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Precursor Role of Winter Sea-Ice in the Labrador Sea for Following-Spring Precipitation over Southeastern North America and Western Europe


doi: 10.1007/s00376-017-6291-3

  • The role of winter sea-ice in the Labrador Sea as a precursor for precipitation anomalies over southeastern North America and Western Europe in the following spring is investigated. In general terms, as the sea ice increases, the precipitation also increases. In more detail, however, analyses indicate that both the winter sea-ice and the sea surface temperature (SST) anomalies related to increases in winter sea-ice in the Labrador Sea can persist into the following spring. These features play a forcing role in the spring atmosphere, which may be the physical mechanism behind the observational relationship between the winter sea-ice and spring precipitation anomalies. The oceanic forcings in spring include Arctic sea-ice anomalies and SST anomalies in the tropical Pacific and high-latitude North Atlantic. Multi-model Coupled Model Intercomparison Project Phase 5 and Atmospheric Model Intercomparison Project simulation results show that the atmospheric circulation response to the combination of sea-ice and SST is similar to that observed, which suggests that the oceanic forcings are indeed the physical reason for the enhanced spring precipitation. Sensitivity experiments conducted using an atmospheric general circulation model indicate that the increases in precipitation over southeastern North America are mainly attributable to the effect of the SST anomalies, while the increases over Western Europe are mainly due to the sea-ice anomalies. Although model simulations reveal that the SST anomalies play the primary role in the precipitation anomalies over southeastern North America, the observational statistical analyses indicate that the area of sea-ice in the Labrador Sea seems to be the precursor that best predicts the spring precipitation anomaly.
    摘要: 当冬季拉布拉多海海冰增加时, 北美东南部和欧洲西部的春季降水会增加. 因此, 冬季拉布拉多海海冰可以作为春季降水的一个预测因子. 进一步的分析表明, 海冰异常和与之同时出现的海温异常都能够持续至春季, 并对春季大气环流产生影响, 从而导致降水异常. 这是冬季海冰和春季降水产生联系的主要原因, CMIP5的AMIP试验也证明了这一点. 在这一联系中, 海冰和海温各自起到何种作用呢?大气环流模式敏感性试验表明, 北美东南部的降水主要是由海温异常造成;欧洲西部的降水主要由海冰异常造成. 值得注意的是, 尽管模式试验表明海温异常主要造成北美东南部的降水异常, 但是冬季的拉布拉多海海冰异常是最好的统计预测因子, 因为我们无法从观测中分离出上述海温异常信号.
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  • Alexand er, M. A., U. S. Bhatt, J. E. Walsh, M. S. Timlin, J. S. Miller, J. D. Scott, 2004: The atmospheric response to realistic Arctic sea ice anomalies in an AGCM during winter. J. Climate, 17, 890-905, https://doi.org/10.1175/1520-0442(2004)017<0890:TARTRA>2.0,CO;2.10.1175/1520-0442(2004)017<0890:TARTRA>2.0.CO;2fc0ae199b9c2388844c40377f6b33268http%3A%2F%2Fadsabs.harvard.edu%2Fcgi-bin%2Fnph-data_query%3Fbibcode%3D2004JCli...17..890A%26amp%3Bdb_key%3DPHY%26amp%3Blink_type%3DABSTRACT%26amp%3Bhigh%3D06304http://journals.ametsoc.org/doi/abs/10.1175/1520-0442%282004%29017%3C0890%3ATARTRA%3E2.0.CO%3B2
    Cavalieri D. J., C. L. Parkinson, P. Gloersen, and H. Zwally, 1996: Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS passive microwave data, version 1. November 1979-2014, Tech. Rep., NASA Natl. Snow and Ice Data Cent. Distrib. Active Archive Cent.,Boulder,Colo.
    Conil S., Z. X. Li, 2005: Linearity of the atmospheric response to North Atlantic SST and sea ice anomalies.J. Climate,18,1986-2003, https://doi.org/10.1175/JCLI3388.1.10.1175/JCLI3388.15712c7c221c1aed81ddcb8ae88516157http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2005JCli...18.1986Chttp://journals.ametsoc.org/doi/abs/10.1175/JCLI3388.1The observations of the ocean09“atmosphere09“sea ice have recently revealed that the oceanic surfaces can have a subtle but significant impact on the atmospheric long-term fluctuations. Low-frequency variations and long-term trends of the North Atlantic atmospheric circulation have been partly related to particular SST and sea ice features. In this work, the influence of typical tripolar SST and dipolar sea ice anomalies in the North Atlantic09“Arctic on the atmosphere is investigated. A large ensemble of AGCM simulations forced by three different anomalous boundary conditions (SST, sea ice, and SST + sea ice) are used. The linearity of the simulated response in the winter season is particularly assessed. In these experiments, while the winter low-level temperature response is mainly symmetric about the sign of the forcing, the asymmetric part of the geopotential response is substantial. The sea ice forcing maintains a baroclinic response with a strong temperature anomaly in the vicinity of the forcing but with a weak vertical penetration. The SST maintains an NAO-like equivalent barotropic temperature and geopotential height response that extends throughout the troposphere. It is also shown that the combination of the two forcings is mainly linear for the low-level temperature and nonlinear for the geopotential height. While the SST forcing seems to be the main contributor to the total temperature and geopotential height responses, the sea ice forcing appears to introduce significant nonlinear perturbations.
    Dee, D. P., Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system.Quart. J. Roy. Meteor. Soc.,137,553-597, https://doi.org/10.1002/qj.828.10.1002/qj.8285b3115ec8b338ee97111270a1831c4b2http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fqj.828%2Fpdfhttp://doi.wiley.com/10.1002/qj.v137.656ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF. Copyright 2011 Royal Meteorological Society
    Deser C., J. E. Walsh, and M. S. Timlin, 2000: Arctic sea ice variability in the context of recent atmospheric circulation trends. J. Climate, 13, 617-633, https://doi.org/10.1175/1520-0442(2000)013<0617:ASIVIT>2.0,CO;2.10.1175/1520-0442(2000)0132.0.CO;24e146878c21adc9de0ce4b8fa43a8ce4http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2000JCli...13..617Dhttp://journals.ametsoc.org/doi/abs/10.1175/1520-0442%282000%29013%3C0617%3AASIVIT%3E2.0.CO%3B2Abstract Forty years (1958–97) of reanalysis products and corresponding sea ice concentration data are used to document Arctic sea ice variability and its association with surface air temperature (SAT) and sea level pressure (SLP) throughout the Northern Hemisphere extratropics. The dominant mode of winter (January–March) sea ice variability exhibits out-of-phase fluctuations between the western and eastern North Atlantic, together with a weaker dipole in the North Pacific. The time series of this mode has a high winter-to-winter autocorrelation (0.69) and is dominated by decadal-scale variations and a longer-term trend of diminishing ice cover east of Greenland and increasing ice cover west of Greenland. Associated with the dominant pattern of winter sea ice variability are large-scale changes in SAT and SLP that closely resemble the North Atlantic oscillation. The associated SAT and surface sensible and latent heat flux anomalies are largest over the portions of the marginal sea ice zone in which the tr...
    Deser C, G. Magnusdottir, R. Saravanan, A. Phillips, 2004: The effects of North Atlantic SST and sea ice anomalies on the winter circulation in CCM3. Part II: direct and indirect components of the response. J. Climate, 17, 877-889, https://doi.org/10.1175/1520-0442(2004)017<0877:TEONAS>2.0,CO;2.
    Duchon C. E., 1979: Lanczos filtering in one and two dimensions. J. Appl. Meteorol., 18, 1016-1022, https://doi.org/10.1175/1520-0450(1979)018<1016:LFIOAT>2.0,CO;2.10.1175/1520-0450(1979)018<1016:LFIOAT>2.0.CO;226ec2d2002010a4ba6313a775aa66556http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1979JApMe..18.1016Dhttp://journals.ametsoc.org/doi/abs/10.1175/1520-0450%281979%29018%3C1016%3ALFIOAT%3E2.0.CO%3B2A Fourier method of filtering digital data called Lanczos filtering is described. Its principal feature is the use of “sigma factors” which significantly reduce the amplitude of the Gibbs oscillation. A pair of graphs is developed that can be used to determine filter response quality given the number of weights and the value of the cutoff frequency, the only two inputs required by the method. Examples of response functions in one and two dimensions are given and comparisons are made with response functions from other filters. The simplicity of calculating the weights and the adequate response make Lanczos filtering an attractive filtering method.
    Frankignoul C., N. Sennèchael, and P. Cauchy, 2014: Observed atmospheric response to cold season sea ice variability in the Arctic.J. Climate,27,1243-1254, https://doi.org/10.1175/JCLI-D-13-00189.1.10.1175/JCLI-D-13-00189.1c7c506e0f5077d90ad785a50301d1668http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2014JCli...27.1243Fhttp://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-13-00189.1Abstract The relation between weekly Arctic sea ice concentrations (SICs) from December to April and sea level pressure (SLP) during 1979-2007 is investigated using maximum covariance analysis (MCA). In the North Atlantic sector, the interaction between the North Atlantic Oscillation (NAO) and a SIC seesaw between the Labrador Sea and the Greenland-Barents Sea dominates. The NAO drives the seesaw and in return the seesaw precedes a midwinter/spring NAO-like signal of the opposite polarity but with a strengthened northern lobe, thus acting as a negative feedback, with maximum squared covariance at a lag of 6 weeks. Statistical significance decreases when SLP is considered in the whole Northern Hemisphere but it increases when North Pacific SIC is included in the analysis. The maximum squared covariance then occurs after 8 weeks, resembling a combination of the NAO response to the Atlantic SIC seesaw and the Aleutian-Icelandic low seesaw-like response to in-phase SIC changes in the Bering and Okhotsk Seas, which is found to lag the North Pacific SIC. Adding SST anomalies to the SIC anomalies in the MCA leads to a loss of significance when the MCA is limited to the North Atlantic sector and a slight degradation in the Pacific and hemispheric cases, suggesting that SIC is the driver of the midwinter/spring atmospheric signal. However, North Pacific cold season SST anomalies also precede a NAO/Arctic Oscillation (AO)-like SLP signal after a shorter delay of 3-4 weeks.
    Guo D., Y. Gao, I. Bethke, D. Gong, M. Johannessen, and H. J. Wang, 2014: Mechanism on how the spring Arctic sea ice impacts the East Asian summer monsoon.Theor. Appl. Climatol.,115,107-119, https://doi.org/10.1007/s00704-013-0872-6.10.1007/s00704-013-0872-6e974c7d3c1cbd752fc0be37fda1807fehttp%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs00704-013-0872-6http://link.springer.com/10.1007/s00704-013-0872-6Observational analysis and purposely designed coupled atmosphere cean (AOGCM) and atmosphere-only (AGCM) model simulations are used together to investigate a new mechanism describing how spring Arctic sea ice impacts the East Asian summer monsoon (EASM). Consistent with previous studies, analysis of observational data from 1979 to 2009 show that spring Arctic sea ice is significantly linked to the EASM on inter-annual timescales. Results of a multivariate Empirical Orthogonal Function analysis reveal that sea surface temperature (SST) changes in the North Pacific play a mediating role for the inter-seasonal connection between spring Arctic sea ice and the EASM. Large-scale atmospheric circulation and precipitation changes are consistent with the SST changes. The mechanism found in the observational data is confirmed by the numerical experiments and can be described as follows: spring Arctic sea ice anomalies cause atmospheric circulation anomalies, which, in turn, cause SST anomalies in the North Pacific. The SST anomalies can persist into summer and then impact the summer monsoon circulation and precipitation over East Asia. The mediating role of SST changes is highlighted by the result that only the AOGCM, but not the AGCM, reproduces the observed sea ice-EASM linkage.
