Snow Disappearance Date Research Articles

Spatial snowfall distribution in mountainous areas estimated with a snow model and satellite remote sensing

We describe an approach for reconstructing snowfall that combines satellite observations of the snow disappearance date (SDD) with a snow model for two mountainous areas in Japan having distinct snow climatology. This approach allows assessment of the distribution of snow and topographical effects on snowfall within a catchment. We also evaluated how the reconstructed snowfall affects the catchment snow hydrology. Validation at observation sites demonstrated that a combination of the snow model and snowfall reconstructions successfully estimated the seasonal changes of snow water equivalent (SWE). In Japan, the dependence of snowfall on elevation is stronger in mountainous areas along the coast on the Sea of Japan side of Japan’s central mountain spine (where snowfall triples with every 1000 m increase in elevation; Csf = 0.002 m−1) compared with inland locations of the same region (where snowfall doubles with every 1000 m increase; Csf = 0.001 m−1). Moreover, the reconstructed snowfall improved the estimation of maximum catchment SWE. Maximum total SWE, estimated with reconstructed snowfall, was 3.8 × 108 m3 in Kurobe catchment (along the coast on the Sea of Japan side of Japan’s central mountain spine), while that, estimated by convectional method with the spatially-constant Csf = 0.001 m−1, was 2.0 × 108 m3. As a result, estimations of the snow disappearance date and of the catchment snowmelt were also improved. These results suggest that it is useful to estimate the spatial snow distribution, especially where steep topography causes large gradients of snowfall amount with respect to elevation.

The date of snow disappearance on the Arctic tundra as determined from satellite, meteorological station and radiometric in situ observations

Satellite-derived snow cover maps for sites in Alaska, Canada, Scandinavia and Siberia were employed to assess the date when snow disappeared on the Arctic tundra and to determine whether the snow has been melting earlier in the spring in recent years. Results show that for three of the four sites there has been a tendency toward earlier snowmelt during the 1980s. In Alaska, the satellite-derived date of snowmelt was compared to the date of snowmelt as observed at the Barrow meteorological station and a site near Barrow where radiometric in situ measurements were made for the last 5 years. The three data sources complement each other even though the satellite site is located 150 km from Barrow. One mechanism which could cause a trend toward earlier snowmelt in Alaska is the deposition of soot and particulates on the snow surface as a result of Arctic haze. >

ランドサットＴＭデータによる立山付近の林相分類とその分布に及ぼす気温と消雪時期の影響

It is the purpose of this paper to clarify relationship between forest distribution and its controlling factors such as cumulative air-temperature (degree-day), landform characteristics and snow-cover duration using remote sensing images, DEM (Digital Elevation Model) and climatological data. The outline of procedure of investigation will be described below.The spring, summer and autumn LANDSAT TM/MSS images were used to analyze seasonal change of vegetation and snow-cover. At first all images were converted into images resampled on a 56/58 m grid of DEM by using the nearest neighborhood method. Then the image data were processed in order to eliminate shadows caused only by azimuth and dip of each grid of DEM and direction of sunbeam. This processing is useful to improve the accuracy of landcover classification for a high relief mountainous region like this study area, the northernmost part of the Hida Range, Central Japan. Finally five categories ; dwarf pine, evergreen coniferous forests, deciduous broad-leaved forests, alpine meadow, bare grounds were interpreted, and a digital map of the estimated date of snow disappearance was obtained from the multi-temporal images.Air-temperature for each pixel of the DEM was calculated using daily surface air-temperature at a local AMeDAS station (Automated Meteorological Data Acquisition System) and daily lapse rate in free air at the nearest aeorological observatory. The estimated values were tested comparing the values observed at temporal observatories of mountain huts during summer season. The cumulative air-temperature is defined as an integrated excess of 5°C of daily air temperature, and it is widely admitted that it controls primarily the distribution of forest plants in rainy Japanese Islands. The other controlling factors such as snow-cover duration and slope azimuth and dip were discussed statistically.In conclusion ;(1) Dwarf pine (Pinus pumila) is distributed in gentle and westward slopes of ridge zones with the maximum occupation ratio at ca. 2, 500 m. This is replaced by alpine meadows or bare grounds in and around snow patches durable to late spring or summer.(2) Evergreen coniferous (Abies mariestii, A. veitchii, Tsuga diversifolia and Picea jesoensis var. hondoensis) forests are distributed with the maximum occupation ratio at ca. 2, 000 m. The coniferous forests will prefer a habitat which is West- to North-facing slope with inclination of less than 25. In the higher zone than 2, 000 m, these forests compete with dwarf pine or birch (Betula ermanii) forsts for occupation according to controlling factors. The coniferous plants are seemed to be snow-intolerant and easily damaged by a loss of the cumulative air-temperature due to snow-cover duration, and by mechanical and physiological injury by snow-cover itself.(3) Deciduous broad-leaved (Fagus crenata, Quercus mongolica var. crispula, Betula ermanii etc.) forests are widely distributed in this area. The Occupation ratio curve has bi-modal peaks at 2, 300 m and 1, 500 m. The lower one indicates the normal altitudinal distribution of forest zone according to thermal condition. The higher one is introduced by occupation of Betula ermanii in alpine-subalpine transitional zone. Betula ermanii is snow-tolerant and distributed in mountain slopes of all directions with the maximum frequency in South to East. The east-facing slope is leeward of the winter snow-bearing winds, but receives much snow accumulation by the blowing effect. Betula ermanii will occupay a habitat unfavorable for the coniferous mainly because of much snow accumulation.

The Significance of the Date of Snow Disappearance on the Arctic Tundra as a Possible Indicator of Climate Change

Variations in the length of the snow-cover season affect the albedo which in turn impacts the energy balance; thus, it is important to have a data set concerned with the spatial and the temporal character of snow. Data on the date when the arctic snow cover disappears in the spring is presented and analyzed for 12 stations between 68 and 74?N latitude. For a few of the stations, data are available for over 50 yr; however, Soviet data are available only from the late 1930s until the mid 1950s, and Canadian data have only been recorded since the late 1950s. Results show that for much of the North American arctic tundra the date of snow disappearance has been occurring earlier in the spring since the late 1960s. For Barrow, Alaska, there has been a trend towards earlier snowmelt since about 1950. It is not yet apparent as to whether this trend can be attributed to increases in carbon dioxide and soot in the arctic environment or whether a particular circulation regime, such as a shift in the location of the polar vortex, may be responsible. But because the Arctic is where anthropogenic atmospheric pollution is expected to have the largest impact on climate, and in view of anticipated increased future emissions of carbon dioxide and soot, a more complete and lengthy snow-cover data set may provide an early indication of the onset of the predicted warming of the polar climate.

The Significance of the Date of Snow Disappearance on the Arctic Tundra as a Possible Indicator of Climate Change

The Significance of the Date of Snow Disappearance on the Arctic Tundra as a Possible Indicator of Climate Change