Data

Drought_National_Grids_1950_2022_RESTRICTED

Centre for Safe Air
CARDAT Data Team (Managed by) Ivan Hanigan (Owned by) Mr Ivan Charles Hanigan (Owned by)
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.17605/OSF.IO/2768R&rft.title=Drought_National_Grids_1950_2022_RESTRICTED&rft.identifier=https://doi.org/10.17605/OSF.IO/2768R&rft.publisher=Centre for Safe Air&rft.description=The data and methods are for the 2022 MJA-Lancet Countdown report. The drought method follows that outlined in Watts et al.12 We used the Standardised Precipitation-Evapotranspiration Index (SPEI) calculated on 6-month timescale. In this report we show that the SPEI can also be used to indicate extremely wet periods that may be associated with flooding (as it was in Eastern Australia during the first three months of 2022). Data We used monthly rainfall and temperatures, calculated using the Australian Water Availability Project (AWAP) gridded data January 1950 - March 2022 at 0.05 × 0.05 degree resolution.11 Methods This indicator represents the area impacted by excess drought events compared to the 1950-2005 baseline. The drought method follows that outlined in Watts et al.12 We used the Standardised Precipitation-Evapotranspiration Index (SPEI) calculated on 6-month timescale. Due to lack of wind speed data, the potential evapotranspiration (PET) was calculated using the Thornthwaite method rather than the FAO-56 Penman-Monteith method. We used the algorithm provided in the R package “SPEI” (Santiago Beguería and Sergio M. Vicente-Serrano (2017). SPEI: Calculation of the Standardised Precipitation-Evapotranspiration Index. R package version 1.7. The SPEI is a multiscalar index, which takes into account both precipitation (using the basis of the more commonly used SPI index) and temperature, to estimate potential evapotranspiration. More information on this index and its calculation can be found here: https://CRAN.R-project.org/package=SPEI.&rft.creator=Ivan Hanigan&rft.creator=Mr Ivan Charles Hanigan&rft.date=2023&rft.relation=https://doi.org/10.5694/mja2.51742&rft.coverage=Australia&rft.coverage=northlimit=-9.1422; southlimit=-43.7405; westlimit=96.8169; eastLimit=167.998&rft_rights=RESTRICTED&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

view details

RESTRICTED

Access:

Restrictions apply

Brief description

The data and methods are for the 2022 MJA-Lancet Countdown report. The drought method follows that outlined in Watts et al.12 We used the Standardised Precipitation-Evapotranspiration Index (SPEI) calculated on 6-month timescale. In this report we show that the SPEI can also be used to indicate extremely wet periods that may be associated with flooding (as it was in Eastern Australia during the first three months of 2022). Data We used monthly rainfall and temperatures, calculated using the Australian Water Availability Project (AWAP) gridded data January 1950 - March 2022 at 0.05 × 0.05 degree resolution.11 Methods This indicator represents the area impacted by excess drought events compared to the 1950-2005 baseline. The drought method follows that outlined in Watts et al.12 We used the Standardised Precipitation-Evapotranspiration Index (SPEI) calculated on 6-month timescale. Due to lack of wind speed data, the potential evapotranspiration (PET) was calculated using the Thornthwaite method rather than the FAO-56 Penman-Monteith method. We used the algorithm provided in the R package “SPEI” (Santiago Beguería and Sergio M. Vicente-Serrano (2017). SPEI: Calculation of the Standardised Precipitation-Evapotranspiration Index. R package version 1.7. The SPEI is a multiscalar index, which takes into account both precipitation (using the basis of the more commonly used SPI index) and temperature, to estimate potential evapotranspiration. More information on this index and its calculation can be found here: https://CRAN.R-project.org/package=SPEI.

Data time period: 1950-01-01 to 2022-04-30

This dataset is part of a larger collection

167.998,-9.1422 167.998,-43.7405 96.8169,-43.7405 96.8169,-9.1422 167.998,-9.1422

132.40745,-26.44135

text: Australia

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover

Identifiers