1. Please write down the name (and abbreviation) of your snow model or land-surface model with snow component?

ISBA-ES (Interactions between Soil, Biosphere and Atmosphere-Explicit Snow) (ISBA is used to represent the soil-vegetation component)

2. Name and address of model developer;

   Aaron Boone

   The model was developed while at:

   Centre National Recherche Meteorologique
   (National Center for Meteorological Research)


   42 ave. Coriolis

   Toulouse Cedex, France 31057


   Current affiliation:

   Centre d'Etudes Spatiales de la BIOsphère
   (Center for the Study of the Biosphere from Space)
   18, avenue Edouard Belin
   31401 Toulouse Cedex 9
   Tel : (33) 5 61 55 85 97 
   Fax : (33) 5 61 55 85 00

3. Name and address of model user;


   as above:
   There are many users by various research groups in France...

4. Please indicate whether your model is developed for application

   in understanding snow processes,     Yes

   in a runoff forecasting model,	    Yes (Operational SIM modeling system)

   in a weather forecasting model,      Yes: Mesoscale research model: Meso-NH

   in a global climate model (GCM),     Eventually in the Météo-France GCM ARPEGE

   or other (please specify)?

5. The first year when the model was used;


6. One paragraph description of your model (e.g. abstract from report or paper);

ISBA-ES is a so-called intermediate complexity snow scheme intended for hydrological and meteorological modeling applications. It has been introduced into ISBA (although it can be run independently) in an effort to better understand which snow processes are the most important for atmospheric and macroscale hydrological applications. Compared to the simple baseline ISBA snow scheme, the explicit multi-layered (with thicknesses varying in time) approach resolves the large vertical density and temperature gradients which can exist in the snow pack, distinguishes the thermal properties between the snow and the composite soil-vegetation layer, includes the effects of liquid water transmission and storage refreezing in the snow pack, and models the absorption of incident radiation within the snowpack. Recent new modules under development include a snow-grain size prognostic variable (and a corresponding new snow albedo routine), and a routine to remove or add snow mass (and energy) owing to drifting between adjacent grid cells.

7. Please specify any known application range or restrictions;

Model time steps of up to one hour have been tested with success: this is probably the upper limit. Also, as ISBA is a composite soil-vegetation model, there are currently no explicit interactions between ISBA-ES (the snow surface) and the canopy (as it is not explicitly resolved in ISBA).

8. What are the development data needs;

Atmospheric Forcing and as much observational data as possible (one or more of the following: snow runoff, snow depth, SWE, density, albedo, snow temperatures, surface fluxes...)

9. What are the operational data needs?

Atmospheric forcing and initial snowpack depth or SWE (and, not required but good if available, snow liquid water content, density, snow albedo). Restart files contain the enthalpy (N-layers), SWE (N-layers), density (N-layers) and albedo.

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                     : ~currently testing adding this aspect

   surface pressure                : X

11. List the state variables (e.g., snow temperature, snow water equivalent, etc) your snow model uses?


    Prognostic variables - 4 (saved in time by model):

    for N-layers: Heat content (enthalpy), density, SWE
    for uppermost layer only: albedo

    Diagnostic (used in computations):

    Snow temperature, layer thicknesses, liquid water content, thermal
    conductivity and heat capacity


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?


    -snow surface aerodynamic roughness (not an adjustable parameter:
     computed by the model)

    -maximum and minimum albedo (fixed unless there

     is a reason to change them: eg. testing, experiments...)

    -minimum turbulent exchange coefficient (maximum bulk Richardson number)

     this aspect is being tested
    -snow surface roughness length (default values are used unless ancillary
     information is available)

13. What are the output data?


    snow depth (total thickness for each layer)

    SWE (total and for each layer)

    liquid water content (total and for each layer)

    snow temperature profile (for each layer)

    snow density profile (snowpack avg and for each layer)

    snow albedo

    surface radiative and turbulent fluxes

    soil/snow flux

    snow runoff (liquid water exceeding the snowpack holding capacity)

14. What computer language does your model use?

F77 and F90 (although the F77 ISBA codes are no longer supported)

15. How many subroutines (or functions) does your snow model have?


    in F90:

    -there is a routine which acts as interface between

    snow scheme and SVAT (makes conversions and calls

    snow scheme)...in stand-alone mode this is replaced by

    a "driver"


    -there is the main snow routine (called by the above)

    -the main routine then calls 23 subroutines

    -in F90 mode, there are also several modules (shared

    with rest of ISBA scheme and atmospheric model which define universal

    constants, physics modules (thermodynamic computations)
    and tridiagnonal matrix solver, etc...)

    - in the F77 code: approximately the same

16. Number of lines of the snow code?

F90 2326 total lines: of which less than approximately 50% are actual executable lines of code: the rest are comments.

