Linking Seasonal Teleconnection Patterns to Winter Climate Variability in the Southern Appalachian Mountains

Authors: Montana Eck*, Appalachian State University, Baker Perry, Appalachian State University, Peter Soulé, Appalachian State University, Johnathan Sugg, Appalachian State University, Douglas Miller, University of North Carolina Asheville
Topics: Climatology and Meteorology, Mountain Environments, Physical Geography
Keywords: Climate variability, climate change, mountain geography, ENSO, NAO
Session Type: Paper
Day: 4/12/2018
Start / End Time: 10:00 AM / 11:40 AM
Room: Galerie 6, Marriott, 2nd Floor
Presentation File: No File Uploaded

Recognized as an anomalous region regarding climate change, this study identifies long-term trends and variation of temperature and snowfall during climatological winter (DJF) from 1910 to 2017. The identification of several teleconnection patterns, namely ENSO, NAO, and PDO, allow for further understanding of how this region has remained a climatic anomaly. Results of this study indicate that the southern Appalachian Mountains have experienced a statistically significant long-term cooling trend since the early 20th century, with recent decades suggesting a reversal of this cooling. Snowfall is characterized by high interannual variability, with the 1960s and 1970s producing anomalously high amounts of snowfall. Several atmospheric forcing couplings are identified that align with anomalous conditions in the region. Most notably, negative temperature anomalies and higher snowfall amounts are frequently found during moderate El Niño and negative NAO seasons, with the opposite being true during strong La Niña and positive NAO winters. The influence of these teleconnection patterns is spatially dependent, with areas east of the Blue Ridge Escarpment highly dependent on the phase of ENSO, whereas higher elevations and western slopes favor the NAO. The identification of these pattern couplings is critical to not only improving understanding of the anomalous climate of the southern Appalachian Mountains but also in enhancing seasonal forecasting and predicting future climate change in the region.

Abstract Information

This abstract is already part of a session. View the session here.

To access contact information login