ORCID Profile
0000-0003-4692-6565
Current Organisations
Deakin University
,
Osaka Prefecture University
,
Dalian University of Technology
,
Australian Bureau of Meteorology
,
Swinburne University of Technology
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Publications
Global wave hindcast with Australian and Pacific Island Focus: From past to present
Publisher: Wiley
Date: 14-08-2021
DOI: 10.1002/GDJ3.104
Abstract: Wind‐wave hindcast data have many applications including climatology assessments for renewable energy projects, maritime engineering design, event‐based impact assessments, generating boundary conditions for further downscaling, amongst others. Here, we present a global wave hindcast with nested high‐resolution grids for the Exclusive Economic Zones of Australia and south west Pacific Island Countries, that is extended in time monthly. The model employs strategic methods to incorporate the effects of subgrid sized features such as small islands and islets. Various bulk wave parameters are available hourly from January 1979 to present, along with the full wave spectra at a set of 3,683 predetermined points distributed globally.
Cheap, reliable, reusable, thermally and chemically stable fluorinated hexagonal boron nitride nanosheets coated Au nanoparticles substrate for surface enhanced Raman spectroscopy
Publisher: Elsevier BV
Date: 02-2020
New high-resolution sea surface temperature forecasts for coral reef management on the Great Barrier Reef
Publisher: Springer Science and Business Media LLC
Date: 22-06-2019
Ocean Temperature Outlooks - Coral Bleaching Risk: Great Barrier Reef and Australian waters
Publisher: Bureau of Meteorology
Date: 2020
Feeding and housing the urban population: Environmental impacts at the peri-urban interface under different land-use scenarios
Publisher: Elsevier BV
Date: 11-2015
Diagnosis of historical inundation events in the Marshall Islands to assist early warning systems
Publisher: Springer Science and Business Media LLC
Date: 10-08-2019
Lessons From the Pacific Ocean Portal: Building Pacific Island Capacity to Interpret, Apply, and Communicate Ocean Information
Publisher: Frontiers Media SA
Date: 02-08-2019
Quantifying the Benefits of Altimetry Assimilation in Seasonal Forecasts of the Upper Ocean
Publisher: American Geophysical Union (AGU)
Date: 28-04-2023
DOI: 10.1029/2022JC019342
Abstract: Satellite altimetry measurements of sea surface height provide near‐global ocean state observations on sub‐monthly time scales, which are not always utilized by seasonal climate forecasting systems. As early as the mid‐1990s, attempts were made to assimilate altimetry observations to initialize climate models. These experiments demonstrated improved ocean forecasting skill, especially compared to experiments that did not assimilate subsurface ocean temperature information. Nowadays, some operational climate forecasting models utilize altimetry in their assimilation systems, whereas others do not. Here, we assess the impact of altimetry assimilation on seasonal prediction skill of ocean variables in two climate forecasting systems that are from the European Centre for Medium‐Range Weather Forecasts (SEAS5) and the Australian Bureau of Meteorology (ACCESS‐S). We show that assimilating altimetry improves the initialization of subsurface ocean temperatures, as well as seasonal forecasts of monthly variability in upper‐ocean heat content and sea level. Skill improvements are largest in the subtropics, where there are typically less subsurface ocean observations available to initialize the forecasts. In the tropics, there are no noticeable improvements in forecast skill. The positive impact of altimetry assimilation on forecast skill related to the subsurface ocean does not seem to affect predictions of sea surface temperature. Whether this is because current forecasting systems are close to the potential predictability limit for the ocean surface, or perhaps altimetry observations are not fully exploited, remains a question. In summary, we find that utilizing altimetry observations improves the overall global ocean forecasting skill, at least for upper‐ocean heat content and sea level.
