High-Resolution Vegetation Traits and Fluxes during NASA's SHIFT campaign, for Dangermond Preserve, California, 2022

Description

Overview

This dataset provides high-resolution (30 m) remote sensing and modeling data collected as part of the SHIFT (Surface Biology and Geology High-Frequency Time Series) campaign conducted in 2022 at the Dangermond Preserve, California. The data, sourced from AVIRIS-NG (Airborne Visible/Infrared Imaging Spectrometer-Next Generation), TROPOMI (TROPOspheric Monitoring Instrument) SIF, and outputs from the Climate Modeling Alliance (CliMA) Land model, offers valuable insights into vegetation traits, plant functional types, ecosystem dynamics, and biogeochemical cycling.

v0.3 correction: All files have been reprocessed using cdo remapcon (conservative area-weighted interpolation) to aggregate AVIRIS-NG 5 m pixels to the 30 m model grid, replacing the bilinear interpolation (cdo remapbil) used in v0.1 and v0.2. The _remapcon and _fixed_005 suffixes in filenames mark the corrected pipeline.

Data Files

CliMA Land Output

• shift_fluxes_day_00_clima_fit_reg_jmax_fixed_005.nc to shift_fluxes_day_12_clima_fit_reg_jmax_fixed_005.nc: Trait-based ecosystem fluxes for each of the 13 SHIFT dates, covering gross primary production (GPP), sun-induced fluorescence (SIF) at 683, 740, 757, and 771 nm, and transpiration at 30 m resolution.
• pft_shift_fluxes_day_00_clima_fit_reg_jmax_fixed_005.nc to pft_shift_fluxes_day_12_clima_fit_reg_jmax_fixed_005.nc: Same as above but using static per-PFT mean traits (plant functional type-based run).
• shift_fluxes_day_00_clima_fit_reg_jmax_apar.nc to shift_fluxes_day_12_clima_fit_reg_jmax_apar.nc: Trait-based outputs including absorbed photosynthetically active radiation (APAR).
• pft_shift_fluxes_day_00_clima_fit_reg_jmax_apar.nc to pft_shift_fluxes_day_12_clima_fit_reg_jmax_apar.nc: PFT-based outputs including APAR.
• shift_fluxes_day_NN_clima_fit_reg_jmax_fixed_005_spatavg.nc / pft_shift_fluxes_day_NN_clima_fit_reg_jmax_fixed_005_spatavg.nc: 30 m flux outputs spatially averaged to the 0.05° TROPOMI grid for comparison against satellite SIF.

Vegetation Traits

• chl_aviris_dangermond_clima_fit_time_00_remapcon.nc to chl_aviris_dangermond_clima_fit_time_12_remapcon.nc: Leaf chlorophyll content per area (μg cm⁻²) across 13 dates.
• lma_aviris_dangermond_clima_fit_time_00_remapcon.nc to lma_aviris_dangermond_clima_fit_time_12_remapcon.nc: Leaf mass per area (g m⁻²) across 13 dates.
• lwc_aviris_dangermond_clima_fit_time_00_remapcon.nc to lwc_aviris_dangermond_clima_fit_time_12_remapcon.nc: Leaf water content (mol m⁻²) across 13 dates.
• lai_aviris_dangermond_time_00_remapcon.nc to lai_aviris_dangermond_time_12_remapcon.nc: Leaf Area Index (m² m⁻²) derived from AVIRIS-NG Simple Ratio across 13 dates.
• CI_map_remapcon.nc: LiDAR-derived clumping index, time-invariant.

Validation

• coloc_for_inversion.csv: Co-located AVIRIS-NG reflectance and field trait measurements used as inversion targets.
• inversion_A.csv to inversion_N.csv: Retrieved traits for 14 inversion configurations evaluated against field data.
• ensemble_retrievals.csv, sobol_samples.csv, sobol_results.csv: Ensemble retrievals and Sobol sensitivity analysis inputs/outputs.
• lai_modis_comparison.csv, lai_trajectory_table.csv: LAI time series and seasonal statistics compared against MODIS.
• sweep_results_section14.csv: Parameter sweep results for TROPOMI SIF R² sensitivity analysis.

Usage Guidelines

This dataset is ideal for researchers focusing on vegetation dynamics, ecological forecasting, and biogeochemical cycling. It supports environmental analysis and land surface modeling.

Citation

When using this dataset, please cite it as follows: "High-Resolution Vegetation Traits and Fluxes during NASA's SHIFT campaign, for Dangermond Preserve, California, 2022, provided by Braghiere R. K./Caltech-NASA-JPL, Caltech Data Library, 2026."

Scripts used to generate this dataset are available at: https://github.com/braghiere/shift_dangermond_trait

Contact Information

For additional information or assistance with the dataset, please contact Braghiere R. K./Caltech-NASA-JPL (renato.braghiere@caltech.edu).

References

Brodrick, P., R. Pavlick, M. Bernas, J.W. Chapman, R. Eckert, M. Helmlinger, M. Hess-Flores, L.M. Rios, F.D. Schneider, M.M. Smyth, M. Eastwood, R.O. Green, D.R. Thompson, K.D. Chadwick, & D.S. Schimel. (2023). SHIFT: AVIRIS-NG L2A Unrectified Reflectance. ORNL DAAC. https://doi.org/10.3334/ORNLDAAC/2183

Chadwick, K. D., Davis, F., Miner, K. R., Pavlick, R., Reynolds, M., Townsend, P. A., Brodrick, P. G., Ade, C., Allen, J., Anderegg, L., Angel, Y., Boving, I., Byrd, K. B., Campbell, P., Carberry, L., Cavanaugh, K. C., Easterday, K., Eckert, R., … Schimel, D. (2024). Unlocking Ecological Insights from Subseasonal Visible-to-Shortwave Infrared Imaging Spectroscopy: The SHIFT Campaign. Ecosphere.

Queally, N., Davis, F. W., Chadwick, K. D., Ade, C., Anderegg, L., Angel, Y., Baker, B., Boving, I., Braghiere, R. K., Brodrick, P., Campbell, P., Cryer, J., Cushman, K. C., Dao, P. D., Dibartolo, A., Eckert, R., Grant, K., Heberlein, B., Johnson, M., … Schimel, D. S. (2024). SHIFT: Vegetation Plot C

Files

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