Energy Balance Models

2005 ◽  
pp. 81-116
Keyword(s):  
Energy Balance ◽  
Energy Balance Models

scholarly journals Parameter estimation for energy balance models with memory

2014 ◽  
Vol 470 (2169) ◽  
pp. 20140349 ◽  
Author(s):  
Lionel Roques ◽  
Mickaël D. Chekroun ◽  
Michel Cristofol ◽  
Samuel Soubeyrand ◽  
Michael Ghil
Keyword(s):  
Parameter Estimation ◽  
Energy Balance ◽  
Statistical Model ◽  
Ice Cores ◽  
Temperature Measurements ◽  
Age Dating ◽  
Observation Process ◽  
Wide Range ◽  
Energy Balance Models ◽  
With Memory

We study parameter estimation for one-dimensional energy balance models with memory (EBMMs) given localized and noisy temperature measurements. Our results apply to a wide range of nonlinear, parabolic partial differential equations with integral memory terms. First, we show that a space-dependent parameter can be determined uniquely everywhere in the PDE's domain of definition D , using only temperature information in a small subdomain E ⊂ D . This result is valid only when the data correspond to exact measurements of the temperature. We propose a method for estimating a model parameter of the EBMM using more realistic, error-contaminated temperature data derived, for example, from ice cores or marine-sediment cores. Our approach is based on a so-called mechanistic-statistical model that combines a deterministic EBMM with a statistical model of the observation process. Estimating a parameter in this setting is especially challenging, because the observation process induces a strong loss of information. Aside from the noise contained in past temperature measurements, an additional error is induced by the age-dating method, whose accuracy tends to decrease with a sample's remoteness in time. Using a Bayesian approach, we show that obtaining an accurate parameter estimate is still possible in certain cases.

scholarly journals Comparison of the Remote Sensing Based-Energy Balance Models for Estimating Evaporation from Salin Lakes

2019 ◽  
Vol 7 (2) ◽  
pp. 155-175
Author(s):  
Mostafa Khorsand Movaghar ◽  
Somayeh Sima ◽  
◽  
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Energy Balance Models

scholarly journals A Maximum Entropy Production Hypothesis for Time Varying Climate Problems: Illustration on a Conceptual Model for the Seasonal Cycle

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 966
Author(s):  
Vincent Labarre ◽  
Didier Paillard ◽  
Bérengère Dubrulle
Keyword(s):  
Energy Balance ◽  
Entropy Production ◽  
Conceptual Model ◽  
Maximum Entropy ◽  
Seasonal Cycle ◽  
Ground Temperature ◽  
Time Varying ◽  
Energy Fluxes ◽  
Maximum Entropy Production ◽  
Energy Balance Models

We investigated the applicability of the maximum entropy production hypothesis to time-varying problems, in particular, the seasonal cycle using a conceptual model. Contrarily to existing models, only the advective part of the energy fluxes is optimized, while conductive energy fluxes that store energy in the ground are represented by a diffusive law. We observed that this distinction between energy fluxes allows for a more realistic response of the system. In particular, a lag is naturally observed for the ground temperature. This study therefore shows that not all energy fluxes should be optimized in energy balance models using the maximum entropy production hypothesis, but only the fast convective (turbulent) part.

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