scholarly journals Trends in Snow Cover Duration Across River Basins in High Mountain Asia From Daily Gap-Filled MODIS Fractional Snow Covered Area

2021 ◽  
Vol 9 ◽  
Author(s):  
Chelsea Ackroyd ◽  
S. McKenzie Skiles ◽  
Karl Rittger ◽  
Joachim Meyer
Keyword(s):  
Snow Cover ◽  
Critical Role ◽  
River Basins ◽  
High Mountain ◽  
Polar Regions ◽  
Snow Cover Area ◽  
Data Limitations ◽  
Snow Cover Duration ◽  
Spectral Mixture ◽  
Syr Darya

High Mountain Asia (HMA) has the largest expanse of snow outside of the polar regions and it plays a critical role in climate and hydrology. In situ monitoring is rare due to terrain complexity and inaccessibility, making remote sensing the most practical way to understand snow patterns in HMA despite relatively short periods of record. Here, trends in snow cover duration were assessed using MODIS between 2002 and 2017 across the headwaters of the region’s primary river basins (Amu Darya, Brahmaputra, Ganges, Indus, and Syr Darya). Data limitations, associated with traditional binary mapping and data gaps due to clouds, were addressed with a daily, spatially and temporally complete, snow cover product that maps the fraction of snow in each pixel using spectral mixture analysis. Trends in fractional snow cover duration (fSCD) were calculated at the annual and monthly scale, and across 1,000 m elevation bands, and compared to trends in binary snow cover duration (SCD). Snow cover is present, on average, for 102 days across all basin headwaters, with the longest duration in western basins and shortest in eastern basins. Broadly, snow cover is in decline, which is most pronounced in elevation bands where snow is most likely to be present and most needed to sustain glaciers. Some of the strongest negative trends in fSCD were in the Syr Darya, which has 13 fewer days between 4,000–5,000 m, and Brahmaputra, which has 31 fewer days between 5,000–6,000 m. The only increasing tendency was found in the Indus between 2,000 and 5,000 m. There were differences between fSCD and SCD trends, due to SCD overestimating snow cover area relative to fSCD.

scholarly journals Variability of snow line elevation, snow cover area and depletion in the main Slovak basins in winters 2001–2014

2016 ◽  
Vol 64 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Pavel Krajčí ◽  
Ladislav Holko ◽  
Juraj Parajka
Keyword(s):  
Snow Cover ◽  
Winter Season ◽  
High Mountain ◽  
Spatial And Temporal Variability ◽  
Considerable Variability ◽  
Snow Cover Area ◽  
The Third ◽  
Snow Line ◽  
Maximum Elevation ◽  
Basin Elevation

Abstract Spatial and temporal variability of snow line (SL) elevation, snow cover area (SCA) and depletion (SCD) in winters 2001–2014 is investigated in ten main Slovak river basins (the Western Carpathians). Daily satellite snow cover maps from MODIS Terra (MOD10A1, V005) and Aqua (MYD10A1, V005) with resolution 500 m are used. The results indicate three groups of basins with similar variability in the SL elevation. The first includes basins with maximum elevations above 1500 m a.s.l. (Poprad, Upper Váh, Hron, Hornád). Winter median SL is equal or close to minimum basin elevation in snow rich winters in these basins. Even in snow poor winters is SL close to the basin mean. Second group consists of mid-altitude basins with maximum elevation around 1000 m a.s.l. (Slaná, Ipeľ, Nitra, Bodrog). Median SL varies between 150 and 550 m a.s.l. in January and February, which represents approximately 40–80% snow coverage. Median SL is near the maximum basin elevation during the snow poor winters. This means that basins are in such winters snow free approximately 50% of days in January and February. The third group includes the Rudava/Myjava and Lower Váh/Danube. These basins have their maximum altitude less than 700 m a.s.l. and only a small part of these basins is covered with snow even during the snow rich winters. The evaluation of SCA shows that snow cover typically starts in December and last to February. In the highest basins (Poprad, Upper Váh), the snow season sometimes tends to start earlier (November) and lasts to March/April. The median of SCA is, however, less than 10% in these months. The median SCA of entire winter season is above 70% in the highest basins (Poprad, Upper Váh, Hron), ranges between 30–60% in the mid-altitude basins (Hornád, Slaná, Ipeľ, Nitra, Bodrog) and is less than 1% in the Myjava/Rudava and Lower Váh/Danube basins. However, there is a considerable variability in seasonal coverage between the years. Our results indicate that there is no significant trend in mean SCA in the period 2001–2014, but periods with larger and smaller SCA exist. Winters in the period 2002–2006 have noticeably larger mean SCA than those in the period 2007–2012. Snow depletion curves (SDC) do not have a simple evolution in most winters. The snowmelt tends to start between early February and the end of March. The snowmelt lasts between 8 and 15 days on average in lowland and high mountain basins, respectively. Interestingly, the variability in SDC between the winters is much larger than between the basins.

