Snow Module Research Articles

Comparison of two snowmelt modelling approaches in the Dudh Koshi basin (eastern Himalayas, Nepal)

The glaciers in the Nepalese Himalayas are retreating due to rising temperatures. Lack of data and information on Nepal’s cryosphere has impeded scientific studies and field investigations in the Nepalese Himalayas. Therefore, IRD France and Ev-K2 CNR Italy have conducted the PAPRIKA (CryosPheric responses to Anthropogenic PRessures in the HIndu Kush-Himalaya regions: impacts on water resources and society adaptation in Nepal) project in Nepal with the financial support of the French and Italian scientific agencies. This project aims to address the current and future evolution of the cryosphere in response to overall environmental changes in South Asia, and its consequences for water resources in Nepal. Thus, two hydrological models, the GR4J lumped precipitation–runoff model and the snowmelt runoff model (SRM), were used in the Dudh Koshi basin. The GR4J model has been successfully applied in different parts of Europe. To obtain better results in such a harsh and rugged topography, modifications needed to be made, particularly in the snow module. The runoff pattern is analysed herein both for past years and, in a sensitivity analysis, for possible future climatic conditions (i.e. precipitation and temperature) using the SRM and GR4J modelling approaches. The results reveal a significant contribution of snow- and glacier-melt to runoff, and the SRM model shows better performance in Nepalese catchments than the GR4J model.Editor D. Koutsoyiannis; Associate editor D. GertenCitation Pokhrel, B.K., Chevallier, P., Andréassian, V., Tahir, A.A., Arnaud, Y., Neppel, L., Bajracharya, O.R., and Budhathoki, K.P., 2014. Comparison of two snowmelt modelling approaches in the Dudh Koshi basin (eastern Himalayas, Nepal). Hydrological Sciences Journal, 59 (8), 1507–1518. http://dx.doi.org/10.1080/02626667.2013.842282

An investigation of the effect of transient climate change on snowmelt, flood frequency and timing in northern Britain

ABSTRACTClimate change is almost certain to affect snow and ice processes. Even at lower latitudes, changes in snow cover at high altitudes can significantly affect catchment hydrology. This article uses data from a transient Regional Climate Model projection (HadRM3Q0) for 1950–2099 (A1B emissions) to drive hydrological models for three nested catchments on the river Dee in north‐east Scotland, to assess potential changes in flood frequency and timing using annual maxima and moving‐window analyses. Some results are also shown for an upland catchment in northern England. Modelling is performed both with and without a snow module, to demonstrate the effects of snowfall/melt and how these change through time and vary between catchments. Modelled changes in flood magnitude and timing are nonlinear, with most changes for daily mean flows not significant. For longer duration (30‐day) flows with snow there are significant decreases in peak magnitude, particularly for the smaller higher altitude Dee catchments, with peaks occurring months earlier in future (changes without snow are generally not significant). There is a general convergence in results with and without snow later in the period, as snow processes become less important, but convergence occurs at different times for different catchments and occurs differently for daily and 30‐day peak flows due to the differential effects of snow at different durations. This not only highlights the importance of including snow processes for such catchments, particularly for longer duration flows, but also highlights the complexity of interactions: Physical catchment properties, the balance between precipitation occurrence and temperature, and how this balance alters as the climate changes will each be critical in determining the impact on the magnitude and timing of peak flows, making it hard to generalize results.

Predictability of soil moisture and streamflow on subseasonal timescales: A case study

Hydrological forecasts constitute an important tool in water resource management, especially in the case of impending extreme events. This study investigates the potential predictability of soil moisture and streamflow in Switzerland using a conceptual model including a simple water balance representation and a snow module. Our results show that simulated soil moisture and streamflow are more predictable (as indicated by significantly improved performance compared to climatology) until lead times of approximately 1 week and 2–3 days, respectively, when using initial soil moisture information and climatological atmospheric forcing. Using also initial snow information and seasonal weather forecasts as forcing, the predictable lead time doubles in case of soil moisture and triples for streamflow. The skill contributions of the additional information vary with altitude; at low altitudes the precipitation forecast is most important, whereas in mountainous areas the temperature forecast and the initial snow information are the most valuable contributors. We find furthermore that the soil moisture and streamflow forecast skills increase with increasing initial soil moisture anomalies. Comparing the respective value of realistic initial conditions and state‐of‐the‐art forcing forecasts, we show that the former are generally more important for soil moisture forecasts, whereas the latter are more valuable for streamflow forecasts. To relate the derived predictabilities to respective soil moisture and streamflow memories investigated in other publications, we additionally illustrate the similarity between the concepts of memory and predictability as measures of persistence in the last part of this study.