17. What is the recommended hardware?


    The code has been compiled and run on:

    F77: UNIX HP workstation, Linux PC (GNU F77 compiler)

    F90: UNIX HP workstation, CRAY ymp, Fujitzu (similar to CRAY),
         Linux PC (Portland Group F90/F95 Compiler, Intel F90/F95 compiler)

    *(Code in F77 is scalar, F90 code is vectorized and follows the coding norms/
      /standards/rules for use in Meso-NH: the mesoscale atmospheric model)

18. How does your model determine the form of precipitation (i.e., snowfall and rainfall)? Please give the formulation.

There is no fixed method as of now: in the operational hydrological forecast system SIM, the components are provided (based on analysis). For Alpine local scale studies, precipitation type has been discerned by instrumentation. Essentially, the snow/rain partitioning is determined "outside" of the snow model.

19. Is your snow model one dimensional or multi-dimensional? Please specify.


20. If one dimensional, how many layers are there in your snow model? Please specify layering structure.


    3 layers is the DEFAULT configuration 
   (Note that N-layers are possible:
    N is simply a USER input parameter...HOWEVER...only values of N up to 10
    have been tested thoroughly) 

    For the default 3-layer configuration:

    each layer has a thickness D_i

    Zt (total snow depth) = D_1 + D_2 + D_3

    When Zt <= 0.03 m;
    D_i = Zt/3

    When 0.03 < Zt <= 0.20 m;

    D_1 = 0.25 * Zt

    D_2 = 0.50 * Zt

    D_3 = 0.25 * Zt

    When 0.20 < Zt <= 1.47 m;

    D_1 = 0.05 m

    D_2 = 0.34 * (Zt - D_1) + D_1

    D_3 = 0.66 * (Zt - D_1) - D_1

    When Zt > 1.47 m;

    D_1 = 0.05 m
    D_2 = 0.50 m
    D_3 = Zt - D_2 - D_1

    (i.e. for deep snow, do not let the ratio between
     the thicknesses of layers 1 and 2 exceed 10)

21. What is your snow model time step?

tests have been done using 5 to 60 minutes (time scheme is fully implicit)

22. Does your model snow albedo allow its

    spectral differences    (visible vs. near-IR)? 

    directional differences (direct  vs. diffuse)?

    No. Although with the new snow grain algorithm,
    tests are being done with this respect.

23. Is your model snow albedo a function of

      snow age                 X

      grain size               X

      solar zenith angle       

      pollution                X

      snow depth?             

      NOTE: a single time constant is used to implicitly

      model the 3 factors above. It decreases either linearly

      or exponentially depending on liquid water content of

      uppermost snow layer. It refreshes back to maximum if

      sufficient snowfall occurs.

24. Does your snow model explicitly treat liquid water retention and percolation within the snowpack?

Yes: a series of tipping buckets.

25. Does your snow model account for changes in the hydraulic and thermal properties of snow due to meltwater refreezing?

Yes: rainfall freezing and meltwater refreezing cause densification of the pack. Density, in turn, is used for all snow internal physics.

26. Is snow density in your snow model changing with time or fixed?

changing with time: due to compaction, new snow, and densification due to melt water retention and rainwater percolation, evaporation

27. Is heat capacity and conductivity in your snow model changing with time or fixed?


28. Does your snow model simulate vapor transfer in the snowpack?

it is used to affect the thermal conductivity: but mass transfer is neglected (the vapor transfer is NOT explicitly modeled). Currently, tests are being done to model vapor transfer (related to grain size growth)

29. Does your snow model account for the heat transfer between the bottom of the snowpack and the underlying soil?

yes: also advection of heat by melt water within the soil

30. In snow energy balance, does your model consider heat convected by rain or falling snow?

yes, by rain. Falling snow is assumed to have the same temperature as the snow surface.

31. Does your snow model include snow drifting and redistribution by wind (or avalanche)? If so, how?

Currently, No. But, a module has been developed which models the remove or addition of the mass and energy due to a "drift" sink/source. It is currently under development.

32. How is areal snow distribution treated?


    Snow fractions calculated based on vegetation cover

    fraction, roughness, SWE and snow depth and a single

    SWE based parameter:

    vegetation snow cover fraction and bare soil

    snow fractions are computed (standard GCM/atmospheric model
    empirical relations)

33. Does your snow model account for sub-grid (or sub-watershed) effects of topography? If so, how is temperature distributed?

how is precipitation (spatial, elevation and corrections) distributed?

how is solar radiation distributed?

how is wind distributed?

how are other meteorological variables distributed?

The model does not currently resolve sub-grid effects of topography explicitly.

