370202. Climatology
| Title | 370202. Climatology |
|---|---|
| Parent | 3702. Climate change science |
Latest research outputs
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Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model
Rashid, Md. Mamunur, Beecham, Simon and Chowdhury, Resaul Kabir. 2017. "Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model." Theoretical and Applied Climatology. 130 (1-2), pp. 453-466. https://doi.org/10.1007/s00704-016-1892-9Article
Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region
Mouatadid, Soukayna, Raj, Nawin, Deo, Ravinesh C. and Adamowski, Jan F.. 2018. "Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region." Atmospheric Research. 212, pp. 130-149. https://doi.org/10.1016/j.atmosres.2018.05.012Article
Re-imagining standard timescales in forecasting precipitation events for Queensland’s grazing enterprises
McCarthy, E., Deo, R. C., Li, Y. and Maraseni, T.. 2017. "Re-imagining standard timescales in forecasting precipitation events for Queensland’s grazing enterprises." Syme, G., Hatton MacDonald, D., Fulton, B. and Piantadosi, J. (ed.) 22nd International Congress on Modelling and Simulation (MODSIM2017). Hobart, Australia 03 - 08 Dec 2017 Australia. Modelling and Simulation Society of Australia and New Zealand . https://doi.org/10.36334/modsim.2017.L1.mccarthyPaper
Wavelet analysis–artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China
Wen, Xiaohu, Feng, Qi, Deo, Ravinesh C., Wu, Min and Si, Jianhua. 2017. "Wavelet analysis–artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China." Hydrology Research: an international journal. 48 (6), pp. 1710-1729. https://doi.org/10.2166/nh.2016.396Article
Ensemble committee-based data intelligent approach for generating soil moisture forecasts with multivariate hydro-meteorological predictors
Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2018. "Ensemble committee-based data intelligent approach for generating soil moisture forecasts with multivariate hydro-meteorological predictors." Soil and Tillage Research. 181, pp. 63-81. https://doi.org/10.1016/j.still.2018.03.021Article
Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey
Ghorbani, Mohammad Ali, Deo, Ravinesh C., Karimi, Vahid, Yaseen, Zaher Mundher and Terz, Ozlem. 2018. "Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey." Stochastic Environmental Research and Risk Assessment. 32 (6), pp. 1683-1697. https://doi.org/10.1007/s00477-017-1474-0Article
Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran
Ghorbani, M. A., Deo, Ravinesh C., Yaseen, Zaher Mundher, Kashani, Mahsa H. and Mohammadi, Babak. 2018. "Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran." Theoretical and Applied Climatology. 133 (3-4), pp. 1119-1131. https://doi.org/10.1007/s00704-017-2244-0Article
Statistical evaluation of rainfall time series in concurrence with agriculture and water resources of Ken River basin, Central India (1901–2010)
Meshram, Sarita Gajbhiye, Singh, Sudhir Kumar, Meshram, Chandrashekhar, Deo, Ravinesh C. and Ambade, Balram. 2018. "Statistical evaluation of rainfall time series in concurrence with agriculture and water resources of Ken River basin, Central India (1901–2010)." Theoretical and Applied Climatology. 134, pp. 1231-1243. https://doi.org/10.1007/s00704-017-2335-yArticle
Improving the use of climate information in decision-making
Hewitt, Chris D., Stone, Roger C. and Tait, Andrew B.. 2017. "Improving the use of climate information in decision-making." Nature Climate Change. 7 (9), pp. 614-616. https://doi.org/10.1038/nclimate3378Notes or commentaries
Separation of the Climatic and Land Cover Impacts on the Flow Regime Changes in Two Watersheds of Northeastern Tibetan Plateau
Yang, Linshan, Feng, Qi, Yin, Zhenliang, Deo, Ravinesh C., Wen, Xiaohu, Si, Jianhua and Li, Changbin. 2017. "Separation of the Climatic and Land Cover Impacts on the Flow Regime Changes in Two Watersheds of Northeastern Tibetan Plateau." Advances in Meteorology. 2017, pp. 1-15. https://doi.org/10.1155/2017/6310401Article
