School of Earth Sciences - Research Publications

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    Observed Relationships Between Sudden Stratospheric Warmings and European Climate Extremes
    King, AD ; Butler, AH ; Jucker, M ; Earl, NO ; Rudeva, I (AMER GEOPHYSICAL UNION, 2019-12-27)
    Abstract Sudden stratospheric warmings (SSWs) have been linked with anomalously cold temperatures at the surface in the middle to high latitudes of the Northern Hemisphere as climatological westerly winds in the stratosphere tend to weaken and turn easterly. However, previous studies have largely relied on reanalyses and model simulations to infer the role of SSWs on surface climate and SSW relationships with extremes have not been fully analyzed. Here, we use observed daily gridded temperature and precipitation data over Europe to comprehensively examine the response of climate extremes to the occurrence of SSWs. We show that for much of Scandinavia, winters with SSWs are on average at least 1 °C cooler, but the coldest day and night of winter is on average at least 2 °C colder than in non‐SSW winters. Anomalously high pressure over Scandinavia reduces precipitation on the northern Atlantic coast but increases overall rainfall and the number of wet days in southern Europe. In the 60 days after SSWs, cold extremes are more intense over Scandinavia with anomalously high pressure and drier conditions prevailing. Over southern Europe there is a tendency toward lower pressure, increased precipitation and more wet days. The surface response in cold temperature extremes over northwest Europe to the 2018 SSW was stronger than observed for any SSW during 1979–2016. Our analysis shows that SSWs have an effect not only on mean climate but also extremes over much of Europe. Only with carefully designed analyses are the relationships between SSWs and climate means and extremes detectable above synoptic‐scale variability.
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    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.
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    Greater probability of extreme precipitation under 1.5 °C and 2 °C warming limits over East-Central Asia (vol 56, pg 631, 2020)
    Zhang, M ; Yu, H ; King, AD ; Wei, Y ; Huang, J ; Ren, Y (SPRINGER, 2020-09)
    The original article has been corrected. During proof correction, the author supplied new images that were unfortunately not included. The original article has been updated to include the correct images.
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    Pathways and pitfalls in extreme event attribution
    van Oldenborgh, GJ ; van der Wiel, K ; Kew, S ; Philip, S ; Otto, F ; Vautard, R ; King, A ; Lott, F ; Arrighi, J ; Singh, R ; van Aalst, M (SPRINGER, 2021-05)
    Abstract The last few years have seen an explosion of interest in extreme event attribution, the science of estimating the influence of human activities or other factors on the probability and other characteristics of an observed extreme weather or climate event. This is driven by public interest, but also has practical applications in decision-making after the event and for raising awareness of current and future climate change impacts. The World Weather Attribution (WWA) collaboration has over the last 5 years developed a methodology to answer these questions in a scientifically rigorous way in the immediate wake of the event when the information is most in demand. This methodology has been developed in the practice of investigating the role of climate change in two dozen extreme events world-wide. In this paper, we highlight the lessons learned through this experience. The methodology itself is documented in a more extensive companion paper. It covers all steps in the attribution process: the event choice and definition, collecting and assessing observations and estimating probability and trends from these, climate model evaluation, estimating modelled hazard trends and their significance, synthesis of the attribution of the hazard, assessment of trends in vulnerability and exposure, and communication. Here, we discuss how each of these steps entails choices that may affect the results, the common problems that can occur and how robust conclusions can (or cannot) be derived from the analysis. Some of these developments also apply to other attribution methodologies and indeed to other problems in climate science.
