scholarly journals Interactions of ENSO, the IOD, and the SAM in CMIP3 Models

2011 ◽  
Vol 24 (6) ◽  
pp. 1688-1704 ◽  
Author(s):  
Wenju Cai ◽  
Arnold Sullivan ◽  
Tim Cowan
Keyword(s):  
Southern Oscillation ◽  
Global Climate ◽  
Coupled Model ◽  
Southern Annular Mode ◽  
Enso Events ◽  
Intercomparison Project ◽  
Wave Trains ◽  
Induced Signal ◽  
The Impact ◽  
The Relationship

Abstract Simulations of individual global climate drivers using models from the Coupled Model Intercomparison Project phase 3(CMIP3) have been examined; however, the relationship among them has not been assessed. This is carried out to address several important issues, including the likelihood of the southern annular mode (SAM) forcing Indian Ocean dipole (IOD) events and the possible impact of the IOD on El Niño–Southern Oscillation (ENSO) events. Several conclusions emerge from statistics based on multimodel outputs. First, ENSO signals project strongly onto the SAM, although ENSO-forced signals tend to peak before ENSO. This feature is similar to the situation associated with the IOD. The IOD-induced signal over southern Australia, through stationary equivalent Rossby barotropic wave trains, peak before the IOD itself. Second, there is no control by the SAM on the IOD, in contrast to what has been suggested previously. Indeed, no model produces a SAM–IOD relationship that supports a positive (negative) SAM driving a positive (negative) IOD event. This is the case even in models that do not simulate a statistically significant relationship between ENSO and the IOD. Third, the IOD does have an impact on ENSO. The relationship between ENSO and the IOD in the majority of models is far weaker than the observed. However, the ENSO’s influence on the IOD is boosted by a spurious oceanic teleconnection, whereby ENSO discharge–recharge signals transmit to the Sumatra–Java coast, generating thermocline anomalies and changing IOD properties. Without the spurious oceanic teleconnection, the influence of the IOD on ENSO is comparable to the impact of ENSO on the IOD. Other model deficiencies are discussed.

Composite Analysis of the Effects of ENSO Events on Antarctica

2016 ◽  
Vol 29 (5) ◽  
pp. 1797-1808 ◽  
Author(s):  
Lee J. Welhouse ◽  
Matthew A. Lazzara ◽  
Linda M. Keller ◽  
Gregory J. Tripoli ◽  
Matthew H. Hitchman
Keyword(s):  
El Niño ◽  
Geopotential Height ◽  
El Nino ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
La Niña ◽  
Austral Spring ◽  
Enso Events ◽  
La Nina ◽  
The Relationship

Abstract Previous investigations of the relationship between El Niño–Southern Oscillation (ENSO) and the Antarctic climate have focused on regions that are impacted by both El Niño and La Niña, which favors analysis over the Amundsen and Bellingshausen Seas (ABS). Here, 35 yr (1979–2013) of European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) data are analyzed to investigate the relationship between ENSO and Antarctica for each season using a compositing method that includes nine El Niño and nine La Niña periods. Composites of 2-m temperature (T2m), sea level pressure (SLP), 500-hPa geopotential height, sea surface temperatures (SST), and 300-hPa geopotential height anomalies were calculated separately for El Niño minus neutral and La Niña minus neutral conditions, to provide an analysis of features associated with each phase of ENSO. These anomaly patterns can differ in important ways from El Niño minus La Niña composites, which may be expected from the geographical shift in tropical deep convection and associated pattern of planetary wave propagation into the Southern Hemisphere. The primary new result is the robust signal, during La Niña, of cooling over East Antarctica. This cooling is found from December to August. The link between the southern annular mode (SAM) and this cooling is explored. Both El Niño and La Niña experience the weakest signal during austral autumn. The peak signal for La Niña occurs during austral summer, while El Niño is found to peak during austral spring.

scholarly journals Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation

2020 ◽  
Vol 13 (1) ◽  
pp. 139-154 ◽  
Author(s):  
Maria-Vittoria Guarino ◽  
Louise C. Sime ◽  
David Schroeder ◽  
Grenville M. S. Lister ◽  
Rosalyn Hatcher
Keyword(s):  
Southern Oscillation ◽  
Coupled Model ◽  
Climate Simulation ◽  
Climate Projections ◽  
Model Intercomparison ◽  
Sea Ice Concentration ◽  
Mip Model ◽  
Climate Simulations ◽  
Intercomparison Project ◽  
The Impact

