Spatially Distributed Surface Energy Flux Modeling

Author(s):  
Wossenu Abtew ◽  
Assefa Melesse
2021 ◽  
Author(s):  
Arindam Chakraborty ◽  
Chetankumar Jalihal ◽  
Jayaraman Srinivasan

<p>Monsoons were traditionally considered to be land-based systems. Recent definitions of monsoons based on either the seasonal reversal of winds or the local summer precipitation accounting for more than 50% of the annual precipitation suggests that monsoon domains extend over oceanic regions as well. The concept of global monsoon combines all the monsoon domains into a single entity. Modern observations show that the variations in precipitation are nearly coherent across all the individual monsoon domains on decadal timescales. Using a transient simulation of the global climate over the last 22,000 years as well as reanalysis data of the modern climate, we have shown that tropical precipitation has different characteristics over land and ocean grids. This is due to the differences in the energetics of monsoon over land and ocean grids. With a lower thermal heat capacity, the net surface energy flux over land is negligible, whereas it is quite large over the ocean. In fact, the orbital scale variability of net energy flux into the atmosphere over the ocean is controlled by the surface energy flux. Another major difference between land and ocean grids of the global monsoon is in the vertical profile of the vertical pressure velocity. It is bottom-heavy over land and top-heavy over the ocean. This results in smaller vertical transport of moist static energy (which has a minimum in the lower troposphere) over land, and a larger vertical transport over the ocean. These differences between the land and ocean, suggest that the land and ocean grids should not be combined as is traditionally done. Global monsoon-land and global monsoon-ocean should be studied separately.</p>


2017 ◽  
Vol 122 (12) ◽  
pp. 6250-6272 ◽  
Author(s):  
Chunlei Liu ◽  
Richard P. Allan ◽  
Michael Mayer ◽  
Patrick Hyder ◽  
Norman G. Loeb ◽  
...  

2005 ◽  
Vol 6 (6) ◽  
pp. 941-953 ◽  
Author(s):  
Wade T. Crow ◽  
Fuqin Li ◽  
William P. Kustas

Abstract The treatment of aerodynamic surface temperature in soil–vegetation–atmosphere transfer (SVAT) models can be used to classify approaches into two broad categories. The first category contains models utilizing remote sensing (RS) observations of surface radiometric temperature to estimate aerodynamic surface temperature and solve the terrestrial energy balance. The second category contains combined water and energy balance (WEB) approaches that simultaneously solve for surface temperature and energy fluxes based on observations of incoming radiation, precipitation, and micrometeorological variables. To date, few studies have focused on cross comparing model predictions from each category. Land surface and remote sensing datasets collected during the 2002 Soil Moisture–Atmosphere Coupling Experiment (SMACEX) provide an opportunity to evaluate and intercompare spatially distributed surface energy balance models. Intercomparison results presented here focus on the ability of a WEB-SVAT approach [the TOPmodel-based Land–Atmosphere Transfer Scheme (TOPLATS)] and an RS-SVAT approach [the Two-Source Energy Balance (TSEB) model] to accurately predict patterns of turbulent energy fluxes observed during SMACEX. During the experiment, TOPLATS and TSEB latent heat flux predictions match flux tower observations with root-mean-square (rms) accuracies of 67 and 63 W m−2, respectively. TSEB predictions of sensible heat flux are significantly more accurate with an rms accuracy of 22 versus 46 W m−2 for TOPLATS. The intercomparison of flux predictions from each model suggests that modeling errors for each approach are sufficiently independent and that opportunities exist for improving the performance of both models via data assimilation and model calibration techniques that integrate RS- and WEB-SVAT energy flux predictions.


2014 ◽  
Vol 13 (4) ◽  
pp. 405-424 ◽  
Author(s):  
Daniele Masseroni ◽  
Arianna Facchi ◽  
Marco Romani ◽  
Enrico Antonio Chiaradia ◽  
Olfa Gharsallah ◽  
...  

2021 ◽  
Vol 40 (10) ◽  
pp. 84-96
Author(s):  
Jialiang Zhu ◽  
Yilin Liu ◽  
Xiaoyu Wang ◽  
Tao Li

2013 ◽  
Vol 136 ◽  
pp. 234-246 ◽  
Author(s):  
L. Morillas ◽  
M. García ◽  
H. Nieto ◽  
L. Villagarcia ◽  
I. Sandholt ◽  
...  

Energies ◽  
2014 ◽  
Vol 7 (3) ◽  
pp. 1770-1791 ◽  
Author(s):  
Jason Hubbart ◽  
Elliott Kellner ◽  
Lynne Hooper ◽  
Anthony Lupo ◽  
Patrick Market ◽  
...  

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