Analysis of Water Vapor Fluxes Over a Seasonal Snowpack Using the Maximum Entropy Production Model

2021 ◽  
Vol 126 (1) ◽  
Author(s):  
Islem Hajji ◽  
Daniel F. Nadeau ◽  
Biljana Music ◽  
François Anctil ◽  
Jingfeng Wang
Keyword(s):  
Water Vapor ◽  
Entropy Production ◽  
Maximum Entropy ◽  
Production Model ◽  
Maximum Entropy Production

scholarly journals A Maximum Entropy Production Evaporation – Transpiration Product for Australia

2019 ◽  
Author(s):  
Olanrewaju Abiodun ◽  
Okke Batelaan ◽  
Huade Guan ◽  
Jingfeng Wang
Keyword(s):  
Entropy Production ◽  
Maximum Entropy ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Production Model ◽  
Model Parameters ◽  
Drought Period ◽  
Maximum Entropy Production ◽  
Millennium Drought ◽  
Mean Square Errors

Abstract. The aim of this research is to develop evaporation and transpiration products for Australia based on the maximum entropy production model (MEP). We introduce a method into the MEP algorithm of estimating the required model parameters over the entire Australia through the use of pedotransfer function, soil properties and remotely sensed soil moisture data. Our algorithm calculates the evaporation and transpiration over Australia on daily timescales at the 5 km2 resolution for 2003–2013. The MEP evapotranspiration (ET) estimates are validated using observed ET data from 20 Eddy Covariance (EC) flux towers across 8 land cover types in Australia. We also compare the MEP ET at the EC flux towers with two other ET products over Australia; MOD16 and AWRA-L products. The MEP model outperforms the MOD16 and AWRA-L across the 20 EC flux sites, with average root mean square errors (RMSE), 8.21, 9.87 and 9.22 mm/8 days respectively. The average mean absolute error (MAE) for the MEP, MOD16 and AWRA-L are 6.21, 7.29 and 6.52 mm/8 days, the average correlations are 0.64, 0.57 and 0.61, respectively. The percentage Bias of the MEP ET was within 20 % of the observed ET at 12 of the 20 EC flux sites while the MOD16 and AWRA-L ET were within 20 % of the observed ET at 4 and 10 sites respectively. Our analysis shows that evaporation and transpiration contribute 38 % and 62 %, respectively, to the total ET across the study period which includes a significant part of the “millennium drought” period (2003–2009) in Australia. The data (Abiodun et al., 2019) is available at https://doi.org/10.25901/5ce795d313db8.

scholarly journals Application of the Maximum Entropy Production Model of Evapotranspiration over Partially Vegetated Water-Limited Land Surfaces

2018 ◽  
Vol 19 (6) ◽  
pp. 989-1005 ◽  
Author(s):  
Islem Hajji ◽  
Daniel F. Nadeau ◽  
Biljana Music ◽  
François Anctil ◽  
Jingfeng Wang
Keyword(s):  
Water Stress ◽  
Entropy Production ◽  
Maximum Entropy ◽  
Land Surface ◽  
Soil Evaporation ◽  
Stress Conditions ◽  
Production Model ◽  
Weighting Coefficient ◽  
Maximum Entropy Production ◽  
Land Surfaces

Abstract The maximum entropy production (MEP) model based on nonequilibrium thermodynamics and the theory of Bayesian probabilities was recently developed to model land surface fluxes, including soil evaporation and vegetation transpiration. This model requires few input data and ensures the closure of the surface energy balance. This study aims to test the capability of such a model to realistically simulate evapotranspiration (ET) over a wide range of climates and vegetation covers. A weighting coefficient is introduced to calculate total ET from soil evaporation and vegetation transpiration over partially vegetated land surfaces, resulting in the MEP-ET model. Using this coefficient, the model outputs are compared with in situ observations of ET at eight FLUXNET sites across the continental United States. Results confirm the close agreement between the MEP-ET predicted daily ET and the corresponding observations at sites characterized by moderately limited water availability. Poor ET results were obtained under high water stress conditions. A regulation parameter was therefore introduced in the MEP-ET model to properly take into account the effects of soil water stress on stomata, yielding the generalized MEP-ET model. This parameter considerably reduced model biases under water stress conditions for various heterogeneous land surface sites. The generalized MEP-ET model outperforms several popular ET models, including Penman–Monteith (PM), modified Priestley–Taylor–Jet Propulsion Laboratory (PT-JPL), and air-relative-humidity-based two-source model (ARTS) at all test sites.

