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Guihua Wang, Chunzai Wang, and Rui Xin Huang

Abstract

Based on the Simple Ocean Data Assimilation (SODA) dataset and three types of Sverdrup streamfunction, an interdecadal variability of the eastward current in the middle South China Sea (SCS) during summer is identified. Both the pattern and strength of the summer Asian monsoon wind stress curl over the SCS contribute to the interdecadal variability of this current. From 1960 to 1979, the monsoon intensified and the zero wind stress curl line shifted southward. Both the core of positive wind stress curl in the northern SCS and the negative curl in the southern SCS moved southward and thus induced a southward shift of both the southern anticyclonic and northern cyclonic gyres, resulting in a southward displacement of the eastward current associated with these two gyres. In the meantime, the southern (northern) SCS anticyclonic (cyclonic) ocean gyre weakened (strengthened) and therefore also induced the southward shift of the eastward current near the intergyre boundary. In contrast, the eastward current shifted northward from 1980 to 1998 because the monsoon relaxed and the zero wind stress curl line shifted northward. After 1998, the eastward jet moved southward again as the zero wind stress curl line shifted southward and the SCS monsoon strengthened. The eastward current identified from the baroclinic streamfunction moved about 1.7° more southward than that from the barotropic streamfunction, indicating that the meridional position of the eastward current is depth dependent.

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Lizhi Tao, Xinguang He, and Rui Wang

Abstract

In this study, a hybrid least squares support vector machine (HLSSVM) model is presented for effectively forecasting monthly precipitation. The hybrid method is designed by incorporating the empirical mode decomposition (EMD) for data preprocessing, partial information (PI) algorithm for input identification, and differential evolution (DE) for model parameter optimization into least squares support vector machine (LSSVM). The HLSSVM model is examined by forecasting monthly precipitation at 138 rain gauge stations in the Yangtze River basin and compared with the LSSVM and LSSVM–DE. The LSSVM–DE is built by combining the LSSVM and DE. Two statistical measures, Nash–Sutcliffe efficiency (NSE) and relative absolute error (RAE), are employed to evaluate the performance of the models. The comparison of results shows that the LSSVM–DE gets a superior performance to LSSVM, and the HLSSVM provides the best performance among the three models for monthly precipitation forecasts. Meanwhile, it is also observed that all the models exhibit significant spatial variability in forecast performance. The prediction is most skillful in the western and northwestern regions of the basin. In contrast, the prediction skill in the eastern and southeastern regions is generally low, which shows a strong relationship with the randomness of precipitation. Compared to LSSVM and LSSVM–DE, the proposed HLSSVM model gives a more significant improvement for most of the stations in the eastern and southeastern regions with higher randomness.

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Rui Mei, Guiling Wang, and Huanghe Gu

Abstract

This study investigates the land–atmosphere coupling strength during summer over the United States using the Regional Climate Model version 4 (RegCM4)–Community Land Model version 3.5 (CLM3.5). First, a 10-yr simulation driven with reanalysis lateral boundary conditions (LBCs) is conducted to evaluate the model performance. The model is then used to quantify the land–atmosphere coupling strength, predictability, and added forecast skill (for precipitation and 2-m air temperature) attributed to realistic land surface initialization following the Global Land–Atmosphere Coupling Experiment (GLACE) approaches. Similar to previous GLACE results using global climate models (GCMs), GLACE-type experiments with RegCM4 identify the central United States as a region of strong land–atmosphere coupling, with soil moisture–temperature coupling being stronger than soil moisture–precipitation coupling, and confirm that realistic soil moisture initialization is more promising in improving temperature forecasts than precipitation forecasts. At a 1–15-day lead, the added forecast skill reflects predictability (or land–atmosphere coupling strength) indicating that that model can capture the realistic land–atmosphere coupling at a short time scale. However, at a 16–30-day lead, predictability cannot translate to added forecast skill, implying that the coupling at the longer time scale may not be represented well in the model. In addition, comparison of results from GLACE2-type experiments with RegCM4 driven by reanalysis LBCs and those driven by GCM LBCs suggest that the intrinsic land–atmosphere coupling strength within the regional model is the dominant factor for the added forecast skill at a 1–15-day lead, while the impact of LBCs from the GCM may play a dominant role in determining the signal of added forecast skill in the regional model at a 16–30-day lead. It demonstrates the complexities of using regional climate model for GLACE-type studies.

