Snow Cover Dynamics and its Spatio-Temporal Distribution in the Central Higher Himalaya of India

2021 ◽  
Vol 14 (9) ◽  
pp. 15-22
Author(s):  
Masoom Reza ◽  
Ramesh Chandra Joshi
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Geographical Area ◽  
Temporal Distribution ◽  
Melting Rate ◽  
Optical Data ◽  
Snow Cover Area ◽  
Central Himalayas ◽  
Spatio Temporal ◽  
The Impact

Retreating glaciers, changing timber line and decreasing accumulation of snow in the Himalaya are considered the indicators of climate change. In this study, an attempt is made to observe the snow cover change in the higher reaches of the Central Himalayas. Investigation of climate change through snow cover is very important to understand the impact and adaptation in an area. Landsat thematic and multi spectral optical data with a spatial resolution of 60m and 30m are considered for the estimation and extraction of snow cover. Total 3,369 Km2 snow cover area is lost since 1972 out of total geographical area i.e. 17,227 Km2. The accumulation of snow during winter is lower than the melting rate during summer. The current study identified the decrease of 19.6 % snow cover in 47 years since 1972 to 2019. Composite satellite imageries of September to December show that the major part of the study area covered with snow lies above 3600m. Overall observation indicates that in 47 years, permanent snow cover is decreasing in Central Himalayas.

scholarly journals Assessment of the Impact of Climate Change on Snow Distribution and River Flows in a Snow-Dominated Mountainous Watershed in the Western Hindukush–Himalaya, Afghanistan

Hydrology ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 74
Author(s):  
Abdul Haseeb Azizi ◽  
Yoshihiro Asaoka
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
21St Century ◽  
General Circulation ◽  
River Flow ◽  
General Circulation Models ◽  
Snow Cover Area ◽  
River Flows ◽  
Late 21St Century ◽  
The Impact

Projected snow cover and river flows are important for planning and managing water resources in snow-dominated basins of the Himalayas. To quantify the impacts of climate change in the data scarce Panjshir River basin of Afghanistan, this study simulated present and future snow cover area (SCA) distributions with the snow model (SM), and river flows with the snowmelt runoff model (SRM). The SRM used the degree-day factor and precipitation gradient optimized by the SM to simulate river flows. Temperature and precipitation data from eight kinds of general circulation models (GCMs) were used for bias correction. The SM and SRM were first calibrated and validated using 2009–2015 data, and then bias-corrected future climate data were input to the models to simulate future SCA and river flows. Under both the representative concentration pathways (RCP) 4.5 and 8.5, the annual average SCA and river flow were projected to decrease in the mid and late 21st century, although seasonal increases were simulated in some instances. Uncertainty ranges in projected SCA and river flow under RCP 8.5 were small in the mid 21st century and large in the late 21st century. Therefore, climate change is projected to alter high-altitude stream sources in the Hindukush mountains and reduce the amount of water reaching downstream areas.

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.

The optical behaviour of snow during a melting season at Ny Ålesund (Svalbard, Norway)

2021 ◽  
Author(s):  
Roberto Salzano ◽  
Christian Lanconelli ◽  
Giulio Esposito ◽  
Marco Giusto ◽  
Mauro Montagnoli ◽  
...  
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Full Range ◽  
Time Lapse ◽  
Test Site ◽  
Remotely Sensed ◽  
Optical Behaviour ◽  
Remotely Sensed Data ◽  
Snow Cover Area ◽  
Significant Information

