Clouds and their radiative impact as examples of histogram (binning) methods

1
Cloudsand their radiative impactas examples of
histogram (binning) methods

• Brian Mapes

2
Global warming projectionsin terms of T
3
Remember this from class 5?

• Climate heat budget over ocean atm
• ? (?Cp dT/dt ) dV ? (Frad_TOA) dA     (small)
• Units Watts
• pert ? (-OLR) dA ? (ASR) dA
• outgoing longwave and absorbed solar
• Integrate over time (indefinite integral)
• ? ? (?Cp dT/dt ) dV dt
• units Joules
• or YottaJoules (1022 Yotta I think)
• Global warming due to increasing ASR (pdf)

4
Issue 1 integrating over area

• dA (df) (cosf dl) in ? (Frad_TOA) dA
• weight by cos(f) when summing over lon bins
• OR dA (dsinf) (dl)
• Rebin latitude to equally spaced sinf bins
• Then ou can just sum them up!
• Related to map projection issue (equal area) but
  thats just for eyeball integrals

5
Equal area map projections
6
Radiative imbalance

• IPCC model ensemble (CMIP3)

Cumulative longwave trapping by increasing GHGs
(clear sky broken lines) Effect is reduced
somewhat by clouds (total sky solid/shaded)
Trenberth and Fasullo 2009 GRL
7
Global warming due to increasing absorbed solar
radiation

• All-sky mean longwave trapping quits by 2030 as
  skies clear (iris effect of clouds?)

2030
All sky
Trenberth and Fasullo 2009 GRL
8
Global warming due to increasing absorbed solar
radiation

• From 2030, models warm largely by reduced albedo
  (clearing skies/ cloud reductions?)

All sky
2030
Trenberth and Fasullo 2009 GRL
9
Cloud cover reductions where?
Non equal area Yellow overemphasized in
perception? see colorbrewer.org
10
Cloud radiative forcing

• Stuff (an additive scalar quantity)
• BW best!
• Color is ambiguous among viewers
• Wm-2 units
• Area integration (or averaging) is what its all
  about
• Can be distributed over bins
• area bins matter (use sin(lat))
• but another dimension (like z) is free

11
2007 Cloud Radiative Effect CRE (aka CRF) from
CloudSat FLXHR product
-55Wm-2
19Wm-2
Ztop (km)

• 19 LW global mean -55 SW
• (Wm-2)

Caution Simple average of 0130 and 1330 local
time samples, not true diurnal mean estimate!
12
Distributions each ink molecule corresponds to
an equal amount of the Stuff (CRF)
Ztop (km)
-55 Wm-2 total
total 19 Wm-2
LW
19
-55
SW
LW
13
Decomposing CRE into cloud types
Lowest possible base, high top precipitating
echo objects
14
Storms vs. layer clouds
Echo Base lt 3km AND Top gt 3km AND Wider than
17km storms
All else layer clouds
15
Decomposing the 19 and -55
-25W
8W
-30W
11W
gt50 in storms
16
Latitude distributions
Layers Have CRE impact everywhere Storms Impact
at high latitudes (and equator)
-25W
8W
43oS
-30W
11W
53oN
53oS
17
SW CRE Storms sunshine
-16W out of -30W SW are poleward of latitude 40
N/S Mostly in local summer
Storms -30W SW CRE
53oN
G. Alaska, Kamchatka
40
-14W in 40S-40N
40
53
Cape Horn 56S
Day of year 2007
18
Half of tropical storm area coverage is in echo
objects gt200 km wide
Half of midlat. storm area coverage is in echo
objects gt500 km wide
19
SW CRE by latitude and size
20
Summary

• Current clouds (cloudsat echo objects) have a
  shortwave effect of -55 Wm-2 and longwave effect
  of 19 Wm-2 according the (imperfect! 2xdaily)
  Cloudsat FLX-HR data set.
• These total impacts can be distributed over
  latitude, cloud object size, season etc.
• gray scale total impact a amount-of-ink-on-page.
  

21
Other ways of binning area on the globe

• methods used also in

22
Bony et al. method

• summarized in wyant et al.

these must be sin(lat) columns in order for
simple sum (2) to be a true area x time average
23
Bony et al. method contd

• 30N-30S

24
Omega500 maps
25
collapse into a 1D PDF
26
scatterplots, and bin averagesof CRF
27
Stretch bins so that dx on the page represents dA
(area on globe)

• T-Tbar
• RH

28
cloud water changes when SST warms

• good use of color
• p is the proper vertical coord (mass)
• so the vertical sum is meaningful

29
Decomposing changes into shift of bins vs.
changes in bin means