Yann H. KERR & SMOS SM Team. Porto 17:4/2003

Transcription

1 Yann H. KERR & SMOS SM Team Porto 17:4/2003

2 Main factors controlling the water, energy and carbon fluxes Atmosphere Control (Radiation) Surface Surface Control Control YHK-Porto (Soil (Freeze/Thaw) Moisture)

3 Role of Soil moisture in surface atmosphere interactions: storage of water (surface and root zone), water uptake by vegetation (root zone), fluxes at the interface (evaporation), influence on run-off Implies relevance for Weather Forecasts Climatic studies Water resources crop management Forecast of extreme events YHK-Porto

4 50S 50S 51S 51S 52S 52S 53S 53S 54S 54S 55S 55S E 60E SUMMER 1993 RAINFALL MINUS SUMMER 1988 RAINFALL Observations 50N 50N 40N 40N Predictability of seasonal climate is dependent on boundary conditions such as SST and soil moisture. In this sensitivity study it is shown that modeled summertime regional rainfall is more a function of soil moisture than SST boundary specifications. 30N 30N 20N 20N Model driven by by SSTs Model driven by by SSTs and soil moisture 50N 50N 50N 50N 40N 40N 40N 40N 30N 30N 30N 30N 20N 20N 20N 20N (mm/day) YHK-Porto

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6 Soil moisture is an important variable in hydrology, meteorology/climatology, ecology, biogeochemical cycles Surface soil moisture plays 2 major roles : It controls runoff/infiltration partition It controls evaporation (& LH) fluxes However, the objective is to represent the coupled atmospheric + SVAT + hydrological system What can surface soil moisture bring in terms of information /constraints with respect to deeper zones? Currently there are no global measurements of soil moisture available YHK-Porto

7 Inputs Precipitations Satellite & ground networks Irrigation pumping Ouputs Evapo-transpiration Models and satellite Run off Models (+ satellites), outflow Storing by difference? Issues depletion, quality of storage salinisation Extreme events YHK-Porto

8 Knowledge of the water cycle Precipitation Runoff and Infiltration evaporative demand Surface measurements, Remote Sensing and, Modelling Understand the dynamics of water and solute balances in semiarid regions at large spatial and temporal scales (i.e. the river basin scale and decadal and longer time scales). Vegetation and Vadose Zone Process of the Basin Floor Basin-Scale Hydrologic Systems YHK-Porto

9 Approximately 33% of the land surface of the Earth is arid or semiarid. The semi-arid regions are experiencing higher than average rates of population growth and development, and are therefore faced with the critical problem of how to support sustainable development and, in particular, how to provide sustainable resources of water. Among the key issues faced by such regions are the water supply (including quantity and quality) and ecosystem health. Policy decisions, planning and management are complicated by various factors including a variable and uncertain global climate, strong heterogeneities in ecology and topography, and rapidly changing land use. Water as a Resource: Competition, Conflict, Planning and Policy YHK-Porto

10 Soil moisture is an important variable in hydrology, meteorology/climatology, ecology, biogeochemical cycles Currently there are no global measurements of soil moisture available Sea Surface Salinity is an important variable in assessing ocean circulation and understanding water cycle Currently there are no global and regular measurements of SSS YHK-Porto

11 Measuring soil moisture Laboratory Oven-drying soil samples chemical methods In situ neutron probes resistivity Remote sensing IR passive and active microwaves Remote sensing using microwaves opens a way towards surface soil moisture mapping YHK-Porto

12 Brightness Temperature (K) Total Brightness Soil Vegetation 0 Sky Canopy Water Content (kg/m2) TB obs = TB sky + TB veg + TB soil Galactic TEC Atmosphere T sky TB sky TB veg TB soil O2, IWC, T, ILWC, rain, and resp heights Vegetation { T veg T veg Tv, ω, WC, structure,s Soil Surface σ,ts,s/c,ρ, T soil YHK-Porto SM

13 Influence of vegetation on radiometric sensitivity to SM In order to penetrate vegetation cover, lowest possible frequencies should be selected. F < 1GHz : large Faraday effects Then the protected frequency is : 1.41 GHz! YHK-Porto

14 T B sensibilité YHK-Porto

15 Mission specifications Soil Moisture (SM) multi-angular dual pol 4 % vol 3 day revisit (Vegetation 7 day) better than 50 km ESTAR-Derived Soil Moisture Image from SGP 97 Jackson, 1999 Predicted Vol. Soil M oisture (% ) CF LW Observed Vol. Soil Moisture (%) SM distribution over a watershed Pellenq, 2001 YHK-Porto

16 View angle configuration (SMOS) SMOS s Footprint Satellite Spacecraft velocity Earth Swath 1000 km η m d N 30 Local incidence angle θ θ = 55 Nadir path η m = Half Swath Angle Walteufel, 01 YHK-Porto

