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Qianzi Yang, Yingying Zhao, Qin Wen, Jie Yao, and Haijun Yang

Abstract

The Bjerknes compensation (BJC) under global warming is studied using a simple box model and a coupled Earth system model. The BJC states the out-of-phase changes in the meridional atmosphere and ocean heat transports. Results suggest that the BJC can occur during the transient period of global warming. During the transient period, the sea ice melting in the high latitudes can cause a significant weakening of the Atlantic meridional overturning circulation (AMOC), resulting in a cooling in the North Atlantic. The meridional contrast of sea surface temperature would be enhanced, and this can eventually enhance the Hadley cell and storm-track activities in the Northern Hemisphere. Accompanied by changes in both ocean and atmosphere circulations, the northward ocean heat transport in the Atlantic is decreased while the northward atmosphere heat transport is increased, and the BJC occurs in the Northern Hemisphere. Once the freshwater influx into the North Atlantic Ocean stops, or the ocean even loses freshwater because of strong heating in the high latitudes, the AMOC would recover. Both the atmosphere and ocean heat transports would be enhanced, and they can eventually recover to the state of the control run, leading to the BJC to become invalid. The above processes are clearly demonstrated in the coupled model CO2 experiment. Since it is difficult to separate the freshwater effect from the heating effect in the coupled model, a simple box model is used to understand the BJC mechanism and freshwater’s role under global warming. In a warming climate, the freshwater flux into the ocean can cool the global surface temperature, mitigating the temperature rise. Box model experiments indicate clearly that it is the freshwater flux into the North Atlantic that causes out-of-phase changes in the atmosphere and ocean heat transports, which eventually plays a stabilizing role in global climate change.

Open access
Jie Cao, Ping Yao, Lin Wang, and Kui Liu

Abstract

Based on reanalysis and observational datasets, this study proposes a reasonable mechanism for summer rainfall variations over the low-latitude highlands (LLH) of China, in which a subtropical Indian Ocean dipole (SIOD)-like pattern is the key external thermal forcing. In summers with a positive SIOD-like pattern, sea surface temperature (SST) anomalies may lead to lower-tropospheric divergence over the tropical Indian Ocean and convergence over the subtropical southwestern Indian Ocean and Arabian Sea. The convergence over the Arabian Sea can induce easterly anomalies of the divergent wind component off the eastern coast of the Bay of Bengal (BOB), while the divergence over the tropical Indian Ocean can change the interhemispheric vertical circulation and produce a descending motion over the same area and cyclonic anomalies in the rotational wind component over the Indian peninsula. The combined effect of the divergent and rotational wind anomalies and enhanced interhemispheric vertical circulation facilitates easterly anomalies and weakens climatological water vapor flux to the northern BOB. Therefore, anomalous water vapor divergence and less precipitation are observed over the LLH. In summers with a negative SIOD-like pattern, the situation is approximately the same but with opposite polarity and a weaker role of the divergent wind component. Further analyses indicate that the summertime SIOD-like pattern can be traced to preceding seasons, especially in positive SIOD-like years. The SST–wind–evaporation feedback mechanism could account for maintenance of the SIOD-like pattern. These results provide efficient prediction potential for summer rainfall variations over the LLH.

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Yao Ha, Zhong Zhong, Yijia Hu, and Xiuqun Yang

Abstract

This study investigates the influences of ENSO on tropical cyclone (TC) kinetic energy and its meridional transport in the western North Pacific (WNP) using the TC wind field obtained after a method for removing TC vortices from reanalysis data is applied. Results show that ENSO strongly modulates TC kinetic energy and its meridional transport in the WNP, but their effects and regions differ. The TC kinetic energy is positively correlated with the Niño-3.4 index in the entire WNP, and its poleward transport is positively (negatively) correlated with the Niño-3.4 index in the eastern WNP (the western WNP and the South China Sea); these correlations are statistically significant. The maximum TC kinetic energy is located around 25°N, 135°E (25°N, 125°E) in the warm (cold) year, showing an east–west pattern during different ENSO phases. The meridional transport of TC kinetic energy exhibits a dipole pattern over the WNP, with the poleward (equatorward) transport in the eastern (western) WNP. Both poleward and equatorward transports strengthen (weaken) and shift eastward (westward) in El Niño (La Niña) years. Therefore, El Niño has strong influences on TC kinetic energy and its meridional transport.