A framework for assessing local PES proposals
Publisher: Elsevier BV
Date: 02-2015
Seasonal Forecasting Skill of Sea‐Level Anomalies in a Multi‐Model Prediction Framework
Publisher: American Geophysical Union (AGU)
Date: 06-2021
DOI: 10.1029/2020JC017060
Abstract: Coastal high water level events are increasing in frequency and severity as global sea‐levels rise, and are exposing coastlines to risks of flooding. Yet, operational seasonal forecasts of sea‐level anomalies are not made for most coastal regions. Advancements in forecasting climate variability using coupled ocean‐atmosphere global models provide the opportunity to predict the likelihood of future high water events several months in advance. However, the skill of these models to forecast seasonal sea‐level anomalies has not been fully assessed, especially in a multi‐model framework. Here, we construct a 10‐model ensemble of retrospective forecasts with future lead times of up to 11 months. We compare predicted sea levels from bias‐corrected forecasts with 20 years of observations from satellite‐based altimetry and shore‐based tide gauges. Forecast skill, as measured by anomaly correlation, tends to be highest in the tropical and subtropical open oceans, whereas the skill is lower in the higher latitudes and along some continental coasts. For most locations, multi‐model averaging produces forecast skill that is comparable to or better than the best performing in idual model. We find that the most skillful predictions typically come from forecast systems with more accurate initializations of sea level, which is generally achieved by assimilating altimetry data. Having relatively higher horizontal resolution in the ocean is also beneficial, as such models seem to better capture dynamical processes necessary for successful forecasts. The multi‐model assessment suggests that skillful seasonal sea‐level forecasts are possible in many, though not all, parts of the global ocean.
Forecasting extreme marine heat events in key aquaculture regions around New Zealand
Publisher: CSIRO Publishing
Date: 09-03-2022
DOI: 10.1071/ES21012
Abstract: The Tasman Sea has been identified as a climate hotspot and has experienced several marine heatwaves (MHWs) in recent years. These events have impacted coastal regions of New Zealand (NZ), which has had a follow-on effect on local marine and aquaculture industries. Advance warning of extreme marine heat events would enable these industries to mitigate potential losses. Here we present an assessment of the forecast skill of the Australian Bureau of Meteorology’s seasonal prediction system, Australian Community Climate and Earth-System Simulator-Seasonal v1.0 (ACCESS-S1), for three key aquaculture regions around NZ: Hauraki Gulf, Western Cook Strait and Foveaux Strait. We investigate the skill of monthly sea surface temperature anomaly (SSTA) forecasts, and forecasts for SSTA exceeding the 90th percentile, which is an accepted MHW threshold. We find that the model has skill for predicting extreme heat events in all three regions at 0–2 month lead times. We then demonstrate that ACCESS-S1 was able to capture observed monthly SSTA exceeding the 90th percentile around coastal NZ during the 2019 Tasman Sea MHW at a lead time of 1 month. Finally, we discuss the relationship between SSTA in the Tasman Sea and SSTA in coastal regions of NZ, and thus the Tasman Sea as a source of model SSTA skill in the three key coastal regions. Results from this study show that skilful forecasts of ocean heat extremes in regional areas have the potential to enable marine operators in the aquaclture industry to mitigate losses due to MHWs, especially in a warming climate.
Subseasonal prediction of the 2020 Great Barrier Reef and Coral Sea marine heatwave
Publisher: IOP Publishing
Date: 12-2021
Abstract: The 2020 marine heatwave (MHW) in the Great Barrier Reef (GBR) and Coral Sea led to mass coral bleaching. Sea surface temperature anomalies reached +1.7 °C for the whole of the GBR and Coral Sea and exceeded +2 °C across broad regions (referenced to 1990–2012). The MHW reached Category 2 (Strong) and warm anomalies peaked between mid-February and mid-March 2020. The MHW’s peak intensity aligned with regions of reduced cloud cover and weak wind speeds. We used a MHW framework to assess the ability of an operational coupled ocean-atmosphere prediction system (Australian Community Climate and Earth System Simulator Seasonal version 1) to capture the MHW’s severity, duration, and spatial extent. For initial week predictions, the predicted MHW severity generally agreed with the magnitude and spatial extent of the observed severity for that week. The model ensemble mean did not capture the MHW’s development phase at lead times beyond the first week. The model underestimated the MHW’s spatial extent, which reached up to 95% of the study area with at least Moderate severity and up to 43% with at least Strong severity. However, most forecast ensemble members correctly predicted the period of Strong severity in the first week of the model forecast. The model correctly predicted MHW conditions to persist from mid-February to mid-March but did not capture the end of the MHW. The inability to predict the end of the event and other periods of less skilful prediction were related to subseasonal variability owing to weather systems, including the passage of tropical cyclones not simulated in the model. On subseasonal time scale, evaluating daily to weekly forecasts of ocean temperature extremes is an important step toward implementing methods for developing operational forecast extremes products for use in early warning systems.
Related Organisations
Related Funding Activities
No related grants have been discovered for Grant Smith.