scholarly journals A temporally consistent 8-day 0.05° gap-free snow cover extent dataset over the Northern Hemisphere for the period 1981–2019

2021 ◽  
Author(s):  
Xiaona Chen ◽  
Shunlin Liang ◽  
Lian He ◽  
Yaping Yang ◽  
Cong Yin
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Land Surface ◽  
Glass Product ◽  
Aggregation Process ◽  
Climate Data ◽  
Important Indicator ◽  
Continental Scale ◽  
Snow Cover Extent ◽  
Frequency Monitoring

Abstract. Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change due to its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among existing continental scale SCE products hampers its detailed studies. Using the latest Advanced Very High Resolution Radiometer Surface Reflectance (AVHRR-SR) Climate Data Record (CDR) and several ancillary datasets, this study generated a temporally consistent 8-day 0.05° gap-free SCE covering the NH landmass for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. The development of GLASS SCE contains five steps. First, a decision tree algorithm with multiple threshold tests was applied to distinguish snow cover (NHSCE-D) with other land cover types from daily AVHRR-SR CDR. Second, gridcells with cloud cover and invalid observations were filled by two existing daily SCE products. The gap-filled gridcells were further merged with NHSCE-D to generate combined daily SCE over the NH (NHSCE-Dc). Third, an aggregation process was used to detect the maximum SCE and minimum gaps in each 8-day periods from NHSCE-Dc. Forth, the gaps after aggregation process were further filled by the climatology of snow cover probability to generate the gap-free GLASS SCE. Fifth, the validation process was carried out to evaluate the quality of GLASS SCE. Validation results by using 562 Global Historical Climatology Network stations during 1981–2017 (r = 0.61, p < 0.05) and MOD10C2 during 2001–2019 (r = 0.97, p < 0.01) proved that the GLASS SCE product is credible in snow cover frequency monitoring. Moreover, cross-comparison between GLASS SCE and surface albedo during 1982–2018 further confirmed its values in climate changes studies. The GLASS SCE data are available at https://doi.org/10.5281/zenodo.5775238 (Chen et al. 2021).

scholarly journals A long-term Northern Hemisphere snow cover extent data record for climate studies and monitoring

2014 ◽  
Vol 7 (2) ◽  
pp. 669-691 ◽  
Author(s):  
T. W. Estilow ◽  
A. H. Young ◽  
D. A. Robinson
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Environmental Data ◽  
Climatic Data ◽  
Climate Data ◽  
Snow Cover Extent ◽  
Data Record ◽  
Climate Data Record ◽  
Climate Studies

Abstract. This paper describes the long-term, satellite-based visible snow cover extent NOAA climate data record (CDR) currently available for climate studies, monitoring, and model validation. This environmental data product is developed from weekly Northern Hemisphere snow cover extent data that have been digitized from snow cover maps onto a Cartesian grid draped over a polar stereographic projection. The data has a spatial resolution of 190.5 km at 60 ° latitude, are updated monthly, and span from 4 October 1966 to present. The data comprise the longest satellite-based CDR of any environmental variable. Access to the data are provided in netCDF format and are archived by the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA) under the satellite climate data record program (doi:10.7289/V5N014G9). The basic characteristics, history, and evolution of the dataset are presented herein. In general, the CDR provides similar spatial and temporal variability as its widely used predecessor product. Key refinements to the new CDR improve the product's grid accuracy and documentation, and bring metadata into compliance with current standards for climate data records.

scholarly journals Northern Hemisphere spring snow cover variability and change over 1922–2010 including an assessment of uncertainty

2011 ◽  
Vol 5 (1) ◽  
pp. 219-229 ◽  
Author(s):  
R. D. Brown ◽  
D. A. Robinson
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Data ◽  
The Past ◽  
The North ◽  
Central Russia ◽  
Air Temperatures ◽  
Snow Cover Extent ◽  
The North Atlantic Oscillation ◽  
Regional Character

