Relationship between precipitation phase and air temperature: comparison between the Bolivian Andes and the Swiss Alps / Relation entre phase de précipitation et température de l'air: comparaison entre les Andes Boliviennes et les Alpes Suisses

Abstract

Determining the precipitation phase—rain or snow—is an important factor in modelling discharge in mountainous basins. In a study carried out in the outer tropical Andes Cordillera of Bolivia, half-hourly determination of precipitation phase was obtained by applying a suitable expert system, taking 11 meteorological parameters into consideration that are measured over 21 months at an altitude close to 4800 m. Straightforward relationships between the determined precipitation phase and observed air temperature were analysed in histograms that contain percentage occurrences of snowfall, rainfall and mixed precipitation events for 0.5°C air temperature increments. The graph shows a nearly identical distribution of percentage occurrences of snowfall in the Andes to that on a 1600-m high site in the Swiss Alps. This result suggests that, for hydrological modelling purposes in the outer tropical Andes, the same rain/snow threshold temperature as in the compared Swiss site can be applied.     

Impact of land-use changes on snow in a forested region with heavy snowfall in Hokkaido,Japan

Abstract

We simulated snow processes in a forested region with heavy snowfall in Japan, and evaluated both the regional-scale snow distribution and the potential impact of land-use changes on the snow cover and water balances over the entire domain. SnowModel reproduced the snow processes at open and forested sites, which were confirmed by snow water equivalent (SWE) measurements at two intensive observation sites and snow depth measurements at the Automated Meteorological Data Acquisition System sites. SnowModel also reproduced the observed snow distribution (from the MODIS snow cover data) over the simulation domain during thaw. The observed SWE was less at the forested site than at the open site. The SnowModel simulations showed that this difference was caused mainly by differences in sublimation. The type of land use changed the maximum SWE, onset and duration of snowmelt, and the daily snowmelt rate due to canopy snow interception.

Citation Suzuki, K., Kodama, Y., Nakai, T., Liston, G. E., Yamamoto, K., Ohata, T., Ishii, Y., Sumida, A., Hara, T. & Ohta, T. (2011) Impact of land-use changes in a forested region with heavy snowfall in Hokkaido, Japan. Hydrol. Sci. J. 56(3), 443–467.     

Mapping of Japanese areas susceptible to snow cover change

Abstract

Many of the Japanese regions subject to seasonal snow cover are characterized by low elevations and relatively high winter temperatures. A small change in winter temperatures could render many of these areas susceptible to snow cover change and consequently affect water resources management. This paper describes a climatological approach combined with an AGCM output to identify the regions and main river basins most sensitive to snow cover change in the case of climate change in Japan. It was found that a 1°C rise in temperature during the winter season could increase the snow-free area of Japan by 6%. The snow cover of Tohoku region and Mogami and Agano river basins was found to be the most sensitive to climate change. The AGCM output for a future scenario presents a reduction in total snowfall and an earlier peak in snowmelt for all regions.

Editor Z.W. Kundzewicz

Citation Chaffe, P.L.B, Takara, K, Yamashiki, Y, Apip, Luo, P., Silva, R.V., and Nakakita, E., 2013. Mapping of Japanese areas susceptible to snow cover change. Hydrological Sciences Journal, 58 (8), 1718–1728.     

Snow and climate trends and their impact on seasonal runoff and hydrological drought types in selected mountain catchments in Central Europe

ABSTRACT

This study investigates changes in seasonal runoff and low flows related to changes in snow and climate variables in mountainous catchments in Central Europe. The period 1966–2012 was used to assess trends in climate and streamflow characteristics using a modified Mann–Kendall test. Droughts were classified into nine classes according to key snow and climate drivers. The results showed an increase in air temperature, decrease in snowfall fraction and snow depth, and changes in precipitation. This resulted in increased winter runoff and decreased late spring runoff due to earlier snowmelt, especially at elevations from 1000 to 1500 m a.s.l. Most of the hydrological droughts were connected to either low air temperatures and precipitation during winter or high winter air temperatures which caused below-average snow storages. Our findings show that, besides precipitation and air temperature, snow plays an important role in summer streamflow and drought occurrence in selected mountainous catchments.     

LE TÉLÉNIVOMÉTRE A FAISCEAU HORIZONTAL MOBILE

Abstract

The study of the radioactive snow gauge has been undertaken in Grenoble in 1962 with the objective to develop, up to the routine operation, an automatic solid state electronic snow gauge, radio transmitting every day.

