ming cai department of earth, ocean, and atmospheric science, florida state university
DESCRIPTION
Why is the Stratosphere More Predictable and What are the Implications for Seasonal Predictions of the Troposphere?. Ming Cai Department of Earth, Ocean, and Atmospheric Science, Florida State University. Acknowledgement: Huug M. van den Dool, Qin Zhang - PowerPoint PPT PresentationTRANSCRIPT
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Why is the Stratosphere More Predictable and What are the Implications for Seasonal
Predictions of the Troposphere?
Ming CaiDepartment of Earth, Ocean, and Atmospheric Science,
Florida State University
Acknowledgement: Huug M. van den Dool, Qin Zhang Rongcai Ren, Chul-Su Shin, and YY-Yu
Grant Support: NOAA CPO: NA10OAR4310168
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Outline• Motivation and theoretical background.
• Observational evidence linking tropical-extratropical coupling coupling to meridional mass circulation and its variability.
• Modeling evidence of high predictability of the stratosphere beyond the two-week limit.
• Mass circulation variability and cold air outbreaks in winter seasons
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Motivation and theoretical background
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Sources of Prediction Skill • NWP: initial value problem. Rossby waves and
baroclinic system => chaotic nature => inherent predictability (1-2 weeks).
• NWP+lower boundary forcing: “forced” problems Internal variability often is as large as the forced anomalies, particularly in the absence of large SST anomalies (e.g. non ENSO years) and over the regions where prominent atmospheric internal modes are present at all time scale =>the forecasts of the “forced” anomalies are indecisive.
• New Source: Global mass circulation => The extratropics is connected to the tropics via stratosphere: => Much a longer time scale.
Timely and zonally averaged circulation in pressure/height coordinates
N S
From ECMWF ERA-40 Atlas
EQ
Pre
ssur
e (h
Pa)
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Mean meridional mass circulation in winter hemisphere (Cai and Shin 2013)
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Vertical and meridional couplings by baroclinically amplifying (westward tilting)
waves (Johnson 1989)
• A net poleward (adiabatic) transport of warm air mass aloft and a net equatorward (adiabatic) transport of cold air mass transport below.
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Westward tilting waves and meridional mass transport
Johnson (1979) and Townsend and Johnson (1985)
Less mass
More mass
More mass
Less massA net warm air
transport polewardat upper layers
A net cold air transport
equatorward at lower layers
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Observational evidence linking tropical-extratropical coupling to meridional mass circulation and its variability (derived from
NCEP/NCAR reanalysis:1979-2003)
Cai (2003, GRL)Cai and Ren (2006, GRL)Ren and Cai (2006, AAS)Cai and Ren (2007, JAS)Ren and Cai (2007, GRL)
1984-88
1979-83
1989-93
1994-98
1998-03
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Daily time series of NH Polar vortex oscillation +NAM
-NAM/SSW
69% variance of NHdaily PV anomalies
Time
A see-saw pattern betweenmid-lat. and high-lat., &between polar stratosphere and polar troposphere.
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Meridional propagation of thermal anomalies
Lead day of PVO index (-60 ~60)
10mb
20mb
50mb
100mb
150mb
200mb
250mb
300mb
500mb
850mb
925mb
1000mb
Upper layers totally in the ST
Middle layers across the Tropopause
Troposphere
10 hPa
20 hPa
50 hPa
100 hPa
150 hPa
200 hPa
250 hPa
300 hPa
500 hPa
850 hPa
925 hPa
1000 hPa
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Downward Propagation of thermal Downward Propagation of thermal anomaliesanomalies
Lead day of PVO index (-60 ~60)
10N 20N 30N 40N
50N 60N 80N70N10 N
50 N
20 N
60 N
30 N
70 N
40 N
80 N
heig
ht
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Summary of theoretical background:
•Stratospheric annular mode variability is intimately associated with variability of the stratospheric part of the warm air branch mass circulation. •Positive phase corresponds to the state of a weaker meridional mass circulation whereas the negative phase results from a stronger meridional mass circulation.•Presence of large-amplitude westward titling waves leads to a stronger poleward mass transport.•Limited meridional scale of westward titling waves results in successive poleward progress of stronger poleward mass transport => slow time scale of annular mode variability.
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Implications for stratosphere predictions:
A numerical model may still have a good skill in predicting stratospheric annular mode variability even when it already loses its skill in predicting the exact locations of individual planetary-scale waves, as long as it can retain the amplitude and westward tilting of these waves.
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NCEP CFSv2 Prediction Skill for Stratospheric Variability
(Zhang, Shin, van den Dool, and Cai 2013)
Day 1 through Day 90 forecastsfor the period from January 1,
1999 to December 2010
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Forecast evaluation procedure•Remove annual cycle of CFSv2 reanalysis (observation) from CFSv2 daily forecasts at all lead times. •Consider Temperature anomalies at 50 hPa (T50 stratosphere) and 500 hp (T500, troposphere). •Verify anomalies of CFSv2 CFSv2 forecasts against anomalies of CFS reanalysis (observations).•Use either map correlation for temporal-spatial field or temporal correlation for time series of anomalies to measure the skill of CFSv2 (AC > 0.5 reliable forecasts and AC > 0.3 useful forecasts)•Calculate the same skill for “persistence forecasts”. The gain of CFSv2 skill over persistence forecasts measures the usefulness of CFSv2 forecasts.
