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Layout. Introduction General remarks Model development and validation The surface energy budget The surface water budget The surface CO2 budget Soil heat transfer Soil water transfer Snow Initial conditions Conclusions and a look ahead. Hillel 1982, 1998. Soil science miscellany (1).

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  1. Layout • Introduction • General remarks • Model development and validation • The surface energy budget • The surface water budget • The surface CO2 budget • Soil heat transfer • Soil water transfer • Snow • Initial conditions • Conclusions and a look ahead PA Surface III of IV - training course 2013

  2. Hillel 1982, 1998 Soil science miscellany (1) • The soil is a 3-phase system, consisting of • minerals and organic matter soil matrix • water condensate (liquid/solid) phase • moist air trapped gaseous phase • Texture - the size distribution of soil particles PA Surface III of IV - training course 2013

  3. Soil science miscellany (2) • Structure - The spatial organization of the soil particles • Porosity - (volume of maximum air trapped)/(total volume) Hillel 1982,1998 • Composition • Water content Reference:Hillel 1998 Environmental Soil Physics, Academic Press Ed. PA Surface III of IV - training course 2013

  4. Rosenberg et al 1983 Arya 1988 Soil properties PA Surface III of IV - training course 2013

  5. TESSEL • Skin layer at the interface between soil (snow) and atmosphere; no thermal inertia, instantaneous energy balance • At the interface soil/atmosphere, each grid-box is divided into fractions (tiles), each fraction with a different functional behaviour. The different tiles see the sameatmospheric column above and the samesoil column below. • If there are N tiles, there will be N fluxes, N skin temperatures per grid-box • There are currently up to 6 tiles over land (N=6) PA Surface III of IV - training course 2013

  6. TESSEL skin temperature equation • Grid-box quantities PA Surface III of IV - training course 2013

  7. Ground heat flux In the absence of phase changes, heat conduction in the soil obeys a Fourier law • Boundary conditions: • Top Net surface heat flux • BottomNo heat flux OR prescribed climate PA Surface III of IV - training course 2013

  8. summer winter surface bare sod summer 50 cm depth Diurnal cycle of soil temperature Rosenberg et al 1983 PA Surface III of IV - training course 2013

  9. TESSEL • Solution of heat transfer equation with the soil discretized in 4 layers, depths 7, 21, 72, and 189 cm. • No-flux bottom boundary condition • Heat conductivity dependent on soil water • Thermal effects of soil water phase change ↓0.1~0.6 d ↓1.1~5.8 d ↓10.6 ~ 55.8 d Time-scale for downward heat transfers in wet/dry soil PA Surface III of IV - training course 2013

  10. TESSEL soil energy equations j-1 Gj-1/2 Tj Dj Gj+1/2 j+1 PA Surface III of IV - training course 2013

  11. 140 m 2 m Soil Case study: winter (1) Model vs observations, Cabauw, The Netherlands, 2nd half of November 1994 PA Surface III of IV - training course 2013

  12. Observations: Numbers Model: Contour Case study: winter (2) Soil Temperature, North Germany, Feb 1996: Model (28-100 cm) vs OBS 50 cm PA Surface III of IV - training course 2013

  13. T air G T skin LE H Rnet Case study: winter (3) Viterbo, Beljaars, Mahfouf, and Teixeira, 1999: Q.J. Roy. Met. Soc., 125,2401-2426. • Model bias: • Net radiation (Rnet) too large • Sensible heat (H) too small • But (Tair-Tsk) too large (too large diurnal cycle) • Therefore f(Ri) problem • Soil does not freeze (soil temperature drops too quickly seasonally) Stability functions Soil water freezing PA Surface III of IV - training course 2013

  14. Apparent heat capacity Winter: Soil water freezing Soil heat transfer equation in soil freezing condition PA Surface III of IV - training course 2013

  15. Observations Stab+Freezing Stability Control 1 Jan 1 Feb 1 Nov 1 Oct 1 Dec Case study: winter (4) Germany soil temperature: Observations vs Long model relaxation integrations PA Surface III of IV - training course 2013

