Gridded Snow Water Equivalent Reconstruction for Utah Using Forest Inventory and Analysis Tree-Ring Data

被引:6
|
作者
Barandiaran, Daniel [1 ,2 ]
Wang, S. -Y. Simon [1 ,2 ]
DeRose, R. Justin [3 ]
机构
[1] Utah State Univ, Dept Plants Soils & Climate, 4820 Old Main Hill, Logan, UT 84322 USA
[2] Utah State Univ, Utah Climate Ctr, 4820 Old Main Hill, Logan, UT 84322 USA
[3] US Forest Serv, USDA, Forest Inventory & Anal, Rocky Mt Res Stn, 507 25th St, Ogden, UT 84401 USA
来源
WATER | 2017年 / 9卷 / 06期
关键词
climate variability; dendrochronology; Forest Inventory and Analysis; paleohydrology; snow water equivalent; tree rings; water resource management; GREAT-SALT-LAKE; QUASI-DECADAL OSCILLATION; WESTERN NORTH-AMERICA; US INTERMOUNTAIN WEST; RIVER-BASIN; STREAMFLOW RECONSTRUCTION; UNITED-STATES; PRECIPITATION; CLIMATE; TELECONNECTION;
D O I
10.3390/w9060403
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Snowpack observations in the Intermountain West are sparse and short, making them difficult for use in depicting past variability and extremes. This study presents a reconstruction of April 1 snow water equivalent (SWE) for the period of 1850-1989 using increment cores collected by the U.S. Forest Service, Interior West Forest Inventory and Analysis program (FIA). In the state of Utah, SWE was reconstructed for 38 snow course locations using a combination of standardized tree-ring indices derived from both FIA increment cores and publicly available tree-ring chronologies. These individual reconstructions were then interpolated to a 4-km grid using an objective analysis with elevation correction to create an SWE product. The results showed a significant correlation with observed SWE as well as good correspondence to regional tree-ring-based drought reconstructions. Diagnostic analysis showed statewide coherent climate variability on inter-annual and inter-decadal time-scales, with added geographical details that would not be possible using courser pre-instrumental proxy datasets. This SWE reconstruction provides water resource managers and forecasters with better spatial resolution to examine past variability in snowpack, which will be important as future hydroclimatic variability is amplified by climate change.
引用
收藏
页数:13
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