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Yi Shi, Zhihong Jiang, Zhengyu Liu, and Laurent Li

Abstract

The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) platform is used to simulate Lagrangian trajectories of air parcels in East China during the summer monsoon. The investigation includes four distinct stages of the East Asian summer monsoon (EASM) during its seasonal migration from south to north. Correspondingly, the main water vapor channel migrates from the west Pacific Ocean (PO) for the premonsoon in South China (SC) to the Indian Ocean (IO) for the monsoon in SC and in the Yangtze–Huaihe River basin, and finally back to the PO for the terminal stage of monsoon in North China. Further calculations permit us to determine water vapor source regions and water vapor contribution to precipitation in East China. To a large extent, moisture leading to precipitation does not come from the strongest water vapor pathways. For example, the proportions of trajectories from the IO are larger than 25% all of the time, but moisture contributions to actual precipitation are smaller than 10%. This can be explained by the large amount of water vapor lost in the pathways across moisture-losing areas such as the Indian and Indochina Peninsulas. Local water vapor recycling inside East China (EC) contributes significantly to regional precipitation, with contributions mostly over 30%, although the trajectory proportions from subregions in EC are all under 10%. This contribution rate can even exceed 55% for the terminal stage of the monsoon in North China. Such a result provides important guidance to understand the role of land surface conditions in modulating rainfall in North China.

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Zhengyu Liu, Haijun Yang, Chengfei He, and Yingying Zhao

Abstract

The response of the atmospheric energy (heat) transport (AHT) to a perturbation oceanic heat transport (OHT) is studied theoretically in a zonal mean energy balance model, with the focus on the effect of climate feedback, especially its spatial variation, on Bjerknes compensation (BJC). It is found that the BJC depends critically on climate feedback. For a stable climate, in which negative climate feedback is dominant, the AHT always compensates the OHT in the opposite direction. Furthermore, if local climate feedback is negative everywhere, the AHT will be weaker than the OHT (undercompensation) because of the damping on the surface oceanic heating through the top-of-atmosphere energy loss. One novel finding is that the compensation magnitude depends on the spatial scale of the forcing and is bounded between a minimum at the global scale and a maximum (of perfect compensation) at small scales. Most interestingly, the BJC is affected significantly by the spatial variation of the feedback, particularly a local positive climate feedback. As such, a regional positive feedback can lead to a compensating AHT greater than the perturbation OHT (overcompensation). This occurs because the positive feedback enhances the local temperature response, the anomalous temperature gradient, and, in turn, the AHT. Finally, the poleward latent heat transport leads to a temperature response with a polar amplification accompanied by a polar steepening of temperature gradient but does not change the BJC significantly. Potential applications of this BJC theory to more complex climate model studies are also discussed.

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Yishuai Jin, Zhengyu Liu, Chengfei He, and Yuchu Zhao

Abstract

The mechanism of the seasonal persistence barrier (SPB) is studied in the framework of an autoregressive (AR) model. In contrast to the seasonal variance, whose minimum is modulated mainly by the minimum growth rate or noise forcing, the SPB is caused primarily by the declining growth rate or increasing noise forcing, instead of the minimum/maximum of the growth rate or noise forcing. In other words, the SPB is caused by the declining signal-to-noise ratio (SNR) rather than the weakest SNR. In a weakly damped system, the phase of the SPB is delayed from that of declining SNR by about a season. The mechanism is further applied to explain the observed SST variability in the tropical and North Pacific. For the tropical Pacific, the spring SPB could be caused by the decreasing growth rate from September to March and weak annual mean damping rate, instead of the minimum growth rate in spring. Over the North Pacific, the increasing noise forcing from March to June may lead to the summer SPB. Our mechanism provides a null hypothesis for understanding the SPB of climate variability.

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Zhengyu Liu, S. G. H. Philander, and R. C. Pacanowski

Abstract

Experiments with an oceanic general circulation model indicate that the tropical and subtropical oceanic circulations are linked in three ways. Far from coast in the oceanic interior, equatorial surface waters flow poleward to the southern part of the subtropical gyre, and then are subducted and returned in the thermocline to the upper part of the core of the Equatorial Undercurrent. There is, in addition, a surface western boundary current that carries waters from the equatorial region to the northern part of the subtropical gyre. After subduction, that water reaches the equator by means of a subsurface western boundary current and provides a substantial part (2/3 approximately) of the initial transport of the Equatorial Undercurrent. The eastward flow in the Equatorial Undercurrent is part of an intense equatorial cell in which water rises to the surface at the equator, drifts westward and poleward, then sinks near 3° latitude to flow equatorward where it rejoins the undercurrent.

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Lixin Wu, Feng He, Zhengyu Liu, and Chun Li

Abstract

In this paper, the atmospheric teleconnections of the tropical Atlantic SST variability are investigated in a series of coupled ocean–atmosphere modeling experiments. It is found that the tropical Atlantic climate not only displays an apparent interhemispheric link, but also significantly influences the North Atlantic Oscillation (NAO) and the El Niño–Southern Oscillation (ENSO). In spring, the tropical Atlantic SST exhibits an interhemispheric seesaw controlled by the wind–evaporation–SST (WES) feedback that subsequently decays through the mediation of the seasonal migration of the ITCZ. Over the North Atlantic, the tropical Atlantic SST can force a significant coupled NAO–dipole SST response in spring that changes to a coupled wave train–horseshoe SST response in the following summer and fall, and a recurrence of the NAO in the next winter. The seasonal changes of the atmospheric response as well as the recurrence of the next winter’s NAO are driven predominantly by the tropical Atlantic SST itself, while the resulting extratropical SST can enhance the atmospheric response, but it is not a necessary bridge of the winter-to-winter NAO persistency. Over the Pacific, the model demonstrates that the north tropical Atlantic (NTA) SST can also organize an interhemispheric SST seesaw in spring in the eastern equatorial Pacific that subsequently evolves into an ENSO-like pattern in the tropical Pacific through mediation of the ITCZ and equatorial coupled ocean–atmosphere feedback.