Forest ecohydrological response to bimodal precipitation during contrasting winter to summer transitions

ABSTRACTThe ecohydrological response of forested landscapes in the Southwestern United States depends on the relative magnitude of precipitation during the winter and summer seasons. Prior climate studies have identified an inverse relation in the bimodal regime such that wet winter periods are followed by dry summers and vice versa. Despite this key prediction, the impact of contrasting winter to summer transitions on hillslope hydrology has not been investigated. In this study, we use the Triangulated Irregular Network‐based Real‐time Integrated Basin Simulator distributed hydrologic model with modifications in the snow module to generate a consistent set of high‐resolution hydrologic estimates in a ponderosa pine hillslope in northern New Mexico, United States. The model is evaluated against available observations of snow depth, soil moisture and runoff over two water years yielding reliable spatial distributions during the winter to summer transitions. We find that a wet winter followed by a dry summer promotes evapotranspiration losses that gradually dry the soil and disconnect lateral fluxes in the forested hillslope, leading to soil moisture patterns resembling vegetation patches. Conversely, a dry winter prior to a wet summer results in soil moisture increases that promote lateral connectivity and soil moisture patterns with the signature of terrain curvature. An opposing temporal switch between infiltration and saturation excess runoff is also identified. These contrasting responses indicate that the inverse relation has significant consequences on hillslope water availability and its spatial distribution with implications on other ecohydrological processes including vegetation phenology, groundwater recharge and geomorphic development. Copyright © 2013 John Wiley & Sons, Ltd.

Future surface mass balance of the Antarctic ice sheet and its influence on sea level change, simulated by a regional atmospheric climate model

A regional atmospheric climate model with multi-layer snow module (RACMO2) is forced at the lateral boundaries by global climate model (GCM) data to assess the future climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS). Two different GCMs (ECHAM5 until 2100 and HadCM3 until 2200) and two different emission scenarios (A1B and E1) are used as forcing to capture a realistic range in future climate states. Simulated ice sheet averaged 2 m air temperature (T2m) increases (1.8–3.0 K in 2100 and 2.4–5.3 K in 2200), simultaneously and with the same magnitude as GCM simulated T2m. The SMB and its components increase in magnitude, as they are directly influenced by the temperature increase. Changes in atmospheric circulation around Antarctica play a minor role in future SMB changes. During the next two centuries, the projected increase in liquid water flux from rainfall and snowmelt, together 60–200 Gt year−1, will mostly refreeze in the snow pack, so runoff remains small (10–40 Gt year−1). Sublimation increases by 25–50 %, but remains an order of magnitude smaller than snowfall. The increase in snowfall mainly determines future changes in SMB on the AIS: 6–16 % in 2100 and 8–25 % in 2200. Without any ice dynamical response, this would result in an eustatic sea level drop of 20–43 mm in 2100 and 73–163 mm in 2200, compared to the twentieth century. Averaged over the AIS, a strong relation between \(\Updelta\)SMB and \(\Updelta\hbox{T}_{2{\rm m}}\) of 98 ± 5 Gt w.e. year−1 K−1 is found.

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

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.

A case study of blowing snow cooling effects on anticyclogenesis and cyclolysis

[1] This paper focuses on blowing snow and its effect, through thermodynamic forcing, on anticyclogenesis and cyclolysis. A triple-moment blowing snow model (PIEKTUK-T) is coupled to an atmospheric model (MC2), and this system is used to simulate an anticyclogenesis event. For comparison, an uncoupled version of MC2 is used to model the same event. The coupled model (CPL) showed colder low-level temperatures in regions where blowing snow occurred. This cooling contributes to a rise in sea level pressure relative to the uncoupled simulation. A potential vorticity (PV) diagnostic is then applied to quantify how this microphysical cooling affects the geopotential height and balanced wind fields. Surface potential temperature differences between the coupled and uncoupled runs were used as lower boundary conditions for the inversion. The results showed that blowing snow has only a small cooling effect over the anticyclogenesis region in CPL and moderate cooling over Baffin Island, where a decaying cyclone was moving northward. The cooling induces positive geopotential height and anticyclonic flow perturbations extending up to 500 mbar over the cyclone region. The averaged inverted geopotential height anomaly at 1000 mbar level over the cooling region is up to 4.6 dam in 72 h. Surface cooling is demonstrated to play a role in the cyclolysis. The CPL run allows the relative humidity with respect to ice in the blowing snow module to remain supersaturated and includes the heat release from the supersaturated water vapor deposition. Another experiment was carried out, in which supersaturated vapor was not allowed in the blowing snow module. The sensitivity experiment results indicated that blowing snow cooling effects over Baffin Island will be much reduced.

