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Yu Gao, Zhengyu Liu, and Zhengyao Lu

Abstract

The effect of ice sheet topography on the East Asian summer monsoon (EASM) during the Last Glacial Maximum is studied using CCSM3 in a hierarchy of model configurations. It is found that receding ice sheets result in a weakened EASM, with the reduced ice sheet thickness playing a major role. The lower ice sheet topography weakens the EASM through shifting the position of the midlatitude jet, and through altering Northern Hemisphere stationary waves. In the jet shifting mechanism, the lowering of ice sheets shifts the westerly jet northward and decreases the westerly jet over the subtropics in summer, which reduces the advection of dry enthalpy and in turn precipitation over the EASM region. In the stationary wave mechanism, the lowering of ice sheets induces an anomalous stationary wave train along the westerly waveguide that propagates into the EASM region, generating an equivalent-barotropic low response; this leads to reduced lower-tropospheric southerlies, which in turn reduces the dry enthalpy advection into East Asia, and hence the EASM precipitation.

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Haijun Yang, Zhengyu Liu, and Hui Wang

Abstract

The equatorial thermocline variability in the Pacific in response to the extratropical thermal and wind forcings is investigated with an ocean general circulation model [Modular Ocean Model, version 3 (MOM3)]. Sensitivity experiments show that the extratropical wind forcing and thermal forcing contribute equally to the equatorial variability. The wind-induced response is attributed to the off-equatorial wind within 30° of the equator; the thermal-induced response can be traced to higher latitudes. The thermal forcing affects the equator mainly through the equatorward transport of the perturbation temperature by mean subduction flow; the wind forcing affects the equator by changing the strength of meridional overturning circulations. It is also found that the Southern Hemisphere contributes more to the equatorial variability than the Northern Hemisphere under both external forcings.

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Zhengyu Liu, Lixin Wu, and H. Hurlburt

Abstract

The formation of an island circulation is investigated both theoretically and numerically in light of the dynamics of coastal Kelvin waves and Rossby waves. An island circulation is formed in three stages. First, the direction of the circulation is initiated by the coastal Kelvin wave; second, the transport of the circulation is established by the short Rossby wave dissipated against the eastern coast of the island; and finally, the basinwide circulation pattern is completed by the long Rossby wave radiated from the western coast of the island. An island circulation can be forced by either a local alongshore wind or a remote vorticity forcing to the east of the island; the initial Kelvin wave is directly forced by the alongshore wind in the former case, but indirectly forced by a planetary wave incident on the eastern coast of the island in the latter case. A comparison is also made between the spinup of an island circulation and a basin circulation. In addition, this spinup study also provides an alternative derivation of the island rule in light of the dynamics of Kelvin and Rossby waves. The implication for understanding the temporal response of an island circulation to a variable forcing is also discussed.

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Zhengyu Liu, Yun Liu, Lixin Wu, and R. Jacob

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The atmospheric response to a North Pacific subsurface oceanic temperature anomaly is studied in a coupled ocean–atmosphere general circulation model using a combined dynamical and statistical approach, with the focus on the evolution at seasonal and longer time scales. The atmospheric response is first assessed dynamically with an ensemble coupled experiment. The atmospheric response is found to exhibit a distinct seasonal evolution and a significant long-term response. The oceanic temperature anomaly reemerges each winter to force the atmosphere through an upward heat flux, forcing a clear seasonal atmospheric response locally over the Aleutian low and downstream over the North America/North Atlantic Ocean and the Arctic regions. The atmospheric response is dominated by the early winter response with a warm SST-equivalent barotropic ridge and a wave train downstream. Starting in later winter, the atmospheric response weakens significantly and remains weak throughout the summer. The seasonal response of the atmosphere is then assessed statistically from the control simulation. It is found that the major features of the seasonal response, especially the strong warm SST–ridge response in early winter, are crudely consistent between the dynamical and statistical assessments. The statistical assessment is finally applied to the observation, which also suggests a strong seasonal atmospheric response locally over the North Pacific dominated by a warm SST–ridge response in early winter.

