MODEL FOR SPATIAL EXTRAPOLATION OF STOMATAL CONDUCTANCE ON A YOUNG DRIP-IRRIGATED 'ARBEQUINA' OLIVE ORCHARD UNDER SEMI-ARID CONDITION

2014 ◽  
pp. 357-362
Author(s):  
C. Acevedo-Opazo ◽  
R. López-Olivari ◽  
F. Jara-Rojas ◽  
H. Valdés-Gómez ◽  
Q. Figueri ◽  
...  
2015 ◽  
Vol 33 (3) ◽  
pp. 43-48 ◽  
Author(s):  
Héctor Valdés-Gómez ◽  
Guajardo ◽  
Francisco Jara-Rojas ◽  
César Acevedo-Opazo ◽  
James A Taylor

2020 ◽  
Author(s):  
Arindam Malakar ◽  
Michael Kaiser ◽  
Daniel D. Snow ◽  
Harkamal Walia ◽  
Chittaranjan Ray

2021 ◽  
Author(s):  
Sean M. Gleason ◽  
Lauren Nalezny ◽  
Cameron Hunter ◽  
Robert Bensen ◽  
Satya Chintamanani ◽  
...  

2019 ◽  
Vol 50 (20) ◽  
pp. 2534-2543 ◽  
Author(s):  
Somayeh Jan Ahmadi ◽  
Forough Mortazaeinezhad ◽  
Hossein Zeinali ◽  
Omid Askari-Khorasgani ◽  
Mohammad Pessarakli

2015 ◽  
Vol 8 (12) ◽  
pp. 10339-10363 ◽  
Author(s):  
D. L. Lombardozzi ◽  
M. J. B. Zeppel ◽  
R. A. Fisher ◽  
A. Tawfik

Abstract. The terrestrial biosphere regulates climate through carbon, water, and energy exchanges with the atmosphere. Land surface models estimate plant transpiration, which is actively regulated by stomatal pores, and provide projections essential for understanding Earth's carbon and water resources. Empirical evidence from 204 species suggests that significant amounts of water are lost through leaves at night, though land surface models typically reduce stomatal conductance to nearly zero at night. Here, we apply observed nighttime stomatal conductance values to a global land surface model, to better constrain carbon and water budgets. We find that our modifications increase transpiration up to 5 % globally, reduce modeled available soil moisture by up to 50 % in semi-arid regions, and increase the importance of the land surface on modulating energy fluxes. Carbon gain declines up to ~ 4 % globally and > 25 % in semi-arid regions. We advocate for realistic constraints of minimum stomatal conductance in future climate simulations, and widespread field observations to improve parameterizations.


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