scholarly journals Coupled Variability and Predictability in a Stochastic Climate Model of the Tropical Atlantic

2008 ◽  
Vol 21 (23) ◽  
pp. 6247-6259 ◽  
Author(s):  
Faming Wang ◽  
Ping Chang
Keyword(s):  
Climate Model ◽  
Dominant Role ◽  
Error Variance ◽  
Ocean Dynamics ◽  
Tropical Atlantic ◽  
Coupled Models ◽  
Stochastic Forcing ◽  
Predictive Skill ◽  
Stochastic Climate Model ◽  
Coupled Variability

Abstract The coupled variability and predictability of the tropical Atlantic ocean–atmosphere system were analyzed within the framework of a linear stochastic climate model. Despite the existence of a meridional dipole as the leading mode, tropical Atlantic variability (TAV) is dominated by equatorial features and the subtropical variability is largely uncorrelated between the northern and southern Atlantic. This suggests that atmospheric stochastic forcing plays a dominant role in defining the spatial patterns of TAV, whereas the active air–sea feedbacks mainly enhance variability at interannual and decadal time scales, causing the spectra distinctive from the red spectrum. Under the stochastic forcing, the useful predictive skill for sea surface temperature measured by normalized error variance is limited to 2 months on average, which is 1 month longer than the predictive skill of damped persistence, indicating that the contribution of ocean dynamics and air–sea feedbacks is moderate in the tropical Atlantic. To achieve maximum predictability, processes such as ocean dynamics, thermodynamical and dynamical air–sea feedbacks, and the delicate mode–mode interactions should be correctly resolved in the coupled models. Therefore, predicting TAV poses more challenge than predicting El Niño in the tropical Pacific.

scholarly journals Weaker AMOC in coupled models inhibits north tropical Atlantic impact on ENSO

2020 ◽  
Author(s):  
Belen Rodriguez-Fonseca ◽  
Irene Polo ◽  
Elsa Mohino ◽  
Teresa Losada ◽  
Marta Martín-Rey ◽  
...  
Keyword(s):  
Climate Model ◽  
Boreal Summer ◽  
Tropical Atlantic ◽  
Coupled Models ◽  
Tropical North Atlantic ◽  
Different Seasons ◽  
Climate Model Simulations ◽  
Open Question ◽  
First Time ◽  
Atlantic Itcz

<p align="justify"><span>Observational studies have reported that interannual variability of sea surface temperature in two tropical Atlantic regions can act as ENSO predictors in different seasons and periods: boreal summer Atlantic Nino (AN) in negative phases of the Atlantic Multidecadal Variabil- ˜ ity (AMV); and boreal spring tropical north Atlantic (TNA) in positive AMV. The robustness of the AMV role in the interbasin connection remains an open question due to the short observational record. Using observations and pre-industrial climate model simulations, we demonstrate for the first time that latitudinal displacements of the Atlantic ITCZ act as a switch for the type of inter-basin teleconnection. During periods in which the Atlantic ITCZ is further equatorward (northward) AN (TNA) impacts ENSO. This ITCZ location can be 1 affected by several factors, including the inter-hemispheric SST gradients associated with AMV.Coupled models success in capturing the AN-ENSO connection. Nevertheless, they have difficulties in reproducing the TNA-ENSO connection because they overestimate rainfall in the southern tropical Atlantic. The TNA-ENSO connection occurs sporadically during periods when the ITCZ is shifted further northward in association with strong heat transports by the AMOC. Weaker AMOC periods in coupled models don't present the TNA-ENSO connection. State-of-the-art models still need to improve for correctly representing tropical Atlantic impact on ENSO.</span></p>

Dynamics of Interdecadal Climate Variability: A Historical Perspective*

2012 ◽  
Vol 25 (6) ◽  
pp. 1963-1995 ◽  
Author(s):  
Zhengyu Liu
Keyword(s):  
Climate Variability ◽  
Time Scale ◽  
Ocean Dynamics ◽  
Interdecadal Variability ◽  
Driving Mechanism ◽  
Stochastic Forcing ◽  
The Pacific ◽  
Ocean Atmosphere ◽  
Almost All ◽  
Interdecadal Climate Variability

