scholarly journals Forcing of the Arctic Oscillation by Eurasian Snow Cover

2011 ◽  
Vol 24 (24) ◽  
pp. 6528-6539 ◽  
Author(s):  
Robert J. Allen ◽  
Charles S. Zender
Keyword(s):  
Twentieth Century ◽  
Snow Cover ◽  
General Circulation ◽  
Arctic Oscillation ◽  
General Circulation Models ◽  
The Arctic ◽  
Positive Trend ◽  
Eurasian Snow Cover ◽  
Eurasian Snow ◽  
The Arctic Oscillation

Abstract Throughout much of the latter half of the twentieth century, the dominant mode of Northern Hemisphere (NH) extratropical wintertime circulation variability—the Arctic Oscillation (AO)—exhibited a positive trend, with decreasing high-latitude sea level pressure (SLP) and increasing midlatitude SLP. General circulation models (GCMs) show that this trend is related to several factors, including North Atlantic SSTs, greenhouse gas/ozone-induced stratospheric cooling, and warming of the Indo-Pacific warm pool. Over the last approximately two decades, however, the AO has been decreasing, with 2009/10 featuring the most negative AO since 1900. Observational and idealized modeling studies suggest that snow cover, particularly over Eurasia, may be important. An observed snow–AO mechanism also exists, involving the vertical propagation of a Rossby wave train into the stratosphere, which induces a negative AO response that couples to the troposphere. Similar to other GCMs, the authors show that transient simulations with the Community Atmosphere Model, version 3 (CAM3) yield a snow–AO relationship inconsistent with observations and dissimilar AO trends. However, Eurasian snow cover and its interannual variability are significantly underestimated. When the albedo effects of snow cover are prescribed in CAM3 (CAM PS) using satellite-based snow cover fraction data, a snow–AO relationship similar to observations develops. Furthermore, the late-twentieth-century increase in the AO, and particularly the recent decrease, is reproduced by CAM PS. The authors therefore conclude that snow cover has helped force the observed AO trends and that it may play an important role in future AO trends.

scholarly journals On the role of Eurasian autumn snow cover in dynamical seasonal predictions 

2021 ◽  
Author(s):  
Paolo Ruggieri ◽  
Marianna Benassi ◽  
Stefano Materia ◽  
Daniele Peano ◽  
Constantin Ardilouze ◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Land Surface ◽  
General Circulation ◽  
Dominant Role ◽  
General Circulation Models ◽  
The Arctic ◽  
Seasonal Forecasts ◽  
Eurasian Snow

<p>Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.</p>

scholarly journals Effect Of Eurasian Snow Cover On Summer Climate Of The Northern Hemisphere: A GCM Study

1990 ◽  
Vol 14 ◽  
pp. 364 ◽  
Author(s):  
Tetsuzo Yasunari ◽  
Akio Kitoh ◽  
Tatsushi Tokioka
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Late Winter ◽  
Hydrological Process ◽  
Eurasian Snow Cover ◽  
Eurasian Snow ◽  
Snow Cover Extent

Observational studies have shown that Eurasian snow-cover anomalies during winter-through-spring seasons have a great effect on anomalies in atmospheric circulation and climate in the following summer season through snow albedo feedback (Hahn and Shukla, 1976; Dey and Bhanu Kumar, 1987). Morinaga and Yasunari (1987) have revealed that large-scale snow-cover extent over central Asia in late winter, which particularly has a great effect on the circulation over Eurasia in the following season, is closely related to the Eurasian pattern circulation (Wallace and Gutzler, 1981) in the beginning of winter. Some atmospheric general circulation models (GCM) have suggested that not only the albedo effect of the snow cover but also the snow-hydrological process are important in producing the atmospheric anomalies in the following seasons (Yeh and others, 1984; Barnett and others, 1988). However, more quantitative evaluations of these effects have not yet been examined. For example, it is not clear to what extent atmospheric anomalies are explained solely by snow-cover anomalies. Spatial and seasonal dependencies of these effects are supposed to be very large. Relative importance of snow cover over Tibetan Plateau should also be examined, particularly relevant to Asian summer monsoon anomalies. Moreover, these effects seem to be very sensitive to parameterizations of these physical processes (Yamazaki, 1988). This study focuses on these problems by using some versions of GCMs of the Meteorological Research Institute. The results include the evaluation of total snow-cover feedbacks as part of internal dynamics of climatic change from 12-year GCM integration, and of the effect of anomalous snow cover over Eurasia in late winter on land surface conditions and atmospheric circulations in the succeeding seasons.

