Michael Grose

Performance of downscaled regional climate simulations using a variable‐resolution regional climate model: Tasmania as a test case

[1] In this study we develop methods for dynamically downscaling output from six general circulation models (GCMs) for two emissions scenarios using a variable-resolution atmospheric climate model. The use of multiple GCMs and emissions scenarios gives an estimate of model range in projected changes to the mean climate across the region. By modeling the atmosphere at a very fine scale, the simulations capture processes that are important to regional weather and climate at length scales that are subgrid scale for the host GCM. We find that with a multistaged process of increased resolution and the application of bias adjustment methods, the ability of the simulation to reproduce observed conditions improves, with greater than 95% of the spatial variance explained for temperature and about 90% for rainfall. Furthermore, downscaling leads to a significant improvement for the temporal distribution of variables commonly used in applied analyses, reproducing seasonal variability in line with observations. This seasonal signal is not evident in the GCMs. This multistaged approach allows progressive improvement in the skill of the simulations in order to resolve key processes over the region with quantifiable improvements in the correlations with observations.

On regional dynamical downscaling for the assessment and projection of temperature and precipitation extremes across Tasmania, Australia

The ability of an ensemble of six GCMs, downscaled to a 0.1° lat/lon grid using the Conformal Cubic Atmospheric Model over Tasmania, Australia, to simulate observed extreme temperature and precipitation climatologies and statewide trends is assessed for 1961–2009 using a suite of extreme indices. The downscaled simulations have high skill in reproducing extreme temperatures, with the majority of models reproducing the statewide averaged sign and magnitude of recent observed trends of increasing warm days and warm nights and decreasing frost days. The warm spell duration index is however underestimated, while variance is generally overrepresented in the extreme temperature range across most regions. The simulations show a lower level of skill in modelling the amplitude of the extreme precipitation indices such as very wet days, but simulate the observed spatial patterns and variability. In general, simulations of dry extreme precipitation indices are underestimated in dryer areas and wet extremes indices are underestimated in wetter areas. Using two SRES emissions scenarios, the simulations indicate a significant increase in warm nights compared to a slightly more moderate increase in warm days, and an increase in maximum 1- and 5-day precipitation intensities interspersed with longer consecutive dry spells across Tasmania during the twenty-first century.

Future fire danger climatology for Tasmania, Australia, using a dynamically downscaled regional climate model

Daily values of McArthur Forest Fire Danger Index were generated at ~10-km resolution over Tasmania, Australia, from six dynamically downscaled CMIP3 climate models for 1961–2100, using a high (A2) emissions scenario. Multi-model mean fire danger validated well against observations for 2002–2012, with 99th percentile fire dangers having the same distribution and largely similar values to those observed over the same time. Model projections showed a broad increase in fire danger across Tasmania, but with substantial regional variation – the increase was smaller in western Tasmania (district mean cumulative fire danger increasing at 1.07 per year) compared with parts of the east (1.79 per year), for example. There was also noticeable seasonal variation, with little change occurring in autumn, but a steady increase in area subject to springtime 99th percentile fire danger from 6% in 1961–1980 to 21% by 2081–2100, again consistent with observations. In general, annually accumulated fire danger behaved similarly. Regional mean sea level pressure patterns resembled observed patterns often associated with days of dangerous fire weather. Days of elevated fire danger displaying these patterns increased in frequency during the simulated twenty-first century: in south-east Tasmania, for example, the number of such events detected rose from 101 (across all models) in 1961–1980 to 169 by 2081–2100. Correspondence of model output with observations and the regional detail available suggest that these dynamically downscaled model data are useful projections of future fire danger for landscape managers and the community.

