@inbook {bnh-8346, title = {Connecting Weather and Hazard: A partnership of physical scientists in connected disciplines}, booktitle = {Towards the {\textquotedblleft}Perfect{\textquotedblright} Weather Warning: Bridging Disciplinary Gaps through Partnership and Communication}, year = {2022}, pages = {149}, publisher = {Springer Nature}, organization = {Springer Nature}, chapter = {6}, abstract = {

Achieving consistency in the prediction of the atmosphere and related environmental hazards requires careful design of forecasting systems. In this chapter, we identify the
benefits of seamless approaches to hazard prediction and the challenges of achieving them in a multi-institution situation. We see that different modelling structures are adopted in different disciplines and that these often relate to the user requirements for those hazards. We then explore the abilities of weather prediction to meet the requirements of these different disciplines. We find that differences in requirement and language can be major challenges to seamless data processing and look at some ways in which these can be resolved. We conclude with examples of partnerships in flood forecasting in the UK and wildfire forecasting in Australia.

}, keywords = {Cold, Coupled model, Evaluation, Fire, Forecaster, Heat, hydrology, Ocean Flood, Seamless, Winter}, issn = {978-3-030-98989-7}, doi = {doi.org/10.1007/978-3-030-98989-7_6}, url = {https://link.springer.com/chapter/10.1007/978-3-030-98989-7_6$\#$Abs1}, author = {Brian Golding and Jenny Sun and MIchael Riemer and Nusrat Yussouf and Helen Titley and Joanne Robbins and Beth Ebert and Tom Pagano and Huw Lewis and Claire Dashwood and Mika Peace} } @article {bnh-7868, title = {Impact-based forecasting for the coastal zone: East Coast Lows - final project report}, number = {647}, year = {2021}, month = {03/2021}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

The Bushfire and Natural Hazards CRC project Impact-based forecasting for the coastal zone: East-Coast Lows set out in 2017 to demonstrate a pilot capability to deliver wind and rain impact forecasts for residential housing from an ensemble of weather prediction models runs. The project was a collaborative effort between the Australian Bureau of Meteorology (Bureau) and Geoscience Australia (GA).

The project was initially focused on the wind and rainfall impact from the 20-22 April 2015 east coast low event in New South Wales (Wehner and Maqsood 2015). The wind and rainfall hazard data were provided by a 24-member ensemble of the Australian Community Climate Earth System Simulator (ACCESS; Bureau of Meteorology 2018) model on a 1.3 km grid, with damage data provided by NSW State Emergency Services (SES) and the Emergency Information Coordination Unit (EICU. Exposure data were sourced from the National EXposure Information System (NEXIS; Nadimpalli et al. 2007; Power et al. 2017) at GA. Heuristic wind vulnerability functions, derived in a previous project, were also provided by GA, while no large-scale rain vulnerability relationships existed.

Through the utilisation of GA{\textquoteright}s HazImp software, we developed and tested a workflow that integrated the numerical weather forecasts, vulnerability relationships and exposure data at the community level, and early in the second year of the project we started producing the first spatial quantitative wind impact plots.

The multi-hazard nature of the east coast low event, the relatively low wind speeds relative to the design wind speeds for the affected residential buildings and the available damage assessment data made attributing the observed building damage to a single hazard such as wind or rain difficult. Wind damage to residential housing in this case was largely due to tree fall, as opposed to structural failure, while the most severe damage for the Dungog event was due to flood inundation. To increase the utility of the damage assessment data we recommended early in our project that the SES/EICU damage survey templates should record multiple damage states and linkages between damage and the associate hazard(s). Such expanded recording practices would lead to improvements in the development of the hazard-damage relationships, a requirement for progress in quantitative hazard impact modelling. Additional uncertainty arose through the NEXIS exposure data which are statistically inferred at the Dungog township and are therefore merely indicative of the actual building attributes.

During the second year of the project a range of scope reductions were introduced in response to our previous and emerging findings during this second year.

The project set up the end-to-end workflow from wind hazard to spatial impact. These spatial impact outputs were delivered into the Visual Weather system at the Bureau of Meteorology, foreshadowing the possibility of easily achievable future visualisation to operational meteorologists.

