Yongqiang Liu

Team Leader/Research Meteorologist
Atmospheric Science Team
Center for Forest Disturbance Science
USDA Forest Service
SRS Staff Directory Profile

Language Skills

Fluent in spoken and written Mandarin Chinese.

SRS Publications List


My research is focused on climate-forest ecosystem interactions. It is aimed at understanding forest disturbances (wildfire, land cover change, and forest water stress), their interactions with climate variability and climate change, and the environmental consequences. The combined approach of field measurements, numerical modeling, and theoretical and statistical analyses is used to investigate the processes, mechanisms, and impacts of the disturbances and to develop evaluation and prediction techniques. This research is expected to help strategy development and implementation to reduce forest vulnerability to forest disturbances and their adverse environmental impacts.

Regional air quality impact of prescribed burning

Prescribed burning is an important forest management technique to temporarily reduces damage from wildfire by removing a portion of the accumulating dead fuels (such as duff and logs on the forest floor) and reduce the stature of the developing understory, and serves as a surrogate for the historical fires by recycling nutrients and restoring/sustaining ecosystem health. Prescribed burning has been extensively used in the South to reduce wildfire risk by removing the accumulating dead fuels. Approximately six million acres of forest and agricultural lands are burned annually, the most among the various Forest Service regions.

Prescribed burning, however, emits large amounts of PM2.5 (particulate matter with diameter less than 2.5 micrometers) and O3 precursors that lead to regional haze, smog, and visibility impairment. The U.S. Environmental Protection Agency (EPA) has established the National Ambient Air Quality Standards (NAAQS) for PM2.5 and O3. The standards are getting tougher, imposing a big threat to normal operation of prescribed burning. Providing tools for evaluating the regional air quality impacts of prescribed burning will assist field managers and policy-makers in developing burn strategies and plans to retain or increase use of prescribed burning while meeting air quality regulations.

This study develops and applies modeling tools to simulate and predict transport and dispersion and the air quality effects of smoke emitted from prescribed burns and wildfires. The objectives of this study are: (1) Developing regional air quality modeling tools for prescribed burning. (2) Developing supporting datasets and fire detection algorithms. (3) Assessing the regional air quality impacts of prescribed burning in the South.

A primary task of this study is to build a regional smoke and air quality modeling framework, i.e., Southern High-Resolution Modeling Consortium Southern Smoke Simulation System (SHRMC-4S) to evaluate the air quality effects of smoke. SHRMC-4S will be developed by integrating the components of fire data collection, emission calculation, meteorological modeling, and air quality modeling. The challenges for this study include specification of smoke plume height in air quality modeling, and lack in prescribed burn information in many southern states. Solutions will be sought by coupling smoke models for plume height calculation and by developing algorithms to detect prescribed burns using advanced techniques such as satellite remote sensing. The expected products from this study include a regional smoke air quality framework and applications to assessment of regional air quality impacts of prescribed burning.

Smoke dynamics

Smoke is one of the products from prescribed burning, which leads to direct local impacts on health of field operating personnel, visibility, air quality, and road safety. In addition, smoke can be transported to remote areas and therefore impact regional air quality. Understanding of smoke dynamics is essential for developing modeling tools for assessing smoke impacts. Smoke plume rise, for example, is an important parameter used in regional air quality models to determine how much smoke pollutants are transported out of the burning site.

This study is to obtain fundamental facts about smoke processes and modeling uncertainty by conducting field measurements.The research objectives include: (1) Understanding temporal and spatial variability of smoke plume properties (especially plume rise) from prescribed burns. (2) Understanding the associated dispersion, transport, and deposition processes. (3) Developing modeling tools for smoke plume rise and other properties

Smoke processes depend on fuel condition, fire behavior, and atmospheric condition. Atmospheric turbulence nature is one of the special challenges for smoke dynamics study. The lack in measurements has been a major obstacle. This study will be made first by conducting field measurement of smoke plume from prescribed burning in the South. The important processes and factors for smoke plume rise and other properties will be identified using sensitivity analysis techniques. The modeling tools are developed based on the field measurement and evaluation of existing smoke models.