4 units of a first design, with steady vertical radioactive beam have been operated from 1964, but the limitation of the measurable depth to 4 meters of snow, 1,2 meter of water, was soon found too low in the French Alps.

A new type of gauge, with moving horizontal beam, profiling the snow pack, was designed in 1965, and evaluated through the last two years—During the measuring cycle, the source (30 millicuries of Cesium 137) and the G.H. detector are moving up at the same level inside two vertical pipes whose distance is 60 cm and height 6 meters; their speed is related to the pulse rate of the detector. One radio signal is emitted each decimeter during the motion. As soon as the team energes from the snow, it stops and returns back to its starting position under the ground level—the snow depth is indicated by the number of signals, and the density in each decimetric interval by the time elapsed between the signals.

The results of the last winter: six months'twice daily telemesured snow profiles are exhibited.

International cooperation is welcome to urge development of this device, which is felt the most promising automatic snow surveyor.     

Characteristics of subarctic snowcover / Les caractéristiques de la couverture de neige presque arctique

Abstract

The areal and temporal characteristics of the snowpack in a small subarctic drainage basin at Schefferville, Quebec, were analysed prior to and during the snowmelt in 1972 and 1973. The data showed that vegetation cover is of prime importance in determining the areal distribution of snowpack properties. The areal distribution of snow water equivalent could be characterized by a normal distribution in each of four vegetation cover types. It was found that the mean and standard deviation of snow water equivalent are closely related to vegetation cover. Also, mean snow water equivalent varies from year to year but standard deviation shows no significant variation. This suggests that mean accumulation is the result of annual snowfall amounts, while the variability is due to the effects of vegetation cover and accumulation processes. The data also showed that during the snowmelt, the variability of snowcover properties shows no significant change. Using the normal distributions of the peak accumulation snow water equivalents, and observed and calculated melt rates, the areal extent of snowcover was determined.     

Estimating snow distribution over a large area and its application for water resources

The spatial and temporal distribution of the snow water equivalent (SWE), snow density and snow depth were estimated by a method combining remote sensing technology and degree‐day techniques over a study area of 370 000 km². The advantages of this simulation model are its simplicity and the availability of degree‐day parameters, which can be successively evaluated by referring to snow area maps created from satellite images. This simulation worked very well for estimating SWE and helped to separate the areas of thin snow cover from heavier snowfall. However, shallow snow in warm regions led to some misjudgments in the snow area maps because of the time lag between when the satellite image was acquired and the simulation itself. Vulnerable areas, where a large variation in the amount of snow affects people's life, could be identified from the differences between heavy and light snow years. This vulnerability stems from a predicted lack of irrigation water for rice production caused by future climate change. The model developed in this study has the potential to contribute to water management activities and decision‐making processes when considering necessary adaptations to future climate change. Copyright © 2007 John Wiley & Sons, Ltd.     

Relative importance of snow accumulation and monsoon rainfall data for estimating annual runoff,Jhelum basin,Pakistan

Abstract

The relative importance of data on winter snow accumulation and summer (monsoon) rainfall for estimating annual runoff in the Jhelum River basin, Punjab Himalaya, Pakistan, has been investigated. Strong correlations were found between point measurements of the annual maximum of snowpack water equivalent and of total winter precipitation in the Kunhar sub-basin, and total annual discharge. In addition, total winter snowfall showed a generally significant correlation with annual discharge. Elevation did not appear to play a strong role in determining the usefulness of these measurements, whereas location within the basin relative to large scale precipitation patterns did, in some cases. Monsoon rainfall appeared to be a very poor indicator of annual discharge. The results also suggest that the operation of a continental scale negative feedback mechanism between Eurasian snow cover and the Indian monsoon might be felt in this region of the Himalaya.     

Soil temperature and soil moisture dynamics in winter and spring under heavy snowfall conditions in North-Eastern Japan

