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Ecosystem biophysical memory in the southwestern North America climate system
被引:11
|作者:
Forzieri, G.
[1
]
Vivoni, E. R.
[2
,3
]
Feyen, L.
[1
]
机构:
[1] European Commiss, Joint Res Ctr, Inst Environm & Sustainabil, Climate Risk Management Unit, I-21027 Ispra, VA, Italy
[2] Arizona State Univ, Sch Earth & Space Explorat, Tempe, AZ 85287 USA
[3] Arizona State Univ, Sch Sustainable Engn & Built Environm, Tempe, AZ 85287 USA
来源:
关键词:
vegetation phenology;
El Nino-Southern oscillation;
precipitation;
temperature;
North American monsoon;
Mexico;
WARM-SEASON PRECIPITATION;
INTERANNUAL VARIABILITY;
SURFACE TEMPERATURES;
NORTHWESTERN MEXICO;
VEGETATION DYNAMICS;
SOIL-MOISTURE;
TREE GROWTH;
MONSOON;
SATELLITE;
PATTERNS;
D O I:
10.1088/1748-9326/8/4/044016
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
To elucidate the potential role of vegetation to act as a memory source in the southwestern North America climate system, we explore correlation structures of remotely sensed vegetation dynamics with precipitation, temperature and teleconnection indices over 1982-2006 for six ecoregions. We found that lagged correlations between vegetation dynamics and climate variables are modulated by the dominance of monsoonal or Mediterranean regimes and ecosystem-specific physiological processes. Subtropical and tropical ecosystems exhibit a one month lag positive correlation with precipitation, a zero-to one-month lag negative correlation with temperature, and modest negative effects of sea surface temperature (SST). Mountain forests have a zero month lag negative correlation with precipitation, a zero-one month lag negative correlation with temperature, and no significant correlation with SSTs. Deserts show a strong one-four month lag positive correlation with precipitation, a low zero-two month lag negative correlation with temperature, and a high four-eight month lag positive correlation with SSTs. The ecoregion-specific biophysical memories identified offer an opportunity to improve the predictability of land-atmosphere interactions and vegetation feedbacks onto climate.
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