  16. Europe Stab+freezing Control Northern Hemisphere Case study: winter (5) 850 hPa T RMS forecast errors • Soil water freezing acts as a thermal regulator in winter, creating a large thermal inertia around 0 C. • Simulations with soil water freezing have a near-surface air temperature 5 to 8 K larger than control. • In winter, stable, situations the atmosphere is decoupled from the surface: large variations in surface temperature affect only the lowest hundred metres and do NOT have a significant impact on the atmosphere. PA Surface III of IV - training course 2013

  17. Layout • Introduction • General remarks • Model development and validation • The surface energy budget • The surface water budget • The surface CO2 budget • Soil heat transfer • Soil water transfer • Snow • Initial conditions • Conclusions and a look ahead PA Surface III of IV - training course 2013

  18. Jacquemin and Noilhan 1990 More soil science miscellany Hillel 1982 • 3 numbers defining soil water properties • Saturation (soil porosity) Maximum amount of water that the soil can hold when all pores are filled 0.472 m3m-3 • Field capacity “Maximum amount of water an entire column of soil can hold against gravity” 0.323 m3m-3 • Permanent wilting point Limiting value below which the plant system cannot extract any water 0.171 m3m-3 PA Surface III of IV - training course 2013

  19. Schematics Boundary conditions: Top See later Bottom Free drainage or bed rock Root extraction The amount of water transported from the root system up to the stomata (due to the difference in the osmotic pressure) and then available for transpiration Hillel 1982 PA Surface III of IV - training course 2013

  20. > 6 orders of magnitude > 3 orders of magnitude Soil water flux Darcy’s law Mahrt and Pan 1984 PA Surface III of IV - training course 2013

  21. TESSEL: soil water budget • Solution of Richards equation on the same grid as for energy • Clapp and Hornberger (1978) diffusivity and conductivity dependent on soil liquid water • Free drainage bottom boundary condition • Surface runoff, but no subgrid-scale variability; It is based on infiltration limit at the top • One soil type for the whole globe: “loam” PA Surface III of IV - training course 2013

  22. A new hydrology scheme • A spatially variable hydrology scheme is being tested following Van den Hurk and Viterbo 2003 • Use of a the Digital Soil Map of World (DSMW) 2003 • Infiltration based on Van Genuchten 1980 and Surface runoff generation based on Dümenil and Todini 1992 Van den Hurk and Viterbo 2003 PA Surface III of IV - training course 2013

  23. A new hydrology scheme(2) █coarse █medium █med-fine █fine █very-fine █organic Soil Diffusivity control Soil Conductivity control Dominant soil type from FAO2003 (at native resolution of ~ 10 km) PA Surface III of IV - training course 2013

  24. TESSEL soil water equations (1) ↓0.1~19.7 d ↓1.2~195.9 d j-1 Fj-1/2 ↓11.7 ~ >> d Dj Fj+1/2 Time-scale for downward water transfers in wet/dry soil j+1 PA Surface III of IV - training course 2013

  25. TESSEL soil water equations (2) PA Surface III of IV - training course 2013

  26. Layout • Introduction • General remarks • Model development and validation • The surface energy budget • The surface water budget • The surface CO2 budget • Soil heat transfer • Soil water transfer • Snow • Initial conditions • Conclusions and a look ahead PA Surface III of IV - training course 2013

  27. Snow • Snow insulates the ground (30% to 90% of the snow mantle is air) • A snow covered surface has a higher albedo than any other natural surface (0.2-0.3 in the presence of forests, 0.5-0.8 for bare ground/low vegetation) • Snow melting keeps the surface temperature at 0 C for a long period in spring PA Surface III of IV - training course 2013

  28. Snow energy budget Apparent heat capacity PA Surface III of IV - training course 2013

  29. Snow mass budget • Snow mass (S) and snow depth (D) PA Surface III of IV - training course 2013

  30. Metamorphism, density, albedo, • Density • Weighted average between current density and the density of fresh snow, in case of snowfall • Overburden, thermal metamorphism (new formulation) • Albedo • Exponential relaxation with different time scales for melting and non-melting snow • Surface albedo for high vegetation regions with snow underneath from MODIS • Snow cover fraction • Function of snow depth (10 cm deep – fully cover) PA Surface III of IV - training course 2013