Warm winters and high precipitation in north-eastern Japan generate snow covers of more than three meters depth and densities of up to 0.55 g cm⁻³. Under these conditions, rain/snow ratio and snowmelt have increased significantly in the last decade under increasing warm winters. This study aims at understanding the effect of rain-on-snow and snowmelt on soil moisture under thick snow covers in mid-winter, taking into account that snowmelt in spring is an important source of water for forests and agriculture. The study combines three components of the Hydrosphere (precipitation, snow cover and soil moisture) in order to trace water mobility in winter, since soil temperatures remained positive in winter at nearly 0.3°C. The results showed that soil moisture increased after snowmelt and especially after rain-on-snow events in mid-winter 2018/2019. Rain-on-snow events were firstly buffered by fresh snow, increasing the snow water equivalent (SWE), followed by water soil infiltration once the water storage capacity of the snowpack was reached. The largest increase of soil moisture was 2.35 vol%. Early snowmelt increased soil moisture with rates between 0.02 and 0.035 vol% hr⁻¹ while, rain-on-snow events infiltrated snow and soil faster than snowmelt and resulted in rates of up to 1.06 vol% hr⁻¹. These results showed the strong connection of rain, snow and soil in winter and introduce possible hydrological scenarios in the forest ecosystems of the heavy snowfall regions of north-eastern Japan. Effects of rain-on-snow events and snowmelt on soil moisture were estimated for the period 2012–2018. Rain/snow ratio showed that only 30% of the total precipitation in the winter season 2011/2012 was rain events while it was 50% for the winter 2018/2019. Increasing climate warming and weakening of the Siberian winter monsoons will probably increase rain/snow ratio and the number of rain-on-snow events in the near future.     

Impacts of spatially and temporally varying snowmelt on subsurface flow in a mountainous watershed: 1. Snowmelt simulation

Abstract

The dominant source of streamflow in many mountainous watersheds is snowmelt recharge through shallow groundwater systems. The hydrological response of these watersheds is controlled by basin structure and spatially distributed snowmelt. The purpose of this series of two papers is to simulate spatially varying snowmelt and groundwater response in a small mountainous watershed. This paper examines the spatially and temporally variable snowmelt to be used as input to the groundwater flow modelling described in the second paper. Snowmelt simulation by the Simultaneous Heat and Water (SHAW) model (a detailed process model of the interrelated heat, water and solute movement through vegetative cover, snow, residue and soil) was validated by applying the model to two years of data at three sites ranging from shallow transient snow cover on a west-facing slope to a deep snow drift on a north-facing slope. The simulated energy balances for several melt periods are presented. Snow depth, density, and the magnitude and timing of snow cover outflow were simulated well for all sites.     

Application of a distributed blowing snow model to the Arctic

Transportation, sublimation and accumulation of snow dominate snow cover development in the Arctic and produce episodic high evaporative fluxes. Unfortunately, blowing snow processes are not presently incorporated in any hydrological or meteorological models. To demonstrate the application of simple algorithms that represent blowing snow processes, monthly snow accumulation, relocation and sublimation fluxes were calculated and applied in a spatially distributed manner to a 68-km² catchment in the low Arctic of north-western Canada. The model uses a Landsat-derived vegetation classification and a digital elevation model to segregate the basin into snow ‘sources’ and ‘sinks’. The model then relocates snow from sources to sinks and calculates in-transit sublimation loss. The resulting annual snow accumulation in specific landscape types was compared with the result of intensive surveys of snow depth and density. On an annual basis, 28% of annual snowfall sublimated from tundra surfaces whilst 18% was transported to sink areas. Annual blowing snow transport to sink areas amounted to an additional 16% of annual snowfall to shrub–tundra and an additional 182% to drifts. For the catchment, 19·5% of annual snowfall sublimated from blowing snow, 5·8% was transported into the catchment and 86·5% accumulated on the ground. The model overestimated snow accumulation in the catchment by 6%. The application demonstrates that winter precipitation alone is insufficient to calculate snow accumulation and that blowing snow processes and landscape patterns govern the spatial distribution and total accumulation of snow water equivalent over the winter. These processes can be modelled by relatively simple algorithms, and, when distributed by landscape type over the catchment, produce reasonable estimates of snow accumulation and loss in wind-swept regions. © 1997 John Wiley & Sons, Ltd.     

A SAMPLING SCHEME FOR SHALLOW SNOWPACKS

ABSTRACT

A hydrological sampling scheme should satisfy the purpose for which the samples are being collected, allowing for the variability of the samples in time and space. Snow measurements are commonly taken to provide estimates of the mean water equivalent over an area. A criterion for selecting a snow sampling scheme for shallow snowpacks is expressed in terms of the standard error of the mean water equivalent as a function of the means, variances, and sample sizes of snow depth and snow density. Analysis of data from the Blue Springs Representative Basin, Ontario, Canada, reveals relatively minor increases in the standard error term as the number of snow density samples is greatly reduced.     

