scholarly journals A spatio-temporal analysis of trends in Northern Hemisphere seasonal snow-cover, 1971-2017

2020 ◽  
Author(s):  
◽  
Michael Ian Allchin
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Temporal Analysis ◽  
Seasonal Snow ◽  
Spatio Temporal ◽  
Seasonal Snow Cover

scholarly journals Global distribution of snow avalanches and changing activity in the Northern Hemisphere due to climate change

1998 ◽  
Vol 26 ◽  
pp. 337-342
Author(s):  
T. G. Glazovskaya
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Lower Boundary ◽  
Active Regions ◽  
Snow Avalanches ◽  
Seasonal Snow ◽  
The World ◽  
Altitudinal Belts ◽  
Using Data ◽  
Seasonal Snow Cover

Snow avalanches occur in the mountains of all continents and climatic zones. The lower boundary of avalanche distribution rises from sea level in polar and temperate zones to 6000 m in the tropics. Four altitudinal belts of avalanching are distinguished: (I) permanent snow; (II) stable seasonal snow cover; (III) unstable snow cover; and (IV) rare snowfalls. Most avalanche-danger areas of the world belong to the stable seasonal snow-cover bell.Using data from a GFDL Q-flux Model, we estimated possible changes of the main characteristics of the avalanche regime in the Northern Hemisphere: depth of snow cover, duration of the avalanche-prone period and number of days with avalanche-prone snowfalls. At the beginning of the twenty-first Century, there will likely be a smoothing of the sharp differences in avalanche activity between various mountain regions of the World. Avalanche activity should be less in the most active regions and it is likely to increase in regions with low avalanche activity.

scholarly journals Seasonal snow cover and climate change in the Hadley Centre GCM

1997 ◽  
Vol 25 ◽  
pp. 362-366 ◽  
Author(s):  
Richard Essery
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Warming ◽  
Land Surface ◽  
Large Impact ◽  
Seasonal Snow ◽  
Sulphate Aerosols ◽  
Hadley Centre ◽  
Seasonal Snow Cover

Northern Hemisphere snow cover varies greatly through the year, and the presence of snow has a large impact on interactions between the land surface and the atmosphere. This paper outlines the representation of snow cover in the Hadley Centre GCM, and compares simulated snow cover with satellite and ground-based observations. Climate warming in a simulation with increased concentrations of CO2 and sulphate aerosols is found to lead to larger reductions in snow cover over North Ameriea and Europe than over Asia.

scholarly journals Global distribution of snow avalanches and changing activity in the Northern Hemisphere due to climate change

1998 ◽  
Vol 26 ◽  
pp. 337-342 ◽  
Author(s):  
T. G. Glazovskaya
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Lower Boundary ◽  
Active Regions ◽  
Snow Avalanches ◽  
Seasonal Snow ◽  
The World ◽  
Altitudinal Belts ◽  
Using Data ◽  
Seasonal Snow Cover

Snow avalanches occur in the mountains of all continents and climatic zones. The lower boundary of avalanche distribution rises from sea level in polar and temperate zones to 6000 m in the tropics. Four altitudinal belts of avalanching are distinguished: (I) permanent snow; (II) stable seasonal snow cover; (III) unstable snow cover; and (IV) rare snowfalls. Most avalanche-danger areas of the world belong to the stable seasonal snow-cover bell. Using data from a GFDL Q-flux Model, we estimated possible changes of the main characteristics of the avalanche regime in the Northern Hemisphere: depth of snow cover, duration of the avalanche-prone period and number of days with avalanche-prone snowfalls. At the beginning of the twenty-first Century, there will likely be a smoothing of the sharp differences in avalanche activity between various mountain regions of the World. Avalanche activity should be less in the most active regions and it is likely to increase in regions with low avalanche activity.

scholarly journals Seasonal snow cover and climate change in the Hadley Centre GCM

1997 ◽  
Vol 25 ◽  
pp. 362-366 ◽  
Author(s):  
Richard Essery
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Warming ◽  
Land Surface ◽  
Large Impact ◽  
Seasonal Snow ◽  
Sulphate Aerosols ◽  
Hadley Centre ◽  
Seasonal Snow Cover