    Honda M., J. Inoue, and S. Yamane, 2009: Influence of low Arctic sea-ice minima on anomalously cold Eurasian winters,Geophys. Res. Lett.,36,L08707, https://doi.org/10.1029/2008GL037079.10.1029/2008GL03707911ff7459b32da24cee92554351efd9cbhttp%3A%2F%2Fwww.cabdirect.org%2Fabstracts%2F20103055291.htmlhttp://www.cabdirect.org/abstracts/20103055291.htmlInfluence of low Arctic sea-ice minima in early autumn on the wintertime climate over Eurasia is investigated. Observational evidence shows that significant cold anomalies over the Far East in early winter and zonally elongated cold anomalies from Europe to Far East in late winter are associated with the decrease of the Arctic sea-ice cover in the preceding summer-to-autumn seasons. Results fro...
    Han Z., F. F. Luo, and J. H. Wan, 2016a: The observational influence of the North Atlantic SST tripole on the early spring atmospheric circulation.Geophys. Res. Lett.,43,2998-3003, https://doi.org/10.1002/2016GL068099.10.1002/2016GL0680992736641738fe653ad6901014b053ba93http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2016GL068099%2Ffullhttp://doi.wiley.com/10.1002/2016GL068099This study investigated the forcing of the North Atlantic sea surface temperature (SST) tripole on the North Atlantic Oscillation (NAO)-like circulation in early spring (February-April) in observations. Corresponding to an SST tripole forcing in early spring, the atmospheric circulation is very weak and insignificant. However, further analyses indicate that the observational effect of the SST anomalies on the NAO-like circulation is disturbed by the concomitant sea ice anomalies. With the linear effects of sea ice anomalies removed, there is an equivalent barotropic NAO-like circulation in early spring related to a North Atlantic SST tripole.
    Han Z., S. L. Li, J. P. Liu, Y. Q. Gao, and P. Zhao, 2016b: Linear additive impacts of arctic sea ice reduction and La Niña on northern hemispheric winter climate. J. Climate 29, https://doi.org/10.1175/JCLI-D-15-0416.1.10.1175/JCLI-D-15-0416.1d4907fc539e130d9769a3bde074b8b3fhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2016JCli...29.5513Hhttp://adsabs.harvard.edu/abs/2016JCli...29.5513HAbstract Both Arctic sea ice loss and La Nina events can result in cold conditions in midlatitude Eurasia in winter. Since the two forcings sometimes occur simultaneously, determining whether they are independent of each other is undertaken first. The result suggests an overall independence. Considering possible interactions between them, their coordinated impacts on the Northern Hemisphere winter climate are then investigated based on observational data analyses, historical simulation analyses from one coupled model (MPI-ESM-LR) contributing to CMIP5, and atmospheric general circulation model sensitive experiments in ECHAM5. The results show that the impacts of the two forcings are overall linearly accumulated. In comparison with one single forcing, there is intensified cooling response in midlatitude Eurasia along with northern warmer outhern cooler dipolar temperature responses over North America. Despite the additive linearity, additive nonlinearity between the two forcings is identifiable. The nonlin...
    Hawcroft M. K., L. C. Shaffrey, K. I. Hodges, and H. F. Dacre, 2012: How much Northern Hemisphere precipitation is associated with extratropical cyclones? Geophys. Res. Lett. 39, https://doi.org/10.1029/2012GL053866.10.1029/2012GL0538667c18acb3ba450f2f04b4ad737ff37691http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2012GL053866%2Ffullhttp://onlinelibrary.wiley.com/doi/10.1029/2012GL053866/fullExtratropical cyclones are often associated with heavy precipitation events and can have major socio-economic impacts. This study investigates how much of the total precipitation in the Northern Hemisphere is associated with extratropical cyclones. An objective feature tracking algorithm is used to locate cyclones and the precipitation associated with these cyclones is quantified to establish their contribution to total precipitation. Climatologies are produced from the Global Precipitation Climatology Project (GPCP) daily dataset and the ERA-Interim reanalysis. The magnitude and spatial distribution of cyclone associated precipitation and their percentage contribution to total precipitation is closely comparable in both datasets. In some regions, the contribution of extratropical cyclones exceeds 90/85% of the total DJF/JJA precipitation climatology. The relative contribution of the most intensely precipitating storms to total precipitation is greater in DJF than JJA. The most intensely precipitating 10% of storms contribute over 20% of total storm associated precipitation in DJF, whereas they provide less than 15% of this total in JJA.
    Huang S. L., X. Q. Yang, and Q. Xie, 1992: The effects of the Arctic sea ice on the variations of atmospheric circulation and climate. Acta Meteorologica Sinica, 6, 1- 14.4c2b75b74d700e31495e2be89229b0c8http%3A%2F%2Fwww.cqvip.com%2FQK%2F88418X%2F199201%2F1005135191.htmlhttp://www.cqvip.com/QK/88418X/199201/1005135191.htmlThe SST anomaly of the central-eastern equatorial Pacific and the arctic sea ice anomalies of the four districts located respectively in 160ºE-110ºW,110ºW-20ºW,70ºE-160ºE and 20ºW-70ºE are taken as five separate factors.And the relationship between each factor and the atmospheric general circulation and the climate is investigated by observational analysis and numerical experiments.It is shown that the effects of the arctic sea ice anomalies on the variations of atmospheric circulation and climate are comparable to or even in some cases greater than that of EI Nino events.So one should pay much attention to the study of polar sea ice anomalies in climate research.http://www.cqvip.com/QK/88418X/199201/1005135191.html
    Kvamst N. G., P. Skeie, and D. B. Stephenson, 2004: Impact of Labrador Sea-ice extent on the North Atlantic Oscillation.Int. J. Climatol.,24,603-612, https://doi.org/10.1002/joc.1015.10.1002/joc.1015082c7633c28a9fb9f9c38f18384ba769http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fjoc.1015%2Fpdfhttp://doi.wiley.com/10.1002/%28ISSN%291097-0088The wintertime atmospheric response to imposed sea-surface temperature and sea-ice extent changes in the Labrador Sea has been investigated by means of ensemble simulations with an atmospheric general circulation model. Low temperatures and heavy ice conditions in the Labrador Sea produce a statistically significant (at 95% confidence) negative North Atlantic oscillation-Arctic oscillation (NAO-AO) response. Conversely, reduced sea-ice extent in the Labrador Sea produces a positive NAO-AO response. The two simulations with opposite sea-ice conditions in the Labrador Sea exhibit a maximum mean wintertime difference of 4-5 hPa in sea-level pressure corresponding to a substantial and statistically significant change in the NAO-AO index of 0.7 standard deviations. The large-scale response to a local perturbation of sea-ice conditions is associated with marked changes in the transient eddies (synoptic storms). Changes in the sea-ice cover cause changes in low-level baroclinicity that perturb the travelling baroclinic disturbances, which then bring the signal downstream to manifest a non-local Atlantic-wide response. The atmospheric response suggests that the sea ice in the Labrador Sea is able to provide an important negative feedback on long-term NAO-AO variations.
    Li F., H. J. Wang, 2013: Relationship between Bering Sea ice cover and East Asian winter monsoon year-to-year variations.Adv. Atmos. Sci.,30,48-56, https://doi.org/10.1007/s00376-012-2071-2.10.1007/s00376-012-2071-2c88dec2c43efb8f9fcc159002dbb6933http%3A%2F%2Fonlinelibrary.wiley.com%2Fresolve%2Freference%2FXREF%3Fid%3D10.1007%2Fs00376-012-2071-2http://link.springer.com/10.1007/s00376-012-2071-2AbstractIn this study, the relationship between year-to-year variations in the Bering Sea ice cover (BSIC) and the East Asian winter monsoon (EAWM) for the period 1969–2001 was documented. The time series of total ice cover in the eastern Bering Sea correlated with the EAWM index at 610.49, indicating that they are two tightly related components. Our results show that the BSIC was closely associated with the simultaneous local and large-scale atmosphere over the Asian-northern Pacific region. Heavy BSIC corresponded to weaker EAWM circulations and light BSIC corresponded to stronger EAWM circulations. Thus, the BSIC should be considered as one of the possible factors affecting the EAWM variation.
    Liu J. P., J. A. Curry, H. Wang, M. Song, and R. M. Horton, 2012: Impact of declining Arctic sea ice on winter snowfall.Proceedings of the National Academy of Sciences of the Unites States of America.,109,4074-4079, https://doi.org/10.1073/pnas.V1114910109.10.1073/pnas.111491010922371563e869b196cae446b30762b978476557d4http%3A%2F%2Fwww.jstor.org%2Fstable%2F41507098http://www.pnas.org/cgi/doi/10.1073/pnas.1114910109While the Arctic region has been warming strongly in recent decades, anomalously large snowfall in recent winters has affected large parts of North America, Europe, and east Asia. Here we demonstrate that the decrease in autumn Arctic sea ice area is linked to changes in the winter Northern Hemisphere atmospheric circulation that have some resemblance to the negative phase of the winter Arctic oscillation. However, the atmospheric circulation change linked to the reduction of sea ice shows much broader meridional meanders in midlatitudes and clearly different interannual variability than the classical Arctic oscillation. This circulation change results in more frequent episodes of blocking patterns that lead to increased cold surges over large parts of northern continents. Moreover, the increase in atmospheric water vapor content in the Arctic region during late autumn and winter driven locally by the reduction of sea ice provides enhanced moisture sources, supporting increased heavy snowfall in Europe during early winter and the northeastern and midwestern United States during winter. We conclude that the recent decline of Arctic sea ice has played a critical role in recent cold and snowy winters.
    Magnusdottir G., C. Deser, and R. Saravanan, 2004: The effects of North Atlantic SST and sea ice anomalies on the winter circulation in CCM3. Part I: Main features and storm track characteristic of the response. J. Climate, 17, 857-876, https://doi.org/10.1175/1520-0442(2004)017<0877:TEONAS>2.0,CO;2.
