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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0" article-type="research-article">
  <front>
    <journal-meta><journal-id journal-id-type="publisher">WCD</journal-id><journal-title-group>
    <journal-title>Weather and Climate Dynamics</journal-title>
    <abbrev-journal-title abbrev-type="publisher">WCD</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Weather Clim. Dynam.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">2698-4016</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/wcd-4-175-2023</article-id><title-group><article-title>Anomalous subtropical zonal winds drive decreases in southern Australian frontal rain</article-title><alt-title>Decreases in frontal rain</alt-title>
      </title-group><?xmltex \runningtitle{Decreases in frontal rain}?><?xmltex \runningauthor{A. S. Pepler and I. Rudeva}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name><surname>Pepler</surname><given-names>Acacia S.</given-names></name>
          <email>acacia.pepler@bom.gov.au</email>
        <ext-link>https://orcid.org/0000-0002-1478-2512</ext-link></contrib>
        <contrib contrib-type="author" corresp="no">
          <name><surname>Rudeva</surname><given-names>Irina</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-9851-8198</ext-link></contrib>
        <aff id="aff1"><institution>Research Program, Australian Bureau of Meteorology, Melbourne, Australia</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Acacia S. Pepler (acacia.pepler@bom.gov.au)</corresp></author-notes><pub-date><day>31</day><month>January</month><year>2023</year></pub-date>
      
      <volume>4</volume>
      <issue>1</issue>
      <fpage>175</fpage><lpage>188</lpage>
      <history>
        <date date-type="received"><day>24</day><month>August</month><year>2022</year></date>
           <date date-type="rev-request"><day>2</day><month>September</month><year>2022</year></date>
           <date date-type="rev-recd"><day>19</day><month>December</month><year>2022</year></date>
           <date date-type="accepted"><day>3</day><month>January</month><year>2023</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2023 Acacia S. Pepler</copyright-statement>
        <copyright-year>2023</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023.html">This article is available from https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023.html</self-uri><self-uri xlink:href="https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023.pdf">The full text article is available as a PDF file from https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023.pdf</self-uri>
      <abstract><title>Abstract</title>

      <p id="d1e87">Cold fronts make a significant contribution to cool season rainfall in the extratropics and subtropics. In many regions of the
Southern Hemisphere the amount of frontal rainfall has declined in recent
decades, but there has been no change in frontal frequency. We show that for
southeast Australia this contradiction cannot be explained by changes in
frontal intensity or moisture at the latitudes of interest. Rather,
declining frontal rainfall in southeast Australia is associated with
weakening of the subtropical westerlies in the mid-troposphere, which is
part of a hemispheric pattern of wind anomalies that modify the
extratropical zonal wave 3. Fronts that generate rainfall are associated
with strong westerlies that penetrate well into the subtropics, and the
observed decrease in frontal rainfall in southern Australia can be linked to
a decrease in the frequency of fronts with strong westerlies at
25<inline-formula><mml:math id="M1" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e108">Fronts are a major cause of rainfall and extremes in the global extratropics
(Catto et
al., 2012; Catto and Pfahl, 2013; Utsumi et al., 2017). While a large part
of frontal precipitation is related to fronts embedded within extratropical
cyclones  (Dowdy and Catto, 2017), trailing cold fronts that are
outside of the cyclone centre are an important cause of rainfall in many
areas of the Southern Hemisphere midlatitudes and subtropics, particularly
during the cool half of the year (Pepler et al., 2020; Utsumi et
al., 2017).</p>
      <p id="d1e111">In recent decades cool season frontal rainfall has decreased over parts of
the Southern Hemisphere continents, including southwestern Australia
(Risbey et al., 2013a), southeastern
Australia  (Pepler et al., 2021; Risbey
et al., 2013b) and southern Africa  (Burls
et al., 2019). However, these studies typically found that this decrease in
rainfall was not due to changes in the frequency of fronts. Indeed, studies
have consistently observed little change in frontal frequency over the
Southern Hemisphere midlatitudes in reanalyses (Berry et
al., 2011; Rudeva and Simmonds, 2015; Solman and Orlanski, 2014), although
some decreases have been observed in the frequency of midlatitude cyclones
(Pepler et al., 2021; Pepler, 2020b). Frontal frequency
in southeastern Australia has had little change over this period despite
expectations of a southward shift in fronts due to observed trends towards a
positive Southern Annular Mode (SAM) phase (Fogt
and Marshall, 2020) and an intensification of the Southern Hemisphere storm
track during winter (Chemke et al., 2022). Climate projections further
suggest a possible future increase in front frequency in Southern Hemisphere
midlatitude regions  (Blázquez
and Solman, 2019; Catto et al., 2014), although in the subtropics frontal
rainfall may still decline  (Utsumi et
al., 2016).</p>
      <p id="d1e114">The observed decrease in frontal rainfall, in the absence of changes in
frequency, suggests a change in either the moisture availability or the
dynamics (e.g. intensity) of fronts that decreases the likelihood that they
produce precipitation. Burls et al. (2019) investigated this for South Africa and suggested that the decrease in
frontal rainfall was related to increasing atmospheric pressure in the
subtropics and Hadley cell expansion. Consistent with that,
Sousa et al. (2018) showed a poleward migration of “water
corridors” due to an expansion of the semi-permanent South Atlantic
high-pressure system followed by a displacement of the jet stream during the
latest drought in South Africa in 2015–2017. But the extent to which these
results are transferrable to elsewhere in the Southern Hemisphere or to
longer time periods is unclear.</p>
      <p id="d1e117">Southeastern Australia (SEA) is an important agricultural region of
Australia, as well as home to a large proportion of Australia's population.
This region has experienced significant drying since the start of the
Millennium Drought (1997–2009), particularly during the cool season (May–October), which has been linked to an intensifying subtropical ridge and
anthropogenic global warming (Timbal and
Drosdowsky, 2013; Rauniyar and Power, 2020). The Millennium Drought ended in
2009 and was followed by heavy rain during the subsequent La Niña years of
2010–2011. However, while average annual rainfall over the 2010–2018 period
was close to the long-term average  (Fu et al., 2021),
this recovery is predominantly associated with increased rainfall during the
warm season, when a lower proportion of rainfall is converted into
streamflow. In contrast, rainfall during the hydrologically important cool
months of the year remained below the long-term average during the
post-drought period of 2010–2019  (Bureau of Meteorology and CSIRO,
2020; DELWP, 2020). While much of the decline in rainfall arises from
decreases in both the frequency and intensity of rainfall from cyclones,
there is an as-yet-unexplained decline in the proportion of trailing cold
fronts that produce rainfall  (Pepler et
al., 2021; Risbey et al., 2013b). In this study, we use front-centred
composites to investigate the causes of declining frontal rainfall in
southeastern Australia and the extent to which this can be linked to changes
in frontal characteristics, as well as large-scale circulation.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Data and methods</title>
      <p id="d1e128">There are a large number of front identification methods, and front
climatologies can be very sensitive to both the method chosen and the
reanalysis product used (Soster and
Parfitt, 2022; Schemm et al., 2015). While methods based on identifying a
change in air mass via gradients of temperature or humidity are the most
widely used, these can produce very high frequencies near coastlines
(Thomas
and Schultz, 2019; Schemm et al., 2015; Soster and Parfitt, 2022; Berry et
al., 2011). They are also more sensitive to choices of reanalysis dataset
and grid resolution than more complex front methods that also incorporate
wind information  (Soster and Parfitt, 2022).
While front methods that incorporate both wind and temperature information
have shown improved skill at representing fronts
(Bitsa et al., 2021; Biard and
Kunkel, 2019), for southern Australia a front detection method based solely
on wind changes has shown good skill at detecting trailing cold fronts
compared to manual fronts and particularly at detecting fronts associated
with rainfall, with the majority of such fronts able to be confirmed by a
temperature-based method
(Hope et al.,
2014; Pepler et al., 2020).</p>
      <p id="d1e131">The wind-based front detection method is described in
Rudeva and Simmonds (2015) and Simmonds et al. (2012). It compares two consecutive 6-hourly
analyses of 10 m wind and identifies a front when the horizontal wind
shifts in direction from the northwest to southwest quadrant and the
meridional wind increases by at least 2 m s<inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> over 6 h. Objective
features are then identified, with the easternmost edge of the frontal
region for the period <inline-formula><mml:math id="M3" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> to <inline-formula><mml:math id="M4" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:math></inline-formula> h identified as a front at time <inline-formula><mml:math id="M5" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>, noting
that some studies suggest this may better approximate atmospheric fields at
time <inline-formula><mml:math id="M6" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:math></inline-formula> h (Papritz et al., 2014). This method is
most useful for detecting cold fronts, which are the main fronts of
relevance to rainfall in southern Australia. While tracking is performed for
the whole Southern Hemisphere, for this study we require that fronts are at
least two grid points long and have at least one point in southeast Australia
(30–40<inline-formula><mml:math id="M7" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, 135–150<inline-formula><mml:math id="M8" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E; Fig. 1). Some supplemental
analysis is also performed on fronts in southwestern Western Australia
(SWWA; 23–38<inline-formula><mml:math id="M9" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, 110–120<inline-formula><mml:math id="M10" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E), as this region is also
experiencing a decline in cool season frontal rainfall
(Hope et al., 2006).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><?xmltex \currentcnt{1}?><?xmltex \def\figurename{Figure}?><label>Figure 1</label><caption><p id="d1e223">The regions referred to in this study. Plot shows the ERA5 rain
rate (shading, mm h<inline-formula><mml:math id="M11" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and MSLP (contours) for a single time (06:00 UTC on 9 June 2004) in the Australian region, with identified cold fronts shown in
red. Orange (SEA) and purple (SWWA) boxes show the regions used for
identifying cold fronts relevant to this study.</p></caption>
        <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023-f01.png"/>