Northern Hemisphere snow cover varies greatly through the year, and the presence of snow has a large impact on interactions between the land surface and the atmosphere. This paper outlines the representation of snow cover in the Hadley Centre GCM, and compares simulated snow cover with satellite and ground-based observations. Climate warming in a simulation with increased concentrations of CO2and sulphate aerosols is found to lead to larger reductions in snow cover over North Ameriea and Europe than over Asia.

scholarly journals Characterising spatio-temporal variability in seasonal snow cover at a regional scale from MODIS data: the Clutha Catchment, New Zealand

2019 ◽  
Vol 23 (8) ◽  
pp. 3189-3217 ◽  
Author(s):  
Todd A. N. Redpath ◽  
Pascal Sirguey ◽  
Nicolas J. Cullen
Keyword(s):  
New Zealand ◽  
Snow Cover ◽  
Temporal Variability ◽  
Catchment Area ◽  
Regional Scale ◽  
Precipitation Variability ◽  
Seasonal Snow ◽  
Temperature And Precipitation ◽  
Spatio Temporal ◽  
Seasonal Snow Cover

Abstract. A 16-year series of daily snow-covered area (SCA) for 2000–2016 is derived from MODIS imagery to produce a regional-scale snow cover climatology for New Zealand's largest catchment, the Clutha Catchment. Filling a geographic gap in observations of seasonal snow, this record provides a basis for understanding spatio-temporal variability in seasonal snow cover and, combined with climatic data, provides insight into controls on variability. Seasonal snow cover metrics including daily SCA, mean snow cover duration (SCD), annual SCD anomaly and daily snowline elevation (SLE) were derived and assessed for temporal trends. Modes of spatial variability were characterised, whilst also preserving temporal signals by applying raster principal component analysis (rPCA) to maps of annual SCD anomaly. Sensitivity of SCD to temperature and precipitation variability was assessed in a semi-distributed way for mountain ranges across the catchment. The influence of anomalous winter air flow, as characterised by HYSPLIT back-trajectories, on SCD variability was also assessed. On average, SCA peaks in late June, at around 30 % of the catchment area, with 10 % of the catchment area sustaining snow cover for > 120 d yr−1. A persistent mid-winter reduction in SCA, prior to a second peak in August, is attributed to the prevalence of winter blocking highs in the New Zealand region. In contrast to other regions globally, no significant decrease in SCD was observed, but substantial spatial and temporal variability was present. rPCA identified six distinct modes of spatial variability, characterising 77 % of the observed variability in SCD. This analysis of SCD anomalies revealed strong spatio-temporal variability beyond that associated with topographic controls, which can result in snow cover conditions being out of phase across the catchment. Furthermore, it is demonstrated that the sensitivity of SCD to temperature and precipitation variability varies significantly across the catchment. While two large-scale climate modes, the SOI and SAM, fail to explain observed variability, specific spatial modes of SCD are favoured by anomalous airflow from the NE, E and SE. These findings illustrate the complexity of atmospheric controls on SCD within the catchment and support the need to incorporate atmospheric processes that govern variability of the energy balance, as well as the re-distribution of snow by wind in order to improve the modelling of future changes in seasonal snow.

Long-term spatio-temporal seasonal snow cover variability in the Hindu Kush Himalaya

2021 ◽  
Author(s):  
Kathrin Naegeli ◽  
Nils Rietze ◽  
Jörg Franke ◽  
Martin Stengel ◽  
Christoph Neuhaus ◽  
...  
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Precipitation Pattern ◽  
Snow Cover Area ◽  
Seasonal Snow ◽  
Hindu Kush ◽  
Spatio Temporal ◽  
Area Percentage ◽  
Seasonal Snow Cover