Abstract. An update is provided of Northern Hemisphere (NH) spring (March, April) snow cover extent (SCE) over the 1922–2010 period incorporating the new climate data record (CDR) version of the NOAA weekly SCE dataset, with annual 95% confidence intervals estimated from regression analysis and intercomparison of multiple datasets. The uncertainty analysis indicates a 95% confidence interval in NH spring SCE of ±5–10% over the pre-satellite period and ±3–5% over the satellite era. The multi-dataset analysis shows larger uncertainties monitoring spring SCE over Eurasia (EUR) than North America (NA) due to the more complex regional character of the snow cover variability and larger between-dataset variability over northern Europe and north-central Russia. Trend analysis of the updated SCE series provides evidence that NH spring snow cover extent has undergone significant reductions over the past ~90 yr and that the rate of decrease has accelerated over the past 40 yr. The rate of decrease in March and April NH SCE over the 1970–2010 period is ~0.8 million km2 per decade corresponding to a 7% and 11% decrease in NH March and April SCE respectively from pre-1970 values. In March, most of the change is being driven by Eurasia (NA trends are not significant) but both continents exhibit significant SCE reductions in April. The observed trends in SCE are being mainly driven by warmer air temperatures, with NH mid-latitude air temperatures explaining ~50% of the variance in NH spring snow cover over the 89-yr period analyzed. However, there is also evidence that changes in atmospheric circulation around 1980 involving the North Atlantic Oscillation and Scandinavian pattern have contributed to reductions in March SCE over Eurasia.

scholarly journals Northern Hemisphere spring snow cover variability and change over 1922–2010 including an assessment of uncertainty

2010 ◽  
Vol 4 (4) ◽  
pp. 2483-2512
Author(s):  
R. D. Brown ◽  
D. A. Robinson
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Temperature Sensitivity ◽  
Northern China ◽  
The Tibetan Plateau ◽  
Climate Data ◽  
The Past ◽  
The North ◽  
Snow Cover Extent ◽  
The North Atlantic Oscillation

Abstract. An update is provided of Northern Hemisphere (NH) spring (March, April) snow cover extent (SCE) over the 1922–2010 period incorporating the new climate data record (CDR) version of the NOAA weekly SCE dataset, with annual 95% confidence intervals estimates from regression analysis and intercomparison of multiple datasets. The uncertainty analysis indicated a 95% confidence interval in NH spring SCE of ±5–10% over the pre-satellite period and ±3–5% over the satellite era. The multi-dataset analysis showed there are larger uncertainties monitoring spring SCE over Eurasia (EUR) than North America (NA) due to the more complex regional character of the snow cover variability with the largest dataset uncertainty located over eastern Eurasia in a large region extending from the Tibetan Plateau across northern China. Trend analysis of the updated SCE series provided evidence that NH spring snow cover extent has undergone significant reductions over the past ~90 years and that the rate of decrease has accelerated over the past 40 years. The rate of decrease in March and April NH SCE over the 1970–2010 period is ~7–8 million km2 per 100 years which corresponds to an 8–11% decrease in NH March and April SCE respectively from pre-1970 values. In March, most of the change is being driven by Eurasia (NA trends are not significant) but both continents exhibit significant SCE reductions in April. The observed trends in SCE are consistent with recent warming trends over northern mid-latitude land areas with NH SCE exhibiting significant negative correlations to air temperature anomalies in March and April. The NH spring SCE-temperature sensitivity has remained relatively stable over the period of record although there is some evidence of contrasting changes in temperature sensitivity over both continents in April. There is evidence that changes in atmospheric circulation around 1980 involving the North Atlantic Oscillation and Scandinavian Pattern have contributed to reductions in March SCE over Eurasia.

scholarly journals A long-term Northern Hemisphere snow cover extent data record for climate studies and monitoring

2015 ◽  
Vol 7 (1) ◽  
pp. 137-142 ◽  
Author(s):  
T. W. Estilow ◽  
A. H. Young ◽  
D. A. Robinson
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Environmental Data ◽  
Climate Data ◽  
Data Set ◽  
Snow Cover Extent ◽  
Data Record ◽  
Climate Data Record ◽  
Climate Studies

Abstract. This paper describes the long-term, satellite-based visible snow cover extent National Oceanic and Atmospheric Administration (NOAA) climate data record (CDR) currently available for climate studies, monitoring, and model validation. This environmental data product is developed from weekly Northern Hemisphere snow cover extent data that have been digitized from snow cover maps onto a Cartesian grid draped over a polar stereographic projection. The data have a spatial resolution of 190.6 km at 60° latitude, are updated monthly, and span the period from 4 October 1966 to the present. The data comprise the longest satellite-based CDR of any environmental variable. Access to the data is provided in Network Common Data Form (netCDF) and archived by NOAA's National Climatic Data Center (NCDC) under the satellite Climate Data Record Program (doi:10.7289/V5N014G9). The basic characteristics, history, and evolution of the data set are presented herein. In general, the CDR provides similar spatial and temporal variability to its widely used predecessor product. Key refinements included in the CDR improve the product's grid accuracy and documentation and bring metadata into compliance with current standards for climate data records.