    Mori M., M. Watanabe, H. Shiogama, J. Inoue, and M. Kimoto, 2014: Robust Arctic sea-ice influence on the frequent Eurasian cold winters in past decades.Nature Geoscience,7,869-873, https://doi.org/10.1038/ngeo2277.10.1038/ngeo2277cdef8a86f56c39f6052fde6e5d1dd7bbhttp%3A%2F%2Fwww.nature.com%2Fngeo%2Fjournal%2Fv7%2Fn12%2Fabs%2Fngeo2277.htmlhttp://www.nature.com/doifinder/10.1038/ngeo2277Over the past decade, severe winters occurred frequently in mid-latitude Eurasia, despite increasing global- and annual-mean surface air temperatures. Observations suggest that these cold Eurasian winters could have been instigated by Arctic sea-ice decline, through excitation of circulation anomalies similar to the Arctic Oscillation. In climate simulations, however, a robust atmospheric response to sea-ice decline has not been found, perhaps owing to energetic internal fluctuations in the atmospheric circulation. Here we use a 100-member ensemble of simulations with an atmospheric general circulation model driven by observation-based sea-ice concentration anomalies to show that as a result of sea-ice reduction in the Barents-Kara Sea, the probability of severe winters has more than doubled in central Eurasia. In our simulations, the atmospheric response to sea-ice decline is approximately independent of the Arctic Oscillation. Both reanalysis data and our simulations suggest that sea-ice decline leads to more frequent Eurasian blocking situations, which in turn favour cold-air advection to Eurasia and hence severe winters. Based on a further analysis of simulations from 22 climate models we conclude that the sea-ice-driven cold winters are unlikely to dominate in a warming future climate, although uncertainty remains, due in part to an insufficient ensemble size.
    Overland, J. E., J. A. Francis, R. Hall, E. Hanna, S.-J. Kim, T. Vihma, 2015: The melting Arctic and midlatitude weather patterns: Are they connected? J.Climate,28,7917-7932, https://doi.org/10.1175/JCLI-D-14-00822.1.10.1175/JCLI-D-14-00822.10eff56c315ae22f8ed4dcb680ca380fchttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2015JCli...28.7917Ohttp://journals.ametsoc.org/doi/10.1175/JCLI-D-14-00822.1The potential of recent Arctic changes to influence hemispheric weather is a complex and controversial topic with considerable uncertainty, as time series of potential linkages are short (<10 yr) and understanding involves the relative contribution of direct forcing by Arctic changes on a chaotic climatic system. A way forward is through further investigation of atmospheric dynamic mechanisms. During several exceptionally warm Arctic winters since 2007, sea ice loss in the Barents and Kara Seas initiated eastward-propagating wave trains of high and low pressure. Anomalous high pressure east of the Ural Mountains advected Arctic air over central and eastern Asia, resulting in persistent cold spells. Blocking near Greenland related to low-level temperature anomalies led to northerly flow into eastern North America, inducing persistent cold periods. Potential Arctic connections in Europe are less clear. Variability in the North Pacific can reinforce downstream Arctic changes, and Arctic amplification can accentuate the impact of Pacific variability. The authors emphasize multiple linkage mechanisms that are regional, episodic, and based on amplification of existing jet stream wave patterns, which are the result of a combination of internal variability, lower-tropospheric temperature anomalies, and midlatitude teleconnections. The quantitative impact of Arctic change on midlatitude weather may not be resolved within the foreseeable future, yet new studies of the changing Arctic and subarctic low-frequency dynamics, together with additional Arctic observations, can contribute to improved skill in extended-range forecasts, as planned by the WMO Polar Prediction Project (PPP). 2015 American Meteorological Society.
    Rayner N. A., D. E. Parker, E. B. Horton, C. K. Folland , L. V. Alexand er, D. P. Powell, E. C. Kent, and A. Kaplan, 2003: Global analyses of sea surface temperature,sea ice,and night marine air temperature since the late nineteenth century. J. Geophys. Res.,108, 4407-4443,https://doi.org/10.1029/2002JD002670.10.1029/2002JD0026700831f099871c89699f00bb6e2586346bhttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2002JD002670%2Ffullhttp://doi.wiley.com/10.1029/2002JD002670We present the Met Office Hadley Centre's sea ice and sea surface temperature (SST) data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1º latitude-longitude grid from 1871. The companion HadMAT1 runs monthly from 1856 on a 5º latitude-longitude grid and incorporates new corrections for the effect on NMAT of increasing deck (and hence measurement) heights. HadISST1 and HadMAT1 temperatures are reconstructed using a two-stage reduced-space optimal interpolation procedure, followed by superposition of quality-improved gridded observations onto the reconstructions to restore local detail. The sea ice fields are made more homogeneous by compensating satellite microwave-based sea ice concentrations for the impact of surface melt effects on retrievals in the Arctic and for algorithm deficiencies in the Antarctic and by making the historical in situ concentrations consistent with the satellite data. SSTs near sea ice are estimated using statistical relationships between SST and sea ice concentration. HadISST1 compares well with other published analyses, capturing trends in global, hemispheric, and regional SST well, containing SST fields with more uniform variance through time and better month-to-month persistence than those in GISST. HadMAT1 is more consistent with SST and with collocated land surface air temperatures than previous NMAT data sets.
    Roeckner, E., Coauthors, 2003: The atmospheric general circulation model ECHAM5. Part I: Model description. Max Planck Institute for Meteorology Rep No. 349, 127 pp.
    Roeckner, E., Coauthors, 2006: Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 atmosphere model.J. Climate,19,3771-3791, https://doi.org/10.1175/JCLI3824.1.10.1175/JCLI3824.1fa3a017a308a4540aebf217736a65fachttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2006JCli...19.3771Rhttp://journals.ametsoc.org/doi/abs/10.1175/JCLI3824.1The most recent version of the Max Planck Institute for Meteorology atmospheric general circulation model, ECHAM5, is used to study the impact of changes in horizontal and vertical resolution on seasonal mean climate. In a series of Atmospheric Model Intercomparison Project (AMIP)-style experiments with resolutions ranging between T21L19 and T159L31, the systematic errors and convergence properties are assessed for two vertical resolutions. At low vertical resolution (L19) there is no evidence for convergence to a more realistic climate state for horizontal resolutions higher than T42. At higher vertical resolution (L31), on the other hand, the root-mean-square errors decrease monotonically with increasing horizontal resolution. Furthermore, except for T42, the L31 versions are superior to their L19 counterparts, and the improvements become more evident at increasingly higher horizontal resolutions. This applies, in particular, to the zonal mean climate state and to the stationary wave patterns in boreal winter. As in previous studies, increasing horizontal resolution leads to a warming of the troposphere, most prominently at midlatitudes, and to a poleward shift and intensification of the midlatitude westerlies. Increasing the vertical resolution has the opposite effect, almost independent of horizontal resolution. Whereas the atmosphere is colder at low and middle latitudes, it is warmer at high latitudes and close to the surface. In addition, increased vertical resolution results in a pronounced warming in the polar upper troposphere and lower stratosphere, where the cold bias is reduced by up to 50% compared to L19 simulations. Consistent with these temperature changes is a decrease and equatorward shift of the midlatitude westerlies. The substantial benefits in refining both horizontal and vertical resolution give some support to scaling arguments deduced from quasigeostrophic theory implying that horizontal and vertical resolution ought to be chosen consistently.
    Schneider, U., Coauthors, 2011: GPCC full data reanalysis version 6.0 at 1.0: Monthly land-surface precipitation from rain-gauges built on GTS-based and historic data. https://doi.org/10.5676/DWD_GPCC/FD_M_V6_100.
    [ Available online from https://rda.ucar.edu/datasets/ds496.0/
    Strong C., G. Magnusdottir, 2011: Dependence of NAO variability on coupling with sea ice.Climate Dyn.,36,1681-1689, https://doi.org/10.1007/s00382-010-0752-z.10.1007/s00382-010-0752-zf3f0c02a4e48865422ed9eb8e7edbfc7http%3A%2F%2Fwww.springerlink.com%2Fcontent%2Fa66j00k135476366%2Fhttp://link.springer.com/10.1007/s00382-010-0752-zThe variance of the North Atlantic Oscillation index (denoted ) is shown to depend on its coupling with area-averaged sea ice concentration anomalies in and around the Barents Sea (index denoted ). The observed form of this coupling is a negative feedback whereby positive tends to produce negative , which in turn forces negative . The effects of this feedback in the system are examined by modifying the feedback in two modeling frameworks: a statistical vector autoregressive model ( ) and an atmospheric global climate model ( ) customized so that sea ice anomalies on the lower boundary are stochastic with adjustable sensitivity to the model evolving . Experiments show that the variance of decreases nearly linearly with the sensitivity of to , where the sensitivity is a measure of the negative feedback strength. Given that the sea ice concentration field has anomalies, the variance of goes down as these anomalies become more sensitive to . If the sea ice concentration anomalies are entirely absent, the variance of is even smaller than the experiment with the most sensitive anomalies. Quantifying how the variance of depends on the presence and sensitivity of sea ice anomalies to has implications for the simulation of in global climate models. In the physical system, projected changes in sea ice thickness or extent could alter the sensitivity of to , impacting the within-season variability and hence predictability of .
    Walsh J. E., 2014: Intensified warming of the Arctic: Causes and impacts on middle latitudes.Global and Planetary Change,117,52-63, 2014. 03. 003.https://doi.org/10.1016/j.gloplacha.10.1016/j.gloplacha.2014.03.0030492af2361aef1eb6ba44877938ed087http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0921818114000575http://linkinghub.elsevier.com/retrieve/pii/S0921818114000575Over the past half century, the Arctic has warmed at about twice the global rate. The reduction of sea ice and snow cover has contributed to the high-latitude warming, as the maximum of the amplification during autumn is a fingerprint of the ice-albedo feedback. There is evidence that atmospheric water vapor, a greenhouse gas, has increased in the Arctic over the past several decades. Ocean heat fluxes into the Arctic from the North Atlantic and North Pacific have also contributed to the Arctic warming through a reduction of sea ice. Observational and modeling studies suggest that reduced sea ice cover and a warmer Arctic in autumn may affect the middle latitudes by weakening the west-to-east wind speeds in the upper atmosphere, by increasing the frequency of wintertime blocking events that in turn lead to persistence or slower propagation of anomalous temperatures in middle latitudes, and by increasing continental snow cover that can in turn influence the atmospheric circulation. While these effects on middle latitudes have been suggested by some analyses, natural variability has thus far precluded a conclusive demonstration of an impact of the Arctic on mid-latitude weather and climate.