  31. Case study: Boreal forest albedo (1) PA Surface III of IV - training course 2013

  32. Northern Hemisphere 0 FAL FAL Forecast day Forecast day 0 0 10 10 -1 CON CON Case study: Boreal forest albedo (2) 850 hPa temperature bias 20 forecasts every 3 days, March-April 1996 No data assimilation Eastern Asia 0 -1 -2 -3 Considering a lower value of snowForest ALbedo was beneficial. PA Surface III of IV - training course 2013

  33. 1997 Operational Bias (FAL) 1996 Operational Bias (CON) Case study: Boreal forest albedo (3) • The surface albedo is the direct regulator of the energy available to the surface. The albedo of natural surfaces has a limited range (0.1-0.3), but in non-forested snow covered areas can reach values up to 0.8. • Snow covered boreal forests have a much lower albedo than grassland to their south and tundra to their north; the presence of boreal forests has a direct control on the climate of high-latitudes. PA Surface III of IV - training course 2013

  34. Snow sublimation, role of roughness Dutra et al. 2008 30R1 32R1 PA Surface III of IV - training course 2013

  35. Snow insulation, role of snow density (1) • New snow formulation improves snow mass and snow density. • Lower snow densities -> increased snow thermal insulation Dutra et al. 2010 PA Surface III of IV - training course 2013

  36. Snow insulation, role of snow density (2) • Increased snow thermal insulation • Stronger decoupling of land –atmosphere • Warm T2M bias are reduced (soil was warming the atmosphere) • Clear impact on long climate runs • Small impact on short range forecasts Hazeleger et al 2010 PA Surface III of IV - training course 2013

  37. Liquid Water in the snow-pack • A diagnostic formulation can take into account liquid water in the snow pack without new prognostic variable (similar to soil ice) PA Surface III of IV - training course 2013

  38. Liquid Water in the snow-pack (II) • The liquid reservoir is function of temperature, snow mass and snow density PA Surface III of IV - training course 2013

  39. Snow density: I. New snow PA Surface III of IV - training course 2013

  40. Snow density: II. Snow on the ground In the old scheme rainfall infiltrates directly into the soil even in presence of snow on the ground. In the new snow scheme it is intercepted by the snow-pack PA Surface III of IV - training course 2013

  41. Forest-Snow Albedo • Albedo of Forest areas with snow underneath was fixed to 0.15 (quite dark). A MODIS-derived vegetation dependent albedo is used. PA Surface III of IV - training course 2013

  42. Open-Area Snow Albedo • Open area albedo is aging from 0.85 in case of fresh snow to 0.5 for old snow, however in case of new snowfall the albedo was istantaneously re-whitened to 0.85, regardless of the snowfall amount. PA Surface III of IV - training course 2013

  43. Snow fraction • Snow fraction is made dependent of snow depth rather than snow mass. • A 10cm snow depth is required for full coverage. PA Surface III of IV - training course 2013

  44. Verification PA Surface III of IV - training course 2013

  45. SNOW-MIP2 PA Surface III of IV - training course 2013

  46. GSWP-2 and Runoff verification PA Surface III of IV - training course 2013

  47. MODIS albedo as snow verification product PA Surface III of IV - training course 2013

  48. Summary and conclusions for snow processes impact The new snow scheme first validated in offline simulations (SNOW-MIP2 and GSWP2) and showed improvements on the water cycle and on the land albedo Further tests in forecasts mode both at ECMWF and in a climate model have demonstrated that snow can improve near-surface temperatures in cold climate. The introduction of multi-layer snow scheme is recognized as high priority in the next years to improve the representation of the diurnal cycle and introduce the right level of decoupling between snow and atmosphere. Perspectives for snow modelling PA Surface III of IV - training course 2013

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