An investigation of some unexpected frost day increases in southern Australia

Dittus, Andrea J.; Karoly, David J.; Lewis, Sophie C.; Alexander, Lisa V.

doi:10.22499/2.6404.002

Cited by 16 publications

(15 citation statements)

References 19 publications

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“…An indication of a climatological explanation for the positive DTR trend is the simultaneously observed negative PRCP trend. Several authors have described a negative correlation between DTR and PRCP trends (Dittus et al, 2014;Jaswal et al, 2016;Zhou et al, 2009). Hence, the observations in the Altiplano would be in accordance with these findings.…”

Section: Discussionsupporting

confidence: 83%

Effects of undetected data quality issues on climatological analyses

et al. 2018

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Abstract. Systematic data quality issues may occur at various stages of the data generation process. They may affect large fractions of observational datasets and remain largely undetected with standard data quality control. This study investigates the effects of such undetected data quality issues on the results of climatological analyses. For this purpose, we quality controlled daily observations of manned weather stations from the Central Andean area with a standard and an enhanced approach. The climate variables analysed are minimum and maximum temperature and precipitation. About 40 % of the observations are inappropriate for the calculation of monthly temperature means and precipitation sums due to data quality issues. These quality problems undetected with the standard quality control approach strongly affect climatological analyses, since they reduce the correlation coefficients of station pairs, deteriorate the performance of data homogenization methods, increase the spread of individual station trends, and significantly bias regional temperature trends. Our findings indicate that undetected data quality issues are included in important and frequently used observational datasets and hence may affect a high number of climatological studies. It is of utmost importance to apply comprehensive and adequate data quality control approaches on manned weather station records in order to avoid biased results and large uncertainties.

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Section: Discussionsupporting

confidence: 83%

Effects of undetected data quality issues on climatological analyses

et al. 2018

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“…Figure 10 shows an extended timeseries of mean minimum temperatures across southeastern Australian stations (see Table S1) for May to August between 1885 and 2016, using stations with historical and modern data in the region displaying the strongest relationship between Tn and STRI. There has been a long-term increase in minimum temperatures over the past century, but the rate of increase has slowed somewhat in recent decades, consistent with Figure 9a and Dittus et al (2015). As was shown in Figure 9b, when the relationship with the coincident increase in regional pressure is removed, the observed increase in mean minimum temperatures during recent decades is stronger.…”

Section: Relationship Between Stri and Changes In Cool Winter Nights supporting

confidence: 82%

“…Data homogeneity is another potential explanation. Crimp et al (2018b) used the unhomogenised SILO data set (Jeffrey et al 2001), whereas this study (and Dittus et al 2015) use the homogenised ACORN-SAT data set (Trewin 2013(Trewin , 2018. Whilst post-1960 differences in minimum temperatures between unhomogenised and homogenised data sets are small at the national scale (Fawcett et al 2012), in inland southeastern Australia they are substantial, largely because a substantial number of sites in the region moved from towns to (generally cooler) out-of-town locations during the 1990s and early 2000s.…”

Section: Discussionmentioning

confidence: 99%

“…An increase in intensity of the STR in recent decades has been associated with decreases in southeast Australian rainfall (Timbal and Drosdowsky 2013), and has been proposed as a driver in the observed increase in frost days in parts of this region (Dittus et al 2015;Crimp et al 2016). The observed increase in frost days in the southeast has occurred despite the overall annual trend towards warmer minimum temperatures and a decrease in cold extremes on a national scale (Alexander and Arblaster 2017).…”

Section: Introductionmentioning

confidence: 99%

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The relationship between the subtropical ridge and Australian temperatures

Pepler¹,

Ashcroft²,

Trewin³

2018

JSHESS

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The intensity and latitude of the subtropical ridge over eastern Australia is strongly associated with southeast Australian rainfall, particularly during the cool months of the year. We show that the subtropical ridge also exerts a strong influence on temperatures across much of Australia, with warmer daytime temperatures and more warm extremes across southern Australia when the subtropical ridge is stronger than average, which is largely independent of the relationship between the subtropical ridge and rainfall. A strong subtropical ridge is also linked to warmer than average minimum temperatures over southern Australia throughout much of the year, except from May to August when a strong ridge is associated with cooler mean minimum temperatures and an increased frequency of cool nights. This relationship, and the observed strengthening of the subtropical ridge during autumn and winter in recent decades, can partially explain the weaker warming trends in minimum temperatures in southeast Australia compared to elsewhere in the country over the period 1960-2016.

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“…While it is generally accepted that a warmer atmosphere will lead to higher atmospheric moisture content and heavier extreme precipitation globally, there are a number of locations where a prior belief that this expectation applies locally could lead to an incorrect conclusion about anthropogenic influence on climate events at regional scales. Some specific examples include projected declines in extreme rainfall in the parts of the sub-tropics associated with tropical circulation changes (Kharin et al 2013;Pfahl et al 2017), observed winter rainfall in the southwest of Australia, which is already showing significant declines due to climate change (Delworth and Zeng 2014), record low October rainfall in October 2015 in Tasmania, Australia , and recent unexpected increases in frost risk in some parts of southern Australia (Dittus et al 2014). …”

Section: The Role Of Hypothesis Testingmentioning

confidence: 99%

Is the choice of statistical paradigm critical in extreme event attribution studies?

2017

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The science of event attribution meets a mounting demand for reliable and timely information about the links between climate change and individual extreme events. Studies have estimated the contribution of human-induced climate change to the magnitude of an event as well as its likelihood, and many types of event have been investigated including heatwaves, floods, and droughts. Despite this progress, such approaches have been criticised for being unreliable and for being overly conservative. We argue that such criticisms are misplaced. Rather, a false dichotomy has arisen between Bconventional^approaches and new alternative framings. We have three points to make about the choice of statistical paradigm for event attribution studies. First, different approaches to event attribution may choose to occupy different places on the conditioning spectrum. Providing this choice of conditioning is communicated clearly, the value of such choices depends ultimately on their utility to the user concerned. Second, event attribution is an estimation problem for which either frequentist or Bayesian paradigms can be used. Third, for hypothesis testing, the choice of null hypothesis is context specific. Thus, the null hypothesis of human influence is not inherently a preferable alternative to the usual null hypothesis of no human influence.

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An investigation of some unexpected frost day increases in southern Australia

Cited by 16 publications

References 19 publications

Effects of undetected data quality issues on climatological analyses

Effects of undetected data quality issues on climatological analyses

The relationship between the subtropical ridge and Australian temperatures

Is the choice of statistical paradigm critical in extreme event attribution studies?

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