scholarly journals A Response of Snow Cover to the Climate in the Northwest Himalaya (NWH) Using Satellite Products

2021 ◽  
Vol 13 (4) ◽  
pp. 655
Author(s):  
Animesh Choudhury ◽  
Avinash Chand Yadav ◽  
Stefania Bonafoni
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Significant Negative Correlation ◽  
Shuttle Radar Topography Mission ◽  
Vital Role ◽  
Snow Cover Area ◽  
Study Region ◽  
Northwest Himalaya ◽  
The Past ◽  
Average Annual Temperature

The Himalayan region is one of the most crucial mountain systems across the globe, which has significant importance in terms of the largest depository of snow and glaciers for fresh water supply, river runoff, hydropower, rich biodiversity, climate, and many more socioeconomic developments. This region directly or indirectly affects millions of lives and their livelihoods but has been considered one of the most climatically sensitive parts of the world. This study investigates the spatiotemporal variation in maximum extent of snow cover area (SCA) and its response to temperature, precipitation, and elevation over the northwest Himalaya (NWH) during 2000–2019. The analysis uses Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra 8-day composite snow Cover product (MOD10A2), MODIS/Terra/V6 daily land surface temperature product (MOD11A1), Climate Hazards Infrared Precipitation with Station data (CHIRPS) precipitation product, and Shuttle Radar Topography Mission (SRTM) DEM product for the investigation. Modified Mann-Kendall (mMK) test and Spearman’s correlation methods were employed to examine the trends and the interrelationships between SCA and climatic parameters. Results indicate a significant increasing trend in annual mean SCA (663.88 km2/year) between 2000 and 2019. The seasonal and monthly analyses were also carried out for the study region. The Zone-wise analysis showed that the lower Himalaya (184.5 km2/year) and the middle Himalaya (232.1 km2/year) revealed significant increasing mean annual SCA trends. In contrast, the upper Himalaya showed no trend during the study period over the NWH region. Statistically significant negative correlation (−0.81) was observed between annual SCA and temperature, whereas a nonsignificant positive correlation (0.47) existed between annual SCA and precipitation in the past 20 years. It was also noticed that the SCA variability over the past 20 years has mainly been driven by temperature, whereas the influence of precipitation has been limited. A decline in average annual temperature (−0.039 °C/year) and a rise in precipitation (24.56 mm/year) was detected over the region. The results indicate that climate plays a vital role in controlling the SCA over the NWH region. The maximum and minimum snow cover frequency (SCF) was observed during the winter (74.42%) and monsoon (46.01%) season, respectively, while the average SCF was recorded to be 59.11% during the study period. Of the SCA, 54.81% had a SCF above 60% and could be considered as the perennial snow. The elevation-based analysis showed that 84% of the upper Himalaya (UH) experienced perennial snow, while the seasonal snow mostly dominated over the lower Himalaya (LH) and the middle Himalaya (MH).

scholarly journals Variation of snow cover in the Nyang River basin of southeastern Tibetan Plateau, China

2021 ◽  
Author(s):  
Rui Zhang ◽  
Zongxue Xu ◽  
Depeng Zuo ◽  
Chunguang Ban
Keyword(s):  
Snow Cover ◽  
River Basin ◽  
Snow Water Equivalent ◽  
Global Climate ◽  
Remote Sensing Data ◽  
Significant Negative Correlation ◽  
Spatial And Temporal Variation ◽  
Snow Cover Area ◽  
Northern Edge ◽  
Slight Upward Trend

Abstract Snow cover is highly sensitive to global climate change and strongly influences the climate at global and regional scales. Because of limited in situ observations, snow cover dynamics in the Nyang River basin (NRB) have been examined in few studies. Five snow cover indices derived from observation and remote sensing data from 2000 to 2018 were used to investigate the spatial and temporal variation of snow cover in the NRB. There was clear seasonality in the snow cover throughout the entire basin. The maximum snow-covered area was 8,751.35 km2, about 50% of the total basin area, and occurred in March. The maximum snow depth (SD) was 5.35 cm and was found at the northern edge of the middle reaches of the basin. Snow cover frequency, SD, and fraction of snow cover area increased with elevation. The decrease in SD was the most marked in the elevation range of 5,000–6,000 m. Above 6,000 m, the snow water equivalent showed a slight upward trend. There was a significant negative correlation between snow cover and temperature. The results of this study could improve our understanding of changes in snow cover in the NRB from multivariate perspectives. It is better for water resources management.

