Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.5194/acp-17-3253-2017 |
Sensitivity of the interannual variability of mineral aerosol simulations to meteorological forcing dataset | |
Smith, Molly B.1,2; Mahowald, Natalie M.1; Albani, Samuel1,3; Perry, Aaron1; Losno, Remi4; Qu, Zihan4,5; Marticorena, Beatrice5; Ridley, David A.6; Heald, Colette L.6 | |
2017-03-07 | |
发表期刊 | ATMOSPHERIC CHEMISTRY AND PHYSICS
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ISSN | 1680-7316 |
EISSN | 1680-7324 |
出版年 | 2017 |
卷号 | 17期号:5 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; France |
英文摘要 | Interannual variability in desert dust is widely observed and simulated, yet the sensitivity of these desert dust simulations to a particular meteorological dataset, as well as a particular model construction, is not well known. Here we use version 4 of the Community Atmospheric Model (CAM4) with the Community Earth System Model (CESM) to simulate dust forced by three different re-analysis meteorological datasets for the period 1990-2005. We then contrast the results of these simulations with dust simulated using online winds dynamically generated from sea surface temperatures, as well as with simulations conducted using other modeling frameworks but the same meteorological forcings, in order to determine the sensitivity of climate model output to the specific reanalysis dataset used. For the seven cases considered in our study, the different model configurations are able to simulate the annual mean of the global dust cycle, seasonality and interannual variability approximately equally well (or poorly) at the limited observational sites available. Overall, aerosol dust-source strength has remained fairly constant during the time period from 1990 to 2005, although there is strong seasonal and some interannual variability simulated in the models and seen in the observations over this time period. Model interannual variability comparisons to observations, as well as comparisons between models, suggest that interannual variability in dust is still difficult to simulate accurately, with averaged correlation coefficients of 0.1 to 0.6. Because of the large variability, at least 1 year of observations at most sites are needed to correctly observe the mean, but in some regions, particularly the remote oceans of the Southern Hemisphere, where interannual variability may be larger than in the Northern Hemisphere, 2-3 years of data are likely to be needed. |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000396128600001 |
WOS关键词 | NORTH-ATLANTIC OSCILLATION ; CHEMICAL-TRANSPORT MODELS ; EARTH SYSTEM MODEL ; LEAF-AREA INDEX ; DESERT DUST ; SAHARAN DUST ; ATMOSPHERIC DUST ; AFRICAN DUST ; TEMPORAL VARIABILITY ; SIZE DISTRIBUTION |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/18409 |
专题 | 地球科学 |
作者单位 | 1.Cornell Univ, Dept Earth & Atmospher Sci, Ithaca, NY 14850 USA; 2.SUNY Albany, Dept Atmospher & Environm Sci, Albany, NY 12222 USA; 3.UVSQ, CNRS, CEA, Lab Sci Climat & Environm, Gif Sur Yvette, France; 4.Univ Paris Diderot, Inst Phys Globe Paris, USPC, CNRS,UMR7154, Paris, France; 5.Univ Paris Est Paris Diderot Paris 7, CNRS, UMR7583, LISA, Creteil, France; 6.MIT, Dept Civil & Environm Engn, 77 Massachusetts Ave, Cambridge, MA 02139 USA |
推荐引用方式 GB/T 7714 | Smith, Molly B.,Mahowald, Natalie M.,Albani, Samuel,et al. Sensitivity of the interannual variability of mineral aerosol simulations to meteorological forcing dataset[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2017,17(5). |
APA | Smith, Molly B..,Mahowald, Natalie M..,Albani, Samuel.,Perry, Aaron.,Losno, Remi.,...&Heald, Colette L..(2017).Sensitivity of the interannual variability of mineral aerosol simulations to meteorological forcing dataset.ATMOSPHERIC CHEMISTRY AND PHYSICS,17(5). |
MLA | Smith, Molly B.,et al."Sensitivity of the interannual variability of mineral aerosol simulations to meteorological forcing dataset".ATMOSPHERIC CHEMISTRY AND PHYSICS 17.5(2017). |
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