<p><span>Polar areas are the most sensitive targets of </span><span>the </span><span>climate change and the continuous monitoring of the cryosphere represents a critical issue. The satellite remote sensing can fill this gap but further integration between remotely-sensed multi-spectral images and field data is crucial to validate retrieval algorithms and climatological models. The optical behaviour of snow, at different wavelengths, provides significant information about the micro-physical characteristics of the surface and this allow to discriminate different snow/ice covers. The aim of this work is to present an approach based on combining unmanned observations on spectral albedo and on the analysis of time-lapse images of sky and ground conditions in a</span><span>n </span><span>Ar</span><span>c</span><span>tic </span><span>test-site </span><span>(Svalbard, Norway). Terrestrial photography can provide, in fact, important information about the cloud cover and support the discrimination between white-sky or clear-sky illuminating conditions. Similarly, time-lapse cameras can provide a detailed description of the snow cover, estimating the fractional snow cover area. The spectral albedo was obtained by a narrow band device that was compared to a full-range commercial system and to remotely sensed data acquired during the 2015 spring/summer period at the </span><span>Amundsen - Nobile</span><span> Climate Change Tower (Ny </span><span>Å</span><span>lesund). The results confirmed the possibility to have continuous observations of the snow surface (microphisical) characteristics and highlighted the opportunity to monitor the spectral variations of snowed surfaces during the melting period. It was possible, </span><span>therefore,</span><span> to estimate spectral indexes, such as NDSI and SWIR albedo, and to found interesting links between both features and air/ground temperatures, wind-speed and precipitations. Different melting phases were detected and different processes were associated with the observed spectral variations.</span></p>

scholarly journals Snow-Cover Area and Runoff Variation under Climate Change in the West Kunlun Mountains

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2246 ◽  
Author(s):  
Ma ◽  
Yan ◽  
Zhao ◽  
Kundzewicz
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
River Basin ◽  
River Flow ◽  
Initial Increase ◽  
Runoff Generation ◽  
The West ◽  
Snow Cover Area ◽  
Kunlun Mountains ◽  
West Kunlun

In recent years, the climate in the arid region of Northwest China has become warmer and wetter; however, glaciers in the north slope of the West Kunlun Mountains (NSWKM) show no obvious recession, and river flow is decreasing or stable. This contrasts with the prevalent response of glaciers to climate change, which is recession and initial increase in glacier discharge followed by decline as retreat continues. We comparatively analyzed multi-timescale variation in temperature–precipitation–snow cover-runoff in the Yarkant River Basin (YRK), Karakax River Basin (KRK), Yurungkax River Basin (YUK), and Keriya River Basin (KRY) in the NSWKM. The Mann–Kendall trend and the mutation–detection method were applied to data obtained from an observation station over the last 60 years (1957–2017) and MODIS snow data (2001–2016). NSWKM temperature and precipitation have continued to increase for nearly 60 years at a mean rate of 0.26 °C/decade and 5.50 mm/decade, respectively, with the most obvious trend (R2 > 0.82) attributed to the KRK and YUK. Regarding changes in the average snow-cover fraction (SCF): YUK (SCF = 44.14%) > YRK (SCF = 38.73%) > KRY (SCF = 33.42%) > KRK (SCF = 33.40%). Between them, the YRK and YUK had decreasing SCA values (slope < −15.39), while the KRK and KRY had increasing SCA values (slope > 1.87). In seasonal variation, the SCF of the three of the basins reaches the maximum value in spring, with the most significant performance in YUK (SCF = 26.4%), except for YRK where SCF in spring was lower than that in winter (−2.6%). The runoff depth of all river basins presented an increasing trend, with the greatest value appearing in the YRK (5.78 mm/decade), and the least value in the YUK (1.58 mm/decade). With the runoff response to climate change, temperature was the main influencing factor of annual and monthly (summer) runoff variations in the YRK, which is consistent with the runoff-generation rule of rivers in arid areas, which mainly rely on ice and snow melt for water supply. However, this rule was not consistent for the YUK and KRK, as it was disturbed by other factors (e.g., slope and slope direction) during runoff generation, resulting in disruptions of their relationship with runoff. This research promotes the study of the response of cold and arid alpine regions to global change and thus better serve regional water resources management.

scholarly journals On the Effect of Red Sea and Topography on Rainfall over Saudi Arabia: Case Study