      </fig>

      <p id="d1e245">All data in this paper are obtained from the ERA5 reanalysis
(Hersbach et al., 2020), with fronts
identified every 6 h on a 1<inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> grid, noting that fronts
identified on the native grid of high resolution show larger uncertainties
in frequency between reanalyses   (Soster and
Parfitt, 2022). In addition to assessing the raw front tracks, ERA5 data are
also used for front-centred composites and all other analyses in the paper.
While reanalyses often evaluate poorly against observed rainfall
measurements  (Alexander et al.,
2020), ERA5 generally evaluated well over Australia
(Lavers et al., 2022). The predecessor
to ERA5 (ERA-Interim) was found to generally perform well in simulating
frontal rainfall and moderate rainfall intensities over the oceans near
Australia  (Lang et al., 2018) despite deficiencies in
simulating prefrontal and non-frontal rainfall, making ERA5 well suited to
this study.</p>
      <p id="d1e257"><?xmltex \hack{\newpage}?>Geopotential height (<inline-formula><mml:math id="M13" display="inline"><mml:mi>Z</mml:mi></mml:math></inline-formula>), horizontal (<inline-formula><mml:math id="M14" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>, <inline-formula><mml:math id="M15" display="inline"><mml:mi>v</mml:mi></mml:math></inline-formula>) and vertical (<inline-formula><mml:math id="M16" display="inline"><mml:mi>w</mml:mi></mml:math></inline-formula>) velocity,
relative vorticity, and temperature (<inline-formula><mml:math id="M17" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>) were extracted and analysed on eight
vertical levels (1000, 925, 850, 700, 600, 500, 300, and 200 hPa). Most
results are presented for 700 hPa where changes were most significant, but
results were broadly consistent across a range of levels. Single-level
variables included mean sea level pressure (MSLP), rain rate, total column
water (TCW), 500–1000 hPa vertically integrated moisture flux including its
zonal and meridional components (IVT;   Reid
et al., 2022), and the Phillips criterion (PC), a measure of baroclinicity.
PC was calculated as in al Fahad et al. (2020):
          <disp-formula id="Ch1.E1" content-type="numbered"><label>1</label><mml:math id="M18" display="block"><mml:mrow><mml:mi mathvariant="normal">PC</mml:mi><mml:mo>=</mml:mo><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:msup><mml:mi>f</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mfenced open="(" close=")"><mml:mrow><mml:msub><mml:mi>u</mml:mi><mml:mn mathvariant="normal">500</mml:mn></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>u</mml:mi><mml:mi mathvariant="normal">lower</mml:mi></mml:msub></mml:mrow></mml:mfenced><mml:mi mathvariant="normal">Θ</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant="italic">β</mml:mi><mml:mi>g</mml:mi><mml:mi>H</mml:mi><mml:mfenced close=")" open="("><mml:mrow><mml:msub><mml:mi mathvariant="italic">θ</mml:mi><mml:mn mathvariant="normal">500</mml:mn></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="italic">θ</mml:mi><mml:mn mathvariant="normal">850</mml:mn></mml:msub></mml:mrow></mml:mfenced></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
        where <inline-formula><mml:math id="M19" display="inline"><mml:mi>H</mml:mi></mml:math></inline-formula> is the geometric height of the column – from the lower level (the
average between 850 and 1000 hPa) to 500 hPa – and <inline-formula><mml:math id="M20" display="inline"><mml:mi mathvariant="normal">Θ</mml:mi></mml:math></inline-formula> is the reference
potential temperature (300 K). While most of these variables are calculated
instantaneously at the time of the front, we calculated the average rain
rate from all hourly data between time <inline-formula><mml:math id="M21" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> and <inline-formula><mml:math id="M22" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:math></inline-formula> h; this can also be
multiplied by 6 to represent the accumulated frontal rainfall over the
corresponding period.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><?xmltex \currentcnt{2}?><?xmltex \def\figurename{Figure}?><label>Figure 2</label><caption><p id="d1e389"><bold>(a)</bold> An example of the front merger process for 00:00 UTC on
27 December 1992, with colours indicating the five distinct fronts identified at
this time and a grey box indicating the SEA tracking domain. <bold>(b)</bold> Of two
overlapping fronts, the one with the largest number of points in the SEA
region is retained, and the other is removed. <bold>(c)</bold> A front at the far north of
the region is removed, as it is too far east of the other identified front
points. <bold>(d)</bold> At latitudes with no identified front point, the longitude is
inferred based on the closest frontal points (black dots).</p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023-f02.png"/>

      </fig>

      <p id="d1e409">In some cases multiple fronts were identified in SEA at a single time, which
could represent either two distinct fronts or a single system incorrectly
broken into multiple parts by the tracking algorithm. To avoid
double-counting any dates in composites, we created a single “merged front”
for each time step over the latitudes 20–50<inline-formula><mml:math id="M23" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, which was used to
extract front-centred data within 10<inline-formula><mml:math id="M24" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> of longitude from the front
location at each latitude for plotting and analysis. The merged front data
were created using a four-step process, summarised in Fig. 2.</p>
      <p id="d1e430"><list list-type="order">
          <list-item>

      <p id="d1e435">Identify all fronts that touch the region of interest (30–40<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S,
135–150<inline-formula><mml:math id="M26" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) at a given time (Fig. 2a).</p>
          </list-item>
          <list-item>

      <p id="d1e459">If there is more than one front, first identify whether they overlap at any
latitudes. If they do, iteratively remove the fronts with the smallest
length within the region until there is only one front identified at each
latitude (Fig. 2b). Where multiple overlapping fronts have the same
length, we prioritise retaining fronts that are nearer in longitude to the
front with the most points in the region.</p>
          </list-item>
          <list-item>

      <p id="d1e465">If there are still multiple fronts, check for cases where there is
3<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> or less of longitude difference between the neighbouring ends
of the two fronts. If so, merge them into one front and set all missing
points to the average of the longitudes at the end of each segment.
Otherwise, remove the event with fewest points (Fig. 2c).</p>
          </list-item>
          <list-item>

