Model simulations of arctic biogeochemistry and permafrost extent are highly sensitive to the implemented snow scheme in LPJ-GUESS

Abstract. The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a realistic simulation of the effect of snow cover on soil conditions to more accurately project the direction of arctic carbon–climate feedbacks under continued winter warming. The Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now – a single layer snow scheme, which underestimated the insulation effect of snow, leading to a cold bias in soil temperature. To address this shortcoming, we developed and integrated a dynamic, multi-layer snow scheme in LPJ-GUESS. The new snow scheme performs well in simulating the insulation of snow at hundreds of locations across Russia compared to observations. We show that improving this single physical factor enhanced simulations of permafrost extent compared to an advanced permafrost product, where the overestimation of permafrost cover decreased from 10 % to 5 % using the new snow scheme. Besides soil thermodynamics, the new snow scheme resulted in a doubled winter respiration and an overall higher vegetation carbon content. This study highlights the importance of a correct representation of snow in ecosystem models to project biogeochemical processes that govern climate feedbacks. The new dynamic snow scheme is an essential improvement in the simulation of cold season processes, which reduces the uncertainty of model projections. These developments contribute to a more realistic simulation of arctic carbon–climate feedbacks.

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Model simulations of arctic biogeochemistry and permafrost extent are highly sensitive to the implemented snow scheme

10.5194/bg-2021-121 ◽

2021 ◽

Author(s):

Alexandra Pongracz ◽

David Wårlind ◽

Paul A. Miller ◽

Frans-Jan W. Parmentier

Keyword(s):

Snow Cover ◽

Large Scale ◽

Global Climate ◽

Single Layer ◽

Physical Factor ◽

Cold Season ◽

The Arctic ◽

Soil Conditions ◽

Cold Bias ◽

Climate Feedbacks

Abstract. The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a realistic simulation of the effect of snow cover on soil conditions to more accurately project the direction of arctic carbon-climate feedbacks under continued winter warming. The Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now – a single layer snow scheme, which underestimated the insulation effect of snow, leading to a cold bias in soil temperature. To address this shortcoming, we developed and integrated a dynamic, multi-layer snow scheme in LPJ-GUESS. The new snow scheme performs well in simulating the insulation of snow at hundreds of locations across Russia compared to observations. We show that improving this single physical factor enhanced simulations of permafrost extent compared to an advanced permafrost product. Besides soil thermodynamics, the new snow scheme resulted in increased winter respiration and an overall lower soil carbon content due to warmer soil conditions. The Dynamic scheme also influenced vegetation dynamics, resulting in an improved vegetation distribution and tundra-taiga boundary simulation. This study highlights the importance of a correct representation of snow in ecosystem models to project biogeochemical processes that govern climate feedbacks. The new dynamic snow scheme is an essential improvement in the simulation of cold season processes, which reduces the uncertainty of model projections. These developments contribute to a better understanding of the Arctic's role in the global climate system.

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Trends and regime shifts in climatic conditions and river runoff in Estonia during 1951–2015

Earth System Dynamics ◽

10.5194/esd-8-963-2017 ◽

2017 ◽

Vol 8 (4) ◽

pp. 963-976 ◽

Cited By ~ 15

Author(s):

Jaak Jaagus ◽

Mait Sepp ◽

Toomas Tamm ◽

Arvo Järvet ◽

Kiira Mõisja

Keyword(s):

Time Series ◽

Snow Cover ◽

Atmospheric Circulation ◽

Air Temperature ◽

Large Scale ◽

Regime Shifts ◽

The Arctic ◽

Dry Period ◽

Snow Cover Duration ◽

Large Scale Atmospheric Circulation

Abstract. Time series of monthly, seasonal and annual mean air temperature, precipitation, snow cover duration and specific runoff of rivers in Estonia are analysed for detecting of trends and regime shifts during 1951–2015. Trend analysis is realised using the Mann–Kendall test and regime shifts are detected with the Rodionov test (sequential t-test analysis of regime shifts). The results from Estonia are related to trends and regime shifts in time series of indices of large-scale atmospheric circulation. Annual mean air temperature has significantly increased at all 12 stations by 0.3–0.4 K decade−1. The warming trend was detected in all seasons but with the higher magnitude in spring and winter. Snow cover duration has decreased in Estonia by 3–4 days decade−1. Changes in precipitation are not clear and uniform due to their very high spatial and temporal variability. The most significant increase in precipitation was observed during the cold half-year, from November to March and also in June. A time series of specific runoff measured at 21 stations had significant seasonal changes during the study period. Winter values have increased by 0.4–0.9 L s−1 km−2 decade−1, while stronger changes are typical for western Estonia and weaker changes for eastern Estonia. At the same time, specific runoff in April and May have notably decreased indicating the shift of the runoff maximum to the earlier time, i.e. from April to March. Air temperature, precipitation, snow cover duration and specific runoff of rivers are highly correlated in winter determined by the large-scale atmospheric circulation. Correlation coefficients between the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices reflecting the intensity of westerlies, and the studied variables were 0.5–0.8. The main result of the analysis of regime shifts was the detection of coherent shifts for air temperature, snow cover duration and specific runoff in the late 1980s, mostly since the winter of 1988/1989, which are, in turn, synchronous with the shifts in winter circulation. For example, runoff abruptly increased in January, February and March but decreased in April. Regime shifts in annual specific runoff correspond to the alternation of wet and dry periods. A dry period started in 1964 or 1963, a wet period in 1978 and the next dry period at the beginning of the 21st century.

