Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to...

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Studies of columnar Studies of columnar observations and model observations and model outputs outputs Brian Mapes Brian Mapes University of Miami University of Miami with thanks to many data with thanks to many data producers and sharers producers and sharers

Transcript of Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to...

Page 1: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

Studies of columnar observations Studies of columnar observations and model outputsand model outputs

Brian MapesBrian Mapes

University of MiamiUniversity of Miami

with thanks to many data producers and sharerswith thanks to many data producers and sharers

Page 2: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

Looking under the hood of monthly mean data “points”

• Time sections: f(submonthly time x pressure)

– a vast, rich domain– complementary to typical climate model

examination space (lat x lon x months)– Natural domain for observations– Sensible domain for physical processes

Page 3: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

Shortcomings• Free-running climate model time axis not directly

comparable to observations– statistical comparisons of course

• Models have climate-regime offsets in space, biasing comparisons at a fixed geo-location– non-mean statistics that is

• Submonthly variations (dynamics-driven) a poor proxy for climate sensitivity (thermo-driven)– tough luck, we do what we can

• Eulerian viewpoint a perverse view of weather– you’re free to leave

Page 4: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

inescapable programming tediumCOARE obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAMGFDL AM2NASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

Common data format,

variables,names,units,

flux sign conventions,

etc.

standard raw plots

standard stat plots

inescapable programming tedium

Page 5: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

Datasets COARE obsKWAJEX obsLBA obsEPIC, JASMINE(more: ARM? etc?)

KWAJEX 3D CRM

NCAR CAMGFDL AM2NASA GMAO(more: CAM-SP?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

All obs are from warm-wet tropics so far - what I have & know best

Cloud obs rare: satellite TOA rad in~GCM-grid areas, but cloud profiles at

only a few points (cloud radar)

the most GCM-comparable cloud dataset

Driving the whole exercise -- an AMIP, at the very least

weird experiments,not done real carefully so far.

Future?

Page 6: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What variables?

COARE obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAMGFDL AM2NASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

TOA radiation and cloud forcing

cloud fraction and condensed water content (p)

humidity (p)

vertical motion (p)

physical tendenciesheating and drying (p)

rain

CLIMATEIMPACT SCALAR

SCALARLINK TO HYD CYC

structure structure within within tropo-tropo-spheresphere

Page 7: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What plots?COARE IFA obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAMGFDL AM2NASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

CRF: LW+, SW-, net ~0 [obs needclear-sky assumptions]

rain

RHcld frac [ crude f(RH) here ]

Q1, CWC (no obs)

wind divergence and vertical grid

0

100

%

note: net <0 at rainiest times

IFA OBS

Page 8: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What stats?COARE IFA obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAMGFDL AM2NASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

Lag regressions I: scalars vs. reference variable (here, ref = qbudget-derived IFA rain)

reflected SW

reduced OLR

net

(here, other obs. estimates models, other rain types)

TOA rad up:

Other rain vars:

Page 9: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What stats?COARE IFA obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAMGFDL AM2NASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

regressions vs. IFA rainfall

~1 mm/h x 1d ~24 mm rain

net

longwave atm heating longwave atm heating ~ 15% of latent heating~ 15% of latent heating

ocean shading*ocean shading* ~ -20% of latent heat in rain~ -20% of latent heat in rain

* straight regression incl. nocturnal zeroes - not really right approach ~6am diurnal rain peak

Page 10: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What stats?COARE obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAMGFDL AM2NASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

II. lag-height regressions of profile fields vs. surface rain

~1/2 day timescale at a point

44 km radius“MCS-resolving”

Page 11: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What stats?COARE IFA obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAMGFDL AM2NASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

regressions vs. surface rainfallSYNOPTIC SCALE (IFA)

multiscale (incl. several-day timescales)

but no cloud profile observations

Page 12: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What should areal cloud

statistics look like?

