Satellite observed changes in the Northern Hemisphere snow cover phenology and the associated radiative forcing and feedback between 1982 and 2013

Snow-induced radiative forcing (SnRF), defined as the instantaneous perturbation of the Earth’s shortwave radiation at the top of the atmosphere (TOA), results from variations in the terrestrial snow cover extent (SCE), and is critical for the regulation of the Earth’s energy budget. However, with the growing seasonal divergence of SCE over the Northern Hemisphere (NH) in the past two decades, novel insights pertaining to SnRF are lacking. Consequently, the contribution of SnRF to TOA shortwave radiation anomalies still remains unclear. Utilizing the latest datasets of snow cover, surface albedo, and albedo radiative kernels, this study investigated the distribution of SnRF over the NH and explored its changes from 2000 to 2019. The 20-year averaged annual mean SnRF in the NH was −1.13 ± 0.05 W m−2, with a weakening trend of 0.0047 Wm−2 yr−1 (p < 0.01) during 2000–2019, indicating that an extra 0.094 W m−2 of shortwave radiation was absorbed by the Earth climate system. Moreover, changes in SnRF were highly correlated with satellite-observed TOA shortwave flux anomalies (r = 0.79, p < 0.05) during 2000–2019. Additionally, a detailed contribution analysis revealed that the SnRF in snow accumulation months, from March to May, accounted for 58.10% of the annual mean SnRF variability across the NH. These results can assist in providing a better understanding of the role of snow cover in Earth’s climate system in the context of climate change. Although the rapid SCE decline over the NH has a hiatus for the period during 2000–2019, SnRF continues to follow a weakening trend. Therefore, this should be taken into consideration in current climate change models and future climate projections.

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

Remote Sensing ◽

10.3390/rs13091843 ◽

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.

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Nimbus-7 SMMR Derived Global Snow Cover Parameters

Annals of Glaciology ◽

10.1017/s0260305500200736 ◽

1987 ◽

Vol 9 ◽

pp. 39-44 ◽

Cited By ~ 200

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.

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

The Cryosphere ◽

10.5194/tc-9-1879-2015 ◽

2015 ◽

Vol 9 (5) ◽

pp. 1879-1893 ◽

Cited By ~ 11

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.

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Global source attribution of sulfate concentration and direct and indirect radiative forcing

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-8903-2017 ◽

2017 ◽

Vol 17 (14) ◽

pp. 8903-8922 ◽

Cited By ~ 20

Author(s):

Yang Yang ◽

Hailong Wang ◽

Steven J. Smith ◽

Richard Easter ◽

Po-Lun Ma ◽

...

Keyword(s):

Southern Hemisphere ◽

Northern Hemisphere ◽

Radiative Forcing ◽

Dimethyl Sulfide ◽

Sulfur Source ◽

Atmospheric Conditions ◽

So2 Emissions ◽

Near Surface ◽

Indirect Radiative Forcing ◽

Global Source

Abstract. The global source–receptor relationships of sulfate concentrations, and direct and indirect radiative forcing (DRF and IRF) from 16 regions/sectors for years 2010–2014 are examined in this study through utilizing a sulfur source-tagging capability implemented in the Community Earth System Model (CESM) with winds nudged to reanalysis data. Sulfate concentrations are mostly contributed by local emissions in regions with high emissions, while over regions with relatively low SO2 emissions, the near-surface sulfate concentrations are primarily attributed to non-local sources from long-range transport. Regional source efficiencies of sulfate concentrations are higher over regions with dry atmospheric conditions and less export, suggesting that lifetime of aerosols, together with regional export, is important in determining regional air quality. The simulated global total sulfate DRF is −0.42 W m−2, with −0.31 W m−2 contributed by anthropogenic sulfate and −0.11 W m−2 contributed by natural sulfate, relative to a state with no sulfur emissions. In the Southern Hemisphere tropics, dimethyl sulfide (DMS) contributes 17–84 % to the total DRF. East Asia has the largest contribution of 20–30 % over the Northern Hemisphere mid- and high latitudes. A 20 % perturbation of sulfate and its precursor emissions gives a sulfate incremental IRF of −0.44 W m−2. DMS has the largest contribution, explaining −0.23 W m−2 of the global sulfate incremental IRF. Incremental IRF over regions in the Southern Hemisphere with low background aerosols is more sensitive to emission perturbation than that over the polluted Northern Hemisphere.

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Nimbus-7 SMMR Derived Global Snow Cover Parameters

Annals of Glaciology ◽

10.3189/s0260305500200736 ◽

1987 ◽

Vol 9 ◽

pp. 39-44 ◽

Cited By ~ 85

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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Differences in snow-induced radiative forcing estimated from satellite and reanalysis surface albedo datasets over the Northern Hemisphere landmass for the overlapping period of 1982–2012

Environmental Research Communications ◽

10.1088/2515-7620/abb3b8 ◽

2020 ◽

Vol 2 (9) ◽

pp. 091001

Author(s):

Chen Xiaona ◽

Liang Shunlin ◽

Yang Yaping

Keyword(s):

Northern Hemisphere ◽

Radiative Forcing ◽

Surface Albedo

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On the role of Eurasian autumn snow cover in dynamical seasonal predictions