Impacts of climate change / variability on wildfire

Wildfire is a natural disaster threatening human life and property. Prediction of fire activities provides land managers with the necessary information for planning fire suppression and other fire-related activities. Southern forests are dynamic ecosystems characterized by rapid growth and hence rapid deposition of fuels within a favorable climate, and a high fire-return rate. Significant climate change has been projected for this century due to the greenhouse effect, with more frequent droughts in many subtropical and mid-latitude regions including the southern US. Thus, it is likely that wildfire potential would increase in these regions. Understanding wildfire disturbance and developing models for wildfire potential prediction is essential for reducing wildfire threat to southern forests, assessing wildfire’s potential impacts in the future and developing mitigation strategies.

The objectives of this study are: (1) Understand the impacts of climate change / variability on wildfire and the environmental consequences. (2) Projecting wildfire potential and risks. (3) Developing management options for adapting and mitigating climatic impacts. This study is expected to provide spatial patterns and temporal variations of wildfire and emissions in the South and the U.S., prediction models of fire season activities, projection of future wildfire potential and risk trends under changing climate, and assessment of future prescribed burning need for mitigating the impacts of climate change on wildfire.

The research will be conducted by analyzing variability of wildfire and emissions, statistical and spatial correlations with atmospheric conditions, simulating and projecting fire potential using drought indices and fuel conditions, and analyzing future needs in prescribed burning as a management option. Climate extremes such as drought are necessary but not sufficient conditions. Thus, there are no definite relationships between climate conditions and widfire. Furthermore, wildfire intensity and emissions are determined not only by atmospheric but also fuel conditions, while fuel condition will change as well under changing climate. In addition, some meteorological variables required for projecting regional fire indices are not provided by popularly used statistical downscaling of regional climate change scenarios. Solutions to these challenges will be sought by developing new approaches to connect fire and dry conditions, projecting future fuel load change, and applying dynamical downscaling of regional climate change scenarios.

Feedback of wildfire on climate

Climate and wildfire are two natural processes with significant seasonal and inter-annual variability. The importance of climate to wildfire has long been recognized, while the possible contributions of wildfire to regional climate anomalies have yet to be understood. Wildfire can impact climate by emitting large amounts of smoke aerosols, which can change atmospheric radiation by scattering and absorbing solar radiation. Radiative forcing of smoke aerosols can further modify atmospheric circulations and precipitation, which may contribute to climate anomalies such as drought.

This study is to understand the roles of wildfires in cliamte variability and climate change. The research objectives include: (1) Simulating radiative forcing of smoke aerosols. (2) Simulating the impacts of smoke aerosols on atmospheric circulation and precipitation. (3) Understanding the contributions and mechanisms of wildfire to the regional climate anomalies which provide favorite conditions for wildfire.

The climatic impact of wildfire smoke aerosols involves complex aerosol-radiation-cloud interactions. This study will investigate this issue by combining knowledge and expertise in both wildfire and climate sciences. This study will provide a picture of the features and estimate the magnitude of changes in atmospheric radiation, circulation, clouds and precipitation during major wildfire events in the U.S. and other geographic regions.

Regional climate and ecosystem modeling

Land cover changes constantly at various time and space scales due to both natural (e.g., climate, wildfire, and disease) and anthropogenic (e.g., conversion and removal of forest for agriculture, industry, and urban development, afforestation, and restoration) disturbances. The tropical rainforests have reduced dramatically in the past due to agricultural and other human activities. Forest lands were also reduced in the southern U.S. mainly due to urbanization. Afforestation, on the other hand, increased forest coverage. This happened, for example, during the agriculture to forest land conversion in the early 20th century in the southern U.S. and the forest shelterbelt project in northern China initiated in the late 1970s. Changes in land cover can affect regional climate by changing the surface albedo, roughness, and the balance between sensible and latent heat loss.

Furthermore, future forest ecosystems are expected to change dramatically in response to climate change due to the greenhouse effect. Forests play an important role in mitigating the greenhouse effect by taking up atmospheric CO2. Forests cal also play a mitigation role through land-surface processes. Forests can moderate local and regional climate through modifying water and heat exchanges on the land surface. Afforestation often leads to reduced temperature and increased rainfall and therefore partially offsets some impacts of greenhouse effect.

