1. Please write down the name (and abbreviation) of your snow model or land-surface model with snow component?
SNAP: Snowmelt Numerical-Analytical Package
2. Name and address of model developer;
Dr. Mary Albert
CRREL
72 Lyme Road
Hanover NH 03755-1290
malbert@crrel.usace.army.mil
3. Name and address of model user;
U.S. Army
4. Please indicate whether your model is developed for application
in understanding snow processes, X
in a runoff forecasting model, X
in a weather forecasting model,
in a global climate model (GCM),
or other (please specify)?
5. The first year when the model was used;
This is a new model, first phase completed May 1997. The U.S. Army is currently incorporating the model in it's spatially distributed modelling efforts for world-wide soil moisture strength prediction package.
6. One paragraph description of your model (e.g. abstract from report or paper);
This object of this work is to develop a new approach to point snow melt modeling that can more accurately predict magnitude and timing of snow melt than currently-employed operational models, but that is computationally simple enough to be employed in GIS distributed runoff forecasting systems. The melt movement through the pack follows a simplified physically-based algorithm to calculate flow within the pack and also includes refreezing within the pack. A surface energy balance using meteorological input drives the melt. The results of the model compare well to several years of field measurements obtained at the Sleepers River Research Watershed in northern Vermont (data on snow melt lysimeter outflow, local meteorology, and snow pack characteristics) In general, the new model predicts snow melt more accurately than the SRM model, and is many times computationally faster than SNTHERM.
7. Please specify any known application range or restrictions;
This is a new model and has not yet been tested on snow melt over permafrost conditions.
8. What are the development data needs;
Data used in the development and testing of the model included meteorological measurements, snow pack characteristics, and lysimeter snow melt outflow measurements. The model requires met input and the model output is snow depth, melt outflow, etc.
9. What are the operational data needs?
Meteorological input is needed for input to the model.
10. Please indicate with an "x" for those meteorological variables used to
DRIVE your snow model?
precipitation : X
air temperature : X
wind speed : X
wind direction :
humidity : X
downwelling shortwave radiation : X
downwelling longwave radiation : X
cloud cover :
surface pressure :
11. List the state variables (e.g., snow temperature, snow water equivalent, etc) your snow model uses?
Snow temperature, density, wetness
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?
Irreducible water saturation
13. What are the output data?
Snow pack depth, magnitude and timing of melt water outflow (hourly), effective grain size
14. What computer language does your model use?
FORTRAN
15. How many subroutines (or functions) does your snow model have?
12
16. Number of lines of the snow code?
approx 2500
17. What is the recommended hardware?
486 pc or better
18. How does your model determine the form of precipitation (i.e., snowfall and rainfall)? Please give the formulation.
Precipitation is input to the model. A user-definable air temperature cutoff is used to assess whether the precip is snow or rain, or the user can enter data that says whether the precip is snow or rain.
19. Is your snow model one dimensional or multi-dimensional? Please specify.
One-dimensional
20. If one dimensional, how many layers are there in your snow model? Please specify layering structure.
Currenly "effective pack"= one layer, but a multiple layer version is currently under development.
21. What is your snow model time step?
Since it uses a new analytical formulation for water movement through the pack (eliminating the need for matrix computations), there is no restriction on the time step. The time step is dictated by the frequency of the input data. Hourly input data is currently what we are using.
22. Does your model snow albedo allow its
spectral differences (visible vs. near-IR)?
directional differences (direct vs. diffuse)?
Not yet, but will in the future.
23. Is your model snow albedo a function of
snow age X
grain size
solar zenith angle
pollution
snow depth? X
Future updates to the model will include more focus on albedo.
24. Does your snow model explicitly treat liquid water retention and percolation within the snowpack?
Yes.
25. Does your snow model account for changes in the hydraulic and thermal properties of snow due to meltwater refreezing?
The version supplied to the Army now has constant properties, but current work on the model involves layering and property evolution.
26. Is snow density in your snow model changing with time or fixed?
Changes with time.
27. Is heat capacity and conductivity in your snow model changing with time or fixed?
Changes with time.
28. Does your snow model simulate vapor transfer in the snowpack?
No.
29. Does your snow model account for the heat transfer between the bottom of the snowpack and the underlying soil?
Yes.
30. In snow energy balance, does your model consider heat convected by rain or falling snow?
Yes.
31. Does your snow model include snow drifting and redistribution by wind (or avalanche)? If so, how?
No.
32. How is areal snow distribution treated?
This is a point model that can be used in any distribution scheme.
33. Does your snow model account for sub-grid (or sub-watershed) effects of topography? If so, how is temperature distributed?
NA
how is precipitation (spatial, elevation and corrections) distributed?
NA
how is solar radiation distributed?
NA
how is wind distributed?
NA
how are other meteorological variables distributed?
NA
34. Does your snow model consider snow-vegetation interaction?
Point model; meteorological input would be adapted to that in forests, etc.
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)?
NA.
36. Are snow interception, drip and melt on canopy surface allowed in your model?
NA.
37. How is the upper limit of the canopy interception determined?
NA.
38. In the presence of vegetation, how is snow surface albedo altered?
NA.
39. In the presence of vegetation, how is snow surface roughness altered?
NA.
40. In the presence of forest, does your snow model allow spatial variability of snow depth and water equivalent on forest floor?
NA
41(a). How does your model deliver snowmelt to the soil system (e.g. affecting soil moisture)?
The model simulates the movement of water through the pack, and the model output of flow out of the bottom of the pack could be linked to any soil model for transport or runoff.
(b). Once snowmelt is generated, how does your model relate it to runoff?
Currently linked to the Army's soil model.
42. How is frozen soil treated in your model?
Current version of the model addresses the snow pack only.
43. Has your snow model been tested with the field data?
Yes.
If so, what data? 5 years of meteorological, snow melt lysimeter, snow pit measurements at the Sleepers River Research Watershed in northern Vermont.
what are their temporal and spatial scales?
My data is 15 minute data over the course of 5 years, at a flat open spot. Snow pit data varies; sometimes multiple per day, other times weekly.
44. Has your snow model been used together with remote sensing data as input?
Not net.
If so, how?
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?
NA.
46. Please list any other previous applications.
NA.
47. Please specify verification criteria, if any?
48. What are the model fitting procedures, if any?
No fitting parameters or fudge factors, this is a physically based model.
49. What are future plans for using/improving the model?
Adding layering and snow pack characteristic evolution, refinements of grain size and albedo predictions.
50. Please provide references relevant to the model description and use.
M.R. Albert, G. Krajeski, 1998: A Fast, Physically-Based Point Snow Melt Model for Use in Distributed Applications", Hydrological Processes, 12 (11), 1809-1824.
M.R. Albert, 1998: Using an analytical solution to model a season of snow melt, A poster at the Intl Snow Hydrology Conference comparing SNAP to a year of snow melt lysimeter data.
Dr. Mary R. Albert Research Mechanical Engineer CRREL 72 Lyme Road Hanover, N.H. 03755-1290 tel: 603-646-4422 fax: 603-646-4278 email: malbert@hanover-crrel.army.mil