10.5194/ems2021-192 ◽

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

<p>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.</p>

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Understanding Land-Atmosphere-Climate Coupling from the Canadian Prairie Dataset

10.20944/preprints201811.0217.v1 ◽

2018 ◽

Author(s):

Alan K Betts ◽

Raymond L Desjardins

Keyword(s):

Snow Cover ◽

Diurnal Cycle ◽

Radiative Forcing ◽

Potential Temperature ◽

Warm Season ◽

Growing Season ◽

Cold Season ◽

Maximum Temperature ◽

Canadian Prairie ◽

Cloud Forcing

Analysis of the hourly Canadian Prairie data for the past 60 years has transformed our quantitative understanding of land-atmosphere-cloud coupling. The key reason is that trained observers made hourly estimates of opaque cloud fraction that obscures the sun, moon or stars, following the same protocol for 60 years at all stations. These 24 daily estimates of opaque cloud data are of sufficient quality that they can be calibrated against Baseline Surface Radiation Network data to give the climatology of the daily short-wave, longwave and total cloud forcing (SWCF, LWCF and CF). This key radiative forcing has not been available previously for climate datasets. Net cloud radiative forcing reverses sign from negative in the warm season to positive in the cold season, when reflective snow reduces the negative SWCF below the positive LWCF. This in turn leads to a large climate discontinuity with snow cover, with a systematic cooling of 10°C or more with snow cover. In addition, snow cover transforms the coupling between cloud cover and the diurnal range of temperature. In the warm season, maximum temperature increases with decreasing cloud, while minimum temperature barely changes; while in the cold season with snow cover, maximum temperature decreases with decreasing cloud and minimum temperature decreases even more. In the warm season, the diurnal ranges of temperature, relative humidity, equivalent potential temperature and the pressure height of the lifting condensation level are all tightly coupled to opaque cloud cover. Given over 600 station-years of hourly data, we are able to extract, perhaps for the first time, the coupling between cloud forcing and the warm season imbalance of the diurnal cycle; which changes monotonically from a warming and drying under clear skies to a cooling and moistening under cloudy skies with precipitation. Because we have the daily cloud radiative forci, which is large, we are able to show that the memory of water storage anomalies, from precipitation and the snowpack, goes back many months. The spring climatology shows the memory of snowfall back through the entire winter, and the memory in summer goes back to the months of snowmelt. Lagged precipitation anomalies modify the thermodynamic coupling of the diurnal cycle to the cloud forcing, and shift the diurnal cycle of mixing ratio which has a double peak. The seasonal extraction of the surface total water storage is a large damping of the interannual variability of precipitation anomalies in the growing season. The large land-use change from summer fallow to intensive cropping, which peaked in the early 1990s, has led to a coupled climate response that has cooled and moistened the growing season, lowering cloud-base, increasing equivalent potential temperature, and increasing precipitation. We show a simplified energy balance of the Prairies during the growing season and its dependence on reflective cloud.

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Representing icebergs in the <i>i</i>LOVECLIM model (version 1.0) – a sensitivity study

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-4353-2014 ◽

2014 ◽

Vol 7 (4) ◽

pp. 4353-4381

Author(s):

M. Bügelmayer ◽

D. M. Roche ◽

H. Renssen

Keyword(s):

Spatial Distribution ◽

Size Distribution ◽

Northern Hemisphere ◽

Radiative Forcing ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Initial Size ◽

Climate Conditions ◽

Melt Water ◽

The Impact

Abstract. Recent modelling studies have indicated that icebergs alter the ocean's state, the thickness of sea ice and the prevailing atmospheric conditions, in short play an active role in the climate system. The icebergs' impact is due to their slowly released melt water which freshens and cools the ocean. The spatial distribution of the icebergs and thus their melt water depends on the forces (atmospheric and oceanic) acting on them as well as on the icebergs' size. The studies conducted so far have in common that the icebergs were moved by reconstructed or modelled forcing fields and that the initial size distribution of the icebergs was prescribed according to present day observations. To address these shortcomings, we used the climate model iLOVECLIM that includes actively coupled ice-sheet and iceberg modules, to conduct 15 sensitivity experiments to analyse (1) the impact of the forcing fields (atmospheric vs. oceanic) on the icebergs' distribution and melt flux, and (2) the effect of the used initial iceberg size on the resulting Northern Hemisphere climate and ice sheet under different climate conditions (pre-industrial, strong/weak radiative forcing). Our results show that, under equilibrated pre-industrial conditions, the oceanic currents cause the bergs to stay close to the Greenland and North American coast, whereas the atmospheric forcing quickly distributes them further away from their calving site. These different characteristics strongly affect the lifetime of icebergs, since the wind-driven icebergs melt up to two years faster as they are quickly distributed into the relatively warm North Atlantic waters. Moreover, we find that local variations in the spatial distribution due to different iceberg sizes do not result in different climate states and Greenland ice sheet volume, independent of the prevailing climate conditions (pre-industrial, warming or cooling climate). Therefore, we conclude that local differences in the distribution of their melt flux do not alter the prevailing Northern Hemisphere climate and ice sheet under equilibrated conditions und constant supply of icebergs. Furthermore, our results suggest that the applied radiative forcing scenarios have a stronger impact on climate than the used initial size distribution of the icebergs.

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