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Variability of the Cold Season Climate in Central Asia. Part II: Hydroclimatic Predictability

Journal of Climate ◽

10.1175/jcli-d-18-0892.1 ◽

2019 ◽

Vol 32 (18) ◽

pp. 6015-6033 ◽

Cited By ~ 5

Author(s):

Lars Gerlitz ◽

Eva Steirou ◽

Christoph Schneider ◽

Vincent Moron ◽

Sergiy Vorogushyn ◽

...

Keyword(s):

Central Asia ◽

Snow Cover ◽

Large Scale ◽

Cold Season ◽

Hadley Cell ◽

Quasi Biennial Oscillation ◽

Large Variability ◽

Forecast Performance ◽

Eurasian Snow Cover ◽

Eurasian Snow

Abstract Central Asia (CA) is subjected to a large variability of precipitation. This study presents a statistical model, relating precipitation anomalies in three subregions of CA in the cold season (November–March) with various predictors in the preceding October. Promising forecast skill is achieved for two subregions covering 1) Uzbekistan, Turkmenistan, Kyrgyzstan, Tajikistan, and southern Kazakhstan and 2) Iran, Afghanistan, and Pakistan. ENSO in October is identified as the major predictor. Eurasian snow cover and the quasi-biennial oscillation further improve the forecast performance. To understand the physical mechanisms, an analysis of teleconnections between these predictors and the wintertime circulation over CA is conducted. The correlation analysis of predictors and large-scale circulation indices suggests a seasonal persistence of tropical circulation modes and a dynamical forcing of the westerly circulation by snow cover variations over Eurasia. An EOF analysis of pressure and humidity patterns allows separating the circulation variability over CA into westerly and tropical modes and confirms that the identified predictors affect the respective circulation characteristics. Based on the previously established weather type classification for CA, the predictors are investigated with regard to their effect on the regional circulation. The results suggest a modification of the Hadley cell due to ENSO variations, with enhanced moisture supply from the Arabian Gulf during El Niño. They further indicate an influence of Eurasian snow cover on the wintertime Arctic Oscillation (AO) and Northern Hemispheric Rossby wave tracks. Positive anomalies favor weather types associated with dry conditions, while negative anomalies promote the formation of a quasi-stationary trough over CA, which typically occurs during positive AO conditions.

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On the Extreme Variability and Change of Cold-Season Temperatures in Northwest Canada

Journal of Climate ◽

10.1175/2007jcli1583.1 ◽

2008 ◽

Vol 21 (1) ◽

pp. 94-113 ◽

Cited By ~ 18

Author(s):

Kit K. Szeto

Keyword(s):

North Pacific ◽

Large Scale ◽

Heat Budget ◽

Thermal Response ◽

Cold Season ◽

Temperature Variability ◽

Cold Bias ◽

Latent Heating ◽

Recent Warming ◽

The Cross

Abstract The Mackenzie River basin (MRB) in northwestern Canada is a climatologically important region that exerts significant influences on the weather and climate of North America. The region exhibits the largest cold-season temperature variability in the world on both the intraseasonal and interannual time scales. In addition, some of the strongest recent warming signals have been observed over the basin. To understand the nature of these profound and intriguing observed thermal characteristics of the region, its atmospheric heat budget is assessed by using the NCEP–NCAR reanalysis dataset. The composite heat budgets and large-scale atmospheric conditions that are representative of anomalous winters in the region are examined in unison to study the processes that are responsible for the development of extreme warm/cold winters in the MRB. It is shown that the large winter temperature variability of the region is largely a result of the strong variability of atmospheric circulations over the North Pacific, the selective enhancement/weakening of latent heating of the cross-barrier flow for various onshore flow configurations, and synoptic-scale feedback processes that accentuate the thermal response of the basin to the changes in upwind conditions. The improved understanding of mechanisms that govern the thermal response of the basin to changes in the upstream environment provides a theoretical basis to interpret the climate change and modeling results for the region. In particular, the large recent warming trend observed for the region can be understood as the enhanced response of the basin to the shift in North Pacific circulation regime during the mid-1970s. The strong cold bias that affected the region in some climate model results can be attributed to the underprediction of orographic precipitation and associate latent heating of the cross-barrier flow, and the subsequent weakening of mean subsidence and warming over the basin in the models.