scholarly journals Effects of shrub and tree cover increase on the near-surface atmosphere in northern Fennoscandia

2017 ◽  
Vol 14 (18) ◽  
pp. 4209-4227 ◽  
Author(s):  
Johanne H. Rydsaa ◽  
Frode Stordal ◽  
Anders Bryn ◽  
Lena M. Tallaksen
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Wrf Model ◽  
Tree Cover ◽  
Atmospheric Response ◽  
Study Region ◽  
Near Surface ◽  
Positive Feedbacks ◽  
Surface Atmosphere ◽  
Northern Fennoscandia

Abstract. Increased shrub and tree cover in high latitudes is a widely observed response to climate change that can lead to positive feedbacks to the regional climate. In this study we evaluate the sensitivity of the near-surface atmosphere to a potential increase in shrub and tree cover in the northern Fennoscandia region. We have applied the Weather Research and Forecasting (WRF) model with the Noah-UA land surface module in evaluating biophysical effects of increased shrub cover on the near-surface atmosphere at a fine resolution (5.4 km  ×  5.4 km). Perturbation experiments are performed in which we prescribe a gradual increase in taller vegetation in the alpine shrub and tree cover according to empirically established bioclimatic zones within the study region. We focus on the spring and summer atmospheric response. To evaluate the sensitivity of the atmospheric response to inter-annual variability in climate, simulations were conducted for two contrasting years, one warm and one cold. We find that shrub and tree cover increase leads to a general increase in near-surface temperatures, with the highest influence seen during the snowmelt season and a more moderate effect during summer. We find that the warming effect is stronger in taller vegetation types, with more complex canopies leading to decreases in the surface albedo. Counteracting effects include increased evapotranspiration, which can lead to increased cloud cover, precipitation, and snow cover. We find that the strength of the atmospheric feedback is sensitive to snow cover variations and to a lesser extent to summer temperatures. Our results show that the positive feedback to high-latitude warming induced by increased shrub and tree cover is a robust feature across inter-annual differences in meteorological conditions and will likely play an important role in land–atmosphere feedback processes in the future.

Dynamics of Maximum Snow Cover Area and Snow Line Altitude Across Nepal (2003-2018) Using Improved MODIS Data

2020 ◽  
Vol 25 (2) ◽  
pp. 17-24
Author(s):  
Nitesh Khadka ◽  
Nitesh Khadka ◽  
Shravan Kumar Ghimire ◽  
Xiaoqing Chen ◽  
Sudeep Thakuri ◽  
...  
Keyword(s):  
Snow Cover ◽  
Monsoon Season ◽  
Temporal Variations ◽  
Vital Role ◽  
Eastern Region ◽  
Snow Cover Area ◽  
Post Monsoon ◽  
Snow Line ◽  
Elevation Zone ◽  
Spatio Temporal

Snow is one of the main components of the cryosphere and plays a vital role in the hydrology and regulating climate. This study presents the dynamics of maximum snow cover area (SCA) and snow line altitude (SLA) across the Western, Central, and Eastern Nepal using improved Moderate Resolution Imaging Spectroradiometer (MODIS; 500 m) data from 2003 to 2018. The results showed a heterogeneous behavior of the spatial and temporal variations of SCA in different months, seasons, and elevation zones across three regions of Nepal. Further, the maximum and minimum SCA was observed in winter (December-February) and post-monsoon (October-November) seasons, respectively. The inter-annual variation of winter SCA showed an overall negative trend of SCA between 2003 to 2018 at the national and regional scales. The SLA was assessed in the post-monsoon season. At the national scale, the SLA lies in an elevation zone of 4500-5000 m, and the approximate SLA of Nepal was 4750 m in 2018. Regionally, the SLA lies in an elevation zone of 4500-5000 m in the Western and Central regions (approx. SLA at 4750 m) and 5000-5500 m in the Eastern region (approx. SLA at 5250 m) in 2018. The SLA fluctuated with the changes in SCA, and the spatio-temporal variations of SLAs were observed in three regions of Nepal. We observed an upward shift of SLA by 33.3 m yr-1 in the Western and Central Nepal and by 66.7 m yr-1 in Eastern Nepal. This study will help to understand the impacts of climate change on snow cover, and the information will be useful for the hydrologist and water resource managers.

