Will a perfect model agree with perfect observations? The impact of spatial sampling
Will a perfect model agree with perfect observations? The impact of spatial sampling
复制标题
完美的模型会与完美的观察一致吗？
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
P. Stier
中科院分区：
文献类型：
--
作者：
N. Schutgens;E. Gryspeerdt;N. Weigum;S. Tsyro;D. Goto;M. Schulz;P. Stier
抽象。具有交互气溶胶的全球气候模式的空间分辨率和用于评估它们的观测结果是非常不同的。目前的模型使用的网格间距为10200公里，而卫星观测气溶胶使用的所谓像素为1010公里。地面或空中观测涉及更小的空间尺度。我们研究了由于不同的分辨率所产生的错误，通过聚合高分辨率模拟（10公里网格间距）在全球模型网格框（“完美”的模型数据）或小面积对应的像素的卫星测量或地面站点（“完美”的观察）的视野。我们的分析表明，对于一系列可观测量，如AOT（气溶胶光学厚度），消光，黑碳质量浓度，PM2.5，数密度和CCN（云凝结核），完美观测与完美全球模型的瞬时均方根（RMS）差异很容易达到30- 160%。这些差异，完全是由于不同的空间采样模型和观测，往往大于测量误差在真实的观测。对一个月的数据进行时间平均，对于某些观测量（例如AOT减少三倍），比其他观测量（例如表面黑碳浓度减少两倍）更强烈地减少了这些差异，但仍然存在显着的RMS差异（10- 75%）。请注意，这项研究忽略了真实的观测值的时间采样问题，这可能会影响我们目前的月度误差估计。我们研究了其他几种策略（如空间聚合的观测，插值模型数据），以减少这些差异，并显示其有效性。最后，我们研究的后果，在全球模型评估中使用的飞行活动数据，并表明，显着的偏见可能会引入取决于所使用的飞行策略。
Abstract. 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, PM2.5, 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.
垂直分辨飞机观测黑碳对气候模型中气溶胶过程的限制
DOI：
10.5194/acpd-13-437-2013
发表时间：
2013
期刊：
--
影响因子：
--
作者：
Kipling Z
通讯作者：
Kipling Z
影响因子：
158.5
作者：
DOCKERY, DW;POPE, CA;SPEIZER, FE
通讯作者：
SPEIZER, FE