This study is to understand the forest ecosystem and climate interactions involved in land cover change. The research objectives of this study are (1) Understanding the climatic and hydrologic impacts of afforestation. (2) Analyzing the associated physical processes and mechanisms in the soil-vegetation-atmosphere (SVA) system. (3) Understanding the implications for mitigating climate change’s impact.

Regional climate and ecossytem modeling tools will be used to simulate responses of regional climate and hydrology to afforestation. The SVA system includes multiple interactions and feedbacks, making it difficult to assess afforestation’s impact. For example, increase in forest coverage would increase temperature because of reduced reflection of solar radiation, but would decrease temperature because of increased latent heat consumption with evapotranspiration. Solutions are sought by using sophisticated regional climate models and evaluating the results with observations. Another complexity is that afforestation is a dynamic process and the atmospheric conditions change during the growth of trees. A coupled system of climate model and dynamic vegetation model will be used to solve this problem.


Evaluation and improvement of smoke plume rise models

Smoke plume rise, also called plume height, is the height where the smoke particles can reach after they are ejected from wildland fires. It ranges from tens of meters for prescribed fires to thousands of meters for wildfires. Plume height is an important factor for local and regional air quality modeling. Fire emissions, if injected into higher elevations, are likely to be transported out of the rural burn site by prevailing winds and therefore possibly affect air quality nearby and remote populated urban areas in downwind direction. Plume rise is a parameter required by many regional air quality models.

Efforts have been made recently that led to the developments of a number of smoke plume models with various levels of complexity. Smoke plume height model evaluation, however, has been a big challenge because of the lack in smoke measurements. This makes it difficult to understand the performance and uncertainties of smoke models. Fire and smoke model validation is one of the fundamental research issues in the Smoke Science Plan, prepared for the U.S. Joint Fire Science Program (JFSP).

The study, funded by JFSP, is to evaluate and improve the performance of Daysmoke, a plume rise model, and to understand the significance for smoke and air quality modeling of prescribed burning. A combined approach of field measurement, numerical modeling, and dynamical and statistical analysis is used to obtain data, conduct simulation and evaluation, and improve the model. The research products include datasets of smoke measurements, case and statistical evaluation results of Daysmoke and other plume rise models, and GIS supported Daysmoke. These products are expected to provide fire and air quality managers and modelers with quantitative information and tools for understanding the accuracy, limits, and uncertainty in plume rise calculation of prescribed burning, and their impacts on simulation and prediction of smoke transport and air quality effects.

For details, see http://shrmc.ggy.uga.edu/smoke_plume.php

Impacts of Mega-fires on Large U.S. Urban Area Air Quality under Changing Climate and Fuels

Mega-fires have extraordinary properties in size, duration, and fire behavior and often lead to dramatic damage to ecosystems, properties, and human life. The Yellowstone wildfires of 1988, for example, lasted for several months with about 800,000 acres burned, and thousands of firefighters involved in the fire fighting. Mega-fires also release large amounts of particulate matter (PM) and ozone precursors, leading to air quality degradation and other environmental consequences.

General circulation models (GCMs) have projected significant climate change for this century due to the greenhouse effect, including overall warming worldwide and more frequent droughts in many subtropical and mid-latitude regions including the U.S. It is likely that mega-fires will increase in these regions. One consequence of the mega-fire trend is more severe air quality impacts from smoke in populated U.S. metro regions. Efforts have been made to project future trends in wildfires and the smoke impacts under a changing climate. Evidence for a significant increase in U.S. fire activities in the future has been provided. For example, it is projected that annual mean area burned in the western U.S. may increase about 50% by the 2050s relative to the present day and that wildfire potential and burned area in the U.S. will increase significantly in the western Mountains.

