Strengthened Impacts of November Snow Cover Over Siberia on the Out-of-phase Change in the Siberian High Between December and January Since 2000 and Implication for Intraseasonal Climate Prediction

This study investigates the out-of-phase change in the Siberian High (SH) between December and January (stronger than normal in December and weaker than normal in January, and vice versa). The results show that the monthly reversal frequency of the SH between December and January increases significantly after 2000 from 30% (1981–2000) to 63% (2001-2019). Correspondingly, the influence of November snow cover over Siberia on the phase reversal of the SH has intensified after 2000. The reasons may be as follows. Higher snow depth over Siberia (SSD) in November corresponds to stronger diabatic cooling and increased snow accumulation over Siberia in November and December, which may strengthen the SH in December via the positive feedback of snow albedo. The dynamic mechanisms between the higher SSD in November and weaker SH in January are further investigated from the perspective of troposphere–stratosphere interaction. Such anomalously higher SSD with strong upward heat flux induces the upward-propagating wave activity flux in November and December over the Urals and Siberia, leading to a weaker and warmer stratospheric polar vortex in January. Subsequently, the anomalies of the stratospheric polar vortex signal propagate downwards, giving rise to a negative Arctic Oscillation–like structure in the troposphere and a weakening of the SH in January. This mechanism can be partly reproduced in CMIP6. Additionally, the variability of the September–October Arctic sea ice mainly leads to coherent variations of the SH in December and January via the eddy–mean flow interaction before 2000. Furthermore, the preceding November snow cover over Siberia enhances the intraseasonal prediction skill for the winter SH after 2000. Meanwhile, considering the previous November SSD, the prediction accuracy for the out-of-phase change in the SH between December and January increases from 16% (outputs of the NCEP’s Climate Forecast System, version 2) to 75%.

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Predictions of the boreal winter stratosphere with the C3S multi-model seasonal forecast system

10.5194/ems2021-42 ◽

2021 ◽

Author(s):

Alice Portal ◽

Paolo Ruggieri ◽

Froila M. Palmeiro ◽

Javier Garcı́a-Serrano ◽

Daniela I. V. Domeisen ◽

...

Keyword(s):

Southern Oscillation ◽

Polar Vortex ◽

Seasonal Prediction ◽

Seasonal Forecast ◽

Wave Activity ◽

Arctic Sea Ice ◽

Mean Flow ◽

Seasonal Forecasts ◽

Stratospheric Polar Vortex ◽

Prediction Systems

As a result of the recent progress in the performance of seasonal prediction systems, forecasts of the mid-latitude weather at seasonal time scales are becoming increasingly important for societal decision making, as in risk estimate and management of meteorological extreme events. The predictability of the Northern-Hemisphere winter troposphere, especially in the Euro-Atlantic region, stems from the representation of a number of sources of predictability, notably El Nino Southern Oscillation, the stratospheric polar vortex, Arctic sea-ice extent, Eurasian snow cover. Among these, the stratospheric polar vortex is known to play a paramount role in seasonal forecasts of the winter tropospheric flow.Here, we investigate the performance in the stratosphere of five seasonal prediction systems taking part in the Copernicus Climate Change Service (C3S), with a focus on the seasonal forecast skill and variability, and on the assessment of stratospheric processes. We show that dynamical forecasts of the stratosphere initialised at the beginning of November are considerably more skilful than empirical forecasts based on observed October or November anomalies. Advances in the representation of stratospheric seasonal variability and extremes, i.e. sudden stratospheric warming frequency, are identified with respect to previous generations of climate models running roughly a decade ago. Such results display, however, a large model dependence. Finally, we stress the importance of the relation between the stratospheric wave activity and the stratospheric polar vortex (i.e. the wave&#8212;mean-flow interaction), applied both to the variability and to the predictability of the stratospheric mean flow. Indeed, forecasts of the winter stratospheric polar vortex are closely connected to the prediction of November-to-February stratospheric wave activity, in particular in the Eurasian sector.

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Isolating the Atmospheric Circulation Response to Arctic Sea Ice Loss in the Coupled Climate System

Journal of Climate ◽

10.1175/jcli-d-16-0257.1 ◽

2017 ◽

Vol 30 (6) ◽

pp. 2163-2185 ◽

Cited By ~ 54

Author(s):

Russell Blackport ◽

Paul J. Kushner

Keyword(s):