scholarly journals Assessment of Snow Cover and Surface Albedo in the ECHAM5 General Circulation Model

2006 ◽  
Vol 19 (16) ◽  
pp. 3828-3843 ◽  
Author(s):  
Andreas Roesch ◽  
Erich Roeckner
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
General Circulation ◽  
Surface Albedo ◽  
Climate Model ◽  
Circulation Model ◽  
Masking Effect ◽  
Second Phase ◽  
Snow Cover Area ◽  
Highly Nonlinear

Abstract Land surface albedo, snow cover fraction (SCF), and snow depth (SD) from two versions of the ECHAM climate model are compared to available ground-based and remote-sensed climatologies. ECHAM5 accurately reproduces the annual cycle of SD and correctly captures the timing of the snowmelt. ECHAM4, in contrast, simulates an excessive Eurasian snow mass in spring due to a delayed snowmelt. Annual cycles of continental snow cover area (SCA) are captured fairly well in both ECHAM4 and ECHAM5. The negative SCA trend observed during the last two decades of the twentieth century is evident also in the ECHAM5 simulation but less pronounced. ECHAM5 captures the interannual variability of SCA reasonably well, which is in contrast with results that were reported earlier for second-phase Atmospheric Model Intercomparison Project (AMIP II) models. An error analysis revealed that, for studies on SCA, it is essential to test the data records for their homogeneity and trends. The second part of the paper compares simulated surface albedos with remote-sensed climatologies derived from PINKER and the Moderate Resolution Imaging Spectroradiometer (MODIS). ECHAM5 is in better agreement with observations in the Himalayan–Tibetan area than ECHAM4. In contrast, the positive surface albedo bias over boreal forests under snow conditions in ECHAM4 is even more pronounced in ECHAM5. This deficiency is mainly due to the neglect of the snow-masking effect of stems and branches after trees have lost their foliage. The analysis demonstrates that positive biases in the SCA are not necessarily related to positive albedo biases. Furthermore, an overestimation of the area-averaged SD is not always related to positive SCF anomalies since the relationship between SD and SCF is highly nonlinear.

scholarly journals Modeling the Spatial Distribution of Snow Cover in the Dudhkoshi Region of the Nepal Himalayas

2012 ◽  
Vol 13 (1) ◽  
pp. 204-222 ◽  
Author(s):  
Maheswor Shrestha ◽  
Lei Wang ◽  
Toshio Koike ◽  
Yongkang Xue ◽  
Yukiko Hirabayashi
Keyword(s):  
Spatial Distribution ◽  
Snow Cover ◽  
Land Surface ◽  
Snow Depth ◽  
Hydrological Model ◽  
Lapse Rate ◽  
Distributed Hydrological Model ◽  
Snow Cover Area ◽  
Temperature Lapse Rate ◽  
Snow Cover Extent

