Controls on the stable isotope composition of daily precipitation in Sydney Australia: 9 years of daily data, including Radon-222.
	
J. Crawford[footnoteRef:1], C. Hughes, S. Chambers [1:  Corresponding author. Tel: +61 2 9717 3885, Fax: +61 2 9717 9260; e-mail: Jagoda.Crawj=ford@ansto.gov.au] 

ANSTO, Locked Bag 2001 Kirrawee DC NSW 2232, Australia








Figure S1: Agreement between the stable isotope composition of weekly samples and precipitation weighted daily samples for the corresponding week. The red dots indicate the outliers that were removed. 

Figure S2: Wind roses at Lucas Heights.


 

Figure S3: Distributions of δ18O and δ2H (in daily sampled data), vertical bars represent the histogram of the measured data, the blue shading is the normal distribution, with the same mean and standard deviation as that observed.


Figure S4: Distributions of selected variables by month of year, for the period of this study.




Figure S5: Correlation δ18O with selected variables (BT = back trajectory).


Figure S6: Correlation between δ2H and rainfall amount, per stability category, by season.

Figure S7: Mean Sea Level pressure maps corresponding to stability categories 0 to 4, for all year.

Figure S8: Mean Sea Level pressure maps corresponding to stability categories 0 to 4, for autumn.

Figure S9: Mean Sea Level pressure maps corresponding to stability categories 0 to 4, for winter.

Figure S10: Mean Sea Level pressure maps corresponding to stability categories 0 to 4, for spring.



Figure S11: Isotopic composition by stability category, by season. Top row summer, then autumn, winter, and spring. 

Table S1: LMWLs for daily data, using the different least squares approaches. OLSR - ordinary least squares regression, RMA – reduced major axis regression, MA – major axis regression. When “PW” is used it is the precipitation weighted regression. The p-value indicates that all slopes are significantly different from the OLSR slope.
	 
	N
	Slope
	Standard error of Slope
	Intercept
	Standard error of Intercept
	p-value

	OLSR
	807
	7.39
	0.08
	11.89
	0.34
	 

	RMA
	807
	7.77
	0.08
	13.03
	0.34
	0.00

	MA
	807
	8.16
	0.09
	14.19
	0.36
	0.00

	PWLSR
	807
	7.82
	0.07
	14.44
	0.37
	0.00

	PWRMA
	807
	8.04
	0.07
	15.54
	0.37
	0.00

	PWMA
	807
	8.27
	0.07
	16.64
	0.38
	0.00



Table S2: LMWLs for weekly data, using the different least squares approaches. OLSR - ordinary least squares regression, RMA – reduced major axis regression, MA – major axis regression. When “PW” is used it is the precipitation weighted regression. The p-value indicates that all slopes are significantly different from the OLSR slope.
	 
	N
	Slope
	Standard error of Slope
	Intercept
	Standard error of Intercept
	p-value

	OLSR
	504
	7.28
	0.09
	11.69
	0.39
	 

	RMA
	504
	7.56
	0.09
	12.61
	0.39
	0.03

	MA
	504
	7.83
	0.09
	13.53
	0.41
	0.00

	PWLSR
	504
	7.83
	0.08
	14.96
	0.42
	0.00

	PWRMA
	504
	8.03
	0.08
	15.88
	0.42
	0.00

	PWMA
	504
	8.22
	0.08
	16.80
	0.43
	0.00



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