Modeling chemistry in and above snow at Summit, Greenland – Part 1: Model description and results

Abstract. Sun-lit snow is increasingly recognized as a chemical reactor that plays an active role in uptake, transformation, and release of atmospheric trace gases. Snow is known to influence boundary layer air on a local scale, and given the large global surface coverage of snow may also be significant on regional and global scales. We present a new detailed one-dimensional snow chemistry module that has been coupled to the 1-D atmospheric boundary layer model MISTRA. The new 1-D snow module, which is dynamically coupled to the overlaying atmospheric model, includes heat transport in the snowpack, molecular diffusion, and wind pumping of gases in the interstitial air. The model includes gas phase chemical reactions both in the interstitial air and the atmosphere. Heterogeneous and multiphase chemistry on atmospheric aerosol is considered explicitly. The chemical interaction of interstitial air with snow grains is simulated assuming chemistry in a liquid-like layer (LLL) on the grain surface. The coupled model, referred to as MISTRA-SNOW, was used to investigate snow as the source of nitrogen oxides (NOx) and gas phase reactive bromine in the atmospheric boundary layer in the remote snow covered Arctic (over the Greenland ice sheet) as well as to investigate the link between halogen cycling and ozone depletion that has been observed in interstitial air. The model is validated using data taken 10 June–13 June, 2008 as part of the Greenland Summit Halogen-HOx experiment (GSHOX). The model predicts that reactions involving bromide and nitrate impurities in the surface snow can sustain atmospheric NO and BrO mixing ratios measured at Summit, Greenland during this period.

SIMULATION OF INTERANNUAL VARIABILITY OF SNOW COVER AT VALDAI (RUSSIA) USING A DISTRIBUTED BIOSPHERE HYDROLOGICAL MODEL WITH IMPROVED SNOW PHYSICS

The distributed biosphere hydrological model (WEB-DHM) was physically improved in snow physics, by incorporating the 3-layer energy balance based snow module of the Simplified Simple Biosphere 3 (SSiB3) model and albedo module of the Biosphere Atmosphere Transfer Scheme (BATS). The new version of WEB-DHM is referred to as WEB-DHM-S. In this study, the WEB-DHM-S is evaluated at Valdai site (Russia) from 1966 to 1983, to check its performance in simulating the interannual variability of snow cover. Results show that the WEB-DHM-S is capable of reproducing the point-scale interannual variations of snow water equivalent, soil and snow surface temperature well. In addition, the good performance of WEB-DHM-S was further confirmed in simulating soil moisture (top 1 m) and evapotranspiration.

Improving the snow physics of WEB-DHM and its point evaluation at the SnowMIP sites

Abstract. In this study, the snow physics of a distributed biosphere hydrological model, referred to as the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) is significantly improved by incorporating the three-layer physically based energy balance snowmelt model of Simplified Simple Biosphere 3 (SSiB3) and the Biosphere-Atmosphere Transfer Scheme (BATS) albedo scheme. WEB-DHM with improved snow physics is hereafter termed WEB-DHM-S. Since the in-situ observations of spatially-distributed snow variables with high resolution are currently not available over large regions, the new distributed system (WEB-DHM-S) is at first rigorously tested with comprehensive point measurements. The stations used for evaluation comprise the four open sites of the Snow Model Intercomparison Project (SnowMIP) phase 1 with different climate characteristics (Col de Porte in France, Weissfluhjoch in Switzerland, Goose Bay in Canada and Sleepers River in USA) and one open/forest site of the SnowMIP phase 2 (Hitsujigaoka in Japan). The comparisons of the snow depth, snow water equivalent, surface temperature, snow albedo and snowmelt runoff at the SnowMIP1 sites reveal that WEB-DHM-S, in general, is capable of simulating the internal snow process better than the original WEB-DHM. Sensitivity tests (through incremental addition of model processes) are performed to illustrate the necessity of improvements over WEB-DHM and indicate that both the 3-layer snow module and the new albedo scheme are essential. The canopy effects on snow processes are studied at the Hitsujigaoka site of the SnowMIP2 showing that the snow holding capacity of the canopy plays a vital role in simulating the snow depth on ground. Through these point evaluations and sensitivity studies, WEB-DHM-S has demonstrated the potential to address basin-scale snow processes (e.g., the snowmelt runoff), since it inherits the distributed hydrological framework from the WEB-DHM (e.g., the slope-driven runoff generation with a grid-hillslope scheme, and the flow routing in the river network).