Abstract. When the same weather or climate simulation is run on different high-performance computing (HPC) platforms, model outputs may not be identical for a given initial condition. While the role of HPC platforms in delivering better climate projections is to some extent discussed in the literature, attention is mainly focused on scalability and performance rather than on the impact of machine-dependent processes on the numerical solution. Here we investigate the behaviour of the Preindustrial (PI) simulation prepared by the UK Met Office for the forthcoming CMIP6 (Coupled Model Intercomparison Project Phase 6) under different computing environments. Discrepancies between the means of key climate variables were analysed at different timescales, from decadal to centennial. We found that for the two simulations to be statistically indistinguishable, a 200-year averaging period must be used for the analysis of the results. Thus, constant-forcing climate simulations using the HadGEM3-GC3.1 model are reproducible on different HPC platforms provided that a sufficiently long duration of simulation is used. In regions where El Niño–Southern Oscillation (ENSO) teleconnection patterns were detected, we found large sea surface temperature and sea ice concentration differences on centennial timescales. This indicates that a 100-year constant-forcing climate simulation may not be long enough to adequately capture the internal variability of the HadGEM3-GC3.1 model, despite this being the minimum simulation length recommended by CMIP6 protocols for many MIP (Model Intercomparison Project) experiments. On the basis of our findings, we recommend a minimum simulation length of 200 years whenever possible.

Impact of strong El Niño events on river discharge in South America

2021 ◽  
Author(s):  
Markus Deppner ◽  
Bedartha Goswami
Keyword(s):  
Machine Learning ◽  
Missing Data ◽  
South America ◽  
River Discharge ◽  
Amazon Basin ◽  
Missing Values ◽  
Southern Oscillation ◽  
Enso Events ◽  
Streamflow Data ◽  
The Impact

<p>The impact of the El Niño Southern Oscillation (ENSO) on rivers are well known, but most existing studies involving streamflow data are severely limited by data coverage. Time series of gauging stations fade in and out over time, which makes hydrological large scale and long time analysis or studies of rarely occurring extreme events challenging. Here, we use a machine learning approach to infer missing streamflow data based on temporal correlations of stations with missing values to others with data. By using 346 stations, from the “Global Streamflow Indices and Metadata archive” (GSIM), that initially cover the 40 year timespan in conjunction with Gaussian processes we were able to extend our data by estimating missing data for an additional 646 stations, allowing us to include a total of 992 stations. We then investigate the impact of the 6 strongest El Niño (EN) events on rivers in South America between 1960 and 2000. Our analysis shows a strong correlation between ENSO events and extreme river dynamics in the southeast of Brazil, Carribean South America and parts of the Amazon basin. Furthermore we see a peak in the number of stations showing maximum river discharge all over Brazil during the EN of 1982/83 which has been linked to severe floods in the east of Brazil, parts of Uruguay and Paraguay. However EN events in other years with similar intensity did not evoke floods with such magnitude and therefore the additional drivers of the 1982/83  floods need further investigation. By using machine learning methods to infer data for gauging stations with missing data we were able to extend our data by almost three-fold, revealing a possible heavier and spatially larger impact of the 1982/83 EN on South America's hydrology than indicated in literature.</p>

scholarly journals The Impact of Obliquity Change on El Niño Southern Oscillation (ENSO) and La Niña Climate Episodes

2022 ◽  
Author(s):  
Paul C. Rivera
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
La Niña ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
La Nina ◽  
The Impact

An alternative physical mechanism is proposed to describe the occurrence of the episodic El Nino Southern Oscillation (ENSO) and La Nina climatic phenomena. This is based on the earthquake-perturbed obliquity change (EPOCH) model previously discovered as a major cause of the global climate change problem. Massive quakes impart a very strong oceanic force that can move the moon which in turn pulls the earth’s axis and change the planetary obliquity. Analysis of the annual geomagnetic north-pole shift and global seismic data revealed this previously undiscovered force. Using a higher obliquity in the global climate model EdGCM and constant greenhouse gas forcing showed that the seismic-induced polar motion and associated enhanced obliquity could be the major mechanism governing the mysterious climate anomalies attributed to El Nino and La Nina cycles.

scholarly journals Experimental and diagnostic protocol for the physical component of the CMIP6 Ocean Model Intercomparison Project (OMIP)

2016 ◽  
Author(s):  
Stephen M. Griffies ◽  
Gokhan Danabasoglu ◽  
Paul J. Durack ◽  
Alistair J. Adcroft ◽  
V. Balaji ◽  
...  
Keyword(s):  
Sea Ice ◽  
Global Climate ◽  
Coupled Model ◽  
Companion Paper ◽  
Ocean Model ◽  
Global Ocean ◽  
Model Intercomparison ◽  
Experimental Protocol ◽  
Diagnostic Protocol ◽  
Intercomparison Project

Abstract. The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses these aims in two complementary manners: (A) by providing an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing, (B) by providing a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) offering details for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows that of the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II have become the standard method to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP (Scenario MIP), as well as the ocean-sea ice OMIP simulations. The bulk of this paper offers scientific rationale for saving these diagnostics.

