How well do stratospheric reanalyses reproduce high-resolution satellite temperature measurements?
How well do stratospheric reanalyses reproduce high-resolution satellite temperature measurements?
复制标题
平流层再分析再现高分辨率卫星温度测量结果的效果如何？
DOI：
10.5194/acp-18-13703-2018
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发表时间：
2018
影响因子：
6.3
通讯作者：
N. Hindley
中科院分区：
文献类型：
--
作者：
C. Wright;N. Hindley
抽象的。大气再分析是数据同化天气模型
被广泛用作大气真实状态的代理
最近的过去。对于平流层来说尤其如此，其中
历史观察很少。但这些平流层有多现实
重新分析？在这里，我们从六个现代的平流层温度数据重新采样
重新分析（CFSR、ERA-5、ERA-Interim、JRA-55、JRA-55C 和 MERRA-2）以生成
合成卫星观测数据，我们直接与检索到的数据进行比较
从 COSMIC、HIRDLS 和 SABRE 到亮度的卫星温度
2003 年至 2012 年 10 年间 AIRS 的气温。我们明确地
对标准公开发布的产品进行抽样，以便最好地评估其
适合典型用途。我们发现历史上所有纬度
临边探测仪观测结果与综合观测结果之间的相关性
从全输入重新分析中，高度为 30 公里时为 0.97–0.99，降至
50 公里处为 0.84–0.94。在高纬度地区可以看到最高的相关性
亚热带地区最低，但均方根 (RMS) 差异为
高纬度冬季最高（10 K 或更高）。在所有纬度上，
差异随着高度的增加而增加。高海拔差异成为
在中断时期尤其大，例如后突发时期
平流层变暖恢复阶段，其中纬向平均差异可以为
不同数据集之间高达 18 K。我们进一步表明，对于
当前一代再分析产品，全 3D 采样方法（即
充分考虑仪器测量体积的一种）总是
需要产生真实的合成 AIRS 观测结果，但几乎
从来不需要产生真实的综合 HIRDLS 观测结果。为了
合成 SABRE 和 COSMIC 观测需要全 3D 采样
赤道地区和高重力波活动地区，但不是
否则。最后，我们使用聚类分析来表明全输入
重新分析（那些吸收全套观察结果的分析，即
不包括 JRA-55C）彼此之间的相关性比与
观察，甚至是他们吸收的观察。这可能表明
这些重新分析被过度调整以匹配其比较器。如果是这样的话，这可以
对未来再分析的发展具有重大影响。
Abstract. Atmospheric reanalyses are data-assimilating weather models
which are widely used as proxies for the true state of the atmosphere in the
recent past. This is particularly the case for the stratosphere, where
historical observations are sparse. But how realistic are these stratospheric
reanalyses? Here, we resample stratospheric temperature data from six modern
reanalyses (CFSR, ERA-5, ERA-Interim, JRA-55, JRA-55C and MERRA-2) to produce
synthetic satellite observations, which we directly compare to retrieved
satellite temperatures from COSMIC, HIRDLS and SABER and to brightness
temperatures from AIRS for the 10-year period of 2003–2012. We explicitly
sample standard public-release products in order to best assess their
suitability for typical usage. We find that all-time all-latitude
correlations between limb sounder observations and synthetic observations
from full-input reanalyses are 0.97–0.99 at 30 km in altitude, falling to
0.84–0.94 at 50 km. The highest correlations are seen at high latitudes and
the lowest in the sub-tropics, but root-mean-square (RMS) differences are
highest (10 K or greater) in high-latitude winter. At all latitudes,
differences increase with increasing height. High-altitude differences become
especially large during disrupted periods such as the post-sudden
stratospheric warming recovery phase, in which zonal-mean differences can be as
high as 18 K among different datasets. We further show that, for the
current generation of reanalysis products, a full-3-D sampling approach (i.e.
one which takes full account of the instrument measuring volume) is always
required to produce realistic synthetic AIRS observations, but is almost
never required to produce realistic synthetic HIRDLS observations. For
synthetic SABER and COSMIC observations full-3-D sampling is required in
equatorial regions and regions of high gravity-wave activity but not
otherwise. Finally, we use cluster analyses to show that full-input
reanalyses (those which assimilate the full suite of observations, i.e.
excluding JRA-55C) are more tightly correlated with each other than with
observations, even observations which they assimilate. This may suggest that
these reanalyses are over-tuned to match their comparators. If so, this could
have significant implications for future reanalysis development.
影响因子：
6.3
作者：
Fujiwara, Masatomo;Wright, Jonathon S.;Zou, Cheng-Zhi
通讯作者：
Zou, Cheng-Zhi
影响因子：
6.3
作者：
Hindley, N. P.;Wright, C. J.;Mitchell, N. J.
通讯作者：
Mitchell, N. J.