scholarly journals Spatio-Temporal Variation Characteristics of Snow Depth and Snow Cover Days over the Tibetan Plateau

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 307
Author(s):  
Chi Zhang ◽  
Naixia Mou ◽  
Jiqiang Niu ◽  
Lingxian Zhang ◽  
Feng Liu
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Feedback Effect ◽  
Effect Of Temperature ◽  
The Tibetan Plateau ◽  
Reanalysis Dataset ◽  
Spatio Temporal ◽  
The Impact ◽  
Main Factor

Changes in snow cover over the Tibetan Plateau (TP) have a significant impact on agriculture, hydrology, and ecological environment of surrounding areas. This study investigates the spatio-temporal pattern of snow depth (SD) and snow cover days (SCD), as well as the impact of temperature and precipitation on snow cover over TP from 1979 to 2018 by using the ERA5 reanalysis dataset, and uses the Mann–Kendall test for significance. The results indicate that (1) the average annual SD and SCD in the southern and western edge areas of TP are relatively high, reaching 10 cm and 120 d or more, respectively. (2) In the past 40 years, SD (s = 0.04 cm decade−1, p = 0.81) and SCD (s = −2.3 d decade−1, p = 0.10) over TP did not change significantly. (3) The positive feedback effect of precipitation is the main factor affecting SD, while the negative feedback effect of temperature is the main factor affecting SCD. This study improves the understanding of snow cover change and is conducive to the further study of climate change on TP.

scholarly journals Spatio-Temporal Change of Snow Cover and Its Response to Climate over the Tibetan Plateau Based on an Improved Daily Cloud-Free Snow Cover Product

2014 ◽  
Vol 7 (1) ◽  
pp. 169-194 ◽  
Author(s):  
Wei Wang ◽  
Xiaodong Huang ◽  
Jie Deng ◽  
Hongjie Xie ◽  
Tiangang Liang
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Temporal Change ◽  
The Tibetan Plateau ◽  
Spatio Temporal

scholarly journals Observed Relationship of Spring and Summer East Asian Rainfall with Winter and Spring Eurasian Snow

2007 ◽  
Vol 20 (7) ◽  
pp. 1285-1304 ◽  
Author(s):  
Renguang Wu ◽  
Ben P. Kirtman
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Southern Oscillation ◽  
Southern China ◽  
Summer Rainfall ◽  
Wave Pattern ◽  
Summer Monsoon Rainfall ◽  
The Tibetan Plateau

Abstract This study investigates the relationship between spring and summer rainfall in East Asia and the preceding winter and spring snow cover/depth over Eurasia, using station rainfall observations, satellite-observed snow cover, satellite-derived snow water equivalent, and station observations of the number of days of snow cover and snow depth. Correlation analysis shows that snow-depth anomalies can persist from winter to spring whereas snow cover anomalies cannot in most regions of Eurasia. Locally, snow cover and snow-depth anomalies in February are not related in most regions to the north of 50°N, but those anomalies in April display consistent year-to-year variations. The results suggest that the winter snow cover cannot properly represent all the effects of snow and it is necessary to separate the winter and spring snow cover in addressing the snow–monsoon relationship. Spring snow cover in western Siberia is positively correlated with spring rainfall in southern China. The circulation anomalies associated with the western Siberian spring snow cover variations show an apparent wave pattern over the eastern Atlantic through Europe and midlatitude Asia. Spring snow cover over the Tibetan Plateau shows a moderate positive correlation with spring rainfall in southern China. Analysis shows that this correlation includes El Niño–Southern Oscillation (ENSO) effects. In contrast to the Indian summer monsoon rainfall for which the ENSO interferes with the snow effects, the Tibetan Plateau snow cover and ENSO work cooperatively to enhance spring rainfall anomalies in southern China. In comparison, ENSO has larger impacts than the snow on spring rainfall in southern China.

Historical change of winter Tibetan Plateau snow cover and its controlling factors

2021 ◽  
Author(s):  
Shixue Li ◽  
Tomonori Sato ◽  
Tetsu Nakamura
Keyword(s):  
Global Warming ◽  
Tibetan Plateau ◽  
Snow Cover ◽  
Internal Variability ◽  
Controlling Factors ◽  
Historical Change ◽  
The Tibetan Plateau ◽  
Vapor Flux ◽  
The Impact ◽  
Tibetan Plateau Snow Cover

