School of Earth Sciences - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 4 of 4
  • Item
    Thumbnail Image
    Sub-seasonal to seasonal prediction of rainfall extremes in Australia
    King, AD ; Hudson, D ; Lim, E-P ; Marshall, AG ; Hendon, HH ; Lane, TP ; Alves, O (WILEY, 2020-07)
    Abstract Seasonal climate prediction to date has largely focussed on probabilistic forecasts for above‐ and below‐average conditions in climate means. Here, we examine the possibility of making sub‐seasonal to seasonal outlooks for daily‐scale precipitation extremes in Australia. We first use observational data to show that significant relationships exist between climate modes, such as the El Niño–Southern Oscillation, and indices representing rainfall extremes across much of Australia. The strong observed teleconnections between climate modes and daily rainfall extremes suggest the potential for predictability on seasonal scales. The current Australian Bureau of Meteorology seasonal prediction system (ACCESS‐S1) is examined for performance in predicting rainfall extreme indices using a range of measures. Ensemble hindcasts, consisting of 11 members initialised every month during 1990–2012, perform well for some extreme rainfall indices on short lead‐times (up to 1 month). We note that at short lead‐times, forecasts are aided by skilful weather prediction, so forecast performance drops at lead‐times of a week or more. Forecast performance is lower in austral summer than other seasons and greater in the north and interior of the continent, particularly in the dry season, than elsewhere. The ACCESS‐S1 ensemble is overconfident but exhibits some reliability in probabilistic forecasts of above‐ or below‐average number of wet days and intensity of the highest daily maximum precipitation, especially in northern Australia. ACCESS‐S1 captures the broad pattern of relationships between climate modes and rainfall extremes that are observed. For two case‐studies of unusually extreme precipitation, ACCESS‐S exhibits contrasting performance for forecasts of extreme rainfall anomalies beyond the first month. These results suggest that ACCESS‐S1 may be used to produce outlooks for some rainfall indices, such as the number of wet days and the intensity of the wettest day, for the month ahead.
  • Item
    Thumbnail Image
    Extreme rainfall in New Zealand and its association with Atmospheric Rivers
    Reid, KJ ; Rosier, SM ; Harrington, LJ ; King, AD ; Lane, TP (Institute of Physics (IoP), 2021-04-01)
    Atmospheric rivers (ARs) are narrow and elongated regions of enhanced horizontal water vapour transport. Considerable research on understanding Northern Hemisphere ARs and their relationship with extreme precipitation has shown that ARs have a strong association with heavy rainfall and flooding. While there has been very little work on ARs in the Southern Hemisphere, global climatologies suggest that ARs are equally as common in both hemispheres. New Zealand in particular is located in a region of high AR frequency. This study aims to test the hypothesis that ARs play a significant role in heavy precipitation and flooding events in New Zealand. We used a recently developed AR identification method and daily station data across New Zealand to test for the concurrence of ARs and extreme rainfall. We found that, at each of the eleven stations analysed, at least seven to all ten of the top ten heaviest precipitation days between 1980 and 2018 were associated with AR conditions. Nine of the ten most damaging floods in New Zealand between 2007 and 2017 occurred during AR events. These results have important implications for understanding extreme rainfall in New Zealand, and ultimately for predicting some of the most hazardous events in the region. This work also highlights that more research on ARs in New Zealand is needed.
  • Item
    Thumbnail Image
    The Sensitivity of Atmospheric River Identification to Integrated Water Vapor Transport Threshold, Resolution, and Regridding Method
    Reid, KJ ; King, AD ; Lane, TP ; Short, E (AMER GEOPHYSICAL UNION, 2020-10-27)
    Atmospheric rivers (ARs) are elongated narrow bands of enhanced water vapor that can cause intense rainfall and flooding. ARs only appeared in the literature the last 30 years, and there has been much debate about how to define ARs and how to identify them. As a result, a wide range of AR identification algorithms have been produced with variations in the conditions required for an object to be classified as an AR and differences in the input data. One of the key conditions in most AR identification algorithms is a minimum threshold of water vapor flux, along with geometric criteria. The aim of this study is to explore uncertainties in global AR identification based on a single integrated water vapor transport (IVT)-based identification method. We conduct a sensitivity analysis under one algorithmic framework to explore the effects of different IVT thresholds, input data resolutions, and regridding methods during the Years of Tropical Convection operational analysis (May 2008 to April 2010). We found that the resolution and regridding method affects the number of ARs identified but the seasonal cycle is maintained. AR identification is highly sensitive to the choice of IVT threshold; importantly, the commonly used 250 kg m−1 s−1 IVT threshold is not appropriate for global studies with detection methods that also include a restrictive geometric condition as this combination can lead to the strongest systems failing to be identified. The uncertainties within a single AR detection method and input data parameters may be as large as uncertainties across AR detection methodologies.
  • Item
    Thumbnail Image
    Global and regional impacts differ between transient and equilibrium warmer worlds
    King, AD ; Lane, TP ; Henley, BJ ; Brown, JR (NATURE PUBLISHING GROUP, 2020-01-01)
    under exclusive licence to Springer Nature Limited. There has recently been interest in understanding the differences between specific levels of global warming, especially the Paris Agreement limits of 1.5 °C and 2 °C above pre-industrial levels. However, different model experiments1–3 have been used in these analyses under varying rates of increase in global-average temperature. Here, we use climate model simulations to show that, for a given global temperature, most land is significantly warmer in a rapidly warming (transient) case than in a quasi-equilibrium climate. This results in more than 90% of the world’s population experiencing a warmer local climate under transient global warming than equilibrium global warming. Relative to differences between the 1.5 °C and 2 °C global warming limits, the differences between transient and quasi-equilibrium states are substantial. For many land regions, the probability of very warm seasons is at least two times greater in a transient climate than in a quasi-equilibrium equivalent. In developing regions, there are sizable differences between transient and quasi-equilibrium climates that underline the importance of explicitly framing projections. Our study highlights the need to better understand differences between future climates under rapid warming and quasi-equilibrium conditions for the development of climate change adaptation policies. Yet, current multi-model experiments1,4 are not designed for this purpose.