12 research outputs found

    Collaborative study of GENIEfy Earth System Models using scripted database workflows in a Grid-enabled PSE

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    The integration of compute and data grids into a common problem solving environment enables collaboration between members of the GENIEfy project. In addition, state-of-the-art optimisation algorithms complement the component framework to provide a comprehensive toolset for Earth system modelling. In this paper, we present for the first time, the application of the non-dominated sorting genetic algorithm (NSGA-II) to perform a multi-objective tuning of a 3D atmosphere model. We then demonstrate how scripted database workflows enable the collective pooling of available resource at distributed client sites to collaboratively progress ensembles of simulations through to completion on the computational grid. A systematic study of the oceanic thermohaline circulation in a hierarchy of 3D atmosphere-ocean-sea-ice models is presented providing evidence for bi-stability in the Atlantic Meridional Overturning Circulation

    The role of ocean and atmosphere feedbacks in maintaining bi-stability of the thermohaline circulation (abstract paper presented at 4th EGU General Assembly, April 2007)

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    We have used the Grid ENabled Integrated Earth system modelling (GENIE) framework to undertake a systematic search for bi-stability of the thermohaline circulation (THC) with a 3-D dynamical atmosphere model (IGCM) coupled to a 3-D frictional geostrophic ocean model (GOLDSTEIN) and slab sea-ice. Three different ocean grids are used: (i) 36x36x8 longitude-sine (latitude), (ii) 72x72x16 longitude-sine(latitude), (iii) 64x32x8 longitude-latitude. In all cases, the IGCM is run at T21 resolution with 7 vertical levels and surface grid (iii). We contrast this with earlier work using an energy-moisture balance atmosphere model (EMBM) and ocean resolution (i).For each model version, we constructed an ensemble of runs in which we vary atmospheric freshwater transport from the Atlantic to Pacific. The resulting ensembles are run toward equilibrium and then restarts are used to search parameter space for regions of THC bi-stability. A total of 407,000 model years were simulated in 3 months by using UK Grid computing resources, including 6 nodes of the National Grid Service, and additional clusters in Norwich, Southampton and Bristol.We find bi-stability of the THC despite significant, quasi-periodic variability in its strength driven by variability in the dynamical atmosphere. The position and width of the hysteresis loop depends on the choice of surface grid (longitude-latitude or equal area), but is less sensitive to changes in ocean resolution. For the same ocean resolution, the region of bi-stability is broader with the IGCM than with the EMBM.Feedbacks involving both ocean and atmospheric dynamics are found to promote THC bi-stability. THC switch-off leads to increased export of salt at the Southern boundary of the Atlantic that tends to maintain the off state. THC switch-off can also generate net freshwater input to the Atlantic from the atmosphere that tends to maintain the off state. The ocean feedback is present in all resolutions, across most of the bi-stable region, whereas the atmosphere feedback is strongest in resolution (iii) and around the transition where the THC off state is disappearing. Here the ocean response reverses, promoting THC switch-on by reducing Atlantic salt export, but the atmosphere counteracts this by increasing net freshwater input. This appears to maintain some bistability even when the THC does switch on - weaker and stronger THC on states can be distinguished under the same boundary conditions and different initialisations of the model

    Tuning GENIE earth system model components using a Grid enabled data management system

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    We present the Grid enabled data management system that has been deployed for the GENIE project and demonstrate its use in tuning studies of an Earth system model. A Matlab client to the system provides a common environment for the project Virtual Organization to share scripts, binaries and output data. By using tools available in the Geodise toolkits we have scripted the execution of tuning studies which exploit multiple heterogeneous computational resources and use the database repository to steer computation using multi-dimensional optimisation methods

    GENIE: Grid enabled integrated earth system model

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    An understanding of the astonishing and, as yet, unexplained natural variability of past climate is an essential pre-requisite to increase confidence in predictions of long-term future climate change. GENIE is a new Grid-enabled modelling framework that can compose an extensive range of Earth System Models (ESMs) for simulation over multi-millennial timescales, to study ice age cycles and long-term human induced global change. Grid technology is a key enabler for the flexible coupling of constituent models, subsequent execution of the resulting ESMs and the management of the data that they generate

    Unpredictable fate of the thermohaline circulation under future CO2 scenarios

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    We examine the bi-stability of the thermohaline circulation and its vulnerability to future CO2 forcing scenarios using the C-GOLDSTEIN Earth system model of intermediate complexity (EMIC), which includes a 3D frictional geostrophic ocean model. An Ensemble Kalman Filter (EnKF) approach is used to tune the parameters of the model by assimilating ocean (temperature, salinity and circulation strength) and atmospheric (surface air temperature and humidity) data. The resulting ensemble of 54 versions of the model (each with different parameter settings) represents a sample of the posterior probability distribution defined by prior beliefs and climate observations. It encapsulates uncertainty in the initial conditions, including the strength of the thermohaline circulation.Initial work has shown that the model thermohaline circulation is close to a non-linear threshold, which may be crossed if the sensitivity of the hydrological cycle to global warming is high. As CO2 is increased, there is a robust decline in overturning strength across all ensemble members, consistent with the century timescale response of full complexity models. However, once CO2 is stabilised, the ensemble diverges with the THC collapsing completely in some members and stabilising at various strengths in others. This uncertainty in outcome is related to the uncertainty in initial conditions, and suggests that the fate of the thermohaline circulation may be inherently unpredictable. We will present the results of forcing all members of an improved ensemble with 21 different CO2 concentration scenarios requested for the IPCC Fourth Assessment Report

    Multiobjective tuning of Grid-enabled Earth System Models using a Non-dominated Sorting Genetic Algorithm (NSGA-II)

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    The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. In this paper we present the first application of the multiobjective non-dominated sorting genetic algorithm (NSGA-II) to the GENIE-1 Earth System Model (ESM). Twelve model parameters are tuned to improve four objective measures of fitness to observational data. Grid computing and data handling technology is harnessed to perform the concurrent simulations that comprise the generations of the genetic algorithm. Recent advances in the method exploit Response Surface Modelling to provide surrogate models of each objective. This enables more extensive and efficient searching of the design space. We assess the performance of the NSGA-II using surrogates by repeating a tuning exercise that has been performed using a proximal analytical centre plane cutting method and the Ensemble Kalman Filter on the GENIE-1 model. We find that the multiobjective algorithm locates Pareto-optimal solutions which are of comparable quality to those obtained using the single objective optimisation methods