scholarly journals Effect Of Eurasian Snow Cover On Summer Climate Of The Northern Hemisphere: A GCM Study

1990 ◽  
Vol 14 ◽  
pp. 364-364 ◽  
Author(s):  
Tetsuzo Yasunari ◽  
Akio Kitoh ◽  
Tatsushi Tokioka
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Late Winter ◽  
Hydrological Process ◽  
Eurasian Snow Cover ◽  
Eurasian Snow ◽  
Snow Cover Extent

Observational studies have shown that Eurasian snow-cover anomalies during winter-through-spring seasons have a great effect on anomalies in atmospheric circulation and climate in the following summer season through snow albedo feedback (Hahn and Shukla, 1976; Dey and Bhanu Kumar, 1987). Morinaga and Yasunari (1987) have revealed that large-scale snow-cover extent over central Asia in late winter, which particularly has a great effect on the circulation over Eurasia in the following season, is closely related to the Eurasian pattern circulation (Wallace and Gutzler, 1981) in the beginning of winter.Some atmospheric general circulation models (GCM) have suggested that not only the albedo effect of the snow cover but also the snow-hydrological process are important in producing the atmospheric anomalies in the following seasons (Yeh and others, 1984; Barnett and others, 1988).However, more quantitative evaluations of these effects have not yet been examined. For example, it is not clear to what extent atmospheric anomalies are explained solely by snow-cover anomalies. Spatial and seasonal dependencies of these effects are supposed to be very large. Relative importance of snow cover over Tibetan Plateau should also be examined, particularly relevant to Asian summer monsoon anomalies. Moreover, these effects seem to be very sensitive to parameterizations of these physical processes (Yamazaki, 1988).This study focuses on these problems by using some versions of GCMs of the Meteorological Research Institute. The results include the evaluation of total snow-cover feedbacks as part of internal dynamics of climatic change from 12-year GCM integration, and of the effect of anomalous snow cover over Eurasia in late winter on land surface conditions and atmospheric circulations in the succeeding seasons.

scholarly journals Snowfall distribution and its response to the Arctic Oscillation: An evaluation of HighResMIP models in the Arctic using CPR/CloudSat observations

2019 ◽  
Author(s):  
Manu Anna Thomas ◽  
Abhay Devasthale ◽  
Tristan L'Ecuyer ◽  
Shiyu Wang ◽  
Torben Koenigk ◽  
...  
Keyword(s):  
General Circulation ◽  
Arctic Oscillation ◽  
Climate Models ◽  
General Circulation Models ◽  
Specific Pattern ◽  
Radiation Budget ◽  
The Arctic ◽  
Northern Latitudes ◽  
Realistic Representation ◽  
The Arctic Oscillation

Abstract. A realistic representation of snowfall in the general circulation models (GCM) is important to accurately simulate snow cover, surface albedo, high latitude precipitation and thus the radiation budget. Hence, in this study, we evaluate snowfall in a range of climate models run at two different resolutions using the latest estimates of snowfall from CloudSat Cloud Profiling Radar over the northern latitudes. We also evaluate if the finer resolution versions of the GCMs simulate the accumulated snowfall better than their coarse resolution counterparts. As the Arctic Oscillation (AO) is the prominent mode of natural variability in the polar latitudes, the snowfall variability associated with the different phases of the AO is examined in both models and in our observational reference. We report that the statistical distributions of snowfall vary considerably between the models and CloudSat observations. While CloudSat shows an exponential distribution of snowfall, the models show a Gaussian distribution that is heavily positively skewed. As a result, the 10 and 50 percentiles, representing the light and median snowfall, are overestimated by a factor of 3 and 1.5 respectively in the models investigated here. The overestimations are strongest during the winter months compared to autumn and spring. The extreme snowfall represented by the 90 percentiles, on the other hand, is positively skewed underestimating the snowfall estimates by a factor of 2 in the models in winter compared to the CloudSat estimates. Though some regional improvements can be seen with increased spatial resolution within a particular model, it is not easy to identify a specific pattern that hold across all models. The characteristic snowfall variability associated with the positive phase of AO over Greenland Sea and central Eurasian Arctic is well captured by the models.

