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Neng-Chun Yao, S. Neshyba, and H. Crew

Abstract

Application of rotary cross-bispectra and energy transfer functions to a set of wind and current data measured from the Totem research buoy shows these elements to be non-Gaussian and that nonlinear interactions do occur between the wind stress and current at 14 m depth. Such transfers account for 35% of the total energy estimates and for 100% of the estimates at the inertial frequency. For the latter, the most effective set of nonlinear interacting components include half-day and quarter-day components of wind stress. No energy transfers linearly. The effect of nonlinear interaction in broadening the current response spectrum is noted.

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XiaoJing Jia, Hai Lin, and Xia Yao

Abstract

The influence of the tropical Pacific sea surface temperature (SST) on the wintertime surface air temperature (SAT) in China is investigated using both the observational data and the output of coupled ocean–atmosphere numerical models during the period from 1960 to 2006. A singular value decomposition analysis (SVD) is applied between 500-hPa geopotential height (Z500) in the Northern Hemisphere and SST in the tropical Pacific Ocean to get the tropical Pacific SST-forced atmospheric patterns. The association of the SAT over China and the tropical Pacific SST is measured by calculating the temporal correlation coefficient (TCC) between the SAT and the expansion coefficient of the atmospheric component of the leading two SVD modes. Results show that the SAT over China is significantly correlated to the second SVD mode (SVD2). The SST component of SVD2 is characterized by negative tropical Pacific SST anomalies centered over the midequatorial Pacific Ocean. The atmospheric component of SVD2 (ASVD2) shares many similarities in spatial structures to the Arctic Oscillation (AO). The time variation of ASVD2, however, is found more closely correlated to the variation of SAT over China than the AO. When SVD2 is in its positive phase, the SAT over China tends to be warmer than normal. Further analysis indicates that the TCC between the SAT in China and ASVD2 is largely decreased after the long-term climate trend is removed. The time variability of the tropical Pacific SST-forced large-scale atmospheric patterns and its relationship to SAT are reasonably captured by the multimodel ensemble (MME) seasonal forecasts. An examination of the MME forecast skill indicates that ASVD2 contributes significantly to the TCC skill of MME forecasts.

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Long Jin, Cai Yao, and Xiao-Yan Huang

Abstract

A new nonlinear artificial intelligence ensemble prediction (NAIEP) model has been developed for predicting typhoon intensity based on multiple neural networks with the same expected output and using an evolutionary genetic algorithm (GA). The model is validated with short-range forecasts of typhoon intensity in the South China Sea (SCS); results show that the NAIEP model is clearly better than the climatology and persistence (CLIPER) model for 24-h forecasts of typhoon intensity. Using identical predictors and sample cases, predictions of the genetic neural network (GNN) ensemble prediction (GNNEP) model are compared with the single-GNN prediction model, and it has been proven theoretically that the former is more accurate. Computation and analysis of the generalization capacity of GNNEP also demonstrate that the prediction of the ensemble model integrates predictions of its optimized ensemble members, so the generalization capacity of the ensemble prediction model is also enhanced. This model better addresses the “overfitting” problem that generally exists in the traditional neural network approach to practical weather prediction.

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Anthony D. Del Genio and Mao-Sung Yao

Abstract

We examine the response of the GISS global climate model to different parameterizations of moist convective man flux. A control run with arbitrarily specified updraft mass flux is compared to experiments that predict cumulus mass flux on the basis of low-level convergence, convergence plus surface evaporation, or convergence and evaporation modified by varying boundary layer height. An experiment that includes a simple parameterization of saturated convective-scale downdrafts is also described. Convergence effects on cumulus mass flux significantly improve the model's January climatology by increasing the frequency of occurrence of deep convection in the tropics and decreasing it at high latitudes, shifting the ITCZ from 12°N to 4°5, strengthening convective heating in the western Pacific, and increasing tropical long-wave eddy kinetic energy. Surface evaporation effects generally oppose the effects of convergence but are necessary to produce realistic continental convective heating and well-defined marine shallow cumulus regions. Varying boundary layer height (as prescribed by variations in lifting condensation level) has little effect on the model climatology. Downdrafts, however, reinforce many of the positive effects of convergence while also improving the model's vertical humidity profile and radiation balance. The diurnal cycle of precipitation over the West Pacific is best simulated when convergence determines cumulus mass flux, while surface flux effects are needed to reproduce diurnal variations in the continental ITCZ. In each experiment the model correctly simulates the observed correlation between deep convection strength and tropical sea surface temperature; the parameterization of cumulus mass flux has little effect on this relationship. The experiments have several implications for cloud effects on climate sensitivity. The dependence of cumulus mass flux on vertical motions, and the insensitivity of mean vertical motions to changes in forcing, suggests that the convective response to climate forcing may be weaker than that estimated in previous global climate model simulations that link convection only to moist static instability. This implies that changes in cloud cover and hence positive cloud feedback have been overestimated in these climate change experiments. Downdrafts may affect the feedback in the same sense by replenishing boundary layer moisture relative to cumulus parameterization schemes with only dry compensating subsidence.