34. Does your snow model consider snow-vegetation interaction?

implicit (snow fraction) as ISBA uses a composite soil/vegetation model (i.e. the canopy is not explicitly resolved). The main impact of vegetation on the snow model is through the snow cover area fraction relations, and the roughness of the vegetation (which influence the roughness over the snowpack).

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)?

The vegetation roughness (lengths), and LAI (which influence a host of vegetation parameters) which impacts the snow cover area fraction of the grid box.

36. Are snow interception, drip and melt on canopy surface allowed in your model?

Not explicitly

37. How is the upper limit of the canopy interception determined?


38. In the presence of vegetation, how is snow surface albedo altered?

total grid box albedo is snow fraction weighted total. vegetation albedo does not directly impact snow

39. In the presence of vegetation, how is snow surface roughness altered?

total surface roughness is the average of the snow fraction weighted portions over non-snow and snow covered portions of grid box

40. In the presence of forest, does your snow model allow spatial variability of snow depth and water equivalent on forest floor?

No (as the forest canopy is not explicitly resolved by ISBA)

41(a). How does your model deliver snowmelt to the soil system (e.g. affecting soil moisture)?

All liquid water in excess of lowest snow layer holding capacity leaves the snow pack: it is then partitioned into infiltration and surface runoff by ISBA runoff scheme based on surface soil wetness, ice content, soil properties and the sub-grid runoff parameters (VIC-type).

(b). Once snowmelt is generated, how does your model relate it to runoff?

see # 41a, 33

42. How is frozen soil treated in your model?

There is a two-layer soil ice algorithm in ISBA-Force-Restore: ice changes the soil thermal and hydrologic coefficients (using freeze/thaw - drying/wetting method). There are 2 explicit soil ice reservoirs/variables. ISBA-ES can also be used with a newer multi-layer soil-diffusive method. Here, ice content, liquid water and temperature are computed for N-layers using standard methods (thermal conductivity of Peters-Lidard et al., 1998: soil hydrological parameters from Cosby et al. 1984: mixed form Richard's equation for water flow: modification of soil hydrological and thermal properties in presence of soil ice: soil-water freezing curves used for phase change, etc..)

43. Has your snow model been tested with the field data?

    If so, what data?

    what are their temporal and spatial scales?


    Alpine data at two micrometeorological sites: 30 minute

    forcing covering a total of 5 years

    Alpine forcing data for the French Alps for

    a mesoscale/macroscale hydrological domain.

    24 snow depth stations (micro-met sites) and 120 river gauges

    for measuring discharge

    Also have re-run with PILPS Valdai, Russia data

    (author used this data with a different PILPS-Valdai participant scheme
    during PILPS), SnowMIP data, PILPS-2e data (as part of PILPS-2e), and
    data from Mt Atlas, Morocco.

44. Has your snow model been used together with remote sensing data as input? If so, how?


	Currently, snow-soil interface temperature data simulated by the model
	is being used in an effort to improve a snow depth/SWE retreival
	algorithm which uses SSM/I data over Siberia (ongoing),
	And results using the GSWP2 framework are being compared to snowmelt
	dates computed using another SSM/I based algorithm at a global
	scale (primarily above 40 deg N)

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.

47. Please specify verification criteria, if any?

48. What are the model fitting procedures, if any?

49. What are future plans for using/improving the model?


    -Ongoing tests with respect to albedo, turbulent transfer,

     liquid water processes and sub-grid effects AND interactions

     with frozen soil

    - further testing and development of a snow grain size 
	(prognostic variable) module

    - ongoing Snow MIP work

    - any future PILPS snow/cold climate work

    - GSWP2 sensitivity test runs

    - eventual use of this scheme as an option in the ARPEGE GCM

    - assimilation of microwave data

50. Please provide references relevant to the model description and use.


    -Technical Note (in English):

    Boone, A., Description du schema de neige ISBA-ES
    (Description of the snow scheme ISBA-ES)
    Note de Centre (Technical Note), CNRM Météo-France,
    Number 70, May 2002, 53 pp.   

    -Main published model (description) reference:

    Boone, A., and P. Etchevers, 2001: An intercomparison of three snow schemes
	of varying complexity coupled to the same land surface model: Local scale
	evaluation at an alpine site. J. Hydrometeor., 2, 374-394.

    - Some model intercomparison results (with discussions related directly to
	snow scheme physics or results)

    PILPS-2e: Habets, F., A. Boone, and J. Noilhan, 2003: Simulation of a Scandinavian 
	basin using the diffusion transfer version of ISBA, Glob. and Plan. Change, 38, 137-149

    (also see other PILPS-2e papers...)

    Rhone-AGG: Boone, A. et al., 2004: The Rhone-Aggregation land surface scheme 
	intercomparison project: An overview, J. Climate, 17(1), 187-208.

    -Other references using the scheme are available...