One important conclusion is that the atmospheric response becomes more significant at annual and longer time scales, with the signal/noise ratio increasing up to 4 times from the monthly to the 4-yr mean response. This increased signal/noise ratio is caused by a much faster reduction of the atmospheric internal variability toward longer time scales than that of the response signal. The slow decrease of the response signal is due to the long persistence associated with the subsurface ocean. This suggests that the subsurface extratropical oceanic variability could have a much stronger impact on the extratropical atmosphere (and climate variability) at interannual–interdecadal time scales than at monthly–seasonal time scales.

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Feiyu Lu, Zhengyu Liu, Shaoqing Zhang, and Yun Liu

Abstract

This paper studies a new leading averaged coupled covariance (LACC) method for the strongly coupled data assimilation (SCDA). The SCDA not only uses the coupled model to generate the forecast and assimilate observations into multiple model components like the weakly coupled version (WCDA), but also applies a cross update using the coupled covariance between variables from different model components. The cross update could potentially improve the balance and quality of the analysis, but its implementation has remained a great challenge in practice because of different time scales between model components. In a typical extratropical coupled system, the ocean–atmosphere correlation shows a strong asymmetry with the maximum correlation occurring when the atmosphere leads the ocean by about the decorrelation time of the atmosphere. The LACC method utilizes such asymmetric structure by using the leading forecasts and observations of the fast atmospheric variable for cross update, therefore, increasing the coupled correlation and enhancing the signal-to-noise ratio in calculating the coupled covariance. Here it is applied to a simple coupled model with the ensemble Kalman filter (EnKF). With the LACC method, the SCDA reduces the analysis error of the oceanic variable by over 20% compared to the WCDA and 10% compared to the SCDA using simultaneous coupled covariance. The advantage of the LACC method is more notable when the system contains larger errors, such as in the cases with smaller ensemble size, bigger time-scale difference, or model biases.

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Na Wen, Zhengyu Liu, Qinyu Liu, and Claude Frankignoul

Abstract

The authors present a comprehensive assessment of the observed atmospheric response to SST variability modes in a unified approach using the Generalized Equilibrium Feedback Analysis (GEFA). This study confirms a dominant atmospheric response to the tropical SST variability associated with ENSO. A further analysis shows that the classical response to ENSO consists of two parts, one responding to the tropical Pacific ENSO mode and the other to the tropical Indian Ocean monopole (IOM) mode. The Pacific ENSO generates a significant baroclinic Rossby wave response locally over the tropical Pacific as well as equivalent barotropic wave train responses remotely into the extratropics. The IOM mode forces a strongly zonally symmetric response throughout the tropics and the extratropics. Furthermore, modest atmospheric responses to other oceanic modes were identified. For example, the North Pacific SST variability mode appears to generate an equivalent barotropic warm SST-ridge response locally over the Aleutian low with significant downstream influence on the North Atlantic Oscillation (NAO), whereas the North Atlantic tripole SST mode tends to force a local response on NAO. Finally, this pilot study serves as a demonstration of the potential utility of GEFA in identifying multiple surface feedbacks to the atmosphere in the observation.

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Zhengyu Liu, Lei Fan, Sang-Ik Shin, and Qinyu Liu

Abstract

The authors compared the assessment of the seasonal cycle of the atmospheric response to surface forcing in three statistical methods, generalized equilibrium feedback analysis (GEFA), linear inverse modeling (LIM), and fluctuation–dissipation theorem (FDT). These methods are applied to both a conceptual climate model and the observation. It is found that LIM and GEFA are able to reproduce the major features of the seasonal response consistently, whereas FDT tends to generate a bias of the phase of the seasonal cycle. The success of LIM and GEFA for the assessment of the seasonal response is due to the slowly varying nature of the annual cycle relative to the atmospheric response time. Therefore, the authors recommend GEFA and LIM as two independent methods for the assessment of the seasonal atmospheric response in the observation.

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Feiyu Lu, Zhengyu Liu, Shaoqing Zhang, Yun Liu, and Robert Jacob

Abstract

This paper uses a fully coupled general circulation model (CGCM) to study the leading averaged coupled covariance (LACC) method in a strongly coupled data assimilation (SCDA) system. The previous study in a simple coupled climate model has shown that, by calculating the coupled covariance using the leading averaged atmospheric states, the LACC method enhances the signal-to-noise ratio and improves the analysis quality of the slow model component compared to both the traditional weakly coupled data assimilation without cross-component adjustments (WCDA) and the regular SCDA using the simultaneous coupled covariance (SimCC).