This study, funded by the Joint Fire Science Program (JFSP), is to identify present and project future mega-fires and evaluate their air quality impacts. The research objectives include: (1) To build mega-fire probability functions and atmospheric pattern thresholds for mega-fire breakout. The probability distribution is formed with respect to dry conditions measured by fire indices, which will be calculated using multiple sets of dynamical downscaling climate. (2) To project areas and seasons of future mega-fires. The fire probability together with the atmospheric patterns will be major tools for future mega-fire projection. (3) To obtain present fuel loading and project future trends. Present fuel conditions are obtained from the FCCS with their seasonal variation specifications based on simulated carbon pools. Future carbon pools and fuel loading are projected under the dynamically downscaled climate change scenarios. (4) To simulate smoke transport from present and future mega-fires. Emissions are calculated based on the burned areas of mega-fires, fuel loading, and other factors. Smoke trajectories are obtained with a smoke transport model to be run under a fire, smoke, and air quality framework. (5) To evaluate the smoke impacts on air quality. Ground PM2.5 and ozone concentrations are analyzed to identify major large U.S. urban areas where air quality and human health are most likely threatened by future mega-fires.

Climate Change Adaptation and Mitigation Management Options (CCAMMO)

CCAMMO is an SRS cross station climate change project. The goal of this project is to provide land management options that buffer the effects of future climatic conditions on a variety of ecosystem services to land managers, who are faced with the challenge of how to manage today’s forests to adapt to and mitigate the impacts of future climate change. The CCAMMO project analyzes relationships among management practices, assesses risks and values of the southern forest ecosystem under changing climate, and develops various management options for mitigation and adaptation. The research and synthesis results will be presented in a book.

Several teams work on vulnerability, wildfire, invasive, biomass, water, species, and recreation. The wildfire team consists of 15 SRS researchers and FS Region 8 and State managers. The objectives of related research with fire team include: (1) projecting wildfire risk under changing climate in the South, (2) understanding interactions with other ecosystem processes, and (3) providing management options to mitigate the impacts of potentially increased wildfire activity.

Wildland Fire Greenhouse Gas/Black Carbon (GHG/BC) Synthesis Project

An FS R&D Core Team initiated an effort in summer of 2010 to review what is known about GHG/BC emissions from wildland fires across all biomes in the United States. This project was tasked by the Research Deputy Director/Assistant Director Group to produce a synthesis report focusing on synthesizing published information on GHG/BC emissions from wildland fires. It will answer questions concerning the extent, magnitude, and potential climate-driven acceleration of global fire emissions that are receiving heightened attention. Since many of our future fire management options in the United States will be impacted by answers to these questions, we need to synthesize the most current scientific information concerning fire emissions and identify future research needs.


