strides, steps and stumbles in the march of the seasons 1.astronomical signal, processed by earth...

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Strides, steps and stumbles in the march of the seasons 1. Astronomical signal, processed by Earth 2. Earthly data sets, processed by computer 3. Strides: annual, semiannual 4. Steps: Asian monsoon onset, Americas MSD 5. Stumbles (a.k.a. “singularities”) the US January Thaw Brazil rain Software demo (DVD available - ask)

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Page 1: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Strides, steps and stumbles in the march of the seasons

1. Astronomical signal, processed by Earth2. Earthly data sets, processed by computer3. Strides: annual, semiannual4. Steps: Asian monsoon onset, Americas MSD5. Stumbles (a.k.a. “singularities”)

• the US January Thaw• Brazil rain

• Software demo (DVD available - ask)

Page 2: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

High frequency aspects of the mean seasonal cycle

Brian Mapes

University of Miami

Page 3: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Seasonality: the forcing

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Page 4: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Astronomical forcing(spherical Earth, circular orbit)

solstice equinox solsticeequinox

Page 5: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Temporal Fourier spectrum of annual insolation

sin(2t/365d)Annual

sin(4t/365d)Semiannual

no forcing, just internal

nonlinearitites

Page 6: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Annual cycle signal processing(by the Earth)

heating

Cloud, albedo

temperature

Heat capacity

pressuregravity

windrotation

evaporation, advectionhumidity

vertical motioncloud

micro-physics

precip

Page 7: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Annual cycle signal processing (by the computer)

1. Form mean daily climatologies: var (365 calendar days; lat, lon, level, dataset)

2. Compute mean, annual + semiannual harmonics

mean, 2 amplitudes, 2 phases

3. Residual is called “HF” HF = climatology - annual - semiannual

4. Wavelet analysis of HF {dates, periods, amplitudes, significances of HF events}

Page 8: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Wavelet example

Paul wavelet •Sharp time localization broad in frequency•Real part: max/min•Imaginary part: rise/fall(Torrence and Compo 1998 BAMS)

Page 9: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Signal processed. Now what??Fourier and wavelet coefficients form a

supplement (index) to climatology.

This doubles the size of the data set.

?? What to do with all this information ??interactive GUI visualization tool

Page 10: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Outline of examples1. Annual

– “Easy” (local, thermal): Tsfc

– Nonlocal: Z250 (jet streams)

2. Semiannual– Nonlinear: angular momentum and u250

– Statistical: 250mb eddy activity

3. Ter-annual and beyond– oceanic subtropical highs, monsoons

Page 11: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Simplest: annual harmonic of surface air T

CSM

OBS

GFDL

Page 12: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Cold winter low tropospheric

thickness?

annual harmonic of Z250

CSM

OBS

GFDL

Page 13: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Temperature thickness?

Not so simple…

Page 14: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Annual Harmonicof atmos. heating

Annual Harmonicof u at 200 hPa

Local Hadley cells?

Jan 1

Apr 1

Page 15: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Outline of examples1. Annual

– “Easy” (local, thermal): Tsfc

– Nonlocal: Z250 (jet streams)

2. Semiannual– Nonlinear: angular momentum and u250

– Statistical: 250mb eddy activity

3. Ter-annual and beyond– oceanic subtropical highs, monsoons

Page 16: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Semiannual harmonic of

250 hPa zonal wind

(Weickmann & Chervin 1988)

Jan maxJan min

Apr Apr

Page 17: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Semiannual harmonic of

250 hPa zonal wind

total

JanApr-Oct

Apr

JanApr-Oct

Apr

Apr

Apr

May+Nov

Jun+DecCSM

OBS

HF

Page 18: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

semiannual harmonic of 250 hPa zonal wind

semiannual u in a forced/damped

barotropic model forced with annual harmonic only of

200mb div (Huang & Sardeshmukh

2000)

total

Jan-Jul

Apr-Oct

Apr-Oct

Apr-OctJan-Jul

Apr-Oct

A nonlinear overtoneA nonlinear overtone

Page 19: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Semiannual eddy (storm) activityMidwinter Suppression of Baroclinic Wave Activity in the PacificNakamura 1992ABSTRACT Seasonal variations in baroclinic wave activity and jet stream structure in the Northern

