall error analysis. Details of the field site information can be found from [28].…”