Peer-Reviewed Journal Publications

  • Heilman, Warren E.; Liu, Yongqiang; Urbanski, Shawn; Kovalev, Vladimir; Mickler, Robert. 2014. Wildland fire emissions, carbon, and climate: Plume rise, atmospheric transport, and chemistry processes. Forest Ecology and Management, 317: 70-79.
  • Liu, Yongqiang; Goodrick, Scott; Heilman, Warren. 2014. Wildland fire emissions, carbon, and climate: Wilfire--climate interactions. Forest Ecology and Management, 317: 80-96.
  • Liu, Yonggiang; Prestemon, Jeffrey P.; Goodrick, Scott L.; Homes, Thomas P.; Stanturf, John A.; Vose, James M.; Sun, Ge. 2014. Future wildfire trends, impacts, and mitigation options in the southern United States. In: Vose, James M.; Klepzig, Kier D., eds. Climate change adaptation and mitigation management options: A guide for natural resource managers in southern forest ecosystems. Boca Raton, FL: CRC Press. 85-126.
  • Marion, Daniel A.; Sun, Ge; Caldwell, Peter V.; Miniat, Chelcy F.; Ouyang, Ying; Amatya, Devendra M.; Clinton, Barton D.; Conrads, Paul A.; Gull Laird, Shelby; Dai, Zhaohua; Clingenpeel, J. Alan; Liu, Yonqiang; Roehl, Edwin A. Jr.; Moore Myers, Jennifer A.; Trettin, Carl. 2014. Managing forest water quantity and quality under climate change. In: Vose, James M.; Klepzig, Kier D., eds. Climate change adaptation and mitigation management options: A guide for natural resource managers in southern forest ecosystems. Boca Raton, FL: CRC Press. 249-305.
  • Mitchell, Robert J.; Liu, Yongqiang; O’Brien, Joseph J.; Elliott, Katherine J.; Starr, Gregory; Miniat, Chelcy Ford; Hiers, J. Kevin. (In Press). Future climate and fire interactions in the southeastern region of the United States. Forest Ecology and Management.
  • Goodrick, Scott L.; Achtemeier, Gary L.; Larkin, Narasimhan K.; Liu, Yongqiang; Strand, Tara M. 2013. Modelling smoke transport from wildland fires: a review. International Journal of Wildland Fire, 22(1): 83-94.
  • Liu, Yongqiang; Goodrick, Scott L.; Achtemeier, Gary L.; Forbus, Ken; Combs, David. 2013. Smoke plume height measurement of prescribed burns in the south-eastern United States, International Journal of Wildland Fire, 22(2): 130-147.
  • McNulty, Steven; Caldwell, Peter; Doyle, Thomas W.; Johnsen, Kurt; Liu, Yongqiang; Mohan, Jacqueline; Prestemon, Jeffrey; Sun, Ge. 2013. Forests and Climate Change in the Southeast USA. In: Ingram, K.; Dow, K.; Carter, L.; Anderson, J., eds. 2013. Climate of the Southeast United States: Variability, change, impacts, and vulnerability. Washington, DC: Island Press. 165-189.
  • McNulty, Steven; Sun, Ge; Mohan, Jacqueline; Prestemon, Jeffrey; Johnsen, Kurt; Liu, Yongqiang. 2013. Forests and Climate Change in the Southeast. NCA Southeast Technical Report 161-183.
  • Sun, Ge; Liu, Yongqiang. 2013. Forest Influences on Climate and Water Resources at the Landscape to Regional Scale. In: Fu, B.; Bruce, K. J., eds. Landscape Ecology for Sustainable Environment and Culture. Springer. 309-334.
  • Achtemeier, Gary L.; Goodrick, Scott A.; Liu, Yongqiang. 2012. Modeling multiple-core updraft plume rise for an aerial ignition prescribed burn by coupling daysmoke with a cellular automata fire model. Atmosphere, 3(3): 352-376.
  • Chen, Guang-Shan; Notaro, Michael; Liu, Zhengyu; Liu, Yongqiang. 2012. Simulated local and remote biophysical effects of afforestation over Southeast United States in boreal summer. Journal of Climate, 25(13): 4511-4522.
  • Achtemeier, Gary L.; Goodrick, Scott A.; Liu, Yongqiang; Garcia-Menendez, Fernando; Hu, Yongtao; Odman, Mehmet Talat. 2011. Modeling smoke plume-rise and dispersion from southern United States prescribed burns with Daysmoke. Atmosphere, 2(3): 358-388.
  • Liu, Yongqiang. 2011. Hydrological Impacts of forest restoration in the southern United States. Ecohydrology 4: 299–314.
  • Liu, Y.-Q., J. Stanturf, S. Goodrick, 2010, Wildfire potential evaluation during a drought event with a regional climate model and NDVI, Ecological Informatics. doi:10.1016/j.ecoinf.2010.04.001.
  • Liu, Y.-Q., G. Achtemeier, S. Goodrick, W.A. Jackson, 2010, Important parameters for smoke plume rise simulation with Daysmoke, Atmospheric Pollution Research. 1 , 250-259.
