School of Earth Sciences - Research Publications
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ItemNo Preview AvailableSpatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation(Institute of Physics (IoP), 2017-04-01)Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumvents assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.
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ItemNo Preview AvailableNonstationary Australasian Teleconnections and Implications for Paleoclimate Reconstructions(American Meteorological Society, 2013)The stationarity of relationships between local and remote climates is a necessary, yet implicit, assumption underlying many paleoclimate reconstructions. However, the assumption is tenuous for many seasonal relationships between interannual variations in the El Niño–Southern Oscillation (ENSO) and the southern annular mode (SAM) and Australasian precipitation and mean temperatures. Nonstationary statistical relationships between local and remote climates on the 31–71-yr time scale, defined as a change in their strength and/or phase outside that expected from local climate noise, are detected on near-centennial time scales from instrumental data, climate model simulations, and paleoclimate proxies.The relationships between ENSO and SAM and Australasian precipitation were nonstationary at 21%–37% of Australasian stations from 1900 to 2009 and strongly covaried, suggesting common modulation. Control simulations from three coupled climate models produce ENSO-like and SAM-like patterns of variability, but differ in detail to the observed patterns in Australasia. However, the model teleconnections also display nonstationarity, in some cases for over 50% of the domain. Therefore, nonstationary local–remote climatic relationships are inherent in environments regulated by internal variability. The assessments using paleoclimate reconstructions are not robust because of extraneous noise associated with the paleoclimate proxies.Instrumental records provide the only means of calibrating and evaluating regional paleoclimate reconstructions. However, the length of Australasian instrumental observations may be too short to capture the near-centennial-scale variations in local–remote climatic relationships, potentially compromising these reconstructions. The uncertainty surrounding nonstationary teleconnections must be acknowledged and quantified. This should include interpreting nonstationarities in paleoclimate reconstructions using physically based frameworks.
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ItemNo Preview AvailableAustralasian Temperature Reconstructions Spanning the Last Millennium(AMER METEOROLOGICAL SOC, 2016-08)Abstract Multiproxy warm season (September–February) temperature reconstructions are presented for the combined land–ocean region of Australasia (0°–50°S, 110°E–180°) covering 1000–2001. Using between 2 (R2) and 28 (R28) paleoclimate records, four 1000-member ensemble reconstructions of regional temperature are developed using four statistical methods: principal component regression (PCR), composite plus scale (CPS), Bayesian hierarchical models (LNA), and pairwise comparison (PaiCo). The reconstructions are then compared with a three-member ensemble of GISS-E2-R climate model simulations and independent paleoclimate records. Decadal fluctuations in Australasian temperatures are remarkably similar between the four reconstruction methods. There are, however, differences in the amplitude of temperature variations between the different statistical methods and proxy networks. When the R28 network is used, the warmest 30-yr periods occur after 1950 in 77% of ensemble members over all methods. However, reconstructions based on only the longest records (R2 and R3 networks) indicate that single 30- and 10-yr periods of similar or slightly higher temperatures than in the late twentieth century may have occurred during the first half of the millennium. Regardless, the most recent instrumental temperatures (1985–2014) are above the 90th percentile of all 12 reconstruction ensembles (four reconstruction methods based on three proxy networks—R28, R3, and R2). The reconstructed twentieth-century warming cannot be explained by natural variability alone using GISS-E2-R. In this climate model, anthropogenic forcing is required to produce the rate and magnitude of post-1950 warming observed in the Australasian region. These paleoclimate results are consistent with other studies that attribute the post-1950 warming in Australian temperature records to increases in atmospheric greenhouse gas concentrations.
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ItemConsistent Trends in a Modified Climate Extremes Index in the United States, Europe, and Australia(AMER METEOROLOGICAL SOC, 2014-02)Abstract The utility of a combined modified climate extremes index (mCEI) is presented for monitoring coherent trends in multiple types of climate extremes across large regions. Its usefulness lies in its ability to distill complex spatiotemporal fields into a simple, flexible nonparametric index. Two versions of the mCEI are computed that incorporate changes in several annual- or daily-scale temperature-related and moisture-related extremes. Applying data from the contiguous United States, Europe, and Australia detects consistent and statistically significant increases in the spatial prevalence of climate extremes from 1950 to 2012. All three continental-scale regions show increasingly widespread warm annual- and daily-scale minimum and maximum temperature extremes, a decreasing spatial extent of cool annual- and daily-scale minimum and maximum temperature extremes, and increasing areas where the proportion of annual total precipitation falls on heavy-rain days. There were no statistically significant trends toward more widespread, annual-scale drought or moisture surplus in any region. The dependence of annual extremes on the frequency of daily-scale extremes is highlighted by the strong covariations between annual- and daily-scale extremes in all regions. By the nature of construction of the combined indices, the differences in the trends of the mCEI and daily-scale mCEI (dmCEI) suggest that extremes in more areas are changing primarily because of a shift of temperature and daily rainfall distributions toward warm extremes and heavy-rainfall extremes.
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ItemA combined climate extremes index for the Australian Region(American Meteorological Society, 2010)Changes in the area of Australia experiencing concurrent temperature and rainfall extremes are investigated through the use of two combined indices. The indices describe variations between the fraction of land area experiencing extreme cold and dry or hot and wet conditions. There is a high level of agreement between the variations and trends of the indices from 1957 to 2008 when computed using (i) a spatially complete gridded dataset without rigorous quality control checks and (ii) spatially incomplete high-quality station datasets with rigorous quality control checks. Australian extremes are examined starting from 1911, which is the first time a broad-scale assessment of Australian temperature extremes has been performed prior to 1957. Over the whole country, the results show an increase in the extent of hot and wet extremes and a decrease in the extent of cold and dry extremes annually and during all seasons from 1911 to 2008 at a rate of between 1% and 2% decade−1. These trends mostly stem from changes in tropical regions during summer and spring. There are relationships between the extent of extreme maximum temperatures, precipitation, and soil moisture on interannual and decadal time scales that are similar to the relationships exhibited by variations of the means. However, the trends from 1911 to 2008 and from 1957 to 2008 are not consistent with these relationships, providing evidence that the processes causing the interannual variations and those causing the longer-term trends are different.
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ItemAtypical influence of the 2007 La Nina on rainfall and temperature in southeastern Australia(American Geophysical Union, 2009)Interannual climate variations associated with El Niño – Southern Oscillation (ENSO) dominate rainfall and temperature variability in southeastern Australia's Murray-Darling Basin (MDB), an important region for agricultural productivity. Following a decade-long dry period, a La Niña during 2007 failed to provide above average rainfall and cool temperatures in the southern half of the MDB, typical of most La Niña events for the region. Instead, annual (winter half-year) rainfall was 17% (35%) below average and maximum temperatures 0.91°C (1.26°C) above average. Based on the past variability between La Niña events, the combined probability of such anomalies is less than 2%. It is likely that these anomalies contain some contribution from a positive Indian Ocean Dipole (IOD). However, the IOD and other large-scale circulation features are unlikely to explain the atypical conditions that occurred in the southern MDB during the 2007 La Niña.