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

Institute of Atmospheric Physics/Chinese Academy of Sciences Land-Surface Model (IAP94)

2. Name and address of model developer;

Yong-jiu Dai
Qing-cun Zeng
Institute of Atmospheric Physics
Chinese Academy of Sciences
P.O. Box 2718
Beijing 100080

3. Name and address of model user;

Yong-jiu Dai
Qing-cun Zeng
Institute of Atmospheric Physics
Chinese Academy of Sciences
P.O. Box 2718
Beijing 100080

4. Please indicate whether your model is developed for application

   in understanding snow processes,      
   in a runoff forecasting model,	  
   in a weather forecasting model,   
   in a global climate model (GCM),     X    
   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);

Institute of Atmospheric Physics land surface model (IAP94) is a comprehensive one with detailed description for the processes of vegetation, snow cover and soil. Particular attention has been paid to the cases with three water phases in land surface media. On the basis of the mixture theory and the theory of fluid dynamics of porous media, the system of universal conservational equations for water and heat of snow, soil and vegetation canopy has been constructed. On this background, all important factors that may affect the water and heat balance in media can be considered naturally, and each factor and term possess distinct physical meaning. In the computation of water content and temperature, the water phase change and heat transportation by water flow is taken into account. Moreover, particular attention has been given to the snow compaction. The model has been validated against field measurements in off-line experiments. The model has been implemented into IAP GCM and 100-year control run was conducted.

7. Please specify any known application range or restrictions;

Climate modelling, numerical weather prediction, snow hydrology and snow thermal dynamics

8. What are the development data needs;

we can not obtain any observation data for evaluating our model performance. What we have done was model intercomparison with CRREL snow model (SNTHERM, R. Jordan). Net radiation, sensible and latent heat fluxes, snow water equivalent, snow depth, snow temperature, soil moisture, soil temperature are intercompared.

9. What are the operational data needs?

downward solar radiation
downward longwave radiation
screen air temperature
air humidity
wind velocity

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                     : X
   surface pressure                : X 

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

Snow temperature
Snow depth
Partitial densities of liquid water, ice and water vapor of snow pack

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?

maximum and minimum of snow albedo,
specific heat of snow,
maximum water saturation rate of snow layer,
coefficient for estimation of heat conductivity of snow layer,
depths of surface and bottom snow layers.

13. What are the output data?

Snow temperature
Snow depth, snow mass
Partitial densities of liquid water, ice and water vapor of snow pack
surface absorbed net radiation, surface sensible heat flux 
   and latent heat flux
surface albedo

14. What computer language does your model use?


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

Ten subroutines are specified for snow model,
(1) Prescribe the precipitation whether rainfall or snowfall, calculation 
    the temperature of the water of precipitation
(2) When the accumulation of new snow reaches 1 cm, Initialize a new snow layer.
(3) Calculate the heat balance of snow layers, soil layers and canopy
(4) Calculate the water balance of snow layers, soil layers and canopy
(5) Calculate the melting, freezing and vaporizing of water in canopy, snow and soil media
(6) Calculate the evaporation and transpiration fluxes, and sensible heat fluxes
(7) Calculate the snow compaction
(8) Calculate the porosity and modify partital density of water
(9) Subdivide the snow layers
(10)Combine the snow layers

16. Number of lines of the snow code?

Difficult to count for snow specified

17. What is the recommended hardware?

Convex C3-120, SGI workstation, DEC workstation. I believe it can be used directly on any computers

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

Upper limit of temperature for snowfall at 275.65 K
          If(surface air temperature .GT. 275.65) then
            precipitation = rainfall
          Else if (surface air temperature .LE. 275.65) then
            precipitation = snowfall

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.