A regional response in mean westerly circulation and rainfall to projected climate warming over Tasmania, Australia

Coupled ocean–atmosphere general circulation models (GCMs) lack sufficient resolution to model the regional detail of changes to mean circulation and rainfall with projected climate warming. In this paper, changes in mean circulation and rainfall in GCMs are compared to those in a variable resolution regional climate model, the Conformal Cubic Atmospheric Model (CCAM), under a high greenhouse gas emissions scenario. The study site is Tasmania, Australia, which is positioned within the mid-latitude westerlies of the southern hemisphere. CCAM projects a different response in mean sea level pressure and mid-latitude westerly circulation to climate warming to the GCMs used as input, and shows greater regional detail of the boundaries between regions of increasing and decreasing rainfall. Changes in mean circulation dominate the mean rainfall response in western Tasmania, whereas changes to rainfall in the East Coast are less related to mean circulation changes. CCAM projects an amplification of the dominant westerly circulation over Tasmania and this amplifies the seasonal cycle of wet winters and dry summers in the west. There is a larger change in the strength than in the incidence of westerly circulation and rainfall events. We propose the regional climate model displays a more sensitive atmospheric response to the different rates of warming of land and sea than the GCMs as input. The regional variation in these results highlight the need for dynamical downscaling of coupled general circulation models to finely resolve the influence of mean circulation and boundaries between regions of projected increases and decreases in rainfall.

Changes to the drivers of fire weather with a warming climate – a case study of southeast Tasmania

Projected changes to the global climate system have great implications for the incidence of large infrequent fires in many regions. Here we examine the synoptic-scale and local-scale influences on the incidence of extreme fire weather days and consider projections of the large-scale mean climate to explore future fire weather projections. We focus on a case study region with periodic extreme fire dangers; southeast Tasmania, Australia. We compare the performance of a dynamically downscaled regional climate model with Global Climate Model outputs as a tool for examining the local-scale influences while accounting for high regional variability. Many of the worst fires in Tasmania and the southeast Australian region are associated with deep cold fronts and strong prefrontal winds. The downscaled simulations reproduce this synoptic type with greater fidelity than a typical global climate model. The incidence of systems in this category is projected to increase through the century under a high emission scenario, driven mainly by an increase in the temperature of air masses, with little change in the strength of the systems. The regional climate model projected increase in frequency is smaller than for the global climate models used as input, with a large model range and natural variability. We also demonstrate how a blocking Foehn effect and topographic channelling contributed to the extreme conditions during an extreme fire weather day in Tasmania in January 2013. Effects such as these are likely to contribute to high fire danger throughout the century. Regional climate models are useful tools that enable various meteorological drivers of fire danger to be considered in projections of future fire danger.

Precursors to Particles (P2P) at Cape Grim 2006: Campaign Overview

Environmental context. Understanding the role of clouds in assessing the impact of climate change is a challenging issue. It is thought that plankton and seaweed contribute to the formation of clouds by emitting gases that lead to the particle production necessary for cloud formation. Macroalgae (kelp) at Mace Head, Ireland, produce large quantities of iodine when exposed to sunlight at low tide and this iodine results in the rapid production of particles. Cape Grim, Tasmania, also has large colonies of kelp and the role of Bull Kelp (Durvillaea potatorum) in particle production was assessed. Abstract. Iodine emissions from coastal macroalgae have been found to be important initiators for nucleation events at Mace Head, Ireland. The source of this iodine is the large beds of the brown kelp Laminaria digitata, which are significantly exposed at low tide. On the coast around Cape Grim, Tasmania, there are beds of the brown kelp Durvillaea potatrum. The Precursors to Particles 2006 (P2P 2006) campaign at the Cape Grim Baseline Air Pollution Station in late summer (February) 2006 focused on the role of this local kelp in providing precursor gases to particle formation. Durvillaea potatorum does not produce iodated precursor gases at the levels observed at Mace Head. IO was measured at 0.5 ± 0.3 ppt, while OIO was below detection limits (9 ppt). The dominant atmospheric iodated species was methyl iodide and the average concentration measured at the Cape Grim Station was 1.5 ± 0.3 pptv in baseline conditions, but showed significant variation in discrete samples collected immediately above the ocean surface. Nucleation events were not detected at the Cape Grim Station, except for one period where the plume of a local bushfire interacted with air of marine origin. The passage of four fronts did not result in nucleation bursts and measurements on the beach 94 m below the Cape Grim Station suggested that Durvillaea potatorum was only a weak source of new particles.

