ﻻ يوجد ملخص باللغة العربية
The climate is a non-equilibrium system undergoing the continuous action of forcing and dissipation. Under the effect of a spatially inhomogeneous absorption of solar energy, all the climate components dynamically respond by redistributing energy until an approximate steady state is reached. In order to improve the skill of climate models and correct their biases, it is essential to investigate how such dynamical balance is reached. In general, the climate system features multiple steady states for a given set of boundary conditions. Here, we apply the Thermodynamic Diagnostic Tool (TheDiaTo) to investigate the statistical properties of the five co-existing climates, ranging from a snowball to an ice-free aquaplanet, obtained in MITgcm coupled simulations under the same boundary conditions. The aim is to explore the multistability of the climate by highlighting differences in competing steady states and their characteristic signatures regarding the meridional transport of heat and water mass, the Lorenz energy cycle and the material entropy production. Alternative cloud parametrizations and descriptions of energy exchange are also used to investigate how robust such signatures are and, at the same time, how the statistical properties can be improved in the simulated climatic states. Thus we show how the diagnostic tool can help in identifying strengths and weaknesses of a model configuration.
We apply two independent data analysis methodologies to locate stable climate states in an intermediate complexity climate model and analyze their interplay. First, drawing from the theory of quasipotentials, and viewing the state space as an energy
The impact of extreme climate such as drought and flooding on agriculture, tourism, migration and peace in Nigeria is immense. There is the need to study the trend and statistics for better planning, preparation and adaptation. In this study, the sta
We propose a second renormalization group method to handle the tensor-network states or models. This method reduces dramatically the truncation error of the tensor renormalization group. It allows physical quantities of classical tensor-network model
Across many scientific and engineering disciplines, it is important to consider how much the output of a given system changes due to perturbations of the input. Here, we study the robustness of the ground states of $pm J$ spin glasses on random graph
Convective and radiative cooling are the two principle mechanisms by which the Earths surface transfers heat into the atmosphere and that shape surface temperature. However, this partitioning is not sufficiently constrained by energy and mass balance