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Title: Detectable Anthropogenic Shift toward Heavy Precipitation over Eastern China

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [6];  [6];  [9];  [6]
  1. Institute of Climate System, Chinese Academy of Meteorological Sciences, Beijing, China, LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  2. LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China, Joint Center for Global Change Studies, Beijing, China
  3. Lawrence Berkeley National Laboratory, Berkeley, California
  4. School of GeoSciences, Grant Institute, University of Edinburgh, Edinburgh, United Kingdom
  5. Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York
  6. Met Office Hadley Centre, Exeter, United Kingdom
  7. KlimaCampus, University of Hamburg, Hamburg, Germany
  8. Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington
  9. Institute of Climate System, Chinese Academy of Meteorological Sciences, Beijing, China
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1342285
Grant/Contract Number:
SC0012602; Earth System Modeling Program; AC05-76RL01830 (PNNL Contract)
Resource Type:
Journal Article: Published Article
Journal Name:
Journal of Climate
Additional Journal Information:
Journal Volume: 30; Journal Issue: 4; Related Information: CHORUS Timestamp: 2017-04-18 16:11:21; Journal ID: ISSN 0894-8755
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English

Citation Formats

Ma, Shuangmei, Zhou, Tianjun, Stone, Dáithí A., Polson, Debbie, Dai, Aiguo, Stott, Peter A., von Storch, Hans, Qian, Yun, Burke, Claire, Wu, Peili, Zou, Liwei, and Ciavarella, Andrew. Detectable Anthropogenic Shift toward Heavy Precipitation over Eastern China. United States: N. p., 2017. Web. doi:10.1175/JCLI-D-16-0311.1.
Ma, Shuangmei, Zhou, Tianjun, Stone, Dáithí A., Polson, Debbie, Dai, Aiguo, Stott, Peter A., von Storch, Hans, Qian, Yun, Burke, Claire, Wu, Peili, Zou, Liwei, & Ciavarella, Andrew. Detectable Anthropogenic Shift toward Heavy Precipitation over Eastern China. United States. doi:10.1175/JCLI-D-16-0311.1.
Ma, Shuangmei, Zhou, Tianjun, Stone, Dáithí A., Polson, Debbie, Dai, Aiguo, Stott, Peter A., von Storch, Hans, Qian, Yun, Burke, Claire, Wu, Peili, Zou, Liwei, and Ciavarella, Andrew. Wed . "Detectable Anthropogenic Shift toward Heavy Precipitation over Eastern China". United States. doi:10.1175/JCLI-D-16-0311.1.
@article{osti_1342285,
title = {Detectable Anthropogenic Shift toward Heavy Precipitation over Eastern China},
author = {Ma, Shuangmei and Zhou, Tianjun and Stone, Dáithí A. and Polson, Debbie and Dai, Aiguo and Stott, Peter A. and von Storch, Hans and Qian, Yun and Burke, Claire and Wu, Peili and Zou, Liwei and Ciavarella, Andrew},
abstractNote = {},
doi = {10.1175/JCLI-D-16-0311.1},
journal = {Journal of Climate},
number = 4,
volume = 30,
place = {United States},
year = {Wed Feb 01 00:00:00 EST 2017},
month = {Wed Feb 01 00:00:00 EST 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1175/JCLI-D-16-0311.1

Citation Metrics:
Cited by: 4works
Citation information provided by
Web of Science

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  • The increase in winter haze over eastern China in recent decades due to variations in meteorological parameters and anthropogenic emissions was quantified using observed atmospheric visibility from the National Climatic Data Center Global Summary of Day database for 1980–2014 and simulated PM2.5 concentrations for 1985–2005 from the Goddard Earth Observing System (GEOS) chemical transport model (GEOS-Chem). Observed winter haze days averaged over eastern China (105–122.5°E, 20–45°N) increased from 21 d in 1980 to 42 d in 2014, and from 22 to 30 d between 1985 and 2005. The GEOS-Chem model captured the increasing trend of winter PM2.5 concentrations for 1985–2005,more » with concentrations averaged over eastern China increasing from 16.1 μg m -3 in 1985 to 38.4 μg m -3 in 2005. Considering variations in both anthropogenic emissions and meteorological parameters, the model simulated an increase in winter surface-layer PM2.5 concentrations of 10.5 (±6.2) μg m -3 decade -1 over eastern China. The increasing trend was only 1.8 (±1.5) μg m -3 decade -1 when variations in meteorological parameters alone were considered. Among the meteorological parameters, the weakening of winds by -0.09 m s -1 decade -1 over 1985–2005 was found to be the dominant factor leading to the decadal increase in winter aerosol concentrations and haze days over eastern China during recent decades.« less
  • The attribution of the widely observed shifted precipitation extremes to different forcing agents represents a critical issue for understanding of changes in the hydrological cycle. To compare aerosol and greenhouse-gas effects on the historical trends of precipitation intensity, we performed AMIP-style NCAR/DOE CAM5 model simulations from 1950-2005 with and without anthropogenic aerosol forcings. Precipitation rates at every time step in CAM5 are used to construct precipitation probability distribution functions. By contrasting the two sets of experiments, we found that the global warming induced by the accumulating greenhouse gases is responsible for the changes in precipitation intensity at the global scale.more » However, regionally over the Eastern China, the drastic increase in anthropogenic aerosols primarily accounts for the observed light precipitation suppression since the 1950s. Compared with aerosol radiative effects, aerosol microphysical effect has a predominant role in determining the historical trends of precipitation intensity in Eastern China.« less
  • Long-term observational data indicated a decreasing trend for the amount of autumn precipitation (i.e. 54.3 mm per decade) over Mid-Eastern China, especially after 1980s (~ 5.6% per decade). To examine the cause of the decreasing trend, the mechanisms associated with the change of autumn precipitation were investigated from the perspective of water vapor transportation, atmospheric stability and cloud microphysics. Results show that the decrease of convective available potential energy (i.e. 12.81 J kg-1/ decade) and change of cloud microphysics, which were closely related to the increase of aerosol loading during the past twenty years, were the two primary factors responsiblemore » for the decrease of autumn precipitation. Ours results showed that increased aerosol could enhance the atmospheric stability thus weaken the convection. Meanwhile, more aerosols also led to a significant decline of raindrop concentration and to a delay of raindrop formation because of smaller size of cloud droplets. Thus, increased aerosols produced by air pollution could be one of the major reasons for the decrease of autumn precipitation. Furthermore, we found that the aerosol effects on precipitation in autumn was more significant than in other seasons, partly due to the relatively more stable synoptic system in autumn. The impact of large-scale circulation dominated in autumn and the dynamic influence on precipitation was more important than the thermodynamic activity.« less
  • In the midsummer of 2013, Central and Eastern China (CEC) was hit by an extraordinary heat event, with the region experiencing the warmest July-August on record. To explore how human-induced greenhouse gas emissions and natural internal variability contributed to this heat event, we compare observed July-August mean surface air temperature wit h that simulated by climate models. We find that both atmospheric natural variability and anthropogenic factors contributed to this heat event. This extreme warm midsummer was associated with a positive high-pressure anomaly that was closely related to the stochastic behavior of atmospheric circulation. Diagnosis of CMIP5 models and largemore » ensembles of two atmospheric models indicates that human influence has substantially increased the chance of warm mid-summers such as 2013 in CEC, although the exact estimated increase depends on the selection of climate models.« less
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