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Peter H. Stone and Mao-Sung Yao

Abstract

A number of perpetual January simulations are carried out with a two-dimensional (2-D) zonally averaged model employing various parameterizations of the eddy fluxes of heat (potential temperature) and moisture. The parameterizations are evaluated by comparing these results with the eddy fluxes calculated in a parallel simulation using a three-dimensional (3-D) general circulation model with zonally symmetric forcing. The 3-D model's performance in turn is evaluated by comparing its results using realistic (nonsymmetric) boundary conditions with observations.

Branscome's parameterization of the meridional eddy flux of heat and Leovy's parameterization of the meridional eddy flux of moisture simulate the seasonal and latitudinal variations of these fluxes reasonably well, while somewhat underestimating their magnitudes. In particular, Branscome's parameterization underestimates the vertically integrated flux of heat by about 30%, mainly because it misses out the secondary peak in this flux near the tropopause; and Leovy's parameterization of the meridional eddy flux of moisture underestimates the magnitude of this flux by about 20%. The analogous parameterizations of the vertical eddy fluxes of heat and moisture are found to perform much more poorly, i.e., they give fluxes only one quarter to one half as strong as those calculated in the 3-D model. New parameterizations of the vertical eddy fluxes are developed that take into account the enhancement of the eddy mixing slope in a growing baroclinic wave due to condensation, and also the effect of eddy fluctuations in relative humidity. The new parameterizations, when tested in the 2-D model, simulate the seasonal, latitudinal, and vertical variations of the vertical eddy fluxes quite well, when compared with the 3-D model, and only underestimate the magnitude of the fluxes by 10% to 20%.

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Mao-Sung Yao and Anthony D. Del Genio

Abstract

The influence of the sea surface temperature distribution on cloud feedbacks is studied by making two sets of doubled CO2 experiments with the Goddard Institute for Space Studies (GISS) GCM at 4° latitude × 5° longitude resolution. One set uses Q fluxes obtained by prescribing observed sea surface temperatures (MODELII′), and the other set uses Q fluxes obtained by prescribing the simulated sea surface temperature of a coupled ocean–atmosphere model (MODELIIO). The global and annual mean surface air temperature change (ΔT s) obtained in MODELII′ is reduced from 4.11° to 3.02°C in MODELIIO. This reduced sensitivity, aside from reduced sea ice/snow–albedo feedback, is mainly due to cloud feedback that becomes nearly neutral in MODELIIO. Furthermore, the negative effect on climate sensitivity of anvil clouds of large optical thickness identified by Yao and Del Genio changes its sign in MODELIIO primarily due to sharply reduced increases of cloud water in the tropical upper troposphere. Colder tropical sea surface temperature in MODELIIO results in weaker deep convective activity and a more humid lower atmosphere in the warmer climate relative to MODELII′, which then removes the negative feedback of anvil clouds and sharply reduces the positive feedback of low clouds. However, an overall positive cloud optical thickness feedback is still maintained in MODELIIO.

It is suggested that the atmospheric climate sensitivity, partially due to changes in cloud feedbacks, may be significantly different for climate changes associated with different patterns of sea surface temperature change, as for example in warm versus cold paleoclimate epochs. Likewise, the climate sensitivity in coupled atmosphere–ocean models is also likely to be significantly different from the results obtained in Q-flux models due to the different simulations of sea surface temperature patterns in each type of model.

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Kao-Shen Chung and I-An Yao

Abstract

Severe weather nowcasting is a crucial mission of atmospheric science for the betterment of society to save life, limb, and property. In this study, composite radar data from the Central Weather Bureau of 16 typhoons are collected to examine the statistical performance of the McGill Algorithm for Precipitation nowcasting using Lagrangian Extrapolation (MAPLE) over Taiwan, an extrapolation algorithm that predicts future precipitation based on current radar echoes. In addition, instead of mixing the precipitation between radar extrapolation and numerical model forecast as in previous studies, a blending system is formed by synthesizing the wind information from model forecast with the echo extrapolation motion field via a variational algorithm to improve the nowcasting system. The statistical results of the radar echo extrapolation for 16 typhoon cases show that while the quantitative precipitation nowcasting skill can persist for up to 2 h, significant distortion for the rotational system is found after 2 h. On the other hand, the blending system helps to capture and maintain the rotation of typhoon rainband structures. The blending system extends the nowcasting skill by 1 h to a total of 3 h. Furthermore, the blending scheme performs especially well after the typhoon makes landfall in Taiwan. For disaster prevention and mitigation, this blending nowcasting technique may provide effective weather information immediately.