Hemisphere are investigated based upon over 20 years of daily data. Baroclinic wave activity at each grid point is represented for each day by an envelope function, the lowpass-filtered time series of the squared highpass-filtered geopotential height. Baroclinic wave activity over the Atlantic exhibits a single maximum in January, whereas in the Pacific it exhibits peaks in late autumn and in early spring and a significant weakening in midwinter, which is more evident at the tropopause level than near the surface. This suppression occurs despite the fact that the low-level baroclinity and the intensity of the jet stream are strongest in midwinter. Based on the analysis of 31-day running mean fields for individual winters, it is shown that over both the oceans baroclinic wave activity is positively correlated with the strength of the upper-tropospheric jet for wind speeds up to 45 m s 1. When the strength of the westerlies exceeds this optimal value, as it usually does over the western Pacific during midwinter, the correlation is negative: wave amplitude and the meridional fluxes of heat and zonal momentum all decrease with increasing wind speed. The phase speed of the waves increases with wind speed, while the steering level drops, which is indicative of the increasing effects of the mean flow advection and the trapping of the waves near the surface.

Page 20: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

midwinter eddy

minimum

semiannual amplitude (color) of

a climatology of stdev of 9d sliding

window v250

Decently simulated by

coupled model

NCEP 1969-96

CSM 1.3

Oct+Apr maximaof eddy v variance

Page 21: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Outline of examples1. Annual

– “Easy” (local, thermal): Tsfc

– Nonlocal: Z250 (jet streams)

2. Semiannual– Nonlinear: angular momentum and u250

– Statistical: 250mb eddy activity

3. Ter-annual and beyond– oceanic subtropical highs, monsoons

Page 22: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Ter-annual variations of

sea-level pressure total

100d

10d

HF

Page 23: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

CSM climate model

total

HF

Page 24: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Understanding SLP

seasonality:Zonal mean

total

100d

10d

HF

Page 25: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

NH Winter High

Pacific ter-annual SLP schematic

NH Summer Low

Oceanic (Aleutian)~semiannual low

Monsoon-related~100d period high

Page 26: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Outline of examples1. Annual

– “Easy” (local, thermal): Tsfc

– Nonlocal: Z250 (jet streams)

2. Semiannual– Nonlinear: angular momentum and u250

– Statistical: 250mb eddy activity

3. Ter-annual and beyond– oceanic subtropical highs, monsoons

Page 27: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Linho and Wang 2002

wavelet method ISM

WNPM

EASM

ISM

WNPM

EASM

Page 28: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

a model:decent

ISM onset, but poor at

oceanic systems ISM

WNPM

EASM

Page 29: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

North America at same time

ISM

WNPM

EASM

ISM

WNPM

EASMNAM

ENASM?

Page 30: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

June onset in southeast US

(from CPC .25deg 1948-98 gauge data set)

(mid-summer dip)

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Jun 1 Jul 1

Page 31: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Ter-annual midsummer

structure

high & dry in tropical

Americas

NCEP 27 year (1969-96) SLPGulf of Mexico area

July Aug

CMAP 23y mean obs. rain

1

5

dry

HF

Page 32: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

21 May-10 June

3-27July

wet

dry

Midsummer high in W. Atlantic

Page 33: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

SLP obs G Mexico

IPRC/ ECHAM model: decent

Page 34: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Key features of Asian vs. American monsoons : a model experiment

IPRC / ECHAM model: shown to have decent Asian onset, American midsummer drought

Enhance monsoons by allowing each calendar day (solar declination) to last 5x24 hours. Summer continents get hotter, atm has time to equilibrate.

(SST fixed to obs. for each calendar day)

Page 35: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

April-Sept rainfall, exp-control:S. Asia wetter, Americas drier

• S. Asia time series shows earlier (May) onset in exp

• Stated regarding the control run,– Land-atm lags delay Asian

monsoon onset behind its seasonal forcing by ~1mo.