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Lei Wang, Tandong Yao, Chenhao Chai, Lan Cuo, Fengge Su, Fan Zhang, Zhijun Yao, Yinsheng Zhang, Xiuping Li, Jia Qi, Zhidan Hu, Jingshi Liu, and Yuanwei Wang

Abstract

Monitoring changes in river runoff at the Third Pole (TP) is important because rivers in this region support millions of inhabitants in Asia and are very sensitive to climate change. Under the influence of climate change and intensified cryospheric melt, river runoff has changed markedly at the TP, with significant effects on the spatial and temporal water resource distribution that threaten water supply and food security for people living downstream. Despite some in situ observations and discharge estimates from state-of-the-art remote sensing technology, the total river runoff (TRR) for the TP has never been reliably quantified, and its response to climate change remains unclear. As part of the Chinese Academy of Sciences’ “Pan-Third Pole Environment Study for a Green Silk Road,” the TP-River project aims to construct a comprehensive runoff observation network at mountain outlets (where rivers leave the mountains and enter the plains) for 13 major rivers in the TP region, thereby enabling TRR to be accurately quantified. The project also integrates discharge estimates from remote sensing and cryosphere–hydrology modeling to investigate long-term changes in TRR and the relationship between the TRR variations and westerly/monsoon. Based on recent efforts, the project provides the first estimate (656 ± 23 billion m3) of annual TRR for the 13 TP rivers in 2018. The annual river runoff at the mountain outlets varies widely between the different TP rivers, ranging from 2 to 176 billion m3, with higher values mainly corresponding to rivers in the Indian monsoon domain, rather than in the westerly domain.

Open access
Dong-Peng Guo, Peng Zhao, Ran Wan, Ren-Tai Yao, and Ji-Min Hu

Abstract

This paper applied a commercial computational fluid dynamics code, STAR-CD, with the renormalization group k–ε turbulence model to simulate the flow and dispersion of contaminants released from a source on the windward side of a hill under different thermal stratifications. In the wake region, the influence of atmospheric stratification on the flow field is inconspicuous under neutral and unstable conditions because of the effect of mechanical disturbance. However, this influence becomes slightly conspicuous under stable conditions. When atmospheric stratification is stable, in the range of z/H < 1.0 (where z is height above the surface and H is height of the hill), the velocity deficits are smaller than those under neutral and unstable conditions. The maximum turbulence kinetic energy (TKE) appears in the wake regions, and the variation in TKE is significantly lower than that under neutral and unstable conditions. When atmospheric stratification is unstable, the vertical and horizontal spread of the plume is slightly greater than that under neutral and stable conditions and the maximum concentration is less than that under neutral conditions. When the Froude number is large (~11; Brunt–Väisälä frequency = 0.52), atmospheric stratification is slightly stable, the structure of flow around the hill is generally similar to that under neutral conditions, and the high-concentration regions are large on the windward side of the hill. Smaller high-concentration regions just appear on the windward side of the hill under unstable conditions. The pollutant concentrations in the wake region of the hill increase as a result of the effect of thermal stability, and the vertical spreading range of the plume along the downwind axis (x axis) is larger than that under neutral and stable conditions.

Free access
Ning Lu, Kevin E. Trenberth, Jun Qin, Kun Yang, and Ling Yao

Abstract

Long-term trends in precipitable water (PW) are an important component of climate change assessments for the Tibetan Plateau (TP). PW products from Moderate Resolution Imaging Spectroradiometer (MODIS) are able to provide good spatial coverage of PW over the TP but limited in time coverage, while the meteorological stations in the TP can estimate long-term PW but unevenly distributed. To detect the decadal trend in PW over the TP, Bayesian inference theory is used to construct long-term and spatially continuous PW data for the TP based on the station and MODIS observations. The prior information on the monthly-mean PW from MODIS and the 63 stations over the TP for 2000–06 is used to get the posterior probability knowledge that is utilized to build a Bayesian estimation model. This model is then operated to estimate continuous monthly-mean PW for 1970–2011 and its performance is evaluated using the monthly MODIS PW anomalies (2007–11) and annual GPS PW anomalies (1995–2011), with RMSEs below 0.65 mm, to demonstrate that the model estimation can reproduce the PW variability over the TP in both space and time. Annual PW series show a significant increasing trend of 0.19 mm decade−1 for the TP during the 42 years. The most significant PW increase of 0.47 mm decade−1 occurs for 1986–99 and an insignificant decrease occurs for 2000–11. From the comparison of the PW data from JRA-55, ERA-40, ERA-Interim, MERRA, NCEP-2, and ISCCP, it is found that none of them are able to show the actual long-term trends and variability in PW for the TP as the Bayesian estimation.

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Chundi Hu, Qigang Wu, Song Yang, Yonghong Yao, Duo Chan, Zhenning Li, and Kaiqiang Deng

Abstract

In this study, the authors apply a lagged maximum covariance analysis (MCA) to capture the cross-seasonal coupled patterns between the Southern Ocean sea surface temperature (SOSST) and extratropical 500-hPa geopotential height anomalies in the Southern Hemisphere, from which Niño-3.4 signals and their linear trends are removed to a certain extent. Statistically significant results show that the dominant feature of ocean–atmosphere interaction is likely the effect of atmosphere on SOSST anomalies, with a peak occurring when the atmosphere leads the SOSST by 1 month.

However, the most eye-capturing phenomenon is that the austral autumn atmospheric signal, characterized by a negatively polarized Antarctic Oscillation (AAO), is significantly related to the gradual evolution of preceding SOSST anomalies, suggesting that the SOSST anomalies tend to exert an effect on the Southern Hemisphere atmospheric circulation. A regression analysis based on SOSST anomaly centers confirms these features. It is also demonstrated that the gradual evolution of changes in SOSST is mainly driven by internal atmospheric variability via surface turbulent heat flux associated with cold or warm advection and that the atmospheric circulation experiences a change from a typical positive AAO to a negative phase in this process. These findings indicate that such a long lead cross-seasonal covariance could contribute to a successful prediction of AAO-related atmospheric circulation in austral autumn from the perspective of SOSST anomalies, with lead times up to 6–7 months.