Changes in climatic elements in the Pan-Hexi region during 1960–2014 and responses to global climatic changes
Wei, Liu, Feng, Qi and Deo, Ravinesh C.. 2018. "Changes in climatic elements in the Pan-Hexi region during 1960–2014 and responses to global climatic changes." Theoretical and Applied Climatology. 133 (1-2), pp. 405-420. https://doi.org/10.1007/s00704-017-2194-6Article
Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones
Nguyen-Huy, Thong, Deo, Ravinesh C., An-Vo, Duc-Anh, Mushtaq, Shahbaz and Khan, Shahjahan. 2017. "Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones." Agricultural Water Management. 191, pp. 153-172. https://doi.org/10.1016/j.agwat.2017.06.010Article
Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm
Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2017. "Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm." Atmospheric Research. 197, pp. 42-63. https://doi.org/10.1016/j.atmosres.2017.06.014Article
Spatial variation in springtime temperature index values during ENSO and IOD events shows non-equivalent phase response for viticultural regions in Australia
Jarvis, C., Darbyshire, R., Goodwin, I., Barlow, E. and Eckard, R.. 2018. "Spatial variation in springtime temperature index values during ENSO and IOD events shows non-equivalent phase response for viticultural regions in Australia." Agriculture and Forest Meteorology. 250-251, pp. 217-225. https://doi.org/10.1016/j.agrformet.2017.12.261Article
Influence of El Niño-Southern Oscillation and the Indian Ocean Dipole on winegrape maturity in Australia
Jarvis, C., Darbyshire, R., Eckard, R., Goodwin, I. and Barlow, E.. 2018. "Influence of El Niño-Southern Oscillation and the Indian Ocean Dipole on winegrape maturity in Australia ." Agriculture and Forest Meteorology. 248, pp. 502-510. https://doi.org/10.1016/j.agrformet.2017.10.021Article
Connecting the dots - climate information has no value unless it changes a management decision: Some illustrative cases
Stone, Roger C.. 2009. "Connecting the dots - climate information has no value unless it changes a management decision: Some illustrative cases." Wesley, Michael, Xinsheng, Wang and McMillen, Don (ed.) Non-traditional security in PRC - Australia relations: GLOBAL issues of common concern (2009). Guangzhou, China 02 - 04 Jul 2009 Brisbane, Australia.Paper
Quantitative definition and spatiotemporal distribution of little water season (LIWAS) in Korea
Kim, Su-Jeong, Byun, Hi-Ryong and Deo, Ravinesh C.. 2016. "Quantitative definition and spatiotemporal distribution of little water season (LIWAS) in Korea." Asia-Pacific Journal of Atmospheric Sciences. 52 (4), pp. 379-393. https://doi.org/10.1007/s13143-016-0012-1Article
The early 20th century warming: Anomalies, causes, and consequences
Hegerl, Gabriele C., Bronnimann, Stefan, Schurer, Andrew and Cowan, Tim. 2018. "The early 20th century warming: Anomalies, causes, and consequences." WIREs Climate Change. 9 (4). https://doi.org/10.1002/wcc.522Article
Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model
Deo, Ravinesh C., Tiwari, Mukesh K., Adamowski, Jan F. and Quilty, John M.. 2017. "Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model." Stochastic Environmental Research and Risk Assessment. 31 (5), pp. 1211-1240. https://doi.org/10.1007/s00477-016-1265-zArticle
Future strategies for climate services in agriculture: GFCS and collaborative implementation Australia / Western Pacific - national / regional implementation strategies
Stone, Roger. 2012. "Future strategies for climate services in agriculture: GFCS and collaborative implementation Australia / Western Pacific - national / regional implementation strategies." Joint International Symposium: ISAM 2012 and WMO-CAgM Climate Services for Agriculture: Best Practices and Future Strategies. Osaka, Japan 13 - 17 Mar 2012Paper
