Excessive ITCZ but negative SST biases in the tropical Pacific simulated by CMIP5/6 models: The role of the meridional pattern of SST bias

2020 ◽  
Author(s):  
Ping Huang
Keyword(s):  
State Of The Art ◽  
Tropical Pacific ◽  
Intertropical Convergence Zone ◽  
Cmip5 Models ◽  
Layer Model ◽  
Sst Bias ◽  
Key Factor ◽  
The Common ◽  
The Tropical Pacific

<p>In the state-of-the-art CMIP5/6 models, there is an apparent excessive rainfall bias with a negative SST bias in the tropical Pacific intertropical convergence zone (ITCZ). The regime of the excessive ITCZ but negative SST bias is inconsistent with the common positive rainfall–SST correlation. Using a two-mode model, we decomposed the rainfall bias into two components, and found that the surface convergence (SC) bias is the key factor forming the excessive ITCZ bias in the historical runs of 25 CMIP5 models and 23 CMIP6 models. A mixed layer model was further applied to connect the formation of the SC bias with the SST pattern bias. The results suggest that the meridional pattern of the SST bias plays a key role in forming the SC bias. In the CMIP5/6 models, the overall negative SST bias has two apparent meridional troughs at around 10°S and 10°N, respectively. The two meridional troughs in the SST bias drive two convergence centers in the SC bias favoring the excessive ITCZ, even though the local SST bias is negative.</p>

scholarly journals Excessive ITCZ but Negative SST Biases in the Tropical Pacific Simulated by CMIP5/6 Models: The Role of the Meridional Pattern of SST Bias

2020 ◽  
Vol 33 (12) ◽  
pp. 5305-5316 ◽  
Author(s):  
Shijie Zhou ◽  
Gang Huang ◽  
Ping Huang
Keyword(s):  
Coupled Model ◽  
Tropical Pacific ◽  
Cmip5 Models ◽  
Climate Anomalies ◽  
Sst Bias ◽  
Key Factor ◽  
Intercomparison Project ◽  
The Tropics ◽  
The Tropical Pacific

AbstractIn phases 5 and 6 of the state-of-the-art Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively) models, there is an apparent excessive rainfall bias with a negative SST bias in the tropical Pacific intertropical convergence zone (ITCZ). The regime of the excessive ITCZ but negative SST bias is inconsistent with the common positive rainfall–SST correlation of climate anomalies over the tropics. Using a two-mode model, we decomposed the rainfall bias into two components and found that the surface convergence (SC) bias is the key factor forming the excessive ITCZ bias in the historical runs of 25 CMIP5 models and 23 CMIP6 models. A mixed layer model was further applied to connect the formation of the SC bias with the SST pattern bias. The results suggest that the meridional pattern of the SST bias plays a key role in forming the SC bias. In the CMIP5 and CMIP6 models, the overall negative SST bias has two apparent meridional troughs at around 10°S and 10°N, respectively. The two meridional troughs in the SST bias drive two convergence centers in the SC bias favoring the excessive ITCZ, even though the local SST bias is negative.

Complex networks approach for detecting tropical basin interactions

2021 ◽  
Author(s):  
Belen Rodríguez de Fonseca ◽  
Veronica Martín-Gómez ◽  
Jose María Aliganga
Keyword(s):  
Indian Ocean ◽  
Decadal Variability ◽  
Tropical Indian Ocean ◽  
Tropical Pacific ◽  
Equatorial Atlantic ◽  
Tropical Oceans ◽  
Collective Interaction ◽  
Tropical North Atlantic ◽  
Key Factor ◽  
The Tropical Pacific

<p>Interaction between the tropical Pacific, Atlantic, and Indian Ocean basins is increasingly recognized as a key factor in understanding climate variability on interannual to decadal timescales. Most of the studies deal with the connection between pair of basins and less attention has been paid to analyze the degree of collective interaction among the three tropical oceans and its variability along time.In this study, we consider a complex network perspective to analyze the collective connectivity among the three tropical basins. To do so, we first construct a climate network considering as network’ nodes the indices that represent the variability of the SST over the tropical Pacific, the tropical north Atlantic, the equatorial Atlantic and the tropical Indian Ocean. Then, we focus on detecting periods of maximum degree of collective connectivity (synchronization periods) using the mean network distance definition.Results show that the degree of collective connectivity among the three tropical oceans present a large muti-decadal variability and that during the observed period there were two synchronization periods: one developed over the period (1900-1935) and the other from 1975 to present. A period center in the 1950’s is characterized by being the three basins uncoupled .Using this information, an analysis of background conditions in the ocean and the atmosphere has been conducted in order to elucidate causes for this change in connectivity.</p>

Remote Sources of Surface Temperature Cold Bias over the Tibetan Plateau: Role of Tropical SST Climatological Bias

