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SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Intro Page Modeling Amazonian Carbon Release with Calibrated Soil-Vegetation-Atmosphere.

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Presentation on theme: "SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Intro Page Modeling Amazonian Carbon Release with Calibrated Soil-Vegetation-Atmosphere."— Presentation transcript:

1 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Intro Page Modeling Amazonian Carbon Release with Calibrated Soil-Vegetation-Atmosphere Transfer Models Soil-Vegetation-Atmosphere Transfer Models NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas

2 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Project Goal  To investigate temporal and spatial variations and model-to-model differences in the calculated carbon exchange of the Amazônian forest ecosystem over the last 40-50 years using models of soil- vegetation-atmosphere interactions which have been calibrated against field data from the LBA field sites using modern multi-parameter estimation techniques.

3 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Project Objectives  Obtain the available data from the LBA field sites relevant to the calibration of SVAT models and carry out a multi-parameter calibration of SiB2 and MOSES-TRIFFID using these data  Explore the variation in optimized parameters obtained by calibrating SiB2 and MOSES-TRIFFID against LBA data, to determine if and how these parameters are related to site-specific seasonal climate, disturbance regimes, underlying soil, and appropriate remotely sensed geophysical variables  Obtain the time series of near-surface forcing variables available from the re-analysis data sets from ECMWF and/or NCEP and validate these time-series against climate records for Amazônia and data from past and ongoing Amazonian field studies (e.g., LBA, ABRACOS, ARME, etc.)  Investigate the temporal and spatial variations and model-to-model differences in the calculated carbon exchange of the Amazônian forest ecosystem over the last 40-50 years by using the time series of meteorological variables [validated in (3)], to force two-dimensional arrays of calibrated SVAT models [specified from (1) and (2)]

4 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Project Progress: Models l The models for which multi-parameter optimization is being (or will be) made:  BATS2: our existing “tried and tested” optimization model, currently being used as our “pathfinder” optimization to explore LBA data set availability/reliability  SiB2: optimization procedures are now largely developed, but refinements are still being made: problems include  unstable iteration methods in the original SiB2 pre-processor package;  some still poorly understood “timing” issues with modeled CO 2 fluxes (implicit time of day in code?)  MOSES: we have not yet obtained a reliable source code for this model or begun setting up an optimization package  Simple-SiB: we are making exploratory optimization of this model for possible future use in CPTEC Eta model

5 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Project Progress: LBA Data Sets Currently trying to use data from Beija-flor and trying to analyze for: Currently trying to use data from Beija-flor and trying to analyze for: l Tapajos national forest, Santarem, Para  Km 67  Km 83 (logged after 1 year) l Reserva Biologica do Cuieiras, Manaus, Amazonas  ZF2 km 34  ZF2 km 14 (EC data only) (km 14 not examined yet) l Reserva Boiologica Jaru (RBJ), Ji Parana, Rondonia l Floresta Nacional de Caxiuana, near Belem, Para  we know data exists but have not found it in Beja- flor yet (Andreae et al, JGR, 2002)

6 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Tapajos, Santarem, km 67 Currently optimizing with: l Measured EC fluxes of sensible and latent heat, and Net Ecosystem Exchange (NEE) calculated from storage flux and EC CO 2 flux l Gaps in model forcing data were filled using km 83 data, where available, or mean data from pervious and next available time periods l Data period shown is that used for optimization l Eleanor’s comments: l Well documented data with good quality control eleanor@hwr.arizona.edu eleanor@hwr.arizona.edu Approx. time EC tower installed

7 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Tapajos, Santarem, km 87 Currently optimizing with: l Measured EC fluxes of sensible and latent heat, and Net Ecosystem Exchange (NEE) calculated from storage flux and EC CO 2 flux l Forest logged after this period therefore not comparable with other primary forests l Data period shown is that used for optimization l Eleanor’s comments: l Well documented data with good quality control eleanor@hwr.arizona.edu eleanor@hwr.arizona.edu Approx. time EC tower installed

8 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Tapajos, Santarem, km 67 BATS2 Optimization: all data (including nighttime) included

9 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Tapajos, Santarem, km 67 BATS2 Optimization: no nighttime data included

10 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Tapajos, Santarem, km 83 BATS2 Optimization: all data (including nighttime) included

11 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Tapajos, Santarem, km 83 BATS2 Optimization: no nighttime data included

12 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Cuieiras, Manaus, km 34, 14 Currently working with: l km 34: measured EC fluxes and forcing and storage data accessible 1999-2003 l km 14: measured EC fluxes accessible 1999-2003 (close enough to use same forcing and CO 2 storage data?) l Significant forcing data missing in 2001 and 2002 (is this correct?) Interpolated forcing data in red. l Currently optimizing using DOY 165-700

13 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Cuieiras, Manaus km 34 BATS2 Optimization: all data included (small spread in Pareto set?)

14 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Cuieiras, Manaus km 34 BATS2 Optimization: no nighttime data included

15 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Jaru, Rondonia BATS2 Optimization: all data included

16 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Some Comments Eleanor’s (eleanor@hwr.arizona.edu) comments: l Data in Beja-flor from:  Reserva Biologica do Cuieiras, Manaus, Amazonas  Reserva Boiologica Jaru (RBJ), Ji Parana, Rondonia Would be easier to use if:  Documentation specifying data were of same standard as that for Tapajos, Santarem  Link given in Beja-flor delivered data for  Link given in Beja-flor delivered data for Cuieiras and Jaru (?)  Time steps were included in data series for periods when no data were taken, but flagged as missing data (for continuity in models)  Net ecosystem were calculated and included (as at Santarem 67 km) l Can’t find (in Beja-flor) the data from:  Floresta Nacional de Caxiuana, near Belem, Para

17 SAHRA – NSF Center for Sustainability of semi-Arid Hydrology and Riparian Areas Data: Some More Comments Jim’s comments (on the basis of discussion this week): l It will not be possible to complete this project in a timely and effective way using data obtained from Beja-flor.  Hence, we will have to go one-on-one with individual groups to obtain data  I believe this will be a common problem for all “synthesis” projects that active over the next 18-24 months  We need to define a list of primary (and secondary) data interface contacts for each flux tower group to service this intermediate need to distribute data rapidly to “synthesis teams” l Recent improvements in the understanding of the origin of flux loss in eddy correlation measurements  mean it is possible that all LBA flux data will require reanalysis.  This has the potential to substantially delay progress in this and other “synthesis” projects  angle of attack dependent calibration of anemometer and longer time periods for rotation analysis


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