TY - JOUR
T1 - Which Sudden Stratospheric Warming Events Are Most Predictable?
AU - Chwat, Dvir
AU - Garfinkel, Chaim I.
AU - Chen, Wen
AU - Rao, Jian
N1 - Publisher Copyright:
© 2022. The Authors.
PY - 2022/9/27
Y1 - 2022/9/27
N2 - The predictability of Northern Hemisphere sudden stratospheric warming (SSW) events is considered in 10 subseasonal to seasonal (S2S) forecast models for 16 major SSWs that have occurred since 1998, a larger sample size than has been considered by previous works. The four factors that most succinctly distinguish those SSWs with above average predictability are a preconditioned vortex prior to the SSW, an active Madden-Julian Oscillation with enhanced convection in the West Pacific, the Quasi-Biennial Oscillation phase with easterlies in the lower stratosphere, and the vortex morphology (displacement more predictable). Two of these factors appear to not have been considered in previous works focusing on a large sample of events. Most of these effects are not statistically significant at the 95% level due to the still relatively small sample size, though all would exceed a 90% criteria at least marginally. Combined, however, they account for 40% of the inter-event spread in SSW predictability, thus indicating that SSWs with favorable precursors are significantly more predictable.
AB - The predictability of Northern Hemisphere sudden stratospheric warming (SSW) events is considered in 10 subseasonal to seasonal (S2S) forecast models for 16 major SSWs that have occurred since 1998, a larger sample size than has been considered by previous works. The four factors that most succinctly distinguish those SSWs with above average predictability are a preconditioned vortex prior to the SSW, an active Madden-Julian Oscillation with enhanced convection in the West Pacific, the Quasi-Biennial Oscillation phase with easterlies in the lower stratosphere, and the vortex morphology (displacement more predictable). Two of these factors appear to not have been considered in previous works focusing on a large sample of events. Most of these effects are not statistically significant at the 95% level due to the still relatively small sample size, though all would exceed a 90% criteria at least marginally. Combined, however, they account for 40% of the inter-event spread in SSW predictability, thus indicating that SSWs with favorable precursors are significantly more predictable.
KW - ENSO
KW - MJO
KW - subseasonal predictability
KW - sudden warmings
UR - http://www.scopus.com/inward/record.url?scp=85138857683&partnerID=8YFLogxK
U2 - 10.1029/2022JD037521
DO - 10.1029/2022JD037521
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C2 - 36248185
AN - SCOPUS:85138857683
SN - 2169-897X
VL - 127
JO - Journal of Geophysical Research: Atmospheres
JF - Journal of Geophysical Research: Atmospheres
IS - 18
M1 - e2022JD037521
ER -