Snow cover models in operational watershed forecasting

Yhteenveto: Lumimallit vesistöjen ennustemalleissa

Changes in seasonal snow cover in Hindu Kush-Himalayan region

The changes in seasonal snow covered area in the Hindu Kush-Himalayan (HKH) region have been examined using Moderate – resolution Imaging Spectroradiometer (MODIS) 8-day standard snow products. The average snow covered area of the HKH region based on satellite data from 2000 to 2010 is 0.76 million km2 which is 18.23% of the total geographical area of the region. The linear trend in annual snow cover from 2000 to 2010 is −1.25±1.13%. This is in consistent with earlier reported decline of the decade from 1990 to 2001. A similar trend for western, central and eastern HKH region is 8.55±1.70%, +1.66% ± 2.26% and 0.82±2.50%, respectively. The snow covered area in spring for HKH region indicates a declining trend (−1.04±0.97%). The amount of annual snowfall is correlated with annual seasonal snow cover for the western Himalaya, indicating that changes in snow cover are primarily due to interannual variations in circulation patterns. Snow cover trends over a decade were also found to vary across seasonally and the region. Snow cover trends for western HKH are positive for all seasons. In central HKH the trend is positive (+15.53±5.69%) in autumn and negative (−03.68±3.01) in winter. In eastern HKH the trend is positive in summer (+3.35±1.62%) and autumn (+7.74±5.84%). The eastern and western region of HKH has an increasing trend of 10% to 12%, while the central region has a declining trend of 12% to 14% in the decade between 2000 and 2010. Snow cover depletion curve plotted for the hydrological year 2000–2001 reveal peaks in the month of February with subsidiary peaks observed in November and December in all three regions of the HKH.

Monitoring of seasonal snow cover in Bhutan using remote sensing technique

All major rivers in Bhutan depend on snowmelt for discharge. Therefore, changes in snow cover due to climate change can influence distribution and availability of water. However, information about distribution of seasonal snow cover in Bhutan is not available. The MODIS snow product was used to study snow cover status and trends in Bhutan. Average snow cover area (SCA) of Bhutan estimated for the period 2002 to 2010 was 9030 sq. km, about 25.5% of the total land area. SCA trend of Bhutan for the period 2002-2010 was found to decrease (-3.27 +/- 1.28%). The average SCA for winter was 14,485 sq. km (37.7%), for spring 7411 sq. km (19.3%), for summer 4326 sq. km (11.2%), and for autumn 7788 sq. km (20.2%), mostly distributed in the elevation range 2500-6000 m amsl. Interannual and seasonal SCA trend both showed a decline, although it was not statistically significant for all sub-basins. Pho Chu sub-basin with 19.5% of the total average SCA had the highest average SCA. The rate of increase of SCA for every 100 m elevation was the highest (2.5%) in the Pa Chu sub-basin. The coefficient of variance of 1.27 indicates high variability of SCA in winter.

Missing (in-situ) snow cover data hampers climate change and runoff studies in the Greater Himalayas

The Himalayas are presently holding the largest ice masses outside the polar regions and thus (temporarily) store important freshwater resources. In contrast to the contemplation of glaciers, the role of runoff from snow cover has received comparably little attention in the past, although (i) its contribution is thought to be at least equally or even more important than that of ice melt in many Himalayan catchments and (ii) climate change is expected to have widespread and significant consequences on snowmelt runoff. Here, we show that change assessment of snowmelt runoff and its timing is not as straightforward as often postulated, mainly as larger partial pressure of H2O, CO2, CH4, and other greenhouse gases might increase net long-wave input for snowmelt quite significantly in a future atmosphere. In addition, changes in the short-wave energy balance such as the pollution of the snow cover through black carbon or the sensible or latent heat contribution to snowmelt are likely to alter future snowmelt and runoff characteristics as well. For the assessment of snow cover extent and depletion, but also for its monitoring over the extremely large areas of the Himalayas, remote sensing has been used in the past and is likely to become even more important in the future. However, for the calibration and validation of remotely-sensed data, and even-more so in light of possible changes in snow-cover energy balance, we strongly call for more in-situ measurements across the Himalayas, in particular for daily data on new snow and snow cover water equivalent, or the respective energy balance components. Moreover, data should be made accessible to the scientific community, so that the latter can more accurately estimate climate change impacts on Himalayan snow cover and possible consequences thereof on runoff. (C) 2013 Elsevier B.V. All rights reserved.

