Estimated seasonal snow cover and snowfall in Japan

The average amounts of seasonal snow cover and snowfall in Japan were calculated as 7.9 × 1013kg and 1.2 × 1014kg, respectively. The mass of seasonal snow cover of a heavy-snowfall winter, 1980–81 (56-Gosetsu), was calculated as 1.3 × 1014kg. The amount of 7.9 × 1013kg was converted to water equivalent of 230 mm on the whole snow-covered area, including snow-prone area. A mean of 370 mm in snow water equivalent was calculated for the snow area where mean snow depth on the ground was more than 10 cm.

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Assessment of MERRA-2 and ERA5 to Model the Snow Water Equivalent in the High Atlas (1981–2019)

Water ◽

10.3390/w13070890 ◽

2021 ◽

Vol 13 (7) ◽

pp. 890

Author(s):

Mohamed Wassim Baba ◽

Abdelghani Boudhar ◽

Simon Gascoin ◽

Lahoucine Hanich ◽

Ahmed Marchane ◽

...

Keyword(s):

River Discharge ◽

Snow Water Equivalent ◽

High Elevation ◽

Water Runoff ◽

High Atlas ◽

Seasonal Snow ◽

Snow Covered Area ◽

Covered Area ◽

Snow Water

Melt water runoff from seasonal snow in the High Atlas range is an essential water resource in Morocco. However, there are only few meteorological stations in the high elevation areas and therefore it is challenging to estimate the distribution of snow water equivalent (SWE) based only on in situ measurements. In this work we assessed the performance of ERA5 and MERRA-2 climate reanalysis to compute the spatial distribution of SWE in the High Atlas. We forced a distributed snowpack evolution model (SnowModel) with downscaled ERA5 and MERRA-2 data at 200 m spatial resolution. The model was run over the period 1981 to 2019 (37 water years). Model outputs were assessed using observations of river discharge, snow height and MODIS snow-covered area. The results show a good performance for both MERRA-2 and ERA5 in terms of reproducing the snowpack state for the majority of water years, with a lower bias using ERA5 forcing.

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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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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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Forward-Looking Assimilation of MODIS-Derived Snow-Covered Area into a Land Surface Model

Journal of Hydrometeorology ◽

10.1175/2008jhm1042.1 ◽

2009 ◽

Vol 10 (1) ◽

pp. 130-148 ◽

Cited By ~ 79

Author(s):

Benjamin F. Zaitchik ◽

Matthew Rodell

Keyword(s):

Snow Cover ◽

Land Surface ◽

Snow Water Equivalent ◽

Land Surface Model ◽

Radiation Budget ◽

Surface Model ◽

Energy Fluxes ◽

Snow Covered Area ◽

Covered Area ◽

Snow Water

Abstract Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow-covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation—SCA indicates only the presence or absence of snow, not snow water equivalent—and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to nonphysical artifacts in the local water balance. In this paper, a novel assimilation algorithm is presented that introduces Moderate Resolution Imaging Spectroradiometer (MODIS) SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm uses observations from up to 72 h ahead of the model simulation to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes during the snow season and, in some regions, on into the following spring.

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Height dependence of the tendency for reduction in seasonal snow cover in the Himalaya and the Tibetan Plateau region, 1966–2001

Annals of Glaciology ◽

10.3189/172756406781811989 ◽

2006 ◽

Vol 43 ◽

pp. 369-377 ◽

Cited By ~ 17

Author(s):

Kunio Rikiishi ◽

Haruka Nakasato

Keyword(s):

Tibetan Plateau ◽

Snow Cover ◽

The Tibetan Plateau ◽

Plateau Region ◽

Seasonal Snow ◽

Snow Covered Area ◽

Covered Area ◽

Height Dependence ◽

Seasonal Snow Cover ◽

The Himalaya

AbstractThe dataset of Northern Hemisphere EASE-Grid Weekly Snow Cover and Sea Ice Extent for the period October 1966-July 2001 is analyzed to examine the height dependence of declining tendencies of seasonal snow cover in the Himalaya and the Tibetan Plateau region (25−45˚ N, 70−110˚E). It is found that the annual mean snow-covered area is decreasing in the Himalaya/Tibet region at a rate of ∼ 1 % a−1, implying that the mean snow-covered area has decreased by one-third from 1966 to 2001. The rate of decrease is largest (1.6%) at the lowest elevations (0−500 m). On the other hand, the length of the snow-cover season is declining at all elevations, with the greatest rate of decline in the 4000−6000 m height range. On the Tibetan Plateau (∼4000−6000 m a.s.l.), the length of the snow-cover season has decreased by 23 days, and the end date for snow cover has advanced by 41 days over this 35 year period. These rates might be somewhat overestimated by the binary definition of snow cover on satellite images. It is likely that the reduction of the snow surface albedo by deposition of Asian dust and anthropogenic aerosols may be at least partly responsible for earlier snowmelt.