To evaluate the performance of the quantitative wind impact forecast that we had produced, very careful and detailed processing of the available damage data was needed to remove damage reports due to tree fall, as opposed to structural failure, rain ingress, and flood inundation. We have now shown that the inclusion of exposure and vulnerability information can outperform a wind impact forecast that only uses a plain wind hazard prediction. In other words, the Dungog case study suggests that the extra effort needed for the quantitative inclusion of exposure and vulnerability information is a promising approach in the pursuit of future quantitative impact forecasts in Australia.

To gain a better understanding of how other agencies have approached the wind impact prediction problem, we also conducted an extensive literature search which resulted in a selective summary of meteorological hazard impact prediction systems. These findings have been submitted to the Australian Journal of Emergency Management as a review paper.

We finally applied our impact forecast methodology to a second extreme weather case during May 2020 in Perth. An extra-tropical cyclone produced widespread wind damage with wind gusts in excess of 100 km/h recorded over many hours. In this case we found that wind impact forecasts are sensitive to the fluctuations in wind gust forecasts produced by the Bureau{\textquoteright}s high-resolution real-time weather prediction models. Alongside the multi-hazard nature of damage to residential buildings, this impact sensitivity to the hazard constitutes a second complication for the quantitative prediction of wind impacts.

}, keywords = {coastal, east coast lows, Forecasting, zone}, issn = {647}, author = {Harald Richter and Craig Arthur and David Wilke and Mark Dunford and Martin Wehner and Beth Ebert} } @article {bnh-7302, title = {Impact-based forecasting for the coastal zone {\textendash} East Coast Lows: annual report 2019-2020}, number = {609}, year = {2020}, month = {09/2020}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

The Bushfire and Natural Hazards CRC project Impact-based forecasting for the coastal zone: East-Coast Lows demonstrates a pilot capability to deliver quantitative impact forecasts for residential housing from the Bureau{\textquoteright}s high resolution weather prediction models (or high resolution reanalysis for hindcasts). The project is a collaborative effort between the Australian Bureau of Meteorology and Geoscience Australia.\ 

The project goals include:

The project focuses on the wind impact on residential buildings from the 20-22 April 2015 east coast low event in New South Wales (a.k.a. the "Dungog case study"; Wehner and Maqsood 2015). The wind hazard data is provided by the high resolution version of the Australian Community Climate Earth System Simulator (ACCESS; Bureau of Meteorology 2018) model, or the equivalent high resolution reanalysis (BARRA-SY). The two damage data sets have been provided by NSW State Emergency Services (SES) and the Emergency Information Coordination Unit (EICU). Exposure and vulnerability information has been sourced from Geoscience Australia. Exposure data are sourced from the National Exposure Information System (NEXIS; Nadimpalli et al. 2007; Power et al. 2017), and heuristically derived vulnerability functions have been compiled as part of a previous project.

The multi-hazard nature of the east coast low event, the relatively low wind speeds and the limited available information in the damage assessment data makes attributing the observed building damage to the specific wind hazard very difficult. To evaluate the performance of the quantitative wind impact forecast that we have produced, very careful and detailed processing of the available damage data is needed to remove damage reports due to tree fall, as opposed to structural failure, rain ingress, and flood inundation.\ 

Despite the challenges above, we have now shown that the inclusion of exposure and vulnerability information can outperform a wind impact forecast that only uses a plain wind hazard prediction. In other words, the Dungog case study suggests that the extra effort needed for the quantitative inclusion of exposure and vulnerability information is a promising approach in the pursuit of future quantitative impact forecasts in Australia.\ 

We applied our impact forecast methodology to a second extreme weather case during May 2020 in Perth. An extra-tropical cyclone produced widespread wind damage with wind gusts in excess of 100 km/h recorded over many hours. In this case we found that wind impact forecasts are sensitive to the fluctuations in wind gust forecasts produced by the Bureau{\textquoteright}s high-resolution real-time weather prediction models. Alongside the multi-hazard nature of damage to residential buildings, this impact sensitivity to the hazard constitutes a second complication for the quantitative prediction of wind impacts.

