Spatiotemporal Variation of Snow Cover in Tianshan Mountains, Central Asia, Based on Cloud-Free MODIS Fractional Snow Cover Product, 2001–2015

Tang, Zilong; Wang, Xiaoru; Jian, Wang; Wang, Xin; Li, Hongyi; Jiang, Zongli

doi:10.3390/rs9101045

Cited by 82 publications

(49 citation statements)

References 46 publications

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“…They found statistically significant negative trends in snow cover duration, date of snow cover onset, and date of snowmelt across most of the basin, except trends of earlier snow onset in the Central Pamir, especially at elevations greater than 4000 m . Tang et al (2017) found that maps of snow cover days based on cloud-screened MODIS daily snow products exhibited a high mean (> 85%) consistency with in-situ observations of snow cover days. Their analysis focused on the Tien Shan range divided into four regions of which Central Tien Shan corresponds most closely to our study area.…”

Section: Discussionmentioning

confidence: 80%

“…Their analysis focused on the Tien Shan range divided into four regions of which Central Tien Shan corresponds most closely to our study area. Using simple linear regression to identify and characterize trends, Tang et al (2017) found in the mean snow-covered area in each of four seasons in the Central Tien Shan ranging from a minimum of −8% in autumn to maximum of −14% in spring, but no trend was statistically significant at p < 0.05. They also calculated a decrease of −12% in the duration of snow cover in the Central Tien Shan from 2001-2015, but it was also not significant.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, changes in snow cover and substantial shrinkage of glaciers induce alterations in the local water cycle, changing runoff and groundwater storage. Less precipitation in the form of snow leads to earlier melting of snow, which can eventually shift peak runoff and river flow toward earlier in the year instead of during the summer when demand for water is highest (Barnett et al 2005, Tang et al 2017. Higher increases of temperature are projected for summer and fall seasons, while lower increases are projected during winter (Xu et al 2017), and a significant decrease in precipitation in spring and summer (Hijioka et al 2014, Yuan-An et al 2013.…”

Section: Discussionmentioning

confidence: 99%

“…However, these precipitation projections are highly uncertain (Flato et al 2013, Hijioka et al 2014. The assessment of climate change effects on snow cover is particularly difficult (Tang et al 2017) because those effects strongly vary with geographic context and elevation. Complex terrain generates many local microclimates with different feedbacks making them harder to compare.…”

Section: Discussionmentioning

confidence: 99%

“…Studies in montane Central Asia are relatively few, especially at higher spatial resolutions, but they have all shown significant changes, whether in snow cover (Dietz et al 2013, Tang et al 2017, glacial extent (Aizen et al 1995, Narama et al 2010, or meltwater runoff (Aizen et al 1997, Chevallier et al 2014. Still, there is a notable paucity of studies on the changing environment across montane Central Asia (Hijioka et al 2014, Reyer et al 2017.…”

Section: Introductionmentioning

confidence: 99%

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Changing snow seasonality in the highlands of Kyrgyzstan

Tomaszewska

Henebry

2018

Environ. Res. Lett.

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Few studies have examined changing snow seasonality in Central Asia. Here, we analyzed changes in the seasonality of snow cover across Kyrgyzstan (KGZ) over 14 years from 2002/03-2015/16 using the most recent version (v006) of MODIS Terra and Aqua 8 day snow cover composites (MOD10A2/MYD10A2). We focused on three metrics of snow seasonality-first date of snow, last date of snow, and duration of snow season-and used nonparametric trends tests to assess the significance and direction of trends. We evaluated trends at three administration scales and across elevation. We used two techniques to assure that our identification of significant trends was not resulting from random spatial variation. First, we report only significant trends (positive or negative) that are at least twice as prevalent as the converse trends. Second, we use a two-stage analysis at the national scale to identify asymmetric directional changes in snow seasonality. Results show that more territory has been experiencing earlier onset of snow than earlier snowmelt, and roughly equivalent areas have been experiencing longer and shorter duration of snow seasons in the past 14 years. The changes are not uniform across KGZ, with significant shifts toward earlier snow arrival in western and central KGZ and significant shifts toward earlier snowmelt in eastern KGZ. The duration of the snow season has significantly shortened in western and eastern KGZ and significantly lengthened in northern and southwestern KGZ. Duration is significantly longer where the snow onset was significantly earlier or the snowmelt significantly later. There is a general trend of significantly earlier snowmelt below 3400 m and the area of earlier snowmelt is 15 times greater in eastern than western districts. Significant trends in the Aqua product were less prevalent than in the Terra product, but the general trend toward earlier snowmelt was also evident in Aqua data.

