Seasonal Snow Cover Change Research Articles

Climate and topographic controls on snow phenology dynamics in the Tienshan Mountains, Central Asia

Abstract Although previous studies have characterized changes in seasonal snow cover or made predictions about snow cover in a changing climate, no comprehensive spatiotemporal analysis of snow phenology has been presented for the Tienshan Mountains, Central Asia. Relying on daily cloud-free snow cover fraction products originating from Moderate Resolution Imaging Spectroradiometer (MODIS) for 2002/03–2017/18, the snow phenology parameters (i.e., snow cover duration [SCD], snow onset date [SOD] and snow end date [SED]) are derived for each hydrological year within the study period and the characteristics analyzed for the Tienshan Mountains. The spatiotemporal changes of snow phenology have strong altitude dependence. The mean gradients of SCD, SOD, and SED with elevation are 6.0, −2.55, and 3.44 d/100 m, respectively. Because of differences in solar radiation and water vapor sources, the north-facing areas generally have a higher SCD, earlier SOD, and later SED than south-facing areas. Also, the trends of the snow phenology parameters at high and low altitudes show opposite changes. Consistent with the increase in snow cover area in recent years, SCD for the entire Tienshan region showed a clear uptick, especially in Northern Tienshan. This prolonged SCD was more related to advanced SOD than to SED, as decreased temperature and increased precipitation in autumn are conducive to snow accumulation.

Mapping Glacial Geomorphology and Livelihood Resources in Urgos Watershed, Lahul and Spiti District, Himachal Pradesh, India

The Urgos watershed is situated in the rain shadow zone of the Pir Panjal Range of the Lahul Himalaya, where western disturbances dominate with solid precipitation. Consequently ice, permafrost and snow meltwater is the main source of the Urgos Nala (stream), which supports agriculture and replenishes drinking water sources downstream in the watersheds. The effect of small amount of glacier retreat and changes in seasonal snow cover is critical for the functioning of meltwater and high natural resources dependent mountain communities. Agriculture, vegetation, fodder and pasture land in the watershed are all entirely dependent on meltwater. Therefore, the study aims to make a quantitative and large-scale map of the study area in relation to rural livelihood. Resource mapping (1:5000) and quantitative characterization of Urgos watershed are achieved using high-resolution satellite images, digital elevation models, Total Station mapping, differential Global Positioning System and collection of field evidences. The landform evolution in the watershed is a result of intense glaciofluvial processes in the past as well as present. The geomorphic features mapped in the area reveal multiple glacial advances in the watershed, in the past. This has direct links with climatic fluctuations and its impact on agriculture and allied activities for the sustenance of people. The analysis shows 22.49% area under glacier and only 1.04% area of the entire watershed under agriculture, fodder, pasture and vegetation land. This 1.04% area of the watershed plays a significant role in the livelihood of the people.

Effects of changes in seasonal snow-cover on litter decomposition and soil nitrogen dynamics in forests.

Changes in snow-cover patterns induced by global climate change profoundly influence ecological processes in terrestrial ecosystems, including litter decomposition and soil nutrient cycling. Forest, a major terrestrial ecosystem, plays a crucial role in global biogeochemical cycling. Here, we reviewed the effects of changes in seasonal snow-cover on litter decomposition and soil nitrogen (N) cycling in forests. Global climate change would result in increasing or decreasing seasonal snow-cover depending on local conditions, with direct and indirect effects on forest litter decomposition. The changes in seasonal snow-cover would directly affect decomposition process by changing environmental temperature and moisture, litter quality, and decomposer dynamics, and would indirectly influence decomposition via altering community structure, vegetation phenology, and soil nutrients. Meanwhile, the changes in seasonal snow-cover would modify forest soil N dynamics through changing N enrichment, soil temperature and moisture, freeze-thaw cycle, forest community, subnivean fauna and microorganisms. Further studies in this field should focus on: 1) employing experiments with divergent protocols to simulate diverse changing patterns of seasonal snow-cover under the global climate change scenarios; 2) the effects of the seasonal snowmelt leaching on forest litter decomposition and soil N dynamics; 3) elucidating mechanisms underlying forest litter decomposition and soil N dynamics driven by changes in seasonal snow-cover patterns in different ecosystems and climate zones; and 4) quantifying the instantaneous and prolonged effects of changes in seasonal snow-cover on forest litter decomposition and soil N dynamics in the snow-covered and snow-free seasons, respectively. These studies will provide theoretical basis and solid data support for the understanding and model-prediction of the responses of the biogeochemical cycle in terrestrial ecosystems to global climate change.

What do we know about past changes in the water cycle of Central Asian headwaters? A review

We have reviewed about 100 studies on past changes in climate, snow cover, glaciers and runoff in Central Asian headwater catchments, which have been published in the past 20years. We included studies published by Central Asian researchers in Russian language, which are usually not easily accessible to international researchers.Most studies agreed on general warming trends in Central Asia with acceleration since the 1970s, but varied with regard to seasonal changes and the magnitude of the warming. Most studies also confirmed that glaciers in the Tien Shan and the Pamir continue to retreat and to shrink, though only little is known about mass and volume changes. Only few studies investigated changes in seasonal snow cover, and they suggested a decrease in maximum snow depth and a reduction in snow cover duration. The studies on runoff trends in the high mountain areas of Central Asia indicated a complex response of catchments to changes in climate. It appears that catchments with a higher fraction of glacierized area showed mainly increasing runoff trends in the past, while river basins with less or no glacierization exhibited large variations in the observed runoff changes.We conclude that our knowledge is still incomplete in particular with regard to the magnitude and the spatio-temporal patterns of changes in the water cycle of Central Asian headwater catchments. The limitations in our knowledge are due to (1) the scarcity of reliable and appropriate data sets especially for the glacio-nival zone; (2) methodological limitations of trend analysis; (3) the heterogeneity in both spatial and temporal extent of the available analyses, hampering the synthesis to a regional picture; and (4) the insufficiently understood interactions between changes in highly-variable climate parameters, the cryosphere, and the hydrological response of individual headwater catchments.Finally, there is a need for sound attribution studies linking the observed hydrological changes in individual catchments to particular processes triggered by climatic and cryospheric changes. This research gap needs urgently to be closed as projections of future hydrological changes are of vital importance for water management in Central Asia.

