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  • 1
    Publication Date: 2017-08-18
    Description: A systematic modular approach to investigate the respective roles of the ocean and atmosphere in setting El Niño characteristics in coupled general circulation models is presented. Several state-of-the-art coupled models sharing either the same atmosphere or the same ocean are compared. Major results include 1) the dominant role of the atmosphere model in setting El Niño characteristics (periodicity and base amplitude) and errors (regularity) and 2) the considerable improvement of simulated El Niño power spectratoward lower frequencywhen the atmosphere resolution is significantly increased. Likely reasons for such behavior are briefly discussed. It is argued that this new modular strategy represents a generic approach to identifying the source of both coupled mechanisms and model error and will provide a methodology for guiding model improvement.
    Type: Article , PeerReviewed
    Format: text
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  • 2
    Publication Date: 2022-03-07
    Description: A new field of study, "decadal prediction," is emerging in climate science. Decadal prediction lies between seasonal/interannual forecasting and longer-term climate change projections, and focuses on time-evolving regional climate conditions over the next 10-30 yr. Numerous assessments of climate information user needs have identified this time scale as being important to infrastructure planners, water resource managers, and many others. It is central to the information portfolio required to adapt effectively to and through climatic changes. At least three factors influence time-evolving regional climate at the decadal time scale: 1) climate change commitment (further warming as the coupled climate system comes into adjustment with increases of greenhouse gases that have already occurred), 2) external forcing, particularly from future increases of greenhouse gases and recovery of the ozone hole, and 3) internally generated variability. Some decadal prediction skill has been demonstrated to arise from the first two of these factors, and there is evidence that initialized coupled climate models can capture mechanisms of internally generated decadal climate variations, thus increasing predictive skill globally and particularly regionally. Several methods have been proposed for initializing global coupled climate models for decadal predictions, all of which involve global time-evolving threedimensional ocean data, including temperature and salinity. An experimental framework to address decadal predictability/prediction is described in this paper and has been incorporated into the coordinated Coupled Model Intercomparison Model, phase 5 (CMIP5) experiments, some of which will be assessed for the IPCC Fifth Assessment Report (AR5). These experiments will likely guide work in this emerging field over the next 5 yr.
    Type: Article , PeerReviewed
    Format: text
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  • 3
    Publication Date: 2020-11-16
    Description: The double-intertropical convergence zone (DI) systematic error, affecting state-of-the-art coupled general circulation models (CGCM) is examined in the multi-model Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) ensemble of simulations of the twentieth-century climate. Aim of this study is to quantify the DI error on precipitation in the tropical Pacific, with a specific focus on the relationship between the DI error and the representation of large-scale vertical circulation regimes in climate models. The DI rainfall signal is analysed using a regime sorting approach for the vertical circulation regimes. Through the use of this compositing technique, precipitation events are regime-sorted based on the large scale vertical motions, as represented by the mid-tropospheric lagrangian pressure tendency omega500 dynamical proxy. This methodology allows the partition of the precipitation signal into deep and shallow convective components. Following the regime-sorting diagnosis, the total DI bias is split into an error affecting the magnitude of precipitation associated with individual convective events and an error affecting the frequency of occurrence of single convective regimes. It is shown that, despite the existing large intra-model differences, CGCMs can be ultimately grouped into a few homegenous clusters, each featuring a well defined rainfall-vertical circulation relationship in the DI region. Three major behavioural clusters are identified within the AR4 models ensemble: two unimodal distributions, featuring maximum precipitation under subsidence and deep convection regimes, respectively, and one bimodal distribution, displaying both components. Extending this analysis to both coupled and uncoupled (atmosphere-only) AR4 simulations reveals that the DI bias in CGCMs is mainly due to the overly frequent occurrence of deep convection regimes, whereas the error on rainfall magnitude associated with individual convective events is overall consistent with errors already present in the corresponding atmosphere stand-alone simulations. A critical parameter controlling the strength of the DI systematic error is identified in the model-dependent sea surface temperature (SST) threshold leading to the onset of deep convection (THR), combined with the average SST in the south-eastern Pacific.
    Description: Published
    Description: 1127–1145
    Description: 4A. Oceanografia e clima
    Description: JCR Journal
    Description: open
    Keywords: double ITCZ ; climate models ; 01. Atmosphere::01.01. Atmosphere::01.01.02. Climate
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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