scholarly journals Snowfall distribution and its response to the Arctic Oscillation: an evaluation of HighResMIP models in the Arctic using CPR/CloudSat observations

2019 ◽  
Vol 12 (8) ◽  
pp. 3759-3772 ◽  
Author(s):  
Manu Anna Thomas ◽  
Abhay Devasthale ◽  
Tristan L'Ecuyer ◽  
Shiyu Wang ◽  
Torben Koenigk ◽  
...  
Keyword(s):  
General Circulation ◽  
Arctic Oscillation ◽  
Climate Models ◽  
Global Climate ◽  
General Circulation Models ◽  
Specific Pattern ◽  
Surface Radiation ◽  
Radiation Budget ◽  
The Arctic ◽  
The Arctic Oscillation

Abstract. A realistic representation of snowfall in general circulation models (GCMs) of global climate is important to accurately simulate snow cover, surface albedo, high-latitude precipitation and thus the surface radiation budget. Hence, in this study, we evaluate snowfall in a range of climate models run at two different resolutions by comparing to the latest estimates of snowfall from the CloudSat Cloud Profiling Radar over the northern latitudes. We also evaluate whether the finer-resolution versions of the GCMs simulate the accumulated snowfall better than their coarse-resolution counterparts. As the Arctic Oscillation (AO) is the prominent mode of natural variability in the polar latitudes, the snowfall variability associated with the different phases of the AO is examined in both models and in our observational reference. We report that the statistical distributions of snowfall differ considerably between the models and CloudSat observations. While CloudSat shows an exponential distribution of snowfall, the models show a Gaussian distribution that is heavily positively skewed. As a result, the 10th and 50th percentiles, representing the light and median snowfall, are overestimated by up to factors of 3 and 1.5, respectively, in the models investigated here. The overestimations are strongest during the winter months compared to autumn and spring. The extreme snowfall represented by the 90th percentiles, on the other hand, is positively skewed, underestimating the snowfall estimates by up to a factor of 2 in the models in winter compared to the CloudSat estimates. Though some regional improvements can be seen with increased spatial resolution within a particular model, it is not easy to identify a specific pattern that holds across all models. The characteristic snowfall variability associated with the positive phase of AO over Greenland Sea and central Eurasian Arctic is well captured by the models.

scholarly journals Observed Influences of Autumn–Early Winter Eurasian Snow Cover Anomalies on the Hemispheric PNA-like Variability in Winter

2011 ◽  
Vol 24 (7) ◽  
pp. 2017-2023 ◽  
Author(s):  
Qigang Wu ◽  
Haibo Hu ◽  
Lujun Zhang
Keyword(s):  
Snow Cover ◽  
Reanalysis Data ◽  
The Arctic ◽  
Early Winter ◽  
Eurasian Snow Cover ◽  
Maximum Covariance Analysis ◽  
Eurasian Snow ◽  
Snow Cover Extent ◽  
The Arctic Oscillation ◽  
The Impact

Abstract The impact of the Eurasian snow cover extent on the Northern Hemisphere (NH) circulation is investigated by applying a lagged maximum covariance analysis (MCA) to monthly satellite-derived snow cover and NCEP reanalysis data. Wintertime atmospheric signals significantly correlated with persistently autumn–early winter snow cover anomalies are found in the leading two MCA modes. The first MCA mode indicates the effect of Eurasian snow cover anomalies on the Arctic Oscillation/North Atlantic Oscillation (AO/NAO). The second MCA mode corresponds with the forcing of Eurasian snow cover anomalies on the hemispheric Pacific–North America (PNA)-like atmospheric variations. This snow–atmosphere relationship may present a significant potential for wintertime predictability.

