User profiles for David E. Robertson
David E. RobertsonResearch Scientist, CSIRO Verified email at csiro.au Cited by 4403 |
Ensemble flood forecasting: Current status and future opportunities
Ensemble flood forecasting has gained significant momentum over the past decade due to
the growth of ensemble numerical weather and climate prediction, expansion in high …
the growth of ensemble numerical weather and climate prediction, expansion in high …
[HTML][HTML] How suitable is quantile mapping for postprocessing GCM precipitation forecasts?
GCMs are used by many national weather services to produce seasonal outlooks of
atmospheric and oceanic conditions and fluxes. Postprocessing is often a necessary step before …
atmospheric and oceanic conditions and fluxes. Postprocessing is often a necessary step before …
Mount St. Helens ash from the 18 May 1980 eruption: chemical, physical, mineralogical, and biological properties
JS Fruchter, DE Robertson, JC Evans, KB Olsen… - Science, 1980 - science.org
Samples of ash from the 18 May 1980 eruption of Mount St. Helens were collected from
several locations in eastern Washington and Montana. The ash was subjected to a variety of …
several locations in eastern Washington and Montana. The ash was subjected to a variety of …
Complex relationship between seasonal streamflow forecast skill and value in reservoir operations
…, JC Bennett, DE Robertson… - Hydrology and Earth …, 2017 - hess.copernicus.org
Considerable research effort has recently been directed at improving and operationalising
ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving …
ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving …
[HTML][HTML] Merging seasonal rainfall forecasts from multiple statistical models through Bayesian model averaging
Merging forecasts from multiple models has the potential to combine the strengths of individual
models and to better represent forecast uncertainty than the use of a single model. This …
models and to better represent forecast uncertainty than the use of a single model. This …
Role of contamination in trace element analysis of sea water
DE Robertson - Analytical Chemistry, 1968 - ACS Publications
A wide variety of solvents, reagents, and other ma-terials normally encounteredin the trace
element analysis of sea water have been analyzedfor trace element impurities by neutron …
element analysis of sea water have been analyzedfor trace element impurities by neutron …
[HTML][HTML] A Bayesian approach to predictor selection for seasonal streamflow forecasting
DE Robertson, QJ Wang - Journal of Hydrometeorology, 2012 - journals.ametsoc.org
Statistical methods commonly used for forecasting climate and streamflows require the
selection of appropriate predictors. Poorly designed predictor selection procedures can result in …
selection of appropriate predictors. Poorly designed predictor selection procedures can result in …
Reliable long‐range ensemble streamflow forecasts: Combining calibrated climate forecasts with a conceptual runoff model and a staged error model
We present a new streamflow forecasting system called forecast guided stochastic scenarios
(FoGSS). FoGSS makes use of ensemble seasonal precipitation forecasts from a coupled …
(FoGSS). FoGSS makes use of ensemble seasonal precipitation forecasts from a coupled …
ADSORPTION OF TRACE ELEMENTS IN SEA WATER ON VARIOUS CONTAINER SURFACES.
DE Robertson - Anal. Chim. Acta, 42: 533-6 (Sept. 1968)., 1968 - osti.gov
Subject: N20230*-Chemistry-Inorganic, Organic, & Physical Chemistry-Physical Chemistry;
ACIDITY; ADSORPTION; ANTIMONY; CESIUM; COBALT; GLASS; HYDROCHLORIC ACID; …
ACIDITY; ADSORPTION; ANTIMONY; CESIUM; COBALT; GLASS; HYDROCHLORIC ACID; …
Combining the strengths of statistical and dynamical modeling approaches for forecasting Australian seasonal rainfall
…, QJ Wang, DE Robertson - Journal of Geophysical …, 2012 - Wiley Online Library
Forecasting rainfall at the seasonal time scale is highly challenging. Seasonal rainfall forecasts
are typically made using statistical or dynamical models. The two types of models have …
are typically made using statistical or dynamical models. The two types of models have …