Maximum layers set to 3
     IF (snow depth .LT. 1cm) then
        It will be combined with surface soil layers, it is meant that
        this thin snow is specified as a component of the soil water 
        (ice and liquid) in surface soil layer, but the effect on 
        surface albedo is considered.
     If (snow depth .GE. 1cm .AND. snow depth .LT. 2cm) then
        one layer is specified;
     If (snow depth .GE. 2cm .AND. snow depth .LT. 5cm) then
        two snow layers are specified,
        surface layer thickness limited in the range of 1cm - 2cm,
        subsurface layer thickness limited in the range of 1cm - 3cm
     If (snow depth .GE. 5cm) then
        three layers are specified,
        the bottom snow layer thickness limited in the range of 
            1cm - non-limited
Note: with the snow accumulating or ablating or compaction, the snow 
layers will be subdivided or combined simultaneously at the end of 
each time step.

21. What is your snow model time step?

One hour or half hour (which is an adjustable variable according to the resolution of forcing data)

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

      snow age                 X
      grain size               X  
      solar zenith angle       X
      pollution                X
      snow depth?              X

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


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?

Changing with time.

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

Changing with time.

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?

The same method as BATS was taken.

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?

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


35. Does the snow-vegetation interaction account for

 different vegetation types     (grass vs. forest),            X
 different vegetation heights   (short vs. tall),              X
 different vegetation densities (small vs. large LAI),         X
 different vegetation coverages (sparse vs. dense vegetation)? X

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?

0.1 (mm) X LAI

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

With similar formulation of BATS

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

A simple area weighted method according to the fraction of vegetation cover, and the canopy height and snow thickness.

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)?

By the hydraulic conductivity of snow media

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

(1) When the snowmelt is greater than the water conductivity of snow layer, the surplus water will be put into surface runoff; (2) When the vertical water flow (flux) at the interface between soil and snow is greater than the maximum infilitration of surface soil layer, the surplus melt snow will be put into surface runoff; (3) When the the surface soil layer is impermeable or saturated, the melt snow arriving the interface of soil and snow will be put into the surface runoff

42. How is frozen soil treated in your model?

Based on the mixture theory, the frozen soil is treated as the chang e of the partitial densities of soil water

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


If so, what data?

what are their temporal and spatial scales?

(1) U.S. Army Cold Region Research and Engineering Lab. field observation data, 15 days, stand-alone; (2) PILPS Valdai experiments, 18 years, stand-alone; (3) Six former U.S.S.R. observation station data, 6 years, stand-alone

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


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?

It has coupled with Institute of Atmospheric Physics GCM, but the mo del snow product is not compared with the satellite data.

If so, what satellite data were used?

46. Please list any other previous applications.

Only evaluating experiments which listed in question (43) were taken.

47. Please specify verification criteria, if any?

We just took the model intercomparison with SNTHERM. In intercomparing, two models' net radiation, sensible and latent heat fluxes, snow water equivalent depth and snow thickness, snow temperature in each layer are highligted.

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

At the present step, we just finished the model evaluation with CRREL and PILPS Valdai, the evaluation by the former U.S.S.R. six Stations data are on going. In fact, there are only meteorological forcing data for our use in former two data, we did not make any tunning, so we have not the model fitting procedures.

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

(1) Develop a new and advanced numerical scheme for the calculation
    of snow hydrology and soil moisture, and for the calculation of 
    snow and soil temperature.
(2) Include a detail runoff model
(3) Implement it into IAP high resolution GCM (18 vertical levels)
(4) Implement it into a regional GCM
(5) Control and sensitive runs with the coupled model
(6) Investigate the mechanism of the Asian monsoon by the coupled 
    model (Global and Regional models)

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

Dai Y-J and Zeng Q-C (1997): A Land Surface Model (IAP94) for Climate Studies, Part I: Formulation and Valiadation in off-line Experiments, Advances in Atmospheric Sciences, 14, 433-460.

-- Last updated Fri Oct 8 12:47:54 MST 1999 by Zong-Liang Yang.
For questions and comments, please contact Zong-Liang Yang