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Spatial regression analysis on 32 years of total column ozone data

机译:对32年总柱臭氧数据的空间回归分析

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Multiple-regression analyses have been performed on 32 years of total ozone column data that was spatially gridded with a 1×1.5° resolution. The total ozone data consist of the MSR (Multi Sensor Reanalysis; 1979–2008) and 2 years of assimilated SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) ozone data (2009–2010). The two-dimensionality in this data set allows us to perform the regressions locally and investigate spatial patterns of regression coefficients and their explanatory power. Seasonal dependencies of ozone on regressors are included in the analysis. A new physically oriented model is developed to parameterize stratospheric ozone. Ozone variations on nonseasonal timescales are parameterized by explanatory variables describing the solar cycle, stratospheric aerosols, the quasibiennial oscillation (QBO), El Ni?o–Southern Oscillation (ENSO) and stratospheric alternative halogens which are parameterized by the effective equivalent stratospheric chlorine (EESC). For several explanatory variables, seasonally adjusted versions of these explanatory variables are constructed to account for the difference in their effect on ozone throughout the year. To account for seasonal variation in ozone, explanatory variables describing the polar vortex, geopotential height, potential vorticity and average day length are included. Results of this regression model are compared to that of a similar analysis based on a more commonly applied statistically oriented model. The physically oriented model provides spatial patterns in the regression results for each explanatory variable. The EESC has a significant depleting effect on ozone at midand high latitudes, the solar cycle affects ozone positively mostly in the Southern Hemisphere, stratospheric aerosols affect ozone negatively at high northern latitudes, the effect of QBO is positive and negative in the tropics and mid- to high latitudes, respectively, and ENSO affects ozone negatively between 30° N and 30° S, particularly over the Pacific. The contribution of explanatory variables describing seasonal ozone variation is generally large at mid- to high latitudes.We observe ozone increases with potential vorticity and day length and ozone decreases with geopotential height and variable ozone effects due to the polar vortex in regions to the north and south of the polar vortices. Recovery of ozone is identified globally. However, recovery rates and uncertainties strongly depend on choices that can be made in defining the explanatory variables. The application of several trend models, each with their own pros and cons, yields a large range of recovery rate estimates. Overall these results suggest that care has to be taken in determining ozone recovery rates, in particular for the Antarctic ozone hole.
机译:已经对32年的总臭氧柱数据进行了多元回归分析,这些数据在空间上以1×1.5°的分辨率进行网格划分。臭氧总数据包括MSR(多传感器再分析; 1979-2008年)和2年同化SCIAMACHY(大气色谱制图成像吸收光谱仪)臭氧数据(2009-2010年)。此数据集中的二维数据使我们可以局部执行回归,并研究回归系数的空间模式及其解释力。分析中包括臭氧对回归因子的季节性依赖性。开发了一种新的物理定向模型来对平流层臭氧进行参数化。臭氧在非季节性时标上的变化是通过解释性变量来参数化的,这些变量描述了太阳周期,平流层气溶胶,准双年度振荡(QBO),厄尔尼诺-南方涛动(ENSO)和平流层替代卤素,而有效等效的平流层氯(EESC) )。对于几个解释变量,构造这些解释变量的季节性调整后的版本,以说明它们对全年臭氧影响的差异。为了说明臭氧的季节性变化,包括了描述极涡,地势高度,势涡和平均日长的解释变量。将该回归模型的结果与基于更常用的统计取向模型的相似分析的结果进行比较。面向物理的模型在每个解释变量的回归结果中提供了空间模式。 EESC对中高纬度地区的臭氧具有显着的消耗作用,太阳周期主要在南半球对臭氧产生积极影响,平流层气溶胶在北高纬度地区对臭氧具有负面影响,QBO在热带和中纬度地区具有正负影响。 ENSO分别在30°N和30°S之间对臭氧产生负面影响,特别是在太平洋地区。在中高纬度地区,描述季节性臭氧变化的解释变量的贡献通常很大。我们观察到,臭氧随着潜在涡度和日长的增加而增加,臭氧随着地势高度的减少而减少,这归因于北部和北部地区的极地涡旋所致。在极地涡旋以南。臭氧的回收是全球公认的。但是,回收率和不确定性在很大程度上取决于在定义解释变量时可以做出的选择。几个趋势模型的应用,每个都有各自的优缺点,可以估计出很大的恢复率。总体而言,这些结果表明,在确定臭氧回收率时必须格外小心,尤其是对南极臭氧洞而言。

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