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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

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Ming cai department of earth ocean and atmospheric science florida state university

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

Rongcai Ren, Chul-Su Shin, and YY-Yu

Grant Support: NOAA CPO: NA10OAR4310168


Outline

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


Motivation and theoretical background

Motivation and theoretical background


Sources of prediction skill

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.


Ming cai department of earth ocean and atmospheric science florida state university

Timely and zonally averaged circulation in pressure/height coordinates

From ECMWF ERA-40 Atlas

Pressure (hPa)

S

N

EQ


Mean meridional mass circulation in winter hemisphere cai and shin 2013

Mean meridional mass circulation in winter hemisphere (Cai and Shin 2013)


Vertical and meridional couplings by baroclinically amplifying westward tilting waves johnson 1989

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.


Westward tilting waves and meridional mass transport

Upper

level

A net warm air

transport poleward

at upper layers

Less mass

More mass

A net cold air

transport

equatorward

at lower layers

Middle level

More mass

Less mass

Lower

level

high

cold

low

warm

high

Westward tilting waves and meridional mass transport

Johnson (1979) and Townsend and Johnson (1985)


Ming cai department of earth ocean and atmospheric science florida state university

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)


Daily time series of nh polar vortex oscillation

+NAM

-NAM/SSW

Daily time series of NH Polar vortex oscillation

69% variance of NH

daily PV anomalies

1979-83

1984-88

1989-93

1994-98

A see-saw pattern between

mid-lat. and high-lat., &

between polar stratosphere and polar troposphere.

1998-03

Time


Meridional propagation of thermal anomalies

10mb

150mb

500mb

200mb

850mb

20mb

50mb

250mb

925mb

300mb

1000mb

100mb

Lead day of PVO index (-60 ~60)

Meridional propagation of thermal anomalies

Upper layers totally in the ST

Middle layers across the Tropopause

Troposphere

150 hPa

500 hPa

10 hPa

200 hPa

850 hPa

20 hPa

250 hPa

925 hPa

50 hPa

300 hPa

1000 hPa

100 hPa


Downward propagation of thermal anomalies

30N

10N

20N

40N

50N

70N

60N

80N

Lead day of PVO index (-60 ~60)

Downward Propagation of thermal anomalies

10 N

20 N

30 N

40 N

height

50 N

60 N

70 N

80 N


Ming cai department of earth ocean and atmospheric science florida state university

  • 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.


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.

Implications for stratosphere predictions:


Ming cai department of earth ocean and atmospheric science florida state university

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


Ming cai department of earth ocean and atmospheric science florida state university

  • 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.


Ming cai department of earth ocean and atmospheric science florida state university

Overall skill (map AC)

SH

NH

T50

T50

T500

15days

T500

18days

Forecast lead time (days)


Ming cai department of earth ocean and atmospheric science florida state university

Seasonal dependency of CFSv2 skill over polar stratosphere

SH

NH


Ming cai department of earth ocean and atmospheric science florida state university

18.6%

23.4%

NH only

1st 4 EOF modes of daily T50 anomalies

13.4%

5.2%


Ming cai department of earth ocean and atmospheric science florida state university

17

AC skill of predictions of PCs of EOF1-4

11

24

36


Ming cai department of earth ocean and atmospheric science florida state university

Temporal evolution of zonal mean of T50 anomalies


Ming cai department of earth ocean and atmospheric science florida state university

CFSv2 skill in predicting zonal mean of T50 anomalies


Ming cai department of earth ocean and atmospheric science florida state university

Gain of CFSv2 over persistence forecasts


Summary 1

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.


Mass circulation variability and cold air outbreaks in winter seasons

Mass circulation variability and cold air outbreaks in winter seasons

Cai (2003, GRL)Cai and Ren (2007, JAS)

Cai and Yu (2013)


Meridional propagation cai and ren 2007

40 days

70 days

Meridional propagation (Cai and Ren 2007)

Poleward propagation in the stratosphere

Equatorward propagation in troposphere

2 Periods


Ming cai department of earth ocean and atmospheric science florida state university

Mass circulation variability and cold air outbreaks in the mid-latitudes

Weaker Meridional Mass

Circulation

Stronger Meridional Mass

Circulation

90N

90N

Warm

air

Warm

air

60N

60N

Cold

air

Cold

air

25N

25N

Less cold air outbreaks in mid-latitudes

Coldness in high latitudes

More cold air outbreaks in mid-latitudes

Warmness in high latitudes


Indices of mass circulation

  • Total mass flux into polar cap in the warm air branch

  • Total mass flux out of polar cap in the cold air branch

  • Total mass flux into polar cap in the stratosphere

Indices of mass circulation


Indices of coldness and warmness

  • Coldness indices

  • 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..

  • 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..

Indices of coldness and warmness

Warmness indices: same as coldness indices except for positive temperature anomalies above n*standard_deviation (local).

The results with n = 0 are representative


Ming cai department of earth ocean and atmospheric science florida state university

High-Lat

Mid-Lat

Area

Example of circulation and temperature indices

(after removing their annual cycles)

Amp.

Mass

circulation


Ming cai department of earth ocean and atmospheric science florida state university

High Lat.

Mid-latitudes

Example of lead/lag correlation between

circulation and temperature indices

Lag days of warm air branch MV

Lag days of warm air branch MV

Lag days of Stratosphere MV

Lag days of Stratosphere MV


Stratosphere mass circulation versus warm cold air branch circulations

Stratosphere mass circulation versus warm/cold air branch circulations

Warm

air

branch

Cold

air

branch

Lag days of Stratosphere MV

Lag days of Stratosphere MV


Stratosphere mass circulation versus temperature indices

Stratosphere mass circulation versus temperature indices

Coldness area indices

Warmness area indices

> 60N 25-60N

> 60N 25-60N

Lag days of Stratosphere MV

Lag days of Stratosphere MV


Stratosphere mass circulation versus temperature indices1

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


Stratosphere mass circulation versus temperature indices2

Stratosphere mass circulation versus temperature indices

High Lat. Mid Lat.

Coldness

Warmness


Summary 2

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.


A hybrid forecasting strategy for intraseasonal cold season climate predictions 14 60 days

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:

    • Likelihood of series and severe winter storms in a time span of a few weeks over a continental domain.

    • Mild versus cold winter season.

    • Timing of the coldest period (“early” versus “late” winter).


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