      <p id="d1e480">Outside of the latitudes with an identified front, we infer an extended
“front” longitude based on the last recorded front point so that composites
can be calculated over the full 20–50<inline-formula><mml:math id="M28" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S region (Fig. 2d).</p>
          </list-item>
        </list></p>
      <p id="d1e495">While fronts can be as short as 1<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> in length, and the total number
of identified fronts is lower at 20<inline-formula><mml:math id="M30" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S than at 50<inline-formula><mml:math id="M31" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S
(Rudeva and Simmonds, 2015), we calculate
composites for latitudes between 20–50<inline-formula><mml:math id="M32" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S for all fronts
regardless of their latitudinal position within that interval. This is
because in many cases an identified cold front can interact strongly with
weather systems to the north of the identified front extent, such as troughs
and northwest cloud bands  (Reid et
al., 2019, 2022), and impact the atmospheric circulation and rainfall
patterns well into the tropics  (Narsey et al., 2017).
Fronts are also often associated with atmospheric rivers that advect
moisture from the tropics into higher latitudes
(Reid et al., 2022); therefore understanding
front-related circulation anomalies in the subtropics may help us to understand
changes in frontal rainfall.</p>
      <p id="d1e534">Results are presented for the cool season (May–October), with the 20-year
periods 1980–1999 and 2000–2019 compared and statistical significance
calculated using Student's <inline-formula><mml:math id="M33" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test. We additionally use three periods,
1979–1996, 1997–2009, and 2010–2019, in some instances to test for recovery in
frontal rainfall following the Millennium Drought. Unless otherwise
specified, front-centred averages are calculated within <inline-formula><mml:math id="M34" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M35" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> of
the front central longitude, representing the region with the majority of
frontal rainfall, with a focus on southeast Australian latitudes (33–38<inline-formula><mml:math id="M36" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S). As the anomalous trends in rainfall are in particular a
feature of trailing fronts (Pepler et al., 2021), we used a
dataset of Australian cyclones detected using ERA5
(Pepler, 2020a) to compare changes in trailing fronts with
those for fronts embedded in extratropical cyclones. Noting that in earlier
studies the area of cyclone rainfall is often taken as 10–12<inline-formula><mml:math id="M37" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>
around the cyclone centre (Hawcroft et al., 2012; Pepler
et al., 2020), we considered a front to be embedded in a cyclone if a
cyclone centre was detected within the 135–150<inline-formula><mml:math id="M38" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E,
20–45<inline-formula><mml:math id="M39" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S region (Hawcroft et al., 2012; Pepler
et al., 2020) or a trailing front if there was no cyclone in this region.
During May–October, 70 % of detected fronts are considered trailing
fronts, as are 55 % of fronts with rain rates exceeding 0.1 mm h<inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in
southeast Australia, as rain rates are higher in cases where cyclone and
front areas overlap  (Dowdy and Catto, 2017; Pepler
et al., 2020).</p>
      <p id="d1e611">Pearson's correlation coefficients are calculated using linearly detrended
data to assess relationships between seasonal mean frontal characteristics
and the intensity (STRI) and position (STRP) of the subtropical ridge
calculated over 140–150<inline-formula><mml:math id="M41" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E  (Timbal and
Drosdowsky, 2013). We also calculate correlations with the
Troup (1965) Southern Oscillation Index
(SOI; <uri>http://www.bom.gov.au/climate/enso/soi/</uri>, last access: 25 February 2021), an indicator of the El
Niño–Southern Oscillation (ENSO); the Dipole Mode Index (DMI), an
indicator of the Indian Ocean Dipole   (IOD: Saji et
al., 1999; <uri>https://stateoftheocean.osmc.noaa.gov/sur/ind/dmi.php</uri>, last access: 25 February 2021); and the
Southern Annular Mode (SAM:
<uri>https://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/aao/aao.shtml</uri>, last access: 6 February 2020). Statistical significance is assessed
using Student's <inline-formula><mml:math id="M42" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test for <inline-formula><mml:math id="M43" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>; this is calculated using
seasonal mean data for differences between periods and between all fronts
when identifying significant differences in structure between the wet and
dry subsets.</p>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Changes in frontal rainfall</title>
      <p id="d1e662">We first assess changes in front statistics using the raw ERA5 output over
1979–2019. There is a front detected somewhere in southeast Australia at
approximately 50 % of time steps during May–October, with no significant
difference in frequencies between the Millennium Drought in 1997–2009
(49 %) and the non-drought periods (50.6 %). No change in front
frequency is found when comparing the periods 1980–1999 and 2000–2019 for
southeast Australia as a whole or for the frequency of fronts detected for
each latitude band within this region (Fig. 3b). There is also no change
in the average front intensity at these latitudes, defined as the strength
of the change in meridional winds. There is a weak decrease in front
frequency at the equatorward edge of the region influenced by fronts
(20–25<inline-formula><mml:math id="M44" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S), from 22.3 % to 21.5 % of hours per season, but
this is not statistically significant.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><?xmltex \currentcnt{3}?><?xmltex \def\figurename{Figure}?><label>Figure 3</label><caption><p id="d1e676"><bold>(a)</bold> Average rain rate (shading, mm h<inline-formula><mml:math id="M45" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>), MSLP (black contours) and
700 hPa zonal wind (red contours) for all hours with at least one front in
SEA during May to October, centred on the longitude of the front. <bold>(b)</bold> Average
number of time steps in May–October with at least one front identified at
each latitude within the longitudes 135–150<inline-formula><mml:math id="M46" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, based on the full
dataset of Southern Hemisphere fronts prior to the merging process. Blue and
red lines show the median for 1980–1999 and 2000–2019, respectively, while
shading shows the interquartile range from seasonal data. <bold>(c–e)</bold> Total
accumulated frontal rainfall <bold>(c)</bold>, number of fronts with rainfall <inline-formula><mml:math id="M47" display="inline"><mml:mi mathvariant="italic">&gt;</mml:mi></mml:math></inline-formula> 0.1 mm h<inline-formula><mml:math id="M48" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> <bold>(d)</bold> and average rain rate where rain is <inline-formula><mml:math id="M49" display="inline"><mml:mi mathvariant="italic">&gt;</mml:mi></mml:math></inline-formula> 0.1 mm h<inline-formula><mml:math id="M50" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> <bold>(e)</bold> across all May–October time steps with a front detected in SEA
using the merged front dataset in 1980–1999 and 2000–2019. In <bold>(b)</bold>–<bold>(e)</bold>, crosses
indicate the differences are statistically significant at <inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>.</p></caption>
        <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023-f03.png"/>