Predicting new snow density in the Italian Alps: A variability analysis based on 10 years of measurements

Despite its strong impact on the time evolution of the snowpack, current estimation of new snow density (ρ_hn) is usually accomplished either by using local empirical techniques or by assuming a constant snow density. Faced with the lack of an estimation model of ρ_hn valid for a wide spatial scale and supported by a suitable number of observations, this study aims to develop simple monthly linear regression models at scale of the entire Italian Alpine chain based on 12,112 snowfall observations at 122 stations, using only air temperature as predictor. Moreover, the remaining variance is investigated in both time and space, also considering some qualitative features of the snowfall events. The daily ρ_hn measurements present a mean value of 115 kg m^?3 (105 and 159 kg m^?3 for dry and wet conditions, respectively). The mean air temperature of the 24 hr preceding the snowfall event has been found to be the best predictor of the ρ_hn, within 31% of uncertainty. The analysis of associated residues allows supporting the idea that the adoption of a more local approach than the one analysed here is not able to substantially increase the predictive capabilities of the model. In fact, the main factor explaining the remaining variance over the air temperature is the wind, but in a complex orography, as mountain regions are, supplying realistic local wind fields is particularly challenging. Therefore, we conclude that using only the daily mean temperature as predictor is a good choice for estimating daily new snow density at scale of Italian Alpine chain, as well as at more regional scale.     

A simple method to combine snow height and meteorological observations to estimate winter precipitation at sub-daily resolution

ABSTRACT

Measuring winter solid and liquid precipitation with high temporal resolution in remote or higher elevation regions is a challenging task because of undercatch and power supply issues. However, the number of micro-meteorological stations and ultrasonic height sensors in mountain regions is steadily increasing. To gain more benefit from such stations, a new simple approach for EStimating SOlid and LIquid Precipitation (ESOLIP) is presented. The method consists of three main steps: (1) definition of precipitation events using micro-meteorological data, (2) quantification of solid and liquid precipitation using wet-bulb temperature and filtered snow height and (3) calculation of fresh snow density. ESOLIP performance was validated using data from a heated rain gauge, snow pillow and daily manual observations both for single precipitation events and over three winter seasons. Results proved ESOLIP as an effective approach for precipitation quantification, where snow height observations and basic meteorological measurements (air temperature, solar radiation, wind speed, relative humidity), but no reliable rain gauges are available.     

Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.     

MODIS Terra Collection 6 fractional snow cover validation in mountainous terrain during spring snowmelt using Landsat TM and ETM+

Daily swath MODIS Terra Collection 6 fractional snow cover (MOD10_L2) estimates were validated with two‐day Landsat TM/ETM + snow‐covered area estimates across central Idaho and southwestern Montana, USA. Snow cover maps during spring snowmelt for 2000, 2001, 2002, 2003, 2005, 2007, and 2009 were compared between MODIS Terra and Landsat TM/ETM + using least‐squared regression. Strong spatial and temporal map agreement was found between MODIS Terra fractional snow cover and Landsat TM/ETM + snow‐covered area, although map disagreement was observed for two validation dates. High‐altitude cirrus cloud contamination during low snow conditions as well as late season transient snowfall resulted in map disagreement. MODIS Terra's spatial resolution limits retrieval of thin‐patchy snow cover, especially during partially cloudy conditions. Landsat's image acquisition frequency can introduce difficulty when discriminating between transient and resident mountain snow cover. Furthermore, transient snowfall later in the snowmelt season, which is a stochastic accumulation event that does not usually persist beyond the daily timescale, will skew decadal snow‐covered area variability if bi‐monthly climate data record development is the objective. As a quality control step, ground‐based daily snow telemetry snow‐water‐equivalent measurements can be used to verify transient snowfall events. Users of daily MODIS Terra fractional snow products should be aware that local solar illumination and sensor viewing geometry might influence fractional snow cover estimation in mountainous terrain. Cross‐sensor interoperability has been confirmed between MODIS Terra and Landsat TM/ETM + when mapping snow from the visible/infrared spectrum. This relationship is strong and supports operational multi‐sensor snow cover mapping, specifically climate data record development to expand cryosphere, climate, and hydrological science applications. Copyright © 2013 John Wiley & Sons, Ltd.     

