Simulation of two types of El Niño from different convective parameters

Jang, Yeon-Soo; Kim, Dae Hyun; Kim, Young‐Ho; Kim, Dong-Hoon; Jin, Fei‐Fei; Kug, Jong‐Seong

doi:10.1007/s13143-013-0020-3

Cited by 12 publications

(14 citation statements)

References 17 publications

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“…According to Zhang (1993), the intensity of convection activity is weaker when the SST is lower. The climatological weak convective activity leads to weak atmospheric responses to SST forcing (Kim et al 2011;Jang et al 2013;Ham and Kug 2012;Kug et al 2012;Watanabe et al 2012). The weaker convective response to lower SST caused by chlorophyll reduces the Bjerkness feedback, and hence suppresses the role of the atmosphere on ENSO dynamics.…”

Section: Influence Of Marine Biology On the Enso Magnitudementioning

confidence: 99%

Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs

et al. 2013

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The bio-physical feedback process between the marine ecosystem and the tropical climate system is investigated using both an ocean circulation model and a fully-coupled ocean-atmosphere circulation model, which interact with a biogeochemical model. We found that the presence of chlorophyll can have significant impact on the characteristics of the El Niño-Southern Oscillation (ENSO), including its amplitude and asymmetry, as well as on the mean state. That is, chlorophyll generally increases mean sea surface temperature (SST) due to the direct biological heating. However, SST in the eastern equatorial Pacific decreases due to the stronger indirect dynamical response to the biological effects outweighing the direct thermal response. It is demonstrated that this biologicallyinduced SST cooling is intensified and conveyed to other tropical-ocean basins when atmosphere-ocean coupling is taken into account. It is also found that the presence of chlorophyll affects the magnitude of ENSO by two different mechanisms; one is an amplifying effect by the mean chlorophyll, which is associated with shoaling of the mean thermocline depth, and the other is a damping effect derived from the interactively-varying chlorophyll coupled with the physical model. The atmosphere-ocean coupling reduces the biologically-induced ENSO amplifying effect through the weakening of atmospheric feedback. Lastly, there is also a biological impact on ENSO which enhances the positive skewness. This skewness change is presumably caused by the phase dependency of thermocline feedback which affects the ENSO magnitude.

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Section: Influence Of Marine Biology On the Enso Magnitudementioning

confidence: 99%

Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs

et al. 2013

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“…In RAS, the Tokioka modification (Tokioka et al, ) is applied to suppress the convection whose entrainment rate is smaller than the minimum threshold

μ_{min} = \frac{α}{D}

that varies with the planetary boundary layer depth D . The value of α , controlling the cumulus entrainment, has great impacts on the high cloud, sea surface temperature (SST), and precipitation in the tropical region, and further influences the tropical cyclone (Held & Zhao, ), MJO (Lee et al, ; Sobel et al, ), Hadley Circulation (Kang et al, ), and ENSO (Jang et al, ; Kim et al, ). A greater α reduces convection, high clouds, incoming sunlight and global temperature, while enhancing ENSO variability, and eastward shifts of westerly wind stress and El Niño related precipitation anomalies (Jang et al, ; Kim et al, ).…”

Section: Model and Methodologymentioning

confidence: 99%

“…The value of α , controlling the cumulus entrainment, has great impacts on the high cloud, sea surface temperature (SST), and precipitation in the tropical region, and further influences the tropical cyclone (Held & Zhao, ), MJO (Lee et al, ; Sobel et al, ), Hadley Circulation (Kang et al, ), and ENSO (Jang et al, ; Kim et al, ). A greater α reduces convection, high clouds, incoming sunlight and global temperature, while enhancing ENSO variability, and eastward shifts of westerly wind stress and El Niño related precipitation anomalies (Jang et al, ; Kim et al, ). The default value of α in CM2.1 is 0.025 which has been found to produce a good overall tropical simulation, although it leads to a cold bias in the upper tropical troposphere (GFDL Global Atmospheric Model Development Team, ).…”

Section: Model and Methodologymentioning

confidence: 99%

“…that varies with the planetary boundary layer depth D. The value of a, controlling the cumulus entrainment, has great impacts on the high cloud, sea surface temperature (SST), and precipitation in the tropical region, and further influences the tropical cyclone , MJO (Lee et al, 2008;Sobel et al, 2010), Hadley Circulation (Kang et al, 2008), and ENSO (Jang et al, 2013;Kim et al, 2011). A greater a reduces Figure 1.…”

Section: Convection Parametersmentioning

confidence: 99%

“…Journal of Advances in Modeling Earth Systems 10.1002/2017MS001222 convection, high clouds, incoming sunlight and global temperature, while enhancing ENSO variability, and eastward shifts of westerly wind stress and El Niño related precipitation anomalies (Jang et al, 2013;Kim et al, 2011). The default value of a in CM2.1 is 0.025 which has been found to produce a good overall tropical simulation, although it leads to a cold bias in the upper tropical troposphere (GFDL Global Atmospheric Model Development Team, 2004).…”

Section: Convection Parametersmentioning

confidence: 99%

See 2 more Smart Citations

Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

Zhang

Liu

et al. 2018

J Adv Model Earth Syst

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Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.

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The influence of ENSO on South American precipitation during austral summer and autumn in observations and models

Tedeschi

Collins

2015

Intl Journal of Climatology

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South American precipitation is observed to respond differently to different types of El Niño Southern Oscillation (ENSO) events, such as those in which the main signal in sea surface temperature (SST) occurs either in the eastern equatorial Pacific or central equatorial Pacific. This study investigates how Coupled Model Intercomparison Project Phase 5 (CMIP5) models represent different types of ENSO and how they represent teleconnections to South American precipitation. It is found that the CMIP5 models can represent the basic structure of SST anomalies that occur during different types of ENSO events and these are described using simple SST indices. Most of the CMIP5 models can reproduce the correct sign of precipitation anomalies in northeast South America during austral summer and autumn, in cases where the observed teleconnections are relatively strong. The same is also true of north South America in austral summer. In the east and southeast regions of South America, many models fail to reproduce the correct sign during both Canonical and Modoki/Central Pacific/Warm Pool ENSO events. The precipitation composites in Atmospheric Model Intercomparison Project (AMIP) models tend to agree with their CMIP5 counterparts, so we conclude that the errors in teleconnections are not principally driven by mean SST biases. Precipitation teleconnections in the northern regions are shown to be linked to variations in the Walker circulation in models, with the exception of that in north South America during March-May. During March-May, composite precipitation in southeast South America is related to wave trains emanating from the equator.

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Simulation of two types of El Niño from different convective parameters

Cited by 12 publications

References 17 publications

Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs

Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs

Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

The influence of ENSO on South American precipitation during austral summer and autumn in observations and models

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