scholarly journals Changes in Snow Cover Dynamics over the Indus Basin: Evidences from 2008 to 2018 MODIS NDSI Trends Analysis

2020 ◽  
Vol 12 (17) ◽  
pp. 2782
Author(s):  
Sikandar Ali ◽  
Muhammad Jehanzeb Masud Cheema ◽  
Muhammad Mohsin Waqas ◽  
Muhammad Waseem ◽  
Usman Khalid Awan ◽  
...  
Keyword(s):  
Time Series ◽  
Snow Cover ◽  
River Basins ◽  
Google Earth ◽  
Indus Basin ◽  
Least Squares Regression ◽  
Snow Cover Area ◽  
Standard Product ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Normalized Difference Snow Index

The frozen water reserves on the Earth are not only very dynamic in their nature, but also have significant effects on hydrological response of complex and dynamic river basins. The Indus basin is one of the most complex river basins in the world and receives most of its share from the Asian Water Tower (Himalayas). In such a huge river basin with high-altitude mountains, the regular quantification of snow cover is a great challenge to researchers for the management of downstream ecosystems. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) daily (MOD09GA) and 8-day (MOD09A1) products were used for the spatiotemporal quantification of snow cover over the Indus basin and the western rivers’ catchments from 2008 to 2018. The high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) was used as a standard product with a minimum Normalized Difference Snow Index (NDSI) threshold (0.4) to delineate the snow cover for 120 scenes over the Indus basin on different days. All types of errors of commission/omission were masked out using water, sand, cloud, and forest masks at different spatiotemporal resolutions. The snow cover comparison of MODIS products with Landsat ETM+, in situ snow data and Google Earth imagery indicated that the minimum NDSI threshold of 0.34 fits well compared to the globally accepted threshold of 0.4 due to the coarser resolution of MODIS products. The intercomparison of the time series snow cover area of MODIS products indicated R2 values of 0.96, 0.95, 0.97, 0.96 and 0.98, for the Chenab, Jhelum, Indus and eastern rivers’ catchments and Indus basin, respectively. A linear least squares regression analysis of the snow cover area of the Indus basin indicated a declining trend of about 3358 and 2459 km2 per year for MOD09A1 and MOD09GA products, respectively. The results also revealed a decrease in snow cover area over all the parts of the Indus basin and its sub-catchments. Our results suggest that MODIS time series NDSI analysis is a useful technique to estimate snow cover over the mountainous areas of complex river basins.

scholarly journals Investigating spatiotemporal patterns of snowline altitude at the end of melting season in High Mountain Asia, using cloud-free MODIS snow cover product, 2001–2016

2019 ◽  
Author(s):  
Zhiguang Tang ◽  
Xiaoru Wang ◽  
Jian Wang ◽  
Xin Wang ◽  
Junfeng Wei
Keyword(s):  
Mass Balance ◽  
Snow Cover ◽  
Large Scale ◽  
Tien Shan ◽  
Spatiotemporal Pattern ◽  
High Mountain ◽  
Mountainous Area ◽  
Polar Regions ◽  
Equilibrium Line Altitude ◽  
Melting Season

Abstract. The snowline altitude at the end of melting season (SLA-EMS) can be used as an indicator of the equilibrium line altitude (ELA) and therefore for the annual mass balance of glaciers in certain conditions. High Mountain Asia (HMA) hosts the largest glacier and perennial snow cover concentration outside the polar regions, but the spatiotemporal pattern of SLA-EMS under climate change is poorly understood in there. Here, we develop a method for estimating SLA-EMS over large-scale area by using the cloud-removed MODIS fractional snow cover data, and investigate the spatiotemporal characteristics and trends of SLA-EMS during 2001–2016 over the HMA. The possible linkage between the SLA-EMS and temperature and precipitation changes over the HMA is also investigated. The results are as follows: (1) There are good linear regression relationships (R = −0.66) between the extracted grid (30 km) SLA-EMS and glaciers annual mass balance over the HMA. (2) Generally, the SLA-EMS in the HMA decreases with increase of latitude. And due to the mass elevation effect, it decreases from the high altitude region of Himalayas and inner Tibet to surrounding low mountainous area. (3) The SLA-EMS of HMA generally shows a rising trend in the recent years (2001–2016). In total, 75.3 % (24.2 % with a significant increase) and 16.1 % (less than 1 % with a significant decrease) of the study area show increasing and decreasing trends in SLA-EMS, respectively. The SLA-EMS significant increases in Tien Shan, Inner Tibet, south and east Tibet, east Himalaya and Hengduan Shan. (4) Temperature (especially the summer temperature) trends to be the dominant climatic factor affecting the variations of SLA-EMS over the HMA. Under the background of the generally losing glaciers mass in HMA, if the SLA-EMS continues to rise as a result of global warming, it will accelerate the negative mass balances of the glaciers. This study is an important step towards reconstruction the time series of glacier annual mass balance using SLA-EMS datasets at the scale of HMA to better document the relationships between climate and glaciers.

