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Ian Simmonds, Daohua Bi, and Pandora Hope

Abstract

The summer moisture transport by the large-scale circulation over China has been investigated using ECMWF–WMO twice-daily analyses for the period 1980–96. The horizontal flux of atmospheric water vapor and its divergence has been calculated over two target regions, namely, southeast China (25°–35°N, 110°–120°E) and northeast China (40°–50°N, 120°–130°E). The time-averaged fluxes show the southeastern Asian and Indian monsoon circulations bringing abundant moisture from the South China Sea and the Bay of Bengal, respectively, to southeast China while the midlatitude westerlies dominate the moisture transport over northeast China.

The association between the interannual variations of moisture flux and rainfall over China has been examined. The comparison of the fluxes for wet and dry years over the southeast showed there to be, for the former, much stronger moisture transport by the southeastern Asian monsoon through the southern boundary but little change associated with transport by the Indian monsoon. Furthermore, comparison between mean and transient eddy transport budgets in wet and dry years and in the climatological mean shows that the mean component is dominant in the total transport. The moisture convergence associated with the transient eddies assumes its largest values in the eastern part of the country and, for the most part, assumes a sign opposite to that of the moisture flux convergence associated with the time-mean circulation and moisture fields. The results of this study suggest that the transient eddies do not play a significant role in the initiation and maintenance of the abnormal climate events over the two domains used in the study. Over both of these domains the two largest terms in the climatological moisture budget are seen to be the evaporation and the precipitation, while for interannual variations the largest terms are the atmospheric moisture convergence and the precipitation.

China has the largest irrigated area in the world and much of this is in the form of flooded paddy fields. It is suggested that this large area of saturated surface may result in evapotranspiration rates that differ significantly from those implied by atlases that have used estimates obtained at “typical” locations. The extent of irrigation over China may also make the task of interpreting its moisture budget more difficult.

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Pandora Hope, Eun-Pa Lim, Harry Hendon, and Guomin Wang
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Guomin Wang, Pandora Hope, Eun-Pa Lim, Harry H. Hendon, and Julie M Arblaster

Abstract

When record-breaking climate and weather extremes occur, decision-makers and planners want to know whether they are random natural events with historical levels of reoccurrence or are reflective of an altered frequency or intensity as a result of climate change. This paper describes a method to attribute extreme weather and climate events to observed increases in atmospheric CO2 using an initialized subseasonal to seasonal coupled global climate prediction system. Application of this method provides quantitative estimates of the contribution arising from increases in the level of atmospheric CO2 to individual weather and climate extreme events. Using a coupled subseasonal to seasonal forecast system differs from other methods because it has the merit of being initialized with the observed conditions and subsequently reproducing the observed events and their mechanisms. This can aid understanding when the reforecasts with and without enhanced CO2 are compared and communicated to a general audience. Atmosphere–ocean interactions are accounted for. To illustrate the method, we attribute the record Australian heat event of October 2015. We find that about half of the October 2015 Australia-wide temperature anomaly is due to the increase in atmospheric CO2 since 1960. This method has the potential to provide attribution statements for forecast events within an outlook period (i.e., before they occur). This will allow for informed messaging to be available as required when an extreme event occurs, which is of particular use to weather and climate services.

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Pandora Hope, Eun-Pa Lim, Guomin Wang, Harry H. Hendon, and Julie M. Arblaster
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Hanh Nguyen, Jason A. Otkin, Matthew C. Wheeler, Pandora Hope, Blair Trewin, and Christa Pudmenzky

Abstract

The seasonal cycle of the evaporative stress index (ESI) over Australia, and its relationship to observed rainfall and temperature, is examined. The ESI is defined as the standardized anomaly of the ratio of actual evapotranspiration to potential evapotranspiration, and as such, is a measure of vegetation moisture stress associated with agricultural or ecological drought. The ESI is computed using the daily output of version 6 of the Bureau of Meteorology’s landscape water balance model [Australian Water Resource Assessment Landscape (AWRA-L)] on a 5-km horizontal grid over a 45-yr period (1975–2019). Here we show that the ESI exhibits marked spatial and seasonal variability and can be used to accurately monitor drought across Australia, where ESI values less than negative one indicate drought. While the ESI is highly correlated with rainfall as expected, its relationship with temperature only becomes significant during the warmer seasons, suggesting a threshold above which temperature may affect vegetation stress. Our analysis also shows that the ESI tends to be strongly negative (i.e., indicating drought) during El Niño and positive phases of the Indian Ocean dipole (IOD), when conditions tend to be anomalously hot and dry. A negative phase of the southern annular mode also tends to drive negative ESI values during austral spring with a one-month delay.

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Pandora Hope, Guomin Wang, Eun-Pa Lim, Harry H. Hendon, and Julie M. Arblaster
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Michael R. Grose, Mitchell Black, James S. Risbey, Peter Uhe, Pandora K. Hope, Karsten Haustein, and Dann Mitchell
Open access
Pandora Hope, Mitchell T. Black, Eun-Pa Lim, Andrew Dowdy, Guomin Wang, Robert J. B. Fawcett, and Acacia S. Pepler
Open access
Pandora Hope, Kevin Keay, Michael Pook, Jennifer Catto, Ian Simmonds, Graham Mills, Peter McIntosh, James Risbey, and Gareth Berry

Abstract

The identification of extratropical fronts in reanalyses and climate models is an important climate diagnostic that aids dynamical understanding and model verification. This study compares six frontal identification methods that are applied to June and July reanalysis data over the Central Wheatbelt of southwest Western Australia for 1979–2006. Much of the winter rainfall over this region originates from frontal systems. Five of the methods use automated algorithms. These make use of different approaches, based on shifts in 850-hPa winds (WND), gradients of temperature (TGR) and wet-bulb potential temperature (WPT), pattern matching (PMM), and a self-organizing map (SOM). The sixth method was a manual synoptic technique (MAN). On average, about 50% of rain days were associated with fronts in most schemes (although methods PMM and SOM exhibited a lower percentage). On a daily basis, most methods identify the same systems more than 50% of the time, and over the 28-yr period the seasonal time series correlate strongly. The association with rainfall is less clear. The WND time series of seasonal frontal counts correlate significantly with Central Wheatbelt rainfall. All automated methods identify fronts on some days that are classified as cutoff lows in the manual analysis, which will impact rainfall correlations. The front numbers identified on all days by the automated methods decline from 1979 to 2006 (but only the TGR and WPT trends were significant at the 10% level). The results here highlight that automated techniques have value in understanding frontal behavior and can be used to identify the changes in the frequency of frontal systems through time.

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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