On the Use of Emulators with Extreme and Highly Nonlinear Geophysical Simulators

Tokmakian, Robin; Challenor, Peter; Andrianakis, Yiannis

doi:10.1175/jtech-d-11-00110.1

Cited by 11 publications

(6 citation statements)

References 29 publications

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“…We present for the first time the use of emulators to resolve the water and salt balance equations at the root zone and at regional scale. Emulators are approximation models of an experiment or a more complex numerical models or simulators [i.e., Tokmakian et al , ]. Emulators are primarily used for their speed and flexibility to represent any system.…”

Section: Introductionmentioning

confidence: 99%

Modeling daily soil salinity dynamics in response to agricultural and environmental changes in coastal Bangladesh

et al. 2017

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Understanding the dynamics of salt movement in the soil is a prerequisite for devising appropriate management strategies for land productivity of coastal regions, especially low-lying delta regions, which support many millions of farmers around the world. At present, there are no numerical models able to resolve soil salinity at regional scale and at daily time steps. In this research, we develop a novel holistic approach to simulate soil salinization comprising an emulator-based soil salt and water balance calculated at daily time steps. The method is demonstrated for the agriculture areas of coastal Bangladesh (∼20,000 km 2 ). This shows that we can reproduce the dynamics of soil salinity under multiple land uses, including rice crops, combined shrimp and rice farming, as well as non-rice crops. The model also reproduced well the observed spatial soil salinity for the year 2009. Using this approach, we have projected the soil salinity for three different climate ensembles, including relative sea-level rise for the year 2050. Projected soil salinity changes are significantly smaller than other reported projections. The results suggest that inter-season weather variability is a key driver of salinization of agriculture soils at coastal Bangladesh. Plain Language SummaryIn this manuscript, we developed a novel "regional" soil salinity model to assess long term (days to decades) changes in coastal agricultural lowlands and we have demonstrate it in coastal Bangladesh. This model can reproduce the soil salinity time series under multiple land uses, including rice crops, combined shrimp and rice farming, as well as non-rice crops. We are now confident that the model structure is adequate to explore future scenarios of soil salinization under different climate and agriculture practices.

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Section: Introductionmentioning

confidence: 99%

Modeling daily soil salinity dynamics in response to agricultural and environmental changes in coastal Bangladesh

et al. 2017

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“…In Tokmakian et al [21], the authors discuss the use of Gaussian process emulators for nonlinear systems and exemplify their methods using Stommel's model Stommel [20]. Zickfield's model consists of four well-mixed boxes that represent the southern (box 1), northern (box 2), tropical (box 3) and deep Atlantic (box 4) as shown in Figure 1.…”

Section: Example: the Zickfeld Et Al (2004) Model Of The Atlanticmentioning

confidence: 99%

Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points

Caiado

Goldstein

2015

Communications in Nonlinear Science and Numerical Simulation

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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractIn this paper we present and illustrate basic Bayesian techniques for the uncertainty analysis of complex physical systems modelled by computer simulators. We focus on emulation and history matching and also discuss the treatment of observational errors and structural discrepancies in time series. We exemplify such methods using a four-box model for the termohaline circulation. We show how these methods may be applied to systems containing tipping points and how to treat possible discontinuities using multiple emulators.

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“…Lee et al (2011) used a Gaussian process methodology to emulate the behavior of a complex global aerosol model, and to quantify sensitivity to uncertain parameters. Other studies that have used statistical emulators to approximate the behavior of complex numerical models include, but are not limited to the following: Bowman et al (1993), Higdon et al (2004), Williams et al (2006), Sanso et al (2008), Tokmakian et al (2012), and Lee et al (2013). The choice of emulator depends on the complexity of the model parameter -response relationship.…”

Section: Introductionmentioning

confidence: 99%

Application of Multivariate Sensitivity Analysis Techniques to AGCM-Simulated Tropical Cyclones

Posselt

Narisetty

et al. 2018

Monthly Weather Review

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This work demonstrates the use of Sobol’s sensitivity analysis framework to examine multivariate input–output relationships in dynamical systems. The methodology allows simultaneous exploration of the effect of changes in multiple inputs, and accommodates nonlinear interaction effects among parameters in a computationally affordable way. The concept is illustrated via computation of the sensitivities of atmospheric general circulation model (AGCM)-simulated tropical cyclones to changes in model initial conditions. Specifically, Sobol’s variance-based sensitivity analysis is used to examine the response of cyclone intensity, cloud radiative forcing, cloud content, and precipitation rate to changes in initial conditions in an idealized AGCM-simulated tropical cyclone (TC). Control factors of interest include the following: initial vortex size and intensity, environmental sea surface temperature, vertical lapse rate, and midlevel relative humidity. The sensitivity analysis demonstrates systematic increases in TC intensity with increasing sea surface temperature and atmospheric temperature lapse rates, consistent with many previous studies. However, there are nonlinear interactions among control factors that affect the response of the precipitation rate, cloud content, and radiative forcing. In addition, sensitivities to control factors differ significantly when the model is run at different resolution, and coarse-resolution simulations are unable to produce a realistic TC. The results demonstrate the effectiveness of a quantitative sensitivity analysis framework for the exploration of dynamic system responses to perturbations, and have implications for the generation of ensembles.

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On the Use of Emulators with Extreme and Highly Nonlinear Geophysical Simulators

Cited by 11 publications

References 29 publications

Modeling daily soil salinity dynamics in response to agricultural and environmental changes in coastal Bangladesh

Modeling daily soil salinity dynamics in response to agricultural and environmental changes in coastal Bangladesh

Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points

Application of Multivariate Sensitivity Analysis Techniques to AGCM-Simulated Tropical Cyclones

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