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Huang Qian, Yao Suxiang, and Zhang Yaocun

Abstract

A regional air–sea coupled climate model based on the third regional climate model (RegCM3) and the regional oceanic model [the Princeton Ocean Model (POM)] is used to analyze the local air–sea interaction over East Asia in this study. The results indicate that the simulated sea surface temperature (SST) of the coupled model RegCM3–POM is reasonably accurate, and that the spatial pattern and temporal variation are consistent with that of the Global Sea Ice and Sea Surface Temperature dataset (GISST). The correlation between the SST and the atmospheric variables shows that the uncoupled model RegCM3 forced by the given SST cannot reproduce the real-time and SST lag correlation between SST and precipitation, and between SST and surface wind speed, whereas the relationship in the coupled model RegCM3–POM is reasonably accurate. RegCM3–POM reflects the air–sea interaction in the South China Sea and western Pacific Ocean, where the SST lead correlation is the inverse of the SST lag correlation between SST and precipitation, and strong winds bring warm water to the midlatitudes, so the correlation between wind speed and SST is negative in low latitudes and positive in the Kuroshio area. The uncoupled model fails to reproduce the effect of the atmosphere on the ocean. The further study on air–sea interaction in the South China Sea indicates that the earlier warm seawater corresponds to strong sensible heat flux, evaporation, precipitation, and weak net solar radiation, and the early strong sensible heat flux, evaporation, wind at the 10-m level, and weak net solar radiation cause the cold SST.

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Shibo Yao, Dabang Jiang, and Zhongshi Zhang

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In this study, the Flexible Particle dispersion model (FLEXPART) is applied to determine the moisture source of heavy precipitation in Xinjiang in the wet season (April–September) from 1979 to 2018. This is investigated for different meteorological patterns of heavy precipitation categories based on the self-organizing maps (SOM) method. The SOM results suggest that there are four main meteorological patterns (N1, N2, N3, and N4) for heavy precipitation in Xinjiang. These match the strength and position of geopotential height anomalies at middle-to-high levels over central Asia and indicate the anomalous activities of the central Asia trough and vortex. Further analysis shows that the heavy precipitation is centered at the Tianshan Mountains and the Kunlun Mountains in the N1 and N3 patterns and around the Tianshan Mountains in the N2 and N4 patterns. There are four moisture source regions that contribute to each of the four meteorological patterns for heavy precipitation in Xinjiang, which are listed in descending order of their contribution rates: southern Xinjiang (29%–37%), north-central Asia (19%–27%), northern Xinjiang (14%–19%), and south-central Asia (13%–16%). The contribution of each source to the heavy precipitation in Xinjiang varies with the meteorological pattern. Additionally, the contribution rates of each source region match well with the precipitation-related particle aggregation before heavy precipitation days. These results help us better understand the moisture source of the heavy precipitation in Xinjiang.

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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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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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Mao-Sung Yao and Peter H. Stone

Abstract

The moist convection parameterization used in the GISS 3-D GCM is adapted for use in a two-dimensional (2-D) zonally averaged statisticai-dynamical model. Experiments with different versions of the parameterization show that its impact on the general circulation in the 2-D model does not parallel its impact in the 3-D model unless the effect of zonal variations is parameterized in the moist convection calculations. A parameterization of the variations in moist static energy is introduced in which the temperature variations are calculated from baroclinic stability theory, and the relative humidity is assumed to be constant. Inclusion of the zonal variations of moist static energy in the 2-D moist convection parameterization allows just a fraction of a latitude circle to be unstable and enhances the amount of deep convection. This leads to a 2-D simulation of the general circulation very similar to that in the 3-D model.

The experiments show that the general circulation is sensitive to the parameterized amount of deep convection in the subsident branch of the Hadley cell. The more there is, the weaker are the Hadley cell circulations and the westerly jets. The experiments also confirm the effects of momentum mixing associated with moist convection found by earlier investigator and, in addition, show that the momentum mixing weakens the Ferrel cell. An experiment in which the moist convection was removed while the hydrological cycle was retained and the eddy forcing was held fixed shows that moist convection by itself stabilizes the tropics, reduces the Hadley circulation, and reduces the maximum speeds in the westerly jets.

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Peter H. Stone and Mao-Sung Yao

Abstract

The effect of eddy momentum fluxes on the general circulation is investigated with the aid of perpetual January simulations with a two-dimensional, zonally averaged model. Sensitivity experiments with this model show that the vertical eddy flux has a negligible effect on the general circulation, while the meridional eddy flux has a substantial effect. The experiments on the effect of the mefidional eddy flux essentially confirm the resultsfound by Schneider in a similar (but not identical) set of sensitivity experiments, and, in addition, show that the vertical structure of the mefidional eddy flux has a relatively small effect on the general circulation.

In order to parameterize the vertically integrated mefidional eddy momentum flux, we take Green's parameterization of this quantity and generalize it to allow for the effects of condensation. In order to do this, it is necessary to use Leovy's approximation for the eddy fluctuations in specific humidity. With this approximation the equivalent potential vorticity defined by Saltzman is conserved even when condensation occurs. Leovy's approximation also allows one to generalize the relation between quasi-geostrophic potential vorticity and theEliassen-Palm flux by replacing the potential vorticity and potential temperature by the corresponding equivalent quantities. Thus, the eddy momentum flux can be related to the eddy fluxes of two conserved quantities even when condensation is present. The eddy fluxes of the two conserved quantities are parametefized by mixing-length expressions, with the mixing coefficient taken to be the sum of Branscome's mixing coefficient, plus a correction which allows for nonlinear effects onthe eddy structure and ensures global momentum conservation.

The parametefization of the mefidional eddy transport is tested in another perpetual January simulation with the two-dimensional averaged model. The results are compared with a parallel three-dimensional simulation which calculates the eddy transport explicitly. The parameterization reproduces the latitudinal and seasonal (interhemisphefic) variations and the magnitude of the eddy transport calculated in the three-dimensional simulation reasonably well.

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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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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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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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