KWAJEX 3D CRMthanks Marat

TOA: obs TOA: obs-forced CRM

4-8 units, vertical

up to 16, vertical

condensatecan’t blow

away

Page 13: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What stats?COARE IFA obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAM - IFAGFDL AM2 - IFANASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

regressions vs. surface rainfall - AM2

layers

upward development

time jitters sometimes

TOA about balanced, long

time scales

zigzag layers

july - 10 mm/d

Page 14: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What stats?COARE IFA obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAM - IFAGFDL AM2 - IFANASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

AM2 - a different month

slow upward development

TOA closely balanced, long

time scale

zigzag layers

nov - 11 mm/d

Page 15: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What stats?COARE IFA obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAM - IFAGFDL AM2NASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

regressions vs. surface rainfall - CAM

3-day waves

vertical thanks to ‘convective’ fraction but…

CRF not well linked to rain

events

…condensed water not

coherent in vertical

jan - 7 mm/d

Page 16: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

What stats?COARE IFA obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAM - IFAGFDL AM2 - IFAGMAO 140E/8N July(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

regressions vs. surface rainfall - GMAO

upward development, zigzag layers

a bit stark but about like IFA

2xKwajCRM ice content

freezing level schism

Page 17: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

rain event met fields - obs

<-KWX

IFA->

Page 18: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

rain event met fields - CAM-IFA

<-Jan

Dec->

Page 19: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

rain event met fields - 3 models

CAM AM2GMAO

Page 20: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

But are these brief rain-event fluctuations a Climate Process?

• hypothesisDivergence profile in tropical rain events

linked to profile of divergent winds

linked to profile of total winds?

( -> coupling issues…climate by any standard)

? Let’s look

Page 21: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

CAMGMAO

Top- stats of div regression sections (lag-height) Bottom- stats of total wind speed (time-height)

each curve shows 1 month of data

AM2IFAmean

stdev w/in 6-day lag section

mean

stdev

All 3 GCMs have unrealistic surface-intensified div fluctuations

but no near- surface enhancement of wind fluctuations

KWAJEX is 3rd line; LBA 4

CAM-jangly wind profiles

1000 vs 850 not right

GMAO-midlevel swoop

Page 22: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

wind profile results

• hypothesis too simplistic

• BUT– Systematic windspeed profile differences from

observations are clear at low levels!

Page 23: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

Regressions wrt TOA CRF “events”?

• Weird idea: submonthly TOA CRF has ~no feedback to the weather that causes it, so there’s less expectation of a repeatable “life cycle”

• Proxy for climate sensitivities? – ? Maybe, if tau << {days, years, decades, etc.} ?

• Anyway, try it (but I have no obs yet)– use 24h smoothing to kill diurnal cycle

Page 24: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

24h-smoothed TOA -CRF as base time series -- CAM 85W 20S

CRF<0, big slow changesSWup>0

Whiter w/clouds at 975 not 925

Page 25: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

Another month at 85W 20S -- CAM

Complicated mixture of events

SWup>0CRF<0

faster changes, polymodal pdf?

Page 26: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

AM2 - 85W 20S whiteness varies little; regression structure not stable

steady -30ish CRF

(Q1 data missing) PBL-based clouds rise to ~550mb here !?Minghua’s AM2 “midlevel” cloud (ISCCP)

Page 27: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

Cross-forced SCMs (CAM <-> AM2)

• V. advection of SCM fields by prescribed vertical velocity from other GCM

• H. advection prescribed (non-interactive)

• Look at LBA (Amazon) just for fun

Page 28: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

LBA obs (via Minghua’s shop), & GCMs

AM2CAMLBA obs

(warning: clear sky not careful)

(sorry: Q1 missing)

Page 29: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

AM2CAMLBA obs

Page 30: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

LBA models

AM2 CAMSCAM driven by AM2omega

Cloud style CAMlike

Page 31: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

LBA models

AM2 CAMSCAM2 driven by CAMomega

Cloud style AM2 ish

Page 32: Studies of columnar observations and model outputs Brian Mapes University of Miami with thanks to many data producers and sharers.

Future plans - team efforts?COARE obsKWAJEX obsLBA obsEPIC, JASMINE

KWAJEX CRM

NCAR CAMGFDL AM2NASA GMAO(super-CAM soon?)

cross-forced SCMs•SCAM2 driven by CAM•SCAM driven by AM2

Common data format,

variables,names,units, sign

conventions

standard raw plots

standard stat plots

clickable from Bony index plot

co-ra.com/~bem

more to come

MORE DATAin (p,t) space

SCMs! CRMs!EXPERIMENTS!

OBS! other people