    Wen N., Z. Y. Liu, Q. Y. Liu, and C. Frankignoul, 2005: Observations of SST,heat flux and north Atlantic ocean-atmosphere interaction. Geophys. Res. Lett.,32,348-362,https://doi.org/10.1029/2005GL024871.
    World Meteorological Organization, 2012: WMO Statement on the Status of the Global Climate in 2011. WMO-No. 1085. World Meteorological Organization,10.1080/147032903100008900353ac1e4149d08c9110bddc245a4e8a02http%3A%2F%2Fwww.indiaenvironmentportal.org.in%2Freports-documents%2Fwmo-statement-status-global-climate-2011http://www.indiaenvironmentportal.org.in/reports-documents/wmo-statement-status-global-climate-2011This issue of WMO annual survey on weather and climate change provides evidence that 2011 had the highest global mean surface temperature levels in a La Ni09a year. Highlighting a number of climate extremes, it provides evidences of the major impacts of one of the strongest La Ni09a events of the past 60 years, among which are the significant flooding in South-East Asia and the major drought in East Africa. It also notes that Arctic sea ice continued its declining trend and returns on the destructive tornado seasons in the United States of America.
    Wu B. Y., J. Z. Su, and R. H. Zhang, 2011: Effects of autumn-winter Arctic sea ice on winter Siberian High.Chinese Science Bulletin,56,3220-3228, https://doi.org/10.1007/s11434-011-4696-4.10.1007/s11434-011-4696-4b20ccb11ea3bfc71e4feadc24effb114http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs11434-011-4696-4http://link.springer.com/10.1007/s11434-011-4696-4The intensity of the winter Siberian High has significantly negative correlations with Arctic sea ice concentration anomalies from the previous autumn to winter seasons in the Eastern Arctic Ocean and Siberian marginal seas. Our results indicate that autumn- winter Arctic sea ice concentration and concurrent sea surface temperature anomalies are responsible for the winter Siberian High and surface air temperature anomalies over the mid-high latitudes of Eurasia and East Asia. Numerical experiments also support this conclusion, and consistently show that the low sea ice concentration causes negative surface air temperature anomalies over the mid-high latitudes of Eurasia. A mechanism is proposed to explain the association between autumn-winter sea ice concentration and winter Siberian High. Our results also show that September sea ice concentration provides a potential precursor for winter Siberian High that cannot be predicted using only tropical sea surface temperatures. In the last two decades (19902009), a strengthening trend of winter Siberian High along with a decline trend in surface air temperature in the mid-high latitudes of the Asian Continent have favored the recent frequent cold winters over East Asia. The reason for these short-term trends in winter Siberian High and surface air temperature are discussed.
    Wu B. Y., R. H. Zhang, R. D'Arrigo, and J. Z. Su, 2013: On the relationship between winter sea ice and summer atmospheric circulation over Eurasia.J. Climate,26,5523-5536, https://doi.org/10.1175/JCLI-D-12-00524.1.10.1175/JCLI-D-12-00524.16fe9af8baa73eb1f5fe21a8a7a354eb0http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F262007320_On_the_Relationship_between_Winter_Sea_Ice_and_Summer_Atmospheric_Circulation_over_Eurasia%3Fev%3Dprf_cithttp://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-12-00524.1Using NCEP-NCAR reanalysis and Japanese 25-yr Reanalysis (JRA-25) data, this paper investigates the association between winter sea ice concentration (SIC) in Baffin Bay southward to the eastern coast of Newfoundland, and the ensuing summer atmospheric circulation over the mid- to high latitudes of Eurasia. It is found that winter SIC anomalies are significantly correlated with the ensuing summer 500-hPa height anomalies that dynamically correspond to the Eurasian pattern of 850-hPa wind variability and significantly influence summer rainfall variability over northern Eurasia. Spring atmospheric circulation anomalies south of Newfoundland, associated with persistent winter-spring SIC and a horseshoe-like pattern of sea surface temperature (SST) anomalies in the North Atlantic, act as a bridge linking winter SIC and the ensuing summer atmospheric circulation anomalies over northern Eurasia. Indeed, this study only reveals the association based on observations and simple simulation experiments with SIC forcing. The more precise mechanism for this linkage needs to be addressed in future work using numerical simulations with SIC and SST as the external forcings. The results herein have the following implication: Winter SIC west of Greenland is a possible precursor for summer atmospheric circulation and rainfall anomalies over northern Eurasia.
    Wu B. Y., J. Z. Su, and R. D'Arrigo, 2015: Patterns of Asian winter climate variability and links to Arctic sea ice.J. Climate,28,6841-6858, https://doi.org/10.1175/JCLI-D-14-00274.1.10.1175/JCLI-D-14-00274.1f21c3c8b63a980f10e5d30bd27c73078http%3A%2F%2Fcpfd.cnki.com.cn%2FArticle%2FCPFDTOTAL-ZGQX201510004011.htmhttp://journals.ametsoc.org/doi/10.1175/JCLI-D-14-00274.1This paper describes two dominant patterns of Asian winter climate variability: the Siberian high(SH) pattern and the Asia-Arctic(AA) pattern. The former depicts atmospheric variability closely associated with the intensity of the Siberian high, and the latter characterizes the teleconnection pattern of atmospheric variability between Asia and the Arctic, which is distinct from the Arctic Oscillation(AO). The AA pattern plays more important roles in regulating winter precipitation and the 850 h Pa meridional wind component over East Asia than the SH pattern, which controls surface air temperature variability over East Asia. In the Arctic Ocean and its marginal seas, sea ice loss in both autumn and winter could bring the positive phase of the SH pattern, or cause the negative phase of the AA pattern. The latter corresponds to a weakened East Asian winter monsoon(EAWM) and enhanced winter precipitation in the mid-latitudes of the Asian continent and East Asia. For the SH pattern, sea ice loss in the prior autumn emerges in the Siberian marginal seas, and winter loss mainly occurs in the Barents Sea,Labrador Sea, and Davis Strait. For the AA pattern, sea ice loss in the prior autumn is observed in the Barents-Kara Seas, the western Laptev Sea, and the Beaufort Sea, and winter loss only occurs in some areas of the Barents Sea, the Labrador Sea, and Davis Strait. Simulation experiments with observed sea ice forcing also support that Arctic sea ice loss may favor frequent occurrence of the negative phase of the AA pattern. The results also imply that the relationship between Arctic sea ice loss and winter atmospheric variability over East Asia is unstable, which is a challenge for predicting the EAWM based on Arctic sea ice loss.
    Wu B. Y., K. Yang, and J. A. Francis, 2016: Summer Arctic dipole wind pattern affects the winter Siberian High.Int. J. Climatol.,36,4187-4201, https://doi.org/10.1002/joc.4623.10.1002/joc.462399f07c0177ca4fcfa796552260943e95http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fjoc.4623%2Fpdfhttp://doi.wiley.com/10.1002/joc.4623ABSTRACT This study investigates the relationship between the summer [June–July–August (JJA)] Arctic dipole wind pattern and the following winter [December–January–February (DJF)] Siberian High. It is found that the summer Arctic dipole wind pattern is not confined only to the Arctic region; it spans the large domain north of 20°N. The negative phase of this wind pattern depicts an anomalous anticyclone over the Arctic Ocean and its marginal seas, except for the Barents-Kara seas where an anomalous cyclone is dominant.This wind pattern is significantly correlated with the strength of the Siberian High during the following winter and with the frequency of extreme cold events over East Asia during the winters of 1979–2014. The relationship of this wind pattern with the winter Siberian High has strengthened over the past decades, particularly since the late 1980s. The more robust relationship coincides with significant changes in the winter atmospheric circulation and frequent occurrences of the negative phase of this wind pattern, which dynamically contributes to low September sea ice extent. The present study's results suggest that autumn Arctic sea ice provides a link between this wind pattern and climate variability over East Asia during the following winter.Results of simulation experiments suggest that (1) autumn sea ice loss favors the occurrence of a stronger East Asian winter monsoon; (2) the summer Arctic dipole wind pattern modulates winter atmospheric responses to sea ice loss, and the negative phase of this wind pattern enhances the negative feedback of Arctic sea ice loss on winter atmospheric variability over Eurasia and North America. These simulation experiments also imply that complex and varying summer circulation patterns obscure linkages between sea ice loss and large-scale circulation responses over Eurasia. Isolation of the summer Arctic dipole wind pattern, however, provides a potential precursor for the seasonal prediction of winter surface air temperature in a populous region of the world.
    Wu Q. G., X. D. Zhang, 2010: Observed forcing-feedback processes between Northern Hemisphere atmospheric circulation and Arctic sea ice coverage,J. Geophys. Res.,115,D14119, https://doi.org/10.1029/2009JD013574.10.1029/2009JD0135745cb701e755bfe153ab260b7fe9b6b422http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2009JD013574%2Fpdfhttp://doi.wiley.com/10.1029/2009JD013574A lagged maximum covariance analysis is applied to investigate linear covariability between monthly sea ice concentration (SIC) and atmosphere circulation in the Northern Hemisphere. The dominant signal is the atmospheric forcing of SIC anomalies throughout the year, but a wintertime atmospheric signal resembling the negatively polarized Arctic Oscillation/North Atlantic Oscillation is significantly correlated with persistently reduced SIC anomalies in the North Atlantic and Pacific sides of Arctic Shelf seas up to the preceding summer. The leading time of SIC anomalies provides an implication for skillful predictability of wintertime atmospheric variability.
    Xie P. P., P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 2539-2558, https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0,CO;2.10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2http://journals.ametsoc.org/doi/abs/10.1175/1520-0477%281997%29078%3C2539%3AGPAYMA%3E2.0.CO%3B2
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Manuscript received: 09 December 2016
Manuscript revised: 24 June 2017
Manuscript accepted: 07 July 2017
通讯作者: 陈斌, bchen63@163.com
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Precursor Role of Winter Sea-Ice in the Labrador Sea for Following-Spring Precipitation over Southeastern North America and Western Europe