Current climate data rescue activities in Australia
Ashcroft, Linden, Allan, Rob, Bridgman, Howard, Gergis, Joelle, Pudmenzky, Christa and Thornton, Ken. 2016. "Current climate data rescue activities in Australia." Advances in Atmospheric Sciences. 33 (12), pp. 1323-1324. https://doi.org/10.1007/s00376-016-6189-5Notes or commentaries
Application of hybrid artificial neural network algorithm for the prediction of Standardized Precipitation Index
Dayal, Kavina S., Deo, Ravinesh C. and Apan, Armando A.. 2016. "Application of hybrid artificial neural network algorithm for the prediction of Standardized Precipitation Index." 2016 IEEE Region 10 International Conference: Technologies for Smart Nation (TENCON 2016). Singapore 22 - 25 Nov 2016 Singapore. https://doi.org/10.1109/TENCON.2016.7848588Paper
Time of Observation Error (TOBs) in temperature maxima can be reliably measured from real data (rather than estimated from models)
House, Ron. 2016. Time of Observation Error (TOBs) in temperature maxima can be reliably measured from real data (rather than estimated from models). Toowoomba, Australia. Unpublished.Working paper
Food shortages are associated with droughts, floods, frosts and ENSO in Papua New Guinea
Cobon, David H., Ewai, Maureen, Inape, Kasis and Bourke, R. Michael. 2016. "Food shortages are associated with droughts, floods, frosts and ENSO in Papua New Guinea." Agricultural Systems. 145, pp. 150-164. https://doi.org/10.1016/j.agsy.2016.02.012Article
Effects of regional climate change on brown rust disease in winter wheat
Junk, J., Kouadio, L., Delfosse, P. and El Jarroudi, M.. 2016. "Effects of regional climate change on brown rust disease in winter wheat." Climatic Change: an interdisciplinary, international journal devoted to the description, causes and implications of climatic change. 135 (3-4), pp. 439-451. https://doi.org/10.1007/s10584-015-1587-8Article
Weather Detective: An Australian citizen science project
Pudmenzky, Christa. 2017. "Weather Detective: An Australian citizen science project." AMOS/MSNZ Conference and ANZ Climate Forum 2017. Canberra, Australia 07 - 10 Feb 2017Presentation
getCRUCLdata: use and explore CRU CL v. 2.0 climatology elements in R
Sparks, Adam H.. 2017. getCRUCLdata: use and explore CRU CL v. 2.0 climatology elements in R. https://cran.r-project.org/package=getCRUCLdata. Comprehensive R Archive Network. https://doi.org/10.21105/joss.00230Software
Prediction of SPEI using MLR and ANN: a case study for Wilsons Promontory Station in Victoria
Mouatadid, Soukayna, Deo, Ravinesh C. and Adamowski, Jan F.. 2015. "Prediction of SPEI using MLR and ANN: a case study for Wilsons Promontory Station in Victoria." Guerrero, Juan E. (ed.) 2015 IEEE 14th International Conference on Machine Learning and Applications. Miami, United States of America 09 - 11 Dec 2015 United States. https://doi.org/10.1109/ICMLA.2015.87Paper
Statistical downscaling of climate change scenarios of rainfall and temperature over Indira Sagar Canal Command area in Madhya Pradesh, India
Shukla, Rituraj, Deo, Ravinesh and Khare, Deepak. 2015. "Statistical downscaling of climate change scenarios of rainfall and temperature over Indira Sagar Canal Command area in Madhya Pradesh, India." Guerrero, Juan E. (ed.) 2015 IEEE 14th International Conference on Machine Learning and Applications. Miami, United States of America 09 - 11 Dec 2015 USA. https://doi.org/10.1109/ICMLA.2015.75Paper
Robusta coffee model: an integrated model for coffee production at a regional scale
Kouadio, Louis, Stone, Roger, Tixier, Philippe, Mushtaq, Shahbaz and Marcussen, Torben. 2015. "Robusta coffee model: an integrated model for coffee production at a regional scale." Tropical Agriculture Conference 2015: Meeting the Productivity Challenge in the Tropics (TropAg2015). Brisbane, Australia 16 - 18 Nov 2015Poster