Abstract In this study, a distributed biosphere hydrological model with three-layer energy-balance snow physics [an improved version of the Water and Energy Budget–based Distributed Hydrological Model (WEB-DHM-S)] is applied to the Dudhkoshi region of the eastern Nepal Himalayas to estimate the spatial distribution of snow cover. Simulations are performed at hourly time steps and 1-km spatial resolution for the 2002/03 snow season during the Coordinated Enhanced Observing Period (CEOP) third Enhanced Observing Period (EOP-3). Point evaluations (snow depth and upward short- and longwave radiation) at Pyramid (a station of the CEOP Himalayan reference site) confirm the vertical-process representations of WEB-DHM-S in this region. The simulated spatial distribution of snow cover is evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day maximum snow-cover extent (MOD10A2), demonstrating the model’s capability to accurately capture the spatiotemporal variations in snow cover across the study area. The qualitative pixel-to-pixel comparisons for the snow-free and snow-covered grids reveal that the simulations agree well with the MODIS data to an accuracy of 90%. Simulated nighttime land surface temperatures (LST) are comparable to the MODIS LST (MOD11A2) with mean absolute error of 2.42°C and mean relative error of 0.77°C during the study period. The effects of uncertainty in air temperature lapse rate, initial snow depth, and snow albedo on the snow-cover area (SCA) and LST simulations are determined through sensitivity runs. In addition, it is found that ignoring the spatial variability of remotely sensed cloud coverage greatly increases bias in the LST and SCA simulations. To the authors’ knowledge, this work is the first to adopt a distributed hydrological model with a physically based multilayer snow module to estimate the spatial distribution of snow cover in the Himalayan region.

scholarly journals Quantifying the Added Value of Snow Cover Area Observations in Passive Microwave Snow Depth Data Assimilation

2015 ◽  
Vol 16 (4) ◽  
pp. 1736-1741 ◽  
Author(s):  
Sujay V. Kumar ◽  
Christa D. Peters-Lidard ◽  
Kristi R. Arsenault ◽  
Augusto Getirana ◽  
David Mocko ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Snow Cover ◽  
Land Surface ◽  
Snow Depth ◽  
Accurate Determination ◽  
Passive Microwave ◽  
Added Value ◽  
Surface Model ◽  
Snow Cover Area ◽  
The Impact

Abstract Accurate determination of snow conditions is important for several water management applications, partly because of the significant influence of snowmelt on seasonal streamflow prediction. This article examines an approach using snow cover area (SCA) observations as snow detection constraints during the assimilation of snow depth retrievals from passive microwave sensors. Two different SCA products [the Interactive Multisensor Snow and Ice Mapping System (IMS) and the Moderate Resolution Imaging Spectroradiometer (MODIS)] are employed jointly with the snow depth retrievals from a variety of sensors for data assimilation in the Noah land surface model. The results indicate that the use of MODIS data is effective in obtaining added improvements (up to 6% improvement in aggregate RMSE) in snow depth fields compared to assimilating passive microwave data alone, whereas the impact of IMS data is small. The improvements in snow depth fields are also found to translate to small yet systematic improvements in streamflow estimates, especially over the western United States, the upper Missouri River, and parts of the Northeast and upper Mississippi River. This study thus demonstrates a simple approach for exploiting the information from SCA observations in data assimilation.

scholarly journals Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

2016 ◽  
Vol XLI-B8 ◽  
pp. 353-360 ◽  
Author(s):  
Shaini Naha ◽  
Praveen K. Thakur ◽  
S. P. Aggarwal
Keyword(s):  
Data Assimilation ◽  
Snow Cover ◽  
Land Surface ◽  
Land Surface Model ◽  
Hydrologic Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Surface Model ◽  
Snowmelt Runoff ◽  
Snow Cover Area

The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity) is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH) have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006). Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I) and Ensemble Kalman Filter (EnKF) that uses observations of snow covered area (SCA) to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU), rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD) data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated using observed data from BBMB (Bhakra Beas Management Board) and coefficient of Correlation(R<sup>2</sup>) measured for (2003-2006) was 0.67 and 0.61 for the year 2006.But as VIC does not consider snowmelt runoff as a part of the total discharge, snowmelt runoff has been estimated for the simulation both with and without D.A. The snow fluxes as generated from VIC gives basin average estimates of Snow Cover, SWE, Snow Depth and Snow melt. It has been observed to be overestimated when model predicted snow cover is compared with MODIS SCA of 500 m resolution from MOD10A2 for each year. So MODIS 8-day snow cover area has been assimilated directly into the model state as well as by using EnKF after every 8 days for the year 2006.D.I Technique performed well as compared to EnKF. R<sup>2</sup> between Model SCA and MODIS SCA is estimated as 0.73 after D.I with Root Mean Square Error (RMSE) of +0.19. After direct Insertion of D.A, SCA has been reduced comparatively which resulted in 7% reduction of annual snowmelt contribution to total discharge.The assimilation of MODIS SCA data hence improved the snow cover area (SCA) fraction and finally updated other snow components.