Abstract The emerging interest in decadal climate prediction highlights the importance of understanding the mechanisms of decadal to interdecadal climate variability. The purpose of this paper is to provide a review of our understanding of interdecadal climate variability in the Pacific and Atlantic Oceans. In particular, the dynamics of interdecadal variability in both oceans will be discussed in a unified framework and in light of historical development. General mechanisms responsible for interdecadal variability, including the role of ocean dynamics, are reviewed first. A hierarchy of increasingly complex paradigms is used to explain variability. This hierarchy ranges from a simple red noise model to a complex stochastically driven coupled ocean–atmosphere mode. The review suggests that stochastic forcing is the major driving mechanism for almost all interdecadal variability, while ocean–atmosphere feedback plays a relatively minor role. Interdecadal variability can be generated independently in the tropics or extratropics, and in the Pacific or Atlantic. In the Pacific, decadal–interdecadal variability is associated with changes in the wind-driven upper-ocean circulation. In the North Atlantic, some of the multidecadal variability is associated with changes in the Atlantic meridional overturning circulation (AMOC). In both the Pacific and Atlantic, the time scale of interdecadal variability seems to be determined mainly by Rossby wave propagation in the extratropics; in the Atlantic, the time scale could also be determined by the advection of the returning branch of AMOC in the Atlantic. One significant advancement of the last two decades is the recognition of the stochastic forcing as the dominant generation mechanism for almost all interdecadal variability. Finally, outstanding issues regarding the cause of interdecadal climate variability are discussed. The mechanism that determines the time scale of each interdecadal mode remains one of the key issues not understood. It is suggested that much further understanding can be gained in the future by performing specifically designed sensitivity experiments in coupled ocean–atmosphere general circulation models, by further analysis of observations and cross-model comparisons, and by combining mechanistic studies with decadal prediction studies.

scholarly journals The Linear Response of ENSO to the Madden–Julian Oscillation

2005 ◽  
Vol 18 (13) ◽  
pp. 2441-2459 ◽  
Author(s):  
J. Zavala-Garay ◽  
C. Zhang ◽  
A. M. Moore ◽  
R. Kleeman
Keyword(s):  
Large Fraction ◽  
Surface Wind ◽  
Low Frequency ◽  
Coupled Model ◽  
Cumulative Effect ◽  
Enso Event ◽  
Kelvin Waves ◽  
Madden Julian Oscillation ◽  
Coupled Models ◽  
Stochastic Forcing

Abstract The possibility that the tropical Pacific coupled system linearly amplifies perturbations produced by the Madden–Julian oscillation (MJO) is explored. This requires an estimate of the low-frequency tail of the MJO. Using 23 yr of NCEP–NCAR reanalyses of surface wind and Reynolds SST, we show that the spatial structure that dominates the intraseasonal band (i.e., the MJO) also dominates the low-frequency band once the anomalies directly related to ENSO have been removed. This low-frequency contribution of the intraseasonal variability is not included in most ENSO coupled models used to date. Its effect in a coupled model of intermediate complexity has, therefore, been studied. It is found that this “MJO forcing” (τMJO) can explain a large fraction of the interannual variability in an asymptotically stable version of the model. This interaction is achieved via linear dynamics. That is, it is the cumulative effect of individual events that maintains ENSOs in this model. The largest coupled wind anomalies are initiated after a sequence of several downwelling Kelvin waves of the same sign have been forced by τMJO. The cumulative effect of the forced Kelvin waves is to persist the (small) SST anomalies in the eastern Pacific just enough for the coupled ocean–atmosphere dynamics to amplify the anomalies into a mature ENSO event. Even though τMJO explains just a small fraction of the energy contained in the stress not associated with ENSO, a large fraction of the modeled ENSO variability is excited by this forcing. The characteristics that make τMJO an optimal stochastic forcing for the model are discussed. The large zonal extent is an important factor that differentiates the MJO from other sources of stochastic forcing.

scholarly journals Application of remote sensing to the study of the pelagic spiny lobster larval transport in the Tropical Atlantic

