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Acacia Pepler and Andrew Dowdy

Abstract

Cyclones can be identified from gridded pressure data at different levels of the troposphere, with vertical structure known to influence the temporal development and impacts of midlatitude cyclones. However, studies of midlatitude cyclones typically focus on cyclones identified at a single atmospheric level. This paper examines how the frequency of vertically organized or deep cyclones varies around the world, with a focus on southeastern Australia. About 50% of global cyclones identified from mean sea level pressure show a coherent vertical structure extending to at least 500 hPa, based on ERA-Interim reanalysis data, and shallow cyclones are most common in the global midlatitudes. Using a combination of reanalysis data and satellite-based rainfall and lightning, we show that in southeast Australia deep cyclones have higher intensities, longer durations, and more severe winds and rainfall than either shallow surface cyclones or upper-level cyclones with no surface low, motivating a three-dimensional approach for future cyclone analyses.

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Acacia S. Pepler and Peter T. May

Abstract

Rainfall estimation using polarimetric radar involves the combination of a number of estimators with differing error characteristics to optimize rainfall estimates at all rain rates. In Part I of this paper, a new technique for such combinations was proposed that weights algorithms by the inverse of their theoretical errors. In this paper, the derived algorithms are validated using the “CP2” polarimetric radar in Queensland, Australia, and a collocated rain gauge network for two heavy-rain events during November 2008 and a larger statistical analysis that is based on data from between 2007 and 2009. Use of a weighted combination of polarimetric algorithms offers some improvement over composite methods that are based on decision-tree logic, particularly at moderate to high rain rates and during severe-thunderstorm events.

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Acacia S. Pepler, Peter T. May, and Merhala Thurai

Abstract

The algorithms used to estimate rainfall from polarimetric radar variables show significant variance in error characteristics over the range of naturally occurring rain rates. As a consequence, to improve rainfall estimation accuracy using polarimetric radar, it is necessary to optimally combine a number of different algorithms. In this study, a new composite method is proposed that weights the algorithms by the inverse of their theoretical error. A number of approaches are discussed and are investigated using simulated radar data calculated from disdrometer measurements. The resultant algorithms show modest improvement over composite methods based on decision-tree logic—in particular, at rain rates above 20 mm h−1.

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Leone Cavicchia, Acacia Pepler, Andrew Dowdy, and Kevin Walsh

Abstract

The subtropical part of the eastern Australian seaboard experiences intense cyclonic activity. The severe damage caused by the intense storms in the region, known as east coast lows (ECLs), has motivated a number of recent studies. Cyclones in this region appear to be driven by a combination of different (barotropic and baroclinic) formation mechanisms, consistent with the view emerging in the last decades that cyclones span a continuous spectrum of dynamical structures, with the barotropically driven tropical cyclone and the baroclinically driven extratropical cyclone being only the extremes of such a spectrum. In this work we revisit the climatology of cyclone occurrence in the subtropical east coast of Australia as seen in a global reanalysis, systematically applying classification criteria based on the cyclone vertical structure and thermal core. Moreover, we investigate the underlying processes driving the cyclone rapid intensification by means of an atmospheric limited-area energetics analysis. We show that ECLs have different spatial patterns according to the cyclone thermal structure, with the fraction of hybrid cyclones being larger toward the tropics and closer to the coast. Moreover, we find that explosively deepening cyclones in this region are driven by a different combination of processes with respect to the global case, with barotropic processes in the surrounding environment having a more dominant role in the energetics of cyclone rapid intensification. The findings of this work contribute to understanding the physical processes underlying the formation and intensification of Australian east coast lows and the associated coastal damage and risk.

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Alejandro Di Luca, Jason P. Evans, Acacia Pepler, Lisa Alexander, and Daniel Argüeso

Abstract

The climate of the eastern seaboard of Australia is strongly influenced by the passage of low pressure systems over the adjacent Tasman Sea due to their associated precipitation and their potential to develop into extreme weather events. The aim of this study is to quantify differences in the climatology of east coast lows derived from the use of six global reanalyses. The methodology is explicitly designed to identify differences between reanalyses arising from differences in their horizontal resolution and their structure (type of forecast model, assimilation scheme, and the kind and number of observations assimilated). As a basis for comparison, reanalysis climatologies are compared with an observation-based climatology. Results show that reanalyses, specially high-resolution products, lead to very similar climatologies of the frequency, intensity, duration, and size of east coast lows when using spatially smoothed (about 300-km horizontal grid meshes) mean sea level pressure fields as input data. Moreover, at these coarse horizontal scales, monthly, interannual, and spatial variabilities appear to be very similar across the various reanalyses with a generally stronger agreement between winter events compared with summer ones. Results also show that, when looking at cyclones using reanalysis data at their native resolution (approaching 50-km grid spacing for the most recent products), uncertainties related to the frequency, intensity, and size of lows are very large and it is not clear which reanalysis, if any, gives a better description of cyclones. Further work is needed in order to evaluate the usefulness of the finescale information in modern reanalyses and to better understand the sources of their differences.

