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In this work, we present a new diagnostic tool for El Niño Southern Oscillation (ENSO) simulations in Earth System Models (ESMs) based on the analysis of upper ocean heat content data. It allows us to identify the seasonally dependent structure of temperature anomalies in the equatorial Pacific Ocean in the form of a dominant spatio-temporal pattern. We demonstrate the results of applying a tool to analysis of real data as well as climate simulations in two versions of the Institute of Numerical Mathematics ESM. We find that the latest version of the model, with improved parameterizations of clouds, large-scale condensation, and aerosols, provides significantly better reproduction of ENSO-related structure of anomalies, as well as the phase locking of ENSO to the annual cycle. We recommend to use the tool for diagnostic analysis of ESMs regarding simulation of climate phenomena with strong seasonality. [ABSTRACT FROM AUTHOR]

Advanced numerical climate models are known to exhibit biases in simulating some features of El Niño–Southern Oscillation (ENSO), which is a key mode of interannual climate variability. In this study we analyze how two fundamental features of observed ENSO – asymmetry between hot and cold states and phase-locking to the annual cycle – are reflected in two different versions of the INMCM Earth system model (state-of-the-art Earth system model participating in the Coupled Model Intercomparison Project). We identify the above ENSO features using the conventional empirical orthogonal functions (EOF) analysis, which is applied to both observed and simulated upper ocean heat content (OHC) data in the tropical Pacific. We obtain that the observed tropical Pacific OHC variability is described well by two leading EOF-modes, which roughly reflect the fundamental recharge-discharge mechanism of ENSO. These modes exhibit strong seasonal cycles associated with ENSO phase locking while the revealed nonlinear dependencies between amplitudes of these cycles reflect ENSO asymmetry.We also assess and compare the predictability of observed and simulated ENSO based on linear inverse modelling. We find that the improved INMCM6 model has significant benefits in simulating described features of observed ENSO as compared with the previous INMCM5 model. The improvements of the INMCM6 model providing such benefits are discussed. We argue that proper cloud parameterization scheme is crucial for accurate simulation of ENSO dynamics with numerical climate models. [ABSTRACT FROM AUTHOR]

The present paper considers numerical properties of two different approaches to discretization of the isoneutral diffusion. The necessity of an alternative treatment of the isoneutral diffusion in a terrain-following climate ocean model as opposed to the more convenient rotated tensor formalism is studied. A new method of the approximation of the isoneutral diffusion based on a non-local computational stencil is formulated. The validity of the non-local discretization of the isoneutral diffusion operator with regard to a terrain-following vertical coordinate in the INMCM ocean model is demonstrated. [ABSTRACT FROM AUTHOR]

The problem of potential predictability of the temperature of the upper layer of the Arctic Ocean for the data of pre-industrial climate modelling run by the INM-CM5 Earth system model developed at the INM RAS is considered. The main attention is paid to the analysis of predictability of the phases of the dominant modes of low-frequency variability of the Arctic Ocean circulation. The initial estimate of its predictability is made by using the method of analogues and calculating the resonances of the invariant measure. Then this estimate is verified by direct ensemble calculations with the model. The results obtained indicate that the maximum predictability time interval reaches ten years for 15-year average values of heat content and corresponds to the states with maximum positive anomalies along the leading low-frequency variability modes. [ABSTRACT FROM AUTHOR]

The problem of modelling 2D isotropic turbulence in a periodic rectangular domain excited by the forcing pattern of prescribed spatial scale is considered. This setting could be viewed as the simplest analogue of the large scale quasi-2D circulation of the ocean and the atmosphere. Since the direct numerical simulation (DNS) of this problem is usually not possible due to the high computational costs we explore several possibilities to construct coarse approximation models and corresponding subgrid closures (deterministic or stochastic). The necessity of subgrid closures is especially important when the forcing scale is close to the cutoff scale of the coarse model that leads to the significant weakening of the inverse energy cascade and large scale component of the system dynamics. The construction of closures is based on the a priori analysis of the DNS solution and takes into account the form of a spatial approximation scheme used in a particular coarse model. We show that the statistics of a coarse model could be significantly improved provided a proper combination of deterministic and stochastic closures is used. As a result we are able to restore the shape of the energy spectra of the model. In addition the lagged auto correlations of the model solution as well as its sensitivity to external perturbations fit the characteristics of the DNS model much better. [ABSTRACT FROM AUTHOR]

The structure of main modes of the decadal and multidecadal variability of the Atlantic meridional overturning circulation (AMOC) is analyzed for the climate models INM-CM5 (INM RAS), CCSM4 (NCAR), MPI-LR and MPI-MR (MPI). It is shown that oscillations with characteristic periods of 25–35 and 50–70 years are recognized in the models, and the corresponding spatial structures are variations of the intensity and position of the AMOC. Relations connecting changes of thermohaline circulation with external impacts on the system are constructed for the above models. The analysis of stability of calculations relative to the length of data series used for calculations is performed. The optimal impacts leading to the greatest response of the AMOC and influence functions causing its response along the leading modes of low-frequency variability are constructed. The optimal impacts have the form of density anomalies localized in the North Atlantic, and the structures of the corresponding responses are dominated by leading low-frequency modes of variability. The structure of optimal impacts varies greatly from model to model. [ABSTRACT FROM AUTHOR]

We consider simulation of the present day climate with the use of the climate model INM-CM48 in comparison with the result of the previous model INMCM4.0 which used different parameterizations of many physical processes and also in comparison with the model INM-CM5 which uses the same parameterizations, but with better spatial resolution. It is shown that the model INM-CM48 reproduces the modern climate better than the model INMCM4.0 in most indicators. [ABSTRACT FROM AUTHOR]

The fluctuation dissipation theorem (FDT), a classical result coming from statistical mechanics, suggests that, under certain conditions, the system response to external forcing can be obtained using the statistics of natural fluctuation of the system. The application of the FDT to the most sophisticated climate models and the real climate system represents a difficult problem due to the huge dimensionality of these systems and the lack of the data available for proper sampling of the system natural variability. As a con- sequence, one has to use some regularization procedures constraining the form of permitted perturbations. Naturally, the skill of the FDT depends on the type and parameters of the regularization procedure. In the present paper we apply FDT to predict the response of a recent version of the NCAR climate system model (CCSM4) to salinity and temperature forcing anomalies in the North Atlantic. We study the sensitivity of our results to the amount of available data and to key parameters used in our numerical algorithm. [ABSTRACT FROM AUTHOR]