88 research outputs found
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Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)
Numerical simulation, and in particular simulation of the earth system, relies on contributions from diverse communities, from those who develop models to those involved in devising, executing, and analysing numerical experiments. Often these people work in different institutions and may be working with significant separation in time (particularly analysts, who may be working on data produced years earlier), and they typically communicate via published information (whether journal papers, technical notes, or websites). The complexity of the models, experiments, and methodologies, along with the diversity (and sometimes inexact nature) of information sources, can easily lead to misinterpretation of what was actually intended or done. In this paper we introduce a taxonomy of terms for more clearly defining numerical experiments, put it in the context of previous work on experimental ontologies, and describe how we have used it to document the experiments of the sixth phase for the Coupled Model Intercomparison Project (CMIP6). We describe how, through iteration with a range of CMIP6 stakeholders, we rationalized multiple sources of information and improved the clarity of experimental definitions. We demonstrate how this process has added value to CMIP6 itself by (a) helping those devising experiments to be clear about their goals and their implementation, (b) making it easier for those executing experiments to know what is intended, (c) exposing interrelationships between experiments, and (d) making it clearer for third parties (data users) to understand the CMIP6 experiments. We conclude with some lessons learnt and how these may be applied to future CMIP phases as well as other modelling campaigns
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The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part III: the shortwave flux feedback
Previous studies using coupled general circulation models (GCMs) suggest that the atmosphere model plays a dominant role in the modeled El Nin Ì oâSouthern Oscillation (ENSO), and that intermodel differences in the thermodynamical damping of sea surface temperatures (SSTs) are a dominant contributor to the ENSO amplitude diversity. This study presents a detailed analysis of the shortwave flux feedback (aSW) in 12 Coupled Model Intercomparison Project phase 3 (CMIP3) simulations, motivated by findings that aSW is the primary contributor to model thermodynamical damping errors.
A ââfeedback decomposition method,ââ developed to elucidate the aSW biases, shows that all models un- derestimate the dynamical atmospheric response to SSTs in the eastern equatorial Pacific, leading to un- derestimated aSW values. Biases in the cloud response to dynamics and the shortwave interception by clouds also contribute to errors in aSW. Changes in the aSW feedback between the coupled and corresponding atmosphere-only simulations are related to changes in the mean dynamics.
A large nonlinearity is found in the observed and modeled SW flux feedback, hidden when linearly cal- culating aSW. In the observations, two physical mechanisms are proposed to explain this nonlinearity: 1) a weaker subsidence response to cold SST anomalies than the ascent response to warm SST anomalies and 2) a nonlinear high-level cloud cover response to SST. The shortwave flux feedback nonlinearity tends to be underestimated by the models, linked to an underestimated nonlinearity in the dynamical response to SST. The process-based methodology presented in this study may help to correct model ENSO atmospheric biases, ultimately leading to an improved simulation of ENSO in GCMs
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The CMIP5 model and simulation documentation: a new standard for climate modelling metadata
Assessment of the tropical Indo-Pacific climate in the SINTEX CGCM
A new coupled GCM (SINTEX) has been developed. The model is formed by the atmosphere model ECHAM-4 and the ocean model ORCA. The atmospheric and oceanic components are coupled through OASIS. The domain is global and no flux correction is applied. In this study, we describe the ability of the coupled model to simulate
the main features of the observed climate and its dominant modes of variability in the tropical Indo-Pacific. Three long experiments have been performed with different horizontal resolution of the atmospheric component in order to assess a possible impact of the atmosphere model resolution onto the simulated climate. Overall, the mean state is captured reasonably well, though the simulated SST tends to be too warm in the tropical Eastern
Pacific and there is a model tendency to produce a double ITCZ. The model gives also a realistic representation of the temperature structure at the equator in the Pacific and Indian Ocean. The slope and the structure of the equatorial thermocline are well reproduced. Compared to the observations, the simulated annual cycle appears to be underestimated in the eastern equatorial Pacific, whereas a too pronounced seasonal variation is found in the Central Pacific. The main basic features of the interannual variability in the tropical Indo-Pacific region are reasonably well reproduced by the model. In the Indian Ocean, the characteristics of the simulated interannual variability are very similar to the results found from the observations. In the Pacific, the modelled ENSO variability appears to be slightly weaker and the simulated period a bit shorter than in the observations. Our results suggest that, both the simulated mean state and interannual variability are generally improved when the horizontal resolution of the atmospheric mode component is increased
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ENSO in a changing climate
The El NiñoâSouthern Oscillation (ENSO) phenomenon is a naturally occurring climate fluctuation, which originates in the tropical Pacific region and affects ecosystems, agriculture, freshwater supplies, hurricanes and other severe weather events worldwide (Goddard and Dilley 2005; McPhaden et al. 2006). Despite considerable progress in our understanding of the impact of climate change on many of the processes that contribute to ENSO variability (e.g., Collins et al. 2010), it is not yet possible to say whether ENSO activity will be enhanced or damped, or if the frequency or character of events will change in the coming decades (Vecchi and Wittenberg 2010). As changes in ENSO have the potential to be one of the largest manifestations of anthropogenic climate change, this status has profound impacts on the reliability of regional attribution of climate variability and change. Two main reasons can be invoked for these shortcomings. First there is a lack of long and comprehensive enough observations of the various ENSO processes to be able to detect past changes. It may be that we need to observe ENSO for another several decades to detect and attribute significant ENSO changes (Wittenberg 2009; Stevenson et al. 2012). Second, as ENSO involves a complex interplay of numerous ocean and atmospheric processes, accurately modeling this climate phenomenon with CGCMs, an
Development and exploitation of a controlled vocabulary in support of climate modelling
There are three key components for developing a metadata system: a container structure laying out the key semantic issues of interest and their relationships; an extensible controlled vocabulary providing possible content; and tools to create and manipulate that content. While metadata systems must allow users to enter their own information, the use of a controlled vocabulary both imposes consistency of definition and ensures comparability of the objects described. Here we describe the controlled vocabulary (CV) and metadata creation tool built by the METAFOR project for use in the context of describing the climate models, simulations and experiments of the fifth Coupled Model Intercomparison Project (CMIP5). The CV and resulting tool chain introduced here is designed for extensibility and reuse and should find applicability in many more projects
The common information model for climate modelling digital repositories: The metafor project
A poster highlighting the common information model for climate modelling digital repositorie
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