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Pandora Hope, Mitchell T. Black, Eun-Pa Lim, Andrew Dowdy, Guomin Wang, Robert J. B. Fawcett, and Acacia S. Pepler
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Acacia S. Pepler, Alejandro Di Luca, Fei Ji, Lisa V. Alexander, Jason P. Evans, and Steven C. Sherwood

Abstract

The Australian east coast low (ECL) is both a major cause of damaging severe weather and an important contributor to rainfall and dam inflow along the east coast, and is of interest to a wide range of groups including catchment managers and emergency services. For this reason, several studies in recent years have developed and interrogated databases of east coast lows using a variety of automated cyclone detection methods and identification criteria. This paper retunes each method so that all yield a similar event frequency within the ECL region, to enable a detailed intercomparison of the similarities, differences, and relative advantages of each method. All methods are shown to have substantial skill at identifying ECL events leading to major impacts or explosive development, but the choice of method significantly affects both the seasonal and interannual variation of detected ECL numbers. This must be taken into consideration in studies on trends or variability in ECLs, with a subcategorization of ECL events by synoptic situation of key importance.

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Agus Santoso, Harry Hendon, Andrew Watkins, Scott Power, Dietmar Dommenget, Matthew H. England, Leela Frankcombe, Neil J. Holbrook, Ryan Holmes, Pandora Hope, Eun-Pa Lim, Jing-Jia Luo, Shayne McGregor, Sonja Neske, Hanh Nguyen, Acacia Pepler, Harun Rashid, Alex Sen Gupta, Andréa S. Taschetto, Guomin Wang, Esteban Abellán, Arnold Sullivan, Maurice F. Huguenin, Felicity Gamble, and Francois Delage

Abstract

El Niño and La Niña, the warm and cold phases of El Niño–Southern Oscillation (ENSO), cause significant year-to-year disruptions in global climate, including in the atmosphere, oceans, and cryosphere. Australia is one of the countries where its climate, including droughts and flooding rains, is highly sensitive to the temporal and spatial variations of ENSO. The dramatic impacts of ENSO on the environment, society, health, and economies worldwide make the application of reliable ENSO predictions a powerful way to manage risks and resources. An improved understanding of ENSO dynamics in a changing climate has the potential to lead to more accurate and reliable ENSO predictions by facilitating improved forecast systems. This motivated an Australian national workshop on ENSO dynamics and prediction that was held in Sydney, Australia, in November 2017. This workshop followed the aftermath of the 2015/16 extreme El Niño, which exhibited different characteristics to previous extreme El Niños and whose early evolution since 2014 was challenging to predict. This essay summarizes the collective workshop perspective on recent progress and challenges in understanding ENSO dynamics and predictability and improving forecast systems. While this essay discusses key issues from an Australian perspective, many of the same issues are important for other ENSO-affected countries and for the international ENSO research community.

Open access
Sarah A. Tessendorf, Roelof T. Bruintjes, Courtney Weeks, James W. Wilson, Charles A. Knight, Rita D. Roberts, Justin R. Peter, Scott Collis, Peter R. Buseck, Evelyn Freney, Michael Dixon, Matthew Pocernich, Kyoko Ikeda, Duncan Axisa, Eric Nelson, Peter T. May, Harald Richter, Stuart Piketh, Roelof P. Burger, Louise Wilson, Steven T. Siems, Michael Manton, Roger C. Stone, Acacia Pepler, Don R. Collins, V. N. Bringi, M. Thurai, Lynne Turner, and David McRae

As a response to extreme water shortages in southeast Queensland, Australia, brought about by reduced rainfall and increasing population, the Queensland government decided to explore the potential for cloud seeding to enhance rainfall. The Queensland Cloud Seeding Research Program (QCSRP) was conducted in the southeast Queensland region near Brisbane during the 2008/09 wet seasons. In addition to conducting an initial exploratory, randomized (statistical) cloud seeding study, multiparameter radar measurements and in situ aircraft microphysical data were collected. This comprehensive set of observational platforms was designed to improve the physical understanding of the effects of both ambient aerosols and seeding material on precipitation formation in southeast Queensland clouds. This focus on gaining physical understanding, along with the unique combination of modern observational platforms utilized in the program, set it apart from previous cloud seeding research programs. The overarching goals of the QCSRP were to 1) determine the characteristics of local cloud systems (i.e., weather and climate), 2) document the properties of atmospheric aerosol and their microphysical effects on precipitation formation, and 3) assess the impact of cloud seeding on cloud microphysical and dynamical processes to enhance rainfall. During the course of the program, it became clear that there is great variability in the natural cloud systems in the southeast Queensland region, and understanding that variability would be necessary before any conclusions could be made regarding the impact of cloud seeding. This article presents research highlights and progress toward achieving the goals of the program, along with the challenges associated with conducting cloud seeding research experiments

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