  • 1. CAS Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 2. Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 3. China University of Geosciences, Wuhan 430074, China

Abstract: The role of winter sea-ice in the Labrador Sea as a precursor for precipitation anomalies over southeastern North America and Western Europe in the following spring is investigated. In general terms, as the sea ice increases, the precipitation also increases. In more detail, however, analyses indicate that both the winter sea-ice and the sea surface temperature (SST) anomalies related to increases in winter sea-ice in the Labrador Sea can persist into the following spring. These features play a forcing role in the spring atmosphere, which may be the physical mechanism behind the observational relationship between the winter sea-ice and spring precipitation anomalies. The oceanic forcings in spring include Arctic sea-ice anomalies and SST anomalies in the tropical Pacific and high-latitude North Atlantic. Multi-model Coupled Model Intercomparison Project Phase 5 and Atmospheric Model Intercomparison Project simulation results show that the atmospheric circulation response to the combination of sea-ice and SST is similar to that observed, which suggests that the oceanic forcings are indeed the physical reason for the enhanced spring precipitation. Sensitivity experiments conducted using an atmospheric general circulation model indicate that the increases in precipitation over southeastern North America are mainly attributable to the effect of the SST anomalies, while the increases over Western Europe are mainly due to the sea-ice anomalies. Although model simulations reveal that the SST anomalies play the primary role in the precipitation anomalies over southeastern North America, the observational statistical analyses indicate that the area of sea-ice in the Labrador Sea seems to be the precursor that best predicts the spring precipitation anomaly.

