Clouds Finding Out What Clouds Are All About. Cirrus Clouds.
Clouds and radiation recent hot topics Stefan Kinne.
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Transcript of Clouds and radiation recent hot topics Stefan Kinne.
![Page 1: Clouds and radiation recent hot topics Stefan Kinne.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1b6b7f8b9ab0599b35da/html5/thumbnails/1.jpg)
clouds and radiation
… recent hot topics
Stefan Kinne
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348 ?CERES
165 ?CERES
Question: how to balance the incoming extra 20W/m2 by CERES at the surface ?
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overview look at combined solar + IR netflux for
CERES SRBAVG (the new ToA reference) SRB ISCCP IPCC-model median
CERES is about 20W/m2 larger than IPCC modeling 10W/m2 larger than SRB 8W/m2 larger than ISCCP
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all-sky netflux at surface
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all-sky diff-netflux at surf
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diagnostics diagnose … why ?
solar down fluxes all-sky CE (all-sky minus clear-sky)
IR down fluxes all-sky CE (all-sky minus clear-sky)
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all-sky dn-solar at surface
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all-sky diff-dn-solar at surf
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CE dn-solar at surface
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CE diff-dn-solar at surface
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all-sky dn-IR at surface
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all-sky diff-dn-IR at surf
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CE dn-IR at surface
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CE diff dn-IR at surface
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different definitions of the clear-sky fluxcloud-free skyall sky
satellite clear-sky: only data from cloud-free areas modeled clear-sky: (= cloud-free) data with cloud removed… but in ‘cloudy columns’ there is more water vapor than in ‘clear-columns’
model simulations underestimate the derived cloud radiative effect … as it includes the increased water vapor in cloudy regions
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expected are …
• overestimates to– OLR (IR up at ToA)– IR dn at surface– IR divergence– solar divergence
• underestimates to – solar transmission– solar reflection
JJA
CRFCERES (Wm-2)
-10 0 10 20 30 40 50 60 70 80 90 100 110 120
CR
F du
e to
UTW
cha
nge
(Wm
-2)
0
2
4
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OLR error~ 10W/m2 !
B.J.Sohn (2005)
modeled cloud-effect biases on fluxes
OLR error (B.J. Sohn, 2010)theoretical simulations
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IPCC-modeling minus CERES (obs)
• divergence
• cloud effect on up-flux
• cloud effect on dn-flux
solar IR
OLR effects are smaller due to compensating differences in cloud altitude
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ISCCP (model based) minus CERES (obs)
• divergence
• cloud effect on up-flux
• cloud effect on dn-flux
solar IR
lack of absorbing aerosol in tropics for ISCCP explains unexpected sA bias
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take-home messages
- data products of the same name often do not mean the same (not identical by definition)- water vapor is expected often to be larger near clouds … thus clear-sky definitions in modeling by differing from observations introduce biases-interestingly, expected differences often do not fully materialize due to other inconsistencies (e.g ancillary data of aerosol)- careful assessments of data-products and assumptions are essential prior to conclusions