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TECHNIQUE POUR ECHANTILLONNER LES RACINES DE PLANTES DANS LE SOL GELE ET ENNEIGE

Canadian Journal of Plant Science ◽

10.4141/cjps76-101 ◽

1976 ◽

Vol 56 (3) ◽

pp. 633-638 ◽

Cited By ~ 2

Author(s):

R. BOLDUC

Keyword(s):

Snow Cover ◽

Large Scale ◽

Cold Season ◽

Frozen Soil ◽

Soil Core ◽

Intact Plants ◽

Large Scale Study ◽

Minimum Disturbance

A tubular drill has been designed to extract a frozen soil core 12–15 cm in diameter and 15–40 cm in length with the roots and collars of intact plants. A snow cylinder is used to clear the sampling spot, causing minimum disturbance to the snow cover. This equipment makes possible a large scale study of vegetation during the cold season.

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Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-4747-2009 ◽

2009 ◽

Vol 9 (14) ◽

pp. 4747-4773 ◽

Cited By ~ 4

Author(s):

I. Sednev ◽

S. Menon ◽

G. McFarquhar

Keyword(s):

Large Scale ◽

Single Layer ◽

Mixed Phase ◽

The Arctic ◽

Ice Crystal ◽

The North ◽

North Slope Of Alaska ◽

Aerosol Cloud Interactions ◽

Mixed Phase Clouds ◽

Ice Initiation

Abstract. The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9–10 October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and subsaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors' contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

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Trends and regime shifts in climatic conditions and river runoff in Estonia during 1951–2015

10.5194/esd-2017-24 ◽

2017 ◽

Author(s):

Jaak Jaagus ◽

Mait Sepp ◽

Toomas Tamm ◽

Arvo Järvet ◽

Kiira Mõisja

Keyword(s):

Time Series ◽

Snow Cover ◽

Atmospheric Circulation ◽

Air Temperature ◽

Large Scale ◽

Regime Shifts ◽

The Arctic ◽

Dry Period ◽

Snow Cover Duration ◽

Large Scale Atmospheric Circulation

Abstract. Time series of monthly, seasonal and annual mean air temperature, precipitation, snow cover duration and specific runoff of rivers in Estonia are analysed for detecting trends and regime shifts during 1951–2015. Trend analysis is performed using the Mann-Kendall test and regime shifts are detected with the Rodionov test (Sequential T-test Analysis of Regime Shifts). The results from Estonia are related to trends and regime shifts in time series of indices of large-scale atmospheric circulation. Annual mean air temperature has significantly increased at 12 observed stations by 0.3–0.4 K per decade. The warming trend was detected in all seasons but with the higher magnitude in spring and winter. Snow cover duration has decreased in Estonia by 3–4 days per decade. Changes in precipitation are not clear and uniform due to their very high spatial and temporal variability. The most significant increase in precipitation was observed during the cold half-year, from November to March. Time series of specific runoff measured at 21 stations has had significant seasonal changes during the study period. Winter values have increased by 0.4–0.9 l/s per km2 per decade while stronger changes are typical for western Estonia and weaker changes for eastern Estonia. At the same time, specific runoff in April and May has notably decreased indicating the shift of the runoff maximum to earlier time, i.e. from April to March. All meteorological and hydrological variables are highly correlated in winter, determined by the large-scale atmospheric circulation. Correlation coefficients between the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices reflecting the intensity of westerlies, and the studied variables were 0.5–0.8. The main result of the analysis of regime shifts was the detection of coherent shifts for air temperature, snow cover duration and specific runoff in the late 1980s, mostly since the winter 1988/1989, which are, in turn, synchronous with the shifts in winter circulation. For example, runoff abruptly increased in January, February and March but decreased in April. Regime shifts in the annual specific runoff correspond to the alternation of wet and dry periods. A dry period started since 1964 or 1963, a wet period since 1978 and the next dry period since the beginning of the 21st century.

