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Layout. Introduction General remarks Model development and validation The surface energy budget The surface water 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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Layout • Introduction • General remarks • Model development and validation • The surface energy budget • The surface water budget • Soil heat transfer • Soil water transfer • Snow • Initial conditions • Conclusions and a look ahead PA Surface III of IV - training course 2010
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 2008
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 2008
Rosenberg et al 1983 Arya 1988 Soil properties PA Surface III of IV - training course 2008
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 2008
TESSEL skin temperature equation • Grid-box quantities PA Surface III of IV - training course 2008
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 2008
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 2008
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 2008
TESSEL soil energy equations j-1 Gj-1/2 Tj Dj Gj+1/2 j+1 PA Surface III of IV - training course 2008
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 2008
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 2008
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 2008
Apparent heat capacity Winter: Soil water freezing Soil heat transfer equation in soil freezing condition PA Surface III of IV - training course 2008
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 2008
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 2008
Layout • Introduction • General remarks • Model development and validation • The surface energy budget • The surface water budget • Soil heat transfer • Soil water transfer • Snow • Initial conditions • Conclusions and a look ahead PA Surface III of IV - training course 2008
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 2008
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 2008
> 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 2008
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 2008
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 2008
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 2008
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 2008
TESSEL soil water equations (2) PA Surface III of IV - training course 2008
Layout • Introduction • General remarks • Model development and validation • The surface energy budget • The surface water budget • Soil heat transfer • Soil water transfer • Snow • Initial conditions • Conclusions and a look ahead PA Surface III of IV - training course 2008
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 2008
Snow energy budget PA Surface III of IV - training course 2008
Snow mass budget • Snow mass (S) and snow depth (D) PA Surface III of IV - training course 2008
Metamorphism, density and albedo • Density • Weighted average between current density and the density of fresh snow, in case of snowfall • Exponential relaxation • Albedo • Exponential relaxation with different time scales for melting and non-melting snow PA Surface III of IV - training course 2008
Tobs Tmod albedo Case study: Boreal forest albedo (1) 2m temperature at BOREAS, Canada, 18 LT Observations vs 48 h forecast PA Surface III of IV - training course 2008
Observed albedo BOREAS 1994 Grass EC control (CON) Aspen EC forest albedo (FAL)1 Conifers Viterbo and Betts, 1999: J. Geophys. Res., 104D, 27,803-27,810. Case study: Boreal forest albedo (2) PA Surface III of IV - training course 2008
Case study: Boreal forest albedo (3) PA Surface III of IV - training course 2008
Northern Hemisphere 0 FAL FAL Forecast day Forecast day 0 0 10 10 -1 CON CON Case study: Boreal forest albedo (4) 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 2008
1997 Operational Bias (FAL) 1996 Operational Bias (CON) Case study: Boreal forest albedo (5) • 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 2008
BOREAS evaporation: One-column integration TESSEL FAL van den Hurk et al 2000 Jan 1994 Jan 1995 Jan 1996 Evaporation: “The sting in the tail” (1) • The model FAL (before tiling) erroneously transform the available energy into evaporation. However, plants have limited transpiration in winter/spring, when the roots are frozen. • The TESSEL model (ECMWF July 2000) simulates much better that behaviour thanks to forest shielding effect (for the tile “snow under the trees”). PA Surface III of IV - training course 2008
Evaporation: “The sting in the tail” (2) PA Surface III of IV - training course 2008
RT P RS Energy budget LE E H Y 65 134 Wm-2 27 40 mmd-1 0.9 1.4 2.2 Summary: Energy and Water budgetsthe NWP perspective Water budget With S (water storage: accounting for soil moisture and snow PA Surface III of IV - training course 2008
Summary: Energy and Water budgetsthe NWP perspective • The NWP model evolves the land surface state but introduces errors • The Data Assimilation (DA) corrects those errors at each cycle (when obs. Are available) to produce a better initial condition for next forecast PA Surface III of IV - training course 2008