2009 ◽  
Vol 57 (1) ◽  
pp. 7-16 ◽  
Author(s):  
Camila Aguirre Góes Rudorff ◽  
João Antônio Lorenzzetti ◽  
Douglas F. M. Gherardi ◽  
Jorge Eduardo Lins-Oliveira
Keyword(s):  
Diffusion Model ◽  
Satellite Data ◽  
El Niño ◽  
El Nino ◽  
Spiny Lobster ◽  
Ocean Dynamics ◽  
Tropical Atlantic ◽  
Geostrophic Current ◽  
Advection Diffusion ◽  
Larval Dispersion

The connectivity of marine populations via larval dispersal is crucial for the maintenance of fisheries production and biodiversity. Because larval dispersion takes place on different spatial scales, global operational satellite data can be successfully used to investigate the connectivity of marine populations on different spatial and temporal scales. In fact, satellite data have long been used for the study of the large and mesoscale biological processes associated with ocean dynamics. This paper presents simulations of spiny lobster larvae transport in the Tropical Atlantic using the geostrophic currents, generated by altimetry that feeds an advection/diffusion model. Simulations were conducted over the Tropical Atlantic (20ºN to 15ºS), considering four larvae release areas: the Cape Verde Archipelago, the Ivory Coast, Ascension Island and Fernando de Noronha Archipelago. We used mean geostrophic current (MGC) calculated from 2001 to 2005 to represent the mean circulation of the Tropical Atlantic. We also ran the model for the El Niño geostrophic current regime (ENGC) using part of the MGC data, representing the El Niño 2002/2003 event. Results suggest that the intensification of the mesoscale ocean processes associated with El Niño events promotes the connectivity between populations, increasing the chances of a genetic flux among different stocks. We concluded that the altimetry geostrophic current data together with a relatively simple advection/diffusion model can provide useful information about the physical dynamics necessary to conduct studies on larval dispersion.

scholarly journals Improving the potential accuracy and usability of EURO-CORDEX estimates of future rainfall climate using frequentist model averaging

2021 ◽  
Vol 28 (3) ◽  
pp. 329-346
Author(s):  
Stephen Jewson ◽  
Giuliana Barbato ◽  
Paola Mercogliano ◽  
Jaroslav Mysiak ◽  
Maximiliano Sassi
Keyword(s):  
Climate Model ◽  
Model Averaging ◽  
Large Data ◽  
Statistical Testing ◽  
Complex Method ◽  
Distribution Fitting ◽  
Data Set ◽  
Potential Accuracy ◽  
Predictive Skill ◽  
Ensemble Mean

Abstract. Probabilities of future climate states can be estimated by fitting distributions to the members of an ensemble of climate model projections. The change in the ensemble mean can be used as an estimate of the change in the mean of the real climate. However, the level of sampling uncertainty around the change in the ensemble mean varies from case to case and in some cases is large. We compare two model-averaging methods that take the uncertainty in the change in the ensemble mean into account in the distribution fitting process. They both involve fitting distributions to the ensemble using an uncertainty-adjusted value for the ensemble mean in an attempt to increase predictive skill relative to using the unadjusted ensemble mean. We use the two methods to make projections of future rainfall based on a large data set of high-resolution EURO-CORDEX simulations for different seasons, rainfall variables, representative concentration pathways (RCPs), and points in time. Cross-validation within the ensemble using both point and probabilistic validation methods shows that in most cases predictions based on the adjusted ensemble means show higher potential accuracy than those based on the unadjusted ensemble mean. They also perform better than predictions based on conventional Akaike model averaging and statistical testing. The adjustments to the ensemble mean vary continuously between situations that are statistically significant and those that are not. Of the two methods we test, one is very simple, and the other is more complex and involves averaging using a Bayesian posterior. The simpler method performs nearly as well as the more complex method.

scholarly journals Improving the simulation of global aerosol with size-segregated anthropogenic number emissions

2017 ◽  
Author(s):  
Filippo Xausa ◽  
Pauli Paasonen ◽  
Risto Makkonen ◽  
Mikhail Arshinov ◽  
Aijun Ding ◽  
...  
Keyword(s):  
Particle Number ◽  
Climate Models ◽  
Climate Model ◽  
Dominant Role ◽  
Particle Diameter ◽  
Radiation Budget ◽  
Size Distributions ◽  
Anthropogenic Aerosol ◽  
Accumulation Mode ◽  
Climate Interactions