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Mao-Sung Yao and Anthony D. Del Genio

Abstract

An improved version of the GISS Model II cumulus parameterization designed for long-term climate integrations is used to study the effects of entrainment and multiple cloud types on the January climate simulation. Instead of prescribing convective mass as a fixed fraction of the cloud base grid-box mass, it is calculated based on the closure assumption that the cumulus convection restores 0the atmosphere to a neutral most convective state at cloud base. This change alone significantly improves the distribution of precipitation, convective mass exchanges and frequencies in the January climate. The vertical structure of the tropical atmosphere exhibits quasi-equilibrium behavior when this closure is used, even though there is no explicit constraint applied above cloud base. Global aspects of the simulation using the neutral buoyancy closure are almost identical to those obtained in a previous study with a closure relating cumulus mass flux explicitly to large-scale forcing.

A prescription of 0.2 km−1 for the fractional rate of entrainment lower the peak of the convective heating profile, reduces equatorial specific humidifies in the upper atmosphere to more realistic values, and greatly increases eddy kinetic energy at the equator due to reduced momentum mixing. With two cloud types per convective event, each cloud type having a prescribed size and entrainment rate, a clear bimodal distribution of convective mass flux is obtained in strong convective events. At the same time, many of the desirable climate features produced by the neutral buoyancy and entrainment experiments are preserved.

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Yonghong Yao, Hai Lin, and Qigang Wu

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The mei-yu onset over the middle to lower reaches of the Yangtze River Valley (MLYRV) varies considerably from early June to mid-July, which leads to large interannual changes in rainy-season length, total summer rainfall, and flooding potential. Previous studies have investigated the impact of El Niño–Southern Oscillation (ENSO) on the mei-yu onset. This study shows that a strong (weak) East Asian and western North Pacific (EAWNP) intraseasonal oscillation (ISO) in spring leads to an early (late) onset of the mei-yu over the MLYRV, and this ISO–mei-yu relationship is attributed to different types of ENSO in the preceding winter. A strong EAWNP ISO in spring is related to an eastern Pacific El Niño (EP El Niño) in the previous winter, and negative sea surface temperature (SST) anomalies in the eastern Indian Ocean and the South China Sea (SCS) in May, which can cause an early onset of the South China Sea summer monsoon that also favors an early mei-yu onset. In contrast, a weak EAWNP ISO in spring is associated with a central Pacific El Niño (CP El Niño) before April, but with an EP El Niño after April, and positive SST anomalies in both the eastern Indian Ocean and the SCS in May. A statistical forecast model combining the intensity of spring EAWNP ISO, CP ENSO, and EP ENSO indices shows a high prediction skill of the observed mei-yu onset date.

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Yonghong Yao, Hai Lin, and Qigang Wu

Abstract

Using pentad data of the Northern Hemisphere extended winter (November–March) from 1979 to 2012 derived from the daily rainfall of the National Meteorological Information Center of China, subseasonal variability of precipitation in China is analyzed. The two dominant modes of subseasonal variability are identified with an empirical orthogonal function (EOF) analysis. The first EOF mode (EOF1) is characterized by a monopole in South China, whereas the second EOF mode (EOF2) has a meridional dipole structure with opposite precipitation anomalies over the Yangtze River basin and the coastal area of South China. These two modes tend to have a phase shift to each other in both space and time, indicating that part of their variability represents a southward-propagating pattern.

The subseasonal variability is decomposed into two components: one related to the Madden–Julian oscillation (MJO) and the other independent of MJO. It is found that the MJO contributes to about 10% of the precipitation variability in South China. EOF1 is associated with MJO phase 3, corresponding to enhanced equatorial convection in the Indian Ocean and depressed convection in the western Pacific, while EOF2 is related to MJO phase 5 when the enhanced tropical convection moves to the Maritime Continent region. Subseasonal precipitation variability in China that is independent of the MJO is especially affected by processes including tropical convection variability and the “cold surge” phenomenon or the development of a Siberian high and cold-air outbreak in East Asia associated with a wave train from the North Atlantic.

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