Search Results

You are looking at 1 - 3 of 3 items for

  • Author or Editor: Yao-Sheng Chen x
  • All content x
Clear All Modify Search
Chuan-Yao Lin, Wan-Chin Chen, Pao-Liang Chang, and Yang-Fan Sheng


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.

Full access
Robert S. Schrom, Marcus van Lier-Walqui, Matthew R. Kumjian, Jerry Y. Harrington, Anders A. Jensen, and Yao-Sheng Chen


The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

Restricted access
Tandong Yao, Yongkang Xue, Deliang Chen, Fahu Chen, Lonnie Thompson, Peng Cui, Toshio Koike, William K.-M. Lau, Dennis Lettenmaier, Volker Mosbrugger, Renhe Zhang, Baiqing Xu, Jeff Dozier, Thomas Gillespie, Yu Gu, Shichang Kang, Shilong Piao, Shiori Sugimoto, Kenichi Ueno, Lei Wang, Weicai Wang, Fan Zhang, Yongwei Sheng, Weidong Guo, Ailikun, Xiaoxin Yang, Yaoming Ma, Samuel S. P. Shen, Zhongbo Su, Fei Chen, Shunlin Liang, Yimin Liu, Vijay P. Singh, Kun Yang, Daqing Yang, Xinquan Zhao, Yun Qian, Yu Zhang, and Qian Li


The Third Pole (TP) is experiencing rapid warming and is currently in its warmest period in the past 2,000 years. This paper reviews the latest development in multidisciplinary TP research associated with this warming. The rapid warming facilitates intense and broad glacier melt over most of the TP, although some glaciers in the northwest are advancing. By heating the atmosphere and reducing snow/ice albedo, aerosols also contribute to the glaciers melting. Glacier melt is accompanied by lake expansion and intensification of the water cycle over the TP. Precipitation has increased over the eastern and northwestern TP. Meanwhile, the TP is greening and most regions are experiencing advancing phenological trends, although over the southwest there is a spring phenological delay mainly in response to the recent decline in spring precipitation. Atmospheric and terrestrial thermal and dynamical processes over the TP affect the Asian monsoon at different scales. Recent evidence indicates substantial roles that mesoscale convective systems play in the TP’s precipitation as well as an association between soil moisture anomalies in the TP and the Indian monsoon. Moreover, an increase in geohazard events has been associated with recent environmental changes, some of which have had catastrophic consequences caused by glacial lake outbursts and landslides. Active debris flows are growing in both frequency of occurrences and spatial scale. Meanwhile, new types of disasters, such as the twin ice avalanches in Ali in 2016, are now appearing in the region. Adaptation and mitigation measures should be taken to help societies’ preparation for future environmental challenges. Some key issues for future TP studies are also discussed.

Open access