Leaf onset in the northern hemisphere triggered by daytime temperature
Shilong Piao,Jianguang Tan,Anping Chen,Yongshuo H. Fu,Philippe Ciais,Qiang Liu,Ivan A. Janssens,Sara Vicca,Zhenzhong Zeng,Su-Jong Jeong,Yue Li,Ranga B. Myneni,Shushi Peng,Miaogen Shen,Josep Peñuelas +14 more
TLDR
This work shows that the interannual anomalies of LUD during 1982–2011 are triggered by daytime (Tmax) more than by nighttime temperature (Tmin), and suggests a new conceptual framework of leaf onset using daytime temperature to improve the performance of phenology modules in current Earth system models.Abstract:
Recent warming significantly advanced leaf onset in the northern hemisphere. This signal cannot be accurately reproduced by current models parameterized by daily mean temperature (Tmean). Here using in situ observations of leaf unfolding dates (LUDs) in Europe and the United States, we show that the interannual anomalies of LUD during 1982–2011 are triggered by daytime (Tmax) more than by nighttime temperature (Tmin). Furthermore, an increase of 1 Ci nTmax would advance LUD by 4.7 days in Europe and 4.3 days in the United States, more than the conventional temperature sensitivity estimated from Tmean. The triggering role of Tmax, rather than the Tmin or Tmean variable, is also supported by analysis of the large-scale patterns of satellite-derived vegetation green-up in spring in the northern hemisphere (430N). Our results suggest a new conceptual framework of leaf onset using daytime temperature to improve the performance of phenology modules in current Earth systemread more
Citations
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Understanding the continuous phenological development at daily time step with a Bayesian hierarchical space-time model: impacts of climate change and extreme weather events
Tong Qiu,Tong Qiu,Conghe Song,James S. Clark,Bijan Seyednasrollah,Nuvan Rathnayaka,Junxiang Li +6 more
TL;DR: In this paper, a Bayesian Hierarchical Space-Time model for Land Surface Phenology (BHST-LSP) was developed to synthesize remotely sensed vegetation greenness with climate covariates at a daily temporal scale from 1981 to 2014 across the entire conterminous United States.
Journal ArticleDOI
A new algorithm for the estimation of leaf unfolding date using MODIS data over China’s terrestrial ecosystems
TL;DR: Wang et al. as mentioned in this paper proposed an improved LUD modeling algorithm by developing a temperature-based scale factor to adjust the traditional VI-based (i.e., two band enhanced vegetation index (EVI2)) LUD estimates.
Journal ArticleDOI
Effect of preseason diurnal temperature range on the start of vegetation growing season in the Northern Hemisphere
TL;DR: In this paper, the authors analyzed the interannual covariation of preseason diurnal temperature range (DTR) with the start of the growing season (SOS) in temperate and boreal areas.
References
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