2020 ◽  
Author(s):  
Yuting Wu ◽  
Xiaoming Hu ◽  
Ziqian Wang ◽  
Zhenning Li ◽  
Song Yang
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Distribution Pattern ◽  
Climate Models ◽  
Cmip5 Models ◽  
Cold Bias ◽  
The Tibetan Plateau ◽  
Sst Bias ◽  
Hypothesis Model

<p>The surface temperature cold bias over the Tibetan Plateau (TP) is a long-lasting problem in both reanalysis data and climate models. While previous studies have mainly focused on local processes for this bias, the TP surface temperature is also closely related to tropical SST in both observations and Coupled Model Inter-comparison Project (CMIP5) models. This study investigates the role of tropical SST climatological bias in the TP surface temperature cold bias, and analysis of CMIP5 models suggests that the surface temperature cold bias over the TP is more obvious (about 4 K) in winter, with an east-west distribution pattern, than in summer (about 1 K), with a south-north distribution pattern. Considering that the tropical SST bias in CMIP5 models may be an important source of the TP surface temperature cold bias, a series of model experiments were conducted by the NCAR CAM4 to test the hypothesis. Model experiment results show that the tropical SST bias can reproduce cold bias over the TP, with 2 K in winter and about 0.5 K in summer. The mechanisms for TP surface temperature cold bias are different in winter and summer. In winter, tropical SST bias influences the TP surface temperature mainly by anomalous snow cover, while anomalous precipitation and clouds are more important for the temperature bias in summer.</p>

scholarly journals Oxygen minimum zones in the tropical Pacific across CMIP5 models: mean state differences and climate change trends

2015 ◽  
Vol 12 (8) ◽  
pp. 6525-6587 ◽  
Author(s):  
A. Cabré ◽  
I. Marinov ◽  
R. Bernardello ◽  
D. Bianchi
Keyword(s):  
Climate Change ◽  
Tropical Pacific ◽  
Cmip5 Models ◽  
Upper Ocean ◽  
Intermediate Water ◽  
Climate Change Projections ◽  
Oxygen Minimum Zones ◽  
Mean State ◽  
Oxygen Minimum ◽  
The Tropical Pacific

Abstract. We analyze simulations of the Pacific Ocean oxygen minimum zones (OMZs) from 11 Earth System model contributions to the Coupled Model Intercomparison Project Phase 5, focusing on the mean state and climate change projections. The simulations tend to overestimate the volume of the OMZs, especially in the tropics and Southern Hemisphere. Compared to observations, five models introduce incorrect meridional asymmetries in the distribution of oxygen including larger southern OMZ and weaker northern OMZ, due to interhemispheric biases in intermediate water mass ventilation. Seven models show too deep an extent of the tropical hypoxia compared to observations, stemming from a deficient equatorial ventilation in the upper ocean combined with a too large biologically-driven downward flux of particulate organic carbon at depth, caused by too high particle export from the euphotic layer and too weak remineralization in the upper ocean. At interannual timescales, the dynamics of oxygen in the eastern tropical Pacific OMZ is dominated by biological consumption and linked to natural variability in the Walker circulation. However, under the climate change scenario RCP8.5, all simulations yield small and discrepant changes in oxygen concentration at mid depths in the tropical Pacific by the end of the 21st century due to an almost perfect compensation between warming-related decrease in oxygen saturation and decrease in biological oxygen utilization. Climate change projections are at odds with recent observations that show decreasing oxygen levels at mid depths in the tropical Pacific. Out of the OMZs, all the CMIP5 models predict a decrease of oxygen over most of the surface, deep and high latitudes ocean due to an overall slow-down of ventilation and increased temperature.

Indian Ocean impact on ENSO evolution 2014-2016 in a set of seasonal forecasting experiments

2020 ◽  
Author(s):  
Michael Mayer ◽  
Magdalena Alonso Balmaseda
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
Initial Conditions ◽  
El Nino ◽  
Tropical Pacific ◽  
Seasonal Forecasting ◽  
The Indian Ocean ◽  
The Impact ◽  
The Tropical Pacific

<p>In 2014 the scientific community and forecasters were expecting a major El Nino event, which was suggested by physical indicators and predicted by several seasonal forecasting systems. However, only moderately warm El Nino – Southern-Oscillation (ENSO) conditions materialized in 2014, but one year later in boreal winter 2015/16, one of the strongest El Ninos on record occurred. Moreover, the 2015/16 El Nino exhibited very unusual energetics: Despite warm conditions in the tropical Pacific in 2014 and especially 2015, its ocean heat content (OHC) did not decrease during that period, which usually is the case during El Nino events. Overall, the 2014-16 evolution of the tropical Pacific was quite different from the evolution during the 1997/98 El Nino, which exhibited exceptionally strong Pacific OHC discharge. This discrepancy was attributed at least partly to the anomalously warm Indian Ocean and the exceptionally weak Indonesian Throughflow transports during 2015-16 that kept Pacific OHC at high levels.</p><p>This contribution aims to elucidate the role of the Indian Ocean in the tropical Pacific Ocean evolution during ENSO for the two periods February 1997-1999 and February 2014-2016. For this purpose, we perform initialized two-year predictions using the ECMWF seasonal forecasting system. To isolate the role of the Indian Ocean, we carry out hindcasts with unperturbed ocean initial conditions and hindcasts with swapped Indian Ocean initial conditions, where the 2014 (1997) hindcasts use Indian Ocean initial conditions from 1997 (2014). We first investigate the impact of the Indian Ocean on the strength of the Indonesian Throughflow and the evolution of the tropical Pacific heat budget. Second, we seize these experiments to explore the impact of the Indian Ocean state on two-yearly ENSO evolution, especially on the probability of extreme events, and which role the atmospheric bridge plays versus the oceanic bridge.</p>