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Section: Discussionmentioning

confidence: 80%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Changing snow seasonality in the highlands of Kyrgyzstan

Tomaszewska

Henebry

2018

Environ. Res. Lett.

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Insight into historical and future spring snow cover from satellite observation and model simulations over the Northern Hemisphere

Guo

Sun²,

Meng³

et al. 2022

Preprint

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Assessment of spring snow cover fraction (SCF) can be valuable for understanding the efficacy of certain Earth system models (ESMs) in simulating the energy exchange between land and atmosphere system, global hydrological cycle and future climate impacts. In this work, we studied the model performance of 23 and 20 ESMs participating CMIP5 and CMIP6 by comparing satellite data from National Oceanic and Atmospheric Administration and National Climatic Data Center (NOAA/NCDC) over the Northern Hemisphere (NH) and its 13 sub-regions and further evaluating potential model improvement from CMIP5 to CMIP6. We found that the mean annual spring SCF that was simulated by CMIP5 and CMIP6 models was underestimated in most of the NH and overestimated on the Tibetan Plateau and in eastern Asia, and most of the model simulations showed a stronger reduction trend as well as an underestimated monthly climatological SCF. However, compared with those in CMIP5, most of the model simulations in CMIP6 had an improved ability to simulate spring SCF in terms of the annual mean, long-term trend and intra-annual variability. We also confirmed that the multi-model ensemble mean (MME) is a better way to represent the three aspects of spring SCF than most individual model simulations. The spring SCF values predicted by the CMIP5 and CMIP6 MMEs over the NH and its 13 sub-regions under different scenarios showed decreasing trends. The decreasing spring SCF trends differed under different scenarios, and the SCF under high emissions scenarios (RCP 8.5 and SSP5-8.5) continued to decrease.

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Inter‐annual variability in snow cover depletion patterns and atmospheric circulation indices in the Upper Irtysh basin, Central Asia

Fugazza

Shaw

Mashtayeva

et al. 2020

Hydrological Processes

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The Irtysh River is the main water resource of Eastern Kazakhstan and its upper basin is severely affected by spring floods each year, primarily as a result of snowmelt. Knowledge of the large‐scale processes that influence the timing of these snow‐induced floods is currently lacking, but critical for the management of water resources in the area. In this study, we evaluated the variability in winter–spring snow cover in five major sub‐basins of the Upper Irtysh basin between 2000 and 2017 as a possible explanatory factor of spring flood events, assessing the time of peak snow cover depletion rate and snow cover disappearance from the moderate‐resolution imaging spectroradiometer (MODIS) MOD10A2 data set. We found that on average, peak snow cover retreat occurs between 22 March and 14 April depending on the basin, with large interannual variations but no clear trend over the MODIS period, while our comparative analysis of longer‐term snow cover extent from the National Oceanic and Atmospheric Administration Climate Data Record data set suggests a shift to earlier snow cover disappearance since the 1970s. In contrast, the annual peak snow cover depletion rate displays a weak increasing trend over the study period and exceeded 5,900 km2/day in 2017. The timing of snow disappearance in spring shows significant correlations of up to 0.82 for the largest basin with winter indices of the Arctic Oscillation (AO) over the region. The primary driver is the impact of the large‐scale pressure anomalies upon the mean spring (MAM) air temperatures and resultant timing of snow cover disappearance, particularly at elevations 500–2,000 m above sea level. This suggests a lagged effect of this atmospheric circulation pattern in spring snow cover retreat. The winter AO index could therefore be incorporated into long‐term runoff forecasts for the Irtysh. Our approach is easily transferable to other similar catchments and could support flood management strategies in Kazakhstan and other countries.

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Spatiotemporal Variation of Snow Cover in Tianshan Mountains, Central Asia, Based on Cloud-Free MODIS Fractional Snow Cover Product, 2001–2015

Cited by 82 publications

References 46 publications

Changing snow seasonality in the highlands of Kyrgyzstan

Changing snow seasonality in the highlands of Kyrgyzstan

Insight into historical and future spring snow cover from satellite observation and model simulations over the Northern Hemisphere

Inter‐annual variability in snow cover depletion patterns and atmospheric circulation indices in the Upper Irtysh basin, Central Asia

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