Comparison of mean age of air in five reanalyses using the BASCOE transport model
Comparison of mean age of air in five reanalyses using the BASCOE transport model
复制标题
使用 BASCOE 传输模型进行五次重新分析中空气平均年龄的比较
DOI：
10.5194/acp-18-14715-2018
复制
发表时间：
2018
影响因子：
6.3
通讯作者：
E. Mahieu
中科院分区：
文献类型：
--
作者：
S. Chabrillat;C. Vigouroux;Y. Christophe;A. Engel;Q. Errera;D. Minganti;B. Monge;A. Segers;E. Mahieu
抽象。我们提出了一个一致的相互比较的平均年龄的空气
(AoA)根据五个现代重新分析：欧洲中心，
中期天气预报中期再分析（ERA-Interim）
日本气象厅的55年再分析（JRA-55），国家
环境预测中心气候预测系统再分析
（CFSR）和美国国家航空航天局的现代时代
研究与应用第1版（MERRA）的回顾性分析和
版本2（MERRA-2）。建模工具是一个运动学传输模型驱动的
只受表面气压和风场的影响经ERA-I验证
通过与另一种传输模式计算的AoA的比较。5次再分析提供的AoA在最差情况下相差1年，
热带平流层下部和上部超过2年
平流层在所有纬度和高度，MERRA-2和MERRA提供
最老的值（中纬度平流层中层的15 -6年），而
JRA-55和CFSR提供了最年轻的值（104岁），ERA-I提供了最年轻的值（104岁）。
提供中间结果。在50 hPa上的AoA的传播范围大到
在化学气候模型的比较中获得的扩散。的
热带和中纬度AoA之间的差异更接近
除了MERRA-2与原位观测结果相比，
热带平流层下部上升流太快。蔓延
在北方中纬度地区的五次模拟之间的差异与
气球的几十年时间序列中的观测不确定性
观察，即，大约2年。皮纳图博没有全球影响
与最近的一项研究相反，在我们对AoA的模拟中可以发现爆发
它使用了由ERA-I和JRA-55风驱动的非绝热传输模型，
加热速率并通过多元线性回归分析了时间变化
分析考虑到季节性周期，准两年期
振荡和四个时间段内的线性趋势。的振幅
平流层下部的AoA季节变化明显较大
当使用MERRA和MERRA-2时，与其他再分析相比。线性
使用ERA-I的AoA趋势证实了早期模型研究发现的趋势，
特别是在2002-2012年期间，
纬度-高度分布（在北方平流层中部为正，
在南部平流层中部为负）也与来自
SF6的卫星观测然而，线性趋势各不相同
基本上取决于所考虑的时期。2002-2015年期间，
结果显示，在北方仍存在偶极子结构，并有正趋势
半球达到0.3年12月-1日。除ERA-I外，无再分析
发现AoA趋势的任何偶极结构。趋势的迹象取决于
强烈的投入再分析和所考虑的时期，与价值
高于10 hPa，变化范围约为-0.4和0.4年12月-1日。
使用ERA-I和CFSR，2002-2015年的趋势在10 hPa以上是负的，
但使用其他三个重新分析，这些趋势是积极的。
在整个时期（1989-2015年），每次再分析都呈现出相反的趋势;
也就是说，AoA主要随CFSR和ERA-I增加，但主要随
JRA-55和MERRA-2。鉴于这种巨大的分歧，我们敦促对旨在
评估仅从再分析风得出的AoA趋势。我们简要地讨论
AoA依赖于输入再分析的一些可能原因，
强调需要使用非绝热
运输模型。
Abstract. We present a consistent intercomparison of the mean age of air
(AoA) according to five modern reanalyses: the European Centre for
Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), the Japanese
Meteorological Agency's Japanese 55-year Reanalysis (JRA-55), the National
Centers for Environmental Prediction Climate Forecast System Reanalysis
(CFSR) and the National Aeronautics and Space Administration's Modern Era
Retrospective analysis for Research and Applications version 1 (MERRA) and
version 2 (MERRA-2). The modeling tool is a kinematic transport model driven
only by the surface pressure and wind fields. It is validated for ERA-I
through a comparison with the AoA computed by another transport model. The five reanalyses deliver AoA which differs in the worst case by 1 year in
the tropical lower stratosphere and more than 2 years in the upper
stratosphere. At all latitudes and altitudes, MERRA-2 and MERRA provide the
oldest values (∼5–6 years in midstratosphere at midlatitudes), while
JRA-55 and CFSR provide the youngest values (∼4 years) and ERA-I
delivers intermediate results. The spread of AoA at 50 hPa is as large as
the spread obtained in a comparison of chemistry–climate models. The
differences between tropical and midlatitude AoA are in better agreement
except for MERRA-2. Compared with in situ observations, they indicate that
the upwelling is too fast in the tropical lower stratosphere. The spread
between the five simulations in the northern midlatitudes is as large as the
observational uncertainties in a multidecadal time series of balloon
observations, i.e., approximately 2 years. No global impact of the Pinatubo
eruption can be found in our simulations of AoA, contrary to a recent study
which used a diabatic transport model driven by ERA-I and JRA-55 winds and
heating rates. The time variations are also analyzed through multiple linear regression
analyses taking into account the seasonal cycles, the quasi-biennial
oscillation and the linear trends over four time periods. The amplitudes of
AoA seasonal variations in the lower stratosphere are significantly larger
when using MERRA and MERRA-2 than with the other reanalyses. The linear
trends of AoA using ERA-I confirm those found by earlier model studies,
especially for the period 2002–2012, where the dipole structure of the
latitude–height distribution (positive in the northern midstratosphere and
negative in the southern midstratosphere) also matches trends derived from
satellite observations of SF6. Yet the linear trends vary
substantially depending on the considered period. Over 2002–2015, the ERA-I
results still show a dipole structure with positive trends in the Northern
Hemisphere reaching up to 0.3 yr dec−1. No reanalysis other than ERA-I
finds any dipole structure of AoA trends. The signs of the trends depend
strongly on the input reanalysis and on the considered period, with values
above 10 hPa varying between approximately −0.4 and 0.4 yr dec−1.
Using ERA-I and CFSR, the 2002–2015 trends are negative above 10 hPa,
but using the three other reanalyses these trends are positive.
Over the whole period (1989–2015) each reanalysis delivers opposite trends;
i.e., AoA is mostly increasing with CFSR and ERA-I but mostly decreasing with
MERRA, JRA-55 and MERRA-2. In view of this large disagreement, we urge great caution for studies aiming
to assess AoA trends derived only from reanalysis winds. We briefly discuss
some possible causes for the dependency of AoA on the input reanalysis and
highlight the need for complementary intercomparisons using diabatic
transport models.
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作者：
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通讯作者：
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