Search Results

You are looking at 1 - 7 of 7 items for

  • Author or Editor: Acacia S. Pepler x
  • Refine by Access: All Content x
Clear All Modify Search
Acacia S. Pepler
and
Andrew J. Dowdy

Abstract

Extratropical cyclones are responsible for the majority of total and extreme rainfall in many regions of the extratropics, including in southern Australia. Using an ensemble of projections from 12 regional climate models, we show that both the number of cyclone days and total cyclone-related rainfall are projected to decline across southern Australia during the twenty-first century. This is a robust signal in projections across models and explains more than 80% of projected declines in total cool-season rainfall in the region. Using cyclone-centered composites, we show that cyclone intensity based on wind speed is projected to decrease but cyclone maximum rainfall is projected to increase by close to 7% K−1 in the southeast. This results in a shift in the distribution of cyclone rainfall, with a decrease in moderate rainfall but little change or an increase in extreme rainfall.

Significance Statement

Extratropical cyclones are very important for southern Australian rainfall, and they are expected to become less frequent in a warming climate. Our research shows this explains at least 80% of the projected decline in cool-season rainfall in southern Australia. However, the frequency of extratropical cyclones with very heavy rainfall may increase, particularly in Tasmania and the southeast coast, with increases in rainfall intensity in line with the Clausius–Clapeyron relationship. This contributes to increases in the frequency of very heavy rainfall in the future.

Open access
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.

Full access
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.

Full access
Pandora Hope
,
Mitchell T. Black
,
Eun-Pa Lim
,
Andrew Dowdy
,
Guomin Wang
,
Robert J. B. Fawcett
, and
Acacia S. Pepler
Full access
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.

Full access
Pandora Hope
,
Mei Zhao
,
S. Abhik
,
Gen Tolhurst
,
Roseanna C. McKay
,
Surendra P. Rauniyar
,
Lynette Bettio
,
Avijeet Ramchurn
,
Eun-Pa Lim
,
Acacia S. Pepler
,
Tim Cowan
, and
Andrew B. Watkins
Open access
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.

Full access