scholarly journals A Numerical Sensitivity Study of the Influence of Siberian Snow on the Northern Annular Mode

2012 ◽  
Vol 25 (2) ◽  
pp. 592-607 ◽  
Author(s):  
Y. Peings ◽  
D. Saint-Martin ◽  
H. Douville
Keyword(s):  
General Circulation ◽  
Arctic Oscillation ◽  
Polar Vortex ◽  
Circulation Model ◽  
Sensitivity Study ◽  
The Arctic ◽  
Annular Mode ◽  
Northern Annular Mode ◽  
Model Free ◽  
The Arctic Oscillation

Abstract The climate version of the general circulation model Action de Recherche Petite Echelle Grande Echelle (ARPEGE-Climat) is used to explore the relationship between the autumn Siberian snow and the subsequent winter northern annular mode by imposing snow anomalies over Siberia. As the model presents some biases in the representation of the polar vortex, a nudging methodology is used to obtain a more realistic but still interactive extratropical stratosphere in the model. Free and nudged sensitivity experiments are compared to discuss the dependence of the results on the northern stratosphere climatology. For each experiment, a positive snow mass anomaly imposed from October to March over Siberia leads to significant impacts on the winter atmospheric circulation in the extratropics. In line with previous studies, the model response resembles the negative phase of the Arctic Oscillation. The well-documented stratospheric pathway between snow and the Arctic Oscillation operates in the nudged experiment, while a more zonal propagation of the signal is found in the free experiment. Thus, the study provides two main findings: it supports the influence of Siberian snow on the winter extratropical circulation and highlights the importance of the northern stratosphere representation in the models to capture this teleconnection. These findings could have important implications for seasonal forecasting, as most of the operational models present biases similar to those of the ARPEGE-Climat model.

A Predictability Measure Applied to Seasonal Predictions of the Arctic Oscillation

2007 ◽  
Vol 20 (18) ◽  
pp. 4733-4750 ◽  
Author(s):  
Youmin Tang ◽  
Hai Lin ◽  
Jacques Derome ◽  
Michael K. Tippett
Keyword(s):  
Confidence Level ◽  
General Circulation ◽  
Arctic Oscillation ◽  
A Priori ◽  
Circulation Model ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Central Pacific ◽  
The Arctic Oscillation ◽  
Sst Anomalies

Abstract In this study, ensemble seasonal predictions of the Arctic Oscillation (AO) were conducted for 51 winters (1948–98) using a simple global atmospheric general circulation model. A means of estimating a priori the predictive skill of the AO ensemble predictions was developed based on the relative entropy (R) of information theory, which is a measure of the difference between the forecast and climatology probability density functions (PDFs). Several important issues related to the AO predictability, such as the dominant precursors of forecast skill and the degree of confidence that can be placed in an individual forecast, were addressed. It was found that R is a useful measure of the confidence that can be placed on dynamical predictions of the AO. When R is large, the prediction is likely to have a high confidence level whereas when R is small, the prediction skill is more variable. A small R is often accompanied by a relatively weak AO index. The value of R is dominated by the predicted ensemble mean. The relationship identified here, between model skills and the R of an ensemble prediction, offers a practical means of estimating the confidence level of a seasonal forecast of the AO using the dynamical model. Through an analysis of the global sea surface temperature (SST) forcing, it was found that the winter AO-related R is correlated significantly with the amplitude of the SST anomalies over the tropical central Pacific and the North Pacific during the previous October. A large value of R is usually associated with strong SST anomalies in the two regions, whereas a poor prediction with a small R indicates that SST anomalies are likely weak in these two regions and the observed AO anomaly in the specific winter is likely caused by atmospheric internal dynamics.

Sign in / Sign up

Export Citation Format

Share Document