scholarly journals SST-Forced Atmospheric Variability in an Atmospheric General Circulation Model

2005 ◽  
Vol 18 (19) ◽  
pp. 3953-3967 ◽  
Author(s):  
Arun Kumar ◽  
Qin Zhang ◽  
Peitao Peng ◽  
Bhaskar Jha
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
Southern Oscillation ◽  
Higher Order ◽  
Dominant Mode ◽  
Atmospheric Response ◽  
Response Patterns ◽  
Seasonal Predictability ◽  
Anomaly Correlation ◽  
Geographical Regions

Abstract From ensembles of 80 AGCM simulations for every December–January–February (DJF) seasonal mean in the 1980–2000 period, interannual variability in atmospheric response to interannual variations in observed sea surface temperature (SST) is analyzed. A unique facet of this study is the use of large ensemble size that allows identification of the atmospheric response to SSTs for each DJF in the analysis period. The motivation of this study was to explore what atmospheric response patterns beyond the canonical response to El Niño–Southern Oscillation (ENSO) SST anomalies exist, and to which SST forcing such patterns may be related. A practical motivation for this study was to seek sources of atmospheric predictability that may lead to improvements in seasonal predictability efforts. This analysis was based on the EOF technique applied to the ensemble mean 200-mb height response. The dominant mode of the atmospheric response was indeed the canonical atmospheric response to ENSO; however, this mode only explained 53% of interannual variability of the ensemble means (often referred to as the external variability). The second mode, explaining 19% of external variability, was related to a general increase (decrease) in the 200-mb heights related to a Tropicwide warming (cooling) in SSTs. The third dominant mode, explaining 12% of external variability, was similar to the mode identified as the “nonlinear” response to ENSO in earlier studies. The realism of different atmospheric response patterns was also assessed from a comparison of anomaly correlations computed between different renditions of AGCM-simulated atmospheric responses and the observed 200-mb height anomalies. For example, the anomaly correlation between the atmospheric response reconstructed from the first mode alone and the observations was compared with the anomaly correlation when the atmospheric response was reconstructed including modes 2 and 3. If the higher-order atmospheric response patterns obtained from the AGCM simulations had observational counterparts, their inclusion in the reconstructed atmospheric response should lead to higher anomaly correlations. Indeed, at some geographical regions, an increase in anomaly correlation with the inclusion of higher modes was found, and it is concluded that the higher-order atmospheric response patterns found in this study may be realistic and may represent additional sources of atmospheric seasonal predictability.

scholarly journals Interannual hydroclimatic variability and its influence on winter nutrient loadings over the Southeast United States

2012 ◽  
Vol 16 (7) ◽  
pp. 2285-2298 ◽  
Author(s):  
J. Oh ◽  
A. Sankarasubramanian
Keyword(s):  
Interannual Variability ◽  
Nutrient Management ◽  
Southern Oscillation ◽  
Management Strategies ◽  
Dominant Mode ◽  
Coefficient Of Determination ◽  
Nutrient Loadings ◽  
Climate Forecasts ◽  
Hydroclimatic Variability ◽  
Low Dimensional

Abstract. It is well established in the hydroclimatic literature that the interannual variability in seasonal streamflow could be partially explained using climatic precursors such as tropical sea surface temperature (SST) conditions. Similarly, it is widely known that streamflow is the most important predictor in estimating nutrient loadings and the associated concentration. The intent of this study is to bridge these two findings so that nutrient loadings could be predicted using season-ahead climate forecasts forced with forecasted SSTs. By selecting 18 relatively undeveloped basins in the Southeast US (SEUS), we relate winter (January-February-March, JFM) precipitation forecasts that influence the JFM streamflow over the basin to develop winter forecasts of nutrient loadings. For this purpose, we consider two different types of low-dimensional statistical models to predict 3-month ahead nutrient loadings based on retrospective climate forecasts. Split sample validation of the predictive models shows that 18–45% of interannual variability in observed winter nutrient loadings could be predicted even before the beginning of the season for at least 8 stations. Stations that have very high coefficient of determination (> 0.8) in predicting the observed water quality network (WQN) loadings during JFM exhibit significant skill in predicting seasonal total nitrogen (TN) loadings using climate forecasts. Incorporating antecedent flow conditions (December flow) as an additional predictor did not increase the explained variance in these stations, but substantially reduced the root-mean-square error (RMSE) in the predicted loadings. Relating the dominant mode of winter nutrient loadings over 18 stations clearly illustrates the association with El Niño Southern Oscillation (ENSO) conditions. Potential utility of these season-ahead nutrient predictions in developing proactive and adaptive nutrient management strategies is also discussed.

