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1. 12/21/2015 Real­time simulation of the iterative calculation of the satellite based surface energy fluxes | Ramesh Dhungel | LinkedIn
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Real­time simulation of the iterative calculation of
the satellite based surface energy fluxes
Dec 21, 2015 7 views 0 Likes 0 Comments   
This will be a continuing post which will be updated until most of the
real time simulations are shown.
White paper
An iterative procedure is still used to converge fluxes in evapotranspiration (ET)
calculation in many ET models like METRIC, SEBAL and SEBS. In this post, a
real­time simulation is shown to expedite the satellite based surface energy
balance fluxes in low wind speed condition. In the surface energy balance,
stability correction of aerodynamic resistance is necessary as it affects the
computation of sensible heat flux. The Monin­Obukhov stability length (L) can be
calculated either from an iterative process using wind profiles, temperature and
Ramesh Dhungel
Water Resources, Remote Sensing and Land
Surface Modeler (LSM) (Ph.D. Civil Engineering)
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Real­time simulation of the
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2. 12/21/2015 Real­time simulation of the iterative calculation of the satellite based surface energy fluxes | Ramesh Dhungel | LinkedIn
https://www.linkedin.com/pulse/real­time­simulation­iterative­calculation­satellite­based­dhungel 2/27
humidity or through more complicated measurements of wind speed, sensible
heat flux, and latent heat flux. The Monin­Obukhov similarity functions are used
to define momentum (ψ) and heat (ψ) stability correction. While computing
Monin­Obukhov similarity functions, a set of the equations must be solved
iteratively as friction velocity (u*) and L (Monin­Obukhov length) are
interdependent. These variables should be revised until the parameters of the
surface energy balance converge within prescribed limits between successive
iterations.
Some technical details:
Improved Methodology ( Dhungel et al., 2014)
Programming language: Python and ArcScript
Plot: matplotlib
Date of the satellite overpass: 05/17/2008 (Landsat 5)

3. 12/21/2015 Real­time simulation of the iterative calculation of the satellite based surface energy fluxes | Ramesh Dhungel | LinkedIn
https://www.linkedin.com/pulse/real­time­simulation­iterative­calculation­satellite­based­dhungel 3/27
Weather data­ NARR (32 km resolution)
Area: Southern Idaho near Raft River
Number of pixels: 1455408
Area: 1300 km2
Convergence criteria: Convergence of aerodynamic resistance within + 1
second / meter
System properties: Intel ® Core (TM) i7­4790 CPU @ 3.6 GHz
Installed memory (RAM): 32 GB
System type: 64­bit Operating System
Recording software: eLecta Live Screen Recorder
Plotting example:
T_cells= Total cells
C_cells= Converged cells
N_cells= Non­converged cells
T_cells = C_cells + N_cells
P_Convg = float(C_cells)/T_cells * 100.0000
N = 50
y= P_Convg
colors = np.random.rand(N)
s = 8 * iteration ** 1.2
plt.scatter(iteration, y,s,c=colors,alpha=0.5,marker=(5, 3),zorder=2)
plt.hold(True)
stop=time.time()

4. 12/21/2015 Real­time simulation of the iterative calculation of the satellite based surface energy fluxes | Ramesh Dhungel | LinkedIn
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test=(stop ­ start) / 60
test1=("%.2f" % test)
plt.title('Improved Methodology ­ Minutes=%s' % test1, fontsize=18)
Increased dots means increased % of convergence:
Wind speed at set 0.8 m/s (minimal value) to understand the extreme behavior.
(97.5 % convergence of pixels at 0.8 m/s wind speed at 30 m, process
manually stopped at about 70 minutes)

5. 12/21/2015 Real­time simulation of the iterative calculation of the satellite based surface energy fluxes | Ramesh Dhungel | LinkedIn
https://www.linkedin.com/pulse/real­time­simulation­iterative­calculation­satellite­based­dhungel 5/27
Real-time simulation of the surface en...
(99.5 % convergence of pixels at 0.8 m/s wind speed at 30 m, process
automatically stopped at about 13 minutes)

6. 12/21/2015 Real­time simulation of the iterative calculation of the satellite based surface energy fluxes | Ramesh Dhungel | LinkedIn
https://www.linkedin.com/pulse/real­time­simulation­iterative­calculation­satellite­based­dhungel 6/27
Written by
Ramesh Dhungel
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Real-time simulation of the surface en...
For the further reading, references and to cite the work, please go to
the following literature.
Dhungel, Ramesh, Richard G. Allen, Ricardo Trezza, and Clarence W. Robison.
"Comparison of Latent Heat Flux Using Aerodynamic Methods and Using the
Penman–Monteith Method with Satellite­Based Surface Energy
Balance." Remote Sensing 6, no. 9 (2014): 8844­8877.
Dhungel, R.; Allen, R. Time Integration of Evapotranspiration Using a Two
Source Surface Energy Balance Model Using NARR Reanalysis Weather and
Satellite Based METRIC Data. Ph.D. Thesis, University of Idaho, Kimberly, ID,
USA, 2014
http://digital.lib.uidaho.edu/cdm/ref/collection/etd/id/829
Dhungel et al., 2015. Improving iterative surface energy balance convergence for
satellite­based flux calculation, 15804L. Journal of Applied Remote Sensing
(Under­review).
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