Monthly prediction of air temperature in Australia and New Zealand with machine learning algorithms
Salcedo-sanz, S., Deo, R. C., Carro-Calvo, L. and Saavedra-Moreno, B.. 2016. "Monthly prediction of air temperature in Australia and New Zealand with machine learning algorithms." Theoretical and Applied Climatology. 125 (1-2), pp. 13-25. https://doi.org/10.1007/s00704-015-1480-4Article
Projection of heat wave mortality related to climate change in Korea
Kim, Do-Woo, Deo, Ravinesh C., Chung, Jea-Hak and Lee, Jong-Seol. 2016. "Projection of heat wave mortality related to climate change in Korea." Natural Hazards. 80 (1), pp. 623-637. https://doi.org/10.1007/s11069-015-1987-0Article
A palaeoclimatic rainfall history from Lake Broadwater, southeast Queensland, Australia
Cottrill, D. A., Ribbe, J., Maron, M. and Jacobsen, G.. 2014. "A palaeoclimatic rainfall history from Lake Broadwater, southeast Queensland, Australia." Proceedings of the Royal Society of Queensland. 119, pp. 35-43.Article
Broad scale mapping of vegetation cover across Australia from rainfall and temperature data
Pudmenzky, Christa, King, Rachel and Butler, Harry. 2015. "Broad scale mapping of vegetation cover across Australia from rainfall and temperature data." Journal of Arid Environments. 120, pp. 55-62. https://doi.org/10.1016/j.jaridenv.2015.04.010Article
On the use of composite analyses to form physical hypotheses: An example from heat wave - SST associations
Boschat, Ghyslaine, Simmonds, Ian, Purich, Purich, Cowan, Tim and Pezza, Alexandre Bernardes. 2016. "On the use of composite analyses to form physical hypotheses: An example from heat wave - SST associations." Scientific Reports. 6. https://doi.org/10.1038/srep29599Article
Flood adaptation strategies under climate change in Nepal: a socio-hydrological aalysis
Devkota, Rohini Prasad. 2014. Flood adaptation strategies under climate change in Nepal: a socio-hydrological aalysis. PhD Thesis Doctor of Philosophy. University of Southern Queensland.PhD Thesis
Spatial and temporal variability of rainfall in the Gandaki River Basin of Nepal Himalaya
Panthi, Jeeban, Dahal, Piyush, Shrestha, Madan Lall, Aryal, Suman, Krakauer, Nir Y., Pradhanang, Soni M., Lakhankar, Tarendra, Jha, Ajay K., Sharma, Mohan and Karki, Ramchandra. 2015. "Spatial and temporal variability of rainfall in the Gandaki River Basin of Nepal Himalaya ." Climate. 3 (1), pp. 210-226. https://doi.org/10.3390/cli3010210Article
On the new concept of the available water climatology and its application
Byun, H. R., Kim, D. W., Choi, K. S., Deo, R. C., Lee, S. M., Park, C. K., Kwon, S. H., Kim, G. B. and Kwon, H. N.. 2014. "On the new concept of the available water climatology and its application." American Geophysical Union, Fall Meeting 2014. San Francisco, United States 15 - 19 Dec 2014 San Francisco, USA.Poster
Application of the artificial neural network model for prediction of monthly standardized precipitation and evapotranspiration index using hydrometeorological parameters and climate indices in eastern Australia
Deo, Ravinesh C. and Sahin, Mehmet. 2015. "Application of the artificial neural network model for prediction of monthly standardized precipitation and evapotranspiration index using hydrometeorological parameters and climate indices in eastern Australia." Atmospheric Research. 161-162, pp. 65-81. https://doi.org/10.1016/j.atmosres.2015.03.018Article
Reconfiguring agriculture through the relocation of production systems for water, environment and food security under climate change
Mushtaq, S., White, N., Cockfield, G., Power, B. and Jakeman, G.. 2015. "Reconfiguring agriculture through the relocation of production systems for water, environment and food security under climate change." The Journal of Agricultural Science. 153 (5), pp. 779-797. https://doi.org/10.1017/S0021859614001117Article