scholarly journals A Comparative Analysis of Change in the First and Second Moment of the PDF of Seasonal Mean 200-mb Heights with ENSO SSTs

2009 ◽  
Vol 22 (6) ◽  
pp. 1412-1423 ◽  
Author(s):  
Bhaskar Jha ◽  
Arun Kumar
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
General Circulation Models ◽  
Seasonal Forecast ◽  
Seasonal Predictability ◽  
Second Moment ◽  
Sst Variability ◽  
Atmospheric General Circulation Models ◽  
The Mean ◽  
Probability Density Function Pdf

Abstract Based on simulations from nine different atmospheric general circulation models (AGCMs), a comparative assessment of the influence of ENSO SST variability on the first and second moment of the probability density function (PDF) of 200-mb seasonal mean height is made. This comparison is quantified by regressing the interannual variability in the mean and the spread of the seasonal means against the Niño-3.4 SSTs. Based on the analysis of simulations from multiple AGCMs, it is concluded that the relative impact of interannual variability of SSTs is larger, and more systematic, on the mean of the PDF of 200-mb heights than on its spread. This result implies that seasonal predictability due to SSTs is predominantly a function of its influence on the seasonal mean. Further, for the practice of seasonal predictions, it might be pragmatic to assume that spread of seasonal means stays constant and that the seasonal forecast information resides entirely in the shift of the seasonal mean PDF.

scholarly journals The Nature and Causes for the Delayed Atmospheric Response to El Niño

2003 ◽  
Vol 16 (9) ◽  
pp. 1391-1403 ◽  
Author(s):  
Arun Kumar ◽  
Martin P. Hoerling
Keyword(s):  
El Niño ◽  
General Circulation ◽  
El Nino ◽  
Southern Oscillation ◽  
Circulation Model ◽  
Atmospheric Response ◽  
Maximum Correlation ◽  
Thermal Anomalies ◽  
Sst Variability ◽  
East Pacific

Abstract Remarkable among the atmospheric phenomena associated with El Niño–Southern Oscillation (ENSO) is the lag in the zonal mean tropical thermal anomalies relative to equatorial east Pacific sea surface temperatures (SSTs). For the period 1950–99, the maximum correlation between observed zonal mean tropical 200-mb heights and a Niño-3.4 (5°N–5°S, 120°–170°W) SST index occurs when the atmosphere lags by 1–3 months, consistent with numerous previous studies. Results from atmospheric general circulation model (GCM) simulations forced by the monthly SST variations of the last half-century confirm and establish the robustness of this observed lag. An additional feature of the delay in atmospheric response that involves an apparent memory or lingering of the tropical thermal anomalies several seasons beyond the Niño-3.4 SST index peak is documented in this study. It is characterized by a strong asymmetry in the strength of the zonal mean tropical 200-mb height response relative to that peak, being threefold stronger in the summer following the peak compared to the preceding summer. This occurs despite weaker Niño-3.4 SST forcing in the following summer compared to the preceding summer. The 1–3-month lag in maximum correlation is reconciled by the fact that the rainfall evolution in the tropical Pacific associated with the ENSO SST anomalies itself lags one season, with the latter acting as the immediate forcing for the 200-mb heights. This aspect of the lagged behavior in the tropical atmospheric response occurs independent of any changes in SSTs outside of the tropical east Pacific core region of SST variability related to ENSO. The lingering of the tropical atmospheric thermal signal cannot, however, be reconciled with the ENSO-related SST variability in the tropical eastern Pacific. This part of the tropical atmospheric response is instead intimately tied to the tropical ocean's lagged response to the equatorial east Pacific SST variability, including a warming of the tropical Indian and Atlantic SSTs that peak several seasons after the Niño-3.4 warming peak.