      </fig>

      <p id="d1e783">Figure 3a shows the average rain rate for hours with an identified front in
southeast Australia, centred on the longitude of the front. Rain rates
greater than 0.1 mm h<inline-formula><mml:math id="M52" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> are recorded within 5<inline-formula><mml:math id="M53" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> of longitude on either
side of the front location, with the heaviest rain rates slightly west of the
front line. We thus define frontal rainfall to be the average over a
10<inline-formula><mml:math id="M54" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> region centred on the frontal line (0<inline-formula><mml:math id="M55" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) and use
the 0<inline-formula><mml:math id="M56" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> line to separate rainfall into “prefrontal” and
“postfrontal” rainfall. The likelihood of frontal rainfall and the average
annual frontal rainfall are highest south of 37<inline-formula><mml:math id="M57" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S. While the
frequency of detected fronts remains higher than 100/season as far north as
25<inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, the average rainfall from fronts decreases rapidly north of
33<inline-formula><mml:math id="M59" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, suggesting that the northern edge of fronts is typically
too weak or dry to produce rainfall.</p>
      <p id="d1e863">Comparing the periods 1980–1999 and 2000–2019, total May–October frontal
rainfall has declined at all latitudes north of 38<inline-formula><mml:math id="M60" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S (Fig. 3c).
In SEA (33–38<inline-formula><mml:math id="M61" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S) there has been a statistically significant
decrease in the mean rain rate across all front days, from 0.155  to
0.138 mm h<inline-formula><mml:math id="M62" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (<inline-formula><mml:math id="M63" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>11 %). This accumulates to a 32 mm (9.4 %) decline in total
frontal rainfall per season between the two periods, with larger relative
declines in rainfall further north where average frontal rainfall is
smaller. While this change is not statistically significant (<inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.14</mml:mn></mml:mrow></mml:math></inline-formula>), it
is similar in magnitude to the annual rainfall decline during the Millennium
Drought (Van Dijk et al.,
2013) and to declines in frontal rainfall reported in previous studies
(Risbey et al., 2013b; Pepler et al.,
2021).</p>
      <p id="d1e915">There was a statistically significant decline in frontal rainfall between
1979–1996 and 1997–2009 (<inline-formula><mml:math id="M65" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">14</mml:mn></mml:mrow></mml:math></inline-formula> %, <inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.03</mml:mn></mml:mrow></mml:math></inline-formula>), with a partial recovery during
2010–2019 (9 % below the 1979–1996 period). The 2010–2019 period had very
high variability, with very high frontal rainfall totals during 2010 and
2016 but low totals in other years, which explains the reduced significance
of trends calculated using the later period. Recovery during the later
period occurred mostly in the early season, April–June, with the frontal
rainfall anomaly in July–October during 2010–2019 (<inline-formula><mml:math id="M67" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula> % compared to
July–October 1979–1996) similar to that in 1997–2009 (<inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">17</mml:mn></mml:mrow></mml:math></inline-formula> %).</p>
      <p id="d1e960">This decline is not related to any change in front frequency (Fig. 3b) but
due to a decrease in the average rainfall intensity calculated across all
fronts. This decrease in intensity is due to a decrease in the likelihood
that a front will produce measurable rain in these latitudes (Fig. 3d) and
a corresponding increase in dry fronts, consistent with Pepler et al. (2021); for fronts that produce rainfall, the average rainfall intensity has
not changed (Fig. 3e). The number of fronts per season with rain rates
exceeding 0.1 mm h<inline-formula><mml:math id="M69" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in SEA decreased from 164 to 140 between 1979–1996 and
1997–2009 (<inline-formula><mml:math id="M70" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">14</mml:mn></mml:mrow></mml:math></inline-formula> %, <inline-formula><mml:math id="M71" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>), with little recovery over the recent period of
2010–2019 (145 per season). There is a decrease in the likelihood that a
front will produce rainfall whether or not the front is collocated with a
cyclone. The total accumulated rainfall in the prefrontal region (0 to
<inline-formula><mml:math id="M72" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M73" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) declines by 14 %, which is larger than the rainfall
decline in the postfrontal region (<inline-formula><mml:math id="M74" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula> %). This is in contrast to
Burls et al. (2019), who found that the
largest decline in South African rainfall occurred on postfrontal days.</p>
</sec>
<sec id="Ch1.S4">
  <label>4</label><title>Comparison of wet and dry fronts</title>
      <p id="d1e1033">Given the observed decrease in the proportion of fronts that generate
rainfall, we now investigate how the characteristics of wet and dry fronts
differ during 1980–1999. We define a front as being wet if the average
rain rate over 33–38<inline-formula><mml:math id="M75" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S and within <inline-formula><mml:math id="M76" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M77" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> of the
frontal line is at least 0.1 mm h<inline-formula><mml:math id="M78" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>, which is satisfied by 51 % of
May–October fronts in 1980–1999.</p>
      <p id="d1e1075"><?xmltex \hack{\newpage}?>Wet and dry fronts differ in many aspects (Fig. 4a–f). Wet fronts have
more negative (stronger) vertical velocities at all levels, with the largest
differences in the mid-troposphere (500–700 hPa); stronger cross-front
gradients in temperature as well as meridional wind (not shown); and
stronger relative vorticity, particularly behind the front. These variables
all indicate that rain-bearing fronts are stronger in southeast Australia
than those that produce little rain. Total column water and integrated
vapour transport (not shown) are also higher for rain-bearing fronts at SEA
latitudes as well as to the north, noting that the moisture for rain events
in southeastern Australia is generally sourced from the oceans to the south
(Holgate et al., 2020). Rain-bearing
fronts show a higher prefrontal PC, a measure of baroclinicity, to the
north of 35<inline-formula><mml:math id="M79" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, and lower prefrontal baroclinicity further south.
This decrease in the PC to the south may be explained by consumption of
baroclinicity during rainfall, which leads to even stronger reduction in PC
after the front. On the other hand, higher PC in rain-bearing fronts to the
north of 35<inline-formula><mml:math id="M80" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S promotes stronger moisture uplift.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><?xmltex \currentcnt{4}?><?xmltex \def\figurename{Figure}?><label>Figure 4</label><caption><p id="d1e1099"><bold>(a–f)</bold> Mean (line) and interquartile range (shading) of six variables
at each latitude for May–October fronts in 1980–1999 with rain rates of at
least 0.1 mm h<inline-formula><mml:math id="M81" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at 33–38<inline-formula><mml:math id="M82" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S compared to dry fronts: <bold>(a)</bold> total column
water (<inline-formula><mml:math id="M83" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M84" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> of front); <bold>(b)</bold> difference between maximum and
minimum 700 hPa temperature (<inline-formula><mml:math id="M85" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> of front), indicating
strength of the temperature change; <bold>(c)</bold> prefrontal 700 hPa vertical velocity
(0 to <inline-formula><mml:math id="M87" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M88" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>); <bold>(d)</bold> postfrontal (<inline-formula><mml:math id="M89" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula> to 0<inline-formula><mml:math id="M90" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>)
700 hPa relative vorticity; <bold>(e)</bold> mean prefrontal Phillips criterion (0 to
<inline-formula><mml:math id="M91" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M92" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>), a measure of baroclinicity, with dashed lines showing the
postfrontal medians (<inline-formula><mml:math id="M93" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> to <inline-formula><mml:math id="M94" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M95" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> behind front); <bold>(f)</bold> 700 hPa zonal wind (<inline-formula><mml:math id="M96" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M97" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> of front);  and <bold>(g–l)</bold> like in top row but
for the median and interquartile range of the seasonal mean value across all
fronts in 2000–2019 vs. 1980–1999. Crosses indicate where the two sets are
statistically significantly different for <inline-formula><mml:math id="M98" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula> at that latitude.</p></caption>
        <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023-f04.png"/>

