Global biomass burning fuel consumption and emissions at 500&thinsp;m spatial resolution based on the Global Fire Emissions Database (GFED)

van Wees, Dave; van der Werf, Guido R.; Randerson, James T.; Rogers, Brendan M.; Chen, Yang; Veraverbeke, Sander; Giglio, Louis; Morton, Douglas C.

doi:https://doi.org/10.5194/gmd-15-8411-2022

Articles | Volume 15, issue 22

Geosci. Model Dev., 15, 8411–8437, 2022

https://doi.org/10.5194/gmd-15-8411-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Geosci. Model Dev., 15, 8411–8437, 2022

https://doi.org/10.5194/gmd-15-8411-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 22

Model description paper

| Highlight paper

21 Nov 2022

Model description paper | Highlight paper | 21 Nov 2022

Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED)

Dave van Wees et al.

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Final revised paper (published on 21 Nov 2022)
Supplement to the final revised paper
Preprint (discussion started on 30 May 2022)
Supplement to the preprint

Interactive discussion

Status: closed

CEC1:
'Comment on gmd-2022-132', Juan Antonio Añel, 16 Jun 2022

Dear authors,
After checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".

https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
We can not accept embargoes such as registration, previous contact with the authors or availability of the model under request.

In this way, you must reply to this comment with the link to an open repository containing the code of the model used in your manuscript, with its DOI.
Also, the same applies to the data. We do not accept generic links to web pages such as globalfiredata.org. First, this webpage is not a trustable long-term repository for scientific data. Secondly, the link does not identify clearly the specific files used in your work. Therefore, as for the code, you must include in one of the acceptable repositories (check them in our policy) the files used in your manuscript and provide its DOI.
Please, reply as soon as possible to this comment with the links and DOIs so that the necessary assets are available for the peer-review process, as they should be.
Be aware that failing to comply with this request will result in the rejection of your manuscript for publication.
Best regards,
Juan A. Añel

Geosci. Model Dev. Executive Editor

Citation: https://doi.org/10.5194/gmd-2022-132-CEC1
- AC1: 'Reply on CEC1', Dave van Wees, 22 Jun 2022
  
  Dear Juan,
  Thank you for your comment. I have uploaded the 500-m model emissions data and the field data synthesis to Zenodo with the DOI identifiers: https://doi.org/10.5281/zenodo.6670750 and https://doi.org/10.5281/zenodo.6670869.
  Please consider this a temporary upload for the review process so that the reviewers can check the data. We are still planning a last rerun of the model as a final check and to include the year 2020. This will also include some changes in the file structure for better usability. This is also the case for the field data synthesis. In general, we want to keep the upload open for changes according to what the reviewers say. Currently I have set the uploads to restricted access so that only the reviewers can view the data. Is this ok for during the review phase? Please let me know.
  Regarding the model code, we would like to upload this as a direct supplementary to the paper, just like how it is in the previous model paper published in GMD: https://doi.org/10.5194/gmd-12-4681-2019. I will mail the model code to GMD the coming days so it can be added as a supplement.
  With kind regards,
  Dave van Wees
  
  Citation: https://doi.org/10.5194/gmd-2022-132-AC1
RC1: 'Comment on gmd-2022-132', Anonymous Referee #1, 01 Sep 2022

Review of “Global biomass burning fuel consumption and emissions at 500-m spatial resolution based on the Global Fire Emissions Database (GFED)”

Submitted to

General Comments

The GFED fire emission inventory is used extensively across a range of environmental disciplines. I expect this 500m dataset will find immediate use among earth system scientists, particularly for applications where the 0.25km spatial resolution of the base GFED database has previously presented challenges, e.g. application for regional scale chemical transport modeling.

In my view this paper is thorough and well-written. I have no substantive comments, other than a handful of very minor suggestions (see below).

Line-by-line

Abstract line 22. I think the abbreviation “(SOC)” after “soil organic carbon” is missing here, given the reference several lines below.

Line 46. Do the FRP approaches really bypass the biogeochemical dependencies? Or is it more accurate to say that they avoid the computational burden of having to calculate these relationships online? My understanding was that the FRP based estimates still implicitly rely on an understanding of the biogeochemistry in order to parameterize the emissions per detection, e.g. the GFAS inventory relying on relationships calculated in GFED. But perhaps my thinking is incorrect.

Line 139. I believe this is the first mention of soil organic carbon in the main text, please move the abbreviation “(SOC)” up to match.

Citation: https://doi.org/10.5194/gmd-2022-132-RC1
RC2: 'Comment on gmd-2022-132', Anonymous Referee #2, 17 Oct 2022

Excellent article. Scientifically sound. Please see attachment for a few minor suggestions (page 2, 5).

Citation: https://doi.org/10.5194/gmd-2022-132-RC2
AC2: 'Response to reviewers and executive editor', Dave van Wees, 19 Oct 2022

Final reply to the reviewers and executive editor
We thank the reviewer for their constructive comments. Below we have answered their comments alongside the accompanying changes in the manuscript.

Reply to referee 1 (RC1)
Response to comment 1 and 3:
Abbreviation of soil organic carbon (SOC) have been fixed.

Response to comment 2:
The introduction text regarding FRP-based emissions estimation has been rewritten and “most of these dependencies” has been changed to “some of these dependencies”:
“Models used for estimating contemporary global fire emissions are typically based on either a biogeochemical model for estimation of fuel load and fuel consumption in combination with satellite-based burned area to calculate emissions (e.g. van der Werf et al., 2017), or remotely-sensed active fire detections from thermal anomalies in combination with parametric relationships that convert fire radiative power (FRP) to fire radiative energy (FRE) and emissions (e.g. Kaiser et al., 2012; Mota and Wooster, 2018). The biogeochemical modelling approach relies heavily on remote sensing data of vegetation cover, vegetation productivity, and moisture conditions, whereas the FRP approach bypasses some of these dependencies by directly relating FRE to emissions.”

Reply to referee 2 (RC2)
Response to comment 1:
Acronym of IPCC written out in text

Response to comment 2:
We added a lint to Introduction section 1:
“…, these data are aggregated by vegetation type to a spatial resolution of 0.25° (approximately 28 km at the equator) for carbon model calculations.”

Response to comment 3:
We added a line to Methods section 2.2:
“The simulation starting year of 2002 was based on the availability of MODIS data from both the Terra and Aqua satellites.”

Reply to the Executive Editor
As indicated earlier, we have extended our simulation and all our results to include 2020. Accordingly, the previously uploaded Zenodo datasets will be updated and produced in their final form. Finally, the model code will be added as a supplement to the paper. The corresponding links and DOI identifiers have been added to the sections “Code and data availability” and “Supplement”.

Citation: https://doi.org/10.5194/gmd-2022-132-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Dave van Wees on behalf of the Authors (20 Oct 2022) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (22 Oct 2022) by Jason Williams

Short summary

We present a global fire emission model based on the GFED model framework with a spatial resolution of 500 m. The higher resolution allowed for a more detailed representation of spatial heterogeneity in fuels and emissions. Specific modules were developed to model, for example, emissions from fire-related forest loss and belowground burning. Results from the 500 m model were compared to GFED4s, showing that global emissions were relatively similar but that spatial differences were substantial.