A new Snow-SVAT to simulate the accumulation and ablation of seasonal snow cover beneath a forest canopy

A new snow-soil-vegetation-atmosphere transfer (Snow-SVAT) scheme, which simulates the accumulation and ablation of the snow cover beneath a forest canopy, is presented. The model was formulated by coupling a canopy optical and thermal radiation model to a physically-based multi-layer snow model. This canopy radiation model is physically-based yet requires few parameters, so can be used when extensive in-situ field measurements are not available. Other forest effects such as the reduction of wind speed, interception of snow on the canopy and the deposition of litter were incorporated within this combined model, SNOWCAN, which was tested with data taken as part of the Boreal Ecosystem-Atmosphere Study (BOREAS) international collaborative experiment. Snow depths beneath four different canopy types and at an open site were simulated. Agreement between observed and simulated snow depths was generally good, with correlation coefficients ranging between r^2=0.94 and r^2=0.98 for all sites where automatic measurements were available. However, the simulated date of total snowpack ablation generally occurred later than the observed date. A comparison between simulated solar radiation and limited measurements of sub-canopy radiation at one site indicates that the model simulates the sub-canopy downwelling solar radiation early in the season to within measurement uncertainty.

An Intercomparison of Regional Atmospheric Circulation and the Melt Season Loss of Arctic Snow Cover and Sea Ice Extent Across the Land-Ocean Boundary

This study is designed to compare the monthly continental snow cover and sea ice extent loss in the Arctic with regional atmospheric conditions including: mean sea level pressure, 925 hPa air temperature, and mean wind direction among others during the melt season (March-August) over the 29-year study period 1979-2007. Little research has gone into studying the concurrent variations in the annual loss of continental snow cover and sea ice extent across the land-ocean boundary, since these data are largely stored in incompatible formats. However, the analysis of these data, averaged spatially over three autonomous study regions located in Siberia, North America, and Western Russia, reveals a distinct difference in the response of snow and sea ice to the atmospheric forcing. On average, sea ice extent is lost earlier in the year, in May, than snow cover, in June, although Arctic sea ice is located farther north than continental snow in all three study regions. Once the loss of snow and ice extent begins, snow cover is completely removed sooner than sea ice extent, even though ice loss begins earlier in the melt season. Further, the analysis of the atmospheric conditions surrounding loss of snow and ice cover over the independent study regions indicates that conditions of cool temperatures with strong northeasterly winds in the later melt season months are effective at removing sea ice cover, likely through ice divergence, as are warmer temperatures via southerly winds directly forcing melt. The results of this study set the framework for further analysis of the direct influence of snow cover loss on later melt season sea ice extents and the predictability of snow and sea ice extent responses to modeled future climate conditions

A satellite-based snow cover climatology (1985–2011) for the European Alps derived from AVHRR data

Seasonal snow cover is of great environmental and socio-economic importance for the European Alps. Therefore a high priority has been assigned to quantifying its temporal and spatial variability. Complementary to land-based monitoring networks, optical satellite observations can be used to derive spatially comprehensive information on snow cover extent. For understanding long-term changes in alpine snow cover extent, the data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensors mounted onboard the National Oceanic and Atmospheric Association (NOAA) and Meteorological Operational satellite (MetOp) platforms offer a unique source of information. In this paper, we present the first space-borne 1 km snow extent climatology for the Alpine region derived from AVHRR data over the period 1985–2011. The objective of this study is twofold: first, to generate a new set of cloud-free satellite snow products using a specific cloud gap-filling technique and second, to examine the spatiotemporal distribution of snow cover in the European Alps over the last 27 yr from the satellite perspective. For this purpose, snow parameters such as snow onset day, snow cover duration (SCD), melt-out date and the snow cover area percentage (SCA) were employed to analyze spatiotemporal variability of snow cover over the course of three decades. On the regional scale, significant trends were found toward a shorter SCD at lower elevations in the south-east and south-west. However, our results do not show any significant trends in the monthly mean SCA over the last 27 yr. This is in agreement with other research findings and may indicate a deceleration of the decreasing snow trend in the Alpine region. Furthermore, such data may provide spatially and temporally homogeneous snow information for comprehensive use in related research fields (i.e., hydrologic and economic applications) or can serve as a reference for climate models.

Arctic moisture source for Eurasian snow cover variations in autumn

Eurasian fall snow cover changes have been suggested as a driver for changes in the Arctic Oscillation and might provide a link between sea-ice decline in the Arctic during summer and atmospheric circulation in the following winter. However, the mechanism connecting snow cover in Eurasia to sea-ice decline in autumn is still under debate. Our analysis is based on snow observations from 820 Russian land stations, moisture transport using a Lagrangian approach derived from meteorological re-analyses. We show that declining sea-ice in the Barents and Kara Seas (BKS) acts as moisture source for the enhanced Western Siberian snow depth as a result of changed tropospheric moisture transport. Transient disturbances enter the continent from the BKS region related to anomalies in the planetary wave pattern and move southward along the Ural mountains where they merge into the extension of the Mediterranean storm track.