      </fig>

      <p id="d1e1307">While there is only a small difference in mean zonal winds at the latitudes
of interest, in fronts that produce rainfall there are stronger westerlies
north of 33<inline-formula><mml:math id="M99" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S but weaker zonal winds south of 38<inline-formula><mml:math id="M100" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S
(Fig. 4f). This reflects a change in the mean patterns of winds at all
levels, with the strongest relationships between rainfall and zonal winds
found at 700 hPa. For instance, the latitude where 700 hPa zonal winds are
strongest during wet fronts is 34.9<inline-formula><mml:math id="M101" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, 6<inline-formula><mml:math id="M102" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> further north
than for dry fronts (40.9<inline-formula><mml:math id="M103" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S). This means that wet fronts have
strong 700 hPa zonal winds (defined as <inline-formula><mml:math id="M104" display="inline"><mml:mrow><mml:mi>u</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> m s<inline-formula><mml:math id="M105" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>), reaching
25.4<inline-formula><mml:math id="M106" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S on average, and average zonal wind speeds of 10.8 m s<inline-formula><mml:math id="M107" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at
23–27<inline-formula><mml:math id="M108" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S. In contrast, strong westerlies only reach
30.6<inline-formula><mml:math id="M109" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S for dry fronts, and wind speeds near 25<inline-formula><mml:math id="M110" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S are
half as strong (4.7 m s<inline-formula><mml:math id="M111" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). There is also a smaller but statistically
significant difference in the northernmost latitude where any front is
identified in the longitudes 135–150<inline-formula><mml:math id="M112" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, which is 26.5<inline-formula><mml:math id="M113" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S for fronts with rainfall and 27.9<inline-formula><mml:math id="M114" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S for dry fronts.</p>
</sec>
<sec id="Ch1.S5">
  <label>5</label><title>Changes in frontal characteristics</title>
      <p id="d1e1479">Having identified key aspects of fronts that differ between wet and dry
fronts, we now investigate how these have changed between 1980–1999 and
2000–2019 to help identify any changes in frontal mean characteristics that
decrease the likelihood of frontal rainfall.</p>
      <p id="d1e1482">Comparing the average across all fronts in 1980–1999 with fronts in
2000–2019 (Fig. 4g–l), there has been a very small decline (<inline-formula><mml:math id="M115" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1.3</mml:mn></mml:mrow></mml:math></inline-formula> %) in
the average TCW at 33–38<inline-formula><mml:math id="M116" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S on front days, suggesting moisture
availability is unlikely to be a major contributor to changes in frontal
rainfall. Changes in metrics of front intensity at these latitudes such as
the average change in meridional wind speed or change in temperature across
the front line are also very small (<inline-formula><mml:math id="M117" display="inline"><mml:mrow><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:math></inline-formula> %). There is no
statistically significant change in baroclinicity measured by the Phillips
criterion in southeast Australian latitudes, although there is a reduction
to the south. There is a statistically significant decrease (<inline-formula><mml:math id="M118" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">14</mml:mn></mml:mrow></mml:math></inline-formula> %) in the
prefrontal 700 hPa vertical velocity in SEA, coinciding with the latitudes of
the largest rainfall decline (Fig. 4c, i), and a weak, non-significant
increase in postfrontal vertical velocity. There is also a statistically
significant weakening of postfrontal relative vorticity over
33–38<inline-formula><mml:math id="M119" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S (<inline-formula><mml:math id="M120" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>11 %), with larger changes in vorticity over
28–32<inline-formula><mml:math id="M121" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S. While these changes are generally weak and not
necessarily aligned with the latitudes most relevant to our region of
interest, together they are suggestive of an overall weakening of uplift in
the frontal area.</p>
      <p id="d1e1551">There are larger changes in both moisture variables and indicators of
frontal intensity between the two periods at latitudes north of
30<inline-formula><mml:math id="M122" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, including mean meridional wind change (not shown), relative
vorticity, and mean zonal winds. This indicates a weakening of the northward
edge of the front and a southward shift in frontal features. Between
1980–1999 and 2000–2019 there has been no change in the average northernmost
latitude with a detected front. However, the mean northernmost latitude of
zonal winds exceeding 10 m s<inline-formula><mml:math id="M123" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> has shifted from 28.0  to
28.8<inline-formula><mml:math id="M124" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, associated with a 12 % decline in the mean zonal wind
speed at 23–27<inline-formula><mml:math id="M125" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, noting that these two variables are strongly
correlated (<inline-formula><mml:math id="M126" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mo>+</mml:mo><mml:mn mathvariant="normal">0.74</mml:mn></mml:mrow></mml:math></inline-formula>). Associated with the weakening zonal winds, there
has also been a reduction in mean IVT at 28–33<inline-formula><mml:math id="M127" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S (not shown),
indicating a reduction in moisture flux at the northern edge of the front,
although there has been no change in IVT over SEA (33–38<inline-formula><mml:math id="M128" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S).</p>
      <p id="d1e1626">To assess the extent to which various front characteristics can be tied to
changes in frontal rainfall we apply multiple linear regressions between
frontal rainfall and one or more explanatory factors over 1980–1999. We then
apply the regression coefficients to the 2000–2019 period to calculate the
reduction in mean rainfall expected from observed changes in the predictors
and divide this by the observed rainfall change between the two periods to
calculate the proportion of rainfall change explained by those factors. We
found that a single linear regression between mean 700 hPa zonal winds at
23–27<inline-formula><mml:math id="M129" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S and mean frontal rainfall at 33–38<inline-formula><mml:math id="M130" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S over
1980–1999 is able to explain 59 % of the decrease in average frontal
rainfall. The proportion of rainfall decline explained can be increased by
adding either prefrontal vertical velocity (71 %) or TCW (81 %); as TCW
and <inline-formula><mml:math id="M131" display="inline"><mml:mi>w</mml:mi></mml:math></inline-formula> are correlated (<inline-formula><mml:math id="M132" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.42</mml:mn></mml:mrow></mml:math></inline-formula>), there is no additional predictive value from a
three-variable regression. Predictive skill is similar but slightly lower if
we use the northernmost latitude of zonal winds exceeding 10 m s<inline-formula><mml:math id="M133" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> combined
with TCW (71 %). In contrast, single linear regressions with either
vertical velocity (32 %) or TCW (25 %) explain only a small proportion
of the rainfall change.</p>
      <p id="d1e1677">These multiple linear regressions typically underestimate the higher end of
frontal rainfall, as the relationship between frontal rainfall and both
zonal winds and TCW are nonlinear. Fronts with strong westerlies extending
to at least 23<inline-formula><mml:math id="M134" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S have average rain rates over 33–38<inline-formula><mml:math id="M135" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S
more than 3 times higher than fronts where strong westerlies are only
observed up to 30<inline-formula><mml:math id="M136" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S. During 1980–1999, only 27 % of fronts had
westerlies extending to 23<inline-formula><mml:math id="M137" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, but these fronts explained 42 %
of all frontal rainfall over SEA.</p>
      <p id="d1e1716">Between 1979–1996 and 1997–2009, i.e. before and during the Millennium
Drought, there was a 28 % decrease in the frequency of fronts with  strong  700 hPa westerlies extending north of 23<inline-formula><mml:math id="M138" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, as well as a 34 % (54 mm,
<inline-formula><mml:math id="M139" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>) decrease in their accumulated rainfall over SEA (Fig. 5). There
has been little recovery following the Millennium Drought, with frequencies
in 2010–2019 25 % below the 1979–1996 average and rainfall 25 % below
the 1979–1996 average. As there is no overall change in the frequency of
fronts during or after the drought, the decrease in the number of fronts
with strong westerlies north of 23<inline-formula><mml:math id="M140" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S is balanced by an increase in the
frequency of fronts where westerlies are poleward of 23<inline-formula><mml:math id="M141" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, as well as a
corresponding weak increase in associated rainfall (<inline-formula><mml:math id="M142" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mn mathvariant="normal">8</mml:mn></mml:mrow></mml:math></inline-formula> to <inline-formula><mml:math id="M143" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mn mathvariant="normal">13</mml:mn></mml:mrow></mml:math></inline-formula> mm). The
decrease in the frequency of fronts where strong westerlies extend northward of
23<inline-formula><mml:math id="M144" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S is thus sufficient to explain the entirety of the observed
change in frontal rainfall at 33–38<inline-formula><mml:math id="M145" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S during the period since
1997.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><?xmltex \currentcnt{5}?><?xmltex \def\figurename{Figure}?><label>Figure 5</label><caption><p id="d1e1799">The average frequency <bold>(a)</bold> and total accumulated rainfall <bold>(b)</bold> in
33–38<inline-formula><mml:math id="M146" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S for May–October fronts in 1979–1996, 1997–2009,
and 2010–2019, separated by the northernmost latitude where 700 hPa zonal
winds exceed 10 m s<inline-formula><mml:math id="M147" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Each bar shows the total across all fronts, with darker
shading indicating the component from trailing fronts and lighter shading
showing the component from fronts embedded in a cyclone.</p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023-f05.png"/>

      </fig>

      <p id="d1e1835">To test the role of cyclones in this result, we further separated our
analysis between trailing fronts and fronts associated with a cyclone.
Almost half (44 %) of fronts with strong westerly winds extending north of
23<inline-formula><mml:math id="M148" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S had an associated low, which is higher than the frequency of
lows across all fronts (29 %). When comparing 1979–1996 and 1997–2009,
there was a 27 % decline (<inline-formula><mml:math id="M149" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.03</mml:mn></mml:mrow></mml:math></inline-formula>) in rainfall from trailing fronts and a
larger 39 % decline (<inline-formula><mml:math id="M150" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.008</mml:mn></mml:mrow></mml:math></inline-formula>) in rainfall from fronts that <italic>co-occurred</italic> with a
cyclone, indicating that declines in frontal rainfall can in part be linked
to the observed decrease in the frequency of low-pressure systems in this
period (Pepler et al., 2021), as any change in low-pressure systems will also
affect rainfall from embedded fronts. In comparison, the 2010–2019 period
has seen a partial recovery of rainfall from embedded fronts (22 % below
the 1979–1996 average) but no recovery in rain from trailing fronts
(<inline-formula><mml:math id="M151" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">31</mml:mn></mml:mrow></mml:math></inline-formula> %). This may indicate the change in rainfall from trailing fronts is
playing an increasingly large role in overall rainfall declines, although
differences between 1997–2009 and 2010–2019 are not statistically
significant. Meanwhile, for fronts where strong westerly winds are south of
23<inline-formula><mml:math id="M152" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, both those with and without cyclones have increased in
frequency, indicating that the westerly winds are playing a stronger role in
rainfall changes than interactions with cyclones.</p>
</sec>
<sec id="Ch1.S6">
  <label>6</label><title>Links to large-scale circulation</title>
      <p id="d1e1902">While we have demonstrated that declines in rainfall at 33–38<inline-formula><mml:math id="M153" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S
can be explained by a weakening and southward shift in the northern edge of
the front, this raises a subsequent question: given that we have shown no
decrease in the frequency or intensity of fronts such as their 700 hPa
longitudinal temperature gradient, measures of frontal baroclinicity such as
the Phillips criterion, or even the latitude of fronts as identified using a
wind-based front identification scheme, what is the driver of this
weakening? We propose that this is related to changes in the atmospheric
extratropical circulation in the SH.</p>
      <p id="d1e1914">Between 1980–1999 and 2000–2019 there has been a change in MSLP and wind
anomalies suggestive of wave number 3 (Fig. 6a). The strongest anomaly in
the MSLP is observed over the southern Atlantic ocean, associated with an
easterly anomaly in both 700 and 300 hPa winds around 40<inline-formula><mml:math id="M154" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S and
westerly anomaly around 60<inline-formula><mml:math id="M155" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S. Weaker trends towards higher
pressure and easterly wind anomalies are also evident around 100
and 220<inline-formula><mml:math id="M156" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, with corresponding westerly anomalies to the south.
Areas of anticyclonic anomalies are interspersed with cyclonic anomalies,
which are typically slightly poleward. Additional analysis of the meridional
wind showed that these changes act to modify the climatological zonal wave 3
(ZW3), defined as the leading EOF of the monthly meridional wind as in
Goyal et al. (2022) but using 700 hPa where we see the
largest wind change in fronts (Supplement Fig. S1). However, changes to the ZW3 do
not represent a perfect zonal wave possibly due to interactions with other
wave numbers and local forcings; hence, no trend in either intensity or
location of the climatological ZW3 was found. With the exception of very
strong anomalies such as in the southern Atlantic and most northward parts
of the two other anticyclonic anomalies, most of the other changes in the SH
circulation are not statistically significant, including in eastern
Australia (Fig. S2).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6"><?xmltex \currentcnt{6}?><?xmltex \def\figurename{Figure}?><label>Figure 6</label><caption><p id="d1e1946">Anomalies of May–October 300 hPa zonal wind speed (shading, every
0.2 m s<inline-formula><mml:math id="M157" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>), 6-hourly mean sea level pressure (black contours, every 0.5 hPa),
and 700 hPa winds (vectors) between 1980–1999 and 2000–2019 in ERA5 for <bold>(a)</bold> front hours only, <bold>(b)</bold> hours without a front in southeast Australia, and <bold>(c)</bold> seasonal mean change.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://wcd.copernicus.org/articles/4/175/2023/wcd-4-175-2023-f06.jpg"/>

