Discrimination of Solid from Liquid Precipitation over Northern Eurasia Using Surface Atmospheric Conditions*

Abstract

Daily synoptic observations were examined to determine the critical air temperatures and dewpoints that separate solid versus liquid precipitation for the fall and spring seasons at 547 stations over northern Eurasia. The authors found that critical air temperatures are highly geographically dependent, ranging from 21.08 to 2.58C, with the majority of stations over European Russia ranging from 0.58 to 1.08C and those over southcentral Siberia ranging from 1.58 to 2.58C. The fall season has a 0.58-1.08C lower value than the spring season at 42% stations. Relative humidity, elevation, the station's air pressure, and climate regime were found to have varying degrees of influences on the distribution of critical air temperature, although the relationships are very complex and cannot be formulated into a simple rule that can be applied universally. Although the critical dewpoint temperatures have a spread of 21.58 to 1.58C, 92% of stations have critical values of 0.58-1.08C. The critical dewpoint is less dependent on environmental factors and seasons. A combination of three critical dewpoints and three air temperatures is developed for each station for spring and fall separately that has improved snow event predictability when the dewpoint is in the range of 20.58-1.58C and has improved rainfall event predictability when the dewpoint is higher than or equal to 08C based on the statistics of all 537 stations. Results suggest that application of site-specific critical values of air temperature and dewpoint to discriminate between solid and liquid precipitation is needed to improve snow and hydrological modeling at local and regional scales.

Meteorological Knowledge Useful for the Improvement of Snow Rain Separation in Surface Based Models

“…Feiccabrino et al [21] and Ye et al [1] compare measured (visual observation) and modeled precipitation phase, while many studies e.g., Wen et al [2] compare modeled and measured snow depths. For the latter type, the representation of (a) wind correction of gauge catch; (b) spatial resolution of the watershed; (c) lapse rate; and (d) snow melt etc.…”

“…TA methods do not include humidity, the second-most significant factor in determining precipitation type [27,29,33]. Some researchers have found TD [20], TW [27], and a combination of RH and TA [1] to be better predictors of the precipitation phase. However, the assumption that surface humidity is fully representative of the atmospheric humidity is incorrect.…”

“…The hydrological, ecological, and atmospheric responses to rain are extremely different from snow responses [1] and correct precipitation phase is, therefore, very important for applications across many scientific fields. Truthful identification of the precipitation phase (rain/snow) is of course crucial for the functioning of meteorological models that forecast the precipitation phase itself [2] but also for accurate correction of gauge measured winter precipitation [3] and for land surface models (LSM) predicting snow accumulation and melt [4], glacier and polar ice water balance models [5], models for lake and sea ice growth [6], and climate change models [7].…”

“…Unfortunately, TA methods are not physically based as they do not attempt to incorporate physical processes present in the real world e.g., the effects of humidity on latent heat transfer [25] and other hydrometeor processes above the soil surface [26]. There are a few hydrological models that attempt to account for moisture in the surface-based PPDS by using surface dew point temperature (TD) [20], surface wet bulb temperature (TW) [27], and surface relative humidity (RH) [1].…”

“…The phase of precipitation at the ground can be univocally determined only by knowing the initial hydrometeor phase [29], hydrometeor shape and size [26], and the properties of the atmosphere through which the hydrometeor falls. These properties include above ground air temperatures (TAG), height of the 0 °C isotherm (Z0 °C) [17], vertical thickness of freezing and melting layers [26], atmospheric humidity [1], atmospheric stability [30], and interactions between hydrometeors [2,25,29,31].…”