Improvement of springtime streamflow simulations in a boreal environment by incorporating snow-covered area derived from remote sensing data

Summary Snow estimation is the major source of errors for spring streamflow simulations in Quebec, Canada. The objective of the study is to improve melting discharge estimation computed with the operational MOHYSE hydrological model by integrating remote sensing snow-cover area in its snow module (SPH-AV). The satellite-derived snow-cover area (SCA) (MODIS & IMS) is first compared with in situ snow depth data measurements and simulated snow-cover area. Results show that the remote sensing products underestimate the snow-cover area on the mainly forested study region. A direct-insertion method of daily satellite SCA images is developed based on an empirical snow water equivalent threshold compensating, on a pixel-by-pixel basis, for the small amount of snow that satellite sensors can not identify during the melting period. This approach improves the streamflow simulation for spring periods (25th March to 25th of May) over 4 years (2004–2007) with a Nash–Sutcliffe coefficient enhancement of 0.11 and a root mean square error (RMSE) improvement of 21% on the Du Nord watershed, for which the threshold was optimized. The threshold found on the Du Nord basin was then directly applied on another watershed ( Aux Ecorces basin) for validation. The simulated streamflow is significantly improved as compared to the observed streamflow for these 4 years (mean Nash increase from 0.72 to 0.85 and RMSE decrease by 22%). The method improves streamflow peaks identification as much as 36% on the Du Nord watershed and 19% on the Aux Ecorces watershed.

Influence of different digital terrain models (DTMs)on alpine permafrost modeling

The thawing of alpine permafrost due to changes in atmospheric conditions can have a severe impact, e.g., on the stability of rock walls. The energy balance model, PERMEBAL, was developed in order to simulate the changes and distribution of ground surface temperature (GST) in complex high-mountain topography. In such environments, the occurrence of permafrost depends greatly on the topography, and thus, the digital terrain model (DTM) is an important input of PERMEBAL. This study investigates the influence of the DTM on the modeling of the GST. For this purpose, PERMEBAL was run with six different DTMs. Five of the six DTMs are based on the same base data, but were generated using different interpolators. To ensure that only the topographic effect on the GST is calculated, the snow module was turned off and uniform conditions were assumed for the whole test area. The analyses showed that the majority of the deviations between the different model outputs related to a reference DTM had only small differences of up to 1 K, and only a few pixels deviated more than 1 K. However, we also observed that the use of different interpolators for the generation of a DTM can result in large deviations of the model output. These deviations were mainly found at topographically complex locations such as ridges and foot of slopes.

The GEOTOP snow module

AbstractA snow accumulation and melt module implemented in the GEOTOP model is presented and tested. GEOTOP, a distributed model of the hydrological cycle, based on digital elevation models (DEMs), calculates the discharge at the basin outlet and estimates the local and distributed values of several hydro‐meteorological quantities. It solves the energy and the mass balance jointly and deals accurately with the effects of topography on the interactions among radiation physics, energy balance and the hydrological cycle. Soil properties are considered to depend on soil temperature and moisture, and the heat and water transfer in the soil is modelled using a multilayer approach. The snow module solves for the soil–snow energy and mass exchanges, and, together with a runoff production module, is embedded in a more general energy balance model that provides all the boundary conditions required. The snowpack is schematized as a single snow layer where a limited number of physical processes are described. The module can be seen essentially as a parameter‐free model. The application to an alpine catchment (Rio Valbiolo, Trentino, Italy), monitored by an in situ snow‐depth sensor, is discussed and shown to give results comparable to those of more complex models. Copyright © 2004 John Wiley & Sons, Ltd.

Atmospheric response to soil-frost and snow in Alaska in March

A hydro-thermodynamic soil-vegetation model including soil freezing/thawing (soil-frost) and snow-metamorphism has been integrated into the PennState/NCAR Mesoscale Meteorological Model MM5 in a two-way coupled mode. A hierarchy of simulations with and without the soil-frost module, each combined with and without the snow module, shows the influence of snow-cover and soil-frost on weather in Alaska. Herein the landscape is featured as it is typically by mesoscale models.