scholarly journals Mechanisms for the Interannual Variability of SST in the East Pacific Warm Pool

2009 ◽  
Vol 22 (6) ◽  
pp. 1375-1392 ◽  
Author(s):  
Kristopher B. Karnauskas ◽  
Antonio J. Busalacchi
Keyword(s):  
Pacific Ocean ◽  
Interannual Variability ◽  
El Niño ◽  
General Circulation ◽  
El Nino ◽  
Southern Oscillation ◽  
Warm Pool ◽  
Equatorial Pacific ◽  
East Pacific ◽  
Pacific Warm Pool

Abstract In comparison with the western and equatorial Pacific Ocean, relatively little is known about the east Pacific warm pool (EPWP). Observations indicate that the interannual variability of sea surface temperature (SST) in the EPWP is highly correlated (0.95) with the El Niño–Southern Oscillation (ENSO). In this paper, an ocean general circulation model (OGCM) of the tropical Pacific Ocean and various atmospheric and oceanic observations are used to diagnose the physical processes governing the interannual variability of SST in the EPWP. Atmospheric forcings for the OGCM are derived purely from satellite observations between 1988 and 2004. Shortwave heating is identified as playing a dominant role in the interannual SST tendency of the EPWP. The high correlation between SST in the EPWP and eastern equatorial Pacific is therefore explained not by ocean processes, but by an atmospheric link. ENSO-driven equatorial SST anomalies modify the distribution of the overlying atmospheric vertical motions and therefore cloud cover and ultimately shortwave heating. During an El Niño event, for example, the ITCZ is equatorward displaced from its normal position over the EPWP, resulting in anomalously large shortwave heating over the EPWP. Analysis of poleward ocean heat transport and coastal Kelvin waves confirms that oceanic processes are not sufficient to explain the interannual variability of the EPWP.

scholarly journals Interannual hydroclimatic variability and its influence on winter nutrients variability over the southeast United States

2011 ◽  
Vol 8 (6) ◽  
pp. 10935-10971 ◽  
Author(s):  
J. Oh ◽  
A. Sankarasubramanian
Keyword(s):  
Interannual Variability ◽  
Nutrient Management ◽  
Southern Oscillation ◽  
Management Strategies ◽  
Dominant Mode ◽  
Nutrient Loadings ◽  
Climate Forecasts ◽  
Southeast Us ◽  
Hydroclimatic Variability ◽  
Low Dimensional

Abstract. It is well established in the hydroclimatic literature that the interannual variability in seasonal streamflow could be partially explained using climatic precursors such as tropical Sea Surface Temperature (SST) conditions. Similarly, it is widely known that streamflow is the most important predictor in estimating nutrient loadings and the associated concentration. The intent of this study is to bridge these two findings so that nutrient loadings could be predicted using season-ahead climate forecasts forced with forecasted SSTs. By selecting 18 relatively undeveloped basins in the Southeast US (SEUS), we relate winter (January-February-March, JFM) precipitation forecasts that influence the JFM streamflow over the basin to develop winter forecasts of nutrient loadings. For this purpose, we consider two different types of low-dimensional statistical models to predict 3-month ahead nutrient loadings based on retrospective climate forecasts. Split sample validation of the predictive models shows that 18–45% of interannual variability in observed winter nutrient loadings could be predicted even before the beginning of the season for at least 8 stations. Stations that have very high R2(LOADEST) (>0.8) in predicting the observed WQN loadings during the winter (Table 2) exhibit significant skill in loadings. Incorporating antecedent flow conditions (December flow) as an additional predictor did not increase the explained variance in these stations, but substantially reduced the RMSE in the predicted loadings. Relating the dominant mode of winter nutrient loadings over 18 stations clearly illustrates the association with El Niño Southern Oscillation (ENSO) conditions. Potential utility of these season-ahead nutrient predictions in developing proactive and adaptive nutrient management strategies is also discussed.