摘要: 当冬季拉布拉多海海冰增加时, 北美东南部和欧洲西部的春季降水会增加. 因此, 冬季拉布拉多海海冰可以作为春季降水的一个预测因子. 进一步的分析表明, 海冰异常和与之同时出现的海温异常都能够持续至春季, 并对春季大气环流产生影响, 从而导致降水异常. 这是冬季海冰和春季降水产生联系的主要原因, CMIP5的AMIP试验也证明了这一点. 在这一联系中, 海冰和海温各自起到何种作用呢?大气环流模式敏感性试验表明, 北美东南部的降水主要是由海温异常造成;欧洲西部的降水主要由海冰异常造成. 值得注意的是, 尽管模式试验表明海温异常主要造成北美东南部的降水异常, 但是冬季的拉布拉多海海冰异常是最好的统计预测因子, 因为我们无法从观测中分离出上述海温异常信号.

1. Introduction
  • Sea ice is a critical component of Earth's climate system, and its variation has been found to be significantly correlated with local and remote climate anomalies (Huang et al., 1992; Alexander et al., 2004; Magnusdottir et al., 2004; Deser et al., 2004; Conil and Li, 2005; Honda et al., 2009; Liu et al., 2012; Li and Wang, 2013; Guo et al., 2014; Mori et al., 2014). Owing to the large heat capacity of the ocean, sea ice can often persist for several months (e.g., Honda et al., 2009; Strong and Magnusdottir, 2011; Wu et al., 2013) and thus can be considered as an indicator of the subsequent climate. Many studies have investigated the role of sea ice as an indicator of winter climate (e.g. Honda et al., 2009; Wu and Zhang, 2010; Wu et al., 2011; Liu et al., 2012; Mori et al., 2014); however, there have been few studies on the role of sea ice as a precursor for spring climate.

    Figure 1.  The (a) winter mean of the monthly standard deviation of sea-ice concentration (%) and (b) normalized sea-ice area in the Labrador Sea [black box in (a)] in December, January, and February.

    Strong sea-ice variability exists in winter in the North Atlantic sector of the Arctic (Fig. 1), and the role of winter sea-ice in the Barents Sea as a precursor for spring climate has been investigated by (Strong and Magnusdottir, 2011). Meanwhile, in another region——the Labrador Sea——large quantities of sea-air heat exchange can be found (Kvamstø et al., 2004) and this may also influence spring climate. Although the spring atmospheric circulation related to the winter sea-ice anomaly in the Labrador Sea has been studied by (Wu et al., 2013), the atmospheric circulation in their study did not show classical modes of large-scale circulation. Therefore, the related spring precipitation and temperature anomalies remain poorly understood and need to be further investigated. Moreover, an observational linkage between winter sea-ice in the Labrador Sea and spring climate may be impacted by other external drivers of the atmosphere, such as the Atlantic SST tripole anomaly, which was mentioned but not investigated in (Wu et al., 2013). In the present study, we use model simulations to quantitatively investigate whether the relationship obtained from observations is contributed by both the sea-ice and SST anomalies, and examine their respective roles.

    The remainder of this paper is organized as follows: Following this introduction, in section 2 we describe the observational datasets, methodologies and models used. Section 3 investigates, from observational data, the nature of the spring precipitation anomalies that follow winter sea-ice anomalies in the Labrador Sea. In section 4, the possible physical mechanism responsible for their connection is investigated, and then the findings are verified in section 5 via atmospheric general circulation model results. A summary and discussion are provided in section 6.

2. Datasets and methods
  • This study uses monthly sea-ice concentration (SIC) and SST datasets from the Hadley Center, Meteorological Office, United Kingdom (Rayner et al., 2003), as well as an additional SIC dataset from the National Snow and Ice Data Center (NSIDC; Cavalieri et al., 1996). The two precipitation datasets used are from the Climate Prediction Center Merged Analysis of Precipitation (CMAP; Xie and Arkin, 1997) and the Global Precipitation Climatology Center (GPCC; Schneider et al., 2011). The monthly surface air temperature (SAT), sea level pressure (SLP), 500-hPa geopotential height (Z500), and surface heat flux (sensible and latent heat flux, shortwave, and longwave radiation flux), as well as daily Z500 datasets, are from the European Center for Medium-Range Weather Forecasts interim reanalysis (Dee et al., 2011). We select the period from 1979 to 2013 for our analyses, because of the better quality of sea-ice data since 1979. Since the present study focuses on the interannual timescale, we apply a detrending process prior to performing all the analyses. In this paper, "winter" refers to the months of December through February and "spring" is the months from March through May. The Niño3.4 index is defined as the monthly average SST anomaly in the Niño3.4 region (5°S-5°N, 170°-120°W), which is used to represent the El Niño-Southern Oscillation (ENSO).

    The atmospheric general circulation model (AGCM) used in this study is ECHAM5 (Roeckner et al., 2003; 2006). The horizontal and vertical resolution used here are the same as in (Han et al., 2016b), and we conduct four sets of experiments:

    (1) In the control experiment (CTRL_Exp), the AGCM is driven by the mean monthly sea-ice and SST climatology for the period 1979-2010.

    (2) In the sea-ice and SST experiment (SST_SIC_Exp), the AGCM is driven by perturbed sea-ice and SST. The perturbed sea-ice is the sum of the monthly sea-ice climatology and sea-ice anomalies in the Arctic, which is double the regression against winter sea-ice area in the Labrador Sea. The perturbed SST is the sum of the monthly SST climatology and SST anomalies in the tropical Pacific and high-latitude North Atlantic, which is double the regression against Lab-SIA.

    (3) In the sea-ice experiment (SIC_Exp), the procedure is the same as that for SST_SIC_Exp, but only the sea ice is perturbed.

    (4) In the SST experiment (SST_Exp), the procedure is again the same as for SST_SIC_Exp, but only the SST is perturbed.

    There are 80 ensemble members with different initial conditions in each experiment. The monthly outputs from March to May are used for our analyses. The anomalies used in the experiments are doubled to obtain significant atmospheric responses. The stronger the oceanic forcing, the more significant the response will be. Oceanic forcing doubling has also been used in many previous studies (e.g. Magnusdottir et al., 2004; Han et al., 2016b). Moreover, winters with two-standard-deviation sea-ice anomalies also exist in the observations (Fig. 1b).

3. Precursor role of winter sea-ice for spring precipitation
  • To analyze the precursor role of winter sea-ice anomalies in the Labrador Sea, an index (Fig. 1b) is defined as the sea-ice area in the domain (50°-80°N, 45°-75°W)——black box in Fig. 1a, and referred to as Lab-SIA. The region selected here differs somewhat from that in (Wu et al., 2013), and the correlation coefficient between the indexes defined in these two different regions is 0.88. The lag autocorrelation of the index shows that it has a long timescale, with a coefficient of 0.48 at a lag of three months (i.e., spring versus winter). Figure S1 shows the correlation coefficients between spring SAT anomalies and Lab-SIA in the previous winter. There are no significant anomalies over land. Moreover, the correlation coefficients are very small, with values between -0.1 and 0.1. Figures 2a and b show the correlation between the CMAP precipitation in spring and the winter Lab-SIA index defined by the Hadley and NSIDC sea-ice datasets. As winter sea-ice increases in the Labrador Sea, there are significant increases in precipitation over southeastern North America and Western Europe. Given the insignificant SAT anomaly, we focus on the spring precipitation anomalies and the possible mechanism behind this linkage.

    Figure 2.  Regressions of (a) CMAP and (b) GPCC precipitation in spring against previous-winter Lab-SIA, and the winter mean of the monthly standard deviation of precipitation obtained from the (c) CMAP and (d) GPCC datasets.

    When the Lab-SIA increases by one standard deviation, the precipitation anomaly reaches a maximum of about 14mm every month in southeastern North America (Fig. 3a), which is about 27% of one standard deviation of precipitation (Fig. 3c), and a maximum of 16 mm every month in Western Europe (Fig. 3a), which is about 32% of one standard deviation of precipitation (Fig. 3c). The precipitation anomalies explained by Lab-SIA do not seem to be very large. However, there are several years when the Lab-SIA is about 2 (or -2) times the standard deviation (Fig. 1b), and the precipitation anomalies explained by the Lab-SIA can exceed half of one standard deviation. Similar results are obtained using the GPCC precipitation dataset (Figs. 3b and d). In addition, there are significant precipitation anomalies in several other regions of the mainland, but these are not investigated any further because the regressions are very small.

