ENSO Modulation: Is It Decadally Predictable?

2014 ◽  
Vol 27 (7) ◽  
pp. 2667-2681 ◽  
Author(s):  
Andrew T. Wittenberg ◽  
Anthony Rosati ◽  
Thomas L. Delworth ◽  
Gabriel A. Vecchi ◽  
Fanrong Zeng
Keyword(s):  
Climate Model ◽  
Initial Conditions ◽  
Southern Oscillation ◽  
Potential Predictability ◽  
Decadal Scale ◽  
Wide Range ◽  
Large Ensembles ◽  
Realistic Representation ◽  
Enso Modulation ◽  
Decadal Predictability

Abstract Observations and climate simulations exhibit epochs of extreme El Niño–Southern Oscillation (ENSO) behavior that can persist for decades. Previous studies have revealed a wide range of ENSO responses to forcings from greenhouse gases, aerosols, and orbital variations, but they have also shown that interdecadal modulation of ENSO can arise even without such forcings. The present study examines the predictability of this intrinsically generated component of ENSO modulation, using a 4000-yr unforced control run from a global coupled GCM [GFDL Climate Model, version 2.1 (CM2.1)] with a fairly realistic representation of ENSO. Extreme ENSO epochs from the unforced simulation are reforecast using the same (“perfect”) model but slightly perturbed initial conditions. These 40-member reforecast ensembles display potential predictability of the ENSO trajectory, extending up to several years ahead. However, no decadal-scale predictability of ENSO behavior is found. This indicates that multidecadal epochs of extreme ENSO behavior can arise not only intrinsically but also delicately and entirely at random. Previous work had shown that CM2.1 generates strong, reasonably realistic, decadally predictable high-latitude climate signals, as well as tropical and extratropical decadal signals that interact with ENSO. However, those slow variations appear not to lend significant decadal predictability to this model’s ENSO behavior, at least in the absence of external forcings. While the potential implications of these results are sobering for decadal predictability, they also offer an expedited approach to model evaluation and development, in which large ensembles of short runs are executed in parallel, to quickly and robustly evaluate simulations of ENSO. Further implications are discussed for decadal prediction, attribution of past and future ENSO variations, and societal vulnerability.

Potential predictability of Southwest US rainfall : role of tropical and high-latitude variability

2021 ◽  
pp. 1-45
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Seasonal Prediction ◽  
Seasonal Rainfall ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Potential Predictability ◽  
Subseasonal Variability ◽  
The Tropics

Abstract This study explores the potential predictability of Southwest US (SWUS) precipitation for the November-March season in a set of numerical experiments performed with the Whole Atmospheric Community Climate Model. In addition to the prescription of observed sea surface temperature and sea ice concentration, observed variability from the MERRA-2 reanalysis is prescribed in the tropics and/or the Arctic through nudging of wind and temperature. These experiments reveal how a perfect prediction of tropical and/or Arctic variability in the model would impact the prediction of seasonal rainfall over the SWUS, at various time scales. Imposing tropical variability improves the representation of the observed North Pacific atmospheric circulation, and the associated SWUS seasonal precipitation. This is also the case at the subseasonal time scale due to the inclusion of the Madden-Julian Oscillation (MJO) in the model. When additional nudging is applied in the Arctic, the model skill improves even further, suggesting that improving seasonal predictions in high latitudes may also benefit prediction of SWUS precipitation. An interesting finding of our study is that subseasonal variability represents a source of noise (i.e., limited predictability) for the seasonal time scale. This is because when prescribed in the model, subseasonal variability, mostly the MJO, weakens the El Niño Southern Oscillation (ENSO) teleconnection with SWUS precipitation. Such knowledge may benefit S2S and seasonal prediction as it shows that depending on the amount of subseasonal activity in the tropics on a given year, better skill may be achieved in predicting subseasonal rather than seasonal rainfall anomalies, and conversely.

scholarly journals Developing Gridded Climate Data Sets of Precipitation for Greece Based on Homogenized Time Series

Climate ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 68 ◽  
Author(s):  
Flora Gofa ◽  
Anna Mamara ◽  
Manolis Anadranistakis ◽  
Helena Flocas
Keyword(s):  
Climate Model ◽  
Interpolation Method ◽  
Region Of Interest ◽  
Data Sets ◽  
Monthly Precipitation ◽  
Climate Data ◽  
Variable Nature ◽  
Wide Range ◽  
Realistic Representation ◽  
Space Data