Abstract. Climate models are important tools that are used for generating climate change projections, in which aerosol-climate interactions are one of the main sources of uncertainties. In order to quantify aerosol-radiation and aerosol-cloud interactions, detailed input of anthropogenic aerosol number emissions is necessary. However, the anthropogenic aerosol number emissions are usually converted from the corresponding mass emissions in precompiled emission inventories through a very simplistic method depending uniquely on chemical composition, particle size and density, which are defined for a few very wide main source sectors. In this work, the anthropogenic particle number emissions converted from the AeroCom mass in the ECHAM-HAM climate model were replaced with the recently-formulated number emissions from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS)-model, where the emission number size distributions vary, for example, with respect to the fuel and technology. A special attention in our analysis was put on accumulation mode particles (particle diameter dp > 100 nm) because of (i) their capability of acting as cloud condensation nuclei (CCN), thus forming cloud droplets and affecting Earth's radiation budget, and (ii) their dominant role in forming the coagulation sink and thus limiting the concentration of sub-100 nanometers particles. In addition, the estimates of anthropogenic CCN formation, and thus the forcing from aerosol-climate interactions are expected to be affected. Analysis of global particle number concentrations and size distributions reveal that GAINS implementation increases CCN concentration compared with AeroCom, with regional enhancement factors reaching values as high as 10. A comparison between modeled and observed concentrations shows that the increase in number concentration for accumulation mode particle agrees well with measurements, but it leads to a consistent underestimation of both nucleation mode and Aitken mode (dp > 100 nm) particle number concentrations. This suggests that revisions are needed in the new particle formation and growth schemes currently applied in global modeling frameworks.

tamh tm iedor sphere -1 el 9a8 ti 0vse , lyc li s m im a p te le models. Much more detailed than in the Australian region (Simpson and Downey 1975; run. Rather they are models than simp allysofomuuscehdm ro ourte in eelxypesn in si cvee th to e V ha osicbe ee anndfoH rc uendt 198 recasting El Nino behav­ tures for the p w er iitohd4o ). bsT1eh rv e BMRC climate model iour (e.g., sea surface temperatures in the east simulated by the model ha 9s49e -d 9 1 se , aasnud rf ac th eet em ra p in efraal ­ lfeoqrueactaosrti al r Pacific), they could, in theory, be used to ob been compared with the coupling o ai fnftahleloacnedantetmoptehrea tu artemoosvpehre re la nidn . th Tehseew te asse rv ru end ra fiinvfea ll t i ( m Fr eesd , er w ik istehne th teal. s1a9m9e5 ). seTahesm ur o fa dceelmmo od deellss , ( hPoowweevrere , tis less than perfect. Improved ocean ph m er p ic e ra ctoun re d s it io bnust . s T li h ghtly different starting atmos­ these coupled mode alls . . 1995) are being developed for ialg lu rseterm ate esnttw he it h ‘ noobisseer ’ veind iffe ed rtahier ence betw nfa m ll, o w de e l . neTeoenge th t e ed to av mru uns O era cghep se aarsto ne pro onfalthperebd le ic m ti own it ihstthheeduisfef ic oufltcy oupled models in all five runs as an ‘ens coupled models has in sitmhue la attim ng osrp ai hnefrailclA of u st p ra rleicainpp it raetc io ip n i tat sihoon, w em abtls le’. eoam st e The en o ve srkin ll sem o rt ihne bl sei ave rn Amuusl rag t a ra ti lnegsgoennte he ia. (Ni ra l sp su a c ti caelsssca in le ssiimmuploartt in an gtaftomrousspeh rs e , ridcesvpairtieab th il e it iyr Fur T th h e es resoau tm th o , stphheem ri odels are less successful. sea cshuo rf l a ls ce1t9e9m6p ) e . ra M tu ordeealneoxmpaelriiemsehnatvsewailtohngspheicsitfo ie ry djtohb er e o fo f re si m pr uolbaa ti bnlgyc th cemSoOdIel ( eFx ig pe urrieme3n .3 ts ) . do ThaegSoO od I an be predicted without the need

