Spatial ModelData Comparison Project Conclusions Forward models are
- Slides: 12
Spatial Model-Data Comparison Project Conclusions • Forward models are very different and do not agree on timing or spatial distribution of C sources/sinks. • Examination of NEE shows GPP is largest component of discrepancies. • Why?
Tower-Based Spectral Measures of LUE, GPP Provide Independent Data at Meter-Scale and Minute-Scale Resolution
Adding Spectral Measures of Vegetation Light Use Efficiency to Existing Towers and Tower Sites Gap-Filler for Tower Measurements Diagnostics For Process Models Scaling to Landscape, Region Globe? ?
Spectral Measures of Surface-Atmosphere Energy, Water, Carbon Exchange Carbon Assimilation Rate Directly From Satellite A= par radiative xfer x fapar NDVI x LUE PRI Latent heat LE = r. Cp [e*- ea] gcga g gc+ga gc = Ah/c Models compute gc gc = gc* x f([e*- ea] , Ta, soil moisture) 0≤f≤ 1 • f is a non-linear function of soil moisture gc* = max gc • Soil moisture is difficult to model • Precipitation & soil properties variability • Soil Moisture diffcult to measure in the presence of dense vegetation.
Photochemical Reflectance Index A Normalized Difference Reflectance Index (NDRI) Gamon et al. 1992, 1993, 1997, Gamon & Surfus 1999 r 531 - r 570 r 531 + r 570 PRI = As LUE decreases r 531 and PRI decrease. Reference Band 570 nm Xanthophyll Band 531 nm At the landscape scale r 531 r 570 are also sensitive to variations in other pigments and conditions other than LUE; beta-carotene, lutein, variations in soil, litter background.
Fluxnet Canada Doug Fir British Columbia a b Figure 3: (a) A dual channel radiometer is mounted on the DF 49 Fluxnet tower with a vertical zenith angle (VZA) of 62°. A motor moves the canopy sensor 360 o every 15 minutes. Data are recorded every 5 seconds, year round. (b) The instrument on the Fluxnet Canada Douglas fir research site
Measured Components For Douglas Fir
Slope of PRI vs LUE Doug Fir LUE ≈ (∂PRI/∂SF-0. 21)/0. 05
COMBINING MODEL, TOWER AND REMOTE SENSING MEASUREMENTS • • Remote sensing estimates of LUE, in combination with process model estimates and tower-based estimates form a powerful set of independent measures for cross-validation of these independent methodologies. Process models calculate – components of gross primary production, e. g. LUE, GPP – autotrophic and heterotrophic respiration, NEP Compare process model predictions to spectral and eddy covariance (EC) measures of same – compare model outputs of these quantities to the minute-scale tower and remote sensing-inferred values – Spectral measures can help gap-fill tower EC flux data – flag and help diagnose problems in any of the methods when the diurnal or longer-term values diverge. Aircraft and satellite landscape-scale measures (available only under clear-sky conditions) could be compared with similar estimates from process models – examine divergences over the landscape – flag and diagnose problems • remote sensing algorithm • variables used by the process models such as soil texture, soil moisture, nutrient levels etc. – data assimilation
What needs to be added to the existing Canadian, U. S. , European and International network of flux towers?
Tower Spectral Measurement Instruments Costs of sensors range from 25 K$ as in the AMSPEC from Hilker et al, to a full spectrum CCD at about 6 -10 K$ - (350 -1500 nm), to a simple PRI sensor using a light sensor and interference filter for about 2 K$ (which could be handmade). Scaling to Landscape Aircraft Spectral Measurements - Missions of opportunity? NASA AVIRIS, the Canadian CASI, EO-1, NASA LVIS Lidar, other Canadian Lidar flights and the NASA airborne SLICER instrument (an aircraft Lidar flown during BOREAS), ASAS, multi-angle along-track hyperspectral flown during BOREAS Scaling to Region and Globe -- Not Global yet, but… Chris Proba, EO-1, MERIS MODIS
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