Overall skill (map AC)NH SH
Forecast lead time (days)
T500
T50
T500
T50
15days 18days
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Seasonal dependency of CFSv2 skill over polar stratosphere
NH SH
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1st 4 EOF modes of daily T50 anomalies
23.4% 18.6%
13.4% 5.2%
NH only
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AC
ski
ll of
pre
dict
ions
of P
Cs
of E
OF1
-4
24 36
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Temporal evolution of zonal mean of T50 anomalies
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CFSv2 skill in predicting zonal mean of T50 anomalies
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Gain of CFSv2 over persistence forecasts
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Summary (1)• The NCEP CFSv2 still has a remarkable prediction skill of polar stratospheric
temperature anomalies at the lead time of 30 days whereas its counterpart in the troposphere at 500 hPa drops very quickly and below the 0.3 level at 12 days. We also prove that the CFSv2 has a high prediction skill both in an absolute sense and in terms of gain over persistence except in the equatorial region where the skill mainly comes from the persistence of the QBO signal.
• In particular, the CFSv2 is capable of predicting mid-winter polar stratosphere sudden warming events in the Northern Hemisphere and the timing of the final warming polar stratosphere warming in both hemispheres 3-4 weeks in advance.
• The remarkable skill comes from the signal of systematic poleward propagation of thermal anomalies from the equator to the pole in the stratosphere associated with the global mass circulation variability (intensity/time scale).
• As long as the westward tilting of planetary waves in the stratosphere and their overall amplitude can be captured, the CFSv2 forecasts would still be very skillful in predicting zonal mean anomalies even though it cannot do so for the exact locations of planetary waves and their spatial scales.
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Mass circulation variability and cold air outbreaks in winter seasons
Cai (2003, GRL)Cai and Ren (2007, JAS)
Cai and Yu (2013)
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Meridional propagation (Cai and Ren 2007) P
olew
ard
prop
agat
ion
in
the
stra
tosp
here
Equ
ator
war
d pr
opag
atio
n in
tro
posp
here
2 Periods
40 days
70 days
60N
25N
90N
Stronger Meridional Mass Circulation
Mass circulation variability and cold air outbreaks in the mid-latitudes
Warmair
Cold air
60N
25N
90N
Weaker Meridional Mass Circulation
WarmairCold
air
Less cold air outbreaks in mid-latitudesColdness in high latitudes
More cold air outbreaks in mid-latitudesWarmness in high latitudes
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Indices of mass circulation (1) Total mass flux into polar cap in the warm air branch(2) Total mass flux out of polar cap in the cold air branch(3) Total mass flux into polar cap in the stratosphere
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Indices of coldness and warmnessColdness indices(1) Percentage of area occupied by negative temperature
anomalies below n*standard_deviation (local) in high latitude zone (60 N poleward) and mid-latitudes (between 25 and 60N), with n = 0, 0.5, 1, 1.5, 2.0 etc..
(2) The areal mean of temperature anomalies below n*standard_deviation (local) in high latitude zone (60 N poleward) and mid-latitudes (between 25 and 60N), with n = 0, 0.5, 1, 1.5, 2.0 etc..
Warmness indices: same as coldness indices except for positive temperature anomalies above n*standard_deviation (local).
The results with n = 0 are representative
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Exa
mpl
e of
circ
ulat
ion
and
tem
pera
ture
indi
ces
(afte
r rem
ovin
g th
eir a
nnua
l cyc
les)
Area
Amp.
Masscirculation
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Exa
mpl
e of
lead
/lag
corr
elat
ion
betw
een
circ
ulat
ion
and
tem
pera
ture
indi
ces
Lag days of warm air branch MV
Lag days of Stratosphere MV
High Lat. Mid-latitudes
Lag days of Stratosphere MV
Lag days of warm air branch MV
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Stratosphere mass circulation versus warm/cold air branch circulations
Lag days of Stratosphere MV Lag days of Stratosphere MV
Warmair
branch
Coldair
branch
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Stratosphere mass circulation versus temperature indices
Coldness area indices
Lag days of Stratosphere MV Lag days of Stratosphere MV
Warmness area indices
> 60N 25-60N > 60N 25-60N
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Stratosphere mass circulation versus temperature indices
Coldness area indices (n =1) Warmness area indices (n=1)
> 60N 25-60N > 60N 25-60N
Lag days of Stratosphere MV Lag days of Stratosphere MV
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Stratosphere mass circulation versus temperature indicesHigh Lat. Mid Lat.
Coldness
Warmness
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Summary (2)• Variability of mass flux into polar stratosphere is synchronized with
that of warm air branch and cold air branch.
• Surface temperature anomalies in winter seasons are intimately coupled with the timing/intensity of global mass circulation variability.
• Lack of warm air into polar stratosphere is accompanied by weaker equatorward advancement of cold air near the surface. As a result, the cold air mass is largely imprisoned within polar circle, responsible for general warmness in mid-latitudes and below climatology temperature in high latitudes.
• Stronger warm air into polar stratosphere is accompanied by stronger equatorward advancement of cold air near the surface, resulting in massive cold air outbreaks in mid-latitudes and warmth in high latitudes.
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A hybrid forecasting strategy for intraseasonal cold season climate predictions (14 - 60? days)
• Prognostic component: Dynamical prediction for (extratropic) stratospheric anomalies using CFS
• Diagnostic component: Statistical “instantaneous” relations between stratospheric and surface temperature anomalies (downscaling)
• Potential products:1.Likelihood of series and severe winter storms in a
time span of a few weeks over a continental domain.2.Mild versus cold winter season.3.Timing of the coldest period (“early” versus “late”
winter).