<p>This study investigates the controlling factors of the interannual variability of Tibetan Plateau snow cover (TPSC) in winter. Since snow observation in Tibetan Plateau is limited in space and time, high-resolution multi-satellite data for TPSC were analyzed during 1982-2016. In addition, a large ensemble AGCM experiment from d4PDF (hereafter, HIST), driven by observed SST and anthropogenic forcings were analyzed during 1951-2010 to compare the contributions arising from internal variability and external forcings including the change in greenhouse gases (GHGs) concentration on TPSC variation. In this study TPSC fraction (hereafter, TPSCF) is defined as the percentage of the snow-covered area over the Tibetan Plateau. For both observation and HIST, high and low TPSCF years determined by the standardized January-March TPSCF were analyzed. The range of interannual TPSCF variation (i.e., TPSCF difference between high and low TPSCF years) is about 11% in both observation and the model, suggesting the AGCM well reproduced the TPSCF variability in the interannual timescale. </p><p>We found that high TPSCF is linked to a positive-AO-like pattern. The interannual variation of the observed AO index and TPSCF are significantly correlated. In d4PDF high TPSCF more likely appears with a higher (positive) AO index and vice versa. In high TPSCF years, the subtropical jet is strengthened, which significantly enhances zonal water vapor flux reaching the plateau supporting more precipitation. Another interesting result is a disagreement for ENSO’s contribution to TPSC appears between observation and HIST. However, several members in HIST show a feature close to the observation, in which TPSCF anomalies are not sensitive to the El Niño/La Niña events. Thus, this weak linkage between ENSO and TPSCF is more likely due to the limited cases of observations rather than the model bias. Finally, by comparing HIST and non-warming experiments (NAT), we found historical global warming has decreased the snow-to-rain ratio over TP. Nonetheless, increased precipitation compensates for it. As a result, the impact of historical global warming on TPSCF could be considered negligibly weak.</p>

scholarly journals A Two-Stage Fusion Framework to Generate a Spatio–Temporally Continuous MODIS NDSI Product over the Tibetan Plateau

2019 ◽  
Vol 11 (19) ◽  
pp. 2261 ◽  
Author(s):  
Jing ◽  
Shen ◽  
Li ◽  
Guan
Keyword(s):  
Tibetan Plateau ◽  
Error Correction ◽  
Snow Cover ◽  
Kernel Function ◽  
Annual Variation ◽  
Gaussian Kernel ◽  
The Tibetan Plateau ◽  
Gaussian Kernel Function ◽  
Spatio Temporal ◽  
Fusion Framework

The Tibetan Plateau (TP) is an important component of the global environmental system, on which the snow cover greatly affects the regional climate and ecology. Moderate resolution imaging spectroradiometer (MODIS) snow cover products have been demonstrated to be appropriate for investigating the snow cover over the TP. However, they are subject to cloud obscuration, and the TP’s extremely complex terrain makes the snow monitoring difficult. Therefore, in this paper, we propose a two-stage spatio–temporal fusion framework for the cloud removal of MODIS C6 snow products, including an adjusted Terra and Aqua combination (TAC) and a spatio–temporal fusion based on Gaussian kernel function and error correction (STF-GKF-EC). To the best of our knowledge, this is the first time that a spatio–temporally continuous daily 500-m MODIS normalized difference snow index (NDSI) product has been generated for the TP, which greatly improves the spatial and temporal resolutions of the current snow cover products. The main stage, STF-GKF-EC, adaptively weights the spatial and temporal correlations by the Gaussian kernel function, and further takes the rapid changes of snow cover into consideration through the error correction. The experiments indicated that STF-GKF-EC removes clouds completely, achieving an overall accuracy (OA) and mean absolute error (MAE) of 91.48% and 3.88, respectively. Based on the cloud-removed results, during 2001–2017, as far as the intra-annual variation is concerned, a large proportion of the snow cover appears between October and May, with a peak in February/March, and the variation is mainly controlled by temperature. For the inter-annual variation, an obvious increasing trend of 0.68/year for NDSI is observed before 2005, followed by a slight decreasing trend of 0.16/year, in which precipitation is a better explanation factor than temperature.

scholarly journals Evaluation of snow depth and snow cover over the Tibetan Plateau in global reanalyses using in situ and satellite remote sensing observations

2019 ◽  
Vol 13 (8) ◽  
pp. 2221-2239 ◽  
Author(s):  
Yvan Orsolini ◽  
Martin Wegmann ◽  
Emanuel Dutra ◽  
Boqi Liu ◽  
Gianpaolo Balsamo ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Operating Conditions ◽  
The Tibetan Plateau ◽  
Critical Surface ◽  
High Altitudes ◽  
Medium Range ◽  
In Situ Observations

