1. Please write down the name (and abbreviation) of your snow model or land-surface model with snow component?
RGM (Regional Geosystem Model)
2. Name and address of model developer;
Dr. Dieter Scherer MCR Lab - Dept. of Geography - University of Basel Spalenring 145 - CH-4055 Basel - Switzerland Tel.: (+41) 61 272 6480 Fax: (+41) 61 272 6923
3. Name and address of model user;
actually myself (will be used by several scientists in the near future)
4. Please indicate whether your model is developed for application
in understanding snow processes, X
in a runoff forecasting model, X (later)
in a weather forecasting model,
in a global climate model (GCM),
or other (please specify)? X (Risk assessment of snow hazards)
5. The first year when the model was used;
6. One paragraph description of your model (e.g. abstract from report or paper);
RGM is a physically-based, spatially distributed model for simulating meltwater flow through snowpacks. It uses a finite difference scheme for computing the energy balance conditions of the snowpack, as well as for the routing of the produced excess meltwater downslope. Time steps can be selected by the user (typically 1 hour). The model uses a recursive approach to split the time interval into two parts, if the non-linearity of the processes are too strong. This enables to regard short-term processes as well as such ones acting on the regular time scale.
7. Please specify any known application range or restrictions;
Actually the applications are restricted to meltwater routing under melting snowpack conditions.
8. What are the development data needs;
A digital elevation model and meteorological time series (temperature, humidity, wind speed...); Remotely sensed data of snow variables as the solar albedo may be used to set-up the initial conditions.
9. What are the operational data needs?
The model is not yet in an operational state.
10. Please indicate with an "x" for those meteorological variables used to
DRIVE your snow model?
precipitation : NYI
air temperature : X
wind speed : X
wind direction : NYI
humidity : X
downwelling shortwave radiation : (is computed by the model)
downwelling longwave radiation : (is computed by the model)
cloud cover : NYI
surface pressure : NYI
11. List the state variables (e.g., snow temperature, snow water equivalent, etc) your snow model uses?
Snow depth, snow water equivalent, liquid fraction, depth of the water saturated layer, meltwater flow velocity and rate, hydraulic conductivity
12. List the measurable/adjustable parameters (e.g., snow surface aerodynamic roughness, maximum albedo at visible wavelength, etc, excluding initial conditions) your snow model uses?
solar albedo, emissivity, snow density (some of them will be later made to state variables)
13. What are the output data?
spatial distributions of user-selectable state variables for each time step
14. What computer language does your model use?
Interactive Data Language (IDL)
15. How many subroutines (or functions) does your snow model have?
Approx. 20 procedures plus a programming library of hundreds of procedures and functions for a large variety of purposes (e.g. GIS, RDBMS, mapping, math ...)
16. Number of lines of the snow code?
More than 1000 lines without the library code (rapidly increasing)
17. What is the recommended hardware?
Each system supporting IDL (PC, VMS, Unix, Mac, SG)
18. How does your model determine the form of precipitation (i.e., snowfall and rainfall)? Please give the formulation.
19. Is your snow model one dimensional or multi-dimensional? Please specify.
Horizontally distributed, vertically lumped
20. If one dimensional, how many layers are there in your snow model? Please specify layering structure.
One snowpack layer, implicit modeling of vertical processes
21. What is your snow model time step?
User-selectable (typically 1 hour)
22. Does your model snow albedo allow its
spectral differences (visible vs. near-IR)? X
directional differences (direct vs. diffuse)? X
23. Is your model snow albedo a function of
solar zenith angle
Actually adjusted e.g. by means of remote sensing data to a fixed
24. Does your snow model explicitly treat liquid water retention and percolation within the snowpack?
YES, since this is the main purpose of the model
25. Does your snow model account for changes in the hydraulic and thermal properties of snow due to meltwater refreezing?
26. Is snow density in your snow model changing with time or fixed?
Actually fixed, but this is subject of actual developments.
27. Is heat capacity and conductivity in your snow model changing with time or fixed?
Actually fixed, but this is subject of actual developments.
28. Does your snow model simulate vapor transfer in the snowpack?
29. Does your snow model account for the heat transfer between the bottom of the snowpack and the underlying soil?
30. In snow energy balance, does your model consider heat convected by rain or falling snow?
31. Does your snow model include snow drifting and redistribution by wind (or avalanche)? If so, how?
32. How is areal snow distribution treated?
Finite difference scheme based on a grid DEM
33. Does your snow model account for sub-grid (or sub-watershed) effects of topography? If so, how is temperature distributed?
Measured or adjusted lapse rate
how is precipitation (spatial, elevation and corrections) distributed?
how is solar radiation distributed?
Full numerical modeling of clear sky solar radiation, and further modified by empirical relations for concerning cloud effects.
how is wind distributed?
Actually fixed using measurements, but this is subject of actual developments.
how are other meteorological variables distributed?
34. Does your snow model consider snow-vegetation interaction?
35. Does the snow-vegetation interaction account for
different vegetation types (grass vs. forest),
different vegetation heights (short vs. tall),
different vegetation densities (small vs. large LAI),
different vegetation coverages (sparse vs. dense vegetation)?
36. Are snow interception, drip and melt on canopy surface allowed in your model?
37. How is the upper limit of the canopy interception determined?
38. In the presence of vegetation, how is snow surface albedo altered?
39. In the presence of vegetation, how is snow surface roughness altered?
40. In the presence of forest, does your snow model allow spatial variability of snow depth and water equivalent on forest floor?
41(a). How does your model deliver snowmelt to the soil system (e.g. affecting soil moisture)?
Infiltration is actually fixed to a value adjusted by the user
(b). Once snowmelt is generated, how does your model relate it to runoff?
Meltwater routing through the snowpack, runoff through snow-free channels under development
42. How is frozen soil treated in your model?
It strongly reduces infiltration (cf. 41(a))
43. Has your snow model been tested with the field data?
If so, what data? (areas)
what are their temporal and spatial scales?
Meteorological and snow-hydrological data sets for two drainage basins in the High Arctic (Spitsbergen) and in a subarctic region (N-Sweden). Data are from several field stations with temporal resolutions of one minute to one hour, covering a time period of several weeks each year (snowmelt period).
44. Has your snow model been used together with remote sensing data as input?
If so, how?
Particularly for determining the spatial distribution of the solar albedo
45. If your snow model is coupled with a numerical weather forecasting model or climate model, has the model snow product been compared with satellite data? If so, what satellite data were used?
46. Please list any other previous applications.
Risk assessment for slushflow release.
47. Please specify verification criteria, if any?
Comprehensive comparisons of measured and modeled solar radiation. Actually, meltwater flow rates, velocities and accu- mulation are checked against field measurements by dye tracers and pressure transducers
48. What are the model fitting procedures, if any?
49. What are future plans for using/improving the model?
RGM will be further developed to fully model the spatial distri- butions of all energy and water balance components including times without snowmelt conditions. This includes to consider precipitation and infiltration losses in detail. Channelled runoff will become an important part to study particularly extreme events not feasible by temperature index methods. In a later stage, the model will also consider mechanical snow properties to simulate mass transports as wind drift, (avalanches ?) and slushflows.
50. Please provide references relevant to the model description and use.
Publications are in preparation!