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    Tropical forcing of Australian extreme low minimum temperatures in September 2019
    Lim, E-P ; Hendon, HH ; Shi, L ; de Burgh-Day, C ; Hudson, D ; King, A ; Trewin, B ; Griffiths, M ; Marshall, A (SPRINGER, 2021-06)
    We explore the causes and predictability of extreme low minimum temperatures (T ) that occurred across northern and eastern Australia in September 2019. Historically, reduced T is related to the occurrence of a positive Indian Ocean Dipole (IOD) and central Pacific El Niño. Positive IOD events tend to locate an anomalous anticyclone over the Great Australian Bight, therefore inducing cold advection across eastern Australia. Positive IOD and central Pacific El Niño also reduce cloud cover over northern and eastern Australia, thus enhancing radiative cooling at night-time. During September 2019, the IOD and central Pacific El Niño were strongly positive, and so the observed T anomalies are well reconstructed based on their historical relationships with the IOD and central Pacific El Niño. This implies that September 2019 T anomalies should have been predictable at least 1–2 months in advance. However, even at zero lead time the Bureau of Metereorolgy ACCESS-S1 seasonal prediction model failed to predict the anomalous anticyclone in the Bight and the cold anomalies in the east. Analysis of hindcasts for 1990–2012 indicates that the model's teleconnections from the IOD are systematically weaker than the observed, which likely stems from mean state biases in sea surface temperature and rainfall in the tropical Indian and western Pacific Oceans. Together with this weak IOD teleconnection, forecasts for earlier-than-observed onset of the negative Southern Annular Mode following the strong polar stratospheric warming that occurred in late August 2019 may have contributed to the T forecast bust over Australia for September 2019. min min min min min
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    Method uncertainty is essential for reliable confidence statements of precipitation projections
    Uhe, P ; Mitchell, D ; Bates, PD ; Allen, MR ; Betts, RA ; Huntingford, C ; King, AD ; Sanderson, BM ; Shiogama, H (American Meteorological Society, 2021-02-01)
    Precipitation events cause disruption around the world and will be altered by climate change. However, different climate modeling approaches can result in different future precipitation projections. The corresponding ''method uncertainty'' is rarely explicitly calculated in climate impact studies and major reports but can substantially change estimated precipitation changes. A comparison across five commonly used modeling activities shows that, for changes in mean precipitation, less than half of the regions analyzed had significant changes between the present climate and 1.58C global warming for the majority of modeling activities. This increases to just over half of the regions for changes between present climate and 28C global warming. There is much higher confidence in changes in maximum 1-day precipitation than in mean precipitation, indicating the robust influence of thermodynamics in the climate change effect on extremes. We also find that none of the modeling activities captures the full range of estimates from the other methods in all regions. Our results serve as an uncertainty map to help interpret which regions require a multimethod approach. Our analysis highlights the risk of overreliance on any single modeling activity and the need for confidence statements in major synthesis reports to reflect this method uncertainty. Considering multiple sources of climate projections should reduce the risks of policymakers being unprepared for impacts of warmer climates relative to using single-method projections to make decisions.
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    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.
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    A protocol for probabilistic extreme event attribution analyses
    Philip, S ; Kew, S ; van Oldenborgh, GJ ; Otto, F ; Vautard, R ; van der Wiel, K ; King, A ; Lott, F ; Arrighi, J ; Singh, R ; van Aalst, M (Copernicus GmbH, 2020-11-10)
    Abstract. Over the last few years, methods have been developed to answer questions on the effect of global warming on recent extreme events. Many “event attribution” studies have now been performed, a sizeable fraction even within a few weeks of the event, to increase the usefulness of the results. In doing these analyses, it has become apparent that the attribution itself is only one step of an extended process that leads from the observation of an extreme event to a successfully communicated attribution statement. In this paper we detail the protocol that was developed by the World Weather Attribution group over the course of the last 4 years and about two dozen rapid and slow attribution studies covering warm, cold, wet, dry, and stormy extremes. It starts from the choice of which events to analyse and proceeds with the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis and ends with the communication procedures. This article documents this protocol. It is hoped that our protocol will be useful in designing future event attribution studies and as a starting point of a protocol for an operational attribution service.
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    Reply to Comment by Mandel et al. on "Numerically Bounded Linguistic Probability Schemes Are Unlikely to Communicate Uncertainty Effectively"
    King, AD ; Perkins-Kirkpatrick, SE ; Wehner, MF ; Lewis, SC (AMER GEOPHYSICAL UNION, 2021-01)
    Abstract We thank the Comment's authors for their considered critique of our paper. We respond to their main criticisms and hope that this discussion motivates further consideration of communication strategies for event attribution analyses.
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    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.