The creation of realistic gridded precipitation fields improves our understanding of the observed climate and is necessary for validating climate model output for a wide range of applications. The challenge in trying to represent the highly variable nature of precipitation is to overcome the lack of density of observations in both time and space. Data sets of mean monthly and annual precipitations were developed for Greece in gridded format with an analysis of 30 arcsec (∼800 m) based on data from 1971 to 2000. One hundred and fifty-seven surface stations from two different observation networks were used to cover a satisfactory range of elevations. Station data were homogenized and subjected to quality control to represent changes in meteorological conditions rather than changes in the conditions under which the observations were made. The Meteorological Interpolation based on Surface Homogenized Data Basis (MISH) interpolation method was used to develop data sets that reproduce, as closely as possible, the spatial climate patterns over the region of interest. The main geophysical factors considered for the interpolation of mean monthly precipitation fields were elevation, latitude, incoming solar irradiance, Euclidian distance from the coastline, and land-to-sea percentage. Low precipitation interpolation uncertainties estimated with the cross-validation method provided confidence in the interpolation method. The resulting high-resolution maps give an overall realistic representation of precipitation, especially in fall and winter, with a clear longitudinal dependence on precipitation decreasing from western to eastern continental Greece.

Analysing Conceptual Climate Models with Monte Carlo Basin Bifurcation Analysis

2020 ◽  
Author(s):  
Maximilian Gelbrecht ◽  
Jürgen Kurths ◽  
Frank Hellmann
Keyword(s):  
Monte Carlo ◽  
Complex Systems ◽  
Bifurcation Analysis ◽  
Climate Models ◽  
Climate Model ◽  
Initial Conditions ◽  
Balance Model ◽  
High Dimensional ◽  
Asymptotic State ◽  
Wide Range

<p>Many high-dimensional complex systems such as climate models exhibit an enormously complex landscape of possible asymptotic state. On most occasions these are challenging to analyse with traditional bifurcation analysis methods. Often, one is also more broadly interested in classes of asymptotic states. Here, we present a novel numerical approach prepared for analysing such high-dimensional multistable complex systems: Monte Carlo Basin Bifurcation Analysis (MCBB).<span>  </span>Based on random sampling and clustering methods, we identify the type of dynamic regimes with the largest basins of attraction and track how the volume of these basins change with the system parameters. In order to due this suitable, easy to compute, statistics of trajectories with randomly generated initial conditions and parameters are clustered by an algorithm such as DBSCAN. Due to the modular and flexible nature of the method, it has a wide range of possible applications. While initially oscillator networks were one of the main applications of this methods, here we present an analysis of a simple conceptual climate model setup up by coupling an energy balance model to the Lorenz96 system. The method is available to use as a package for the Julia language.<span> </span></p>

scholarly journals Reproducibility of Seasonal Land Surface Climate

2006 ◽  
Vol 7 (1) ◽  
pp. 114-136 ◽  
Author(s):  
Thomas J. Phillips
Keyword(s):  
Land Surface ◽  
Seasonal Cycle ◽  
General Circulation ◽  
Climate Model ◽  
Initial Conditions ◽  
Southern Oscillation ◽  
Circulation Model ◽  
Seasonal Prediction ◽  
Climate Simulation ◽  
Continental Climate

Abstract In this study, the sensitivity of the continental seasonal climate to initial conditions is estimated from an ensemble of decadal simulations of an atmospheric general circulation model with the same specifications of radiative forcings and monthly ocean boundary conditions, but with different initial states of atmosphere and land. As measures of the “reproducibility” of continental climate for different initial conditions, spatiotemporal correlations are computed across paired realizations of 11 model land surface variables in which the seasonal cycle is either included or excluded—the former case being pertinent to climate simulation and the latter to seasonal prediction. It is found that the land surface variables that include the seasonal cycle are impacted only marginally by changes in initial conditions; moreover, their seasonal climatologies exhibit high spatial reproducibility. In contrast, the reproducibility of a seasonal land surface anomaly is generally low, although it is substantially higher in the Tropics; its spatial reproducibility also markedly fluctuates in tandem with warm and cold phases of the El Niño–Southern Oscillation. However, the overall degree of reproducibility depends on the particular land surface anomaly considered. It is also shown that the predictability of a land surface anomaly implied by its reproducibility statistics is consistent with what is inferred from more conventional predictability metrics. Implications of these results for climate model intercomparison projects and for operational forecasts of seasonal continental climate also are elaborated.

scholarly journals Description of the resolution hierarchy of the global coupled HadGEM3-GC3.1 model as used in CMIP6 HighResMIP experiments