scholarly journals A Multimodel Ensemble Pattern Regression Method to Correct the Tropical Pacific SST Change Patterns under Global Warming

2015 ◽  
Vol 28 (12) ◽  
pp. 4706-4723 ◽  
Author(s):  
Ping Huang ◽  
Jun Ying
Keyword(s):  
Regional Climate ◽  
Walker Circulation ◽  
Regional Climate Change ◽  
Warm Pool ◽  
Tropical Pacific ◽  
Multimodel Ensemble ◽  
Epr Method ◽  
Circulation Change ◽  
The Common ◽  
The Tropical Pacific

Abstract This study develops a new observational constraint method, called multimodel ensemble pattern regression (EPR), to correct the projections of regional climate change by the conventional unweighted multimodel mean (MMM). The EPR method first extracts leading modes of historical bias using intermodel EOF analysis, then builds up the linear correlated modes between historical bias and change bias using multivariant linear regression, and finally estimates the common change bias induced by common historical bias. Along with correcting common change bias, the EPR method implicitly removes the intermodel uncertainty in the change projection deriving from the intermodel diversity in background simulation. The EPR method is applied to correct the patterns of tropical Pacific SST changes using the historical and representative concentration pathway 8.5 (RCP8.5) runs in 30 models from phase 5 of CMIP (CMIP5) and observed SSTs. The common bias patterns of the tropical Pacific SSTs in historical runs, including the excessive cold tongue, the southeastern warm bias, and the narrower warm pool, are estimated to induce La Niña–like change biases. After the estimated common change biases are removed, the corrected SST changes display a pronounced El Niño–like pattern and have much greater zonal gradients. The bias correction decreases by around half of the intermodel uncertainties in the MMM SST projections. The patterns of corrected tropical precipitation and circulation change are dominated by the enhanced SST change patterns, displaying a pronounced warmer-get-wetter pattern and a decreased Walker circulation with decreased uncertainties.

scholarly journals Cloud–Radiation Feedback as a Leading Source of Uncertainty in the Tropical Pacific SST Warming Pattern in CMIP5 Models

2016 ◽  
Vol 29 (10) ◽  
pp. 3867-3881 ◽  
Author(s):  
Jun Ying ◽  
Ping Huang
Keyword(s):  
Heat Budget ◽  
Tropical Pacific ◽  
Eastern Pacific ◽  
Shortwave Radiation ◽  
Cmip5 Models ◽  
Central Pacific ◽  
Surface Warming ◽  
Sst Warming ◽  
Radiation Feedback ◽  
The Tropical Pacific

Abstract The role of the intermodel spread of cloud–radiation feedback in the uncertainty in the tropical Pacific SST warming (TPSW) pattern under global warming is investigated based on the historical and RCP8.5 runs from 32 models participating in CMIP5. The large intermodel discrepancies in cloud–radiation feedback contribute 24% of the intermodel uncertainty in the TPSW pattern over the central Pacific. The mechanism by which the cloud–radiation feedback influences the TPSW pattern is revealed based on an analysis of the surface heat budget. A relatively weak negative cloud–radiation feedback over the central Pacific cannot suppress the surface warming as greatly as in the multimodel ensemble and thus induces a warm SST deviation over the central Pacific, producing a low-level convergence that suppresses (enhances) the evaporative cooling and zonal cold advection in the western (eastern) Pacific. With these processes, the original positive SST deviation over the central Pacific will move westward to the western and central Pacific, with a negative SST deviation in the eastern Pacific. Compared with the observed cloud–radiation feedback from six sets of reanalysis and satellite-observed data, the negative cloud–radiation feedback in the models is underestimated in general. It implies that the TPSW pattern should be closer to an El Niño–like pattern based on the concept of observational constraint. However, the observed cloud–radiation feedback from the various datasets also demonstrates large discrepancies in magnitude. Therefore, the authors suggest that more effort should be made to improve the precision of shortwave radiation observations and the description of cloud–radiation feedback in models for a more reliable projection of the TPSW pattern in future.

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