DOI: 10.5281/zenodo.18504592
title: Supporting data for: Airborne observations reveal underestimated riverine methane emissions across the Amazon

description: This data set collection contains the following files: 

STILT_foot_matrices2.nc - netCDF file containing all footprints of the CAFE Brazil campaign over n observations and m grid cells in different units as written in the file. "foot_matrix_cleaned" and "foot_matrix" are both in ppm/(umol m^-2 s^-1) and "cleaned" excludes numerical artefacts (-inf, +inf) caused from the simulation. 

STILT_foot_meta_ref.csv - text file containing the meta data of the STILT simulation (receptor positions), and CH4 observations (see Ort et al., 2024), and CH4 model data interpolated along the flight tracks from CAMS, CLaMS and GEOS-Chem, as explained in Ort et al., 2026 in 60s resolution. 

STILT_foot_matrices_fine_allalt_tau25_LC_corrQ_Rnorm_AK.nc - netCDF containing prior and posterior matrices in 0.1°x0.1° resolution of the inversion using all available footprints, land-cover correlation with (GLWD) expanding in exponential decay circular using tau_s = 25 km, and also calulating the averagin kernel sensitivity. This file contains the posterior state vector (x_post), prior state vector (x_prior), their difference (post - prior; x_diff), posterior covariance matrix (Q_post_diag, diagonal variance), prior covaraiance matrix (P_prior_diag, diagonal variance), all in units of g CH4 m^-2 yr^-1, and the averaging kerne sensitivity. The dimensions are the spatial domain in latitude and longitude, the product of which results in m (similar m to footprint matrix).   

 

The following files contain the prior state vector and its error covariance matrix (sparse). Detailed information can be found in the metadata file prior_wetcharts_jandec_umolms_prior_tau25.npz . 

prior_wetcharts_jandec_umolms_grid_tau25.npz - contains the grid of the spatial domain in latitude and longitude.

prior_wetcharts_jandec_umolms_prior_tau25.npz  - contains the prior state vector, ensemble mean of WetCHARTs simulations, replicated for finer resolution. 

prior_wetcharts_jandec_umolms_Qprior_tau25.npz - contains the prior error covariance matrix, scaled with correlation of p=0.95 to fine resolution, and correlated with tau_s=25km over similar land-cover types from GLWD (Lahner et al., 2025).

 

CAFE_Brazil_merged_corr2_CAMS_GC_CLaMSv3.nc - Merged file of CAFE Brazil data including CH4 [ppb], O3[ppbv], CO [ppbv], N2O [ppb] (N2O was aligned with FT background), and interpolated model data (mainly CH4) from CAMS, CLaMS and GEOS-Chem, as well as ERA5 data. 

 

 

References and author contributions: 

Creator of files and contact person: Linda Ort

STILT simulation: Nikhil Dadheech, Alexander Turner

CH4 Observations: Linda Ort, Horst Fischer (Ort et al., 2024)

CAMS: release: v23r1, source: TM5-MP 4D-Var (Copernicus Atmosphere Monitoring Service. (2020))

GEOS-Chem: James Yoon 

CLaMS: Hans-Christoph Lachnitt, Paul Konopka

WetCHARTs v1.3.3: Anthony Bloom (Bloom et al., 2024)

 

Ort, Linda, et al. "In-flight characterization of a compact airborne quantum cascade laser absorption spectrometer." Atmospheric Measurement Techniques 17.11 (2024): 3553-3565. https://doi.org/10.5194/amt-17-3553-2024

Ort et al., 2026 - submitted to GRL

Copernicus Atmosphere Monitoring Service. (2020). Cams global inversion-optimised greenhouse gas fluxes and concentrations. Copernicus Atmosphere Monitoring Service (CAMS) Atmosphere Data Store. Retrieved from https://doi.org/10.24381/ed2851d2 (Accessed on 07-03-2025) doi: 10.24381/ed2851d2

Bloom, A. A., Bowman, K. W., Lee, M., Turner, A. J., Schroeder, R., Worden, J. R., . . . Jacob, D. J. (2024). CMS: Global 0.5-deg Wetland Methane Emissions and Uncertainty (WetCHARTs v1.3.3). ORNL Distributed Active Archive Center. Retrieved from https://doi.org/10.3334/ORNLDAAC/2346413 (Accessed: 2026-01-07) doi: 10.3334/ORNLDAAC/2346

Lehner, B., Anand, M., Fluet-Chouinard, E., Tan, F., Aires, F., Allen, G.H., Bousquet, P., Canadell, J.G., Davidson, N., Ding, M., Finlayson, C.M., Gumbricht, T., Hilarides, L., Hugelius, G., Jackson, R.B., Korver, M.C., Liu, L., McIntyre, P.B., Matthews, E., Nagy, S., Olefeldt, D., Pavelsky, T.M., Pekel, J.-F., Poulter, B., Prigent, C., Wang, J., Worthington, T.A., Yamazaki, D., Zhang, X., Thieme, M. (2025). Mapping the world’s inland surface waters: an upgrade to the Global Lakes and Wetlands Database (GLWD v2). Earth System Science Data 17, 2277–2329. https://doi.org/10.5194/essd-17-2277-2025