Cloud and Water Vapor Feedbacks in a Vertical Energy-Balance Model with Maximum Entropy Production

2008 ◽  
Vol 21 (24) ◽  
pp. 6689-6697 ◽  
Author(s):  
Biao Wang ◽  
Teruyuki Nakajima ◽  
Guangyu Shi
Keyword(s):  
Water Vapor ◽  
Entropy Production ◽  
Maximum Entropy ◽  
Surface Albedo ◽  
Cloud Fraction ◽  
Lapse Rate ◽  
Balance Model ◽  
Maximum Entropy Production ◽  
Mean Climate ◽  
Global Mean

Abstract A vertically one-dimensional model is developed with cloud fraction constrained by the maximum entropy production (MEP) principle. The model reasonably reproduces the global mean climate with its surface temperature, radiation and heat fluxes, cloud fraction, and lapse rate. The maximum convection hypothesis in Paltridge’s models is related to the MEP principle, and the MEP state of climate is approximately equivalent to that with the maximum lapse rate. The sensitivity investigation about the model assumptions and the prescribed parameters show that the model is considerably robust in simulating the global mean climate. With the MEP constraint, the feedbacks of cloud and water vapor to external forcings, such as changes of CO2 concentration, solar incidence, and surface albedo, are evaluated. While water vapor always behaves as a strong positive feedback, cloud feedbacks to the different forcings are different, in both magnitude and sign. The modeled feedback of cloud fraction to the forcing resulting from surface albedo variation seems in good agreement with the observed seasonal variation of the global cloud fraction.

The mechanics of granitoid systems and maximum entropy production rates

2010 ◽  
Vol 368 (1910) ◽  
pp. 53-93 ◽  
Author(s):  
Bruce E. Hobbs ◽  
Alison Ord
Keyword(s):  
Entropy Production ◽  
Maximum Entropy ◽  
Melt Inclusions ◽  
Selection Process ◽  
Finite Thickness ◽  
Control Valve ◽  
Entropy Production Rate ◽  
Constitutive Behaviour ◽  
Maximum Entropy Production ◽  
Physical Height

A model for the formation of granitoid systems is developed involving melt production spatially below a rising isotherm that defines melt initiation. Production of the melt volumes necessary to form granitoid complexes within 10 4 –10 7 years demands control of the isotherm velocity by melt advection. This velocity is one control on the melt flux generated spatially just above the melt isotherm, which is the control valve for the behaviour of the complete granitoid system. Melt transport occurs in conduits initiated as sheets or tubes comprising melt inclusions arising from Gurson–Tvergaard constitutive behaviour. Such conduits appear as leucosomes parallel to lineations and foliations, and ductile and brittle dykes. The melt flux generated at the melt isotherm controls the position of the melt solidus isotherm and hence the physical height of the Transport/Emplacement Zone. A conduit width-selection process, driven by changes in melt viscosity and constitutive behaviour, operates within the Transport Zone to progressively increase the width of apertures upwards. Melt can also be driven horizontally by gradients in topography; these horizontal fluxes can be similar in magnitude to vertical fluxes. Fluxes induced by deformation can compete with both buoyancy and topographic-driven flow over all length scales and results locally in transient ‘ponds’ of melt. Pluton emplacement is controlled by the transition in constitutive behaviour of the melt/magma from elastic–viscous at high temperatures to elastic–plastic–viscous approaching the melt solidus enabling finite thickness plutons to develop. The system involves coupled feedback processes that grow at the expense of heat supplied to the system and compete with melt advection. The result is that limits are placed on the size and time scale of the system. Optimal characteristics of the system coincide with a state of maximum entropy production rate.

Sign in / Sign up

Export Citation Format

Share Document