globalchange  > 影响、适应和脆弱性
DOI: 10.1002/jgrd.50874
论文题名:
Characterizing sampling biases in the trace gas climatologies of the SPARC Data Initiative
作者: Toohey M.; Hegglin M.I.; Tegtmeier S.; Anderson J.; Añel J.A.; Bourassa A.; Brohede S.; Degenstein D.; Froidevaux L.; Fuller R.; Funke B.; Gille J.; Jones A.; Kasai Y.; Krüger K.; Kyrölä E.; Neu J.L.; Rozanov A.; Smith L.; Urban J.; Von Clarmann T.; Walker K.A.; Wang R.H.J.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期:20
起始页码: 11847
结束页码: 11862
语种: 英语
英文关键词: climatologies ; sampling ; satellite measurements ; stratosphere
Scopus关键词: Climatology ; Gases ; Instruments ; Sampling ; Satellites ; Upper atmosphere ; Atmospheric measurement ; Chemistry-climate models ; Natural variability ; Nonuniform sampling ; Satellite instruments ; Satellite measurements ; Southern Hemisphere ; Stratospheric trace gas ; Importance sampling ; air sampling ; atmospheric chemistry ; climate modeling ; data acquisition ; ozone ; sampling bias ; satellite imagery ; stratosphere ; trace gas ; troposphere ; water
英文摘要: Monthly zonal mean climatologies of atmospheric measurements from satellite instruments can have biases due to the nonuniform sampling of the atmosphere by the instruments. We characterize potential sampling biases in stratospheric trace gas climatologies of the Stratospheric Processes and Their Role in Climate (SPARC) Data Initiative using chemical fields from a chemistry climate model simulation and sampling patterns from 16 satellite-borne instruments. The exercise is performed for the long-lived stratospheric trace gases O3 and H2O. Monthly sampling biases for O3 exceed 10% for many instruments in the high-latitude stratosphere and in the upper troposphere/lower stratosphere, while annual mean sampling biases reach values of up to 20% in the same regions for some instruments. Sampling biases for H2O are generally smaller than for O3, although still notable in the upper troposphere/lower stratosphere and Southern Hemisphere high latitudes. The most important mechanism leading to monthly sampling bias is nonuniform temporal sampling, i.e., the fact that for many instruments, monthly means are produced from measurements which span less than the full month in question. Similarly, annual mean sampling biases are well explained by nonuniformity in the month-to-month sampling by different instruments. Nonuniform sampling in latitude and longitude are shown to also lead to nonnegligible sampling biases, which are most relevant for climatologies which are otherwise free of biases due to nonuniform temporal sampling. Key Points Stratospheric trace gas climatologies may contain sampling biases Strongest sampling bias results from non-uniform temporal sampling Sampling bias greatest when natural variability is strongest ©2013. American Geophysical Union. All Rights Reserved.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63206
Appears in Collections:影响、适应和脆弱性
气候减缓与适应

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作者单位: GEOMAR Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany; Department of Meteorology, University of Reading, Reading, United Kingdom; Atmospheric Science, Hampton University, Hampton VA, United States; Smith School of Enterprise and the Environment, University of Oxford, Oxford, United Kingdom; EPhysLab, Universidade de Vigo, Ourense, Spain; Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon SK, Canada; Department of Earth and Space Sciences, Chalmers University of Technology, Göteborg, Sweden; FluxSense AB, Göteborg, Sweden; Jet Propulsion Laboratory, California Institute of Technology, Pasadena CA, United States; Instituto de Astrofísica de Andalucía, Granada, Spain; National Center for Atmospheric Research, Boulder CO, United States; Center for Limb Atmospheric Sounding, University of Colorado Boulder, Boulder CO, United States; Department of Physics, University of Toronto, Toronto ON, Canada; National Institute of Information and Communications Technology, Koganei, Japan; Department of Geosciences, University of Oslo, Oslo, Norway; Finnish Meteorological Institute, Helsinki, Finland; Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany; Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Karlsruhe, Germany; School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta GA, United States

Recommended Citation:
Toohey M.,Hegglin M.I.,Tegtmeier S.,et al. Characterizing sampling biases in the trace gas climatologies of the SPARC Data Initiative[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(20)
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