scholarly journals Imprint of chaotic ocean variability on transports in the Southwest Pacific at interannual timescales

2020 ◽  
Author(s):  
Sophie Cravatte ◽  
Guillaume Serazin ◽  
Thierry Penduff ◽  
Christophe Menkes
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Initial Perturbation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Atmospheric Forcing ◽  
Southwest Pacific ◽  
Ocean Variability

Abstract. The Southwest Pacific Ocean sits at a bifurcation where southern subtropical waters are redistributed equatorward and poleward by different ocean currents. The processes governing the interannual variability of these currents are not completely understood. This issue is investigated using a probabilistic modeling strategy that allows disentangling the atmospherically-forced deterministic ocean variability and the chaotic intrinsic ocean variability. A large ensemble of 50 simulations performed with the same ocean general circulation model (OGCM) driven by the same realistic atmospheric forcing that only differ by a small initial perturbation is analyzed over 1980–2015. Our results show that, in the Southwest Pacific, the interannual variability of the transports is strongly dominated by chaotic ocean variability south of 20° S. In the tropics, while the interannual variability of transports and eddy kinetic energy modulation is largely deterministic and explained by El Nino Southern Oscillation (ENSO), ocean nonlinear processes still explain 10 to 20 % of their interannual variance at large-scale. Regions of strong chaotic variance generally coincide with regions of high mesoscale activity, suggesting that a spontaneous inverse cascade is at work from mesoscale toward lower frequencies and larger scales. The spatiotemporal features of the low-frequency oceanic chaotic variability are complex but spatially coherent within certain regions. In the Subtropical Countercurrent area, they appear as interannually-varying, zonally elongated alternating current structures, while in the EAC region, they are eddy-shaped. Given this strong imprint of large-scale chaotic oceanic fluctuations, our results question the attribution of interannual variability to the atmospheric forcing in the region from point-wise observations and one-member simulations.

Effects of mean state of climate models on the response to prescribed forcing: Sensitivity experiments with the SPEEDY general circulation model.

2020 ◽  
Author(s):  
Emanuele Di Carlo ◽  
Paolo Ruggieri ◽  
Paolo Davini ◽  
Stefano Tibaldi ◽  
Susanna Corti
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Southern Oscillation ◽  
Surface Condition ◽  
Circulation Model ◽  
Climate Simulation ◽  
Atmospheric Response ◽  
Large Ensemble ◽  
Mean State

<pre>Understanding how the general circulation of the atmosphere is affected by global warming is one of the grand challenges in climate science. Climate models are a valuable tool to: i) identifying potential mechanism for changes in general circulation, ii) recognizing signals that can be related to external forcing and iii) produce projections for future scenarios. Despite the use of large ensemble of continuosly improving climate models, uncertainty for the extratropical circulation is still large. It is therefore important to understand processes driving the variability of the circulation in climate models and how these processes are affected by model bias. To characterize the effect of models bias on the response to a given forcing, several simulations were performed with the Simplified Parameterizations, primitivE - Equation DYnamics (SPEEDY), an intermediate complexity model developed by International Center for Theoretical Physics (ICTP). Four simulations are performed with a modified orography in order to obtain an atmospheric circulation at mid-latitudes characterized by different mean states and a control climate simulation carried in standard configuration is used as baseline. For each of these experiments, we have studied the climatic response to El Niño Southern Oscillation (ENSO) and to the Atlantic Multidecadal Variability (AMV). All the <em>Sensitivity </em>simulations were performed with a large ensemble (~100 members).</pre> <pre>Results show that indeed the model response is non-negligibly influenced by its mean state and reveal geographic areas where the sensitivity is large. On the other hand, they also show large scale regions of the world where the atmospheric response to ENSO and AMV is unlikely to depend on the atmospheric mean state. We also found that the relationship between changes in the model mean state and the response to the forcing appears to be non linear. These results cam be used to interpret and understand multi-model spread in atmospheric response to aforementioned surface condition.</pre>

scholarly journals Imprint of chaotic ocean variability on transports in the southwestern Pacific at interannual timescales

