Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology †

• Main Authors: W. Troy Baisden, Keller, Elizabeth D., Hale, Robert Van, Frew, Russell D., Wassenaar, Leonard I.
• Format: Text
• Language: unknown
• Published: Taylor & Francis 2016
• Subjects: Neuroscience; 59999 Environmental Sciences not elsewhere classified; FOS Earth and related environmental sciences; 39999 Chemical Sciences not elsewhere classified; FOS Chemical sciences; Ecology; FOS Biological sciences; 20199 Astronomical and Space Sciences not elsewhere classified; FOS Physical sciences; Sociology; FOS Sociology; 69999 Biological Sciences not elsewhere classified; Plant Biology; Antarctic; New Zealand; Antarc*
• Online Access: https://dx.doi.org/10.6084/m9.figshare.3204544; https://tandf.figshare.com/articles/journal_contribution/Precipitation_isoscapes_for_New_Zealand_enhanced_temporal_detail_using_precipitation_weighted_daily_climatology/3204544

Predictive understanding of precipitation δ 2 H and δ 18 O in New Zealand faces unique challenges, including high spatial variability in precipitation amounts, alternation between subtropical and sub-Antarctic precipitation sources, and a compressed latitudinal range of 34 to 47 °S. To map the precipitation isotope ratios across New Zealand, three years of integrated monthly precipitation samples were acquired from >50 stations. Conventional mean-annual precipitation δ 2 H and δ 18 O maps were produced by regressions using geographic and annual climate variables. Incomplete data and short-term variation in climate and precipitation sources limited the utility of this approach. We overcome these difficulties by calculating precipitation-weighted monthly climate parameters using national 5-km-gridded daily climate data. This data plus geographic variables were regressed to predict δ 2 H, δ 18 O, and d-excess at all sites. The procedure yields statistically-valid predictions of the isotope composition of precipitation (long-term average root mean square error (RMSE) for δ 18 O = 0.6 ‰; δ 2 H = 5.5 ‰); and monthly RMSE δ 18 O = 1.9 ‰, δ 2 H = 16 ‰. This approach has substantial benefits for studies that require the isotope composition of precipitation during specific time intervals, and may be further improved by comparison to daily and event-based precipitation samples as well as the use of back-trajectory calculations.