A bias corrected WRF mesoscale fire weather dataset for Victoria, Australia 1972-2012

Abstract

Climatology data of fire weather across the landscape can provide science-based evidence for informing strategic decisions to ameliorate the impacts (at times extreme) of bushfires on community socio-economic wellbeing and to sustain ecosystem health and functions. A long-term climatology requires spatial and temporal data that are consistent to represent the landscape in sufficient detail to be useful for fire weather studies and management purposes. To address this inhomogeneity problem for analyses of a variety of fire weather interests and to provide a dataset for management decision-support, a homogeneous 41-year (1972-2012), hourly interval, 4 km gridded climate dataset for Victoria has been generated using a combination of mesoscale modelling, global reanalysis data, surface observations, and historic observed rainfall analyses. Hourly near-surface forecast fields were combined with Drought Factor (DF) fields calculated from the Australian Water Availability Project (AWAP) rainfall analyses to generate fields of hourly fire danger indices for each hour of the 41-year period. A quantile mapping (QM) bias correction technique utilizing available observations during 1996-2012 was used to ameliorate any model biases in wind speed, temperature and relative humidity. Extensive evaluation was undertaken including both quantitative and case study qualitative assessments. The final dataset includes 4-km surface hourly temperature, relative humidity, wind speed, wind direction, Forest Fire Danger Index (FFDI), and daily DF and Keetch-Byram Drought Index (KBDI), and a 32-level full three-dimensional volume atmosphere.

Victorian fire weather trends and variability

“…The VicClim dataset was developed for Victoria using the Weather and Research Forecasting (WRF) model (Brown et al 2016) in a decade-long partnership project between the Desert Research Institute in Nevada, USA, DELWP and Monash University. This dataset has a spatial resolution of 4 x 4 km and an hourly temporal resolution for surface parameters FFDI, temperature, relative humidity, wind speed and wind direction, extending from 1972 to 2017.…”

“…Such information based on the observation record is constrained to the few observation sites that have sufficiently long record, while climate model produced climate datasets tend to lack the spatial and temporal resolution required by fire agencies. A new and unique high spatial (4x4 km) and temporal (1-hour) resolution bias-corrected homogenous 46-year gridded fire weather dataset developed for Victoria (Brown et al 2016) makes it possible to identify the trends and variability of FFDI. In this study we characterise the variability and trends of fire weather in Victoria, Australia using the latest version of the gridded fire weather dataset -VicClim Version 3.…”