    Figure 3.  Correlation coefficients of CMAP precipitation in spring with the Lab-SIA in the previous winter, based on data from (a) the Hadley Center and (b) NSIDC. The green lines indicate statistical significance at the 95% confidence level.

    Figure 4.  As in Fig. 2, but for (a, b) SLP, (c, d) Z500 and (e, f) storm track, defined as the variance of bandpass-filtered Z500. The black contours indicate statistical significance at the 95% confidence level.

    To further understand the linkage between the winter sea-ice in the Labrador Sea and the spring precipitation over southeastern North America and Western Europe, the spring atmospheric circulation anomalies related to the Labrador Sea's ice in winter are investigated. Figure 4 shows the atmospheric circulation anomalies associated with an increase in winter sea-ice in the Labrador Sea. Significant SLP anomalies exist mainly over the oceans, with positive anomalies over the western Pacific and the oceans west of Greenland, and negative anomalies over the southeastern subtropical Pacific (Fig. 4a). This may be the main reason why there are no significant SAT anomalies over land. In the middle troposphere (Fig. 4c), negative height anomalies exist over southern North America, and positive height anomalies exist over northern North America and the northern North Atlantic. This circulation pattern benefits the increase in precipitation over southeastern North America, as it can bring warm and moist air from the ocean. In addition, anomalies from the North Pacific to North America are similar to the Pacific-North America teleconnection pattern. Over Western Europe and the adjoining Atlantic, there are negative height anomalies, which could bring moist air from the ocean to southeastern Europe and favor an increase in precipitation. The relationship between the associated atmospheric circulation and the Lab-SIA defined by the NSIDC dataset (Figs. 4b and d) is consistent with that indicated above. This means that the connection between the atmospheric circulation anomalies and the sea-ice anomalies in the Labrador Sea is reliable. The atmospheric circulation anomalies are basically consistent with those in (Wu et al., 2013), with only slight differences between them that may be related to the different domains used for the Lab-SIA index, as well as the use of a monthly rather than seasonal mean. Some studies have suggested that the precipitation anomalies in the midlatitudes are strongly impacted by storms (e.g. Hawcroft et al., 2012). Figures 5e and f show the storm track related to the sea-ice area in the Labrador Sea, which is defined as the variance of synoptic Z500 with periodicity of 2-8 days using a Lanczos filter with 21 weights (Duchon, 1979). As we can see, the storm track becomes strengthened in Western Europe and adjoining regions, and in southern North America, where the precipitation anomalies are, which means the storm track may play an important role in determining the precipitation anomalies.

4. Possible physical mechanism behind the observational relationship
  • As the boundary of the atmosphere, the ocean has a large heat capacity and sea ice may persist for several months and continuously drive the atmosphere. Thus, the persistence of the ocean thermal state may be the reason for the close observational connection indicated in section 3. First, the sea-ice and SST anomalies associated with winter sea-ice are investigated. The reason for studying the SST is that there are significant atmospheric anomalies in spring over the tropical oceans (Fig. 4a), which may be caused by the SST anomalies. Because there are both sea-ice and SST anomalies, the question naturally arises as to whether winter sea-ice is more suitable than SST as an observational precursor for the precipitation anomalies of the following spring (subsection 4.1). After that, we investigate the possible forcing effects of both sea-ice and SST anomalies on the atmosphere during spring (subsection 4.2).

  • In winter, the sea ice decreases in the Greenland and Barents (G-B) seas (Fig. 5a), along with an increase in sea ice in the Labrador Sea. In the remote open oceans, there are significant SST anomalies in the North Atlantic and tropical Pacific. In the North Atlantic, the SST anomalies show a tripole pattern in winter, which is similar to that reported in (Wu et al., 2013). The physical mechanism behind the relationship between sea ice and SST in winter is not investigated because it is beyond the scope of the present study.

    Given that there are significant SST anomalies in the remote oceans, it is necessary to identify whether it is the sea ice in the Labrador Sea or the SST in the open oceans that is the better statistical precursor for the following-spring precipitation anomalies. First, the spring precipitation anomalies associated with the North Atlantic SST tripole are largely different from those associated with Lab-SIA (cf. Fig. S2 and Fig. 2). This means that the role played by North Atlantic SST anomalies in the linkage between winter Labrador Sea sea-ice and spring precipitation is weak. Second, the first three modes of the tropical Pacific SST anomalies are not the same as those related to winter Lab-SIA (cf. Fig. S3 and Fig. 5b). The first mode mainly reflects a traditional El Niño-Southern Oscillation (ENSO) event, and the correlation coefficient between ENSO and the Lab-SIA is only 0.15, which is below the 90% significance level. The correlation coefficient between the second mode and Lab-SIA is 0.12, which is also below the 90% significance level. The third mode is insignificant because it cannot be separated from the fourth mode. This means that the winter Labrador Sea sea-ice anomaly, rather than the SST anomaly, is a better index for predicting spring anomalies in southeastern North America and Western Europe.

    Figure 5.  Correlation coefficients of (a, c) SIC and (b, d) SST with winter Lab-SIA: (a, b) winter; (c, d) following spring. Panels (e, f) are the same as (c, d), but for the regression. The blue boxes are used to mark the regions where the SST anomalies are used in the model experiments. The black contours indicate statistical significance at the 95% confidence level.

  • In spring, there are significant sea-ice and SST anomalies that persist from the previous winter (cf. Figs. 5a, b and c, d), and this persistence may be caused by the large heat content of the ocean. If these persistent features are the drivers of the atmospheric anomalies in spring, the linkage between the winter sea-ice and spring precipitation may be easy to understand. This aspect is investigated next. As a general speculation regarding the large-scale air-sea interaction, if the ocean does influence the atmosphere, there should be heat transfer from the ocean (atmosphere) to the atmosphere (ocean) where sea ice decreases (increases) or where SST is warmer (colder) than normal. Figure 6b shows that there is heat absorption in the Labrador Sea and the adjoining open oceans (blue box in Fig. 6b), and heat release in the G-B seas and the adjoining open oceans (red box in Fig. 6b). The consistent surface heat flux anomalies in the sea-ice region and the adjoining open oceans in spring differ from those in winter. This suggests that the overlying atmospheric conditions may be primarily driven by the sea ice, because the surface heat flux is opposite between the sea-ice region and the adjoining oceans when the sea-ice is forced by the atmosphere (e.g., Deser et al., 2000, Han et al., 2016a). Therefore, the sea-ice anomaly in winter is forced by the simultaneous atmosphere; when it persists into the ensuing spring, it seems to be the driver of the atmosphere.

    Figure 6.  As in Figs. 5a and c, but for surface heat fluxes. The blue and red rectangles contain the ocean covered by sea ice and the adjoining open ocean.

    With respect to the extratropical SST anomalies in the North Atlantic, a cold anomaly at high latitudes can influence the atmosphere by absorbing heat from it, while a warm anomaly at midlatitudes seems to be forced by the atmosphere because warmer SSTs are related to heat absorption (cf. Figs. 5d and 6b). These results indicate that the role played by North Atlantic SST anomalies in the linkage between winter sea-ice and spring atmospheric conditions is weak, which is consistent with the results reported by (Frankignoul et al., 2014). In the tropical Pacific, there is heat release (more precipitation) in the western region and heat absorption (less precipitation) in the eastern region (not shown), which corresponds to warmer and cooler SSTs, respectively. This means that the tropical SST anomalies are forcing factors with respect to the atmosphere. Further proof of the forcing role played by the Pacific SST is provided by the SLP anomaly, which is above normal over regions with colder SSTs and below normal over regions with warmer SSTs (cf. Figs. 4a and 5d). Such atmospheric circulation anomalies are consistent with the direct thermal response of the atmosphere to tropical SST anomalies. Therefore, the possible oceanic forcings in spring include the sea-ice anomalies in the Labrador and G-B seas, an SST anomaly over the North Pole of the North Atlantic, and SST anomalies in the tropical Pacific.

    The results of the analyses carried out in section 4 indicate that both sea ice and SST might play roles in determining the atmospheric conditions during spring, and the winter Lab-SIA is a better observational precursor of spring precipitation than SST in the open oceans. However, the above analyses cannot clarify whether the spring atmospheric anomalies are really caused by collaborative roles of the sea-ice and SST anomalies. Atmospheric model simulations are a useful tool for solving such issues, which is discussed in the next section.

