@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} } @conference {bnh-6410, title = {ACCESS-Fire: coupled fire-atmosphere modelling}, booktitle = {Bushfire and Natural Hazards CRC Research Day AFAC19}, year = {2019}, month = {12/2019}, address = {Melbourne}, abstract = {

Coupled models are a class of fire prediction models that integrate a fire component with an atmospheric component, to examine how the energy released by a fire modifies the surrounding atmosphere. Coupled models can resolve complex interactions between the fire, topography and atmosphere, which subsequently manifest on fire behaviour. Results from simulations promote understanding of the driving processes in dynamic fire events. This can inform development of predictive tools that may be used to anticipate extreme fire behaviour and mitigate against the impacts of significant fires.

Globally, several coupled models have been developed; mostly by meteorological institutions for application in a research capacity. They can be broadly separated as taking either physical or empirical modelling approaches. We are running ACCESS-Fire; an empirical coupled model. It links the research version of the Australian Community Climate and Earth System Simulator (ACCESS) Numerical Weather Prediction (NWP) to a set of empirically derived fire spread equations. In this presentation we will describe the coupled fire-atmosphere model ACCESS Fire and report on progress on simulations of recent significant fire events.

In Australia and overseas, the imperative for accurate, flexible and timely predictions for prescribed (fuel reduction) burns and bushfires will only increase. Incorporating complex, dynamical meteorological fields is a critical component in building fire prediction systems that can resolve some of the most destructive elements of fire behaviour. Although coupled fire-atmosphere models are currently limited in producing timely operational output due to computational requirements, these restrictions will diminish as technology capabilities continue to increase.

}, keywords = {coupled models, Fire behaviour, fire-atmosphere, Forecasting, modelling}, url = {https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/}, author = {Mika Peace and Jeffrey Kepert and Harvey Ye} } @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-6399, title = {Improving flood forecasting skill using remotely sensed data}, booktitle = {Bushfire and Natural Hazards CRC Research Day AFAC19}, year = {2019}, month = {12/2019}, address = {Melbourne}, abstract = {

This paper presents research undertaken to develop and implement a coupled hydrologic-hydraulic model which utilises remotely sensed data to improve flood forecasting skill in rural catchments subject to fluvial flooding. The discussion of literature reviews and subsequent knowledge gaps aids in the identification of key obstacles towards implementation. Collected data and modelling algorithms developed as part of the project are described before an overview of the progress towards implementation is given. To maximise the potential utilisation of this research end-users have been involved in providing data, setting up case studies, and defining research priorities and methods.

}, keywords = {catchments, Flood, Forecasting, hydraulic, hydrological, modelling}, url = {https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/}, author = {Ashley Wright and Stefania Grimaldi and Yuan Li and Jeffrey Walker and Valentijn Pauwels} } @article {bnh-5804, title = {Mitigating the effects of severe fires, floods and heatwaves through the improvements of land dryness measures and forecasts - annual report 2018-2019}, number = {507}, year = {2019}, month = {08/2019}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

The Bushfire and Natural Hazards CRC project titled {\textquotedblleft}Mitigating the Effects of Severe Fires, Floods and Heatwaves through the Improvements of Land Dryness Measures and Forecasts{\textquotedblright} examines the use of detailed land surface models,
satellite measurements and ground-based observations for the monitoring and prediction of landscape dryness. This project will address a fundamental limitation in our ability to prepare for fires, floods and heatwaves and is directly
linked to pre-event planning as well as forecasting of events.

Currently landscape dryness is estimated in Australia using simple empirical models developed in the 1960{\textquoteright}s. The most prominent of those used in Australia are the Keetch-Byram Drought Index (KBDI; Keetch \& Byram 1968) and the Soil Dryness Index (SDI; Mount 1972). An initial study performed as part of this project suggest that analyses of soil moisture can be improved by using physically based land surface models, remote sensing measurements and data assimilation. The project has developed a stand-alone prototype land surface modelling system to produce daily soil moisture analyses at 5km resolution and at 4 soil layers. Verification against ground-based soil moisture observations show that this prototype system is significantly more skilful than both KBDI and SDI.

The present report documents the activities undertaken in 2018-2019. A major focus for the year has been on the downscaling of soil moisture from the JASMIN system, enhancing the spatial resolution from 5 km to 1km. Applications like fire danger mapping may require soil moisture information at higher spatial resolution due to the large spatial variability of soil moisture in the landscape. Another major outcome from the project during this year was the publication of a peerreviewed paper in the highly regarded Agriculture and Forest Meteorology journal.

}, keywords = {Emergency management, fires, Floods, Forecasting, heatwaves, land dryness}, issn = {507}, author = {Vinod Kumar and Paul Fox-Hughes and Imtiaz Dharssi} } @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} } @article {bnh-6928, title = {Sources of soil dryness measures and forecasts for fire danger rating }, year = {2015}, month = {12/2015}, institution = {Bureau of Meteorology }, address = {Canberra}, abstract = {

The fuel availability estimates in McArthur Forest Fire Danger Index used in Australia for issuing operational fire warnings is based on soil moisture deficit, calculated as either the Keetch{\textendash}Byram Drought Index (KBDI) or Mount{\textquoteright}s Soil Dryness Index (MSDI). These indices are essentially simplified, empirical water balance models designed to estimate soil moisture depletion in the upper soil levels. These two models over-simplify processes like evapotranspiration and runoff which can lead to large uncertainties in the predicted soil moisture deficit. With advancements in the science of soil moisture measurement and modelling, better products are available for use in fire danger ratings. As such, a detailed review of the established and emerging soil moisture estimation techniques becomes necessary. With this in view, efforts have been made in this paper to discuss various soil moisture estimation methods, their advantages and limitations in a fire danger rating context. The discussion is not intended to be complete and reflect the authors{\textquoteright} interests, but we hope that it helps to highlight the soil moisture data sources that may not be well known outside the hydrological community, especially the people in fire management.

}, keywords = {fire management, Forecasting, forest fire danger index, fuel, soil dryness}, isbn = {978-0-642-70672-0}, issn = {Bureau Research Report - BRR009}, url = {http://www.bom.gov.au/research/publications/researchreports/BRR-009.pdf}, author = {Vinod Kumar and Imtiaz Dharssi} }