To increase the utility of the damage assessment data we continue to recommend that the SES/EICU damage survey templates record multiple damage states and linkages between damage and the associated hazard(s). Such expanded recording practices would lead to improvements in the development of the hazard-damage relationships. Additional uncertainty arises through the NEXIS exposure data which are statistically inferred at the Dungog township and are therefore merely indicative of the actual building attributes.

}, keywords = {coastal zone, east coast lows, Forecasting}, issn = {609}, author = {Harald Richter and Craig Arthur and David Wilke and Mark Dunford and Beth Ebert and Martin Wehner} } @article {bnh-7802, title = {Report on the second end-user workshop {\textendash} Impact-based forecasting for the coastal zone: East Coast Lows}, number = {642}, year = {2020}, month = {01/2021}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

A virtual End-User Workshop was held on 25 and 27 August 2020 to present key outcomes of the Impact-based forecasting for the coastal zone: East Coast Lows project. This was the second end-user workshop for the project, and focused on four key themes:

  1. Verification of impact forecasts
  2. Demonstrating evolution of impact forecasts
  3. Identifying needs to deliver and support future impact forecast products
  4. Future utilisation opportunities.

We invited participants from emergency services agencies in Queensland, NSW, Victoria, South Australia and Western Australia, along with Emergency Management Australia (EMA). Also participating were a number of Bureau of Meteorology (BoM) officers who are embedded within the respective State Operations Centres in several states. A full list is provided at the end of this report.

}, keywords = {coastal zone, east coast low, Forecasting, impact based}, issn = {642}, author = {Harald Richter and Craig Arthur and David Wilke and Mark Dunford and Martin Wehner and Beth Ebert} } @article {bnh-5432, title = {Impact-Based Forecasting for the Coastal Zone: East Coast Lows- Annual Report 2017/2018}, number = {463}, year = {2019}, month = {03/2019}, pages = {1-28}, type = {Report}, keywords = {Built Environment, Forecasting, Severe Weather}, issn = {463}, author = {Harald Richter and Craig Arthur and Serena Schroeter and Martin Wehner and Jane Sexton and Beth Ebert and Mark Dunford and Jeffrey Kepert and Shoni Maguire and Russell Hay and Mark Edwards} } @conference {bnh-6402, title = {The physical impact of strong winds and heavy rain on residential housing: a pilot study}, booktitle = {Bushfire and Natural Hazards CRC Research Day AFAC19}, year = {2019}, month = {12/2019}, address = {Melbourne}, abstract = {

Research in the social science area have pointed out that "traditional" hazard-based forecasts and warnings may not be well understood so that mitigating actions for the protection of life and property are not taken (Demuth et al. 2012). The extension of a hazard forecast towards the description of impacts on the forecast recipient might effect a more suitable mitigating response and has led to an emerging and growing desire among National Hydrological and Meteorological Services for impact-based forecasts and warnings (Harrowsmith 2015; World Meteorological Organization 2015).

A number of major weather services (e.g. UK Met Office, Bureau of Meteorology) have therefore introduced impact-based services in recognition of the above findings. Since 2011 the UK Met Office has issued impact-based warnings where the warning level is derived from a risk matrix in a partly subjective procedure (Met Office 2018). In a related manner, the Extreme Weather Desk at the Australian Bureau of Meteorology has recently developed the Community Hazard Risk Outlook. Forecasters subjectively rate the expected impact level of a model-predicted hazard on a range of assets from which an aggregated impact level is calculated. Combined with a subjective likelihood assessment the UK Met Office risk matrix concept is again utilised to derive an overall hazard risk.

In addition to subjective or partly subjective impact specifications, the factors influential in the final likelihood, location or magnitude of an impact can be delivered as layers, which leaves their integration to the user. An example of such a system is the Global Hazard Map, also produced by the UK Met Office (Robbins and Titley 2018).