Sea Ice ◽

Polar Vortex ◽

Arctic Sea Ice ◽

Low Latitude ◽

Stratospheric Polar Vortex ◽

Sea Level Pressure ◽

Surface Warming ◽

Arctic Sea ◽

Pressure Anomaly ◽

Arctic Sea Ice Loss

Abstract In this study, coupled ocean–atmosphere–land–sea ice Earth system model (ESM) simulations driven separately by sea ice albedo reduction and by projected greenhouse-dominated radiative forcing are combined to cleanly isolate the sea ice loss response of the atmospheric circulation. A pattern scaling approach is proposed in which the local multidecadal mean atmospheric response is assumed to be separately proportional to the total sea ice loss and to the total low-latitude ocean surface warming. The proposed approach estimates the response to Arctic sea ice loss with low-latitude ocean temperatures fixed and vice versa. The sea ice response includes a high northern latitude easterly zonal wind response, an equatorward shift of the eddy-driven jet, a weakening of the stratospheric polar vortex, an anticyclonic sea level pressure anomaly over coastal Eurasia, a cyclonic sea level pressure anomaly over the North Pacific, and increased wintertime precipitation over the west coast of North America. Many of these responses are opposed by the response to low-latitude surface warming with sea ice fixed. However, both sea ice loss and low-latitude surface warming act in concert to reduce subseasonal temperature variability throughout the middle and high latitudes. The responses are similar in two related versions of the National Center for Atmospheric Research Earth system models, apart from the stratospheric polar vortex response. Evidence is presented that internal variability can easily contaminate the estimates if not enough independent climate states are used to construct them.

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Weak Stratospheric Polar Vortex Events Modulated by the Arctic Sea‐Ice Loss

Journal of Geophysical Research Atmospheres ◽

10.1029/2018jd029222 ◽

2019 ◽

Vol 124 (2) ◽

pp. 858-869 ◽

Cited By ~ 8

Author(s):

Kazuhira Hoshi ◽

Jinro Ukita ◽

Meiji Honda ◽

Tetsu Nakamura ◽

Koji Yamazaki ◽

...

Keyword(s):

Sea Ice ◽

Polar Vortex ◽

Arctic Sea Ice ◽

The Arctic ◽

Stratospheric Polar Vortex ◽

Arctic Sea ◽

Arctic Sea Ice Loss

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Weakening of the stratospheric polar vortex by Arctic sea-ice loss

Nature Communications ◽

10.1038/ncomms5646 ◽

2014 ◽

Vol 5 (1) ◽

Cited By ~ 304

Author(s):

Baek-Min Kim ◽

Seok-Woo Son ◽

Seung-Ki Min ◽

Jee-Hoon Jeong ◽

Seong-Joong Kim ◽

...

Keyword(s):

Sea Ice ◽

Polar Vortex ◽

Arctic Sea Ice ◽

Stratospheric Polar Vortex ◽

Arctic Sea ◽

Arctic Sea Ice Loss

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Dynamical Link between the Barents–Kara Sea Ice and the Arctic Oscillation

Journal of Climate ◽

10.1175/jcli-d-15-0669.1 ◽

2016 ◽

Vol 29 (14) ◽

pp. 5103-5122 ◽

Cited By ~ 52

Author(s):

Xiao-Yi Yang ◽

Xiaojun Yuan ◽

Mingfang Ting

Keyword(s):

Sea Ice ◽

Atmospheric Circulation ◽

Arctic Oscillation ◽

Arctic Sea Ice ◽

The Arctic ◽

Mean Flow ◽

Stratospheric Polar Vortex ◽

Arctic Sea ◽

Barents And Kara Seas ◽

The Arctic Oscillation

Abstract The recent accelerated Arctic sea ice decline has been proposed as a possible forcing factor for midlatitude circulation changes, which can be projected onto the Arctic Oscillation (AO) and/or North Atlantic Oscillation (NAO) mode. However, the timing and physical mechanisms linking AO responses to the Arctic sea ice forcing are not entirely understood. In this study, the authors suggest a connection between November sea ice extent in the Barents and Kara Seas and the following winter’s atmospheric circulation in terms of the fast sea ice retreat and the subsequent modification of local air–sea heat fluxes. In particular, the dynamical processes that link November sea ice in the Barents and Kara Seas with the development of AO anomalies in February is explored. In response to the lower-tropospheric warming associated with the initial thermal effect of the sea ice loss, the large-scale atmospheric circulation goes through a series of dynamical adjustment processes: The decelerated zonal-mean zonal wind anomalies propagate gradually from the subarctic to midlatitudes in about one month. The equivalent barotropic AO dipole pattern develops in January because of wave–mean flow interaction and firmly establishes itself in February following the weakening and warming of the stratospheric polar vortex. This connection between sea ice loss and the AO mode is robust on time scales ranging from interannual to decadal. Therefore, the recent winter AO weakening and the corresponding midlatitude climate change may be partly associated with the early winter sea ice loss in the Barents and Kara Seas.

