Seasonal and Interannual Variation of
Cloud Type Revealed by 10- year
CloudSat and CALIPSO
Measurements and
Its Implications
Zhien Wang, Tao Luo, Min Deng, and
Kang Yang
University of Wyoming
Why Study Cloud Type Variations
1. Different impacts on Earth energy and water cycles.
Global annual mean overcast sky cloud-induced radiative flux changes in W m-2 (Chen et al. J.
Climate, 13, 264-286, 2000)
Ci
TOA
total
5.4
Cs
Dc
Ac
As
Ns
Cu
Sc
St
-27.7
-65.5
-16.3
-58.8
-78.2
-29.8
-67.0
-76.8
2. Different types of clouds are controlled by different
dynamics and thermodynamics.
3. Climate changes can result in changing frequency of
cloud types and changing properties of a cloud type. The
combination of them determines cloud feedbacks.
Active Measurements for Effective
Cloud Type Identifications
From https://en.wikipedia.org/wiki/List_of_cloud_types
CloudSat Cloud Classification Products
• Radar-only (2B-CLDCLASS)
• Radar-lidar combined (2B-CLDCLASS-Lidar)
2B-CLDCLASS-Lidar Flowchart
~10 year 2B-CLDCLASS-Lidar will be used to study seasonal and
inter-annal variations.
Month Index
Monthly Mean Cloud Occurrence
Cloud Occurrence Map
Each type cloud has their
preferred regions
associated with dynamics,
thermodynamics, and water
vapor supply.
Sc + St has contrast land
and ocean difference
Before Do-op
After Do-op
High
As
Ac
Sc+St
Deep convective clouds are
mainly over tropics, while
Ns cloud are main
concentrated over midllatitude
The two periods offer a
consistent annual mean
daytime cloud type
distributions.
Cu
Ns
Deep
Day/Night Cloud Type Variations
• Over the tropics, high Day
and Ac clouds have
higher occurrence at
night due to LW
cooling. The difference
of Dc and Cu
occurrence depends
on regions.
• In midlatitude and
polar regions, As and
Ns have higher
occurrence at night. Sc
and St have relatively
higher occurrence
over ocean, but lower
occurrence over land.
High
As
Ac
Sc+St
Cu
Ns
Deep
Night
Annual Cycles of Zonal Mean Cloud Types
Dc
• Clear signatures of
solar radiation driven
annual cycle.
• In tropics, high, Ac, Cu,
and deep convective
clouds share similar
features.
• As, Sc + St, and Ns
clouds are also driven
by large-scale
dynamics and
thermodynamics.
Ac
As
High
As
Cu
Sc+St
Ns
Latitude
Annual Variations over Land and Ocean
• The seasonal transition over ocean is relatively more smooth due to larger
coverage.
• Abundant water vapor over marine atmospheric boundary layer promotes
more Cu and Sc+St clouds, especially over subsidence regions.
Deep
Ac
Deep
Ac
As
High
As
High
Cu
Sc+St
Cu
Ns
Sc+St
Ns
Annual Cycles of Meridional Mean
Cloud Types (20S-20N)
Month Index
• The locations of
tropical deep
convective clouds
indicate the Walker
circulations, which
shifts with seasons
All
Ac
Deep
• High cloud
production or
maintenance rate
is higher over the
warm pool region.
High
Cu
Interannual Cloud Type Variations
20S-20N
Month Index
• From 2006-2015, there are a few significant ENSO events, which drive
interannual tropical cloud type variations.
Longitude
Interannual Cloud Type Variations
Anomaly
Deep convective clouds and associated high and Ac clouds
move systematically as ENSO evolves!
Deep x8
High
Ac
MEI Index
2010
Longitude
Anomaly (%)
Month Index
2015
Tropical Cloud Type Distributions
during Positive and Negative Phases
El Nino
La Nino
?
Cloud Type Dependent TOA Cloud
Radiative Forcings
• 2B-CLDCLASS-lidar data (2006-2015) were collocated with CERES TOA
cloud radiative forcings (FlashFlux, 25x25 km).
• Single type dominated CERES data were used.
Conclusions and Discussions
• Difference types of clouds working together regulate
global water and energy cycles.
• Cloud type distributions vary seasonally and interannually with solar radiation, large-scale dynamics
and thermodynamics.
• 10-Year combined CloudSat and CALIPSO cloud type
product (2B-CLDCLASS-lidar) offer an important data
source to check how good climate models capture the
key variations.
Contribution of different cloud types
to the daytime TOA cloud radiative
forcing
MCci: multiple-layer cloud, topped by Ci MCas: multiple-layer cloud, topped by As
Month Index
Day-Night Difference
Longitude
Interannual Cloud Type Variations