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Tim R. McVicar  - - - 
Top co-authors See all
A.J. Dolman

233 shared publications

Department of Earth Sciences, Vrije Universiteit Amsterdam, Boelelaan 1085, Amsterdam, 1081 HV, NETHERLANDS

Santiago Beguería

117 shared publications

Estación Experimental de Aula Dei (EEAD-CSIC), Zaragoza, E-50059, Spain

Diego G. Miralles

80 shared publications

Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, 9000 Gent, Belgium

Fernando Domínguez-Castro

69 shared publications

Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones (IPE-CSIC), Zaragoza, SPAIN

Tim R. McVicar

69 shared publications

CSIRO Land and Water, Canberra, Australian Capital Territory, and Australian Research Council Centre of Excellence for Climate System Science, Sydney, New South Wales, Australia

Publication Record
Distribution of Articles published per year 
(2002 - 2018)
Total number of journals
published in
Publications See all
Article 0 Reads 2 Citations MSWEP V2 Global 3-Hourly 0.1° Precipitation: Methodology and Quantitative Assessment Hylke E. Beck, Eric F. Wood, Ming Pan, Colby K. Fisher, Dieg... Published: 01 March 2019
Bulletin of the American Meteorological Society, doi: 10.1175/bams-d-17-0138.1
DOI See at publisher website
Article 0 Reads 1 Citation Hydrologic implications of vegetation response to elevated CO2 in climate projections Yuting Yang, Michael L. Roderick, Shulei Zhang, Tim R. McVic... Published: 17 December 2018
Nature Climate Change, doi: 10.1038/s41558-018-0361-0
DOI See at publisher website
Article 0 Reads 0 Citations An approach to homogenize daily peak wind gusts: An application to the Australian series Cesar Azorin-Molina, Jose A. Guijarro, Tim R. McVicar, Blair... Published: 13 December 2018
International Journal of Climatology, doi: 10.1002/joc.5949
DOI See at publisher website ABS Show/hide abstract
Daily Peak Wind Gust (DPWG) time series are important for the evaluation of wind‐related hazard risks to different socioeconomic and environmental sectors. Yet wind time series analyses can be impacted by several artefacts, both temporally and spatially, that may introduce inhomogeneities that mislead the study of their decadal variability and trends. The aim of this study is to present a strategy in the homogenization of a challenging climate extreme such as the DPWG using 548 time series across Australia for 1941‐2016. This automatic homogenization of DPWG is implemented in the recently developed Version 3.1 of the R package Climatol. This approach is an advance in homogenization of climate records as it identifies 353 breakpoints based on monthly data, splits the daily series into homogeneous sub‐periods, and homogenizes them without needing the monthly corrections. The major advantages of this homogenization strategy are its ability to: (i) automatically homogenize a large number of DPWG series, including short‐term ones and without needing site metadata (e.g., the change in observational equipment in 2010/2011 was correctly identified); (ii) use the closest reference series even not sharing a common period with candidate series or presenting missing data; and (iii) supply homogenized series, correcting anomalous data (quality control by spatial coherence), and filling in all the missing data. The NCEP/NCAR reanalysis wind speed data was also trialled in aiding homogenization given the station density was very low during the early decades of the record; however, reanalysis data did not improve the homogenization. Application of this approach found a reduced range of DPWG trends based on site data, and an increased negative regional trend of this climate extreme, compared to raw data and homogenized data using NCEP/NCAR. The analysis produced the first homogenized DPWG dataset to assess and attribute long‐term variability of extreme winds across Australia.
Article 0 Reads 0 Citations Determining the initial spatial extent of an environmental impact assessment with a probabilistic screening methodology Luk J.M. Peeters, Daniel E. Pagendam, Russell S. Crosbie, Pr... Published: 01 November 2018
Environmental Modelling & Software, doi: 10.1016/j.envsoft.2018.08.020
DOI See at publisher website ABS Show/hide abstract
A crucial decision in defining the scope of an environmental impact assessment is to delineate the initial assessment area. We developed a probabilistic methodology to determine this area, which starts by identifying a key environmental variable, maximum acceptable change and acceptable probability of exceeding that threshold. The exceedance probability is determined with a limits of acceptability rejection sampling of informed prior parameter distributions. A qualitative uncertainty analysis, a formal and systematic discussion of the main assumptions and model choices, is complemented with global sensitivity analysis of the model results to identify the major sources of uncertainty and provide guidance for further research and data collection. For the case study on coal development in the Gloucester Basin (NSW, Australia), the initial assessment extent is unlikely to extend more than 5 km from the edge of the planned coal mines. The major source of uncertainty is the planned mine water production rate.
Article 0 Reads 4 Citations Present and future Köppen-Geiger climate classification maps at 1-km resolution Hylke E. Beck, Niklaus E. Zimmermann, Tim R. McVicar, Noemi ... Published: 30 October 2018
Scientific Data, doi: 10.1038/sdata.2018.214
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
We present new global maps of the Köppen-Geiger climate classification at an unprecedented 1-km resolution for the present-day (1980–2016) and for projected future conditions (2071–2100) under climate change. The present-day map is derived from an ensemble of four high-resolution, topographically-corrected climatic maps. The future map is derived from an ensemble of 32 climate model projections (scenario RCP8.5), by superimposing the projected climate change anomaly on the baseline high-resolution climatic maps. For both time periods we calculate confidence levels from the ensemble spread, providing valuable indications of the reliability of the classifications. The new maps exhibit a higher classification accuracy and substantially more detail than previous maps, particularly in regions with sharp spatial or elevation gradients. We anticipate the new maps will be useful for numerous applications, including species and vegetation distribution modeling. The new maps including the associated confidence maps are freely available via
Article 0 Reads 0 Citations Revisiting Pan Evaporation Trends in Australia a Decade on Clare M. Stephens, Tim R. McVicar, Fiona M. Johnson, Lucy A.... Published: 27 October 2018
Geophysical Research Letters, doi: 10.1029/2018gl079332
DOI See at publisher website