Abstract. The Tibetan Plateau (TP) region, often referred to as the Third Pole, is the world's highest plateau and exerts a considerable influence on regional and global climate. The state of the snowpack over the TP is a major research focus due to its great impact on the headwaters of a dozen major Asian rivers. While many studies have attempted to validate atmospheric reanalyses over the TP area in terms of temperature or precipitation, there have been – remarkably – no studies aimed at systematically comparing the snow depth or snow cover in global reanalyses with satellite and in situ data. Yet, snow in reanalyses provides critical surface information for forecast systems from the medium to sub-seasonal timescales. Here, snow depth and snow cover from four recent global reanalysis products, namely the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 and ERA-Interim reanalyses, the Japanese 55-year Reanalysis (JRA-55) and the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-2), are inter-compared over the TP region. The reanalyses are evaluated against a set of 33 in situ station observations, as well as against the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover and a satellite microwave snow depth dataset. The high temporal correlation coefficient (0.78) between the IMS snow cover and the in situ observations provides confidence in the station data despite the relative paucity of in situ measurement sites and the harsh operating conditions. While several reanalyses show a systematic overestimation of the snow depth or snow cover, the reanalyses that assimilate local in situ observations or IMS snow cover are better capable of representing the shallow, transient snowpack over the TP region. The latter point is clearly demonstrated by examining the family of reanalyses from the ECMWF, of which only the older ERA-Interim assimilated IMS snow cover at high altitudes, while ERA5 did not consider IMS snow cover for high altitudes. We further tested the sensitivity of the ERA5-Land model in offline experiments, assessing the impact of blown snow sublimation, snow cover to snow depth conversion and, more importantly, excessive snowfall. These results suggest that excessive snowfall might be the primary factor for the large overestimation of snow depth and cover in ERA5 reanalysis. Pending a solution for this common model precipitation bias over the Himalayas and the TP, future snow reanalyses that optimally combine the use of satellite snow cover and in situ snow depth observations in the assimilation and analysis cycles have the potential to improve medium-range to sub-seasonal forecasts for water resources applications.

scholarly journals Snow cover variations across China from 1951–2018

2020 ◽  
Author(s):  
Xiaodong Huang ◽  
Changyu Liu ◽  
Zhaojun Zheng ◽  
Yunlong Wang ◽  
Xubing Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regional Differences ◽  
Meteorological Factors ◽  
Onset Date ◽  
The Tibetan Plateau ◽  
Maximum Snow Depth ◽  
The Postponement

Abstract. Based on a snow depth dataset retrieved from meteorological stations, this experiment explored snow indices, including snow depth (SD), snow covered days (SCDs), and snow phenology variations, across China from 1951 to 2018. The results indicated that the snow cover in China exhibits regional differences. The annual mean SD tended to increase, and the increases in mean and maximum snow depth were 0.04 cm and 0.1 cm per decade, respectively. SCDs tended to increase by approximately 0.5 days per decade. The significant increases were concentrated at latitudes higher than 40° N, especially in Northeast China. However, in the Tibetan Plateau, the SD and SCDs tended to decrease but not significantly. Regarding the snow phenology variations, the snow duration days in China decreased, and 25.2 % of the meteorological stations showed significant decreasing trends. This result was mainly caused by the postponement of the snow onset date and the advancement of the snow end date. Geographical and meteorological factors are closely related to snow cover, especially the change in temperature, which will lead to significant changes in snow depth and phenology.

scholarly journals Evaluation of snow depth and snow-cover over the Tibetan Plateau in global reanalyses using in-situ and satellite remote sensing observations

2019 ◽  
Author(s):  
Yvan Orsolini ◽  
Martin Wegmann ◽  
Emanuel Dutra ◽  
Boqi Liu ◽  
Gianpaolo Balsamo ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Global Climate ◽  
Operating Conditions ◽  
The Tibetan Plateau ◽  
Critical Surface ◽  
High Altitudes ◽  
In Situ Observations

Abstract. The Tibetan Plateau (TP) region, often referred to as the Third Pole and, is the world highest plateau and exerts a considerable influence on regional and global climate. The state of the snowpack over the TP is a major research focus due to its great impacts on the headwaters of a dozen major Asian rivers. While many studies have attempted to validate atmospheric re-analyses over the TP area in terms of temperature or precipitation, there have been – remarkably – no studies aimed at systematically comparing the snow depth or snow cover in global re-analyses with satellite and in-situ data. Yet, snow in re-analyses provides critical surface information for forecast systems from the medium to sub-seasonal time scales. Here, snow depth and snow cover from 5 recent global reanalysis products are inter-compared over the TP region, and evaluated against a set of 33 in-situ station observations, as well as against the Interactive Multi-sensor Snow and Ice Mapping System (or IMS) snow cover and a satellite microwave snow depth dataset. The high temporal correlation coefficient (0.78) between the IMS snow cover and the in-situ observations provides confidence in the station data despite the relative paucity of in-situ measurement sites and the harsh operating conditions. While several re-analyses show a systematic over-estimation of the snow depth or snow cover, the reanalyses that assimilate local in-situ observations or IMS snow-cover are better capable of representing the shallow, transient snowpack over the TP region. The later point is clearly demonstrated by examining the family of re-analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF), of which only the older ERA-Interim assimilated IMS snow cover at high altitudes, while ERA5 did not consider IMS snow cover for high altitudes. One missing process in the re-analyses is the blown snow sublimation, which seems important in the dry, windy and cold conditions of the TP. By incorporating a simple parametrisation of this process in the ECMWF land re-analysis, the positive snow bias is somewhat alleviated. Future snow reanalyses that optimally combine the use of satellite snow cover and in-situ snow-depth observations over the Tibetan Plateau region in the assimilation and analysis cycles, along with improved representation of snow processes, have the potential to substantially improve weather and climate prediction and water resources applications.

