a network of scintillometers a network of scintillometers
play

A NETWORK OF SCINTILLOMETERS A NETWORK OF SCINTILLOMETERS FOR - PowerPoint PPT Presentation

A NETWORK OF SCINTILLOMETERS A NETWORK OF SCINTILLOMETERS FOR GROUND-TRUTHING OF SURFACE FLUXES IN NEW MEXICO Jan Kleissl, J. Gomez, S.-H. Hong, W. Defoor, K. Bandy, J.M.H. Hendrickx New Mexico Tech Outline Outline Ground Truthing for


  1. A NETWORK OF SCINTILLOMETERS A NETWORK OF SCINTILLOMETERS FOR GROUND-TRUTHING OF SURFACE FLUXES IN NEW MEXICO Jan Kleissl, J. Gomez, S.-H. Hong, W. Defoor, K. Bandy, J.M.H. Hendrickx New Mexico Tech

  2. Outline Outline • Ground Truthing for SEBAL NM Ground Truthing for SEBAL • Large Aperture Scintillometer (LAS): Principle of Operation Principle of Operation • LASs for Hydrology: The New Mexico T Tech LAS Network h LAS N t k • Preliminary validation results from SEBAL applied to MODIS for July 2006

  3. Energy Balance at the Earth’s surface R net = H + LE + G net R net : net radiation H R sd l: longwave; s: shortwave R lu u: upwelling p g d: downwelling g lu R su LE G: soil / ground heat flux H: sensible heat flux LE: latent heat flux LE: latent heat flux G E Energy balance can be used to estimate LE: b l b d t ti t LE LE = R net – G - H

  4. SEBAL NM ET from Landsat SEBAL: Surface Energy Balance Algorithm for Land SEBAL: Surface Energy Balance Algorithm for Land April 07 2000 June 16 2002 September 14 2000 Rio Grande basin, NM ET (mm/d) 0.0 0.0 < 1.0 < 2.0 < 3.0 < 4.0 ET < 5.0 E < 6.0 6 0 < 7.0 < 8.0 < 9.0 cold pixel: H = 0 ld i l H 0 Hot pixel: ET = 0 � H = R n - G BUT: dT dT Remote sensing algorithms need to be = ρ H c dT r / T T 0 T hot validated using ground-truth measurements p ah cold = f LAI α z ( , ) o o = r f u z z ( , , ) ah * o Hong, Kleissl et al. WRR 2006 [s m -1 ]

  5. The NMT LAS network for SEBAL NM The NMT LAS network for SEBAL • Validate remote sensing sensible heat fluxes estimates using ground measurements – Scintillometer: large constrained fp – Scintillometer: large, constrained fp – EC: smaller variable footprint • 7 scintillometers installed over arid and humid transects in NM • Derive and calibrate ET maps: – Index H to surface temperature Scintillometer – LE = Rn – G – H dT dT EC T 0 T T hot cold

  6. Locations oca o s SNWR Valles Caldera McKenzie Flats San Acacia S A i San Acacia Alfalfa Riparian K Key: Grants G t arid humid humid San Acacia San Acacia Sevilleta Sevilleta irrigated Socorro lava flow EMRTC Magdalena Ridge mountain t i MRO MRO

  7. Sevilleta National Wildlife Refuge Dry grassland Aerial Photos

  8. SNWR Intercomparison Studies Dry grassland � Good agreement for H measured by different LASs and EC

  9. Magdalena Ridge San Acacia Other Scintillometer Mountainous Grassland Riparian Area t transects in New t i N Mexico Valle Grande, VCNP Base of M-mountain Mountainous Grassland Desert

  10. Coming soon … g I-25 S San Acacia Alfalfa A i Alf lf Photograph from Indian Hill facing West El Malpais Lava flows Lava flows

  11. Transect overview Transect overview • Transect lengths 1.8 – 3.4 km • Effective heights 31 - 63 m

  12. Thanks to the Field Crew! Thanks to the Field Crew!

  13. LAS Operation Setup Scintillation Hot surface f

  14. LAS Specs LAS Specs Large Aperture Scintillometer Transmitter Voltage 12 VDC nominal Power 0.5 A maximum Optical wavelength of LED 880 nm (spectral bandwidth at 50% ~ 80nm) Optical power output of LED Maximum 80 mW (IF = 1A), eye safe Beam width ~1 m at 100 m distance Aperture Diameter .152 m Physical dimensions 0.37 m x 0.23 m x 0.32 m Weight 13.5 kg Path Length g 250 m – 4500 m

  15. Scintillometer Data Processing Scintillometer Data Processing Monin-Obukhov similarity Scintillations theory in the surface theory in the surface T,q � n layer, e.g. Structure St t parameter σ σ → → → → 2 2 2 C C C C χ n T Small Aperture (SAS) S ll A t (SAS) L Large Aperture (LAS) A t (LAS) ≤ 250 m pathlength ≤ 5000 m pathlength Heat flux H Inner length scale