2019 ◽  
Vol 12 (12) ◽  
pp. 4999-5028 ◽  
Author(s):  
Malcolm J. Roberts ◽  
Alex Baker ◽  
Ed W. Blockley ◽  
Daley Calvert ◽  
Andrew Coward ◽  
...  
Keyword(s):  
Experimental Design ◽  
Ocean Circulation ◽  
Climate Model ◽  
Initial Conditions ◽  
Southern Oscillation ◽  
Global Climate Model ◽  
Coupled Model ◽  
Climate Simulation ◽  
Model Biases ◽  
The Impact

Abstract. The Coupled Model Intercomparison Project phase 6 (CMIP6) HighResMIP is a new experimental design for global climate model simulations that aims to assess the impact of model horizontal resolution on climate simulation fidelity. We describe a hierarchy of global coupled model resolutions based on the Hadley Centre Global Environment Model 3 – Global Coupled vn 3.1 (HadGEM3-GC3.1) model that ranges from an atmosphere–ocean resolution of 130 km–1∘ to 25 km–1∕12∘, all using the same forcings and initial conditions. In order to make such high-resolution simulations possible, the experiments have a short 30-year spinup, followed by at least century-long simulations with constant forcing to assess drift. We assess the change in model biases as a function of both atmosphere and ocean resolution, together with the effectiveness and robustness of this new experimental design. We find reductions in the biases in top-of-atmosphere radiation components and cloud forcing. There are significant reductions in some common surface climate model biases as resolution is increased, particularly in the Atlantic for sea surface temperature and precipitation, primarily driven by increased ocean resolution. There is also a reduction in drift from the initial conditions both at the surface and in the deeper ocean at higher resolution. Using an eddy-present and eddy-rich ocean resolution enhances the strength of the North Atlantic ocean circulation (boundary currents, overturning circulation and heat transport), while an eddy-present ocean resolution has a considerably reduced Antarctic Circumpolar Current strength. All models have a reasonable representation of El Niño–Southern Oscillation. In general, the biases present after 30 years of simulations do not change character markedly over longer timescales, justifying the experimental design.

Robust ENSO across a Wide Range of Climates

2014 ◽  
Vol 27 (15) ◽  
pp. 5836-5850 ◽  
Author(s):  
Georgy E. Manucharyan ◽  
Alexey V. Fedorov
Keyword(s):  
Temperature Gradient ◽  
Climate Model ◽  
Southern Oscillation ◽  
Stability Index ◽  
Tropical Pacific ◽  
Decay Rates ◽  
Natural Mode ◽  
Wide Range ◽  
The Mean ◽  
East West

Abstract El Niño–Southern Oscillation (ENSO) is a pronounced mode of climate variability that originates in the tropical Pacific and affects weather patterns worldwide. Growing evidence suggests that despite extensive changes in tropical climate, ENSO was active over vast geological epochs stretching millions of years from the late Cretaceous to the Holocene. In particular, ENSO persisted during the Pliocene, when a dramatic reduction occurred in the mean east–west temperature gradient in the equatorial Pacific. The mechanisms for sustained ENSO in such climates are poorly understood. Here a comprehensive climate model is used to simulate ENSO for a broad range of tropical Pacific mean climates characterized by different climatological SST gradients. It is found that the simulated ENSO remains surprisingly robust: when the east–west gradient is reduced from 6° to 1°C, the amplitude of ENSO decreases only by 30%–40%, its dominant period remains close to 3–4 yr, and the spectral peak stays above red noise. To explain these results, the magnitude of ocean–atmosphere feedbacks that control the stability of the natural mode of ENSO (the Bjerknes stability index) is evaluated. It is found that as a result of reorganization of the atmospheric Walker circulation in response to changes in the mean surface temperature gradient, the growth/decay rates of the ENSO mode stay nearly constant throughout different climates. These results explain the persistence of ENSO in the past and, in particular, reconcile the seemingly contradictory findings of ENSO occurrence and the small mean east–west temperature gradient during the Pliocene.

scholarly journals The Land Surface Contribution to the Potential Predictability of Boreal Summer Season Climate

2005 ◽  
Vol 6 (5) ◽  
pp. 618-632 ◽  
Author(s):  
Paul A. Dirmeyer
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Climate Model ◽  
Initial Conditions ◽  
Surface Fluxes ◽  
Boreal Summer ◽  
Potential Predictability ◽  
Noise Component ◽  
Near Surface ◽  
Soil Wetness

Abstract The role of the land surface in contributing to the potential predictability of the boreal summer climate is investigated with a coupled land–atmosphere climate model. Ensemble simulations for 1982–99 have been conducted with specified observed sea surface temperatures (SSTs). Several treatments of the land surface are investigated: climatological land surface initialization, realistic initialization of soil wetness, and a series of experiments where downward surface fluxes over land are replaced with observed proxies of precipitation, shortwave, and longwave radiation. Without flux replacement the model exhibits strong drift in soil wetness and both systematic errors and poor simulation of interannual variations of precipitation and near-surface temperature. With flux replacement there are large improvements in simulation of both spatial patterns and interannual variability of precipitation and surface temperature. The land surface apparently does contribute, through positive feedback with the atmosphere, to regional climate anomalies. However, because of the sizeable noise component in precipitation, the strong land–atmosphere feedback may not translate into reliable enhancements in predictability, particularly in years of weak anomalies in the land surface initial conditions at the start of boreal summer.

scholarly journals Description of the resolution hierarchy of the global coupled HadGEM3-GC3.1 model as used in CMIP6 HighResMIP experiments

2019 ◽  
Author(s):  
Malcolm J. Roberts ◽  
Alex Baker ◽  
Ed W. Blockley ◽  
Daley Calvert ◽  
Andrew Coward ◽  
...  
Keyword(s):  
Experimental Design ◽  
Ocean Circulation ◽  
Climate Model ◽  
Initial Conditions ◽  
Southern Oscillation ◽  
Global Climate Model ◽  
Horizontal Resolution ◽  
Climate Simulation ◽  
Model Biases ◽  
The Impact

Abstract. CMIP6 HighResMIP is a new experimental design for global climate model simulations that aims to assess the impact of model horizontal resolution on climate simulation fidelity. We describe a hierarchy of global coupled model resolutions based on the HadGEM3-GC3.1 model that range from an atmosphere-ocean resolution of 130 km-1° to 25 km-1/12°, all using the same forcings and initial conditions. In order to make such high resolution simulations possible, the experiments have a short 30 year spinup, followed by at least century-long simulations with both constant forcing (to assess drift and the focus of this work), and historic forcing. We assess the change in model biases as a function of both atmosphere and ocean resolution, together with the effectiveness and robustness of this new experimental design. We find reductions in the biases in top of atmosphere radiation components and cloud forcing. There are significant reductions in some common surface climate model biases as resolution is increased, particularly in the Atlantic for sea surface temperature and precipitation, primarily driven by increased ocean resolution. There is also a reduction in drift from the initial conditions both at the surface and in the deeper ocean at higher resolution. Using an eddy-present and eddy-rich ocean resolution enhances the strength of the North Atlantic ocean circulation (boundary currents, overturning circulation and heat transports), while an eddy-present ocean resolution has a considerably reduced Antarctic Circumpolar Current strength. All models have a reasonable representation of El Nino – Southern Oscillation. In general the biases present after 30 years of simulations do not change character markedly over longer timescales, justifying the experimental design.

scholarly journals On the generation of internal waves by river plumes in subcritical initial conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
R. Mendes ◽  
J. C. B. da Silva ◽  
J. M. Magalhaes ◽  
B. St-Denis ◽  
D. Bourgault ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
Internal Waves ◽  
Coastal Waters ◽  
Initial Conditions ◽  
Spatial Scales ◽  
River Plumes ◽  
Wide Range ◽  
Near Shore ◽  
Generation Mechanisms ◽  
Douro River

AbstractInternal waves (IWs) in the ocean span across a wide range of time and spatial scales and are now acknowledged as important sources of turbulence and mixing, with the largest observations having 200 m in amplitude and vertical velocities close to 0.5 m s−1. Their origin is mostly tidal, but an increasing number of non-tidal generation mechanisms have also been observed. For instance, river plumes provide horizontally propagating density fronts, which were observed to generate IWs when transitioning from supercritical to subcritical flow. In this study, satellite imagery and autonomous underwater measurements are combined with numerical modeling to investigate IW generation from an initial subcritical density front originating at the Douro River plume (western Iberian coast). These unprecedented results may have important implications in near-shore dynamics since that suggest that rivers of moderate flow may play an important role in IW generation between fresh riverine and coastal waters.

scholarly journals Incorrect Asian aerosols affecting the attribution and projection of regional climate change in CMIP6 models

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhili Wang ◽  
Lei Lin ◽  
Yangyang Xu ◽  
Huizheng Che ◽  
Xiaoye Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Impact Analysis ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern China ◽  
Coupled Model ◽  
Regional Climate Change ◽  
Anthropogenic Aerosol ◽  
Wide Range

AbstractAnthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

Sign in / Sign up

Export Citation Format

Share Document