How is snow cover in global mountain area changing? Detection of snow cover and snow phenology changes by using MODIS imagery over 2000 - 2018

2020 ◽  
Author(s):  
Claudia Notarnicola
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Lower Latitude ◽  
Snow Melt ◽  
Snow Cover Area ◽  
Mountain Areas ◽  
Snow Albedo ◽  
Modis Imagery ◽  
Snow Cover Duration

<p>Mountain areas have raised a lot of attention in the past years, as they are considered sentinel of climate changes. Quantification of snow cover changes and related phenology in global mountain areas can have multiple implications on water resources, ecosystem services, tourism, and energy production [1]. Up to now, several studies have investigated snow cover changes at continental scale and there are several indications of snow cover decline over the Northern Hemisphere [2, 3], despite no study has analyzed snow behavior specifically in mountain areas at global level. In this context, this study investigates the changes in the main snow cover parameters (snow cover area, snow cover duration, snow onset and snow melt) over global mountain areas from 2000 to 2018.</p><p>To proper monitor the evolution of snow changes at global mountain areas and interlinkages with meteorological drivers (air temperature, snowfall), automatic procedures were developed based on MODIS imagery in global mountain areas over the period 2000-2018 by exploiting Google Earth Engine where the whole time series of MODIS is available at a global scale. MODIS snow cover products have the highest resolution available, 500 m, and with daily global acquisitions. From MODIS snow cover areas (MOD10v6), snow phenology parameters were derived, namely snow cover duration, snow onset and snow melt. Together with snow cover and phenology changes, snow albedo changes were assessed, especially in relation to snow onset and melt variability.</p><p>The results of the trend analysis carried with Man-Kendall statistics indicate that around 78% of the global mountain areas present a snow decline. In average, snow cover duration has decreased up to 43 days, and a snow cover area up to 13%. Significant snow cover duration changes can be linked in 58% of the areas to both delayed snow onset, and advanced melt. Few areas show positive changes, mainly during winter time and located in the Northern Hemisphere.</p><p>Considering the relationship with meteorological parameters and albedo, air temperature is detected as the main driver for snow onset and melt, while a mixed effect of air temperature and precipitation dominates the winter season. Moreover, snowmelt timing is strongly related to significant changes in snow albedo during March and April in the Northern Hemisphere. Regarding snow onset changes, it has been detected a latitude amplification for the dependency con air temperature, indicating that the sensitivity of snow onset on temperature changes is amplified going from higher to lower latitude.</p><p><strong> </strong></p><p><strong>References</strong></p><p>[1] Barnett, T.P., Adam J.C., Lettenmaier D.P. Potential impact of a warming climate on water availability in snow-dominated regions, Nature <strong>438</strong> (2005).</p><p>[2] Bormann, K. J., Brown, R. D., Derksen, C., Painter, T. H. Estimating snow-cover trends from space, Nat. Clim. Change<strong> 8</strong>, 924–928 (2018).</p><p>[3] Ye. K. H., & Wu, R. G. Autumn snow cover variability over northern Eurasia and roles of atmospheric circulation. Adv. Atmos. Sci. <strong>34(7)</strong>, 847–858 (2017) doi: 10.1007/s00376-017-6287-z.</p>

scholarly journals Changes in Central Asia’s Water Tower: Past, Present and Future

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Yaning Chen ◽  
Weihong Li ◽  
Haijun Deng ◽  
Gonghuan Fang ◽  
Zhi Li
Keyword(s):  
Snow Cover ◽  
River Runoff ◽  
Average Rate ◽  
Water Storage ◽  
Water Source ◽  
River Basins ◽  
Total Water ◽  
Snow Cover Area ◽  
The North ◽  
Runoff Changes

