School of Earth Sciences - Research Publications
Permanent URI for this collection
Search Results
1 - 10 of 38
-
ItemObserved Relationships Between Sudden Stratospheric Warmings and European Climate Extremes(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.
-
ItemSub-seasonal to seasonal prediction of rainfall extremes in Australia(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.
-
ItemNo Preview AvailableGreater probability of extreme precipitation under 1.5 °C and 2 °C warming limits over East-Central Asia (vol 56, pg 631, 2020)(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.
-
ItemA protocol for probabilistic extreme event attribution analyses(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.
-
ItemThe Sensitivity of Atmospheric River Identification to Integrated Water Vapor Transport Threshold, Resolution, and Regridding Method(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.
-
ItemGlobal and regional impacts differ between transient and equilibrium warmer worlds(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.
-
ItemGreater probability of extreme precipitation under 1.5 °C and 2 °C warming limits over East-Central Asia(Springer (part of Springer Nature), 2020-05-27)East-Central Asia is one of the most vulnerable and sensitive regions to climate change, and the variability of extreme precipitation attracts great attention due to the large population and the importance of its economy. Here, three special runs with the Community Earth System Model (CESM) are used to project the changes in representative extreme precipitation indices (Rx1day, Rx5day, R95p, SDII) over East-Central Asia under the 1.5 °C and 2 °C Paris Agreement limits. The results indicate that Rx1day and Rx5day will increase by 28% and 15%, respectively, under the 1.5 °C warming level relative to the historical period (1971–2000). Most areas over East-Central Asia are projected to experience an accelerated increase in response to a further 0.5 °C warming. Specifically, humid areas (HAs) are projected to experience a greater increase in R95p annual days and area fraction, whereas arid and semiarid areas (ASAs) may have threefold higher risks. The proportion of extreme precipitation in total will increase ~10% in most HAs in response to the 0.5 °C additional warming. Holding global warming at 1.5 °C instead of 2 °C reduces the occurrence of R95p annual days by ~3 days/year in humid areas and ~1 day/year in ASAs. For SDII, most HAs will experience 0.2–0.6 mm/day and 0.2–0.4 mm/day increases in 1.5 °C or 2 °C warming limits, especially in Southeast China and the Himalayas. Therefore, limiting global warming to under 1.5 °C is beneficial to reducing the occurrence and associated impact of precipitation extremes in East-Central Asia.
-
ItemThe role of climate variability in Australian drought(NATURE PUBLISHING GROUP, 2020-02-24)The Poisson regression model remains an important tool in the econometric analysis of count data. In a pioneering contribution to the econometric analysis of such models, Lung-Fei Lee presented a specification test for a Poisson model against a broad class of discrete distributions sometimes called the Katz family. Two members of this alternative class are the binomial and negative binomial distributions, which are commonly used with count data to allow for under-and over-dispersion, respectively. In this paper we explore the structure of other distributions within the class and their suitability as alternatives to the Poisson model. Potential difficulties with the Katz likelihood leads us to investigate a class of point optimal tests of the Poisson assumption against the alternative of over-dispersion in both the regression and intercept only cases. In a simulation study, we compare score tests of ‘Poisson-ness’ with various point optimal tests, based on the Katz family, and conclude that it is possible to choose a point optimal test which is better in the intercept only case, although the nuisance parameters arising in the regression case are problematic. One possible cause is poor choice of the point at which to optimize. Consequently, we explore the use of Hellinger distance to aid this choice. Ultimately we conclude that score tests remain the most practical approach to testing for over-dispersion in this context.
-
ItemObserved Emergence of the Climate Change Signal: From the Familiar to the Unknown(AMER GEOPHYSICAL UNION, 2020-03-28)Abstract Changes in climate are usually considered in terms of trends or differences over time. However, for many impacts requiring adaptation, it is the amplitude of the change relative to the local amplitude of climate variability which is more relevant. Here, we develop the concept of “signal‐to‐noise” in observations of local temperature, highlighting that many regions are already experiencing a climate which would be “unknown” by late 19th century standards. The emergence of observed temperature changes over both land and ocean is clearest in tropical regions, in contrast to the regions of largest change which are in the northern extratropics—broadly consistent with climate model simulations. Significant increases and decreases in rainfall have also already emerged in different regions with the United Kingdom experiencing a shift toward more extreme rainfall events, a signal which is emerging more clearly in some places than the changes in mean rainfall.
-
ItemDetermining the Anthropogenic Greenhouse Gas Contribution to the Observed Intensification of Extreme Precipitation(AMER GEOPHYSICAL UNION, 2020-06-28)Abstract This study conducts a detection and attribution analysis of the observed changes in extreme precipitation during 1951–2015. Observed and CMIP6 multimodel simulated changes in annual maximum daily and consecutive 5‐day precipitation are compared using an optimal fingerprinting technique for different spatial scales from global land, Northern Hemisphere extratropics, tropics, three continental regions (North America and western and eastern Eurasia), and global “dry” and “wet” land areas (as defined by their average extreme precipitation intensities). Results indicate that anthropogenic greenhouse gas influence is robustly detected in the observed intensification of extreme precipitation over the global land and most of the subregions considered, all with clear separation from natural and anthropogenic aerosol forcings. Also, the human‐induced greenhouse gas increases are found to be a dominant contributor to the observed increase in extreme precipitation intensity, which largely follows the increased moisture availability under global warming.