scholarly journals Impact of Snow-Darkening by Deposition of Light-Absorbing Aerosols on Snow Cover in the Himalaya-Tibetan-Plateau and Influence on the Asian Monsoon: A Possible Mechanism for the Blanford Hypothesis 

2018 ◽  
Author(s):  
William K. Lau ◽  
Kyu-Myong Kim
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Asian Monsoon ◽  
The Tibetan Plateau ◽  
Surface Solar Radiation ◽  
Gangetic Plain ◽  
Northern India ◽  
Absorbing Aerosols ◽  
The Impact ◽  
The Himalaya

The impact of snow darkening by deposition of light absorbing aerosols (LAAs) on snow cover over the Himalaya-Tibetan-Plateau (HTP) and influence on the Asian monsoon are investigated using the NASA Goddard Earth Observing System Model Version 5 (GEOS-5). We find that during April-May-June, deposition of LAAs on snow leads to a reduction in surface albedo, initiating a sequence of feedback processes, starting with increased surface solar radiation, rapid snowmelt in HTP and warming of the surface and upper troposphere, followed by enhanced low-level southwesterlies and increased dust loading over the Himalayas-Indo-Gangetic Plain. The warming is amplified by increased dust aerosol heating, and subsequently amplified by latent heating from enhanced precipitation over the Himalaya foothills and northern India, via the Elevated Heat Pump (EHP) effect during June-July-August. The reduced snow cover in the HTP anchors the enhanced heating over the Tibetan Plateau and its southern slopes, in conjunction with an enhancement of the Tibetan Anticyclone, and the development of an anomalous Rossby wavetrain over East Asia, leading to weakening of the subtropical westerly jet, and northward displacement and intensification of the Mei-Yu rainbelt. Our results suggest that atmosphere-land heating by LAAs, particularly desert dust play a fundamental role in physical processes underpinning the snow-monsoon relationship proposed by Blandford more than a century ago.

scholarly journals Characterizing Surface Albedo of Shallow Fresh Snow and Its Importance for Snow Ablation on the Interior of the Tibetan Plateau

2020 ◽  
Vol 21 (4) ◽  
pp. 815-827 ◽  
Author(s):  
Wenli Wang ◽  
Kun Yang ◽  
Long Zhao ◽  
Ziyan Zheng ◽  
Hui Lu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Snow Depth ◽  
Surface Model ◽  
Transfer Model ◽  
The Tibetan Plateau ◽  
Ground Truth Data ◽  
Snow Albedo ◽  
Fresh Snow ◽  
The Impact

AbstractSnow depth on the interior of Tibetan Plateau (TP) in state-of-the-art reanalysis products is almost an order of magnitude higher than observed. This huge bias stems primarily from excessive snowfall, but inappropriate process representation of shallow snow also causes excessive snow depth and snow cover. This study investigated the issue with respect to the parameterization of fresh snow albedo. The characteristics of TP snowfall were investigated using ground truth data. Snow in the interior of the TP is usually only some centimeters in depth. The albedo of fresh snow depends on snow depth, and is frequently less than 0.4. Such low albedo values contrast with the high values (~0.8) used in the existing snow schemes of land surface models. The SNICAR radiative transfer model can reproduce the observations that fresh shallow snow has a low albedo value, based on which a fresh snow albedo scheme was derived in this study. Finally, the impact of the fresh snow albedo on snow ablation was examined at 45 meteorological stations on TP using the land surface model Noah-MP which incorporated the new scheme. Allowing albedo to change with snow depth can produce quite realistic snow depths compared with observations. In contrast, the typically assumed fresh snow albedo of 0.82 leads to too large snow depths in the snow ablation period averaged across 45 stations. The shallow snow transparency impact on snow ablation is therefore particularly important in the TP interior, where snow is rather thin and radiation is strong.

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