Ice‐cover variability on shallow lakes at high latitudes: model simulations and observations

A one‐dimensional thermodynamic model for simulating lake‐ice phenology is presented and evaluated. The model can be driven with observed daily or hourly atmospheric forcing of air temperature, relative humidity, wind speed, cloud amount and snowfall. In addition to computing the energy balance components, key model output includes the temperature profile at an arbitrary number of levels within the ice/snow (or the water temperature if there is no ice) and ice thickness (clear ice and snow‐ice) on a daily basis, as well as freeze‐up and break‐up dates. The lake‐ice model is used to simulate ice‐growth processes on shallow lakes in arctic, sub‐arctic, and high‐boreal forest environments. Model output is compared with field and remote sensing observations gathered over several ice seasons. Simulated ice thickness, including snow‐ice formation, compares favourably with field measurements. Ice‐on and ice‐off dates are also well simulated when compared with field and satellite observations, with a mean absolute difference of 2 days. Model simulations and observations illustrate the key role that snow cover plays on the seasonal evolution of ice thickness and the timing of spring break‐up. It is also shown that lake morphometry, depth in particular, is a determinant of ice‐off dates for shallow lakes at high latitudes. Copyright © 2003 John Wiley & Sons, Ltd.     

A Downscaling Approach Toward High-Resolution Surface Mass Balance Over Antarctica

The Antarctic ice sheet surface mass balance shows high spatial variability over the coastal area. As state-of-the-art climate models usually require coarse resolutions to keep computational costs to a moderate level, they miss some local features that can be captured by field measurements. The downscaling approach adopted here consists of using a cascade of atmospheric models from large scale to meso-?? scale. A regional climate model (Modèle Atmosphérique Régional) forced by meteorological reanalyses provides a diagnostic physically-based rain- and snowfall downscaling model with meteorological fields at the regional scale. Although the parameterizations invoked by the downscaling model are fairly simple, the knowledge of small-scale topography significantly improves the representation of spatial variability of precipitation and therefore that of the surface mass balance. Model evaluation is carried out with the help of shallow firn cores and snow height measurements provided by automatic weather stations. Although downscaling of blowing snow still needs to be implemented in the model, the net accumulation gradient across Law Dome summit is shown to be induced mostly by orographic effects on precipitation.     

Passive microwave remote sensing of the historic February 2010 snowstorms in the Middle Atlantic region of the USA

The snowfall in the Baltimore/Washington metropolitan area during the winter of 2009/2010 was unprecedented and caused serious snow‐related disruptions. In February 2010, snowfall totals approached 2 m, and because maximum temperatures were consistently below normal, snow remained on the ground the entire month. One of the biggest contributing factors to the unusually severe winter weather in 2009/2010, throughout much of the middle latitudes, was the Arctic Oscillation. Unusually high pressure at high latitudes and low pressure at middle latitudes forced a persistent exchange of mass from north to south. In this investigation, a concerted effort was made to link remotely sensed falling snow observations to remotely sensed snow cover and snowpack observations in the Baltimore/Washington area. Specifically, the Advanced Microwave Scanning Radiometer onboard the Aqua satellite was used to assess snow water equivalent, and the Advanced Microwave Sounding Unit‐B and Microwave Humidity Sounder were employed to detect falling snow. Advanced Microwave Scanning Radiometer passive microwave signatures in this study are related to both snow on the ground and surface ice layers. In regard to falling snow, signatures indicative of snowfall can be observed in high frequency brightness temperatures of Advanced Microwave Sounding Unit‐B and Microwave Humidity Sounder. Indeed, retrievals show an increase in snow water equivalent after the detection of falling snow. Yet, this work also shows that falling snow intensity and/or the presence of liquid water clouds impacts the ability to reliably detect snow water equivalent. Moreover, changes in the condition of the snowpack, especially in the surface features, negatively affect retrieval performance. Copyright © 2011. This article is a U.S. Government work and is in the public domain in the USA.     

Streamflow elasticity,in a context of climate change,in arid Andean watersheds of north-central Chile

ABSTRACT

Based on a future temperature increase of 0.5°C and precipitation decrease of 25%, the climate elasticity of streamflow to precipitation and temperature changes in 12 Andean watersheds of the Coquimbo Region, north-central Chile, was assessed. Also, the possible relationships between this elasticity and specific physiographic characteristics of the watersheds (area, average elevation, slope distribution, terrain roughness, slope orientation, vegetation cover) were studied. Climate elasticity of streamflow ranged between 0 and 2.8. Watersheds presenting higher elevations, with a fairly well-balanced distribution of slope exposure tend to exhibit lower elasticity, which could be explained by the contribution of snowfall to the hydrological regime, more significant in those watersheds. Results should be considered when downscaling climate model projections at the basin scale in mountain settings. Finally, uncertainties in the approach, given by factors such as streamflow seasonality, data availability and representativeness and watershed characteristics, and therefore the scope of the results, are discussed.