scholarly journals Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere

2015 ◽  
Vol 9 (5) ◽  
pp. 1879-1893 ◽  
Author(s):  
K. Atlaskina ◽  
F. Berninger ◽  
G. de Leeuw
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Land Surface ◽  
Surface Albedo ◽  
Vegetation Index ◽  
Precipitation Amount ◽  
Snow Cover Fraction ◽  
Air Temperatures ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo data for the Northern Hemisphere during the spring months (March–May) were analyzed to determine temporal and spatial changes over snow-covered land surfaces. Tendencies in land surface albedo change north of 50° N were analyzed using data on snow cover fraction, air temperature, vegetation index and precipitation. To this end, the study domain was divided into six smaller areas, based on their geographical position and climate similarity. Strong differences were observed between these areas. As expected, snow cover fraction (SCF) has a strong influence on the albedo in the study area and can explain 56 % of variation of albedo in March, 76 % in April and 92 % in May. Therefore the effects of other parameters were investigated only for areas with 100 % SCF. The second largest driver for snow-covered land surface albedo changes is the air temperature when it exceeds a value between −15 and −10 °C, depending on the region. At monthly mean air temperatures below this value no albedo changes are observed. The Enhanced Vegetation Index (EVI) and precipitation amount and frequency were independently examined as possible candidates to explain observed changes in albedo for areas with 100 % SCF. Amount and frequency of precipitation were identified to influence the albedo over some areas in Eurasia and North America, but no clear effects were observed in other areas. EVI is positively correlated with albedo in Chukotka Peninsula and negatively in eastern Siberia. For other regions the spatial variability of the correlation fields is too high to reach any conclusions.

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

&lt;p&gt;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.&lt;/p&gt;

scholarly journals Fast Warming Has Accelerated Snow Cover Loss during Spring and Summer across the Northern Hemisphere over the Past 52 Years (1967–2018)

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 728
Author(s):  
Xuejiao Wu ◽  
Yongping Shen ◽  
Wei Zhang ◽  
Yinping Long
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Spatial Scales ◽  
Summer Precipitation ◽  
Temperature Changes ◽  
The Past ◽  
Four Seasons ◽  
Snow Cover Extent ◽  
Summer Temperatures ◽  
Substantial Decline

With snow cover changing worldwide in several worrisome ways, it is imperative to determine both the variability in snow cover in greater detail and its relationship with ongoing climate change. Here, we used the satellite-based snow cover extent (SCE) dataset of National Oceanic and Atmospheric Administration (NOAA) to detect SCE variability and its linkages to climate over the 1967–2018 periods across the Northern Hemisphere (NH). Interannually, the time series of SCE across the NH reveal a substantial decline in both spring and summer (−0.54 and −0.71 million km2/decade, respectively), and this decreasing trend corresponded with rising spring and summer temperatures over high-latitude NH regions. Among the four seasons, the temperature rise over the NH was the highest in winter (0.39 °C/decade, p < 0.01). More precipitation in winter was closely related to an increase of winter SCE in mid-latitude areas of NH. Summer precipitation over the NH increased at a significant rate (1.1 mm/decade, p < 0.01), which likely contribute to the accelerated reduction of summer’s SCE across the NH. However, seasonal sensitivity of SCE to temperature changes differed between the Eurasian and North American continents. Thus, this study provides a better understanding of seasonal SCE variability and climatic changes that occurred at regional and hemispheric spatial scales in the past 52 years.

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.

Investigating the Linear and Nonlinear Stationary Wave Response to Anomalous North American Snow Cover

2011 ◽  
Vol 68 (4) ◽  
pp. 904-917 ◽  
Author(s):  
Stefan Sobolowski ◽  
Gavin Gong ◽  
Mingfang Ting
Keyword(s):  
Snow Cover ◽  
North American ◽  
Land Surface ◽  
Large Scale ◽  
Wave Model ◽  
Stationary Wave ◽  
Response Analysis ◽  
Stationary Waves ◽  
Continental Scale ◽  
Wave Response

Abstract 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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