Can We Constrain CMIP5 Rainfall Projections in the Tropical Pacific Based on Surface Warming Patterns

AbstractClimate warming has large implications for rainfall patterns, and identifying the most plausible pattern of rainfall change over the next century among various model projections would be valuable for future planning. The spatial pattern of projected sea surface temperature change has a key influence on rainfall changes in the tropical Pacific Ocean. Here it is shown that simple indices of the size of the equatorial peak in the spatial pattern of warming and to a lesser extent the hemispheric asymmetry in warming are useful for classifying the surface temperature change in different models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Models with a more pronounced equatorial warming show a fairly distinct rainfall response compared to those with more uniform warming, including a greater “warmer-get-wetter” or dynamical response, whereby rainfall increases follow the surface warming anomaly. Models with a more uniform warming pattern project a smaller rainfall increase at the eq...

Attribution of Exceptional Mean Sea Level Pressure Anomalies South of Australia in August 2014

August 2014 saw very strong monthly positive mean sea level pressure (MSLP) anomalies and intense daily to multiday MSLP events south of Australia and in the Tasman Sea (Fig. 32.1a). To the west of Tasmania there were monthly anomalies of over 10 hPa (2.4 standard deviations from the mean), the highest on record since 1979 using ERA-Interim reanalysis (ERAint; Dee et al. 2011), or from 1850 using the Hadley Centre Sea Level Pressure analysis (HadSLP2r; Allan and Ansell 2006). Atmospheric blocking west of Tasmania on 10–15 August (Figs. 32.1b,c) featured the highest daily August MSLP anomaly in either record in that location. Blocking was seen in the south Tasman Sea later in the month, including the highest daily MSLP anomaly on record at that location. The spatial distribution of the monthly MSLP anomalies resembles a wave-3 pattern (Fig. 32.1a).

Constraints on Southern Australian Rainfall Change Based on Atmospheric Circulation in CMIP5 Simulations

AbstractAtmospheric circulation change is likely to be the dominant driver of multidecadal rainfall trends in the midlatitudes with climate change this century. This study examines circulation features relevant to southern Australian rainfall in January and July and explores emergent constraints suggested by the intermodel spread and their impact on the resulting rainfall projection in the CMIP5 ensemble. The authors find relationships between models’ bias and projected change for four features in July, each with suggestions for constraining forced change. The features are the strength of the subtropical jet over Australia, the frequency of blocked days in eastern Australia, the longitude of the peak blocking frequency east of Australia, and the latitude of the storm track within the polar front branch of the split jet. Rejecting models where the bias suggests either the direction or magnitude of change in the features is implausible produces a constraint on the projected rainfall reduction for southern A...

The Roles of Climate Change and El Niño in the Record Low Rainfall in October 2015 in Tasmania, Australia

Introduction. The island state of Tasmania, in southeast Australia, received record low average rainfall of 21 mm in October 2015, 17% of the 1961–90 normal (Fig. 25.1a; Bureau of Meteorology 2015). This had major impacts across the state, affecting agriculture and hydroelectric power generation and preconditioning the landscape for major bushfires the following summer (Hobday et al. 2016). Rainfall in Tasmania is normally high throughout the year, with variations in Austral spring associated with mean sea level pressure (MSLP) and circulation variations due to El Niño, the Indian Ocean dipole (IOD), and the southern annular mode (SAM; Hill et al. 2009). Spring rainfall is declining and projected to decrease further in Tasmania (Hope et al. 2015) This record low rainfall was associated with extreme high MSLP over much of southeast Australia (Fig. 25.1b) and record high October mean maximum temperature over southern Australia (Black and Karoly 2016). The wave train pattern of MSLP anomalies in October (Fig. 25.1b) from southern Australia across the South Pacific is typical of the Pacific South American (PSA) pattern (Mo and Higgins 1998). El Niño conditions, such as in late 2015, are associated with a shift in tropical Pacific rainfall and in waveguides in the extratropical Pacific that inf luence the PSA pattern (Karoly 1989) and rainfall in Tasmania. We have investigated the roles of anthropogenic climate change, the 2015/16 El Niño, and internal atmospheric variability on this record low October rainfall using observational data, regional climate simulat ions driven by speci f ied sea surface temperatures (SSTs) from the weather@home Australia and New Zealand (w@h ANZ) project (Black et al. 2015, 2016; Massey et al. 2015), and coupled climate model simulations from the Coupled Anthropogenic climate change and El Niño made small but significant contributions to increasing the likelihood of record low rainfall in October 2015 in Tasmania. Atmospheric variability was the main contributor.