      </fig>

      <p id="d1e1977">This hemispheric wavy pattern of anomalies is still apparent when data are
separated into days with (Fig. 6b) and without (Fig. 6c) a front in
southeast Australia. However, on front days the wave pattern is amplified,
and there are easterly wind anomalies at 700 hPa over northeastern Australia, with weak easterly anomalies extending to 300 hPa, as well as westerly anomalies and below-average pressure to the south of Australia, consistent with
the composites shown in Fig. 4. (We note here that the low-pressure
anomaly to the south of Australia is located further south than the area
that was considered for separation between embedded and trailing fronts.)
The topography of New Zealand then acts as a barrier to the intensified
westerlies around 45<inline-formula><mml:math id="M158" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, with return flow potentially contributing
to the anticyclonic anomaly in the Tasman Sea and therefore the stronger
subtropical easterly anomalies. This pattern of zonal wind anomalies is
weaker or absent on days with no front in SEA, with increasing MSLP over the
Australian Bight and westerly anomalies at 300 hPa over northeast Australia.
This demonstrates a more complex relationship between changes in the mean
state and synoptic anomalies. An anticyclonic anomaly to the east of
Australia on front days suggests Rossby wave breaking, noting that SEA is
known for a high number of Rossby wave breaking events
(de Vries, 2021) and cut-off
lows  (Portmann et al.,
2021).</p>
      <p id="d1e1989">To test the statistical significance of wind changes, we calculated the
average zonal wind anomalies for each latitude band over eastern Australia (135–150<inline-formula><mml:math id="M159" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E). There are no statistically significant changes in
seasonal mean 300 hPa winds between 1980–1999 and 2000–2019 at any latitude,
with weak westerly anomalies (0.3 m s<inline-formula><mml:math id="M160" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) around 25<inline-formula><mml:math id="M161" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, easterly
anomalies (<inline-formula><mml:math id="M162" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.35</mml:mn></mml:mrow></mml:math></inline-formula> m s<inline-formula><mml:math id="M163" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) around 30–35<inline-formula><mml:math id="M164" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, and
stronger westerly anomalies southward (Fig. 6a). This mean pattern
combines very different patterns over eastern Australia between days with
and without fronts, which had trends of opposite signs over most of
20–40<inline-formula><mml:math id="M165" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S. In contrast to the mean change, there was a weak
subtropical easterly anomaly on front days, averaging <inline-formula><mml:math id="M166" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.4</mml:mn></mml:mrow></mml:math></inline-formula> m s<inline-formula><mml:math id="M167" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> over
20–25<inline-formula><mml:math id="M168" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, in agreement with an anticyclonic anomaly to the east of
Australia. Subtropical anomalies are more consistent at 700 hPa with a mean
zonal wind change of <inline-formula><mml:math id="M169" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.6</mml:mn></mml:mrow></mml:math></inline-formula> m s<inline-formula><mml:math id="M170" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at 20–25<inline-formula><mml:math id="M171" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, which is stronger for
front days (<inline-formula><mml:math id="M172" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.8</mml:mn></mml:mrow></mml:math></inline-formula> m s<inline-formula><mml:math id="M173" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>, <inline-formula><mml:math id="M174" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.08</mml:mn></mml:mrow></mml:math></inline-formula>) than for non-front days (<inline-formula><mml:math id="M175" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.4</mml:mn></mml:mrow></mml:math></inline-formula> m s<inline-formula><mml:math id="M176" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>).</p>
</sec>
<sec id="Ch1.S7">
  <label>7</label><title>Drivers of interannual variability</title>
      <p id="d1e2193">To test the role of major climate drivers in observed changes, we calculated
the detrended correlations during May–October between several climate indices and the total number of fronts in SEA, as well as several metrics of frontal winds or rainfall (Table 1). The overall frequency of
fronts is negatively correlated with the intensity and position of the
subtropical ridge, with fewer fronts when the ridge is strong or shifted to
the south, noting that cold fronts are typically linked to the storm tracks
and westerlies and are less likely to be identified in easterly wind regimes
to the north of the ridge. These correlations are a result of very strong
negative correlations between both indices (STRI and STRP) and the frequency
of wet fronts, with weaker positive correlations between the STR and dry
fronts. The STR is also very strongly correlated with the average
northernmost latitude of strong westerlies for fronts and the number of
fronts with strong westerlies north of 23<inline-formula><mml:math id="M177" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S. However, it is only
weakly correlated with the seasonal mean zonal winds at 20–25<inline-formula><mml:math id="M178" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S,
with stronger negative correlations between STRI and zonal winds between
26–35<inline-formula><mml:math id="M179" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S. This may indicate a role of the STR in keeping frontal
westerlies south and thus influencing frontal rainfall; however, the STR
itself is also influenced by pressure variations associated with synoptic
systems, so the relationship may be more complex.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e2226">Detrended Pearson's correlations between front frequency, rainfall,
and the northernmost latitude with 700 hPa zonal wind <inline-formula><mml:math id="M180" display="inline"><mml:mrow><mml:mo>≥</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> m s<inline-formula><mml:math id="M181" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>  (strong winds) and six climate indices for May–October, 1979–2019
(1982–2019 for DMI and NINO3.4). Also shown are the partial correlations for
NINO3.4 and DMI. Bold indicates significance for <inline-formula><mml:math id="M182" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.93}[.93]?><oasis:tgroup cols="9">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:colspec colnum="9" colname="col9" align="right"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Variable</oasis:entry>
         <oasis:entry colname="col2">STRI</oasis:entry>
         <oasis:entry colname="col3">STRP</oasis:entry>
         <oasis:entry colname="col4">SOI</oasis:entry>
         <oasis:entry colname="col5">NINO3.4</oasis:entry>
         <oasis:entry colname="col6">DMI</oasis:entry>
         <oasis:entry colname="col7">SAM</oasis:entry>
         <oasis:entry colname="col8">NINO3.4<inline-formula><mml:math id="M183" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">DMI</mml:mi></mml:msub></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col9">DMI<inline-formula><mml:math id="M184" display="inline"><mml:msub><mml:mi/><mml:mrow><mml:mi mathvariant="normal">NINO</mml:mi><mml:mn mathvariant="normal">3.4</mml:mn></mml:mrow></mml:msub></mml:math></inline-formula></oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Front days</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M185" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.53</bold></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M186" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.58</bold></oasis:entry>
         <oasis:entry colname="col4">0.28</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M187" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.19</oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M188" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.19</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M189" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.12</oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M190" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.13</oasis:entry>
         <oasis:entry colname="col9"><inline-formula><mml:math id="M191" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.09</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Total front rainfall</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M192" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.66</bold></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M193" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.53</bold></oasis:entry>
         <oasis:entry colname="col4"><bold>0.56</bold></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M194" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.40</bold></oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M195" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.68</bold></oasis:entry>
         <oasis:entry colname="col7">0.08</oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M196" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.11</oasis:entry>
         <oasis:entry colname="col9"><inline-formula><mml:math id="M197" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.62</bold></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Number of wet fronts</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M198" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.76</bold></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M199" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.65</bold></oasis:entry>
         <oasis:entry colname="col4"><bold>0.56</bold></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M200" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.42</bold></oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M201" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.60</bold></oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M202" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.01</oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M203" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.17</oasis:entry>
         <oasis:entry colname="col9"><inline-formula><mml:math id="M204" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.53</bold></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Number of dry fronts</oasis:entry>
         <oasis:entry colname="col2"><bold>0.34</bold></oasis:entry>
         <oasis:entry colname="col3">0.18</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M205" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.35</bold></oasis:entry>
         <oasis:entry colname="col5">0.28</oasis:entry>
         <oasis:entry colname="col6"><bold>0.48</bold></oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M206" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.09</oasis:entry>
         <oasis:entry colname="col8">0.04</oasis:entry>
         <oasis:entry colname="col9"><bold>0.45</bold></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Average northernmost latitude of <inline-formula><mml:math id="M207" display="inline"><mml:mrow><mml:mi>U</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>≥</mml:mo></mml:mrow></mml:math></inline-formula> 10 m s<inline-formula><mml:math id="M208" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M209" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.78</bold></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M210" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.65</bold></oasis:entry>
         <oasis:entry colname="col4"><bold>0.57</bold></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M211" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.36</bold></oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M212" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.67</bold></oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M213" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.08</oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M214" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.04</oasis:entry>
         <oasis:entry colname="col9"><inline-formula><mml:math id="M215" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.63</bold></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Number of fronts with strong winds north of 23<inline-formula><mml:math id="M216" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M217" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.73</bold></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M218" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.60</bold></oasis:entry>
         <oasis:entry colname="col4"><bold>0.51</bold></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M219" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.30</oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M220" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.65</bold></oasis:entry>
         <oasis:entry colname="col7">0.02</oasis:entry>
         <oasis:entry colname="col8">0.03</oasis:entry>
         <oasis:entry colname="col9"><inline-formula><mml:math id="M221" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.62</bold></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Number of fronts with strong winds south of 23<inline-formula><mml:math id="M222" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S</oasis:entry>
         <oasis:entry colname="col2"><bold>0.38</bold></oasis:entry>
         <oasis:entry colname="col3">0.22</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M223" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula><bold>0.34</bold></oasis:entry>
         <oasis:entry colname="col5">0.17</oasis:entry>
         <oasis:entry colname="col6"><bold>0.55</bold></oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M224" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.10</oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M225" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.13</oasis:entry>
         <oasis:entry colname="col9"><bold>0.56</bold></oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