Abstract The Tienshan Mountains, with its status as “water tower”, is the main water source and ecological barrier in Central Asia. The rapid warming affected precipitation amounts and fraction as well as the original glacier/snowmelt water processes, thereby affecting the runoff and water storage. The ratio of snowfall to precipitation (S/P) experienced a downward trend, along with a shift from snow to rain. Spatially, the snow cover area in Middle Tienshan Mountains decreased significantly, while that in West Tienshan Mountains increased slightly. Approximately 97.52% of glaciers in the Tienshan Mountains showed a retreating trend, which was especially obvious in the North and East Tienshan Mountains. River runoff responds in a complex way to changes in climate and cryosphere. It appears that catchments with a higher fraction of glacierized area showed mainly increasing runoff trends, while river basins with less or no glacierization exhibited large variations in the observed runoff changes. The total water storage in the Tienshan Mountains also experienced a significant decreasing trend in Middle and East Tienshan Mountains, but a slight decreasing trend in West Tienshan Mountains, totally at an average rate of −3.72 mm/a. In future, water storage levels are expected to show deficits for the next half-century.

scholarly journals The Guadalfeo Monitoring Network (Sierra Nevada, Spain): 14 years of measurements to understand the complexity of snow dynamics in semiarid regions

2019 ◽  
Vol 11 (1) ◽  
pp. 393-407 ◽  
Author(s):  
María J. Polo ◽  
Javier Herrero ◽  
Rafael Pimentel ◽  
María J. Pérez-Palazón
Keyword(s):  
Snow Cover ◽  
Sierra Nevada ◽  
Spatial Scales ◽  
Monitoring Network ◽  
Time Lapse ◽  
High Mountain ◽  
Data Sets ◽  
Snow Cover Area ◽  
Semiarid Regions ◽  
Weather Stations

Abstract. This work presents the Guadalfeo Monitoring Network in Sierra Nevada (Spain), a snow monitoring network in the Guadalfeo Experimental Catchment, a semiarid area in southern Europe representative of snowpacks with highly variable dynamics on both annual and seasonal scales and significant topographic gradients. The network includes weather stations that cover the high mountain area in the catchment and time-lapse cameras to capture the variability of the ablation phases on different spatial scales. The data sets consist of continuous meteorological high-frequency records at five automatic weather stations located at different altitudes ranging from 1300 to 2600 m a.s.l. that include precipitation, air temperature, wind speed, air relative humidity and the short- and longwave components of the incoming radiation, dating from 2004 for the oldest station (2510 m a.s.l.) (https://doi.org/10.1594/PANGAEA.895236); additionally, daily data sets of the imagery from two time-lapse cameras are presented, with different scene area (30 m × 30 m, and 2 km2, respectively) and spatial resolution, that consist of fractional snow cover area and snow depth from 2009 (https://doi.org/10.1594/PANGAEA.871706) and snow cover maps for selected dates from 2011 (https://doi.org/10.1594/PANGAEA.898374). Some research applications of these data sets are also included to highlight the value of high-resolution data sources to improve the understanding of snow processes and distribution in highly variable environments. The data sets are available from different open-source sites and provide both the snow hydrology scientific community and other research fields, such as terrestrial ecology, riverine ecosystems or water quality in high mountains, with valuable information of high potential in snow-dominated areas in semiarid regions.

scholarly journals Linear trends of the length of snow-cover season in the Northern Hemisphere as observed by the satellites in the period 1972–2000

2004 ◽  
Vol 38 ◽  
pp. 229-237 ◽  
Author(s):  
Kunio Rikiishi ◽  
Eisuke Hashiya ◽  
Masafumi Imai
Keyword(s):  
Global Warming ◽  
Snow Cover ◽  
Northern Hemisphere ◽  
Rocky Mountains ◽  
Data Center ◽  
High Elevation ◽  
Snow Accumulation ◽  
Snow Cover Area ◽  
Sea Ice Extent ◽  
Snow Cover Duration

AbstractThe dataset of Northern Hemisphere EASE-Grid weekly snow cover and sea-ice extent (U.S. National Snow and Ice Data Center) for the period September 1972–August 2000 is analyzed to examine the possible influence of recent global warming on the seasonal change of snow cover in the Northern Hemisphere. It is found that the total snow-cover area in the 1980s and 1990s is diminished by 36106 km2, and the length of snow-cover season is reduced by 2 –3 weeks, as compared with the 1970s. In general, the contribution from earlier snowmelt is greater than that from delayed snow accumulation. In addition, the maximum snow-cover area during January–February has gradually decreased by about 36106 km2 within the two decades. Geographically, the rate of decrease of snow-cover duration is 50.1 week per year (wpy) in the high-latitude regions such as the Siberian Plains and Northwest Territories of Canada and 40.2 wpy in the high-elevation regions such as the Scandinavian Peninsula, Tibetan Plateau and Rocky Mountains. The earlier snowmelt in the high-elevation regions suggests that the snowfall amounts there are decreasing owing to global warming.