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Model and state dependence of the atmospheric response to Arctic sea-ice loss

10.5194/egusphere-egu2020-11872 ◽

2020 ◽

Author(s):

Amber Walsh ◽

James Screen ◽

Adam Scaife ◽

Doug Smith ◽

Rosie Eade

Keyword(s):

Sea Ice ◽

Polar Vortex ◽

Horizontal Resolution ◽

Arctic Sea Ice ◽

Atmospheric Response ◽

Model Resolution ◽

Quasi Biennial Oscillation ◽

Stratospheric Polar Vortex ◽

Arctic Sea ◽

Arctic Sea Ice Loss

The climate response to Arctic sea-ice loss is highly uncertain. There exists considerable disagreement between observational and modelling studies, and between models, for reasons that remain poorly understood. To make progress, the Polar Amplification Model Intercomparison Project (PAMIP) was designed to provide coordinated experiments, with consistent sea-ice loss applied in multiple models. Results from the PAMIP are presented, focussing on the robustness of the atmospheric response to Arctic sea-ice loss across models and, within individual models, the dependence of the response on the mean state.In the troposphere, the mid-latitude jet is either weakened and/or shifted towards the equator in all models, albeit with varying magnitudes. We hypothesise that the magnitude of the jet response is sensitive to the atmospheric model resolution. To test this, and to more broadly identify the aspects of the atmospheric response that are sensitive to model resolution, we compare like-for-like experiments with two versions of the HadGEM3 model at low (N96) and high (N216) horizontal resolution.The stratospheric polar vortex response to Arctic sea-ice loss is not consistent between models, and appears to be influenced by both the size of the ensemble for each model and the phase of the Quasi-Biennial Oscillation (QBO). The possible modulating effect of the QBO is further explored using new simulations with background atmospheric states representing the easterly and westerly QBO phases.A surprising early result from the PAMIP simulations were sizeable changes in the Southern Hemisphere in response to Arctic sea-ice loss and significant changes in the Northern Hemisphere in response to Antarctic sea-ice loss, even in atmosphere-only model experiments. The robustness of such apparent interhemispheric connections across models, ensemble sizes and mean states is investigated.&#160;&#160;&#160;

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Intraseasonal and Interdecadal Jet Shifts in the Northern Hemisphere: The Role of Warm Pool Tropical Convection and Sea Ice

Journal of Climate ◽

10.1175/jcli-d-14-00057.1 ◽

2014 ◽

Vol 27 (17) ◽

pp. 6497-6518 ◽

Cited By ~ 49

Author(s):

Steven B. Feldstein ◽

Sukyoung Lee

Keyword(s):

Sea Ice ◽

Polar Vortex ◽

Warm Pool ◽

Wave Activity ◽

Arctic Sea Ice ◽

Tropical Convection ◽

The Arctic ◽

Stratospheric Polar Vortex ◽

Arctic Sea ◽

Wave Activity Flux

Abstract This study uses cluster analysis to investigate the interdecadal poleward shift of the subtropical and eddy-driven jets and its relationship to intraseasonal teleconnections. For this purpose, self-organizing map (SOM) analysis is applied to the ECMWF Interim Re-Analysis (ERA-Interim) zonal-mean zonal wind. The resulting SOM patterns have time scales of 4.8–5.7 days and undergo notable interdecadal trends in their frequency of occurrence. The sum of these trends closely resembles the observed interdecadal trend of the subtropical and eddy-driven jets, indicating that much of the interdecadal climate forcing is manifested through changes in the frequency of intraseasonal teleconnection patterns. Two classes of jet cluster patterns are identified. The first class of SOM pattern is preceded by anomalies in convection over the warm pool followed by changes in the poleward wave activity flux. The second class of patterns is preceded by sea ice and stratospheric polar vortex anomalies; when the Arctic sea ice area is reduced, the subsequent planetary wave anomalies destructively interfere with the climatological stationary waves. This is followed by a decrease in the vertical wave activity flux and a strengthening of the stratospheric polar vortex. An increase in sea ice area leads to the opposite chain of events. Analysis suggests that the positive trend in the Arctic Oscillation (AO) up until the early 1990s might be attributed to increased warm pool tropical convection, while the subsequent reversal in its trend may be due to the influence of tropical convection being overshadowed by the accelerated loss of Arctic sea ice.