17 SMOS FOV; 756 km, 3x6, 32, 0.875λ, scl=1 ; abscissa y along track - teta : across track km - inci = elo = 1.5 reso (3) = YHK-Porto

18 Surface soil moisture Usefulness in models Spatial resolution Global coverage Temporal resolution Issues Vegetation contribution deeper soil moisture mixed pixels Topography /roughness 4 % Vol <1 to 100 km < 3 days Direct measurement L band Antenna size Large FOV Large FOV Use several frequencies or angles SVAT assimilation Other wavelengths, a priori knowledge YHK-Porto

19 T B Observations are sensitive to three main surface variables: -soil moisture w S (m 3 /m 3 ) -vegetation optical depth τ -surface temperature - w S and T S can be obtained from the SVAT simulations - How can we account for vegetation optical depth τ? Approach I: τ = b. VWC the vegetation water content VWC can be obtained from ancillary data (SPOT,...)? Approach II: Approach III: τ can be retrieved from the multi-angular TB observations τ = K. LAI_ ISBA the Interactive vegetation parameters (G M, BsL, D E ) can be retrieved from the TB observations YHK-Porto

20 (Boulet and al. 2000) 0 θ 0 evaporation Inter-storm Évaporation + percolation d z f (t+dt) A=θ 0 d Wg Potential Evaporation Rain p time de=edt K 0 dt infiltration Saturation exces Infiltration exces Runoff Runoff z Storm Infiltration + Runoff YHK-Porto

21 Coupling and desaggregation Scheme Wg mean, W mean t LE, Rn,H,G percolation Infiltration Saturation excess Runoff SVATSIMPLE TOPMODEL Subsurface flow DTM { Wg i }, { W i } t + dt Soil proprieties Wg mean, W mean t + dt YHK-Porto Pellenq et al.,

22 Results at catchment scale 1. Mean soil water content Rain S im ulated M ean S oil W ater C ontent O bserved m ean S oil W ater C ontent % (v/v) mm Day of Year 0 Pellenq et al., 2001 YHK-Porto

23 Data Assimilation Products Data Update Land Surface Modeled Physics Update Model Integrations Global at 5 km at model time-step L4_5km_4DDA product YHK-Porto

24 COUPLING INTERACTIVE VEGETATION MODEL (ISBA-AGS) and RT MODELS Climatic Données Data Climatiques (Rayon t, Ta, ua, qa,..) (Rg, Ta, ua, qa,...) Remote Sensing measurements W2_init Interactive Vegetation parameters: -Mes. Conductance G M -Biomass/LAI ratio: BsL -effective life Duration: D E Interactive SVAT MODEL Vegetation LAI Biomass w S, T S w 2, Fluxes Optical Depth = K. LAI Radiative Transfer. Model of T B T B, σ Soil / Vegetation Parameters Wigneron et al., 2001 YHK-Porto

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26 Proof of Concept --> HUT 2D Cities and RFI --> Eurostarrs + models Topography --> SMMR + models Physics (vegetation) --> Avignon/ SMOSREX Physics (forest) --> Models + EUROSTARRS Bordeaux, Agre? Mixed pixels --> Simulations Eurostarrs, SGP and SMEX assimilation and use in models --> ELDAS Other uses --> YHK-Porto

27 Physics of measurements long terma data set ( --> SMOSREX) and perturbating factors --> Frost, snow, dew atmospheric effects others effects rain and interception, litter angular effects on b, ω calibration --> Assimilation YHK-Porto

28 Avignon 2001 YHK-Porto

29 See other presentations at EGS Miller et al, 2002 YHK-Porto

30 Instrumentation SMOS - CESBIO/CNRM Profil humidité et température du sol, radiomètre micro ondes 1.4 Ghz PC Consultation CESBIO PC Consultation CNRM Modem PC visualisation télétransmission des données PC acquisition Hub / 8 Carte multivoie série Station de mesure Sol Nu CESBIO Pseudo Modem RS 485 Station de mesure Prairie CNRM YHK-Porto

31 Lemaitre, 2002 Root zone soil moisture 0,5 0,45 0,4 Volumetric moisture 0,35 0,3 0,25 0,2 YHK-Porto time

32 The radiometer F. Lemaître ONERA YHK-Porto

33 Sky measurements ONERA/DEMRT François Lemaître Elévation Total mesuré Total mesuré Total Polar H Polar V attendu degrés mini maxi mini maxi mini maxi Soleil. 2 YHK-Porto

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35 SMOS Mission will fill a significant gap Soil moisture fields globally and with adequate time sampling Derivation of vegetation characteristics Potentially other parameters assimilation and root zone soil moisture Disaggregartion and soil moisture Still issues to be solved (Topography, frost,forest, litter,...) Many other applications Retrieval algorithms Cal Val activities Plenty of Scope for collaborations! YHK-Porto