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William B. Willis, William E. Eichinger, John H. Prueger, Cathleen J. Hapeman, Hong Li, Michael D. Buser, Jerry L. Hatfield, John D. Wanjura, Gregory A. Holt, Alba Torrents, Sean J. Plenner, Warren Clarida, Stephen D. Browne, Peter M. Downey, and Qi Yao

Abstract

Pollutant emissions to the atmosphere commonly derive from nonpoint sources that are extended in space. Such sources may contain area, volume, line, or a combination of emission types. Currently, point measurements, often combined with models, are the primary means by which atmospheric emission rates are estimated from extended sources. Point measurement arrays often lack in spatial and temporal resolution and accuracy. In recent years, lidar has supplemented point measurements in agricultural research by sampling spatial ensembles nearly instantaneously. Here, a methodology using backscatter data from an elastic scanning lidar is presented to estimate emission rates from extended sources. To demonstrate the approach, a known amount of particulate matter was released upwind of a vegetative environmental buffer, a barrier designed to intercept emissions from animal production facilities. The emission rate was estimated downwind of the buffer, and the buffer capture efficiency (percentage of particles captured) was calculated. Efficiencies ranged from 21% to 74% and agree with the ranges previously published. A comprehensive uncertainty analysis of the lidar methodology was performed, revealing an uncertainty of 20% in the emission rate estimate; suggestions for significantly reducing this uncertainty in future studies are made. The methodology introduced here is demonstrated by estimating the efficiency of a vegetative buffer, but it can also be applied to any extended emission source for which point samples are inadequate, such as roads, animal feedlots, and cotton gin operations. It can also be applied to any pollutant for which a lidar system is configured, such as particulate matter, carbon dioxide, and ammonia.

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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

Abstract

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.

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Gavin A. Schmidt, Reto Ruedy, James E. Hansen, Igor Aleinov, Nadine Bell, Mike Bauer, Susanne Bauer, Brian Cairns, Vittorio Canuto, Ye Cheng, Anthony Del Genio, Greg Faluvegi, Andrew D. Friend, Tim M. Hall, Yongyun Hu, Max Kelley, Nancy Y. Kiang, Dorothy Koch, Andy A. Lacis, Jean Lerner, Ken K. Lo, Ron L. Miller, Larissa Nazarenko, Valdar Oinas, Jan Perlwitz, Judith Perlwitz, David Rind, Anastasia Romanou, Gary L. Russell, Makiko Sato, Drew T. Shindell, Peter H. Stone, Shan Sun, Nick Tausnev, Duane Thresher, and Mao-Sung Yao

Abstract

A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

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Ibrahim Hoteit, Yasser Abualnaja, Shehzad Afzal, Boujemaa Ait-El-Fquih, Triantaphyllos Akylas, Charls Antony, Clint Dawson, Khaled Asfahani, Robert J. Brewin, Luigi Cavaleri, Ivana Cerovecki, Bruce Cornuelle, Srinivas Desamsetti, Raju Attada, Hari Dasari, Jose Sanchez-Garrido, Lily Genevier, Mohamad El Gharamti, John A. Gittings, Elamurugu Gokul, Ganesh Gopalakrishnan, Daquan Guo, Bilel Hadri, Markus Hadwiger, Mohammed Abed Hammoud, Myrl Hendershott, Mohamad Hittawe, Ashok Karumuri, Omar Knio, Armin Köhl, Samuel Kortas, George Krokos, Ravi Kunchala, Leila Issa, Issam Lakkis, Sabique Langodan, Pierre Lermusiaux, Thang Luong, Jingyi Ma, Olivier Le Maitre, Matthew Mazloff, Samah El Mohtar, Vassilis P. Papadopoulos, Trevor Platt, Larry Pratt, Naila Raboudi, Marie-Fanny Racault, Dionysios E. Raitsos, Shanas Razak, Sivareddy Sanikommu, Shubha Sathyendranath, Sarantis Sofianos, Aneesh Subramanian, Rui Sun, Edriss Titi, Habib Toye, George Triantafyllou, Kostas Tsiaras, Panagiotis Vasou, Yesubabu Viswanadhapalli, Yixin Wang, Fengchao Yao, Peng Zhan, and George Zodiatis

Abstract

The Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.

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