Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology †
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 preci...
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ftdatacite:10.6084/m9.figshare.3204544 2023-05-15T13:48:22+02:00 Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology † W. Troy Baisden Keller, Elizabeth D. Hale, Robert Van Frew, Russell D. Wassenaar, Leonard I. 2016 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 unknown Taylor & Francis https://dx.doi.org/10.1080/10256016.2016.1153472 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY 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 Text article-journal Journal contribution ScholarlyArticle 2016 ftdatacite https://doi.org/10.6084/m9.figshare.3204544 https://doi.org/10.1080/10256016.2016.1153472 2021-11-05T12:55:41Z 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. Text Antarc* Antarctic DataCite Metadata Store (German National Library of Science and Technology) Antarctic New Zealand |
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DataCite Metadata Store (German National Library of Science and Technology) |
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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 |
spellingShingle |
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 W. Troy Baisden Keller, Elizabeth D. Hale, Robert Van Frew, Russell D. Wassenaar, Leonard I. Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology † |
topic_facet |
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 |
description |
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. |
format |
Text |
author |
W. Troy Baisden Keller, Elizabeth D. Hale, Robert Van Frew, Russell D. Wassenaar, Leonard I. |
author_facet |
W. Troy Baisden Keller, Elizabeth D. Hale, Robert Van Frew, Russell D. Wassenaar, Leonard I. |
author_sort |
W. Troy Baisden |
title |
Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology † |
title_short |
Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology † |
title_full |
Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology † |
title_fullStr |
Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology † |
title_full_unstemmed |
Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology † |
title_sort |
precipitation isoscapes for new zealand: enhanced temporal detail using precipitation-weighted daily climatology † |
publisher |
Taylor & Francis |
publishDate |
2016 |
url |
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 |
geographic |
Antarctic New Zealand |
geographic_facet |
Antarctic New Zealand |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
https://dx.doi.org/10.1080/10256016.2016.1153472 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.6084/m9.figshare.3204544 https://doi.org/10.1080/10256016.2016.1153472 |
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1766249183058067456 |