  • Zhang, C., Tian, H.Q., Wang, Y.H., Zeng, T. and Liu, Y.Q., 2010, Predicting response of fuel load to future changes in climate and atmospheric composition in the southeastern United States. doi:10.1016/j.foreco.2010.05.012.
  • Liu, Y.-Q., J. Stanturf, S. Goodrick, 2009, Trends in global wildfire potential in a changing climate, Forest Ecology and Management, 259, 378-1127, DOI:10.1016/j.foreco.2009.09.002.
  • Liu, Y.-Q., S. Goodrick, G. Achtemeier, W.A. Jackson, J. J. Qu and W. Wang, 2009, Smoke incursions into urban areas: simulation of a Georgia prescribed burn, International Journal of Wildland Fire, 18, 336–348. DOI:10.1071/WF08082.
  • Wang W., Qu, J.J., Hao, X., Liu, Y.-Q., 2009. Analysis of the moderate resolution imaging spectroradiometer contextual algorithm for small fire detection, Journal of Applied Remote Sensing, 3. DOI: 10.1117/1.3078426.
  • Wang W., Qu, J.J., Hao, X., Liu, Y.-Q., Stanturf, J., 2009. Post-hurricane forest damage assessment using satellite remote sensing, Agric. Forest Meteorol. doi:10.1016/j.agrformet.2009.09.009.
  • Liu, Y-Q., G. Achtemeier and S. Goodrick, 2008, Sensitivity of air quality simu­lation to smoke plume rise. Journal of Applied Remote Sensing Vol. 2, 021503 (20 May 2008) DOI: 10.1117/1.2938723.
  • Di Tian, Yuhang Wang, Michelle Bergin, Yongtao Hu, Yongqiang Liu and Ar­mistead G. Russell. 2008. Air quality impacts from prescribed forest fires under different management practices. Environmental Science and Technology 42: 2767 – 2772.
  • Liu, Y.-Q., J. Stanturf and H.-Q. Lu, 2008, Modeling the potential of the northern China forest shelterbelt in improving hydroclimate conditions, J. Amer. Water Res. Asso., 44 (5): 1-17. DOI: 10.1111/j.1752-1688.2008.20240.x
  • Wang, Wanting; Qu, John J.; Hao, Xianjun; Liu, Yongqiang; Sommers, William T. 2007. An improved algorithm for small and cool fire detection using MODIS data: a preliminary study in the southeastern United States. Remote Sensing of Environment 108 (2): 163-170.
  • Liu, Y.-Q. 2006, Northwest Pacific warming and intense Northwestern U.S. wildfire, Geophys. Res. Let. 33(21), L21710, 10.1029/GL027442.
  • Wu, W., R. Dickinson, H. Wang, Y.-Q. Liu, and H. Shaikh, 2006, Summer rainfall variability over the United States and its association with spring soil moisture in a climate simulation. International Journal of Climatology DOI: 10.1002/joc.1419.
  • Liu, Y.-Q. 2005, Atmospheric response and feedback to radiative forcing frombiomass burning in tropical South America, Agri. Forest. Meteoro., 133, 40-57.
  • Liu, Y. –Q., 2005, Enhancement of the 1988 Northern U.S. drought due to wildfires, Geophy. Res. Let., 32 (No. 10), L1080610.1029/2005GL022411.
  • Liu, Y.-Q., R. Fu and R. Dickinson, 2005, Smoke aerosols altering South American monsoon, Bull. Amer. Meteor. Soc., 86(8), 1062-1063.
  • Liu, Y.-Q., 2005, Land Breeze and Thermals: A Scale Threshold to distinguish their effects, Advance in Atmos. Sci., 22 (6).
  • Lu, A., H. Tian, and Y. Liu (2005), State-of-the-art in quantifying fire disturbance and ecosystem carbon cycle (in Chinese), Acta Ecol. Sinica, 25, 2734–2743.
  • Qu, J.X. Hao, R. Yang, W. Sommers, S. Dasgupta, S. Bhoi, M. Kafatos, Y.-Q. Liu, G. Achtemeier, A. R. Riebau, and P. Coronado, 2005, Bridging Earth observations: remote sensing measurements, fire modeling, and air quality decision support system in the eastern United States, Earth Observation Magazine, 14 (6).
  • Liu, Y.-Q., and R. Avissar, 2005, Modeling of the global water cycle - analytical models, in “Encyclopedia of Hydrological Sciences (Ed. M.G. Anderson)”, John Wiley & Sons. 2781-2794.
  • Liu, Y. –Q. 2004, Variability of wildland fire emissions across the continuous United States, Atmos. Environ., 38, 3489-3499.
  • Liu Y.-Q., 2004, Monthly-seasonal variability of the land-atmospheric system, World Scientific Series on Meteor. of East Asia, 3, 73-91.
  • Liu, Y.-Q.,2003, Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region, J. Geophy. Res., 108 (D22), 8856, doi:10.1029/2002JD003124.