  16. Footprint of LAS measurements Footprint Footprint measurements Wind • Model by Hsieh et al. 2000 • Footprint weighting function F t i t i hti f ti for each pixel Wind � peak of weighting � peak of weighting function is usually within 1km x 1km pixel from transect i l f t t center

  17. SEBAL – LAS Intercomparison SEBAL LAS Intercomparison • MODIS images: 1 km x 1 km resolution at MODIS images: 1 km x 1 km resolution at nadir • cloud free images centered over NM • cloud-free images centered over NM – June 18, 1100 MST • 3 transects in operation: – Valles Caldera: mountains, grass – Sevilleta: desert – San Acacia: riparian area

  18. SEBAL NM -MODIS sensible heat flux SEBAL MODIS sensible heat flux Valles Caldera Sevilleta San Acacia

  19. Results Valles C Caldera wind Sevilleta H [W m -2 ] LAS SEBAL San Ac VCNP 222-306 221-278 cacia Sevilleta 328-376 286 San Acacia 215 112-167

  20. Conclusions Conclusions • NMT-LASNet nearing completion NMT LASNet nearing completion � NM ideal for ground truthing • Large Aperture Scintillometers provide reliable Large Aperture Scintillometers provide reliable estimates of H over footprints similar to MODIS pixels • Future Research: – Analyze more images & sites – Include surface temperature, downwelling shortwave radiation measurements – Calibrate SEBAL NM using LASNet Calibrate SEBAL NM using LASNet

  21. Acknowledgements Acknowledgements • NSF-EPSCOR • USGS – WRRI • Field Assistance: Kathy Fleming, Jack Cheney • Flux Tower data: James Cleverly, Jim Thibault Fl T d J Cl l Ji Thib l • Site selection: – San Acacia: Rob Bowman Korky Herkenhoff David – San Acacia: Rob Bowman, Korky Herkenhoff, David Morris – MRO: Dan Klinglesmith – VCNP: Bob Parmenter, Johnny, Albert, & Juglio, VCNP: Bob Parmenter Johnny Albert & Juglio Karen Montgomery (DGPS) – Sevilleta: Renee Robichaud, Mike Friggens – El Malpais: Jeff Albers, Herschel Schulz El M l i J ff Alb H h l S h l

  22. LAS Sensible Heat Fluxes W m LAS Sensible Heat Fluxes W m -2 Sev- VCNP-EC Sev San Valles EC 30 min Acacia A i C ld Caldera 189 no data no data 6/6 1030-1040 336* 226* 219 219 210 210 6/18 1050 1100 6/18 1050-1100 328 213 306±23 6/18 1100-1110 234 212 376 222 222±16 7/16 1120-1130 266* 169* 142 44±4 cloudy * >30% variation in 10 min prior and/or thereafter

  23. Additional variables d= =.02, z o = wdir wspd σ θ L Rsd T_sfc Sev deg m s-1 deg m W m-2 deg C 6/6 1030-1040 343 1.13* 36* -3.3* -- -- villet .03, z U = 6/18 1050-1100 356 1.60 39 -1.57 1008 52.5 CSAT 345 3.04 24 -1.47 1018 52.9 6/18 1100-1110 6/18 1100 1110 = 2.85m a CSAT 7/16 1120-1130 238 1.23* 13* -1.03* 43.2 480* wdir di wspd d σ θ L L R d Rsd deg m s-1 deg m W m-2 6/6 1030-1040 No data Ca V Valles aldera 173 | 151 2.68 | 4.65* 7.9* -1.3 1000 6/18 1050-1100 EC30 | LAS EC30 | LAS 6/18 1100 1110 6/18 1100-1110 144 | 155 | 4.60 | 3.77 | 11 -8.3 1008 EC30 | LAS EC30 | LAS | 205 | 1.76* 22* 7/16 1120-1130 781*

  24. Additional variables d wdir wspd σ θ L Rsd San = 2, z o = deg m s-1 deg m W m-2 6/6 1000-1030 205 1.16 50.9* -9.3* No data CSAT LAS Rnet=630 .52, z U = Acac 6/6 1030-1040 244 1.08 33.3* -8.8 No data CSAT Rnet=705 LAS = 6.53m cia 7 0.86 20 -12.4* 1018 6/18 1050-1100 LAS Rnet=726 CSAT 6/18 1100-1110 20 0.82 31* -7.5* 1030 LAS LAS Rnet=747 R t 747 CSAT 262* 0.75* 12 -1.4* 960 7/16 1120-1130 LAS Rnet = 764

Recommend


More recommend