RADIOMETRIC CALIBRATION OF TLS INTENSITY: APPLICATION TO SNOW COVER CHANGE DETECTION

Abstract. This paper reports on the radiometric calibration and the use of calibrated intensity data in applications related to snow cover monitoring with a terrestrial laser scanner (TLS). An application of the calibration method to seasonal snow cover change detection is investigated. The snow intensity from TLS data was studied in Sodankylä, Finland during the years 2008–2009 and in Kirkkonummi, Finland in the winter 2010–2011. The results were used to study the behaviour of TLS intensity data on different types of snow and measurement geometry. The results show that the snow type seems to have little or no effect on the incidence angle behaviour of the TLS intensity and that the laser backscatter from the snow surface is not directly related to any of the snow cover properties, but snow structure has a clear effect on TLS intensity.

Streamflow response to seasonal snow cover mass changes over large Siberian watersheds

We used remotely sensed weekly snow water equivalent (SWE) data (1988–2000) to investigate streamflow response to seasonal snow cover change in the large Siberian watersheds (the Ob, Yenisei, and Lena basins). We quantified the seasonal cycles and variations of snow cover mass and river streamflow and identified a clear correspondence of river discharge to seasonal snow cover mass change. We also examined and compared the weekly mean streamflow with the weekly basin SWE for the study period. The results revealed a strong relation between the streamflow and snow cover mass change during the spring melt season over the large Siberian watersheds. This relationship provides a practical procedure of using remotely sensed snow cover information for snowmelt runoff estimation over the large northern watersheds. Analyses of extreme (high/low) SWE cases (years) and the associated streamflow conditions indicate an association of high (low) flood peak with high (low) maximum SWE in the Ob and Yenisei basins. Comparative analyses of weekly basin SWE data versus snow cover extent (SCE), peak snowmelt floods, and climatic variables (temperature and winter precipitation) indicate consistency among basin SWE, SCE, and temperature but incompatibility between basin SWE and winter precipitation, particularly for the Lena watershed. The inconsistency suggests uncertainties in determination of basin winter snowfall amounts and limitations in applications of the SWE retrieval algorithm over large watersheds/regions with very different physical characteristics. Overall, the results of this study clearly demonstrate that the weekly SWE data/products derived from microwave remote sensing technology are useful in understanding seasonal streamflow changes in the arctic regions.

Snow effect on North American ground temperatures, 1950–2002

Changes in snow's influence on surface ground temperature (SGT) could create a bias in the borehole temperature record of climate change. Using a snow‐ground thermal model which predicts changes in the mean annual offset between SGT and surface air temperature (SAT), we calculate the response of SGT to changes in seasonal snow cover in North America from 1950 to 2002, the period for which comprehensive snow and air observations exist across the region. Daily snow and SAT observations come from the U.S. Historical Climatology Network, the Canadian Daily Climatic Dataset, and a set of National Weather Service cooperative stations in Alaska. For the period 1961–1990 the mean snow onset date in North America is 15 December, with mean snow cover duration of 81 days. There are no significant trends in either onset or duration from 1950 to 2002. Winter season air temperature, however, has warmed during this period, particularly from 1970 to 2002. The effect of the combination of a relatively stationary snow season with winter season SAT warming has been to diminish the mean annual SGT‐SAT offset by −0.05 K/decade over the past 30 years. This effect is most pronounced between 50° and 75°N in west central North America, coincident with the location of greatest winter season warming since 1970. Although comprehensive snow cover data do not exist prior to 1950, this analysis quantifies the changes in snow cover required to account for the difference between borehole temperature and multiproxy climate reconstructions.

Streamflow response to seasonal snow cover extent changes in large Siberian watersheds

This study uses remotely sensed long‐term (1966–1999) weekly snow cover extent data to investigate snowmelt runoff response to seasonal snow cover change in the large Siberian watersheds (Ob, Yenisei, and Lena basins). It quantified the seasonal cycles and variations of snow cover extent and river streamflow and identified a clear correspondence of river streamflow to seasonal snow cover extent change; i.e., an association of low streamflow with high snow cover extent during the cold season and an increase in discharge associated with a decrease of snow cover extent during the melt periods. This study also examined and compared the weekly mean streamflow with the weekly basin snow cover extent for the study period. The results revealed a very strong linkage between the streamflow and snow cover extent change during the spring melt season over the large Siberian watersheds and developed a statistically significant weekly runoff‐snow cover relation. This relation suggests a practical procedure of using remotely sensed snow cover information for snowmelt runoff forecasting over the large northern watersheds. Analyses of extreme (high/low) streamflow cases (years) and the associated snow cover conditions indicate an association of high (low) flood peak with late (early) snowmelt in the Ob and Yenisei basins. Comparisons of snowmelt timing with peak flow show different associations between these two variables among the large Siberian rivers. These results demonstrate that the NOAA weekly snow cover extent data are useful for understanding and predicting streamflow changes in the Arctic regions. Snow cover water equivalent data/products obtained by remote sensing technology and in situ snow observations are currently being examined for what we expect will eventually improve hydrologic forecasts over the large northern watersheds.