scholarly journals Insolation-weighted assessment of northern hemisphere snow-cover and sea-ice variability

2000 ◽  
Vol 27 (19) ◽  
pp. 3061-3064 ◽  
Author(s):  
R. A. Pielke ◽  
G. E. Liston ◽  
A. Robock
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Northern Hemisphere

Actual and insolation-weighted Northern Hemisphere snow cover and sea-ice between 1973–2002

2004 ◽  
Vol 22 (6-7) ◽  
pp. 591-595 ◽  
Author(s):  
R. A. Pielke ◽  
G. E. Liston ◽  
W. L. Chapman ◽  
D. A. Robinson
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Northern Hemisphere

Seasonal variations in the properties and structural composition of sea ice and snow cover in the Bellingshausen and Amundsen Seas, Antarctica

1997 ◽  
Vol 43 (143) ◽  
pp. 138-151 ◽  
Author(s):  
M. O. Jeffries ◽  
K. Morris ◽  
W.F. Weeks ◽  
A. P. Worby
Keyword(s):  
Sea Ice ◽  
Isotopic Composition ◽  
Snow Cover ◽  
Sea Water ◽  
Ice Cores ◽  
Ice Cover ◽  
Snow Accumulation ◽  
Ice Formation ◽  
Frazil Ice ◽  
Core Sets

AbstractSixty-three ice cores were collected in the Bellingshausen and Amundsen Seas in August and September 1993 during a cruise of the R.V. Nathaniel B. Palmer. The structure and stable-isotopic composition (18O/16O) of the cores were investigated in order to understand the growth conditions and to identify the key growth processes, particularly the contribution of snow to sea-ice formation. The structure and isotopic composition of a set of 12 cores that was collected for the same purpose in the Bellingshausen Sea in March 1992 are reassessed. Frazil ice and congelation ice contribute 44% and 26%, respectively, to the composition of both the winter and summer ice-core sets, evidence that the relatively calm conditions that favour congelation-ice formation are neither as common nor as prolonged as the more turbulent conditions that favour frazil-ice growth and pancake-ice formation. Both frazil- and congelation-ice layers have an av erage thickness of 0.12 m in winter, evidence that congelation ice and pancake ice thicken primarily by dynamic processes. The thermodynamic development of the ice cover relies heavily on the formation of snow ice at the surface of floes after sea water has flooded the snow cover. Snow-ice layers have a mean thickness of 0.20 and 0.28 m in the winter and summer cores, respectively, and the contribution of snow ice to the winter (24%) and summer (16%) core sets exceeds most quantities that have been reported previously in other Antarctic pack-ice zones. The thickness and quantity of snow ice may be due to a combination of high snow-accumulation rates and snow loads, environmental conditions that favour a warm ice cover in which brine convection between the bottom and top of the ice introduces sea water to the snow/ice interface, and bottom melting losses being compensated by snow-ice formation. Layers of superimposed ice at the top of each of the summer cores make up 4.6% of the ice that was examined and they increase by a factor of 3 the quantity of snow entrained in the ice. The accumulation of superimposed ice is evidence that melting in the snow cover on Antarctic sea-ice floes ran reach an advanced stage and contribute a significant amount of snow to the total ice mass.

scholarly journals Distribution and Attribution of Terrestrial Snow Cover Phenology Changes over the Northern Hemisphere during 2001–2020

2021 ◽  
Vol 13 (9) ◽  
pp. 1843
Author(s):  
Xiaona Chen ◽  
Yaping Yang ◽  
Yingzhao Ma ◽  
Huan Li
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Onset Date ◽  
Driving Factor ◽  
Climate Variables ◽  
Significance Level ◽  
The Past ◽  
Attribution Analysis ◽  
Altitudinal Distributions ◽  
Melting Season

Snow cover phenology has exhibited dramatic changes in the past decades. However, the distribution and attribution of the hemispheric scale snow cover phenology anomalies remain unclear. Using satellite-retrieved snow cover products, ground observations, and reanalysis climate variables, this study explored the distribution and attribution of snow onset date, snow end date, and snow duration days over the Northern Hemisphere from 2001 to 2020. The latitudinal and altitudinal distributions of the 20-year averaged snow onset date, snow end date, and snow duration days are well represented by satellite-retrieved snow cover phenology matrixes. The validation results by using 850 ground snow stations demonstrated that satellite-retrieved snow cover phenology matrixes capture the spatial variability of the snow onset date, snow end date, and snow duration days at the 95% significance level during the overlapping period of 2001–2017. Moreover, a delayed snow onset date and an earlier snow end date (1.12 days decade−1, p < 0.05) are detected over the Northern Hemisphere during 2001–2020 based on the satellite-retrieved snow cover phenology matrixes. In addition, the attribution analysis indicated that snow end date dominates snow cover phenology changes and that an increased melting season temperature is the key driving factor of snow end date anomalies over the NH during 2001–2020. These results are helpful in understanding recent snow cover change and can contribute to climate projection studies.

scholarly journals Nimbus-7 SMMR Derived Global Snow Cover Parameters

1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
Theoretical Calculations ◽  
Winter Season ◽  
Western China ◽  
High Plains ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Snow covers about 40 million km2of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

scholarly journals Multi-model dynamic climate emulator for solar geoengineering

2016 ◽  
Author(s):  
Douglas G. MacMartin ◽  
Ben Kravitz
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Circulation Model ◽  
Nonlinear Effects ◽  
Accurate Estimate ◽  
Natural Variability ◽  
Sea Ice Extent ◽  
Temperature And Precipitation ◽  
Solar Geoengineering

Abstract. Climate emulators trained on existing simulations can be used to project the climate effects that would result from different possible future pathways of anthropogenic forcing, without relying on general circulation model (GCM) simulations for every possible pathway. We extend this idea to include different amounts of solar geoengineering in addition to different pathways of green-house gas concentrations by training emulators from a multi-model ensemble of simulations from the Geoengineering Model Intercomparison Project (GeoMIP). The emulator is trained on the abrupt 4 x CO2 and a compensating solar reduction simulation (G1), and evaluated by comparing predictions against a simulated 1 % per year CO2 increase and a similarly smaller solar reduction (G2). We find reasonable agreement in most models for predicting changes in temperature and precipitation (including regional effects), and annual-mean Northern hemisphere sea ice extent, with the difference between simulation and prediction typically smaller than natural variability. This verifies that the linearity assumption used in constructing the emulator is sufficient for these variables over the range of forcing considered. Annual-minimum Northern hemisphere sea ice extent is less-well predicted, indicating the limits of the linearity assumption. For future pathways involving relatively small forcing from solar geoengineering, the errors introduced from nonlinear effects may be smaller than the uncertainty due to natural variability, and the emulator prediction may be a more accurate estimate of the forced component of the models' response than an actual simulation would be.

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.

Northern Hemisphere sea ice variability: lag structure and its implications

2007 ◽  
Vol 59 (2) ◽  
pp. 261-272 ◽  
Author(s):  
Jinro Ukita ◽  
Meiji Honda ◽  
Hisashi Nakamura ◽  
Yoshihiro Tachibana ◽  
Donald J. Cavalieri ◽  
...  
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Lag Structure

scholarly journals Nimbus-7 SMMR Derived Global Snow Cover Parameters

1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
Theoretical Calculations ◽  
Winter Season ◽  
Western China ◽  
High Plains ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Snow covers about 40 million km2 of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

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