North Atlantic Climate Variability from Labrador and Greenland Tree Rings

Authors: Brendan Buckley*, Lamont-Doherty Earth Observatory, Rhys Parfitt, Woods Hole Oceanographic Institute, Caroline Ummenhofer, Woods Hole Oceanographic Institute, Kyle Hansen, Lamont-Doherty Earth Observatory
Topics: Climatology and Meteorology, Canada, Paleoenvironmental Change
Keywords: dendroclimatology, Labrador, Greenland, North Atlantic, spruce, birch
Session Type: Paper
Day: 4/6/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Marshall East, Marriott, Mezzanine Level
Presentation File: No File Uploaded


We present a recently updated spruce tree ring network from Labrador that reveals strong connections to North Atlantic climate variability. Along with ring width (RW) we developed Blue Intensity (BI) from latewood (LW) from each site collection, to derive maximum latewood density (LWBI). We also introduce a Greenland birch RW collection from 1999, allowing a look at climate across the Labrador Sea and insights into long-term trends. New analyses show wintertime (Jan-April) significant correlations for RW with precipitation, temperature and mean sea level pressure (MSLP), but not for LWBI. Consistency between these signals suggests a dynamic driver such as increasing strength of the winter storm track. We interpret the strong correlation between RW and Jan-April MSLP as possible forcing from the January Pacific North American mode of variability. For May-September, RW exhibits its strongest correlation with precipitation, however a lack of consistency between precipitation, temperature and MSLP suggests this relationship is less dynamically driven during summer compared with winter. LWBI exhibits the strongest correlation with summer (May-September) temperature and MSLP, but the relationship is weak with precipitation. Prior studies note that RW and LWBI differ in sensitivity to precipitation or temperature, where LWBI is more connected to late summer temperature and RW is more responsive to spring and early summer temperature. We explore the possibility to distinguish seasonal rainfall and temperature by analyzing these two parameters.

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