MODIS Remote Sensing. Dr Helen Cleugh CSIRO Marine and Atmospheric Research June 14, 2011

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1 Regional Land Surface Evaporation using MODIS Remote Sensing Dr Helen Cleugh CSIRO Marine and Atmospheric Research June 14, 2011

2 Acknowledgements e to CSIRO Colleagues Ray Leuning and Yongqiang g Zhang Edward King and WIRADA project on ET Intercomparisons

3 Context: Terrestrial carbon and water budget dynamics Goal: Fine space and time scale assessments of surface energy, water and carbon exchanges for regions and continents ( m; weekly to monthly) Flux station measurements are key, but not sufficient Net CO 2 and water vapour fluxes highly resolved temporally, but spatially-averaged at smaller scales only (up to 10 3 m) Advanced land surface models (e.g. CABLE) not yet adequate for near real time, operational delivery MODIS remote sensing provides space/time coverage 250 m - 1 km resolution; global domain; 8 and 16 days But, measure radiances not fluxes

4 Challenge: Develop an operational model for land surface evapotranspiration (E, ET) that combines the continuity of flux tower measurements with space/time coverage of MODIS remote sensing s Inputs: routinely available over large regions, continents Robust: estimated ET constrained and insensitive to attributes of multi-temporal remote sensing Validated: using ET from a range of bioclimates and ecosystems Simple algorithm: for routine operational use

5 Surface energy balance and land surface evaporation from remote sensing Traditionally, the aerodynamic model is used: E AH A c ( T T )/ R p sa a a where T sa and T a: aerodynamic surface and air temperatures Assumes equality of radiative and aerodynamic surface Assumes equality of radiative and aerodynamic surface temperatures (i.e. T sr = T sa )

6 Ts ( o C) Average Tsa sa Avg-LST Average T sr Tumbarumba /02/01 31/07/01 27/01/02 26/07/02 22/01/03 21/07/03 17/01/04 Small differences between radiative and aerodynamic surface temperatures lead to large differences in estimated evaporation Tumbarumba m -2 ) E (W Measured Modelled 01/02/01 31/07/01 27/01/02 26/07/02 22/01/03 21/07/03 17/01/04

7 ET from Penman-Monteith Penman-Monteith equation for surface evaporation: E surface A ( c / )D G p a a (1) 1 G /G A available energy Da water vapour deficit G a aerodynamic conductance G s surface conductance- we model this latent heat of vaporisation s/ a s

8 ET from Penman-Monteith: Summary of Inputs Gridded meteorology (1 or 5 km) for the Australian continent from Bureau (daily) Radiation T and RH Rainfall (where needed) MODIS remote sensing Leaf Area Index: 8-day/1km MOD15A2 LAI product Land Cover: Yearly/1km MOD12 land cover product Gridded annual albedo product Parameterisation ti and optimisation i using: Eddy fluxes from FluxNet Catchment water balance in gauged catchments

9 Modelling surface conductance for landscapes using MODIS Leaf Area Index (LAI) product 1. Cleugh et al (2007) G c L G s L ai smini Mid Summer, Monthly ET

10 2. Leuning et al (2008): Separating canopy and soil E E (2) E surface canopy soil f varies from 0 (dry) to 1 (wet) soil Esoil f A 1 Asoil = A exp(- kalai ) (3) E canopy A ( c / )DG c p a a (4) 1G /G a c G c g sx Qh Q 50 1 ln kq Qh exp( kq Lai ) Q50 1 Da / D50 stomatal light humidity deficit (5)

11 Penman Monteith Leuning (PML) model for land surface evaporation Combine, rearrange and solve for surface conductanceg s G s G c G a ( 1)( 1 f )G c Ga 1 f ( 1)G G G ( 1)( 1 f )G c Ga 1 f G a Gi c a i 6 parameters g sx, f, k A, k Q, Q 50, D 50 but no significant loss in performance if all held constant except for g sx, f which are optimised using daily fluxes

12 Parameterise and validate PML model at 15 Fluxnet sites across a range of ecosystems and climates E meas = daily ET measured at flux towers E RS = PML model (2-parameter for G s ) and MODIS L ai 6 5 (d) y = 0.82x N = 1197 R 2 = 0.82 E m/d) (mm/d) RS2 E RS (mm Y = 0.85x N=1197 R 2 = 0.82 Leuning et al (2008) E (mm/d) E meas 6 meas (mm/d)

13 3. Zhang et al (2008): Modelled E RS for Murray Darling Basin (MDB) Optimise g sx, f by minimizing difference between mean annual E PML and E WB Single value for each rainfall zone in the MDB E WB are 5-year averages using water balance for 120 gauged g catchments

14 5-year average age E RS vs E WB for 135 catchments ts 1000 y = 1.05x R 2 = (mm/yr) ERS ( E WB (mm/yr) Zhang et al (2008)

15 5-year average E RS vs E WB for 120 gauged catchments in MDB (Zhang et al, 2008) E WB are 5-year averages using water balance for 120 gauged catchments in MDB Performance comparable to calibrated rainfall runoff model (SIMHYD) and better than Budyko climatological approach The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

16 and measured vs modelled runoff R RS and R SIMHYD Annual runoff from SIMHYD, a rainfall runoff model calibrated using runoff from gauged catchments Annual modelled runoff RSIMHYD R (m mm/yr) 800 y = 0.80x 600 R 2 = 0.76 RMSE=70.6 mm/yr CE= from P - E RS R meas (mm/yr)

17 4. Zhang et al (2010): Including soil water constraint t and finer scale information o PML model overestimates ET in some semiarid and arid catchments Improve parameterisation of g sx and f : Using water balance to constrain Better knowledge of their spatial distribution Optimise g sx for each grid cell by optimising i i PML against a calibrated water balance model (Budyko-style, y Fu model)

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19 From Dr Edward King, CSIRO s Water for a Healthy Country Flagship (2009)

20 Concluding Comments ET measurements can improve estimates of catchment yield in ungauged basins and water availability Energy constraint Largest term and spatially-averagedaveraged Developed an approach combining flux measurements, Penman Monteith model and remote sensing Energy constraint and robust Biophysical i model for Gs using remote sensing Reasonable performance for ET and runoff Further work: Remotely-sensed measurements to quantify f Carbon fluxes (GPP, NEE) The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology

21 CSIRO Marine and Atmospheric Research Helen Cleugh Web: Thank you Contact Us Phone: or enquiries@csiro.au Web: