Papers on Indian Ocean Dipole (IOD) and climate change

This is a list of papers on Indian Ocean Dipole (IOD) and climate change. The list is not complete, and will most likely be updated in future in order to make it more thorough and more representative.

Indo-Pacific Climate Modes in Warming Climate: Consensus and Uncertainty Across Model Projections – Zheng (2019)
“Purpose of Review: Understanding the changes in climate variability in a warming climate is crucial for reliable projections of future climate change. This article reviews the recent progress in studies of how climate modes in the Indo-Pacific respond to greenhouse warming, including the consensus and uncertainty across climate models. Recent Findings: Recent studies revealed a range of robust changes in the properties of climate modes, often associated with the mean state changes in the tropical Indo-Pacific. In particular, the intermodel diversity in the ocean warming pattern is a prominent source of uncertainty in mode changes. The internal variability also plays an important role in projected changes in climate modes. Summary: Model biases and intermodel variability remain major challenges for reducing uncertainty in projecting climate mode changes in warming climate. Improved models and research linking simulated present-day climate and future changes are essential for reliable projections of climate mode changes. In addition, large ensembles should be used for each model to reduce the uncertainty from internal variability and isolate the forced response to global warming.”
Zheng, X. Indo-Pacific Climate Modes in Warming Climate: Consensus and Uncertainty Across Model Projections. Curr Clim Change Rep 5, 308–321 (2019) doi:10.1007/s40641-019-00152-9. [FULL TEXT]

Disentangling the Changes in the Indian Ocean Dipole–Related SST and Rainfall Variability under Global Warming in CMIP5 Models – Huang et al. (2019)
“This study disentangles the changes in Indian Ocean (IO) dipole (IOD)-related SST and rainfall variability under global warming projected by the RCP8.5 runs in 29 CMIP5 models. The IOD rainfall changes consist of the thermodynamic component due to the surface moisture increase and the dynamic component due to the changes in IOD-related circulation. The IOD circulation changes are dominated by the IOD SST changes, which were further clarified using the amplitude and structural decomposition. The amplitudes of IOD SST and circulation are both decreased at rates of around 7.2% and 13.7% °C⁻¹, respectively. The structural changes in IOD SST and circulation show a pattern with increases from the eastern to the western coast of the equatorial IO, similar to the pattern of so-called extreme IOD events in previous studies. Disentangling previous mechanisms and projections, we conclude that the increased atmospheric stability suppresses the amplitudes in IOD SST and circulation, whereas the positive IOD (pIOD)-like mean-state SST changes, leading to greater warming in the west than the east, mainly alter the structure of IOD SST and circulation. Both the amplitude and structural changes in the IOD SST and circulation are robust among the CMIP5 models, but their distinct patterns and out-of-step changes lead to an uncertain projection of IOD changes defined by the dipole mode index or EOF analysis in previous studies. Furthermore, the structural changes, dominated by the pIOD-like mean-state SST changes, are significantly correlated with the historical IOD amplitude among the models. Considering the commonly overestimated IOD amplitude as an emergent constraint, the structural changes in IOD SST and circulation should not be as robust as the original multimodel projection.”
Huang, P., X. Zheng, and J. Ying, 2019: Disentangling the Changes in the Indian Ocean Dipole–Related SST and Rainfall Variability under Global Warming in CMIP5 Models. J. Climate, 32, 3803–3818, https://doi.org/10.1175/JCLI-D-18-0847.1. [FULL TEXT]

Influence of internal climate variability on Indian Ocean Dipole properties – Ng et al. (2018)
“The Indian Ocean Dipole (IOD) is the dominant mode of interannual variability over the tropical Indian Ocean (IO) and its future changes are projected to impact the climate and weather of Australia, East Africa, and Indonesia. Understanding the response of the IOD to a warmer climate has been largely limited to studies of individual coupled general circulation models or multi-model ensembles. This has provided valuable insight into the IOD’s projected response to increasing greenhouse gases but has limitations in accounting for the role of internal climate variability. Using the Community Earth System Model Large Ensemble (CESM-LE), the IOD is examined in thirty-five present-day and future simulations to determine how internal variability influences properties of the IOD and their response to a warmer climate. Despite small perturbations in the initial conditions as the only difference between ensemble members, significant relationships between the mean state of the IO and the IOD arise, leading to a spread in the projected IOD responses to increasing greenhouse gases. This is driven by the positive Bjerknes feedback, where small differences in mean thermocline depth, which are caused by internal climate variability, generate significant variations in IOD amplitude, skewness, and the climatological zonal sea surface temperature gradient.”
Ng, B., Cai, W., Cowan, T. et al. Influence of internal climate variability on Indian Ocean Dipole properties. Sci Rep 8, 13500 (2018) doi:10.1038/s41598-018-31842-3. [FULL TEXT]

Uncertainty in Indian Ocean Dipole response to global warming: the role of internal variability – Hui & Zheng (2018)
“The Indian Ocean Dipole (IOD) is one of the leading modes of interannual sea surface temperature (SST) variability in the tropical Indian Ocean (TIO). The response of IOD to global warming is quite uncertain in climate model projections. In this study, the uncertainty in IOD change under global warming, especially that resulting from internal variability, is investigated based on the community earth system model large ensemble (CESM-LE). For the IOD amplitude change, the inter-member uncertainty in CESM-LE is about 50% of the intermodel uncertainty in the phase 5 of the coupled model intercomparison project (CMIP5) multimodel ensemble, indicating the important role of internal variability in IOD future projection. In CESM-LE, both the ensemble mean and spread in mean SST warming show a zonal positive IOD-like (pIOD-like) pattern in the TIO. This pIOD-like mean warming regulates ocean-atmospheric feedbacks of the interannual IOD mode, and weakens the skewness of the interannual variability. However, as the changes in oceanic and atmospheric feedbacks counteract each other, the inter-member variability in IOD amplitude change is not correlated with that of the mean state change. Instead, the ensemble spread in IOD amplitude change is correlated with that in ENSO amplitude change in CESM-LE, reflecting the close inter-basin relationship between the tropical Pacific and Indian Ocean in this model.”
Hui, C., Zheng, X. Uncertainty in Indian Ocean Dipole response to global warming: the role of internal variability. Clim Dyn 51, 3597–3611 (2018) doi:10.1007/s00382-018-4098-2.

Assessing the Impact of Model Biases on the Projected Increase in Frequency of Extreme Positive Indian Ocean Dipole Events – Wang et al. (2017)
“For many generations, models simulate an Indian Ocean dipole (IOD) that is overly large in amplitude. The possible impact of this systematic bias on climate projections, including a projected frequency increase in extreme positive IOD (pIOD) using a rainfall-based definition, has attracted attention. In particular, a recent study suggests that the increased frequency is an artifact of the overly large IOD amplitude. In contrast, here the opposite is found. Through intermodel ensemble regressions, the present study shows that models producing a high frequency in the present-day climate generate a small future frequency increase. The frequency is associated with the mean equatorial west-minus-east sea surface temperature (SST) gradient: the greater the gradient, the greater the frequency because it is easier to shift convection to the west, which characterizes an extreme pIOD. A greater present-day gradient is associated with a present-day shallower thermocline, lower SSTs, and lower rainfall in the eastern equatorial Indian Ocean (EEIO). Because there is an inherent limit for a maximum rainfall reduction and for the impact on surface cooling by a shallowing of an already shallow mean EEIO thermocline, there is a smaller increase in frequency in models with a shallower present-day EEIO thermocline. Given that a bias of overly shallow EEIO thermocline and overly low EEIO SSTs and rainfall is common in models, the future frequency increase should be underestimated, opposite to an implied overestimation resulting from the overly large IOD amplitude bias. Therefore, correcting the projected frequency from a single bias, without considering other biases that are present, is not appropriate and should be avoided.”
Wang, G., W. Cai, and A. Santoso, 2017: Assessing the Impact of Model Biases on the Projected Increase in Frequency of Extreme Positive Indian Ocean Dipole Events. J. Climate, 30, 2757–2767, https://doi.org/10.1175/JCLI-D-16-0509.1. [FULL TEXT]

A Robust but Spurious Pattern of Climate Change in Model Projections over the Tropical Indian Ocean – Li et al. (2016)
“Climate models consistently project reduced surface warming over the eastern equatorial Indian Ocean (IO) under increased greenhouse gas (GHG) forcing. This IO dipole (IOD)-like warming pattern, regarded as robust based on consistency among models by the new Intergovernmental Panel on Climate Change (IPCC) report, results in a large increase in the frequency of extreme positive IOD (pIOD) events, elevating the risk of climate and weather disasters in the future over IO rim countries. These projections, however, do not consider large model biases in both the mean state and interannual IOD variance. In particular, a “present–future relationship” is identified between the historical simulations and representative concentration pathway (RCP) 8.5 experiments from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble: models with an excessive IOD amplitude bias tend to project a strong IOD-like warming pattern in the mean and a large increase in extreme pIOD occurrences under increased GHG forcing. This relationship links the present simulation errors to future climate projections, and is also consistent with our understanding of Bjerknes ocean–atmosphere feedback. This study calibrates regional climate projections by using this present–future relationship and observed IOD amplitude. The results show that the projected IOD-like pattern of mean changes and frequency increase of extreme pIOD events are largely artifacts of model errors and unlikely to emerge in the future. These results illustrate that a robust projection may still be biased and it is important to consider the model bias effect.”
Li, G., S. Xie, and Y. Du, 2016: A Robust but Spurious Pattern of Climate Change in Model Projections over the Tropical Indian Ocean. J. Climate, 29, 5589–5608, https://doi.org/10.1175/JCLI-D-15-0565.1. [FULL TEXT]

Monsoon-Induced Biases of Climate Models over the Tropical Indian Ocean – Li et al. (2015)
“Long-standing biases of climate models limit the skills of climate prediction and projection. Overlooked are tropical Indian Ocean (IO) errors. Based on the phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble, the present study identifies a common error pattern in climate models that resembles the IO dipole (IOD) mode of interannual variability in nature, with a strong equatorial easterly wind bias during boreal autumn accompanied by physically consistent biases in precipitation, sea surface temperature (SST), and subsurface ocean temperature. The analyses show that such IOD-like biases can be traced back to errors in the South Asian summer monsoon. A southwest summer monsoon that is too weak over the Arabian Sea generates a warm SST bias over the western equatorial IO. In boreal autumn, Bjerknes feedback helps amplify the error into an IOD-like bias pattern in wind, precipitation, SST, and subsurface ocean temperature. Such mean state biases result in an interannual IOD variability that is too strong. Most models project an IOD-like future change for the boreal autumn mean state in the global warming scenario, which would result in more frequent occurrences of extreme positive IOD events in the future with important consequences to Indonesia and East Africa. The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) characterizes this future IOD-like projection in the mean state as robust based on consistency among models, but the authors’ results cast doubts on this conclusion since models with larger IOD amplitude biases tend to produce stronger IOD-like projected changes in the future.”
Li, G., S. Xie, and Y. Du, 2015: Monsoon-Induced Biases of Climate Models over the Tropical Indian Ocean. J. Climate, 28, 3058–3072, https://doi.org/10.1175/JCLI-D-14-00740.1. [FULL TEXT]

Increased frequency of extreme Indian Ocean Dipole events due to greenhouse warming – Cai et al. (2014)
“The Indian Ocean dipole is a prominent mode of coupled ocean–atmosphere variability, affecting the lives of millions of people in Indian Ocean rim countries. In its positive phase, sea surface temperatures are lower than normal off the Sumatra–Java coast, but higher in the western tropical Indian Ocean. During the extreme positive-IOD (pIOD) events of 1961, 1994 and 1997, the eastern cooling strengthened and extended westward along the equatorial Indian Ocean through strong reversal of both the mean westerly winds and the associated eastward-flowing upper ocean currents. This created anomalously dry conditions from the eastern to the central Indian Ocean along the Equator and atmospheric convergence farther west, leading to catastrophic floods in eastern tropical African countries but devastating droughts in eastern Indian Ocean rim countries. Despite these serious consequences, the response of pIOD events to greenhouse warming is unknown. Here, using an ensemble of climate models forced by a scenario of high greenhouse gas emissions (Representative Concentration Pathway 8.5), we project that the frequency of extreme pIOD events will increase by almost a factor of three, from one event every 17.3 years over the twentieth century to one event every 6.3 years over the twenty-first century. We find that a mean state change—with weakening of both equatorial westerly winds and eastward oceanic currents in association with a faster warming in the western than the eastern equatorial Indian Ocean—facilitates more frequent occurrences of wind and oceanic current reversal. This leads to more frequent extreme pIOD events, suggesting an increasing frequency of extreme climate and weather events in regions affected by the pIOD.”
Wenju Cai, Agus Santoso, Guojian Wang, Evan Weller, Lixin Wu, Karumuri Ashok, Yukio Masumoto & Toshio Yamagata (2014). Nature volume 510:254–258. doi:10.1038/nature13327. [FULL TEXT]

Projected response of the Indian Ocean Dipole to greenhouse warming – Cai et al. (2013)
“Natural modes of variability centred in the tropics, such as the El Niño/Southern Oscillation and the Indian Ocean Dipole, are a significant source of interannual climate variability across the globe. Future climate warming could alter these modes of variability. For example, with the warming projected for the end of the twenty-first century, the mean climate of the tropical Indian Ocean is expected to change considerably. These changes have the potential to affect the Indian Ocean Dipole, currently characterized by an alternation of anomalous cooling in the eastern tropical Indian Ocean and warming in the west in a positive dipole event, and the reverse pattern for negative events. The amplitude of positive events is generally greater than that of negative events. Mean climate warming in austral spring is expected to lead to stronger easterly winds just south of the Equator, faster warming of sea surface temperatures in the western Indian Ocean compared with the eastern basin, and a shoaling equatorial thermocline. The mean climate conditions that result from these changes more closely resemble a positive dipole state. However, defined relative to the mean state at any given time, the overall frequency of events is not projected to change — but we expect a reduction in the difference in amplitude between positive and negative dipole events.”
Cai, W., Zheng, X., Weller, E. et al. Projected response of the Indian Ocean Dipole to greenhouse warming. Nature Geosci 6, 999–1007 (2013) doi:10.1038/ngeo2009. [FULL TEXT]

Indian Ocean Dipole Response to Global Warming in the CMIP5 Multimodel Ensemble – Zheng et al. (2013)
“The response of the Indian Ocean dipole (IOD) mode to global warming is investigated based on simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). In response to increased greenhouse gases, an IOD-like warming pattern appears in the equatorial Indian Ocean, with reduced (enhanced) warming in the east (west), an easterly wind trend, and thermocline shoaling in the east. Despite a shoaling thermocline and strengthened thermocline feedback in the eastern equatorial Indian Ocean, the interannual variance of the IOD mode remains largely unchanged in sea surface temperature (SST) as atmospheric feedback and zonal wind variance weaken under global warming. The negative skewness in eastern Indian Ocean SST is reduced as a result of the shoaling thermocline. The change in interannual IOD variance exhibits some variability among models, and this intermodel variability is correlated with the change in thermocline feedback. The results herein illustrate that mean state changes modulate interannual modes, and suggest that recent changes in the IOD mode are likely due to natural variations.”
Zheng, X., S. Xie, Y. Du, L. Liu, G. Huang, and Q. Liu, 2013: Indian Ocean Dipole Response to Global Warming in the CMIP5 Multimodel Ensemble. J. Climate, 26, 6067–6080, https://doi.org/10.1175/JCLI-D-12-00638.1. [FULL TEXT]

Indian Ocean Dipole Response to Global Warming: Analysis of Ocean–Atmospheric Feedbacks in a Coupled Model – Zheng et al. (2010)
“Low-frequency modulation and change under global warming of the Indian Ocean dipole (IOD) mode are investigated with a pair of multicentury integrations of a coupled ocean–atmosphere general circulation model: one under constant climate forcing and one forced by increasing greenhouse gas concentrations. In the unforced simulation, there is significant decadal and multidecadal modulation of the IOD variance. The mean thermocline depth in the eastern equatorial Indian Ocean (EEIO) is important for the slow modulation, skewness, and ENSO correlation of the IOD. With a shoaling (deepening) of the EEIO thermocline, the thermocline feedback strengthens, and this leads to an increase in IOD variance, a reduction of the negative skewness of the IOD, and a weakening of the IOD–ENSO correlation. In response to increasing greenhouse gases, a weakening of the Walker circulation leads to easterly wind anomalies in the equatorial Indian Ocean; the oceanic response to weakened circulation is a thermocline shoaling in the EEIO. Under greenhouse forcing, the thermocline feedback intensifies, but surprisingly IOD variance does not. The zonal wind anomalies associated with IOD are found to weaken, likely due to increased static stability of the troposphere from global warming. Linear model experiments confirm this stability effect to reduce circulation response to a sea surface temperature dipole. The opposing changes in thermocline and atmospheric feedbacks result in little change in IOD variance, but the shoaling thermocline weakens IOD skewness. Little change under global warming in IOD variance in the model suggests that the apparent intensification of IOD activity during recent decades is likely part of natural, chaotic modulation of the ocean–atmosphere system or the response to nongreenhouse gas radiative changes.”
Zheng, X., S. Xie, G.A. Vecchi, Q. Liu, and J. Hafner, 2010: Indian Ocean Dipole Response to Global Warming: Analysis of Ocean–Atmospheric Feedbacks in a Coupled Model. J. Climate, 23, 1240–1253, https://doi.org/10.1175/2009JCLI3326.1. [FULL TEXT]

Recent unprecedented skewness towards positive Indian Ocean Dipole occurrences and its impact on Australian rainfall – Cai et al. (2009)
“Is the recent high frequency of positive Indian Ocean Dipole (pIOD) events a consequence of global warming? Using available observations and reanalyses, we show that the pIOD occurrences increase from about four per 30 years early in the 20th century to about 10 over the last 30 years; by contrast, the number of negative Indian Ocean Dipole (nIOD) events decreases from about 10 to two over the same periods, respectively. A skewness measure, defined as the difference in occurrences of pIODs and nIODs, illustrates a systematic trend in this parameter commencing early in the 20th century. After 1950, there are more pIODs than nIODs, with consistent mean circulation changes in the pIOD‐prevalent seasons. Over southeastern Australia (SEA), these changes potentially account for much of the observed austral winter and spring rainfall reduction since 1950. These features are consistent with projected future climate change and hence with what is expected from global warming.”
Cai, W., Cowan, T., and Sullivan, A. ( 2009), Recent unprecedented skewness towards positive Indian Ocean Dipole occurrences and its impact on Australian rainfall, Geophys. Res. Lett., 36, L11705, doi:10.1029/2009GL037604. [FULL TEXT]

Climate change contributes to more frequent consecutive positive Indian Ocean Dipole events – Cai et al. (2009)
“Are the 2006–2008 three‐consecutive positive Indian Ocean Dipole (pIOD) events linked to climate change? Using 20th century experiments submitted for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), we show that a 19‐model average IOD index over the 1950–1999 period yields an upward trend. The associated circulation trends provide a favourable environment for pIOD development, leading to a 17% increase in pIOD frequency compared with the case in which trends are removed. The majority of the increase manifests as a frequency increase in the two‐ and three‐consecutive events. The circulation trends are in turn consistent with wind changes associated with a weaker Walker circulation in the Pacific and an enhanced land‐sea temperature contrast in the Indian Ocean (IO) sector. Our results suggest that although it is difficult to attribute the trigger of the recent consecutive pIODs, climate change is increasing the occurrences of such events.”
Cai, W., Sullivan, A., and Cowan, T. ( 2009), Climate change contributes to more frequent consecutive positive Indian Ocean Dipole events, Geophys. Res. Lett., 36, L23704, doi:10.1029/2009GL040163. [FULL TEXT]

Recent intensification of tropical climate variability in the Indian Ocean – Abram et al. (2008)
“The interplay of the El Niño Southern Oscillation, Asian monsoon and Indian Ocean Dipole (IOD) drives climatic extremes in and around the Indian Ocean. Historical and proxy records reveal changes in the behaviour of the El Niño Southern Oscillation and the Asian monsoon over recent decades. However, reliable instrumental records of the IOD cover only the past 50 years, and there is no consensus on long-term variability of the IOD or its possible response to greenhouse gas forcing. Here we use a suite of coral oxygen-isotope records to reconstruct a basin-wide index of IOD behaviour since AD 1846. Our record reveals an increase in the frequency and strength of IOD events during the twentieth century, which is associated with enhanced seasonal upwelling in the eastern Indian Ocean. Although the El Niño Southern Oscillation has historically influenced the variability of both the IOD and the Asian monsoon, we find that the recent intensification of the IOD coincides with the development of direct, positive IOD–monsoon feedbacks. We suggest that projected greenhouse warming may lead to a redistribution of rainfall across the Indian Ocean and a growing interdependence between the IOD and Asian monsoon precipitation variability.”
Abram, N., Gagan, M., Cole, J. et al. Recent intensification of tropical climate variability in the Indian Ocean. Nature Geosci 1, 849–853 (2008) doi:10.1038/ngeo357. [FULL TEXT]

GCM simulations of the Indian Ocean dipole influence on East African rainfall: Present and future – Conway et al. (2007)
“Six coupled GCMs are assessed in terms of their ability to simulate observed characteristics of East African rainfall, the Indian Ocean dipole and their temporal correlation. Model results are then used to analyze the future behaviour of rainfall and the DMI. All models simulate reasonably well the spatial distribution and variability of annual and seasonal rainfall over the 1961–1990 period. Model simulation of observed DMI characteristics is less consistent with observations, however, five models reproduce similar correlations to those observed between the DMI and East African short rains (SON). In the future, there are no clear inter‐model patterns of rainfall or DMI behaviour. In this sample of models four (two) out of six simulate modest increases (decreases) in annual rainfall by the 2080s. For SON, three of the six models indicate a trend towards increasingly positive phase of the DMI, two indicate a decrease and one shows no substantial change.”
Conway, D., Hanson, C. E., Doherty, R., and Persechino, A. ( 2007), GCM simulations of the Indian Ocean dipole influence on East African rainfall: Present and future, Geophys. Res. Lett., 34, L03705, doi:10.1029/2006GL027597. [FULL TEXT]

Papers on Australia wildfires and climate change

This is a list of papers on Australia wildfires and climate change. The list is not complete, and will most likely be updated in future in order to make it more thorough and more representative.

UPDATE (January 10, 2020): Cai et al. (2009) added.

Climate change effects on the frequency, seasonality and interannual variability of suitable prescribed burning weather conditions in south-eastern Australia – Clarke et al. (2019)
“Despite the importance of prescribed burning in contemporary fire management, there is little understanding of how climate change will influence the weather conditions under which it is deployed. We provide quantitative estimates of potential changes in the number of prescribed burning days in coastal NSW in south-eastern Australia, a fire-prone area dominated by dry sclerophyll forests. Burning days are calculated from an objectively designed regional climate model ensemble using three definitions of suitable weather conditions based on: a literature search (Literature), actual weather observed during recorded prescribed burns (Observed) and operational guidelines (Operational). Contrary to some claims, evidence for a decrease in prescribed burning days under projected future climates is weak. We found a complex pattern of changes, with the potential for substantial and widespread increases in the current burning seasons of autumn (March-May) and spring (August-October). Projected changes were particularly uncertain in northern NSW, spanning substantial increases and decreases during autumn. The magnitude of projected changes in the frequency of burning days was highly sensitive to which definition of suitable weather conditions was used, with a relatively small change for the Operational definition (+0.3 to +1.9 days per year across the study area) and larger ranges for the Observed (+0.2 to +7.9 days) and Literature (+1.7 to +6.2 days) definitions. Interannual variability in the number of burning days is projected to increase slightly under projected climate change. Our study highlights the need for a better understanding of the weather conditions required for safe and effective prescribed burning. Our analysis provides practitioners with quantitative information to assess their exposure to a range of potential changes in the frequency, seasonality and variability of prescribed burning weather conditions.”
Hamish Clarke, Bruce Tran, Matthias M. Boer, Owen Price, Belinda Kenny, Ross Bradstock (2019). Agricultural and Forest Meteorology 271(15):148-157. doi:https://doi.org/10.1016/j.agrformet.2019.03.005.

Future changes in extreme weather and pyroconvection risk factors for Australian wildfires – Dowdy et al. (2019)
“Extreme wildfires have recently caused disastrous impacts in Australia and other regions of the world, including events with strong convective processes in their plumes (i.e., strong pyroconvection). Dangerous wildfire events such as these could potentially be influenced by anthropogenic climate change, however, there are large knowledge gaps on how these events might change in the future. The McArthur Forest Fire Danger Index (FFDI) is used to represent near-surface weather conditions and the Continuous Haines index (CH) is used here to represent lower to mid-tropospheric vertical atmospheric stability and humidity measures relevant to dangerous wildfires and pyroconvective processes. Projected changes in extreme measures of CH and FFDI are examined using a multi-method approach, including an ensemble of global climate models together with two ensembles of regional climate models. The projections show a clear trend towards more dangerous near-surface fire weather conditions for Australia based on the FFDI, as well as increased pyroconvection risk factors for some regions of southern Australia based on the CH. These results have implications for fields such as disaster risk reduction, climate adaptation, ecology, policy and planning, noting that improved knowledge on how climate change can influence extreme wildfires can help reduce future impacts of these events.”
Andrew J. Dowdy, Hua Ye, Acacia Pepler, Marcus Thatcher, Stacey L. Osbrough, Jason P. Evans, Giovanni Di Virgilio & Nicholas McCarthy (2019). Scientific Reports 9:10073. doi:10.1038/s41598-019-46362-x. [FULL TEXT]

Exploring the future change space for fire weather in southeast Australia – Clarke & Evans (2019)
“High-resolution projections of climate change impacts on fire weather conditions in southeast Australia out to 2080 are presented. Fire weather is represented by the McArthur Forest Fire Danger Index (FFDI), calculated from an objectively designed regional climate model ensemble. Changes in annual cumulative FFDI vary widely, from − 337 (− 21%) to + 657 (+ 24%) in coastal areas and − 237 (− 12%) to + 1143 (+ 26%) in inland areas. A similar spread is projected in extreme FFDI values. In coastal regions, the number of prescribed burning days is projected to change from − 11 to + 10 in autumn and − 10 to + 3 in spring. Across the ensemble, the most significant increases in fire weather and decreases in prescribed burn windows are projected to take place in spring. Partial bias correction of FFDI leads to similar projections but with a greater spread, particularly in extreme values. The partially bias-corrected FFDI performs similarly to uncorrected FFDI compared to the observed annual cumulative FFDI (ensemble root mean square error spans 540 to 1583 for uncorrected output and 695 to 1398 for corrected) but is generally worse for FFDI values above 50. This emphasizes the need to consider inter-variable relationships when bias-correcting for complex phenomena such as fire weather. There is considerable uncertainty in the future trajectory of fire weather in southeast Australia, including the potential for less prescribed burning days and substantially greater fire danger in spring. Selecting climate models on the basis of multiple criteria can lead to more informative projections and allow an explicit exploration of uncertainty.”
Clarke, H. & Evans, J.P. Theor Appl Climatol (2019) 136: 513. https://doi.org/10.1007/s00704-018-2507-4. [FULL TEXT]

On Determining the Impact of Increasing Atmospheric CO2 on the Record Fire Weather in Eastern Australia in February 2017 – Hope et al. (2019)
“February 2017 saw a broad region with record fire weather across central-eastern Australia. A hybrid attribution technique using modified observations and a seasonal forecast framework did not give a clear signal as to the influence of increasing atmospheric CO2 on the fire weather.”
Pandora Hope, Mitchell T. Black, Eun-Pa Lim, Andrew Dowdy, Guomin Wang, Acacia S. Pepler, and Robert J. B. Fawcett (2019). Bulletin of the American Meteorological Society, vol. 100, issue 1, pp. S111-S117. doi:10.1175/BAMS-D-18-0135.1. [FULL TEXT]

Climatological Variability of Fire Weather in Australia – Dowdy (2018)
“Long-term variations in fire weather conditions are examined throughout Australia from gridded daily data from 1950 to 2016. The McArthur forest fire danger index is used to represent fire weather conditions throughout this 67-yr period, calculated on the basis of a gridded analysis of observations over this time period. This is a complementary approach to previous studies (e.g., those based primarily on model output, reanalysis, or individual station locations), providing a spatially continuous and long-term observations-based dataset to expand on previous research and produce climatological guidance information for planning agencies. Long-term changes in fire weather conditions are apparent in many regions. In particular, there is a clear trend toward more dangerous conditions during spring and summer in southern Australia, including increased frequency and magnitude of extremes, as well as indicating an earlier start to the fire season. Changes in fire weather conditions are attributable at least in part to anthropogenic climate change, including in relation to increasing temperatures. The influence of El Niño–Southern Oscillation (ENSO) on fire weather conditions is found to be broadly consistent with previous studies (indicating more severe fire weather in general for El Niño conditions than for La Niña conditions), but it is demonstrated that this relationship is highly variable (depending on season and region) and that there is considerable potential in almost all regions of Australia for long-range prediction of fire weather (e.g., multiweek and seasonal forecasting). It is intended that improved understanding of the climatological variability of fire weather conditions will help lead to better preparedness for risks associated with dangerous wildfires in Australia.”
Dowdy, A.J., 2018: Climatological Variability of Fire Weather in Australia. J. Appl. Meteor. Climatol., 57, 221–234, https://doi.org/10.1175/JAMC-D-17-0167.1. [FULL TEXT]

Pyroconvection Risk in Australia: Climatological Changes in Atmospheric Stability and Surface Fire Weather Conditions – Dowdy & Pepler (2018)
“Extreme wildfires with strong convective processes in their plumes have recently led to disastrous impacts on various regions of the world. The Continuous Haines index (CH) is used in Australia to represent vertical atmospheric stability and humidity measures relating to pyroconvective processes. CH climatology is examined here using reanalysis data from 1979 to 2016, revealing large spatial and seasonal variations throughout Australia. Various measures of severity are investigated, including regionally specific thresholds. CH is combined with near‐surface fire weather conditions, as a type of compound event, and is examined in relation to environmental conditions associated with pyroconvection. Significant long‐term changes in CH are found for some regions and seasons, with these changes corresponding to changes in near‐surface conditions in some cases. In particular, an increased risk of pyroconvection is identified for southeast Australia during spring and summer, due to decreased vertical atmospheric stability and humidity combined with more severe near‐surface conditions.”
Dowdy, A. J., & Pepler, A. ( 2018). Pyroconvection risk in Australia: Climatological changes in atmospheric stability and surface fire weather conditions. Geophysical Research Letters, 45, 2005– 2013. https://doi.org/10.1002/2017GL076654. [FULL TEXT]

Fire frequency analysis for different climatic stations in Victoria, Australia – Khastagir (2018)
“Frequent occurrence of fire events will have severe impact on Victoria’s water supply catchments. Hence, it is important to perform fire frequency analysis to obtain fire frequency curves (FFC) on fire intensity using Forest Fire Danger Index (FFDI) at different parts of Victoria. FFDI is a measure of fire initiation, spreading speed and containment difficulty. FFC will guide water harvesting by providing information with regard to future fire events and the subsequent impact on catchment yield. Five probability distributions, namely normal, Log Pearson Type III (LPIII), gamma, log-normal and Weibull distributions were used for the development of FFCs at ten selected meteorological stations spread all over Victoria. LPIII distribution was identified as the best fit distribution for Victoria and subsequently applied for an additional 30 more stations to show spatial variability for the entire Victoria.”
Anirban Khastagir (2018). Natural Hazards volume 93, pages 787–802. doi:https://doi.org/10.1007/s11069-018-3324-x.

Fanning the Blame: Media Accountability, Climate and Crisis on the Australian “Fire Continent” – Anderson et al. (2018)
“This paper raises questions of media coverage of “compounded crises” related to extreme weather disaster, in the context of urgent calls to address the implications of a changing climate. Through media analysis, it examines the ways debate over bushfire protection policy was framed and made culturally meaningful, thereby politically consequential, in the wake of the worst bushfires in modern Australian history, Black Saturday (2009). The fires, in which 173 people died, led to a Royal Commission and fierce debate over the use of prescribed burning to reduce bushfire hazard. Longitudinal analysis of local, state and national mainstream media coverage (2009–2016) reveals blame games that targeted environmentalists and the government, which near-silenced meaningful discussion of the complexity of fire science, impacts of climate change on weather conditions, and calls for adaptation. By exploring the media’s constitutive role in crisis response, the paper highlights the legacy and potency of ideological conflict that shapes the media-policy nexus in Australia.”
Deb Anderson, Philip Chubb & Monika Djerf-Pierre (2018) Fanning the Blame: Media Accountability, Climate and Crisis on the Australian “Fire Continent”, Environmental Communication, 12:7, 928-941, DOI: 10.1080/17524032.2018.1424008. [FULL TEXT]

Big data integration shows Australian bush-fire frequency is increasing significantly – Dutta et al. (2016)
“Increasing Australian bush-fire frequencies over the last decade has indicated a major climatic change in coming future. Understanding such climatic change for Australian bush-fire is limited and there is an urgent need of scientific research, which is capable enough to contribute to Australian society. Frequency of bush-fire carries information on spatial, temporal and climatic aspects of bush-fire events and provides contextual information to model various climate data for accurately predicting future bush-fire hot spots. In this study, we develop an ensemble method based on a two-layered machine learning model to establish relationship between fire incidence and climatic data. In a 336 week data trial, we demonstrate that the model provides highly accurate bush-fire incidence hot-spot estimation (91% global accuracy) from the weekly climatic surfaces. Our analysis also indicates that Australian weekly bush-fire frequencies increased by 40% over the last 5 years, particularly during summer months, implicating a serious climatic shift.”
Ritaban Dutta, Aruneema Das and Jagannath Aryal (2016). Royal Society Open Science 3(2). doi:https://doi.org/10.1098/rsos.150241. [FULL TEXT]

Natural hazards in Australia: extreme bushfire – Sharples et al. (2016)
“Bushfires are one of the most frequent natural hazards experienced in Australia. Fires play an important role in shaping the landscape and its ecological dynamics, but may also have devastating effects that cause human injuries and fatalities, as well as broad-scale environmental damage. While there has been considerable effort to quantify changes in the occurrence of bushfire in Australia, a comprehensive assessment of the most extreme bushfire cases, which exact the greatest economic and environmental impacts, is lacking. In this paper we reflect upon recently developed understanding of bushfire dynamics to consider (i) historical changes in the occurrence of extreme bushfires, and (ii) the potential for increasing frequency in the future under climate change projections. The science of extreme bushfires is still a developing area, thus our conclusions about emerging patterns in their occurrence should be considered tentative. Nonetheless, historical information on noteworthy bushfire events suggests an increased occurrence in recent decades. Based on our best current understanding of how extreme bushfires develop, there is strong potential for them to increase in frequency in the future. As such there is a pressing need for a greater understanding of these powerful and often destructive phenomena.”
Sharples, J.J., Cary, G.J., Fox-Hughes, P. et al. Climatic Change (2016) 139: 85. https://doi.org/10.1007/s10584-016-1811-1. [FULL TEXT]

ENSO controls interannual fire activity in southeast Australia – Mariani et al. (2016)
“El Niño–Southern Oscillation (ENSO) is the main mode controlling the variability in the ocean‐atmosphere system in the South Pacific. While the ENSO influence on rainfall regimes in the South Pacific is well documented, its role in driving spatiotemporal trends in fire activity in this region has not been rigorously investigated. This is particularly the case for the highly flammable and densely populated southeast Australian sector, where ENSO is a major control over climatic variability. Here we conduct the first region‐wide analysis of how ENSO controls fire activity in southeast Australia. We identify a significant relationship between ENSO and both fire frequency and area burnt. Critically, wavelet analyses reveal that despite substantial temporal variability in the ENSO system, ENSO exerts a persistent and significant influence on southeast Australian fire activity. Our analysis has direct application for developing robust predictive capacity for the increasingly important efforts at fire management.”
Mariani, M., Fletcher, M.‐S., Holz, A., and Nyman, P. ( 2016), ENSO controls interannual fire activity in southeast Australia, Geophys. Res. Lett., 43, 10,891– 10,900, doi:10.1002/2016GL070572. [FULL TEXT]

People, El Niño southern oscillation and fire in Australia: fire regimes and climate controls in hummock grasslands – Bird et al. (2016)
“While evidence mounts that indigenous burning has a significant role in shaping pyrodiversity, the processes explaining its variation across local and external biophysical systems remain limited. This is especially the case with studies of climate–fire interactions, which only recognize an effect of humans on the fire regime when they act independently of climate. In this paper, we test the hypothesis that an anthropogenic fire regime (fire incidence, size and extent) does not covary with climate. In the lightning regime, positive El Niño southern oscillation (ENSO) values increase lightning fire incidence, whereas La Niña (and associated increases in prior rainfall) increase fire size. ENSO has the opposite effect in the Martu regime, decreasing ignitions in El Niño conditions without affecting fire size. Anthropogenic ignition rates covary positively with high antecedent rainfall, whereas fire size varies only with high temperatures and unpredictable winds, which may reduce control over fire spread. However, total area burned is similarly predicted by antecedent rainfall in both regimes, but is driven by increases in fire size in the lightning regime, and fire number in the anthropogenic regime. We conclude that anthropogenic regimes covary with climatic variation, but detecting the human–climate–fire interaction requires multiple measures of both fire regime and climate.”
Bliege Bird Rebecca, Bird Douglas W. and Codding Brian F. People, El Niño southern oscillation and fire in Australia: fire regimes and climate controls in hummock grasslands. Phil. Trans. R. Soc. B. 371(1696). doi:https://doi.org/10.1098/rstb.2015.0343. [FULL TEXT]

Responses of resilience traits to gradients of temperature, rainfall and fire frequency in fire-prone, Australian forests: potential consequences of climate change – Hammill et al. (2016)
“The composition of plant communities may be driven by responses of key plant resilience traits (resprouting R+, non-resprouting R−, persistent P+ and transient P− seedbanks) to either resource competition or disturbance regimes. We explored responses of overall species richness and the richness of herbs and shrubs within the three most common functional types (i.e. facultative resprouters R+P+, obligate resprouters R+P−, obligate seeders R−P+) to orthogonal combinations of temperature (MAT), rainfall (MAP) and fire frequency (FF) in Dry Sclerophyll Forest in the Sydney basin (south-eastern Australia). R+ and P+ species were predominant (>72 % of total species). Overall richness was a significant positive function of MAT, MAP and FF. Positive relationships between species richness and MAP, MAT and FF occurred across all trait and functional type groups, with MAP being the most influential and FF the least. Responses of proportions of species within trait- and functional-type groups were complex. Proportion of R+ species was negatively related to MAT and MAP, but species-rich herb and shrub R+P+ proportions were positively and negatively related to MAT, respectively. The herb R+P+ proportion was negatively related to FF. The results were inconsistent with the disturbance frequency and resource competition models of resilience variation. Rises in MAT under climate change have the potential not only to increase overall species plus richness across all trait groups but also to diminish shrubs relative to herbs in the key R+P+ functional types. Such a scenario is highly uncertain given the variability in future MAP projections for the region.”
Hammill, K., Penman, T. & Bradstock, R. Plant Ecol (2016) 217: 725. https://doi.org/10.1007/s11258-016-0578-9.

Divergent responses of fire to recent warming and drying across south‐eastern Australia – Bradstock et al. (2014)
“The response of fire to climate change may vary across fuel types characteristic of differing vegetation types (i.e. litter vs. grass). Models of fire under climatic change capture these differing potential responses to varying degrees. Across south‐eastern Australia, an elevation in the severity of weather conditions conducive to fire has been measured in recent decades. We examined trends in area burned (1975–2009) to determine if a corresponding increase in fire had occurred across the diverse range of ecosystems found in this part of the continent. We predicted that an increase in fire, due to climatic warming and drying, was more likely to have occurred in moist, temperate forests near the coast than in arid and semiarid woodlands of the interior, due to inherent contrasts in the respective dominant fuel types (woody litter vs. herbaceous fuels). Significant warming (i.e. increased temperature and number of hot days) and drying (i.e. negative precipitation anomaly, number of days with low humidity) occurred across most of the 32 Bioregions examined. The results were mostly consistent with predictions, with an increase in area burned in seven of eight forest Bioregions, whereas area burned either declined (two) or did not change significantly (nine) in drier woodland Bioregions. In 12 woodland Bioregions, data were insufficient for analysis of temporal trends in fire. Increases in fire attributable mostly to warming or drying were confined to three Bioregions. In the remainder, such increases were mostly unrelated to warming or drying trends and therefore may be due to other climate effects not explored (e.g. lightning ignitions) or possible anthropogenic influences. Projections of future fire must therefore not only account for responses of different fuel systems to climatic change but also the wider range of ecological and human effects on interactions between fire and vegetation.”
Bradstock, R., Penman, T., Boer, M., Price, O. and Clarke, H. (2014), Divergent responses of fire to recent warming and drying across south‐eastern Australia. Glob Change Biol, 20: 1412-1428. doi:10.1111/gcb.12449.

Changes in Australian fire weather between 1973 and 2010 – Clarke et al. (2013)
“A data set of observed fire weather in Australia from 1973–2010 is analysed for trends using the McArthur Forest Fire Danger Index (FFDI). Annual cumulative FFDI, which integrates daily fire weather across the year, increased significantly at 16 of 38 stations. Annual 90th percentile FFDI increased significantly at 24 stations over the same period. None of the stations examined recorded a significant decrease in FFDI. There is an overall bias in the number of significant increases towards the southeast of the continent, while the largest trends occur in the interior of the continent and the smallest occur near the coast. The largest increases in seasonal FFDI occurred during spring and autumn, although with different spatial patterns, while summer recorded the fewest significant trends. These trends suggest increased fire weather conditions at many locations across Australia, due to both increased magnitude of FFDI and a lengthened fire season. Although these trends are consistent with projected impacts of climate change on FFDI, this study cannot separate the influence of climate change, if any, with that of natural variability.”
Clarke, H., Lucas, C. and Smith, P. (2013), Changes in Australian fire weather between 1973 and 2010. Int. J. Climatol., 33: 931-944. doi:10.1002/joc.3480. [FULL TEXT]

Fire and carbon dynamics under climate change in south-eastern Australia: insights from FullCAM and FIRESCAPE modelling – King et al. (2011)
“This study used simulation modelling to investigate fire and carbon dynamics for projected warmer and drier climates in the south-eastern Australian high country. A carbon accounting model FullCAM and the landscape fire regime simulator FIRESCAPE were combined and used to simulate several fire management options under three climate scenarios – the recent climate (1975–2005); a moderate climate projected for 2070 (B1); and a more extreme climate projected for 2070 (A1FI). For warmer and drier climates, model simulations predicted (i) an increase in fire incidence; (ii) larger areas burned; (iii) higher mean fire intensities; (iv) shorter fire cycle lengths; (v) a greater proportion of fires burning earlier in the fire season; (vi) a reduction in carbon stores; (vii) a reduction in carbon sequestration rates; and (viii) an increase in the proportion of stored carbon emitted to the atmosphere. Prescribed burning at historical or twice historical levels had no effect on fire or carbon dynamics. In contrast, increasing the initial attack success (a surrogate for suppression) partially offset the adverse effects of warmer and drier climates on fire activity, but not on carbon dynamics. For the south-eastern Australian high country, simulations indicated that fire and carbon dynamics are sensitive to climate change, with simulated fire management only being able to partially offset the adverse effects of warmer and drier climate.”
King Karen J., de Ligt Robert M., Cary Geoffrey J. (2011) Fire and carbon dynamics under climate change in south-eastern Australia: insights from FullCAM and FIRESCAPE modelling. International Journal of Wildland Fire 20, 563-577. doi:https://doi.org/10.1071/WF09073.

Assessing the impact of climate change on extreme fire weather events over southeastern Australia – Hasson et al. (2009)
“Extreme fire weather events in southeastern Australia are frequently associated with strong cold fronts moving through the area. A recent study has shown that the 850 hPa temperature and the magnitude of its gradient over a small region of southeastern Australia provide a simple means of discriminating the most extreme cold frontal events during the last 40 yr from reanalysis data sets. Applying this technique to 10 general circulation models (GCMs) from the Coupled Model Intercomparison Project and calibrating the temperature gradient and temperature climatology of each model’s simulation of the climate of the 20th century against the reanalysis climates allows estimates of likely changes in frequency of this type of extreme cold front in the middle and end of the 21st century. Applying this analysis to the output of 10 GCM simulations of the 21st century, using low and high greenhouse gas emissions scenarios, suggests that the frequency of such events will increase from around 1 event every 2 yr during the late 20th century to around 1 event per year in the middle of the 21st century and 1 to 2 events per year by the end of the 21st century; however, there is a great degree of variation between models. In addition to a greater overall increase under the high emissions scenario, the rate at which the increase occurs amplifies during the second half of the century, whereas under the low emissions scenario the number of extreme cases stabilizes, although still at a higher rate than that experienced in the late 20th century.”
Hasson AEA, Mills GA, Timbal B, Walsh K (2009) Assessing the impact of climate change on extreme fire weather events over southeastern Australia. Clim Res 39:159-172. https://doi.org/10.3354/cr00817. [FULL TEXT]

Positive Indian Ocean Dipole events precondition southeast Australia bushfires – Cai et al. (2009)
“The devastating “Black Saturday” bushfire inferno in the southeast Australian state of Victoria in early February 2009 and the “Ash Wednesday” bushfires in February 1983 were both preceded by a positive Indian Ocean Dipole (pIOD) event. Is there a systematic pIOD linkage beyond these two natural disasters? We show that out of 21 significant bushfires seasons since 1950, 11 were preceded by a pIOD. During Victoria’s wet season, particularly spring, a pIOD contributes to lower rainfall and higher temperatures exacerbating the dry conditions and increasing the fuel load leading into summer. Consequently, pIODs are effective in preconditioning Victoria for bushfires, more so than El Niño events, as seen in the impact on soil moisture on interannual time scales and in multi‐decadal changes since the 1950s. Given that the recent increase in pIOD occurrences is consistent with what is expected from global warming, an increased bushfire risk in the future is likely across southeast Australia.”
Cai, W., Cowan, T., and Raupach, M. ( 2009), Positive Indian Ocean Dipole events precondition southeast Australia bushfires, Geophys. Res. Lett., 36, L19710, doi:10.1029/2009GL039902. [FULL TEXT]

The impact of climate change on the risk of forest and grassland fires in Australia – Pitman et al. (2007)
“We explore the impact of future climate change on the risk of forest and grassland fires over Australia in January using a high resolution regional climate model, driven at the boundaries by data from a transitory coupled climate model. Two future emission scenarios (relatively high and relatively low) are used for 2050 and 2100 and four realizations for each time period and each emission scenario are run. Results show a consistent increase in regional-scale fire risk over Australia driven principally by warming and reductions in relative humidity in all simulations, under all emission scenarios and at all time periods. We calculate the probability density function for the fire risk for a single point in New South Wales and show that the probability of extreme fire risk increases by around 25% compared to the present day in 2050 under both relatively low and relatively high emissions, and that this increases by a further 20% under the relatively low emission scenario by 2100. The increase in the probability of extreme fire risk increases dramatically under the high emission scenario by 2100. Our results are broadly in-line with earlier analyses despite our use of a significantly different methodology and we therefore conclude that the likelihood of a significant increase in fire risk over Australia resulting from climate change is very high. While there is already substantial investment in fire-related management in Australia, our results indicate that this investment is likely to have to increase to maintain the present fire-related losses in Australia.”
Pitman, A.J., Narisma, G.T. & McAneney, J. The impact of climate change on the risk of forest and grassland fires in Australia. Climatic Change 84, 383–401 (2007) doi:10.1007/s10584-007-9243-6. [FULL TEXT]

The Sensitivity of Australian Fire Danger to Climate Change – Williams et al. (2001)
“Global climate change, such as that due to the proposed enhanced greenhouse effect, is likely to have a significant effect on biosphere-atmosphere interactions, including bushfire regimes. This study quantifies the possible impact of climate change on fire regimes by estimating changes in fire weather and the McArthur Forest Fire Danger Index (FDI), an index that is used throughout Australia to estimate fire danger. The CSIRO 9-level general circulation model(CSIRO9 GCM)is used to simulate daily and seasonal fire danger for the present Australian climate and for a doubled-CO2 climate. The impact assessment includes validation of the GCMs daily control simulation and the derivation of ‘correction factors’ which improve the accuracy of the fire danger simulation. In summary, the general impact of doubled-CO2 is to increase fire danger at all sites by increasing the number of days of very high and extreme fire danger.Seasonal fire danger responds most to the large CO2-induced changes in maximum temperature.”
Williams, A.A.J., Karoly, D.J. & Tapper, N. Climatic Change (2001) 49: 171. https://doi.org/10.1023/A:1010706116176. [FULL TEXT]

Fire Regime Sensitivity to Global Climate Change: An Australian Perspective – Cary & Banks (2000)
“The Australian eucalypt forests are highly adapted to fire, and their component species possess well-developed response mechanisms that ensure post-fire recovery of these ecosystems. Fire regimes, which may alter forest floristics and structure, have changed since pre-European times because of management practices and may again change because of a changing climate. Two complimentary approaches are used to determine spatial and temporal patterns of fire regimes, a) dendrochronology to determine pre- and post-European fire histories for specific sites and b) fire-climate-landscape modelling to predict spatial patterns in fire regimes for topographically complex landscapes. This paper brings together these two approaches which have been applied independently to the same forest in the Southern Tablelands of New South Wales. The model predictions of spatial patterns in fire regimes under the present climate provide reasonable results when compared with observed site fire histories. Also, model results indicate that around half of the landscape is likely to experience a significant increase in fire frequency as a result of climate change. These findings, which have implications for fire-prone forest environments world-wide, are discussed in relation to the effects that anthropogenic ignition have had on the fire frequency in the study area over the last century.”
Cary G.J., Banks J.C.G. (2000) Fire Regime Sensitivity to Global Climate Change: An Australian Perspective. In: Innes J.L., Beniston M., Verstraete M.M. (eds) Biomass Burning and Its Inter-Relationships with the Climate System. Advances in Global Change Research, vol 3. Springer, Dordrecht.