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Zhihong Jiang, Hao Yang, Zhengyu Liu, Yanzhu Wu, and Na Wen

Abstract

This study investigates the influence of different sea surface temperature (SST) modes on the winter temperature in China using the generalized equilibrium feedback assessment (GEFA). It is found that the second EOF mode of winter temperature in China during 1958–2010 shows a typical northeast–southwest (NE–SW) pattern, which is a major spatial mode of Chinese winter temperature at interannual scales. The winter temperature of the NE–SW pattern is forced mainly by SST modes in the tropical Pacific and Atlantic. For 2009/10, the tropical Pacific El Niño mode and tropical Atlantic tripole mode have the largest contribution to the response. The physical mechanism of the cold northeast–warm southwest (CNE–WSW) pattern is also explained in terms of GEFA of the responses of the atmospheric circulation. The northerly flow at the low level transports cold air to northern and northeastern China, resulting in a lower temperature there. Meanwhile, the anomaly meridional wind advects warm air from the southern oceans to southwestern China, leading to warming there.

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Fuyao Wang, Michael Notaro, Zhengyu Liu, and Guangshan Chen

Abstract

The observed local and nonlocal influences of vegetation on the atmosphere across North America are quantified after first removing the oceanic impact. The interaction between vegetation and the atmosphere is dominated by forcing from the atmosphere, making it difficult to extract the forcing from vegetation. Furthermore, the atmosphere is not only influenced by vegetation but also the oceans, so in order to extract the vegetation impact, the oceanic forcing must first be excluded. This study identified significant vegetation impact in two climatically and ecologically unique regions: the North American monsoon region (NAMR) and the North American boreal forest (NABF). A multivariate statistical method, a generalized equilibrium feedback assessment, is applied to extract vegetation influence on the atmosphere. The statistical method is validated using a dynamical experiment for the NAMR in a fully coupled climate model, the Community Climate System Model, version 3.5 (CCSM3.5).

The observed influence of NAMR vegetation on the atmosphere peaks in June–August and is primarily attributed to both roughness and hydrological feedbacks. Elevated vegetation amount increases evapotranspiration and surface roughness, which leads to a local decline in sea level pressure and generates an atmospheric teleconnection response. This atmospheric response leads to moister and cooler (drier and warmer) conditions over the western and central United States (Gulf states). The observed influence of the NABF on the atmosphere peaks in March–May, related to a thermal feedback. Enhanced vegetation greenness increases the air temperature locally. The atmosphere tends to form a positive Pacific–North American (PNA)-like pattern, and this anomalous atmospheric circulation and associated moisture advection lead to moister (drier) conditions in the western (eastern) United States.

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Guijun Han, Xinrong Wu, Shaoqing Zhang, Zhengyu Liu, and Wei Li

Abstract

Coupled data assimilation uses a coupled model consisting of multiple time-scale media to extract information from observations that are available in one or more media. Because of the instantaneous exchanges of information among the coupled media, coupled data assimilation is expected to produce self-consistent and physically balanced coupled state estimates and optimal initialization for coupled model predictions. It is also expected that applying coupling error covariance between two media into observational adjustments in these media can provide direct observational impacts crossing the media and thereby improve the assimilation quality. However, because of the different time scales of variability in different media, accurately evaluating the error covariance between two variables residing in different media is usually very difficult. Using an ensemble filter together with a simple coupled model consisting of a Lorenz atmosphere and a pycnocline ocean model, which characterizes the interaction of multiple time-scale media in the climate system, the impact of the accuracy of coupling error covariance on the quality of coupled data assimilation is studied. Results show that it requires a large ensemble size to improve the assimilation quality by applying coupling error covariance in an ensemble coupled data assimilation system, and the poorly estimated coupling error covariance may otherwise degrade the assimilation quality. It is also found that a fast-varying medium has more difficulty being improved using observations in slow-varying media by applying coupling error covariance because the linear regression from the observational increment in slow-varying media has difficulty representing the high-frequency information of the fast-varying medium.

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Zhengyu Liu, Joseph Pedlosky, David Marshall, and Tornster Warncke

Abstract

The model developed by Pedlosky and Young is used to investigate the feedback of a Rhines–Young pool on a ventilated thermocline. It is found that the potential vorticity gradient in a ventilated layer is reduced due to the nonlinear coupling with a deep Rhines–Young pool. Physically, this occurs because part of the Sverdrup transport is carried by the deep pool. As a result the subduction velocity, and in turn, the potential vorticity gradient of the subducted water, is decreased.

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Xiuhua Zhu, Klaus Fraedrich, Zhengyu Liu, and Richard Blender

Abstract

Climate forecast skills are evaluated for surface temperature time series at grid points of a millennium control simulation from a state-of-the-art global circulation model [ECHAM5–Max Planck Institute Ocean Model (MPI-OM)]. First, climate predictability is diagnosed in terms of potentially predictable variance fractions and the fluctuation power-law exponent (using detrended fluctuation analysis). Long-term memory (LTM) with a fluctuation exponent (or Hurst exponent) close to 0.9 occurs mainly in high-latitude oceans, which are also characterized by high potential predictability. Next, explicit prediction experiments for various time steps are conducted on a gridpoint basis using an autocorrelation predictor. In regions with LTM, prediction skills are beyond that expected from red noise persistence—exceptions occur in some areas in the southern oceans and over the Northern Hemisphere continents. Extending the predictability analysis to the fully forced simulation shows a large improvement in prediction skills.

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