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Rui Wang, Yunfei Fu, Tao Xian, Fengjiao Chen, Renmin Yuan, Rui Li, and Guosheng Liu

Abstract

Variations and trends of atmospheric precipitable water (APW) are examined using radiosonde data from Integrated Global Radiosonde Archive (IGRA) and China Meteorological Administration (CMA) from 1995 to 2012 in mainland China. The spatial distribution of the climatological mean APW shows that APW gradually decreases from the southern to the northern regions of mainland China. The seasonal mean pattern of APW shows clear regional difference, except for higher APW in summer (June–August) and lower APW in winter (December–February). Four regions show significantly downward trends in APW. Moreover, the trends of APW calculated using reanalysis datasets are consistent with the results of radiosonde data. Furthermore, the relationship between APW and the general circulation is investigated. The summer East Asian monsoon intensity and El Niño events show positive correlations with APW, whereas the North Atlantic Oscillation shows negative correlation with APW. The downward trend of APW is in accordance with the downward trend of mean column temperature (1000–300 hPa) at most stations, which suggests that decreasing mean column temperature results in decreasing APW in mainland China. Additionally, statistical analysis has revealed the regional trends in APW are not consistent with the regional trends in precipitation, implying that not all the variation of precipitation can be explained by APW.

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Guihua Wang, Rui Xin Huang, Jilan Su, and Dake Chen

Abstract

The dynamic influence of thermohaline circulation on wind-driven circulation in the South China Sea (SCS) is studied using a simple reduced gravity model, in which the upwelling driven by mixing in the abyssal ocean is treated in terms of an upward pumping distributed at the base of the upper layer.

Because of the strong upwelling of deep water, the cyclonic gyre in the northern SCS is weakened, but the anticyclonic gyre in the southern SCS is intensified in summer, while cyclonic gyres in both the southern and northern SCS are weakened in winter. For all seasons, the dynamic influence of thermohaline circulation on wind-driven circulation is larger in the northern SCS than in the southern SCS. Analysis suggests that the upwelling associated with the thermohaline circulation in the deep ocean plays a crucial role in regulating the wind-driven circulation in the upper ocean.

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Di Liu, Guiling Wang, Rui Mei, Zhongbo Yu, and Huanghe Gu

Abstract

This paper focuses on diagnosing the strength of soil moisture–atmosphere coupling at subseasonal to seasonal time scales over Asia using two different approaches: the conditional correlation approach [applied to the Global Land Data Assimilation System (GLDAS) data, the Climate Forecast System Reanalysis (CFSR) data, and output from the regional climate model, version 4 (RegCM4)] and the Global Land–Atmosphere Coupling Experiment (GLACE) approach applied to the RegCM4. The conditional correlation indicators derived from the model output and the two observational/reanalysis datasets agree fairly well with each other in the spatial pattern of the land–atmosphere coupling signal, although the signal in CFSR data is stronger and spatially more extensive than the GLDAS data and the RegCM4 output. Based on the impact of soil moisture on 2-m air temperature, the land–atmosphere coupling hotspots common to all three data sources include the Indochina region in spring and summer, the India region in summer and fall, and north-northeastern China and southwestern Siberia in summer. For precipitation, all data sources produce a weak and spatially scattered signal, indicating the lack of any strong coupling between soil moisture and precipitation, for both precipitation amount and frequency. Both the GLACE approach and the conditional correlation approach (applied to all three data sources) identify evaporation and evaporative fraction as important links for the coupling between soil moisture and precipitation/temperature. Results on soil moisture–temperature coupling strength from the GLACE-type experiment using RegCM4 are in good agreement with those from the conditional correlation analysis applied to output from the same model, despite substantial differences between the two approaches in the terrestrial segment of the land–atmosphere coupling.

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Ling Ling Liu, Wei Wang, and Rui Xin Huang

Abstract

Wind stress and tidal dissipation are the most important sources of mechanical energy for maintaining the oceanic general circulation. The contribution of mechanical energy due to tropical cyclones can be a vitally important factor in regulating the oceanic general circulation and its variability. However, previous estimates of wind stress energy input were based on low-resolution wind stress data in which strong nonlinear events, such as tropical cyclones, were smoothed out.

