Slower Snowmelt in Spring Along With Climate Warming Across the Northern Hemisphere

Wu, Xuejiao; Che, Tao; Li, Xin; Wang, Ninglian; Yang, Xiaofan

doi:10.1029/2018gl079511

Cited by 53 publications

(29 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, a strange phenomenon that the variation trend of seasonal maximum SD in the Russian Far East show extremely significant decrease, while it is in inverse in spring. This variation trend of maximum SD in spring analyzed using NHSnow products is consistent with the analysis results using GlobSnow products from recently published study (Wu et al, 2018). It need be pointed out that the significant increase (decrease) area is located around extremely significant increase (decrease) as shown in Figure 8.…”

Section: Variation Of Snow Depthsupporting

confidence: 90%

Spatiotemporal variation of snow depth in the Northern Hemisphere from 1992 to 2016

Xiao¹,

Zhang²,

Zhong³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. Snow cover is an effective best indicator of climate change due to its effect on regional and global surface energy, water balance, hydrology, climate, and ecosystem function. We developed a long term Northern Hemisphere daily snow depth and snow water equivalent product (NHSnow) by the application of the support vector regression (SVR) snow depth retrieval algorithm to historical passive microwave sensors from 1992 to 2016. The accuracies of the snow depth product were evaluated against observed snow depth at meteorological stations along with the other two snow cover products (GlobSnow and ERA-Interim/Land) across the Northern Hemisphere. The evaluation results showed that NHSnow performs generally well with relatively high accuracy. Further analysis were performed across the Northern Hemisphere during 1992–2016, which used snow depth, total snow water equivalent (snow mass) and, snow cover days as indexes. Analysis showed the total snow water equivalent has a significant declining trends (~ 5794 km3 yr−1, 12.5 % reduction). Although spatial variation pattern of snow depth and snow cover days exhibited slight regional differences, it generally reveals a decreasing trend over most of the Northern Hemisphere. Our work provides evidence that rapid changes in snow depth and total snow water equivalent are occurring beginning at the turn of the 21st century with dramatic, surface-based warming.

show abstract

Section: Variation Of Snow Depthsupporting

confidence: 90%

Spatiotemporal variation of snow depth in the Northern Hemisphere from 1992 to 2016

Xiao¹,

Zhang²,

Zhong³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…The seasonal maximum SD variations in fall and winter in Russian Far East exhibit the extremely significant decrease trend, while in spring, it shows an extremely significant increase trend. This variation trend of maximum SD in spring, analyzed using NHSnow products, is consistent with the analysis results obtained using GlobSnow products (Wu et al, 2018),…”

supporting

confidence: 89%

“…The primary reason for the increase of SD may be due to the increase in the frequency of extreme snowfall. Additionally, a recent study found that the greater SWE, the faster melting rate leading to a shortened SCD in the Northern Hemisphere (Wu et al, 2018).…”

mentioning

confidence: 98%

Spatiotemporal variation of snow depth in the Northern Hemisphere from 1992 to 2016

Xiao

Zhang

Zhong

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. Snow cover is an effective indicator of climate change due to its impact on regional and global surface energy and water balance, and thus also weather and climate, hydrological processes and water resources, and the ecosystem as a whole. The overall objective of this study is to investigate changes and variations of snow depth and snow mass over the Northern Hemisphere from 1992 to 2016. We developed a long term Northern Hemisphere daily snow depth and snow water equivalent product (NHSnow) by applying the support vector regression snow depth retrieval algorithm, using passive microwave remote sensing data from the period. NHSnow product was evaluated along with the other two snow cover products (GlobSnow and ERA-Interim/Land) for its accuracy across the Northern Hemisphere. The evaluation results show that NHSnow performs comparably well with relatively high accuracy (bias: −0.59 cm, mean absolute error: 15.12 cm, and root mean square error: 20.11 cm) when benchmarked against the station snow depth measurements. Further analyses were conducted across the Northern Hemisphere using snow depth, snow mass, and snow cover days as indices. Analysis results show that annual average snow mass have a significant declining trend, with a rate of about 19.72 km3 yr.−1 or a 13 % reduction in snow mass. Although spatial variation pattern of snow depth and snow cover days exhibited slight regional differences, they generally reveal the decreasing trend over the most area of the Northern Hemisphere. Our work provides evidence that rapid changes in snow depth and snow mass are occurring since the beginning of the 21st century, accompanied by dramatic climate warming.

show abstract

“…In many regions, especially in cold mountainous watersheds (Dozier et al, 2016;Li & Williams, 2008;Yin et al, 2016), snowmelt runoff supplies the majority of water resources in the middle and lower reaches of these systems. Under rapid climate change, hydrological processes, including snowmelt processes, have been greatly affected (Pachauri et al, 2014;Wu et al, 2018). A series of hydrological responses to temperature and precipitation change, including time shifts and volume changes in springtime snowmelt discharge, have been observed over the past few years in many regions, including North America (Stewart et al, 2004(Stewart et al, , 2009Tang et al, 2019), the Tibetan Plateau (Immerzeel et al, 2010), Europe (Kay, 2016), and central Asia (Yucel et al, 2015); thus, the accurate evaluation of snowmelt contributions will be increasingly important in the future.…”

Section: Introductionmentioning

confidence: 99%

Tracing Snowmelt Paths in an Integrated Hydrological Model for Understanding Seasonal Snowmelt Contribution at Basin Scale

Yang

et al. 2019

JGR Atmospheres

Self Cite

View full text Add to dashboard Cite

Snowmelt contributions to water resources in cold regions are receiving increasing attention. However, there are clear challenges to accurately distinguish the snowmelt contributions to different hydrological processes in seasonal snow regions. Here, we present an improved method to evaluate snowmelt contributions by tracing the snowmelt flow paths in different media based on a distributed geomorphology‐based ecohydrological model coupled with a physically based snow module. The calculated snowmelt contribution is not limited to river discharge but is also applicable to evaporation and soil storage. The study region, the upstream Heihe River (UHR) basin, is located in the northeastern Tibetan Plateau. Our results indicate that snowmelt can continuously contribute to hydrological processes throughout the year because most of the snowmelt remains in soil voids, even on snow‐free days. In UHR, the snowmelt contribution to total runoff on snow days accounts for a minor part of the total snowmelt contribution, and the snowmelt contribution on snow‐free days accounts for a major part of the total. There is notable snowmelt retention in the soil in each year, which continues to supply discharge into next year. Our results also indicate that the role of snowmelt contribution to annual discharge could be gradually weakened if rainfall more greatly increases the summer discharge in the UHR basin. The improved evaluation method will contribute to a more comprehensive assessment of snowmelt contributions to hydrological processes in seasonal snow regions.

show abstract

Slower Snowmelt in Spring Along With Climate Warming Across the Northern Hemisphere

Cited by 53 publications

References 40 publications

Spatiotemporal variation of snow depth in the Northern Hemisphere from 1992 to 2016

Spatiotemporal variation of snow depth in the Northern Hemisphere from 1992 to 2016

Spatiotemporal variation of snow depth in the Northern Hemisphere from 1992 to 2016

Tracing Snowmelt Paths in an Integrated Hydrological Model for Understanding Seasonal Snowmelt Contribution at Basin Scale

Contact Info

Product

Resources

About