  • Liu, Y.-Q., 2003, Prediction of monthly-seasonal precipitation using coupled SVD patterns between soil moisture and subsequent precipitation, J. Geophys. Lett., 30 (15), 1827, doi:10.1029/2003GL017709.
  • Liu, Y.-Q., and R.Avissar, 1999, A study of persistence in the land-atmosphere system with a general circulation model and observations, J. Clim., 12, 2139-2153.
  • Liu, Y.-Q., and R.Avissar, 1999, A study of persistence in the land-atmosphere system with a fourth-order analytical model, J. Clim., 12, 2154-2168.
  • Liu, Y.-Q., C.P. Weaver and R. Avissar, 1999, A parameterizationof shallow convection induced by landscape heterogeneity for use in GCM, J. Geophy. Res., 104 (D16), 19515-19534.
  • Liu,Y.-Q. and R. Avissar, 1996, Sensitivity of a shallow convective precipitationinduced by land-surface heterogeneity to dynamical and cloudmicrophysical parameters. J. Geophy. Res., 101 (D3), 7477-7497.
  • Avissar, R. andY.-Q. Liu, 1996, A three-dimensional numerical study of shallow convective clouds and precipitation induced by land-surface forcing. J. Geophy. Res.,101 (D3), 7499-7518.
  • Liu,Y.-Q., R. Avissar, and F. Giorgi, 1996, A simulation with the regional climate model (RegCM2) of extremely anomalous precipitation during the 1991 East-Asia flood: An evaluation study. J. Geophy. Res.101(D21), 26199-26215.
  • Liu,Y.-Q. andY.H. Ding, 1995, Reappraisal of the influences of ENSO events on seasonal precipitation and temperature in China.Scientia Atmospheria Sinica,19, 200-208 (in Chinese).
  • Liu,Y.-Q. and Y.H. Ding, 1995, A review of the study on simulation of regional climate, Chinese Q. J. Appl. Met.,6, 228-239 (in Chinese).
  • Liu,Y.-Q., F. Giorgi, and W. Washington, 1994, Simulation of summer monsoon climate over East Asia with an NCAR regional climate model, Mon. Wea. Rev.,102, 2331-2348.
  • Li, Y. H. andY.-Q. Liu, 1993, An analysis on the causes of the typical drought/flood over the valleys of the Yellow and the Changjiang Rivers during the last decades,Meteor. Mon,19(5), 9-15 (in Chinese).
  • Liu,Y.-Q., D.Z. Ye and J.J. Ji, 1993, Influence of soil moisture and vegetation on climate (II): numerical experiments on persistence of short-term climate anomalies,Sciences in China (series B), No.1., 102-109.
  • Liu,Y.-Q., D.Z. Ye and J.J. Ji, 1992a, Influence of soil moisture and vegetation on climate (I):theoreticalanalysistopersistenceof short-term climate anomalies.Sciences in China (series B), No.4, 441-448.
  • Liu,Y.-Q., D.Z. Ye and J.J. Ji, 1992b, Influence of soil moisture andvegetation on climate change induced by thermal forcing.Acta Meteor. Sinica,6 (1),58-69 (in Chinese).
  • Liu,Y.-Q. and Y.H. Ding, 1992, Influence of El Nino events on weather and climate in China.Acta Meteor. Sinica,6 (1), 117-131.
  • Liu,Y.-Q., Y.H. Ding and Y.H. Li, 1992,Water vapor transfer over Yellow River valley during the drought period in summer of 1980.Advances in Atmos. Sci.,9(2), 213-222.
  • Ji, J. J. andY.-Q. Liu, 1992, Modeling of land surface process and its climate effects,Bull. of CNC-IGBP, China Meteor. Press, 2(1), 33-54.
  • Li, Y.H.,Y.-Q. Liu and Y.H. Ding, 1992, Diagnostic analysis ofdistributionof apparent heat source and sink in mid-lower reaches ofYellow River during the drought period of 1980. Chinese Q. J. Appl. Met.(Supple).3.93-99 (in Chinese).
  • Liu,Y.-Q., 1990, Effect of mean horizontal temperature gradient over mountainon terrain-induced atmospheric disturbance. Additional Issue of Scientia Atmospheria Sinica (1990), 178-185 (in Chinese).
  • Liu,Y.-Q. and R.Z. Zhu, 1988, Model study on wind energy over a hilly area. Acta Meteor. Sinica,46(1), 67-74 (in Chinese).
  • Liu,Y.-Q., 1988, Statistics of the atmospheric humidity in the monsoon area in China.Meteor. Mon.,14 (11), 13-16 (in Chinese).
  • Liu,Y.-Q., 1985,A view of drought simulation in China from therelevant study in Sahel.J. Beijing Ins. of Met., China Met. Press, 140-146 (in Chinese).
  • Liu,Y.-Q., 1983, Case analysis of conditions for formation and enhancement of mesoscale rainstorm.Hubai Meteor., No.2, 5-8 (in Chinese).