Droughts ◽  
2016 ◽  
pp. 77-77
Keyword(s):  
El Niño ◽  
Climate Model ◽  
El Nino ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Coupled Models ◽  
Coupled Mode ◽  
Australian Region ◽  
Surface Temperatures

scholarly journals Contributions of Atmospheric Stochastic Forcing and Intrinsic Ocean Modes to North Atlantic Ocean Interdecadal Variability

2020 ◽  
Vol 33 (6) ◽  
pp. 2351-2370 ◽  
Author(s):  
Olivier Arzel ◽  
Thierry Huck
Keyword(s):  
Ocean Circulation ◽  
North Atlantic ◽  
General Circulation ◽  
Thermal Structure ◽  
Ocean Dynamics ◽  
Dimensionless Number ◽  
Stochastic Forcing ◽  
The North ◽  
Wide Range ◽  
The North Atlantic

AbstractAtmospheric stochastic forcing associated with the North Atlantic Oscillation (NAO) and intrinsic ocean modes associated with the large-scale baroclinic instability of the North Atlantic Current (NAC) are recognized as two strong paradigms for the existence of the Atlantic multidecadal oscillation (AMO). The degree to which each of these factors contribute to the low-frequency variability of the North Atlantic is the central question in this paper. This issue is addressed here using an ocean general circulation model run under a wide range of background conditions extending from a supercritical regime where the oceanic variability spontaneously develops in the absence of any atmospheric noise forcing to a damped regime where the variability requires some noise to appear. The answer to the question is captured by a single dimensionless number Γ measuring the ratio between the oceanic and atmospheric contributions, as inferred from the buoyancy variance budget of the western subpolar region. Using this diagnostic, about two-thirds of the sea surface temperature (SST) variance in the damped regime is shown to originate from atmospheric stochastic forcing whereas heat content is dominated by internal ocean dynamics. Stochastic wind stress forcing is shown to substantially increase the role played by damped ocean modes in the variability. The thermal structure of the variability is shown to differ fundamentally between the supercritical and damped regimes, with abrupt modifications around the transition between the two regimes. Ocean circulation changes are further shown to be unimportant for setting the pattern of SST variability in the damped regime but are fundamental for a preferred time scale to emerge.

scholarly journals Numerical Development and Evaluation of an Energy Conserving Conceptual Stochastic Climate Model

2019 ◽  
Vol 5 (1) ◽  
pp. 45-64 ◽  
Author(s):  
Federica Gugole ◽  
Christian L. E. Franzke
Keyword(s):  
Energy Conservation ◽  
Total Energy ◽  
Prediction Models ◽  
Climate Model ◽  
Empirical Orthogonal Functions ◽  
Correlated Noise ◽  
Spatial Covariance ◽  
Conservation Of Energy ◽  
Stochastic Climate Model ◽  
Energy Conserving

AbstractIn this study we aim to present the successful development of an energy conserving conceptual stochastic climate model based on the inviscid 2-layer Quasi-Geostrophic (QG) equations. The stochastic terms have been systematically derived and introduced in such away that the total energy is conserved. In this proof of concept studywe give particular emphasis to the numerical aspects of energy conservation in a highdimensional complex stochastic system andwe analyzewhat kind of assumptions regarding the noise should be considered in order to obtain physical meaningful results. Our results show that the stochastic model conserves energy to an accuracy of about 0.5% of the total energy; this level of accuracy is not affected by the introduction of the noise, but is mainly due to the level of accuracy of the deterministic discretization of the QG model. Furthermore, our results demonstrate that spatially correlated noise is necessary for the conservation of energy and the preservation of important statistical properties, while using spatially uncorrelated noise violates energy conservation and gives unphysical results. A dynamically consistent spatial covariance structure is determined through Empirical Orthogonal Functions (EOFs). We find that only a small number of EOFs is needed to get good results with respect to energy conservation, autocorrelation functions, PDFs and eddy length scale when comparing a deterministic control simulation on a 512 × 512 grid to a stochastic simulation on a 128 × 128 grid. Our stochastic approach has the potential to seamlessly be implemented in comprehensive weather and climate prediction models.

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