Near real-time mapping of air temperature at high spatiotemporal resolutions in Tasmania, Australia

Webb, Mathew; Kidd, Darren; Minasny, Budiman

doi:10.1007/s00704-020-03259-4

Cited by 5 publications

(18 citation statements)

References 38 publications

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“…5 and 6)-a multivariate approach to modelling might be more appropriate along with a denser network of AWS sites. This approach was conducted by Webb, Kidd & Minasny (2020), and showed errors improved during winter when using regression tree interpolation (along with multiple terrain and satellite covariate datasets). However, the substantially longer processing times may not be appropriate for real-time application, negating its ability to produce outputs in a timely manner as required for this study.…”

Section: Discussionmentioning

confidence: 99%

“…The performance of the TPS algorithm was evaluated in the period from 1 March 2019 to 29 February 2020. A leave-one-out cross-validation procedure was employed for each AWS site, similar to the method employed in Webb, Kidd & Minasny (2020). Specifically, the training dataset was split into i parts such that i is equal to the number of AWS sites, that is 534.…”

Section: Air Temperature Datamentioning

confidence: 99%

“…The proposed methodology, as advocated by Webb, Kidd & Minasny (2020), was adopted in this study for operational real-time monitoring of T a across continental Australia. However, since the formation of BoM grids and calibration equations were not required in this study, the methodology was retrofitted to consist of two major components.…”

Section: Application To Real-time Monitoring Of T Amentioning

confidence: 99%

“…However, if this threshold was not met during the allocated query times, the mapping was still permitted to commence at the 30-min mark regardless of the number of observations available (this was subsequently recorded). To provide context of the proposed system, the same procedure by Webb, Kidd & Minasny (2020) found that most observations tended to be imported at the 15-min mark (from the nearest observation hour) with corresponding TPS maps completed thereafter at the 17-min mark. The rationale for this study assumes a similar time frame, albeit at bi-hourly intervals, where observations are imported every 30-min (with an import time lag of~15-min from the nearest half-hour), followed by T a mapping thereafter.…”

Section: Application To Real-time Monitoring Of T Amentioning

confidence: 99%

“…The objective of this study was to apply and extend the methods in Webb, Kidd & Minasny (2020) for production of T a maps across continental Australia. TPS interpolation is used to produce T a maps at sub-hourly intervals (every 30-min) based on recordings garnered directly from BoM automatic weather station (AWS) sites.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A digital mapping application for quantifying and displaying air temperatures at high spatiotemporal resolutions in near real-time across Australia

Webb¹,

Minasny²

2020

PeerJ

Self Cite

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Surface air temperature (Ta) required for real-time environmental modelling applications should be spatially quantified to capture the nuances of local-scale climates. This study created near real-time air temperature maps at a high spatial resolution across Australia. This mapping is achieved using the thin plate spline interpolation in concert with a digital elevation model and ‘live’ recordings garnered from 534 telemetered Australian Bureau of Meteorology automatic weather station (AWS) sites. The interpolation was assessed using cross-validation analysis in a 1-year period using 30-min interval observation. This was then applied to a fully automated mapping system—based in the R programming language—to produce near real-time maps at sub-hourly intervals. The cross-validation analysis revealed broad similarities across the seasons with mean-absolute error ranging from 1.2 °C (autumn and summer) to 1.3 °C (winter and spring), and corresponding root-mean-square error in the range 1.6 °C to 1.7 °C. The R2 and concordance correlation coefficient (Pc ) values were also above 0.8 in each season indicating predictions were strongly correlated to the validation data. On an hourly basis, errors tended to be highest during the late afternoons in spring and summer from 3 pm to 6 pm, particularly for the coastal areas of Western Australia. The mapping system was trialled over a 21-day period from 1 June 2020 to 21 June 2020 with majority of maps completed within 28-min of AWS site observations being recorded. All outputs were displayed in a web mapping application to exemplify a real-time application of the outputs. This study found that the methods employed would be highly suited for similar applications requiring real-time processing and delivery of climate data at high spatiotemporal resolutions across a considerably large land mass.

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Section: Discussionmentioning

confidence: 99%

Section: Air Temperature Datamentioning

confidence: 99%

Section: Application To Real-time Monitoring Of T Amentioning

confidence: 99%

Section: Application To Real-time Monitoring Of T Amentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A digital mapping application for quantifying and displaying air temperatures at high spatiotemporal resolutions in near real-time across Australia

Webb¹,

Minasny²

2020

PeerJ

Self Cite

View full text Add to dashboard Cite

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Continental scale spatial temporal interpolation of near-surface air temperature: do 1 km hourly grids for Australia outperform regional and global reanalysis outputs?

Stewart,

McVicar,

Van Niel

et al. 2024

Clim Dyn

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Near-surface air temperature is an essential climate variable for the study of many biophysical phenomena, yet is often only available as a daily mean or extrema (minimum, maximum). While many applications require sub-diurnal dynamics, temporal interpolation methods have substantial limitations and atmospheric reanalyses are complex models that typically have coarse spatial resolution and may only be periodically updated. To overcome these issues, we developed an hourly air temperature product for Australia with spatial interpolation of hourly observations from 621 stations between 1990 and 2019. The model was validated with hourly observations from 28 independent stations, compared against empirical temporal interpolation methods, and both regional (BARRA-R) and global (ERA5-Land) reanalysis outputs. We developed a time-varying (i.e., time-of-day and day-of-year) coastal distance index that corresponds to the known dynamics of sea breeze systems, improving interpolation performance by up to 22.4% during spring and summer in the afternoon and evening hours. Cross-validation and independent validation (n = 24/4 OzFlux/CosmOz field stations) statistics of our hourly output showed performance that was comparable with contemporary Australian interpolations of daily air temperature extrema (climatology/hourly/validation: R2 = 0.99/0.96/0.92, RMSE = 0.75/1.56/1.78 °C, Bias = -0.00/0.00/-0.03 °C). Our analyses demonstrate the limitations of temporal interpolation of daily air temperature extrema, which can be biased due to the inability to represent frontal systems and assumptions regarding rates of temperature change and the timing of minimum and maximum air temperature. Spatially interpolated hourly air temperature compared well against both BARRA-R and ERA5-Land, and performed better than both reanalyses when evaluated against the 28 independent validation stations. Our research demonstrates that spatial interpolation of sub-diurnal meteorological fields, such as air temperature, can mitigate the limitations of alternative data sources for studies of near-surface phenomena and plays an important ongoing role in supporting numerous scientific applications.

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Geostatistical modelling of rainfall in Fars Province of Iran using non-Gaussian spatial process

Zareifard

Mahbod

Mohammadi

2023

Theor Appl Climatol

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Near real-time mapping of air temperature at high spatiotemporal resolutions in Tasmania, Australia

Cited by 5 publications

References 38 publications

A digital mapping application for quantifying and displaying air temperatures at high spatiotemporal resolutions in near real-time across Australia

A digital mapping application for quantifying and displaying air temperatures at high spatiotemporal resolutions in near real-time across Australia

Continental scale spatial temporal interpolation of near-surface air temperature: do 1 km hourly grids for Australia outperform regional and global reanalysis outputs?

Geostatistical modelling of rainfall in Fars Province of Iran using non-Gaussian spatial process

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