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Zeng-Zhen Hu and Bohua Huang
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Zeng-Zhen Hu and Bohua Huang

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The major modes of seasonal sea surface temperature (SST) meridional gradient and their connection with some regional mean SST indices in the Atlantic Ocean are examined using reanalysis data. The focus of the work is on the evolution of the dominant mode of the meridional SST gradient in boreal spring and the associated physical processes. The spatial distribution of the dominant mode in boreal spring is a seesaw pattern, reflecting the opposite variation of the meridional SST gradient between the subtropical and tropical North Atlantic, which resulted from a coherent warming or cooling with maxima along 10°–15°N. It is confirmed that this mode is dominated by the wind–evaporation–SST feedback. The feedback persists a longer time in the western Atlantic than in the eastern. The contribution to the SST variation is mainly from latent heat flux. The surface longwave and shortwave cloud radiative forcings are mainly determined by low cloud cover variations. The authors also found that the thermodynamic mode that peaked in boreal spring becomes weak in the following boreal summer. A similar thermodynamic mode appears in a northward position in boreal autumn, and its life cycle is shorter than the one in boreal spring.

In contrast to the leading mode in boreal spring, it is shown that the leading mode in boreal summer is a dynamical air–sea feedback mode, reflecting a coherent warming or cooling pattern extending from the Angolan coast toward the equator in the Gulf of Guinea. The thermodynamic processes act as a negative feedback. The net surface latent heat flux anomalies are the leading damping factor, while the sensible heat flux plays the same role on a smaller scale.

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Zeng-Zhen Hu and Bohua Huang

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The influence of the El Niño–Southern Oscillation (ENSO) and Pacific decadal oscillation (PDO) interference on the dry and wet conditions in the Great Plains of the United States has been examined using monthly observational datasets. It is shown that both ENSO and PDO can generate a similar pattern of atmospheric and oceanic anomalies over the eastern part of the North Pacific and western North America that has significant impact on the climate over the Great Plains. Furthermore, the relationship between ENSO–PDO and climate anomalies in the Great Plains is intensified when ENSO and PDO are in phase (El Niño and warm PDO or La Niña and cold PDO). On average, anomalies over the Great Plains favor wet (dry) conditions when both ENSO and PDO are in the positive (negative) phase. However, when ENSO and PDO are out of phase, the relationship is weakened and the anomalies over the Great Plains tend toward neutral. Without ENSO, PDO alone does not affect the North American climate significantly. The relationship is quite robust for different seasons, with the strongest effects for the months of spring and the weakest effects for the months of autumn, whereas the months of winter and summer fall in between. The seasonality of the relationship may be associated with the seasonal dependence of the anomalies of general circulation and the pattern of mean seasonal cycle in the North Pacific.

The contrasting impact of the interference of ENSO and PDO on the climate anomalies in the Great Plains is associated with differences in the ocean–atmosphere anomalies. When ENSO and PDO are in phase, the sea surface temperature (SST) anomalies extend from the equatorial Pacific to the higher latitudes of the North Pacific via the eastern ocean. The distribution of the corresponding anomalies of sea level pressure (SLP) and the wind at 1000 hPa form an ellipse with a southeast–northwest orientation of the long axis because the SST anomalies promote coherent changes in SLP in the central North Pacific. In the upper troposphere, a similar teleconnection pattern with the same sign generated by ENSO and PDO is overlapped and enhanced, which favors anomaly (dry and wet) conditions in the Great Plains. However, when ENSO and PDO are out of phase, the SST anomalies have the same sign in the tropical and central North Pacific, which is opposite to the anomalies near the west coast of North America. The anomalously cyclonic circulation over the North Pacific is weaker in the out-of-phase situation than in the in-phase situation. The distribution of the anomalies of SLP and the wind at 1000 hPa resembles a circle. Meanwhile, in the upper troposphere, ENSO and PDO generate a similar teleconnection pattern with opposite sign, causing cancellation of the anomalous circulation and favoring neutral climate in the Great Plains.

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Zeng-Zhen Hu and Bohua Huang
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Zeng-Zhen Hu and Bohua Huang

Abstract

This work investigates the predictive skill and most predictable pattern in the NCEP Climate Forecast System (CFS) in the tropical Atlantic Ocean. The skill is measured by the sea surface temperature (SST) anomaly correlation between the predictions and the corresponding analyses, and the most predictable patterns are isolated by an empirical orthogonal function analysis with a maximized signal-to-noise ratio. On average, for predictions with initial conditions (ICs) of all months, the predictability of SST is higher in the west than in the east. The highest skill is near the tropical Brazilian coast and in the Caribbean Sea, and the lowest skill occurs in the eastern coast. Seasonally, the skill is higher for predictions with ICs in summer or autumn and lower for those with ICs in spring. The CFS poorly predicts the meridional gradient in the tropical Atlantic Ocean. The superiority of the CFS predictions to the persistence forecasts depends on IC month, region, and lead time. The CFS prediction is generally better than the corresponding persistence forecast when the lead time is longer than 3 months. The most predictable pattern of SST in March has the same sign in almost the whole tropical Atlantic. The corresponding pattern in March is dominated by the same sign for geopotential height at 200 hPa in most of the domain and by significant opposite variation for precipitation between the northwestern tropical North Atlantic and the regions from tropical South America to the southwestern tropical North Atlantic. These predictable signals mainly result from the influence of the El Niño–Southern Oscillation (ENSO). The significant values in the most predictable pattern of precipitation in the regions from tropical South America to the southwestern tropical North Atlantic in March are associated with excessive divergence (convergence) at low (high) levels over these regions in the CFS. For the CFS, the predictive skill in the tropical Atlantic Ocean is largely determined by its ability to predict ENSO. This is due to the strong connection between ENSO and the most predictable patterns in the tropical Atlantic Ocean in the model. The higher predictive skill of tropical North Atlantic SST is consistent with the ability of the CFS to predict ENSO on interseasonal time scales, particularly for the ICs in warm months from March to October. In the southeastern ocean, the systematic warm bias is a crucial factor leading to the low skill in this region.

