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Yan Ge and Gavin Gong

Abstract

Snow–atmosphere relationships have been studied for nearly half a century, but the primary focus has been on snow extent variability, largely because of the relative scarcity of snow depth data. A recently released North American snow depth dataset, with extensive spatial coverage and multidecadal temporal duration, provides a new opportunity to compare snow depth–climate relationships with snow extent–climate relationships over North America. Robust concurrent lead and lag correlations are observed between snow depth and two major climate modes, the Pacific decadal oscillation (PDO) and the Pacific–North America (PNA) pattern, across North America and throughout the snow season. In contrast, snow extent exhibits a less coherent relationship with PDO and PNA except in late spring, which can be interpreted as a residual of the snow depth–climate mode relationship. A regional signature for the snow depth–PDO/PNA relationship is also identified, centered over interior central-western North America. Smaller scales mask the regional effect of PDO and PNA because of local snow depth variability, while larger continental scales exceed the regional domain of the climate mode teleconnections. Overall these results suggest that North American snow depth variability may have greater climatic causes and consequences than snow extent. Physical mechanisms that may be responsible for the observed snow depth–climate teleconnection patterns such as the surface energy balance, moisture transport, and atmospheric flow regimes are briefly discussed.

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Yan Ge and Gavin Gong

Abstract

Snow extent and snow depth are two related characteristics of a snowpack, but they do not need to be mutually consistent. Differences between these two variables at local scales are readily apparent. However, at larger scales, which interact with atmospheric circulation and climate, snow extent is the primary variable considered, owing largely to the scarcity of snow depth data. In this study, three regional-/continental-scale gridded snow depth/snow water equivalent (SWE) datasets, derived from station observations or passive microwave satellite sensors, are utilized to quantitatively evaluate the relationship between snow extent and snow depth/SWE over North America. Various statistical methods are used to ensure the robustness of the results, including correlations, composites, and singular value decomposition analyses.

Results indicate that continental-scale snow depth variations are substantial in their own right and that depth and extent anomalies are largely unrelated over broad high-latitude regions north of the snow line. Snow extent and snow depth vary more consistently in the vicinity of the snow line, especially in autumn and spring, during which precipitation and ablation can affect both variables. It is also found that deeper (shallower) winter snow translates into larger (smaller) snow-covered areas in the following spring/summer season, and also a longer (shorter) snow season, but only in specific regions. These results suggest a possible influence of snow depth on spring and summer climate. Overall, the observed lack of mutual consistency between these two snowpack variables at continental/regional scales suggests that snow depth variations may be of sufficiently large magnitude, spatial scope, and temporal duration to interact with regional–hemispheric climate, in a manner unrelated to the more extensively studied snow extent variations.

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Debjani Ghatak, Gavin Gong, and Allan Frei

Abstract

The snowpack is an important seasonal surface water storage reservoir that affects the availability of water resources during the spring and summer seasons in mid–high latitudes. Not surprisingly, interannual variations in snow cover extent and snow water equivalent have been extensively studied in arid regions such as western North America. This study broadens the focus by examining snow depth as an alternative snowpack metric, and considers its variability over different parts of North America. The authors use singular value decomposition (SVD) in conjunction with linear and partial correlation to show that regional snow-depth variations can be largely explained by the winter North Atlantic Oscillation (NAO) and the Pacific–North American (PNA) modes of atmospheric variability through distinct mechanistic pathways involving regional winter circulation patterns and hydrologic fluxes. The high index phase of the NAO generates positive winter air temperature anomalies over eastern parts of North America, causing thinning of the winter snowpack via snowmelt. Meanwhile, the high index phase of the PNA generates negative winter snowfall anomalies across midlatitudinal areas of North America, which also serve to thin the snowpack. Positive PNA anomalies have also been shown to increase temperatures and decrease snow depths over western North America. The PNA influence extends across the continent, whereas the NAO influence is limited to eastern North America. The winter snow-depth variations associated with all of these pathways exhibit seasonal persistence, which ultimately yield regional-scale spring snow-depth anomalies throughout much of North America.