– Onset is the main disequilibrium of the Asian monsoon wrt seasonal forcing

May

total

Page 36: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

July

April-Sept rainfall, exp-control:S. Asia wetter, Americas drier

• Americas time series shows mid-summer drought earlier and drier in exp

• Stated regarding the control run,– Land-atm lags prevent

American midsummer drought from developing fully

– Midsummer drought is the main disequilibrium of the American summer monsoon wrt seasonal forcing

Jun

Page 37: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Outline of examples1. Ter-annual and beyond

– oceanic subtropical highs– monsoons

• Asian onset

• American midsummer drought

• These things are related

Page 38: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Chen, Hoerling and Dole 2001

Heating

Eddy Z1000

w/o shear

Eddy Z1000

July u(y,p)

Page 39: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

u300, zonal mean

Westerlies retreat to >30N in midsummerQuickTime™ and aTIFF (LZW) decompressorare needed to see this picture.

<0

time slice

easterlies protrudeto 30N suddenlyin mid summer

WHY, in terms of [u] budget? • Not f[v]: ~barotropic; [v](t) wrong

• [u’v’]: Tilted TUTTs, Tibetan High, Transients?

Eq

60N

J F M A M J J A S O N D

Jul-Aug time slice

Page 40: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Suggested story timing as seen in Key West data

Page 41: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Winter Wiggles

• Sub-ter-annual time scales: real ??

– ‘The January Thaw’• a statistical phantom? (BAMS Jan 2001)

– Brazilian rainfall

Page 42: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

January Thawlit. of 1919

Page 43: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Boston, 1872-1965

Entire debate centerson this spike

missing this

Page 44: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Revisit, withmore spatialaveraging

• 1969-96 NCEP reanalysis surface air temperature

• N. America mean

• (think vdT/dy)

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

100d

10d

unsmoothed

daily THF part

Jul JunJan

5K

3K

Page 45: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

CPC USprecip1948-98

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Page 46: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Winter Wiggles

• Sub-ter-annual time scales: real ??

– ‘The January Thaw’• a statistical phantom? (BAMS Jan 2001)

– Brazilian rainfall

Page 47: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Where are those boxes? W. subtropical oceans

High HighHighHigh

Page 48: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

CMAP rainfall climatologies:

TAIWAN 25N

CUBA 25N

SE BRAZIL 25S

MADAGASCAR 25S

May

Nov.

Nov.

May

Page 49: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Source: CPTEC Web site

East Brazil rain gauge data

?

Page 50: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

SP & Rio

clim.

Source: Hotel inter-continental Web site

?

Page 51: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Sub-ter-annual Wiggles

– Brazilian rainfall

Live software demo

[email protected] for a DVD copy

Page 52: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

1. Semiannual jets: questions

• OK, it’s a nonlinear overtone driven by the annual harmonic of divergence. What and where is the nonlinearity?

• Superposition fails of course, but surely one could say more than ann div everywhere -> semiann u– Tropical vs. extratropical divergence?– Advection of/by divergent vs. rotational wind, u vs v?– Zonal mean vs. longitudinal features (where)?– Spring/summer/fall/winter?

(HS2000 is really just a succession of steady states)

Does using obs. divergence presuppose too much?

Page 53: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

East Asia midsummer

drought mechanism: the

Bonin High

upper level (barotropic)

“Formation mechanism of the Bonin High in

August”(Enomoto, Hoskins, & Matsuda 2003)

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Page 54: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

HF anomalies (total - annual - semiannual):

Yes, the Bonin High and 2 other stationary waves are evident, but also a zonally elongated u

anomaly spanning all Asia-WPAC

time slice

0 m/s 2-4 -2

u200 HF anomaly plot, July-Aug

HF wavelet analysis

100d

10d

total HF

Japan

Jul Aug

Page 55: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

Interannual consistency of the Asian HF jet anomaly ~1 Aug

Page 56: Strides, steps and stumbles in the march of the seasons 1.Astronomical signal, processed by Earth 2.Earthly data sets, processed by computer 3.Strides:

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

A hemisphericadjustment?

• SLP 1969-96 from NCEP reanalysis