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  3. Forestry and Resource Conservation / 森林環境暨資源學系
  4. Interannual Variations in Spring Snowmelt Timing of Alaskan Black Spruce Forests Using a Bulk‐Surface Energy Balance Approach
 
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Interannual Variations in Spring Snowmelt Timing of Alaskan Black Spruce Forests Using a Bulk‐Surface Energy Balance Approach

Journal
Water Resources Research
Journal Volume
60
Journal Issue
5
ISSN
0043-1397
1944-7973
Date Issued
2024-05
Author(s)
Hiroki Ikawa
TARO NAKAI  
Robert C. Busey
Yoshinobu Harazono
Kyoko Ikeda
Hiroki Iwata
Hirohiko Nagano
Kazuyuki Saito
Masahito Ueyama
Hideki Kobayashi
DOI
10.1029/2023wr035984
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/719422
Abstract
AbstractSpring snowmelt occurs for a short duration on an annual time scale, but their timings considerably affect the carbon and hydrological cycle in high‐latitude ecosystems. Here, we developed a simple snowmelt model, treating the ecosystem surface as a bulk‐surface layer. Energy fluxes across this bulk surface and the snow‐soil boundary determine snow temperature and the energy utilized for snowmelt. Parameterizing the bulk surface using decade‐long eddy covariance site data from two Alaskan open black spruce forests offered an opportunity to quantitatively evaluate meteorological drivers affecting snowmelt timings without the needs for detailed canopy information. The sensitivity analysis suggested that the total snowfall on the forest floor, ranging from 0.35 m in 2016 to about 1 m in 2018 and 2020, was the most crucial driver for snowmelt timing. This factor accounted for a 10‐day difference in the interannual variations in snow disappearance dates. The importance of the snowfall varied from year to year, and in 2013, the late snowmelt was characterized by low air temperatures, which increased sensible heat loss from the snowpack. The importance of atmospheric radiation was revealed in relatively warm years, such as 2016 and 2019. Our modeling approach necessitates adjusting one empirical parameter that reflects the heat conductivity from the bulk surface to the snow, based on observations. Nevertheless, despite this need for adjustment, the bulk‐surface approach helps identify important meteorological drivers underlying observed snowmelt within a simple theoretical framework.
SDGs

[SDGs]SDG15

Publisher
American Geophysical Union (AGU)
Type
journal article

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