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Gavin Gong, Dara Entekhabi, and Judah Cohen

Abstract

Previous modeling studies have identified a teleconnection pathway linking observation-based early season Siberian snow perturbations to a modulation of the winter Arctic Oscillation (AO) mode. In this study, the key role of orography in producing this modeled teleconnection is explicitly investigated using numerical experiments analogous to the previous studies. The climatic response to the same snow perturbation is investigated under modified orographic barriers in southern and eastern Siberia. Reducing these barriers results in a weakening of the prevailing orographically forced region of stationary wave activity centered over Siberia, as well as the snow-forced upward wave flux anomaly that initiates the teleconnection. This diminished anomaly propagates upward, but does not extend into the stratosphere to weaken the polar vortex. Consequently, poleward refraction of upper-tropospheric waves and downward propagation of coupled wave–mean flow anomalies, which ultimately produce the negative winter AO response, fail to develop. Thus, the mountains represent an orographic constraint on the snow–AO teleconnection pathway. By reducing the orographic barrier, the snow-forced influx of wave energy remains in the troposphere and, instead, produces a hemispheric-scale equatorward wave refraction.

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Stefan Sobolowski, Gavin Gong, and Mingfang Ting

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Continental-scale snow cover represents a broad thermal forcing on monthly-to-intraseasonal time scales, with the potential to modify local and remote atmospheric circulation. A previous GCM study reported robust transient-eddy responses to prescribed anomalous North American (NA) snow cover. The same set of experiments also indicated a robust upper-level stationary wave response during spring, but the nature of this response was not investigated until now. Here, the authors diagnose a deep, snow-induced, tropospheric cooling over NA and hypothesize that this may represent a pathway linking snow to the stationary wave response. A nonlinear stationary wave model is shown to reproduce the GCM stationary wave response to snow more accurately than a linear model, and results confirm that diabatic cooling is the primary driver of the stationary wave response. In particular, the total nonlinear effects due to cooling, and its interactions with transient eddies and orography, are shown to be essential for faithful reproduction of the GCM response. The nonlinear model results confirm that direct effects due to transients and orography are modest. However, with interactions between forcings included, the total effects due to these terms make important contributions to the total response. Analysis of observed NA snow cover and stationary waves is qualitatively similar to the patterns generated by the GCM and linear/nonlinear stationary wave models, indicating that the snow-induced signal is not simply a modeling artifact. The diagnosis and description of a snow–stationary wave relationship adds to the understanding of stationary waves and their forcing mechanisms, and this relationship suggests that large-scale changes in the land surface state may exert considerable influence on the atmosphere over hemispheric scales and thereby contribute to climate variability.

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Gavin Gong, Dara Entekhabi, and Judah Cohen

Abstract

Numerous studies have hypothesized that surface boundary conditions or other external mechanisms drive the hemispheric mode of atmospheric variability known as the Arctic Oscillation (AO), or its regional counterpart, the North Atlantic Oscillation (NAO). However, no single external factor has emerged as the dominant forcing mechanism, which has led, in part, to the characterization of the AO–NAO as a fundamental internal mode of the atmospheric system. Nevertheless, surface forcings may play a considerable role in modulating, if not driving, the AO–NAO mode. In this study, a pair of large-ensemble atmospheric GCM experiments (with SST climatology), one with prescribed climatological snow mass and another with freely varying snow mass, is conducted to investigate the degree to which the AO–NAO is modulated by interannual variability of surface snow conditions. Statistical analysis of the results indicates that snow anomalies are not required to produce the AO–NAO mode of variability. Nevertheless, interannual variations in snow mass are found to exert a modulating influence on the AO–NAO mode. Snow variations excite the AO pattern over the North Atlantic sector, produce correlated hemispheric AO features throughout the troposphere and stratosphere, and generate autumn sea level pressure anomalies over Siberia that evolve into the winter AO–NAO. These numerical modeling results are consistent with previous observational analyses that statistically link the AO–NAO mode with the Siberian high and associated snow cover variations.

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Gavin Gong, Dara Entekhabi, and Judah Cohen

Abstract

Wintertime Northern Hemisphere climate variability is investigated using large-ensemble (20) numerical GCM simulations. Control simulations with climatological surface (land and ocean) conditions indicate that the Arctic Oscillation (AO) is an internal mode of the Northern Hemisphere atmosphere, and that it can be triggered through a myriad of perturbations. In this study the role of autumn land surface snow conditions is investigated. Satellite observations of historical autumn–winter snow cover are applied over Siberia as model boundary conditions for two snow-forced experiments, one using the highest observed autumn snow cover extent over Siberia (1976) and another using the lowest extent (1988). The ensemble-mean difference between the two snow-forced experiments is computed to evaluate the climatic response to Siberian snow conditions. Experiment results suggest that Siberian snow conditions exert a modulating influence on the predominant wintertime Northern Hemisphere (AO) mode. Furthermore, an atmospheric teleconnection pathway is identified, involving well-known wave–mean flow interaction processes throughout the troposphere and stratosphere. Anomalously high Siberian snow increases local upward stationary wave flux activity, weakens the stratospheric polar vortex, and causes upper-troposphere stationary waves to refract poleward. These related stationary wave and mean flow anomalies propagate down through the troposphere via a positive feedback, which results in a downward-propagating negative AO anomaly during the winter season from the stratosphere to the surface. This pathway provides a physical explanation for how regional land surface snow anomalies can influence winter climate on a hemispheric scale. The results of this study may potentially lead to improved predictions of the winter AO mode, based on Siberian snow conditions during the preceding autumn.

