A model of energy budgets over water, snow, and ice surfaces

et al. 2019

JGR Atmospheres

Self Cite

Surface heat fluxes over the central Tibetan Plateau have been estimated using the maximum entropy production (MEP) model with the surface energy balance and the observation data from the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX‐III). The MEP surface heat fluxes are highly correlated with those of the TIPEX‐III observations. The agreement between the MEP and TIPEX‐III heat fluxes is higher when the observed surface energy balance closure is better. The errors of the MEP heat fluxes are smaller compared to those of the fluxes derived from the bulk transfer method, the Land Data Assimilation Systems, and the Simple Biosphere Model version 2 reported in the previous studies. The values of MEP sensible and latent heat fluxes tend to be less than those of the previous bulk heat fluxes. Thus, the MEP model can reasonably estimate surface heat fluxes over the central Tibetan Plateau.

“…The MEP model is sensitive to B ( μ ), which is determined by the dimensionless variable

μ ((), \propto q_{s} / T_{s}^{2})

, and then Δ μ is dominated by Δ q s . As reported in Wang et al () and Huang et al (), the uncertainties of humidity (

\frac{Δ q_{s}}{q_{s}}

) and land surface temperature (

\frac{Δ T_{s}}{T_{s}}

) are about 10% and 0.3%, respectively. This indicates a larger uncertainty of humidity compared to the surface temperature.…”

Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

([], 1 + B ((), μ) + \frac{B ((), μ)}{μ} \frac{I_{italicswsi}}{I_{0}} {|italicSH|}^{- \frac{1}{6}}) italicSH = R_{net}

italicLE = B ((), μ) italicSH

G + italicSH + italicLE = R_{net}

B ((), μ) = 6 ((), \sqrt{1 + \frac{11}{36}} μ - 1), μ ((),, T_{s}, q_{s}) = \frac{{Lv}^{2} q_{s}}{C_{p} R_{V} T_{s}^{2}}

where I swsi ( =

\sqrt{ρCλ}

Section: Methodsmentioning

confidence: 99%

“…

I_{s} = \sqrt{{I_{d}}^{2} + θ {I_{w}}^{2}}

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of Surface Heat Fluxes Over the Central Tibetan Plateau using the Maximum Entropy Production Model

Zhao

et al. 2019

JGR Atmospheres

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“…The MEP model simultaneously solves turbulent sensible heat flux H , latent heat flux E , and conductive heat flux Q over the Earth‐atmosphere interface in terms of analytical functions of surface radiation fluxes, temperature and/or humidity satisfying conservation of energy at all space‐time scales. The formulation of MEP model is described in Wang and Bras () for the case of land surfaces, and in Wang et al () for the case of water‐ice‐snow surfaces. According to the MEP formalism, maximizing the entropy production function under the constraint of surface energy balance equations in equations and , we obtain the solution of H , E , and Q :

([]|, 1 + B (|, σ) + \frac{B (|, σ)}{σ} \frac{I_{s}}{I_{0}} {(|||, H)}^{- \frac{1}{6}}) H = R_{n},

E = B (|, σ) H,

Q = ({|, \begin{matrix} R_{n} - E - H normall normala normaln normald \\ R_{n}^{L} - E - H normalw normala normalt normale normalr, normali normalc normale, normala normaln normald normals normaln normalo normalw \end{matrix})

with

B (|, σ) = 6 (|, \sqrt{1 + \frac{11}{36} σ} - 1), σ = \frac{L_{v}^{2} q_{s}}{C_{p} R_{v} T_{s}^{2}} .

where

B (|, σ)

is the reciprocal Bowen ratio,

σ

a dimensionless parameter representing the relative role of surface humidity and temperature on the partition of surface net radiation into the surface heat fluxes,

…”

Section: Methodsmentioning

confidence: 90%

Hindcasting the Madden‐Julian Oscillation With a New Parameterization of Surface Heat Fluxes

Chen

Deng

et al. 2017

J Adv Model Earth Syst

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The recently developed maximum entropy production (MEP) model, an alternative parameterization of surface heat fluxes, is incorporated into the Weather Research and Forecasting (WRF) model. A pair of WRF cloud‐resolving experiments (5 km grids) using the bulk transfer model (WRF default) and the MEP model of surface heat fluxes are performed to hindcast the October Madden‐Julian oscillation (MJO) event observed during the 2011 Dynamics of the MJO (DYNAMO) field campaign. The simulated surface latent and sensible heat fluxes in the MEP and bulk transfer model runs are in general consistent with in situ observations from two research vessels. Compared to the bulk transfer model, the convection envelope is strengthened in the MEP run and shows a more coherent propagation over the Maritime Continent. The simulated precipitable water in the MEP run is in closer agreement with the observations. Precipitation in the MEP run is enhanced during the active phase of the MJO with significantly reduced regional dry and wet biases. Large‐scale ocean evaporation is stronger in the MEP run leading to stronger boundary layer moistening to the east of the convection center, which facilitates the eastward propagation of the MJO.

Land surface energy partitioning revisited: A novel approach based on single depth soil measurement

Yang

Geophysical Research Letters

2014

The partitioning of solar energy into sensible, latent, and ground heat fluxes over the land surface is responsible for changes of state variables in the soil-atmosphere system. Recent research enables the reconstruction of the land surface temperature and ground heat flux using Green's function approach, as well as the estimate of the distribution of available energy into latent and sensible heat fluxes based on linear stability analysis. Combining the Green's function approach and linear stability analysis, we propose a new physically based numerical procedure to estimate the land surface energy partitioning in this paper. The new method is capable of predicting all surface energy budgets using a single depth soil measurement; the model reliability is evaluated with comparisons to flux tower measurements. The results of this study deepen our insight into the implicit link between surface energy partition and subsurface soil dynamics and how the link can be employed to related research areas.