Will a perfect model agree with perfect observations? The impact of spatial sampling

doi:10.5194/acp-16-6335-2016

GSTDTAP > 地球科学

DOI	10.5194/acp-16-6335-2016
	Will a perfect model agree with perfect observations? The impact of spatial sampling
	Nick A. J. Schutgens, Edward Gryspeerdt, Natalie Weigum, Svetlana Tsyro, Daisuke Goto, Michael Schulz, and Philip Stier
	2016-05-24
发表期刊	Atmospheric Chemistry and Physics
出版年	2016
英文摘要	The spatial resolution of global climate models with interactive aerosol and the observations used to evaluate them is very different. Current models use grid spacings of ∼ 200 km, while satellite observations of aerosol use so-called pixels of ∼ 10 km. Ground site or airborne observations relate to even smaller spatial scales. We study the errors incurred due to different resolutions by aggregating high-resolution simulations (10 km grid spacing) over either the large areas of global model grid boxes ("perfect" model data) or small areas corresponding to the pixels of satellite measurements or the field of view of ground sites ("perfect" observations). Our analysis suggests that instantaneous root-mean-square (RMS) differences of perfect observations from perfect global models can easily amount to 30–160 %, for a range of observables like AOT (aerosol optical thickness), extinction, black carbon mass concentrations, PM_2.5, number densities and CCN (cloud condensation nuclei). These differences, due entirely to different spatial sampling of models and observations, are often larger than measurement errors in real observations. Temporal averaging over a month of data reduces these differences more strongly for some observables (e.g. a threefold reduction for AOT), than for others (e.g. a twofold reduction for surface black carbon concentrations), but significant RMS differences remain (10–75 %). Note that this study ignores the issue of temporal sampling of real observations, which is likely to affect our present monthly error estimates. We examine several other strategies (e.g. spatial aggregation of observations, interpolation of model data) for reducing these differences and show their effectiveness. Finally, we examine consequences for the use of flight campaign data in global model evaluation and show that significant biases may be introduced depending on the flight strategy used.
领域	地球科学
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文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/287937
专题	地球科学
推荐引用方式 GB/T 7714	Nick A. J. Schutgens, Edward Gryspeerdt, Natalie Weigum, Svetlana Tsyro, Daisuke Goto, Michael Schulz, and Philip Stier. Will a perfect model agree with perfect observations? The impact of spatial sampling[J]. Atmospheric Chemistry and Physics,2016.
APA	Nick A. J. Schutgens, Edward Gryspeerdt, Natalie Weigum, Svetlana Tsyro, Daisuke Goto, Michael Schulz, and Philip Stier.(2016).Will a perfect model agree with perfect observations? The impact of spatial sampling.Atmospheric Chemistry and Physics.
MLA	Nick A. J. Schutgens, Edward Gryspeerdt, Natalie Weigum, Svetlana Tsyro, Daisuke Goto, Michael Schulz, and Philip Stier."Will a perfect model agree with perfect observations? The impact of spatial sampling".Atmospheric Chemistry and Physics (2016).