5. Roles of sea ice and SST revealed by model simulations
  • The Coupled Model Intercomparison Project Phase 5 (CMIP5) and Atmospheric Model Intercomparison Project (AMIP) experiments support many available datasets in analyzing the atmospheric response to oceanic forcings. Although the oceanic forcings in the CMIP5 and AMIP experiments include the warm SST anomalies in the midlatitude North Atlantic (Fig. 5f), which is not a driver of the atmosphere, the simulated results should be qualitatively consistent with those forced by the oceanic anomalies excluding the warm SST anomaly, since its area is so much smaller than that of the other forcings. Figure 7 shows the response of the spring Z500 anomalies to the oceanic forcings (Figs. 5e and f), from which it can be seen that the response is very similar to that regressed on the Lab-SIA index (cf. Figs. 7a and b). Also, the correlation coefficient between the observations and the model simulation is 0.72 over the region from the central Pacific to Western Europe (0°-80°N, 180°-0°E).

    Figure 7.  Regressions of Z500 in spring against the Lab-SIA index in the previous winter for the multi-model ensemble means of (a) CMIP5 and AMIP and (b) ERA-Interim. The black contours in (a) indicate statistical significance at the 95% confidence level.

    Figure 8.  Atmospheric responses to the combined sea-ice and SST anomalies (difference between SST_SIC_Exp and CTRL_Exp) for (a) precipitation and (b) Z500. The black contours indicate statistical significance at the 95% confidence level.

    Figure 9.  As in Fig. 8, but for the response to (a, c) sea-ice and (b, d) SST anomalies.

    As the oceanic forcings include both sea-ice anomalies in the Arctic and SST anomalies in the remote open oceans, the role of each forcing cannot be identified by observational analyses and the CMIP5 and AMIP experiments. To investigate this issue, we use an AGCM model, ECHAM5, to carry out sensitivity experiments. We first evaluate the atmospheric response to the combined sea-ice (Fig. 5e) and SST anomalies (blue box in Fig. 5f), and compare them with the observational results. Figure 8a shows the precipitation response to the combined sea-ice and SST anomalies, which is above normal in southern North America and Western Europe, and is consistent with the observational regression (Fig. 3a). Figure 8b is the Z500 response, which also resembles the observational regression (Fig. 7b), with a correlation coefficient of 0.65 over the domain (0°-80°N, 180°-0°E). Besides the spatial similarity, the amplitude of the response is also comparable to the observational regression. For example, the maximum Z500 response over the midlatitude North Pacific is about twice that of the regression, because the amplitude of the oceanic forcings driving the AGCM doubles that of the regression. Consistency between the simulation and observational regression means that the model simulation is reliable.

    Figure 9a shows the precipitation response to the sea-ice anomalies in the Labrador and G-B seas. Precipitation increases significantly over Western Europe, but is insignificant over North America. Figure 9c shows the Z500 response; a negative height response over Western Europe and the adjoining Atlantic benefits the transfer of moist air from the subtropical Atlantic, and results in a significant increase in precipitation (Fig. 9a). Meanwhile, the center of the negative height response over southern North America is eastwards relative to observations, as well as the response to the combined sea-ice and SST anomalies. This means that moist air cannot be transferred from the subtropical ocean to southern North America, and so the positive precipitation anomaly in that region is insignificant. The differences in the center of the negative height response between the model simulation and observation were also seen in (Wu et al., 2013), but they did not indicate this can lead to different precipitation anomalies or what causes the inconsistency. The following investigation shows that the SST anomalies are responsible for the differences (Fig. 9d). Figure 9b shows the precipitation response to the SST anomalies in the tropical Pacific and high-latitude North Atlantic, which is above normal in southern North America, and indicates that the observed precipitation anomalies in southern North America that are linked to the increase in sea-ice in the Labrador Sea are mainly caused by the SST anomalies. The precipitation response over Western Europe is much weaker than that caused by the sea-ice anomalies. The Z500 response indicates that the positive precipitation in southern North America is related to the moist air transfer from the subtropical ocean (Fig. 9d), which is consistent with observations. The center of the negative Z500 response over the eastern North Atlantic is shifted westwards relative to the observations, and this is the reason for the weak precipitation response in Western Europe relative to the observations.

6. Summary and discussion
  • In this study, we investigate the role played by the winter sea-ice in in the Labrador Sea ice as a precursor for following-spring precipitation, and analyze the possible underlying physical mechanism. The SAT anomalies are not discussed, as there are almost no significant anomalies over land. Consistent with this, there are almost no significant SLP anomalies over land too. Observational analyses indicate that there are increased precipitation anomalies in southeastern North America and Western Europe as the sea ice in the Labrador Sea increases. Correspondingly, the atmospheric circulation shows a negative height anomaly over southern North America, which supports the transfer of warm and moist air from the subtropical ocean. The increased precipitation over Western Europe is associated with the negative height anomalies there and in the adjoining North Atlantic, which facilitates the transport of warm and moist air from the subtropical North Atlantic. Moreover, the storm activity strengthens over the regions with precipitation anomalies, and this may have an important impact on the precipitation anomalies.

    Next, we investigate the possible physical mechanism behind this relationship. Along with the increased winter sea-ice in the Labrador Sea, there is decreased sea-ice in the G-B seas, and the SST anomaly shows a tripole pattern in the North Atlantic and a dipole pattern in the tropical Pacific, with colder SSTs in the western region and warmer SSTs in the eastern region. The oceanic anomalies, except for the tropical SST anomaly in the North Atlantic, persist into the following spring. By analyzing the surface heat fluxes and SLP, we identify the oceanic forcings in spring, which contain both the sea-ice and SST anomalies mentioned above, except for the positive SST anomaly in the midlatitude North Atlantic. This also indicates that the role played by the North Atlantic SST is relatively weak for the spring climate, which is consistent with the findings of (Frankignoul et al., 2014). Although the role played by sea ice and SST as a forcing is identified, whether the atmospheric circulation is really caused by oceanic forcing must be studied further.

    Multi-model CMIP5 and AMIP simulations suggest that oceanic forcing is indeed the reason for the atmospheric circulation anomalies. Furthermore, we carry out sensitivity experiments using ECHAM5 to investigate the relative roles played by the sea-ice and SST anomalies. Their combined role is consistent with observational analyses, indicating the reliability of this model simulation. The results show that sea-ice anomalies play a strong role in the increased precipitation in Western Europe, but only a relative weak role in the precipitation anomalies in southern North America. The atmospheric circulation response resembles that indicated in (Wu et al., 2013). It should be noted that, because the sea-ice forcings in this experiment contain sea-ice anomalies in the Labrador and G-B seas, the experiment cannot determine which region plays the most important role in the increased precipitation in Western Europe. Different from the sea-ice anomalies, the SST anomalies play a dominant role in the increased precipitation over southern North America, but a relatively weak role in the precipitation anomalies over Western Europe. This indicates that the sea-ice and SST anomalies play independent and dominant roles in the increased spring precipitation in the two regions. This work also explains the reason for the shift in Z500 over southeastern North Atlantic between the observation and the atmospheric response in (Wu et al., 2013), which are the SST anomalies responsible for this shift. Most of Western Europe experienced severe drought in spring 2011, which resulted in fire risk in some regions (WMO, 2012). The south-central United States was also extremely dry for the whole of 2011 (WMO 2012). In winter 2010/11, there was a strong La Niña event, but the significant effects of ENSO cannot explain the extreme drought in the south-central United States and Western Europe (Fig. S4). The results of this study suggest that the extreme drought in the southern United States and Western Europe in spring 2011 may to a certain extent have been predictable from the sea-ice and SST anomalies related to winter sea-ice in the Labrador Sea.

    It should be noted that the sea ice in the Labrador Sea is a better observational precursor for spring climate relative to SST anomalies (i.e., in terms of the statistical relationship). Although model simulations indicate that the role played by SST anomalies in the tropical Pacific is apparently more important than that of sea ice, the observational analyses suggest that the SST anomalies cannot be defined as a precursor because there is no significant mode of tropical Pacific SST that shows a similar spatial pattern with that related to the Labrador Sea sea-ice. In other words, if we establish an empirical model to predict the spring precipitation anomaly, the sea-ice area in the Labrador Sea is the better precursor.

    Recently, many studies have indicated that uncertainties exist in the linkage between Arctic sea-ice and large-scale circulation anomalies (Walsh, 2014; Overland et al., 2015; Wu et al., 2015; Wu et al., 2016). For the linkage indicated here, the sea ice in the Labrador Sea is not the only driver of the atmosphere. Therefore, if the relationship between it and other drivers, such as the SST anomaly, changes, its role as a precursor for spring precipitation will also change. This indicates that the relationships among the Labrador Sea sea-ice anomaly and remote sea-ice and SST anomalies should be further investigated and, in doing so, it should be possible to reduce the level of uncertainty involved in the connection.

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