Using a hurricane–ocean coupled model constructed from an axisymmetric hurricane model and a three-layer ocean model, the rate of energy input to the world’s oceans induced by tropical cyclones over the period from 1984 to 2003 was estimated. The energy input is estimated as follows: 1.62 TW to the surface waves and 0.10 TW to the surface currents (including 0.03 TW to the near-inertial motions). The rate of gravitational potential energy increase due to tropical cyclones is 0.05 TW. Both the energy input from tropical cyclones and the increase of gravitational potential energy of the ocean show strong interannual and decadal variability with an increasing rate of 16% over the past 20 years. The annual mean diapycnal upwelling induced by tropical cyclones over the past 20 years is estimated as 39 Sv (Sv ≡ 106 m3 s−1). Owing to tropical cyclones, diapycnal mixing in the upper ocean (below the mixed layer) is greatly enhanced. Within the regimes of strong activity of tropical cyclones, the increase of diapycnal diffusivity is on the order of (1 − 6) × 10−4 m2 s−1. The tropical cyclone–related energy input and diapycnal mixing may play an important role in climate variability, ecology, fishery, and environments.

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Guihua Wang, Shang-Ping Xie, Rui Xin Huang, and Changlin Chen

Abstract

The subsurface ocean response to anthropogenic climate forcing remains poorly characterized. From the Coupled Model Intercomparison Project (CMIP), a robust response of the lower thermocline is identified, where the warming is considerably weaker in the subtropics than in the tropics and high latitudes. The lower thermocline change is inversely proportional to the thermocline depth in the present climatology. Ocean general circulation model (OGCM) experiments show that sea surface warming is the dominant forcing for the subtropical gyre change in contrast to natural variability for which wind dominates, and the ocean response is insensitive to the spatial pattern of surface warming. An analysis based on a ventilated thermocline model shows that the pattern of the lower thermocline change can be interpreted in terms of the dynamic response to the strengthened stratification and downward heat mixing. Consequently, the subtropical gyres become intensified at the surface but weakened in the lower thermcline, consistent with results from CMIP experiments.

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Xiao-Yi Yang, Rui Xin Huang, and Dong Xiao Wang

Abstract

Using 40-yr ECMWF Re-Analysis (ERA-40) data and in situ observations, the positive trend of Southern Ocean surface wind stress during two recent decades is detected, and its close linkage with spring Antarctic ozone depletion is established. The spring Antarctic ozone depletion affects the Southern Hemisphere lower-stratospheric circulation in late spring/early summer. The positive feedback involves the strengthening and cooling of the polar vortex, the enhancement of meridional temperature gradients and the meridional and vertical potential vorticity gradients, the acceleration of the circumpolar westerlies, and the reduction of the upward wave flux. This feedback loop, together with the ozone-related photochemical interaction, leads to the upward tendency of lower-stratospheric zonal wind in austral summer. In addition, the stratosphere–troposphere coupling, facilitated by ozone-related dynamics and the Southern Annular Mode, cooperates to relay the zonal wind anomalies to the upper troposphere. The wave–mean flow interaction and the meridional circulation work together in the form of the Southern Annular Mode, which transfers anomalous wind signals downward to the surface, triggering a striking strengthening of surface wind stress over the Southern Ocean.

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Mengnan Zhao, Rui M. Ponte, Ou Wang, and Rick Lumpkin

Abstract

Properly fitting ocean models to observations is crucial for improving model performance and understanding ocean dynamics. Near-surface velocity measurements from the Global Drifter Program (GDP) contain valuable information about upper-ocean circulation and air–sea fluxes on various space and time scales. This study explores whether GDP measurements can be used for usefully constraining the surface circulation from coarse-resolution ocean models, using global solutions produced by the consortium for Estimating the Circulation and Climate of the Ocean (ECCO) as an example. To address this problem, a careful examination of velocity data errors is required. Comparisons between an ECCO model simulation, performed without any data constraints, and GDP and Ocean Surface Current Analyses Real-Time (OSCAR) velocity data, over the period 1992–2017, reveal considerable differences in magnitude and pattern. These comparisons are used to estimate GDP data errors in the context of the time-mean and time-variable surface circulations. Both instrumental errors and errors associated with limitations in model physics and resolution (representation errors) are considered. Given the estimated model–data differences, errors, and signal-to-noise ratios, our results indicate that constraining ocean-state estimates to GDP can have a substantial impact on the ECCO large-scale time-mean surface circulation over extensive areas. Impact of GDP data constraints on the ECCO time-variable circulation would be weaker and mainly limited to low latitudes. Representation errors contribute substantially to degrading the data impacts.

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