Air mass boundary identification : improvement of precipitation phase determination in surface based modeling

Sammanfattning: Snowpack properties derived from hydrological models play an important role for many ecological, water resource, and climate applications; such as winter survival of plants, reindeer, small mammals and birds, avalanche hazards, glaciers and polar ice accumulation, growth of sea and lake ices, climate change, snow melt flooding etc. These hydrological models need accurate precipitation phase discrimination schemes to closely portray e. g. energy balance for melt and refreeze cycles, water lost to sublimation, and snow water equivalent within a watershed for the above applications. Precipitation phase is seldom reported from automated surface meteorological stations, so most hydrological models apply an empirical formula based on surface air temperature. There are many different empirical formulas used for precipitation type determination in hydrological models. The most commonly used formulas have one or two fixed air temperatures to separate rain from snow, however, some use more elaborate algorithms. The first part of this study consists of a comparison of common precipitation phase determination schemes to a database of 45 years of three-hour man-made weather observations for nineteen Swedish meteorological stations. These observations consist of surface air and dew point temperatures, precipitation mass and phase (classified as snow, rain, or mixed precipitation). Model schemes using two air temperature thresholds, one threshold all snow (TS) and one all rain (TR) having a linear snow fraction decrease between the thresholds (TS = 0.0˚C; TR = 2.0˚C, or TS = -1.0; TR = 3.0˚C) performed better than using a single rain/snow temperature threshold at all but two of 19 stations. A fitted air temperature dependent snow probability polynomial scheme resulted in similar, but slightly improved classification than a linear decreasing snow fraction approach at 13 of 19 locations. However, using the same empirical formula for all surface weather observations is a flawed technique since surface precipitation phase results from energy exchanges between falling precipitation and air in the lower atmosphere. Different lower atmospheric conditions cause dissimilar precipitation phase probabilities for near-freezing temperatures. Directly measured lower atmospheric conditions are seldom available for remote areas. However, meteorological observations occurring before/after similar air mass boundaries can be assumed to have alike atmospheric conditions which vary from most other observations. Therefore, hydrological models can indirectly account for lower atmospheric conditions. The second part of this study used twenty years of manual observations from eight U.S. weather stations to compare misclassified precipitation proportions when analyzing (a) all precipitation observations together and (b) identified cold air mass boundary observations (CAB) and non-CAB observations separately. The CAB observations were identified by a rapid surface air temperature decrease. Applying a linear decrease in snow fraction method, CAB had a TS (0˚C), and TR (4˚C) 1˚C warmer than non-CAB (-1˚C, 3˚C). Analyzing CAB and non-CAB separately reduced misclassified precipitation by 23%, from 7.0 to 5.4%.