}, keywords = {assessment, Forecasting, impact-based, likelihood, mitigation, Warnings}, url = {Research in the social science area have pointed out that "traditional" hazard-based forecasts and warnings may not be well understood so that mitigating actions for the protection of life and property are not taken (Demuth et al. 2012). The extension of }, author = {Harald Richter and Craig Arthur and Martin Wehner and David Wilke and Mark Dunford and Beth Ebert} } @conference {bnh-4792, title = {Impact-based forecasting for the coastal zone}, booktitle = {AFAC18}, year = {2018}, month = {09/2018}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Perth}, abstract = {

Strong surface wind gusts and heavy rain are meteorological hazards that are predominantly produced by storms such as east coast lows, tropical cyclones or thunderstorms. Interest in these hazards from a response agency point of view lies in their impact on the natural and built environment. At present, weather forecast models still predict mostly {\textquoteright}raw{\textquoteright} meteorological output such as surface wind speeds at certain times, or rain accumulations over a specified period. This model output needs to be combined with exposure and vulnerability information to translate the forecast hazard into predicted impact.

The Bushfire and Natural Hazards CRC project Impact-based forecasting for the coastal zone: East-Coast Lows attempts to demonstrate a pilot capability to deliver impact forecasts for residential housing from an ensemble of weather prediction models runs. The project is a collaborative effort between the Australian Bureau of Meteorology and Geoscience Australia.

The project is initially focusing on the wind and rainfall impact from the 20-22 April 2015 east coast low event in NSW. The wind and rainfall hazard data are provided by a 24-member ensemble of the ACCESS model on a 1.3 km grid, with damage data acquired from NSW State Emergency Services (SES) and the Emergency Information Coordination Unit (EICU) for the 2015 event.

We will show that the multi-hazard nature of an east coast low event makes attributing the observed building damage to a single hazard difficult. Wind damage to residential housing in this case is largely due to tree fall. This {\textquoteright}damage-byintermediary{\textquoteright} mechanism requires not just the knowledge of building properties in an exposed area, but also additional knowledge of the surrounding vegetation and its response to strong winds. We will discuss enhancements to the SES/EICU damage survey templates that would lead to improvements in the development of the hazard-damage relationships.

}, author = {Harald Richter and Craig Arthur and Serena Schroeter and Martin Wehner and Jane Sexton and Beth Ebert and Mark Dunford and Jeffrey Kepert and Shoni Maguire and Russell Hay and Mark Edwards} } @conference {bnh-3898, title = {A new quantitative smoke forecasting system for Victoria}, booktitle = {AFAC17}, year = {2017}, month = {09/2017}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Sydney}, abstract = {

Smoke dispersion is a key concern for Government agencies. Government has a responsibility to protect community health in response to smoke events and to minimise the impact of smoke from planned burning.\  To inform community warnings and planned burn management, quality information is needed to support evidence-based decision making.

The Bureau of Meteorology has operated the HYSPLIT smoke dispersion system for use by fire and land management agencies for around 15 years. Recently DELWP funded research to improve smoke emission and transport modelling in Victoria. This project developed a new multi-tiered quantitative smoke prediction system which is a significant step forward compared with the old system.\  It applies recent observations of Victorian smoke emissions and atmospheric chemistry (as embodied in CSIRO{\textquoteright}s Chemical Transport Model) with the increased numerical capability in ensemble and high resolution weather modelling of the Bureau{\textquoteright}s ACCESS Numerical Weather Prediction suite.

The new smoke forecasting system has 3 tiers; Tier 1: 10-day ensemble forecasts of fire weather and fire danger indices to assist decisions on burn scheduling, Tier 2: 3-day forecasts of ambient air quality and smoke concentration from existing fires to provide background conditions for burns, and Tier 3: 1-day high resolution forecasts of smoke for planned prescribed burns to support go/no-go decisions.

In this presentation we will demonstrate the improved user interface for the smoke dispersion system and provide examples of output for each of the 3 forecast tiers. We will also describe the methodology for verifying the system output, including initial verification results. Finally areas of potential future work will be discussed, including how other jurisdictions can be involved so that this can become a national smoke dispersion system.

}, author = {Monica Long and Alan Wain and Cope, ME and Beth Ebert and Maree Carroll and Kevin Parkyn and Natalie Tostovrsnik} }