DOI: 10.5281/zenodo.12820514
title: dataset for: Fire activity and drought increases ozone-plant damage to the Amazon rainforest.

description: Abstract



This dataset relates to work undertaken for publication 'Fire activity and drought increases ozone-plant damage to the Amazon rainforest.'

Datasets and jupyter notebooks allow the figures and data to be reproduced.

 

ABSTRACT: Human activity is exposing the Amazon rainforest to increasing stressors, including plant damage due to elevated ozone (O3) pollution. O3-plant damage reduces plant photosynthesis and the land carbon sink thus increasing atmospheric CO2. Factors that control O3-plant damage in the Amazon have not been characterised so damage may be exacerbated by recurrent extreme drought and fires. We identify drivers of interannual variability in O3-plant damage using a land surface model validated against satellite products. We find that O3-plant damage increases with fire activity, with additional interactive effects during major droughts. The indirect increase in atmospheric CO2 from fire-driven O3-plant damage is ~50% the magnitude of direct CO2 emissions from fires in non-drought years, suggesting the negative impact of fires on the Amazon carbon budget is severely underestimated. During droughts, leaves close their stomata, which reduces O3 uptake and should protect against O3 damage. However, due to higher fire activity, and elevated O3 concentrations, O3-plant damage during droughts is up to 77 Tg-C (or over 2 times) greater than average. As droughts are set to become more frequent, our results demonstrate that high fire activity associated with drought increases the O3-plant damage risk to the rainforest, especially in remote areas.
description: Model description

This dataset relates to simulated data produced using a land surface model. The study used the Joint UK Land Environment Simulator (JULES) vn. 5.6 at a spatial resolution of 1.25° latitude by 1.875° longitude.

Simulations

To isolate the effect of O3-plant damage, we compared two simulations for the period 1997–2014: one with and one without O3-plant damage. The simulation that included O3-plant damage used an average O3 susceptibility for tropical trees based on an average response observed in tropical trees. The simulation without O3-plant damage was identical, except with the damage parameter set to 0. Both simulations underwent separate 1000-year spin ups (cycling 50 times over a 20-year period from 1975 − 1995) in which O3 was fixed at 1975 concentrations. Only changes during the period 1997–2014 were evaluated due to data availability of fire emissions (beginning in 1997) and high temporal-resolution O3 concentrations (available until 2014).

Other datasets

For comparison to observations, we also use fire data (The Global Fire Emissions Database 4 including small fires (GFED4s) was used for fire carbon emissions); NOx column data (Satellite-derived atmospheric NOx columns were taken from the TROPOMI instrument on the Sentinel-5 satellite); and GPP data (GOSIF, the Global OCO-2 based SIF product, used sun-induced fluorescence (SIF) to infer GPP, and Fluxsat, a satellite product used vegetation index (EVI) from MODIS and calibrated with FLUXNET 2015 GPP).

Analysis

All datasets were regridded to the resolution of the JULES simulation (1.25° latitude by 1.875° longitude), if they were not already available at that resolution, and the Amazon region was selected. This was defined by the tropical broadleaf tree fraction from the 2015 land cover map produced by Harper et al. 2016 . Analysis was limited to the period 1997–2014, constrained by GFED fire data beginning in 1997 and modelled O3 data ending in 2014.

To obtain correlations between variables (O3, fire activity, total land carbon), annual mean gridded data were averaged over the Amazon region, weighted by fraction of tropical broadleaf tree plant functional type and gridcell area. These values were presented as anomalies relative to the 1997–2014 mean.

To establish drought effects, monthly means were calculated for the northern and southern Amazon by dividing datasets at the equator, weighted by fraction of tropical broadleaf tree and gridcell area. Data were then divided into drought years (1998, 2005, 2007, 2010) and non-drought years. The average of drought years was compared to the average of non-drought years.

For comparison to GPP satellite products, GPP from simulations and satellite data was masked over all gridcells with less than 90% tropical tree cover. Annual means were detrended to remove impacts of CO2 fertilisation that were included in the JULES simulations but cannot be detected by the EVI product. For evaluation of seasonality, JULES GPP was compared to satellite-derived GPP in the central, less seasonal part of the Amazon (4°S–4°N) and the outer, more seasonal part of the Amazon (> 4°S, > 4°N) as well as separating into drought and non-drought years.
description: This dataset provides netCDF files and jupyter notebooks that can be used to recreate figures from the publication of the same name. In the study, we identify drivers of interannual variability in O3-plant damage in the Amazon using a land surface model validated against satellite products.

Data is presented in netCDF format for 4 main figures and 8 supplementary figures. Metadata attached to the netCDF file describes its contents. Below gives an overview of the data and scripts needed to recreate the figures.

Description of the data and file structure

Fig.1: 



Fig.1 (Jupyter notebook)

Annual mean detrended GPP for simulations with and without O3 damage (2 netCDFs)

Annual mean detrended GPP derived from GOSIF and FluxSat products (2 netCDFs)


Fig.2, Fig. S4, Fig. S8:



These figures are similar and use some shared datasets

Fig.2, Fig. S4, Fig. S8 (Jupyter notebooks)

Annual mean simulated O3 concentration from UKESM1 (3 netCDFs)

Annual mean simulated O3 concentration from 5 other ESMs (1 netCDF)

Annual mean simulated fire carbon emissions from GFED4s (1 netCDF)

Annual mean simulated O3 damage under present day and elevated CO2 (2 netCDFs)


Fig. 3, Fig.4, Fig.S5, Fig.S6:



These figures are similar and use some shared datasets

Fig.3, Fig. 4, Fig. S5 , Fig. S6 (Jupyter notebooks)

Fraction of tropical tree in each grid cell (1 netCDF)

Spatial monthly mean O3 distribution (1 netCDF)

Spatial monthly mean O3 flux into stomata (1 netCDF)

Spatial monthly mean NPP with and without O3 damage (2 netCDFs)


Fig.S1:



Fig.S1 (Jupyter notebook)

Annual mean NO2 column from UKESM1 (simulated) and OMI (satellite) (2 netCDFs)


Fig.S2:



Fig.S2 (Jupyter notebook)

Spatially explicit NO2 column from UKESM1 (simulated) and OMI (satellite) (2 netCDFs)


Fig.S3:



Fig.S3  (Jupyter notebook)

GPP from outer amazon region (greater than 4N-4S) from simulations, GOSIF and FluxSat (8 .npy files)

GPP from central amazon region (within 4N-4S) from simulations, GOSIF and FluxSat (8 .npy files)


Sharing/Access information

Links to other publicly accessible locations of the data:



Total carbon emissions from fires from GFED4 are available at https://www.globalfiredata.org/(opens in new window)

UKESM1-0-LL simulations are available at ESGF: https://aims2.llnl.gov/search/cmip6/

GPP remote sensing data is available from https://climatesciences.jpl.nasa.gov/sif/download-data/gpp/(opens in new window)


Code/Software

To analyse the data, Python 3 with Jupyter notebooks on the JASMIN sever was used: https://help.jasmin.ac.uk/docs/interactive-computing/jasmin-notebooks-service/. The scripts are provided to recreate the data using the following packages:



numpy vn 1.26.4

matplotlib vn 3.8.4

iris vn 3.9.0

cartopy vn 0.23.0

scipy vn 1.13.0