scholarly journals Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

2016 ◽  
Vol XLI-B8 ◽  
pp. 353-360
Author(s):  
Shaini Naha ◽  
Praveen K. Thakur ◽  
S. P. Aggarwal
Keyword(s):  
Data Assimilation ◽  
Snow Cover ◽  
Land Surface ◽  
Land Surface Model ◽  
Hydrologic Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Surface Model ◽  
Snowmelt Runoff ◽  
Snow Cover Area

The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity) is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH) have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006). Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I) and Ensemble Kalman Filter (EnKF) that uses observations of snow covered area (SCA) to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU), rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD) data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated using observed data from BBMB (Bhakra Beas Management Board) and coefficient of Correlation(R<sup>2</sup>) measured for (2003-2006) was 0.67 and 0.61 for the year 2006.But as VIC does not consider snowmelt runoff as a part of the total discharge, snowmelt runoff has been estimated for the simulation both with and without D.A. The snow fluxes as generated from VIC gives basin average estimates of Snow Cover, SWE, Snow Depth and Snow melt. It has been observed to be overestimated when model predicted snow cover is compared with MODIS SCA of 500 m resolution from MOD10A2 for each year. So MODIS 8-day snow cover area has been assimilated directly into the model state as well as by using EnKF after every 8 days for the year 2006.D.I Technique performed well as compared to EnKF. R<sup>2</sup> between Model SCA and MODIS SCA is estimated as 0.73 after D.I with Root Mean Square Error (RMSE) of +0.19. After direct Insertion of D.A, SCA has been reduced comparatively which resulted in 7% reduction of annual snowmelt contribution to total discharge.The assimilation of MODIS SCA data hence improved the snow cover area (SCA) fraction and finally updated other snow components.

Changing Characteristic of Land Surface Evapotranspiration and Soil Moisture in China during the Past 30 Years

2012 ◽  
Vol 14 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Longfei BING ◽  
Hongbo SU ◽  
Quanqin SHAO ◽  
Jiyuan LIU
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
The Past

scholarly journals Use of PRP, PRF and CGF in Periodontal Regeneration and Facial Rejuvenation—A Narrative Review

Biology ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 317
Author(s):  
Eitan Mijiritsky ◽  
Haya Drora Assaf ◽  
Oren Peleg ◽  
Maayan Shacham ◽  
Loredana Cerroni ◽  
...  
Keyword(s):  
Growth Factors ◽  
Platelet Rich Plasma ◽  
Periodontal Regeneration ◽  
Clinical Work ◽  
Gingival Recession ◽  
Vital Role ◽  
Facial Rejuvenation ◽  
Cochrane Library ◽  
The Past ◽  
Autologous Platelet

Growth factors (GFs) play a vital role in cell proliferation, migration, differentiation and angiogenesis. Autologous platelet concentrates (APCs) which contain high levels of GFs make them especially suitable for periodontal regeneration and facial rejuvenation. The main generations of APCs presented are platelet-rich plasma (PRP), platelet-rich fibrin (PRF) and concentrated growth factor (CGF) techniques. The purpose of this review is to provide the clinician with an overview of APCs’ evolution over the past decade in order to give reliable and useful information to be used in clinical work. This review summarizes the most interesting and novel articles published between 1997 and 2020. Electronic and manual searches were conducted in the following databases: Pubmed, Scopus, Cochrane Library and Embase. The following keywords were used: growth factors, VEGF, TGF-b1, PRP, PRF, CGF and periodontal regeneration and/or facial rejuvenation. A total of 73 articles were finally included. The review then addresses the uses of the three different techniques in the two disciplines, as well as the advantages and limitations of each technique. Overall, PRP is mainly used in cases of hard and soft tissue procedures, while PRF is used in gingival recession and the treatment of furcation and intrabony defects; CGF is mainly used in bone regeneration.

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