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Connecting European snow cover variability with large scale atmospheric patterns

Advances in Geosciences ◽

10.5194/adgeo-26-93-2010 ◽

2010 ◽

Vol 26 ◽

pp. 93-97 ◽

Cited By ~ 11

Author(s):

E. Bartolini ◽

P. Claps ◽

P. D'Odorico

Keyword(s):

Climate Variability ◽

Snow Cover ◽

Temporal Variability ◽

Large Scale ◽

Management Strategies ◽

The Other ◽

The Arctic ◽

Spatial And Temporal Variability ◽

East Atlantic ◽

The North

Abstract. Winter snowfall and its temporal variability are important factors in the development of water management strategies for snow-dominated regions. For example, mountain regions of Europe rely on snow for recreation, and on snowmelt for water supply and hydropower. It is still unclear whether in these regions the snow regime is undergoing any major significant change. Moreover, snow interannual variability depends on different climatic variables, such as precipitation and temperature, and their interplay with atmospheric and pressure conditions. This paper uses the EASE Grid weekly snow cover and Ice Extent database from the National Snow and Ice Data Center to assess the possible existence of trends in snow cover across Europe. This database provides a representation of snow cover fields in Europe for the period 1972–2006 and is used here to construct snow cover indices, both in time and space. These indices allow us to investigate the historical spatial and temporal variability of European snow cover fields, and to relate them to the modes of climate variability that are known to affect the European climate. We find that both the spatial and temporal variability of snow cover are strongly related to the Arctic Oscillation during wintertime. In the other seasons, weaker correlation appears between snow cover and the other patterns of climate variability, such as the East Atlantic, the East Atlantic West Russia, the North Atlantic Oscillation, the Polar Pattern and the Scandinavian Pattern.

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Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-8-11755-2008 ◽

2008 ◽

Vol 8 (3) ◽

pp. 11755-11819 ◽

Cited By ~ 2

Author(s):

I. Sednev ◽

S. Menon ◽

G. McFarquhar

Keyword(s):

Large Scale ◽

Single Layer ◽

Mixed Phase ◽

The Arctic ◽

Ice Crystal ◽

The North ◽

North Slope Of Alaska ◽

Aerosol Cloud Interactions ◽

Mixed Phase Clouds ◽

Ice Initiation

Abstract. The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9th–10th October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and undersaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors' contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

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Modelled sensitivity of the snow regime to topography, shrub fraction and shrub height

Hydrology and Earth System Sciences ◽

10.5194/hess-18-2375-2014 ◽

2014 ◽

Vol 18 (6) ◽

pp. 2375-2392 ◽

Cited By ~ 24

Author(s):

C. B. Ménard ◽

R. Essery ◽

J. Pomeroy

Keyword(s):

Snow Cover ◽

Energy Budget ◽

Large Scale ◽

Heat Fluxes ◽

The Arctic ◽

Balance Model ◽

Blowing Snow ◽

Shrub Cover ◽

Shrub Expansion ◽

Shrub Tundra

Abstract. Recent studies show that shrubs are colonizing higher latitudes and altitudes in the Arctic. Shrubs affect the wind transport, accumulation and melt of snow, but there have been few sensitivity studies of how shrub expansion might affect snowmelt rates and timing. Here, a three-source energy balance model (3SOM), which calculates vertical and horizontal energy fluxes – thus allowing within-cell advection – between the atmosphere, snow, snow-free ground and vegetation, is introduced. The three-source structure was specifically adopted to investigate shrub–tundra processes associated with patchy snow cover that single- or two-source models fail to address. The ability of the model to simulate the snow regime of an upland tundra valley is evaluated; a blowing snow transport and sublimation model is used to simulate premelt snow distributions and 3SOM is used to simulate melt. Some success at simulating turbulent fluxes in point simulations and broad spatial pattern in distributed runs is shown even if the lack of advection between cells causes melt rates to be underestimated. The models are then used to investigate the sensitivity of the snow regime in the valley to varying shrub cover and topography. Results show that, for domain average shrub fractional cover &leq;0.4, topography dominates the pre- and early melt energy budget but has little influence for higher shrub cover. The increase in domain average sensible heat fluxes and net radiation with increasing shrub cover is more marked without topography where shrubs introduce wind-induced spatial variability of snow and snow-free patches. As snowmelt evolves, differences in the energy budget between simulations with and without topography remain relatively constant and are independent of shrub cover. These results suggest that, to avoid overestimating the effect of shrub expansion on the energy budget of the Arctic, future large-scale investigations should consider wind redistribution of snow, shrub bending and emergence, and sub-grid topography as they affect the variability of snow cover.

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