Landscape air temperature thresholds (TA) and percent misclassified precipitation (error) for 12 years of meteorological observations from 40 stations across the Scandinavian Peninsula were derived and compared using both manual and geographic information system (GIS) landscape classification methods. Dew-point, wet-bulb, and wet bulb 0.5 were also tested. Both classification methods used the following west to east landscape categories: windward (WW) ocean, coast, fjord, hill, and mountain in Norway; and leeward (LW) mountain, hill, rolling terrain, and coast in Sweden. GIS landscape classification has the advantages of automating the classification process and increasing objectivity. The GIS classification was based on station location (LW or WW) relative to the Scandinavian mountain range, and the % water or range of elevation change within 15 km. The GIS and manual method had the same TA for 20 stations, and similar total reduction in error (2.29 to 2.17% respectively) when compared to country TA. Therefore, automated GIS landscape classification can be used to decrease error from common country or global scale TA. Wet-bulb temperature thresholds for GIS landscapes resulted in a greater reduction in error (8.26%) compared to air (2.29%), and dew-point (−16.67%) thresholds. However, finding stations reporting relative humidity or wet-bulb temperature may limit its widespread use.
A new GIS landscape classification method for rain/snow temperature thresholds in surface based models
James M. Feiccabrino, Laurie D. Grigg; A new GIS landscape classification method for rain/snow temperature thresholds in surface based models. Hydrology Research 1 August 2017; 48 (4): 902–914. doi: https://doi.org/10.2166/nh.2016.055
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