Predictability of the Arctic Oscillation From Stratospheric Influences in Operational Forecasts

Junsu Kim1, Arun Kumar2, and Thomas Reichler1

(1 Univ. of Utah, 2 NOAA)

http://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index

Questions

• To what extent do current prediction systems exploit stratospheric signals?

• How much practical skill is associated with it?

• How important is a good stratospheric component?

2

• Hindcasts or retrospective forecasts, Hamill et al. (2006, BAMS)

• Fixed 1998 version of NCEP/GFS, T62• Low-top: L28, 7 levels above 100, top @ 2.5 hPa• 1979 – present, daily forecasts out to day 15• 15-member ensemble

+daily forecasts; each SSW event is captured

˗ forecasts go only out to day 15

˗ no data on stratospheric levels are archived

NOAA/CDC Reforecasts

3

Validation

• Against NCEP/NCAR reanalysis• Ensemble means• Northern Annular Mode (NAM) derived from

– Sea level pressure (SLP) → AO– Z850, 700, 500, 250, and 150 → NAMx

SLP errors

5

Day 1

4

13

JFM AMJ JAS OND

• Reforecasts were bias-corrected as a function of lead time and day of year

Reforecast Climatology Drift

Case Study: Winter 2004

JAN1 FEB1 MAR1

Day 8.5 Day 14.5Day 0.5

6

AO

NCEP/NCAR reanalysis

NAM index by level and day

range 1 sdevNNR CDC

Strong SSW EventsReanalysis (1979-2007)

• NAM10<-3 → 16 events

• Discard 6 events which exhibit no downward propagation

• → 10 strong events

Reforecasts

• Reduced amplitudes

• Basic patterns are retained

7

Day 15 Forecasts (EM)Reanalysis

Days after event

SSW Composite10 strong events

NCEP/NCAR Reanalysis

8

Day 15

Day 0

Day 10

Day 5

SSW Composite

9

Reforecasts

Co

rre

latio

nLagged Correlation AO (61 days, centered at day 19)

NAM10 / AO

Evolution

Ind

ex

Days after SSW event

Composite NAM/AO Index

Reforecast signal arrives too late (ca. 10 days) at surface

NAM10 reanalyses

AOreanalyses

AOreforecasts day 15

Basic PredictabilityACCSLP vs. AO

ACCSLP

AOAO

Winter

11

AO Predictability

Day

of

year

Lead time (day)

r12

• 1979-2007• Shading: Daily

correlations• Contours: Monthly

running means• Increased

predictability in winter• Low predictability in

summer• Fast decline in spring;

final warmings?• Gradual increase in

fall

Correlation: Reanalysis vs. Reforecastr=0.6

Correlation Anomalies Index

130

Correlations

SSW 0

-10

-20

-30

10

20

30

NAM10 reanalyses

AO reforecasts

AO reanalyses

AO Predictability During SSWs

t [days]

Composite of 10 SSWs

31 days AO r(reanalysis; reforecasts)

Anomalies: February climatology removed

Enhanced AO predictability at longer leads and after SSW event

Conclusion• Despite low stratospheric resolution (7 levels), reforecasts

show skill in simulating downward propagating signals

• These signals arrive too late at surface with the delay increasing with lead time

• SSW events improve AO predictability 0-15 days after the event and at leads of 8-15 days

• Beside the 10 SSW events examined here, additional skill from stratospheric influences may be realized during other warm events or during cold events