Other Peer-Reviewed Publications

  • Liu, Y. –Q., J. Qu,W. Wang, and X. Hao, 2011, Estimates of wildland fire emissions, Springer-Verlag EastFire Conference Book (in press)
  • Achtemeier, G., S. Goodrick and Y-Q. Liu, 2011: A coupled modeling system for connecting prescribed fire activity data through CMAQ for simulating regional scale air quality. Springer-Verlag EastFire Conference Book (in press).
  • Liu, Y. –Q., J. Qu,W. Wang, and X. Hao, 2009, Estimates of wildland fire emissions, Springer-Verlag EastFire Conference Book (in press).
  • Qu, J.J., X. Hao, Y.-Q. Liu, A.R. Riebau, H.Yi, X. Qin, 2008. Remote sensing applications of wildland fire and air quality in China. In Bytnerowicz, Andrzej, Arbaugh, Michael J., Riebau Allen R., Andersen, Christian (Editors), Wild Land Fires and Air Pollution, Vol. 8, Developments in Environmental Science, pp. 277–288. The Netherlands: Elsevier.
  • Liu, Y.-Q., 2003, Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region, JGR GCIP/GAPP Special Volume, 22-1~14.
  • Liu,Y.-Q., Y.H. Ding, and Z.C. Zhao, 1996, Regional climate modeling on the extreme anomalous rainfall over the Yangtze-Huaihe River Valley in 1991. In “The Model Study on Prediction of the Short-Term ClimaticVariations in China'' (Ed. Zhao, Z.C.), China Meteorological Press, 106-120 (in Chinese).
  • Liu,Y.-Q., R. Avissar, and F. Giorgi, 1995, A simulation with the regional climate model (RegCM2) of extremely anomalous precipitation during the 1991 East-Asia flood: An evaluation study. In “Collection of Papers of Fifth International Conference on Precipitation”, June 14-16, Elounda, Crete, Greece.
  • Liu,Y.-Q., 1992, Land condition and short-term climate changes. In "Proceedings of the China Association of Science and Technology First Academic Annual Meeting of Youths", 451-456, China Science and Technology Press.
  • Liu,Y.-Q., D.Z. Ye and J.J. Ji, 1990, Land condition and greenhouse effect. In “Proceedings of the National Conference on Climate and Environment” (Ed. China Association of Sci. and Tech.) (in Chinese).
  • Zhu, R.Z. andY.-Q. Liu , 1989,Forecast and variation characteristic of wind over mountain area.in"Recent Advances in Wind Engineering", International Academic Publishers, 163-170.
  • Jia, P.Q, L.G.Bian andY.-Q. Liu, 1989, Wind energy potential at the China Great Wall Meteorological Station in Antarctic. in"Paper Collection of Antarctic Meteorology", China Oceanic Press, 158-163 (in Chinese).


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Center for Forest Disturbance Science (SRS RWU 4156)

University of Georgia
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