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# High Spatial Resolution Prediction of Tritium (3H) in Contemporary Global Precipitation

Three best-fitting multiple regression models were found to accurately predict 3H in global annual precipitation. All models had a high degree of confidence and accuracy, whether the model was (i) global, (ii) extratropical or (iii) tropical (supplementary SM1 material). The most parsimonious multiple regression predictive models were:

$${text{Global}},^{{3}} {text{H }} ,left( {{text{TU}}} right) , = , 0.0313{text { wLT }} + , 2.56 , 10^{{ – {6}}} , {text{DTC }} , {-} , 0.2077{text{ AT }} + ,6,2068{text{ LMF }}+, 0.0056{text{ LONG }}-, 0.0279{text{ NLR }}+, {61}. {3961}$$

(1)

which is a first global model resulting in an R2= 0.79 (p3H-distributions9.24. The significant response from wLT asserted the need to specifically consider the differences between the northern and southern hemispheres in the distribution of their land masses. However, the global model (Eq. 1) did not perform as well in tropical and low latitude regions. As a result, it has been beneficial to develop the regional extra-tropical and secondary tropical models (see Discussion in23):

$${text{Extratropical}},^{{3}} {text{H }} , = , – 0.2505{text{ AT }} + , 8.0153{text{ LMF }} + , { 3}.0{4 ,1}0^{{ – {6}}}, {text{ DTC }} + , 0.0053{text{LONG }} + , 0.0176{text{ wLT}} ,{-} ,0.0011{text{ ALT }} + ,71.7114$$

(2)

giving an R2= 0.81 (p3H production rate and substantial dilution by3H tropical ocean moisture sources:

$${text{Tropical}},^{{3}} {text{H }} ,= , 0.0513{text{ wLT }} + , 2.2882{text{LMF }} + , 0.0061{text{ AT }}{-} , 0.0399{text{ OLR }} ,{-} , 0.059{text{ CPN }} + , 0.0003{text { PP }} + , { 9}. {3437}$$

(3)

which gave an R2 = 0.62, p 3H data was available, RCWIP clusters were calculated with the appropriate regionalized regression equations. For clusters with 3Due to lack of data, the tropical and extra-tropical models were used to replace the global model. The resulting prediction models were applied and merged for each 0.1 × 0.1 degree grid cell using fuzzy clustering climate zone membership fractions.22to create a single unified prediction map of 3H in the annual global precipitation (Fig. 1).