      <p id="d1e2860">There were no statistically significant correlations between the seasonal
mean SAM and front frequency or rainfall, which may be a consequence of the
large intraseasonal variability in SAM. There was also no correlation
between fronts and NINO3.4 after accounting for covariations with DMI, with
the stronger correlations with SOI potentially due to interactions between
the Indian Ocean Dipole and sea level pressure at Darwin. Interestingly,
however, while DMI was not strongly correlated with the seasonal frequency
of fronts, it had a very strong correlation with both total frontal rainfall
and the frequency of wet fronts, which was independent of any effect of
ENSO. Notably, the three seasons with the highest total frontal rainfall
during the period all occurred during negative IOD conditions (1992, 2010,
and 2016), and the three seasons with lowest frontal rainfall occurred under
positive IOD (1982, 1994, and 2006).</p>
      <p id="d1e2864">While the link between IOD and frontal rainfall could in part be associated
with increases in moisture from the tropics, the IOD was also associated
with a shift in the average northernmost latitude of strong frontal
westerlies, consistent with the extratropical pathway of IOD impacts
(Cai et al., 2011) and the link between the IOD and the mean
westerlies in southeast Australia  (Pepler et
al., 2014). Given that the IOD is most active in spring, the influence of
IOD on the Australian rainfall is strongest during spring (e.g. Cai et al.,
2011). The correlation between the DMI and total frontal rainfall also
strengthens from <inline-formula><mml:math id="M226" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.39</mml:mn></mml:mrow></mml:math></inline-formula> during May–July to <inline-formula><mml:math id="M227" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.65</mml:mn></mml:mrow></mml:math></inline-formula> during August–October. In
both seasons negative IOD is associated with an increased frequency of wet
fronts and a northward shift in frontal westerlies but no significant
change in the total number of fronts.</p>
      <p id="d1e2887">These results show that wet and dry fronts can have very different
relationships with climate drivers, resulting in the weaker relationships
that have previously been identified between front frequency and DMI (Rudeva
and Simmons, 2015). Negative Indian Ocean Dipole events and a weaker
subtropical ridge (negative STRI) allow front-related westerlies to extend
further north, resulting in an increased frequency of wet fronts, although
statistically significant correlations between these drivers and the
seasonal mean zonal wind are only identified south of 26<inline-formula><mml:math id="M228" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S. Note
that the DMI is correlated with both the intensity (<inline-formula><mml:math id="M229" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mn mathvariant="normal">0.58</mml:mn></mml:mrow></mml:math></inline-formula>) and position
(<inline-formula><mml:math id="M230" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mn mathvariant="normal">0.32</mml:mn></mml:mrow></mml:math></inline-formula>) of the subtropical ridge during this season, so these
relationships are not independent, and an equatorward shift in fronts may
itself cause changes in the pressure fields which are used to calculate the
STR.</p>
      <p id="d1e2919">During the period 1979–2019, there has been a weak increasing trend in the
intensity of the subtropical ridge, of 0.26 hPa per decade (<inline-formula><mml:math id="M231" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.09</mml:mn></mml:mrow></mml:math></inline-formula>), consistent
with longer-term increases over the historical record (Timbal and
Drosdowsky, 2013). This may partially explain the observed trends in wet
fronts: while there is a statistically significant linear trend in the
number of wet fronts over 1979–2019 (<inline-formula><mml:math id="M232" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.92</mml:mn></mml:mrow></mml:math></inline-formula> fronts per year, <inline-formula><mml:math id="M233" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.03</mml:mn></mml:mrow></mml:math></inline-formula>), this trend
becomes weaker and nonsignificant after removing variability associated with
the subtropical ridge intensity (<inline-formula><mml:math id="M234" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.35</mml:mn></mml:mrow></mml:math></inline-formula> fronts per year). Similarly, while there was
a <inline-formula><mml:math id="M235" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.4</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M236" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> per decade linear trend in the average northernmost latitude
with  <inline-formula><mml:math id="M237" display="inline"><mml:mrow><mml:mi>U</mml:mi><mml:mn mathvariant="normal">700</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M238" display="inline"><mml:mrow><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>=</mml:mo></mml:mrow></mml:math></inline-formula> 10 m s<inline-formula><mml:math id="M239" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (<inline-formula><mml:math id="M240" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>), removing variability associated
with STRI decreased this trend to <inline-formula><mml:math id="M241" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.2</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M242" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> per decade (<inline-formula><mml:math id="M243" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.06</mml:mn></mml:mrow></mml:math></inline-formula>).</p>
</sec>
<sec id="Ch1.S8">
  <label>8</label><title>Changes in fronts in southwest Western Australia</title>
      <p id="d1e3069">The very strong easterly anomalies at 700 and 300 hPa identified over
southwest Western Australia in Fig. 6 raise the question of whether
changes in the background zonal winds are also playing a role in rainfall
declines in this region. Similar to southeast Australia, SWWA
(110–120<inline-formula><mml:math id="M244" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W) has seen little decrease in the frequency of fronts
between 1980–1999 and 2000–2019 but a statistically significant 11 %
(38 mm) decrease in total frontal rainfall, particularly prefrontal rainfall
(<inline-formula><mml:math id="M245" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">21</mml:mn></mml:mrow></mml:math></inline-formula> %), which is linked to a decrease in the frequency of rain-bearing
fronts (Fig. S3). The average differences between wet and dry fronts are
also similar between the two regions, with the most significant change
relevant to frontal rainfall observed in the zonal winds to the north of
SWWA (Fig. S4). Consistent with SEA, there has been a 21 % decrease
in the frequency of fronts in SWWA with strong 700 hPa westerlies extending
north of 23<inline-formula><mml:math id="M246" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S and a 44 mm (<inline-formula><mml:math id="M247" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">23</mml:mn></mml:mrow></mml:math></inline-formula> %) decline in associated
rainfall, which explains the entirety of the observed decline in frontal
rainfall. The extratropical circulation on SWWA front days resembles the
zonal wave 3 pattern shown for SEA in Fig. 6b, with the low-pressure
anomaly to the south of Australia shifted westward (Fig. S5). While most
of the decline in frontal rainfall in SWWA can also be attributed to fronts
with westerlies reaching at least 23<inline-formula><mml:math id="M248" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, the decline over time is
more linear than SEA, with lower frontal rainfall during 2010–2019 than
1997–2009 (Fig. S6).</p>
</sec>
<sec id="Ch1.S9" sec-type="conclusions">
  <label>9</label><title>Discussion and conclusions</title>
      <p id="d1e3127">Frontal rainfall is influenced by a large number of factors, including
available moisture (e.g. TCW) and frontal dynamics (e.g. temperature/wind
change, vertical velocity, and relative vorticity). This is consistent with
other studies  (Solari et al., 2022) and suggests that
changes in any of these variables could result in changes in frontal
rainfall. However, while the frequency of rain-bearing fronts is decreasing
during the cool season in many parts of the Southern Hemisphere
midlatitudes, including in southeast Australia, this decrease is occurring
despite little change in front frequency (Burls et
al., 2019; Pepler et al., 2021; Risbey et al., 2013b), as well as little
change in metrics of frontal moisture or traditional measures of front
intensity beyond a slight weakening of average prefrontal vertical velocity
and postfrontal vorticity.</p>
      <p id="d1e3130">There has been no observed change in the mean latitude of tracked fronts in
southeast Australia during the cold season, consistent with previous studies
(e.g. Rudeva and Simmonds 2015), despite decreases in the frequency of
associated cyclones. However, if the northernmost edge of the front is
instead defined as the northernmost latitude with strong westerly winds,
here defined as 700 hPa zonal winds <inline-formula><mml:math id="M249" display="inline"><mml:mrow><mml:mo>≥</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> m s<inline-formula><mml:math id="M250" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>, we see a
0.8<inline-formula><mml:math id="M251" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> southward shift in the mean equatorward extent of fronts over
this period. We find a particularly strong decline in the frequency of
fronts with strong westerlies north of 23<inline-formula><mml:math id="M252" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, which were
responsible for 42 % of frontal rainfall at 33–38<inline-formula><mml:math id="M253" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S between
1980–1999. This highlights an aspect of frontal intensity and associated
rainfall that is worthy of further research and may be relevant for other
regions of the Southern Hemisphere. There has also been a decrease in the
overall intensity of the subtropical westerlies over eastern Australia and
many other areas of the Southern Hemisphere, consistent with
Simmons (2022), although the trend in the mean
state is weaker than on front days.</p>
      <p id="d1e3182">Frontal winds and rainfall have shown little recovery since the end of the
Millennium Drought and may be part of a longer-term decline in cool season
rainfall over this region. While the total decrease in rainfall from fronts
is relatively small – a 9.4 % decline in frontal rainfall from 1980–1999 to
2000–2019 in southeast Australia – even small changes in rainfall can be
magnified to much larger changes in streamflow and corresponding
hydrological impacts. This was seen during the Millennium Drought, when a
11 % decline in total annual rainfall was magnified to a 46 % decline in
streamflow in southeast Australia (Van Dijk et al., 2013).
Changes in frontal rainfall may potentially play an important role in these
declines, as fronts contribute strongly to the number of days with low to
moderate rainfall intensity  (Pepler et al., 2020), and the
number of rain days is an important predictor of streamflow changes in
southeast Australia  (Fu et al., 2021). Consequently,
any continuation of declines in frontal rainfall over the coming decades may be
of critical importance in catchments where runoff has yet to recover after
the Millennium Drought  (Peterson et al., 2021).</p>
      <p id="d1e3185">The link identified in this paper between subtropical wind changes and
changes in frontal rainfall is a statistical link and would require further
modelling studies to understand the dynamical interaction between
subtropical winds and rainfall <inline-formula><mml:math id="M254" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M255" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> further south.
However, there are a number of potential mechanisms. The southward shift in
frontal westerlies could simply be an indication of a southward shift in the
latitude at which fronts occur, which would suggest that the front detection
method based on wind changes is deficient at detecting the equatorward
extent of cold fronts and subtle changes at these latitudes. However, front
detection methods based on other variables such as temperature gradients
also do not identify any changes in frontal frequency
(Pepler et al., 2021; Berry et al., 2011).
Another potential mechanism is a link between weakening subtropical
westerlies and a reduction in atmospheric moisture flux into the region;
while there has been little change in total column water or IVT in SEA, both
TCW and IVT have decreased in the region of 28–33<inline-formula><mml:math id="M256" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S associated with
the weakening subtropical winds. Finally, while we found only a weak change
in vertical velocity and no significant change in PC, changes in other
factors such as convective inhibition or the level of condensation in a
warming climate could also reduce the ability of fronts to generate
rainfall, particularly during the cool season and moderate rain events where
convection is weak   (Rasmussen et al., 2020).</p>
      <p id="d1e3216">Timbal and Drosdowsky (2013) identified an
intensification of the subtropical ridge during the early 21st century,
which they proposed as a major cause of rainfall declines in southeast
Australia during the years 1997–2009. This decline has continued, with the
average intensity of the May–October subtropical ridge at 140–150<inline-formula><mml:math id="M257" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E increasing by 0.26 hPa per decade over the period 1979–2019. There has also
been an increase in the mean sea level pressure and a weakening of the
background zonal wind speeds in subtropical Australia. We find that the
northern edge of the front and the likelihood of fronts producing rainfall
show strong statistical relationships with the intensity and position of the
subtropical ridge, suggesting a possible link between trends in pressure and
frontal rainfall. A link between decreasing frontal rain and increasing
pressure was also identified by  Burls et
al. (2019) in southern Africa. However, the nature of this relationship
depends on the location of the subtropical high, and mechanisms may differ on
frontal and non-frontal days. We also found that frontal rainfall is
favoured during negative IOD conditions, consistent with
Lawrence et al. (2022), and that IOD has a
stronger influence on frontal rainfall than frequency. While robust trends
cannot be calculated for the IOD over this short time period, palaeoclimate
data indicate that positive IOD events may be becoming more common
(Abram et al., 2020).</p>
      <p id="d1e3228">An alternate explanation could be due to links between the mid-tropospheric
frontal westerlies and the strength or location of the subtropical jet. In
contrast to the observed strengthening of the subtropical ridge, there have
been no robust trends identified in the Southern Hemisphere subtropical jet
(Maher et al., 2019). However, a weakening of
700 hPa zonal winds between 20–35<inline-formula><mml:math id="M258" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S during July was also
identified for southeast and southwest Australia by
Osbrough and Frederiksen (2021), which they
linked to decreases in July baroclinicity and rainfall in southern
Australia. Our analysis also indicates no change in the latitude of the
subtropical jet (not shown) but a possible weakening of its intensity on
front days in eastern Australia, although the average change in zonal wind
speed is smaller at 300 hPa than it is at 700 hPa. The mean state changes in
Figs. 6 and S1 are also indicative of a modification of the ZW3 in the
Southern Hemisphere, which has been associated with rainfall variability in
parts of southeast Australia but has no clear trend in the cool season
(Campitelli et al., 2021).</p>
      <p id="d1e3240">The strong link between frontal rainfall and changes in the subtropical
700 hPa westerlies was tested for a second region that has experienced
declines in cool season frontal rainfall, southwest Western Australia, with
remarkably similar results. Easterly 300 hPa wind anomalies and 850 hPa
moisture flux in the subtropics have also been noted during dry winters in
South Africa  (Mahlalela et al., 2019),
which is another region which has experienced decreases in winter rainfall
(Sousa et al., 2018; Burls et al.,
2019) and weakening of the subtropical westerlies between 1980–1999 and
2000–2019. These results raise the question of what role changes in
subtropical zonal winds may be playing in frontal rainfall in other areas of
the Southern Hemisphere. Future work will develop a more generalisable
approach to investigate how the northern extent of frontal westerlies is
changing in other parts of the Southern Hemisphere, as well as how this is
likely to change in the future climate given the projected poleward shift in
the storm tracks and the edge of the Hadley cell  (Lee et al., 2021).
This may provide a potential avenue to reconcile projected declines in cool season rainfall across Southern Hemisphere midlatitude regions
(Lee et al., 2021) with the
lack of change projected in frontal frequency
(Catto et al., 2014).</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability"><title>Data availability</title>