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 669
Author(s):  
Al-Mutairi ◽  
Abdel Basset ◽  
Morsy ◽  
Abdeldym
Keyword(s):  
Saudi Arabia ◽  
Red Sea ◽  
Sea Water ◽  
Wrf Model ◽  
Temporal Distribution ◽  
Surface Fluxes ◽  
Sensitivity Experiment ◽  
Low Level ◽  
Spatio Temporal ◽  
The Impact

This paper aimed to investigate the impact of Red Sea topography and water on the development and rainfall of a case of cyclogenesis occurs over Saudi Arabia during the period 16–18 November 2015 using the Weather Research and Forecasting (WRF) model. The WRF Control Run (WRF-CR) experiment was performed with presence of actual topography and surface water of the Red Sea, while the other three sensitivity experiments were carried out without (i) Red Sea Topography (NRST), (ii) Red Sea Water (NRSW), and (iii) Red Sea Topography and Water (NRSTW). The simulated rainfall in the control experiment depicts in well agreement with Tropical Rainfall Measurement Mission (TRMM) rainfall estimates in terms of intensity as well as spatio-temporal distribution. Results demonstrate that rainfall intensity and spatio-temporal distribution significantly changes through each sensitivity experiment compared to the WRF-CR, where the significant variation was found in the NRST experiment. The absence of topography (NRST) leads to formation of strong convergence area over the middle of Red Sea which enhanced uplift motion that further strengthened the low-level jet over Red Sea and the surrounding regions, which enhanced the moisture and temperature gradient and created a conditionally unstable atmosphere that favored the development of the cyclonic system. The absence of Red Sea water (NRSW) changed rainfall spatial distribution and reduced its amount by about 30–40% due to affecting of the dynamics of the upward motion and moisture gradient, suggesting that surface fluxes play an important role in regulating the low-level moist air convergence prior to convection initiation and development.

Revealing snow cover dynamics in the Hindu Kush Himalaya over the past decades

2020 ◽  
Author(s):  
Kathrin Naegeli ◽  
Carlo Marin ◽  
Valentina Premier ◽  
Gabriele Schwaizer ◽  
Martin Stengel ◽  
...  
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Satellite Data ◽  
Weather Forecast ◽  
Short Wave ◽  
Climate Modelling ◽  
Snow Cover Area ◽  
Hindu Kush ◽  
Spatio Temporal ◽  
Area Percentage

&lt;p&gt;Knowledge about the snow cover distribution is of high importance for climate studies, weather forecast, hydrological investigations, irrigation or tourism, respectively. The Hindu Kush Himalayan (HKH) region covers almost 3.5 million km&lt;sup&gt;2&lt;/sup&gt; and extends over eight different countries. The region is known as &amp;#8216;water tower&amp;#8217; as it contains the largest volume of ice and snow outside of the polar ice sheets and it is the source of Asia&amp;#8217;s largest rivers. These rivers provide ecosystem services, the basis for livelihoods and most importantly living water for drinking, irrigation, energy production and industry for two billion people, a fourth of the world&amp;#8217;s population, living in the mountains and downstream.&lt;/p&gt;&lt;p&gt;The spatio-temporal variability of snow cover in the HKH is high and studies reported average snow-covered area percentage of 10&amp;#8211;18%, with greater variability in winter (21&amp;#8211;42%) than in summer (2&amp;#8211;4%). However, no study systematically investigated snow cover metrics, such as snow cover area percentage (SCA), snow cover duration (SCD) or snow cover onset (SCOD) and melt-out day (SCMD), for the entire region so far. Here, we thus present unique in-sights of regional and sub-regional snow cover dynamics for the HKH based on almost four decades, an exceptionally long and in view of the climate modelling community valuable timeseries, of satellite data obtained within the ESA CCI+ Snow project.&lt;/p&gt;&lt;p&gt;Our results are based on Advanced Very High Resolution Radiometer (AVHRR) data, collected onboard the polar orbiting satellites NOAA-7 to -19, providing daily, global imagery at a spatial resolution of 5 km. Calibrated and geocoded reflectance data and a consistent cloud mask pre-processed and provided by the ESA Cloud_cci project as global 0.05&amp;#176; composites are used. The retrieval of snow extent considers the high reflectance of snow in the visible spectra and the low reflectance values in the short-wave infrared expressed in the Normalized Difference Snow Index (NDSI). Additional thresholds related to topography and land cover are included to derive the fractional snow cover of every pixel. A temporal gap-filling was applied to mitigate the influence of clouds. Reference snow maps from high-resolution optical satellite data as well as in-situ station data were used to validate the time series.&lt;/p&gt;

Climate change and health in the Eastern Mediterranean countries: a systematic review

2015 ◽  
Vol 30 (3) ◽  
Author(s):  
Yousef S. Khader ◽  
Mostafa Abdelrahman ◽  
Nour Abdo ◽  
Munjed Al-Sharif ◽  
Ahmed Elbetieha ◽  
...  
Keyword(s):  
Climate Change ◽  
Systematic Review ◽  
Eastern Mediterranean ◽  
Geographical Area ◽  
Eastern Mediterranean Region ◽  
Small Sample ◽  
Research Gaps ◽  
Mediterranean Countries ◽  
The Impact ◽  
Climate Change And Health

AbstractTo summarize the existing knowledge of the impact of climate change on health from previous research in the Eastern Mediterranean region (EMR) and identify knowledge and research gaps.Different databases were searched for relevant studies published in the region between 2000 and 2014. The review was limited to studies reporting the impacts of climate change on health or studying associations between meteorological parameters and well-defined human health outcomes.This systematic review of 78 studies identified many knowledge and research gaps. Research linking climate change and health is scarce in the most vulnerable countries of the region. There is limited information regarding how changes in temperature, precipitation and other weather variables might affect the geographic range and incidence of mortality and morbidity from various diseases. Available research has many limitations and shortcomings that arise from inappropriate study designs, poor assessment of exposure and outcomes, questionable sources of data, lack of standardized methods, poor adjustment of confounders, limited geographical area studies, small sample sizes, poor statistical modeling and not testing for possible interactions between exposures.Research and information on the effect of climate change on health are limited. Longitudinal studies over extended periods of time that investigate the link between climate change and health are needed. There is a need for studies to be expanded to include more countries in the region and to include other environmental, social and economic factors that might affect the spread of the disease.

scholarly journals Assessing water resources in China using PRECIS projections and a VIC model

2012 ◽  
Vol 16 (1) ◽  
pp. 231-240 ◽  
Author(s):  
G. Q. Wang ◽  
J. Y. Zhang ◽  
J. L. Jin ◽  
T. C. Pagano ◽  
R. Calow ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Temporal Distribution ◽  
Annual Runoff ◽  
Model Parameters ◽  
Infiltration Capacity ◽  
Climate Conditions ◽  
Vic Model ◽  
Sustainable Water Resources Management ◽  
The Impact

Abstract. Climate change is now a major environmental and developmental issue, and one that will increase the challenge of sustainable water resources management. In order to assess the implications of climate change for water resources in China, we calibrated a Variable Infiltration Capacity (VIC) model with a resolution of 50×50 km2 using data from 125 well-gauged catchments. Based on similarities in climate conditions, soil texture and other variables, model parameters were transferred to other areas not covered by the calibrated catchments. Taking runoff in the period 1961–1990 as a baseline, we studied the impact of climate change on runoff under three emissions scenarios, A2, B2 and A1B. Model findings indicate that annual runoff over China as a whole will probably increase by approximately 3–10% by 2050, but with quite uneven spatial and temporal distribution. The prevailing pattern of "north dry and south wet" in China is likely to be exacerbated under global warming.

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