Maps showing risk and potential impacts of ozone on sugarcane production in south-central Brazil, 2010-2014

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This dataset is available under the terms of the Open Government Licence

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https://doi.org/10.5285/1513d8ed-67a9-40fc-a8e5-bd7864d0d422

This dataset contains gridded model outputs of the predicted risk to C4 sugarcane production across south central Brazil for 2010-2014. The outputs are given as production in kg m-2 yr-1, percentage of control production (%) and production losses in kg yr-1 and Tg yr-1. The spatial resolution is 1.25 x 1.875 degrees. Three different levels of ozone susceptibility (low, moderate or high) and two distinct threshold values of phytotoxic ozone dose (0 and 2 nmol m-2 s-1) were considered.

Publication date: 2024-02-12

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View numbers valid from 12 February 2024 Download numbers valid from 20 June 2024 (information prior to this was not collected)

Format

NetCDF

Spatial information

Study area

Spatial representation type

Raster

Spatial reference system

WGS 84

Temporal information

Temporal extent

2010-01-01 to 2014-12-31

Provenance & quality

These data were produced using the Joint UK Land earth simulator (JULES v5.6) run on JASMIN. The sugarcane was represented in JULES by using the C4 plant functional type. The input modelled O3 exposure data were simulated using the Earth System Model (UKESM1) for the period 2000 to 2014. JULES was used to calculate annual yields with or without consideration of ozone susceptibility for a 10-year period across south-central Brazil. The spatially explicit model outputs were compared to control model output to calculate the proportional decline and absolute impacts.

Licensing and constraints

This dataset is available under the terms of the Open Government Licence

Cite this dataset as:

Cheesman, A.W.; Brown, F.; Farha, M.N.; Rosan, T.M.; Folberth, G.A.; Hayes, F.; Moura, B.B.; Paoletti, E.; Hoshika, Y.; Osborne, C.P.; Cernusak, L.A.; Ribeiro, R.V.; Sitch, S. (2024). Maps showing risk and potential impacts of ozone on sugarcane production in south-central Brazil, 2010-2014. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/1513d8ed-67a9-40fc-a8e5-bd7864d0d422

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