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Understanding of European Cold Extremes, Sudden Stratospheric Warming, and Siberian Snow Accumulation in the Winter of 2017/18

Journal of Climate ◽

10.1175/jcli-d-18-0861.1 ◽

2020 ◽

Vol 33 (2) ◽

pp. 527-545 ◽

Cited By ~ 2

Author(s):

Zhuozhuo Lü ◽

Fei Li ◽

Yvan J. Orsolini ◽

Yongqi Gao ◽

Shengping He

Keyword(s):

Snow Depth ◽

Time Lag ◽

Snow Accumulation ◽

Arctic Sea Ice ◽

Planetary Waves ◽

Stratospheric Warming ◽

Mean Flow ◽

Sudden Stratospheric Warming ◽

Cold Extremes

AbstractIt is unclear whether the Eurasian snow plays a role in the tropospheric driving of sudden stratospheric warming (SSW). The major SSW event of February 2018 is analyzed using reanalysis datasets. Characterized by predominant planetary waves of zonal wave 2, the SSW developed into a vortex split via wave–mean flow interaction. In the following two weeks, the downward migration of zonal-mean zonal wind anomalies was accompanied by a significant transition to the negative phase of the North Atlantic Oscillation, leading to extensive cold extremes across Europe. Here, we demonstrate that anomalous Siberian snow accumulation could have played an important role in the 2018 SSW occurrence. In the 2017/18 winter, snow depths over Siberia were much higher than normal. A lead–lag correlation analysis shows that the positive fluctuating snow depth anomalies, leading to intensified “cold domes” over eastern Siberia (i.e., in a region where the climatological upward planetary waves maximize), precede enhanced wave-2 pulses of meridional heat fluxes (100 hPa) by 7–8 days. The snow–SSW linkage over 2003–19 is further investigated, and some common traits among three split events are found. These include a time lag of about one week between the maximum anomalies of snow depth and wave-2 pulses (100 hPa), high sea level pressure favored by anomalous snowpack, and a ridge anchoring over Siberia as precursor of the splits. The role of tropospheric ridges over Alaska and the Urals in the wave-2 enhancement and the role of Arctic sea ice loss in Siberian snow accumulation are also discussed.

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The role of cyclone activity in snow accumulation on Arctic sea ice

Nature Communications ◽

10.1038/s41467-019-13299-8 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 4

Author(s):

M. A. Webster ◽

C. Parker ◽

L. Boisvert ◽

R. Kwok

Keyword(s):

Sea Ice ◽

Snow Accumulation ◽

Arctic Sea Ice ◽

Surface Energy Budget ◽

The Arctic ◽

Cyclone Activity ◽

In Situ Data ◽

Arctic Sea ◽

Spatio Temporal

AbstractIdentifying the mechanisms controlling the timing and magnitude of snow accumulation on sea ice is crucial for understanding snow’s net effect on the surface energy budget and sea-ice mass balance. Here, we analyze the role of cyclone activity on the seasonal buildup of snow on Arctic sea ice using model, satellite, and in situ data over 1979–2016. On average, 44% of the variability in monthly snow accumulation was controlled by cyclone snowfall and 29% by sea-ice freeze-up. However, there were strong spatio-temporal differences. Cyclone snowfall comprised ~50% of total snowfall in the Pacific compared to 83% in the Atlantic. While cyclones are stronger in the Atlantic, Pacific snow accumulation is more sensitive to cyclone strength. These findings highlight the heterogeneity in atmosphere-snow-ice interactions across the Arctic, and emphasize the need to scrutinize mechanisms governing cyclone activity to better understand their effects on the Arctic snow-ice system with anthropogenic warming.

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Arctic sea-ice albedo derived from RGPS-based ice-thickness estimates

Annals of Glaciology ◽

10.3189/172756401781818103 ◽

2001 ◽

Vol 33 ◽

pp. 225-229 ◽

Cited By ~ 8

Author(s):

R.W. Lindsay

Keyword(s):

Sea Ice ◽

Empirical Relationship ◽

Early Spring ◽

Snow Accumulation ◽

Arctic Sea Ice ◽

Ice Thickness ◽

First Year ◽

Large Set ◽

Radar Images ◽

Arctic Sea

AbstractThe RADARSAT geophysical processor system (RGPS) uses sequential synthetic aperture radar images of Arctic sea ice taken every 3 days to track a large set of Lagrangian points over the winter and spring seasons. The points are the vertices of cells, which are initially square and 10 km on a side, and the changes in the area of these cells due to opening and closing of the ice are used to estimate the fractional area of a set of first-year ice categories. The thickness of each category is estimated by the RGPS from an empirical relationship between ice thickness and the freezing degree-days since the formation of the ice. With a parameterization of the albedo based on the ice thickness, the albedo may be estimated from the first-year ice distribution. We compute the albedo for the first spring processed by the RGPS, the early spring of 1997. The data include most of the Beaufort and Chukchi Seas. We find that the mean albedo is 0.79 with a standard deviation of 0.04, with lower albedo values near the edge of the perennial ice zone. The biggest source of error is likely the assumed rate of snow accumulation on new ice.

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