      <p id="d1e3247">The merged front datasets for SEA and SWWA are available online at
<ext-link xlink:href="https://doi.org/10.6084/m9.figshare.20453325.v1" ext-link-type="DOI">10.6084/m9.figshare.20453325.v1</ext-link> (Pepler, 2022). The front composites were
developed using ERA5 data, which are freely available from the Copernicus
Climate Change Service Climate Data Store at
<ext-link xlink:href="https://doi.org/10.24381/cds.bd0915c6" ext-link-type="DOI">10.24381/cds.bd0915c6</ext-link>  (Hersbach et al., 2018).</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e3257">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/wcd-4-175-2023-supplement" xlink:title="pdf">https://doi.org/10.5194/wcd-4-175-2023-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e3266">ASP and IR jointly conceived the study and methodology. AP performed most analyses and visualisation, with IR contributing EOF analysis for Fig. S1. ASP wrote the original draft, which both authors reviewed and edited.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e3272">At least one of the (co-)authors is a member of the editorial board of <italic>Weather and Climate Dynamics</italic>. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.</p>
  </notes><notes notes-type="disclaimer"><title>Disclaimer</title>

      <p id="d1e3281">Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>
  </notes><?xmltex \hack{\newpage}?><ack><title>Acknowledgements</title><p id="d1e3288">We thank Sugata Narsey, Pandora Hope, and two anonymous
reviewers for their comments that have improved this paper.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e3293">This work has been supported by the Victorian Department of Environment, Land, Water and Planning through the Victorian Water and Climate Initiative  and has used computing resources from the National Computational Infrastructure.</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e3299">This paper was edited by Shira Raveh-Rubin and reviewed by two anonymous referees.</p>
  </notes><ref-list>
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