The Role of Oceanic Feedback in the Climate Response to Doubling CO2

2012 ◽  
Vol 25 (21) ◽  
pp. 7544-7563 ◽  
Author(s):  
Jian Lu ◽  
Bin Zhao
Keyword(s):  
Ocean Circulation ◽  
Global Climate ◽  
Coupled Model ◽  
Southern Annular Mode ◽  
Ocean Dynamics ◽  
Climate Response ◽  
Tropical Precipitation ◽  
Fluctuation Dissipation ◽  
Wes Feedback ◽  
Partial Coupling

Two suites of partial coupling experiments are devised with the upper-ocean dynamics version (UOM) of the CCSM3 to isolate the effects of the feedbacks from the change of the wind-driven ocean circulation and air–sea heat flux in the global climate response to the forcing of doubling CO2. The partial coupling is achieved by implementing a so-called overriding technique, which helps quantitatively partition the total response in the fully coupled model to the feedback component in question and the response to external forcing in the absence of the former. By overriding the wind stress seen by the ocean and the wind speed through the bulk formula for evaporation, the experiments help to reveal that (i) the wind–evaporation–SST (WES) feedback is the main formation mechanism for the tropical SST pattern under the CO2 forcing, verifying the hypothesis proposed by Xie et al.; (ii) the weakened tropical Pacific wind is shown in this UOM model not to be the cause for the enhanced equatorial Pacific warming, as one might expect from the thermocline and Bjerknes feedbacks; (iii) WES is also the leading mechanism for shaping the tropical precipitation response in the ocean; and (iv) both the wind-driven ocean dynamical feedback and the WES feedback act to increase the persistence of the southern annular mode (SAM) and the increased time scale of the SAM due to these feedbacks manifests itself in the response of the jet shift to an identical CO2 forcing, in a manner conforming to the fluctuation–dissipation theorem.

scholarly journals The impact of the 2015/2016 El Niño on global photosynthesis using satellite remote sensing

2018 ◽  
Vol 373 (1760) ◽  
pp. 20170409 ◽  
Author(s):  
Xiangzhong Luo ◽  
Trevor F. Keenan ◽  
Joshua B. Fisher ◽  
Juan-Carlos Jiménez-Muñoz ◽  
Jing M. Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Carbon Cycle ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Carbon Sink ◽  
Global Climate ◽  
Prognostic Models ◽  
Positive Anomaly ◽  
The Impact

The El Niño-Southern Oscillation exerts a large influence on global climate regimes and on the global carbon cycle. Although El Niño is known to be associated with a reduction of the global total land carbon sink, results based on prognostic models or measurements disagree over the relative contribution of photosynthesis to the reduced sink. Here, we provide an independent remote sensing-based analysis on the impact of the 2015–2016 El Niño on global photosynthesis using six global satellite-based photosynthesis products and a global solar-induced fluorescence (SIF) dataset. An ensemble of satellite-based photosynthesis products showed a negative anomaly of −0.7 ± 1.2 PgC in 2015, but a slight positive anomaly of 0.05 ± 0.89 PgC in 2016, which when combined with observations of the growth rate of atmospheric carbon dioxide concentrations suggests that the reduction of the land residual sink was likely dominated by photosynthesis in 2015 but by respiration in 2016. The six satellite-based products unanimously identified a major photosynthesis reduction of −1.1 ± 0.52 PgC from savannahs in 2015 and 2016, followed by a highly uncertain reduction of −0.22 ± 0.98 PgC from rainforests. Vegetation in the Northern Hemisphere enhanced photosynthesis before and after the peak El Niño, especially in grasslands (0.33 ± 0.13 PgC). The patterns of satellite-based photosynthesis ensemble mean were corroborated by SIF, except in rainforests and South America, where the anomalies of satellite-based photosynthesis products also diverged the most. We found the inter-model variation of photosynthesis estimates was strongly related to the discrepancy between moisture forcings for models. These results highlight the importance of considering multiple photosynthesis proxies when assessing responses to climatic anomalies. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

scholarly journals Correction to: The impact of stochastic physics on the El Niño Southern Oscillation in the EC-Earth coupled model

2019 ◽  
Vol 53 (3-4) ◽  
pp. 2479-2479 ◽  
Author(s):  
Chunxue Yang ◽  
Hannah M. Christensen ◽  
Susanna Corti ◽  
Jost von Hardenberg ◽  
Paolo Davini
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Coupled Model ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
The Impact ◽  
Stochastic Physics
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