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Arun Kumar and Zeng-Zhen Hu

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The magnitude of seasonal predictability for a variable depends on departure of its probability density function (PDF) for a particular season from the corresponding climatological PDF. Differences in the PDF can be due to differences in various moments of the PDF (e.g., mean or the spread) from their corresponding values for the climatological PDF. Year-to-year changes in which moments of the PDF systematically contribute to seasonal predictability are an area of particular interest. Previous analyses for seasonal atmospheric variability have indicated that most of atmospheric predictability is (i) due to El Niño–Southern Oscillation (ENSO) sea surface temperatures (SSTs) and (ii) primarily due to change in the mean of the PDF for the atmospheric variability with changes in the spread of the PDF playing a secondary role. Present analysis extends to the assessment of seasonal predictability of ENSO SSTs themselves. Based on analysis of seasonal hindcasts, the results indicate that the spread (or the uncertainty) in the prediction of ENSO SSTs does not have a systematic dependence on the mean of the amplitude of predicted ENSO SST anomalies, and further, year-to-year changes in uncertainty are small. Therefore, similar to the atmospheric predictability, predictability of ENSO SSTs may also reside in the prediction of its mean amplitude; spread being almost constant does not have a systematic impact on the predictability.

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Xing Yuan, Shanshan Wang, and Zeng-Zhen Hu
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Lei Zhang, Weiqing Han, and Zeng-Zhen Hu

Abstract

An unprecedented extreme positive Indian Ocean Dipole event (pIOD) occurred in 2019, which has caused widespread disastrous impacts on countries bordering the Indian Ocean, including the East African floods and vast bushfires in Australia. Here we investigate the causes for the 2019 pIOD by analyzing multiple observational datasets and performing numerical model experiments. We find that the 2019 pIOD is triggered in May by easterly wind bursts over the tropical Indian Ocean associated with the dry phase of the boreal summer intraseasonal oscillation, and sustained by the local atmosphere-ocean interaction thereafter. During September-November, warm sea surface temperature anomalies (SSTA) in the central-western tropical Pacific further enhance the Indian Ocean’s easterly winds, bringing the pIOD to an extreme magnitude. The central-western tropical Pacific warm SSTA is strengthened by two consecutive Madden Julian Oscillation (MJO) events that originate from the tropical Indian Ocean. Our results highlight the important roles of cross-basin and cross-timescale interactions in generating extreme IOD events. The lack of accurate representation of these interactions may be the root for a short lead time in predicting this extreme pIOD with a state-of-the-art climate forecast model.

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Xiaofan Li, Zeng-Zhen Hu, and Bohua Huang

Abstract

Evolutions of oceanic and atmospheric anomalies in the equatorial Pacific during four strong El Niños (1982/83, 1991/92, 1997/98, and 2015/16) since 1979 are compared. The contributions of the atmosphere–ocean coupling to El Niño–associated sea surface temperature anomalies (SSTA) are identified and their association with low-level winds as well as different time-scale variations is examined. Although overall SSTA in the central and eastern equatorial Pacific is strongest and comparable in the 1997/98 and 2015/16 El Niños, the associated subsurface ocean temperature as well as deep convection and surface wind stress anomalies in the central and eastern equatorial Pacific are weaker during 2015/16 than that during 1997/98. That may be associated with a variation of the wind–SST and wind–thermocline interactions. Both the wind–SST and wind–thermocline interactions play a less important role during 2015/16 than during 1997/98. Such differences are associated with the differences of the low-level westerly wind as well as the contribution of different time-scale variations in different events. Similar to the interannual time-scale variation, the intraseasonal–interseasonal time-scale component always has positive contributions to the intensity of all four strong El Niños. Interestingly, the role of the interdecadal-trend time-scale component varies with event. The contribution is negligible during the 1982/83 El Niño, negative during the 1997/98 El Niño, and positive during the 1991/92 and 2015/16 El Niños. Thus, in addition to the atmosphere–ocean coupling at intraseasonal to interannual time scales, interdecadal and longer time-scale variations may play an important and sometimes crucial role in determining the intensity of El Niño.

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Xiaofan Li, Zeng-Zhen Hu, and Bohua Huang

Abstract

Based on observational data, this work examines the multi-time-scale feature of the sea surface temperature (SST) variability averaged in the whole North Atlantic Ocean (to be referred to as NASST), as well as its time-scale-dependent connections with El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). Traditionally, the NASST index is used to characterize the SST trend and multidecadal variability in the North Atlantic. This study found that superimposed on a prominent long-term trend, NASST is nonnegligible at subannual and interannual time scales, compared with that at decadal to multidecadal time scales. Spatially, the interannual variation of NASST is characterized by a horseshoe-like pattern of the SST anomaly (SSTA) in the North Atlantic. It is mainly a lagged response to ENSO through the atmospheric bridge, and NAO plays a secondary role. At the subannual time scale, both ENSO and NAO play a role in generating the fluctuations of NASST and a horseshoe-like pattern in the North Atlantic. Nevertheless, both the ENSO- and NAO-driven variations only explain a small fraction of the variances in both the interannual and subannual time scales. Thus, other factors unrelated to ENSO or NAO may play a more important role. The associated thermodynamical processes are similar at the two time scales; however, the dynamical processes have a significant contribution to the subannual component, but not to the interannual component. Thus, the SSTA averaged in the North Atlantic as a whole varies at different time scales and is associated with different mechanisms.

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