<p>The Hindu Kush Himalaya (HKH), the worlds ‘water tower’, contains the largest volume of snow and ice outside of the polar ice sheets and is the headwater area of Asia’s largest rivers. Due to the complex topography and its great spatial extent the HKH is characterised by variable temperature and precipitation pattern and thus exhibits large heterogeneity in the presence of seasonal snow cover (SSC). Previous studies usually focused on regional studies of snow cover area percentage or the influence of snow melt on the local hydrological system. Here we present a systematic overview of spatio-temporal SSC variability of the entire HKH region on a climate relevant time scale (four decades).</p><p>Our results are based on Advanced Very High Resolution (AVHRR) data, collected onboard the polar orbiting satellites NOAA-7 to -19, providing daily, global imagery at a spatial resolution of 5 km since 1982 up to today. This unique dataset is exceptionally valuable to derive pixel-based SSC information using a Normalised Difference Snow Cover (NDSI) approach including additional thresholds related to topography and land cover, and developed in the frame of ESA CCI+ snow.  Calibrated and geocoded reflectance data and a consistent cloud mask, derived in the ESA CCI cloud project, are used. A temporal gap-filling was applied to mitigate the influence of clouds. Reference snow maps from high-resolution optical satellite data as well as in-situ station data were used to validate the time series.</p><p>The dataset allows analysis of the state and trends of SSC at regional and sub-regional level. We thus investigated spatio-temporal evolution and long-term variability of SSC for the entire HKH as well as for 14 hydrological basins. We find large spatial difference in the amount of SSC depending on the regional elevation and precipitation characteristics. Furthermore, we investigate SSC phenology, which is directly linked to climate change and thus of high relevance for seasonal water storage and mountain streamflow. Our analysis indicates a significant decline in snow cover area percentage (SCA %) during warm and dry summer month and a decreasing tendency from high winter through spring to early summer. At the hydrological basin level, no significant long-term trend was detected, however, both western and central basins indicate a decrease in SCA % and generally the latest years are strongly negative. Moreover, we examine SCA % anomalies at the highest available temporal frequency (daily information) and reveal an overall shortening of the SSC occurrence and a general decrease of SSC extent in the HKH region.</p>

scholarly journals Charactersing spatio-temporal variability in seasonal snow cover at a regional scale from MODIS data: The Clutha Catchment, New Zealand

2019 ◽  
Author(s):  
Todd A. N. Redpath ◽  
Pascal Sirguey ◽  
Nicolas J. Cullen
Keyword(s):  
New Zealand ◽  
Snow Cover ◽  
Temporal Variability ◽  
Catchment Area ◽  
Regional Scale ◽  
Seasonal Snow ◽  
Temperature And Precipitation ◽  
Spatio Temporal ◽  
Distributed Analysis ◽  
Seasonal Snow Cover

Abstract. A 16-year series of daily snow covered area (SCA) for 2000–2016 is derived from MODIS imagery to produce a regional scale snow cover climatology for New Zealand's largest catchment, the Clutha Catchment. Filling a geographic gap in observations of seasonal snow, this record provides a basis for understanding spatio-temporal variability in seasonal snow cover, and combined with climatic data, provides insight into controls on variability. Metrics including daily SCA, mean snow cover duration (SCD), annual SCD anomaly and daily snowline elevation (SLE) were derived and assessed for temporal trends. Raster principal components analysis (rPCA) was applied to maps of annual SCD anomaly to characterise modes of spatial variability whilst preserving temporal signals. Semi-distributed analysis between SCD and temperature and precipitation anomalies allowed sensitivity of SCD to climatic forcings to be assessed spatially. The influence of anomalous winter air flow, as characterised by HYSPLIT back-trajectories, on SCD variability was also assessed. On average, SCA peaks in late June, at around 30 % of the catchment area, with 10 % of the catchment area sustaining snow cover for > 120 days per year. A reduction in SCA through mid-winter, prior to a second peak in August and persistent throughout the time series is attributed to the prevalence of winter blocking highs in the New Zealand region. In contrast to other regions globally, no significant decrease in SCD was observed. rPCA identified six distinct modes of spatial variability, characterising 77 % of the observed variability in SCD. rPCA and semi-distributed analysis of SCD anomalies reveal strong spatio-temporal variability beyond that associated with topographic controls, which can result in snow cover conditions being out of phase across the catchment. Furthermore, it is demonstrated that the sensitivity of SCD to temperature and precipitation variability varies significantly across the catchment. While two large scale climate modes, the SOI and SAM, fail to explain observed variability, specific spatial modes of SCD are favoured by anomalous airflow from the NE, E and SE. These findings illustrate the complexity of atmospheric controls on SCD within the catchment and support the need to incorporate atmospheric processes that govern variability of the energy balance, as well as the re-distribution of snow by wind in order to improve the modelling of future changes in seasonal snow.

Sign in / Sign up

Export Citation Format

Share Document