Here in Part II, the LACC method is tested with a CGCM in a perfect-model framework. By adding the observational adjustments from the low-level atmosphere temperature to the sea surface temperature (SST), the SCDA using LACC significantly reduces the SST error compared to WCDA over the globe; it also improves from the SCDA using SimCC, which performs better than the WCDA only in the deep tropics. The improvement in SST analysis is a result of the enhanced signal-to-noise ratio in the LACC method, especially in the extratropical regions. The improved SST analysis also benefits the subsurface ocean temperature and low-level atmosphere temperature analyses through dynamic and statistical processes.

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Guang-Shan Chen, Michael Notaro, Zhengyu Liu, and Yongqiang Liu

Abstract

Afforestation has been proposed as a climate change mitigation strategy by sequestrating atmospheric carbon dioxide. With the goal of increasing carbon sequestration, a Congressional project has been planned to afforest about 18 million acres by 2020 in the Southeast United States (SEUS), the Great Lake states, and the Corn Belt states. However, biophysical feedbacks of afforestation have the potential to counter the beneficial climatic consequences of carbon sequestration. To assess the potential biophysical effects of afforestation over the SEUS, the authors designed a set of initial value ensemble experiments and long-term quasi-equilibrium experiments in a fully coupled Community Climate System Model, version 3.5 (CCSM3.5). Model results show that afforestation over the SEUS not only has a local cooling effect in boreal summer [June–August (JJA)] at short and long time scales but also induces remote warming over adjacent regions of the SEUS at long time scales. Precipitation, in response to afforestation, increases over the SEUS (local effect) and decreases over adjacent regions (remote effect) in JJA. The local surface cooling and increase in precipitation over SEUS in JJA are hydrologically driven by the changes in evapotranspiration and latent heat flux. The remote surface warming and decrease in precipitation over adjacent regions are adiabatically induced by anomalous subsidence. Our results suggest that the planned afforestation efforts should be developed carefully by taking account of short-term (local) and long-term (remote) biophysical effects of afforestation.

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Zhengyu Liu, M. Notaro, J. Kutzbach, and Naizhuang Liu

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The feedback between global vegetation greenness and surface air temperature and precipitation is assessed using remote sensing observations of monthly fraction of photosynthetically active radiation (FPAR) for 1982 to 2000 with a 2.5° grid resolution. Lead/lag correlations are used to infer vegetation–climate interactions. Furthermore, a statistical method is used to quantify the efficiency of vegetation feedback on climate in the observations. This feedback analysis provides a first quantitative assessment of global vegetation feedback on climate. In northern mid- and high latitudes, vegetation variability is found to be driven predominantly by temperature; in the meantime, vegetation also exerts a strong positive feedback on temperature with the feedback accounting for over 10%–25% of the total monthly temperature variance. The strongest positive feedback occurs in the boreal regions of southern Canada/northern United States, northern Europe, and southern Siberia, where the feedback efficiency exceeds 1°C (0.1 FPAR)−1. Over most of the Tropics and subtropics (outside the equatorial rain belt), vegetation is driven primarily by precipitation. However, little vegetation feedback is found on local precipitation when averaged year-round, with the feedback explained variance usually accounting for less than 5% of the total precipitation variance. Nevertheless, in a few isolated small regions such as Northeast Brazil, East Africa, East Asia, and northern Australia, there appears to be some positive vegetation feedback on local precipitation, with the feedback efficiency over 1 cm month−1 (0.1 FPAR)−1. Further studies suggest a significant seasonal variation of the vegetation feedback in some regions. A preliminary analysis also seems to suggest an enhanced intensity of the vegetation feedback, especially on precipitation, at longer time scales and over a larger grid box area. Limitations and implications of the assessment of vegetation feedback are also discussed. The assessed vegetation feedback is shown to be valuable for the evaluation of vegetation–climate feedback in coupled climate–vegetation models.

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