On the timescales and length scales of the Arctic sea ice thickness anomalies: a study based on 14 reanalyses
On the timescales and length scales of the Arctic sea ice thickness anomalies: a study based on 14 reanalyses
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北极海冰厚度异常的时间尺度和长度尺度：基于14次重新分析的研究
DOI：
10.5194/tc-13-521-2019
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
D. Docquier
中科院分区：
文献类型：
--
作者：
L. Ponsoni;F. Massonnet;T. Fichefet;M. Chevallier;D. Docquier
抽象的。海洋-海冰再分析是北极海冰的主要来源之一
厚度数据的空间和时间分辨率，因为
观测在时间和空间上仍然稀少。在这项工作中，我们首先瞄准
在比较14个国家的海冰厚度时，
再分析与不同的观测源进行比较，如系泊
上视声纳、潜艇、飞机、卫星和冰钻孔。
其次，基于同样的再分析，我们打算描述
海冰厚度异常的时间尺度（持续性）和长度尺度。我们
调查海冰浓度的数据同化是否由
再分析影响了海冰厚度的真实性，
时间尺度和长度尺度。结果表明，海冰数据的再分析
同化并不一定在海冰厚度方面表现得更好
与不同化海冰浓度的再分析相比。
然而，数据同化对时间尺度和长度尺度有明显的影响：
用海冰数据同化建立的再分析提供了较短的时间尺度，
长度刻度。数据再分析的平均时间尺度和长度尺度
同化变化范围分别为2.5 - 5.0个月和337.0 - 732.5公里，
而没有数据同化的再分析的特征是
4.9 846.7 ~ 935.7 km。
Abstract. The ocean–sea ice reanalyses are one of the main sources of Arctic sea ice
thickness data both in terms of spatial and temporal resolution, since
observations are still sparse in time and space. In this work, we first aim
at comparing how the sea ice thickness from an ensemble of 14
reanalyses compares with different sources of observations, such as moored
upward-looking sonars, submarines, airbornes, satellites, and ice boreholes.
Second, based on the same reanalyses, we intend to characterize the
timescales (persistence) and length scales of sea ice thickness anomalies. We
investigate whether data assimilation of sea ice concentration by the
reanalyses impacts the realism of sea ice thickness as well as its respective
timescales and length scales. The results suggest that reanalyses with sea ice data
assimilation do not necessarily perform better in terms of sea ice thickness
compared with the reanalyses which do not assimilate sea ice concentration.
However, data assimilation has a clear impact on the timescales and length scales:
reanalyses built with sea ice data assimilation present shorter timescales and
length scales. The mean timescales and length scales for reanalyses with data
assimilation vary from 2.5 to 5.0 months and 337.0 to 732.5 km, respectively,
while reanalyses with no data assimilation are characterized by values from
4.9 to 7.8 months and 846.7 to 935.7 km, respectively.
影响因子：
4.6
作者：
P. Uotila;H. Goosse;K. Haines;M. Chevallier;A. Barthélemy;C. Bricaud;J. Carton;N. Fučkar;G. Garric;D. Iovino;F. Kauker;M. Korhonen;V. Lien;M. Marnela;F. Massonnet;D. Mignac;K. Andrew Peterson;Remon Sadikni;Li Shi;S. Tietsche;T. Toyoda;Jiping Xie;Zhaoru Zhang
通讯作者：
P. Uotila;H. Goosse;K. Haines;M. Chevallier;A. Barthélemy;C. Bricaud;J. Carton;N. Fučkar;G. Garric;D. Iovino;F. Kauker;M. Korhonen;V. Lien;M. Marnela;F. Massonnet;D. Mignac;K. Andrew Peterson;Remon Sadikni;Li Shi;S. Tietsche;T. Toyoda;Jiping Xie;Zhaoru Zhang
影响因子：
30.7
作者：
Sevellec, Florian;Fedorov, Alexey V.;Liu, Wei
通讯作者：
Liu, Wei