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Monitoring snowpack evolution with meteorological reanalysis data in the Atlas Mountains

10.5194/egusphere-egu21-486 ◽

2021 ◽

Author(s):

Wassim Mohamed Baba ◽

Abdelghani Boudhar ◽

Simon Gascoin ◽

Lahoucine Hanich ◽

Ahmed Marchane ◽

...

Keyword(s):

Snow Cover ◽

Snow Water Equivalent ◽

Growing Season ◽

Reanalysis Data ◽

Water Runoff ◽

Snow Cover Area ◽

Seasonal Snow ◽

Atlas Mountains ◽

Snow Water ◽

Seasonal Snow Cover

The seasonal snow cover in the Altas mountains of Morocco is an important resource, mostly because it provides melt-water runoff for irrigation during the crop growing season. However, the knowledge on physical properties of the snowpack (e.g., snow water equivalent (SWE) and snowmelt) is still very limited due to the scarcity or the lack of ground measurements in the elevated area. In this study we suggest that the recent progresses of meteorological reanalysis data (e.g., MERRA-2 and ERA-5) open new perspectives to overcome this issue. We fed a distributed snowpack evolution model (SnowModel) with downscaled ERA-5 and MERRA-2 reanalyses and evaluate their performance to simulate snow cover. The modeling covers the period 1981 to 2019 (37 water years). SnowModel simulations were assessed using observations of river discharge, snow height and snow cover area derived from MODIS.For most of hydrological years, the results show a good performance for both MERRA-2 and ERA-5 with a slight superiority of ERA-5, to reproduce the snowpack state.Key words: snow, snow water equivalent, reanalysis , MERRA-2, ERA-5

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Changes in seasonal snow cover in Hindu Kush-Himalayan region

The Cryosphere Discussions ◽

10.5194/tcd-5-755-2011 ◽

2011 ◽

Vol 5 (2) ◽

pp. 755-777 ◽

Cited By ~ 41

Author(s):

D. R. Gurung ◽

A. V. Kulkarni ◽

A. Giriraj ◽

K. S. Aung ◽

B. Shrestha ◽

...

Keyword(s):

Snow Cover ◽

Linear Trend ◽

Geographical Area ◽

Western Himalaya ◽

Seasonal Snow ◽

Snow Covered Area ◽

Covered Area ◽

Depletion Curve ◽

Hindu Kush ◽

Seasonal Snow Cover

Abstract. The changes in seasonal snow covered area in the Hindu Kush-Himalayan (HKH) region have been examined using Moderate – resolution Imaging Spectroradiometer (MODIS) 8-day standard snow products. The average snow covered area of the HKH region based on satellite data from 2000 to 2010 is 0.76 million km2 which is 18.23% of the total geographical area of the region. The linear trend in annual snow cover from 2000 to 2010 is −1.25±1.13%. This is in consistent with earlier reported decline of the decade from 1990 to 2001. A similar trend for western, central and eastern HKH region is 8.55±1.70%, +1.66% ± 2.26% and 0.82±2.50%, respectively. The snow covered area in spring for HKH region indicates a declining trend (−1.04±0.97%). The amount of annual snowfall is correlated with annual seasonal snow cover for the western Himalaya, indicating that changes in snow cover are primarily due to interannual variations in circulation patterns. Snow cover trends over a decade were also found to vary across seasonally and the region. Snow cover trends for western HKH are positive for all seasons. In central HKH the trend is positive (+15.53±5.69%) in autumn and negative (−03.68&plusmn3.01) in winter. In eastern HKH the trend is positive in summer (+3.35±1.62%) and autumn (+7.74±5.84%). The eastern and western region of HKH has an increasing trend of 10% to 12%, while the central region has a declining trend of 12% to 14% in the decade between 2000 and 2010. Snow cover depletion curve plotted for the hydrological year 2000–2001 reveal peaks in the month of February with subsidiary peaks observed in November and December in all three regions of the HKH.

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Nimbus-7 SMMR Derived Global Snow Cover Parameters

Annals of Glaciology ◽

10.1017/s0260305500000355 ◽

1987 ◽

Vol 9 ◽

pp. 39-44 ◽

Cited By ~ 286

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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Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

The Cryosphere ◽

10.5194/tc-11-1647-2017 ◽

2017 ◽

Vol 11 (4) ◽

pp. 1647-1664 ◽

Cited By ~ 29

Author(s):

Emmy E. Stigter ◽

Niko Wanders ◽

Tuomo M. Saloranta ◽

Joseph M. Shea ◽

Marc F. P. Bierkens ◽

...

Keyword(s):

Kalman Filter ◽

Data Assimilation ◽

Snow Cover ◽

Climate Sensitivity ◽

Snow Depth ◽

Snow Water Equivalent ◽

Snowmelt Runoff ◽

Snow Water ◽

Snow Model

Abstract. Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water equivalent (SWE). Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of) SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF). Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May) and decreases during the late melt season (June to September) as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly) compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

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