Ocean Science ◽  
2021 ◽  
Vol 17 (2) ◽  
pp. 487-507
Author(s):  
Sophie Cravatte ◽  
Guillaume Serazin ◽  
Thierry Penduff ◽  
Christophe Menkes
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Initial Perturbation ◽  
Low Frequency ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Atmospheric Forcing ◽  
Ocean Variability

Abstract. The southwestern Pacific Ocean sits at a bifurcation where southern subtropical waters are redistributed equatorward and poleward by different ocean currents. The processes governing the interannual variability of these currents are not completely understood. This issue is investigated using a probabilistic modeling strategy that allows disentangling the atmospherically forced deterministic ocean variability and the chaotic intrinsic ocean variability. A large ensemble of 50 simulations performed with the same ocean general circulation model (OGCM) driven by the same realistic atmospheric forcing and only differing by a small initial perturbation is analyzed over 1980–2015. Our results show that, in the southwestern Pacific, the interannual variability of the transports is strongly dominated by chaotic ocean variability south of 20∘ S. In the tropics, while the interannual variability of transports and eddy kinetic energy modulation are largely deterministic and explained by the El Niño–Southern Oscillation (ENSO), ocean nonlinear processes still explain 10 % to 20 % of their interannual variance at large scale. Regions of strong chaotic variance generally coincide with regions of high mesoscale activity, suggesting that a spontaneous inverse cascade is at work from the mesoscale toward lower frequencies and larger scales. The spatiotemporal features of the low-frequency oceanic chaotic variability are complex but spatially coherent within certain regions. In the Subtropical Countercurrent area, they appear as interannually varying, zonally elongated alternating current structures, while in the EAC (East Australian Current) region, they are eddy-shaped. Given this strong imprint of large-scale chaotic oceanic fluctuations, our results question the attribution of interannual variability to the atmospheric forcing in the region from pointwise observations and one-member simulations.

Successive Modulation of ENSO to the Future Greenhouse Warming

2008 ◽  
Vol 21 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Soon-Il An ◽  
Jong-Seong Kug ◽  
Yoo-Geun Ham ◽  
In-Sik Kang
Keyword(s):  
General Circulation ◽  
Southern Oscillation ◽  
General Circulation Models ◽  
Tropical Pacific ◽  
Greenhouse Warming ◽  
Delayed Response ◽  
Subsurface Temperature ◽  
Climate System Model ◽  
The Mean ◽  
The Tropical Pacific

Abstract The multidecadal modulation of the El Niño–Southern Oscillation (ENSO) due to greenhouse warming has been analyzed herein by means of diagnostics of Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled general circulation models (CGCMs) and the eigenanalysis of a simplified version of an intermediate ENSO model. The response of the global-mean troposphere temperature to increasing greenhouse gases is more likely linear, while the amplitude and period of ENSO fluctuates in a multidecadal time scale. The climate system model outputs suggest that the multidecadal modulation of ENSO is related to the delayed response of the subsurface temperature in the tropical Pacific compared to the response time of the sea surface temperature (SST), which would lead a modulation of the vertical temperature gradient. Furthermore, an eigenanalysis considering only two parameters, the changes in the zonal contrast of the mean background SST and the changes in the vertical contrast between the mean surface and subsurface temperatures in the tropical Pacific, exhibits a good agreement with the CGCM outputs in terms of the multidecadal modulations of the ENSO amplitude and period. In particular, the change in the vertical contrast, that is, change in difference between the subsurface temperature and SST, turns out to be more influential on the ENSO modulation than changes in the mean SST itself.

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