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Gavin Gong, Dara Entekhabi, and Guido D. Salvucci

Abstract

Simulated climates using numerical atmospheric general circulation models (GCMS) have been shown to he highly sensitive to the fraction of GCM grid area assumed to be wetted during rain events. The model hydrologic cycle and land-surface water and energy balance are influenced by the parameter k̄, which is the dimensionless fractional wetted area for GCM grids. Hourly precipitation records for over 1700 precipitation stations within the contiguous United States are used to obtain observation-based estimates of fractional wetting that exhibit regional and seasonal variations. The spatial parameter k̄ is estimated from the temporal raingauge data using conditional probability relations. Monthly k̄ values are estimated for rectangular grid areas over the contiguous United States as defined by the Goddard Institute for Space Studies 4° × 5° GCM. A bias in the estimates is evident due to the unavoidably sparse raingauge network density, which causes some storms to go undetected by the network. This bias is corrected by deriving the probability of a storm escaping detection by the network. A Monte Carlo simulation study is also conducted that consists of synthetically generated storm arrivals over an artificial grid area. It is used to confirm the k̄ estimation procedure and to test the nature of the bias and its correction. These monthly fractional wetting estimates, based on the analysis of station precipitation data, provide an observational basis for assigning the influential parameter k̄ in GCM land-surface hydrology parameterizations.

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Yan Ge, Gavin Gong, and Allan Frei

Abstract

The wintertime Pacific–North American (PNA) teleconnection pattern has previously been shown to influence springtime snow conditions over portions of North America. This paper develops a more complete physical understanding of this linkage across the continent, using a recently released long-term, continental-scale gridded North American snow depth dataset and the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis data. An empirical orthogonal function–based filtering process is used to identify and isolate the interannual snow depth variations associated with PNA. Then linear and partial correlations are employed to investigate the physical mechanisms that link winter PNA with spring snow depth. In the positive phase of PNA, the enhanced PNA pressure centers lead to warmer temperatures over northwestern North America and less precipitation at midlatitudes. The temperature and precipitation pathways act independently and in distinct geographical regions, and together they serve to reduce winter snow depth across much of North America. Winter anomalies in the snow depth field then tend to persist into spring. Dynamic mechanisms responsible for the PNA-influenced North American precipitation and temperature anomalies, involving moisture transport and cold air intrusions, are confirmed in this study and also extended to continental snow depth anomalies.

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Stefan Sobolowski, Gavin Gong, and Mingfang Ting

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The radiative and thermal properties of widespread snow cover anomalies have the potential to modulate local and remote climate over monthly to seasonal time scales. In this study, physical and dynamical links between anomalous North American snow conditions and Northern Hemisphere climate are examined. A pair of 40-member ensemble AGCM experiments is run, with prescribed high- and low-snow forcings over North America during the course of an entire year (EY). The difference between the two ensemble averages reflects the climatic response to sustained EY snow forcing. Local surface responses over the snow forcing occur in all seasons, and a significant remote surface temperature response occurs over Eurasia during spring. A hemispheric-scale transient eddy response to EY forcing also occurs, which propagates downstream from the forcing region to Eurasia, and then reaches a maximum in extent and amplitude in spring. The evolution of this transient eddy response is indicative of considerable downstream development and is consistent with known storm-track dynamics. This transient response is shown to be a result of persistent steepened temperature gradients created by the anomalous snow conditions, which contribute to enhanced baroclinicity over the storm-track entrance regions. A second pair of experiments is run, with the prescribed high- and low-snow forcings over North America restricted to the fall season (FS). The dynamical response to FS forcing is muted compared to the EY scenario, suggesting that the seasonal timing and persistence of the snow forcing are essential for the remote teleconnection.

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