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Liguo Su, Richard L. Collins, David A. Krueger, and Chiao-Yao She

Abstract

A statistical study is presented of the errors in sodium Doppler lidar measurements of wind and temperature in the mesosphere that arise from the statistics of the photon-counting process that is inherent in the technique. The authors use data from the Colorado State University (CSU) sodium Doppler wind-temperature lidar, acquired at a midlatitude site, to define the statistics of the lidar measurements in different seasons under both daytime and nighttime conditions. The CSU lidar measurements are scaled, based on a 35-cm-diameter receiver telescope, to the use of large-aperture telescopes (i.e., 1-, 1.8-, and 3.5-m diameters). The expected biases in vertical heat flux measurements at a resolution of 480 m and 150 s are determined and compared to Gardner and Yang’s reported geophysical values of 2.3 K m s−1. A cross-correlation coefficient of 2%–7% between the lidar wind and temperature estimates is found. It is also found that the biases vary from −4 × 10−3 K m s−1 for wintertime measurements at night with a 3.5-m telescope to −61 K m s−1 for summertime measurements at midday with a 1-m telescope. During winter, at night, the three telescope systems yield biases in their heat flux measurements that are less than 10% of the reported value of the heat flux; and during summer, at night, the 1.8- and 3.5-m systems yield biases in their heat flux measurements that are less than 10% of the geophysical value. While during winter at midday the 3.5-m system yields biases in their heat flux measurements that are less than 10% of the geophysical value, during summer at midday all of the systems yield flux biases that are greater than the geophysical value of the heat flux. The results are discussed in terms of current lidar measurements and proposed measurements at high-latitude sites.

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Anthony D. Del Genio, Mao-Sung Yao, William Kovari, and Kenneth K-W. Lo

Abstract

An efficient new prognostic cloud water parameterization designed for use in global climate models is described. The scheme allows for life cycle effects in stratiform clouds and permits cloud optical properties to be determined interactively. The parameterization contains representations of all important microphysical processes, including autoconversion, accretion, Bergeron–Findeisen diffusional growth, and cloud/rain water evaporation. Small-scale dynamical processes, including detrainment of convective condensate, cloud-top entrainment instability, and stability-dependent cloud physical thickness variations, are also taken into account. Cloud optical thickness is calculated from the predicted liquid/ice water path and a variable droplet effective radius estimated by assuming constant droplet number concentration. Microphysical and radiative properties are assumed to be different for liquid and ice clouds, and for liquid clouds over land and ocean.

The parameterization is validated in several simulations using the Goddard Institute for Space Studies (GISS) general circulation model (GCM). Comparisons are made with a variety of datasets, including ERBE radiative fluxes and cloud forcing, ISCCP and surface-observed cloud properties, SSM/I liquid water path, and SAGE II thin cirrus cover. Validation is judged on the basis of the model's depiction of both the mean state; diurnal, seasonal, and interannual variability; and the temperature dependence of cloud properties. Relative to the diagnostic cloud scheme used in the previous GISS GCM, the prognostic parameterization strengthens the model's hydrologic cycle and general circulation, both directly and indirectly (via increased cumulus heating). Sea surface temperature (SST) perturbation experiments produce low climate sensitivity and slightly negative cloud feedback for globally uniform SST changes, but high sensitivity and positive cloud feedback when tropical Pacific SST gradients weaken with warming. Changes in the extent and optical thickness of tropical cumulus anvils appear to be the primary factor determining the sensitivity. This suggests that correct simulations of upward transport of convective condensate and of Walker circulation changes are of the highest priority for a realistic estimate of cloud feedback in actual greenhouse gas increase scenarios.

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Chuan-Yao Lin, Wan-Chin Chen, Pao-Liang Chang, and Yang-Fan Sheng

Abstract

To evaluate the impacts of the urban heat island (UHI) effect on precipitation over a complex geographic environment in northern Taiwan, the next-generation mesoscale model, the Weather Research and Forecasting (WRF) model, coupled with the Noah land surface model and urban canopy model (UCM), was used to study this issue. Based on a better land use classification derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data (the MODIS case), it has significantly improved simulation results for the accumulation rainfall pattern as compared with the original U.S. Geological Survey (USGS) 25-category land use classification (the USGS case). The precipitation system was found to develop later but stronger in the urban (MODIS) case than in the nonurban (USGS) case. In comparison with the observation by radar, simulation results predicted reasonably well; not only was the rainfall system enhanced downwind of the city over the mountainous area, but it also occurred at the upwind plain area in the MODIS case. The simulation results suggested that the correct land use classification is crucial for urban heat island modeling study. The UHI effect plays an important role in perturbing thermal and dynamic processes; it affects the location of thunderstorms and precipitation over the complex geographic environment in northern Taiwan.

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