Spatial and temporal variation of snow cover in the Himalayan and Karakorum region using MODIS data (2000-2019)

2020 ◽  
Author(s):  
Jaydeo Kumar Dharpure ◽  
Ajanta Goswami ◽  
Anil V. Kulkarni
Keyword(s):  
Snow Cover ◽  
Geographical Area ◽  
Spatial And Temporal Variation ◽  
Polar Regions ◽  
Regional Variability ◽  
Snow Cover Area ◽  
Modis Data ◽  
Slope Test ◽  
Depletion Curve ◽  
The Mean

<p>The Himalayan and Karakorum (H-K) region comprise the highest amount of snow and ice cover outside the Polar Regions. The H-K region is grouped into four-part, i.e., the Karakorum (KK), Western (WH), Central (CH), and Eastern Himalayas (EH), based on climate and geographic location. The EH and CH mainly feed by summer-monsoon snowfall, whereas the KK and WH are winters accumulated. This regional variability of climate will affect the water availability for hydropower generation, agriculture, and ecosystem. Therefore, the mapping and monitoring of snow cover change over the study area played an essential role in the context of climate change. The snow cover area (SCA) was observed using Moderate-resolution Imaging Spectroradiometer (MODIS) daily snow cover products version 6 during 2000-2019. Different cloud removal techniques (e.g., multi-sensor, temporal, spatial, regional snow line, multiday backward) are applied to reduce the cloud cover pixels over snow pixels of the MODIS data. The mean annual SCA of the H-K region is ∼26.4% of the total geographical area during the study period. The statistical trend analysis of mean monthly, seasonal, and annual SCA is examined using Mann-Kendal and Sen’s slope test. The mean yearly SCA of the H-K region shows an increasing trend during 2000-2009 and start decreasing significantly during 2009-2019. Similar results are observed in the KK, WH, CH, and EH, which shows a decreasing trend of mean annual SCA since 2009. The mean seasonal SCA shows a significant decreasing trend in summer (June to September) and winter (December to February) since 2009, suggesting a seasonal shift or change in snow cover. Overall, the winter shows an insignificant decreasing trend in comparison to the other seasons during 19 hydrological years (2000-01 to 2018-19). The mean monthly minimum SCA observed in August for the KK and WH, July for the CH, and June for the EH. However, the mean maximum SCA in February for the KK, WH, CH, and March for the EH. The snow cover depletion curve suggests that the maximum SCA in February and minimum in August of the entire region during the study period. The seasonal variation of SCA can be highly related to the influence of monsoonal patterns in the region.</p>

scholarly journals Variations of the Snow Water Equivalent in the Ourika Catchment (Morocco) over 2000–2018 Using Downscaled MERRA-2 Data

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1120 ◽  
Author(s):  
Mohamed Baba ◽  
Simon Gascoin ◽  
Lionel Jarlan ◽  
Vincent Simonneaux ◽  
Lahoucine Hanich
Keyword(s):  
Snow Cover ◽  
River Flow ◽  
Snow Water Equivalent ◽  
Temporal Variations ◽  
In Situ Measurements ◽  
High Mountain ◽  
Snow Cover Area ◽  
Mountain Areas ◽  
Snow Water

The Ourika River is an important tributary of the Tensift River in the water-stressed region of Marrakesh (Morocco). The Ourika river flow is dominated by the snow melt contribution from the High Atlas mountains. Despite its importance in terms of water resources, the snow water equivalent (SWE) is poorly monitored in the Ourika catchment. Here, we used MERRA-2 data to run a distributed energy-balance snowpack model (SnowModel) over 2000–2018. MERRA-2 data were downscaled to 250-m spatial resolution using a digital elevation model. The model outputs were compared to in situ measurements of snow depth, precipitation, river flow and remote sensing observations of the snow cover area from MODIS. The results indicate that the model provides an overall acceptable representation of the snow cover dynamics given the coarse resolution of the MERRA-2 forcing. Then, we used the model output to analyze the spatio-temporal variations of the SWE in the Ourika catchment for the first time. We suggest that MERRA-2 data, which are routinely available with a delay of a few weeks, can provide valuable information to monitor the snow resource in high mountain areas without in situ measurements.

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