Return to search

Tracking the moisture sources of storms at Barrow, Alaska| Seasonal variations and isotopic characteristics

<p> Enhanced warming and increasingly ice-free Arctic seas affect Arctic precipitation. We investigate increased Arctic precipitation due to declining sea ice by relating variations in moisture sources to stable isotope compositions of precipitation. We develop a novel method for deriving moisture sources using condensation profiles derived from cloud radar measurements to formulate initial heights for air mass back trajectories. This method was used to locate the moisture sources of seventy Barrow, AK storm events between 2009 and 2013. Trajectories were calculated by NOAA's HYSPLIT, using GDAS reanalysis wind fields. We demonstrate that the moisture source migrates with season, from distal in winter to proximal in summer. Moisture source dew point exhibits a semiannual cycle, with summer and winter maxima. The spring minimum reflects the reintroduction of the Arctic source. The autumn dew point minimum reflects pre-ice ocean cooling locally. 36% of isotopic variation is statistically explained by a combination of the moisture source dew point and trajectory cooling. Transport distance and path both influence the best descriptor of isotopic composition. For local events, dew point is the stronger influence on isotopic composition, explaining 21% of variance. For distal events, the effects of trajectory cooling supersedes the moisture source signal. The orographic effect of the Alaskan and Brooks ranges account for the influence of trajectory path on isotopic composition. Local moisture events during transition seasons were slightly enriched relative to distal events. If we measure further isotopic enrichment during future transition seasons, it may reflect increased contributions from the Arctic source and thus precipitation increase. Deuterium excess reflects various combinations of latitude, sea surface temperature and relative humidity. Moisture source dew point significantly but weakly predicts storm-specific d-excess. Similar analyses can be performed across the Arctic if reanalysis data can generate reliable condensation profiles. To evaluate the efficacy of condensation profiles produced by reanalysis data, we compared the condensation profiles derived from cloud radar to those from reanalysis. On average, reanalysis produced condensation profiles with mean cloud height 1.4 times higher than those from cloud radar. The greater elevation bias translated into a more distal, and thus warmer and drier, moisture source.</p>

Identiferoai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:1553179
Date17 April 2014
CreatorsPutman, Annie L.
PublisherDartmouth College
Source SetsProQuest.com
LanguageEnglish
Detected LanguageEnglish
Typethesis

Page generated in 0.0021 seconds