Indicators and trends of polar cold airmass

Trends and variations in the amount of cold airmass in the Arctic and the Northern Hemisphere are evaluated for the 60 year period, 1959–2018. The two indicators are (1) polar cold air mass (PCAM), which is the amount of air below a potential temperature threshold, and (2) negative heat content (NHC...

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Bibliographic Details
Published in:Environmental Research Letters
Main Authors: Yuki Kanno, John E Walsh, Muhammad R Abdillah, Junpei Yamaguchi, Toshiki Iwasaki
Format: Article in Journal/Newspaper
Language:English
Published: IOP Publishing 2019
Subjects:
Q
Online Access:https://doi.org/10.1088/1748-9326/aaf42b
https://doaj.org/article/ed7642dcf12f469e9242417131afd583
Description
Summary:Trends and variations in the amount of cold airmass in the Arctic and the Northern Hemisphere are evaluated for the 60 year period, 1959–2018. The two indicators are (1) polar cold air mass (PCAM), which is the amount of air below a potential temperature threshold, and (2) negative heat content (NHC), which includes a weighting by coldness. Because the metrics of coldness are based on multiple layers in the atmosphere, they provide a more comprehensive framework for assessment of warming than is provided by surface air temperatures alone. The negative trends of PCAM and NHC are stronger (as a % per decade) when the threshold is 245 K rather than 280 K, indicating that the loss of extremely cold air is happening at a faster rate than the loss of moderately cold air. The loss of cold air has accelerated, as the most rapid loss of NHC has occurred in recent decades (1989–2018). The spatial patterns of the trends of PCAM and NHC provide another manifestation of Arctic amplification. Of the various teleconnection indices, the Atlantic Multidecadal Oscillation shows the strongest correlations with the spatially integrated metrics of moderate coldness. Several Pacific indices also correlate significantly with these indicators. However, the amount of extremely cold air mass does not correlate significantly with the indices of internal variability used here.