Inves&ga&on of Earth radia&on budget variability by cloud object analysis Seiji Kato1, Seung Hee Ham1, Kuan-­‐Man Xu1, Takmeng Wong1, Patrick C. Taylor1, Tristan S. L’Ecuyer2, Shengtao Dong3, Jenny Chen3, Sunny Sun-­‐Mack3, Fred Rose3, Walter Miller3, and Yan Chen3 1NASA Langley Research Center 2University of Wisconsin 3Science System & Applica&ons Inc. CCCM product •  Contains: 1.  Merged CALIPSO, CloudSat derived clouds, CERES TOA radia&ve flux (SW, LW, and WN), MODIS (CERES_ST) derived cloud proper&es both along CALIPSO-­‐
CloudSat ground-­‐track and over the whole CERES footprint, 2.  MODIS derived cloud proper&es by an enhanced cloud algorithm, 3.  CALIPSO and MODIS derived aerosol proper&es 4.  Ver&cal radia&ve flux profiles computed with CALIPSO, CloudSat, and MODIS derived cloud proper&es. • 
57 months of data (July 2006 through April 2011) are available from hcp://
eosweb.larc.nasa.gov/PRODOCS/ceres-­‐news/table_ceres-­‐news.html Cloud objects (day&me only) ! 
! 
A cloud object is a con&guous patch of cloudy regions with a single dominant cloud-­‐system type, shieing from Eulerian to Lagrangian views of cloud systems The shape and size of a cloud object is determined by the satellite footprint data and by the footprint selec1on criteria for a given cloud-­‐system type Type of cloud objects
Cloud top height
Cloud
fraction
Latitude band
Stratus (St)
< 3 km
99 - 100%
40S – 40N
Stratocumulus (Sc)
< 3 km
40 - 99%
40S – 40N
Cumulus (Cu)
< 3 km
10 - 40%
40S – 40N
Objec&ves and Scien&fic ques&ons •  Understand radia&on budget variability caused by clouds •  Reduces the uncertainty of cloud object analysis by CALIPSO and CloudSat observa&ons •  How is the frequency of occurrence of cloud objects variability related to the variability of TOA radia&on budget? •  How do cloud proper&es within a cloud object change with sea surface temperature (or large scale dynamics) and cloud top height? •  How oeen is an adiaba&c assump&on appropriate for marine stratocumulus and stratus clouds and how does it depends on the size of cloud object? Annual mean cloud thickness for horizontally extensive liquid cloud Wood 2012 Cloud physical thickness derived from LWP with an adiaba&c assump&on (lee) agrees with observed cloud physical thickness (right) Extended cloud object type Focusing on cumulus, stratocumulus, and stratus in this study Data
Cloud Object data (http://cloud-object.larc.nasa.gov)
"  Classification of stratocumulus (Sc) into 9 sub-types depending on horizontal
scale (100-150 km, 150-300 km, >300 km), and cloud fraction (0-40%, 40-99%,
99-100%)
"  One cloud object is consist of several number of CERES footprints
CALIPSO-CloudSat-CERES-MODIS (CCCM) data
"  Shortwave and longwave irradiance profiles computed with enhanced MODIS
cloud products for cloudy and no-aerosol sky (138 levels)
"  MODIS cloud optical thickness and 3.7-µm effective radius provided for up to 16
groups along the satellite ground-track
"  CALIPSO-CloudSat derived cloud top and base heights provided for up to 16
groups along the satellite ground-track
CloudSat
"  Rain rate from CloudSat 2C-RAIN-PROFILE (variable name: rain_rate) or 2CPRECIP-COLUMN (variable name: Precip_rate)
"  Rain detection from CloudSat 2C-RAIN-PROFILE precip-flag
Precipitating case defined if >10% of CloudSat pixels within an object detect
precipitation; Non-precipitating case defined if >90% of CloudSat pixels does not
detect precipitation
Collocation between Used Datasets
“Cloud Object”
CERES footprint:
Irradiance profiles
MODIS cloud parameters
CALIPSO-CloudSat-derived cloud
boundary
CloudSat footprint:
Rain rate (mm/hr)
Rain detection
Definition of Cloud Top/Base and fraction of Low Clouds
1, 2, 3, ……………………, 16x(# of FOVS in an object) cloud groups
Merge cloud
groups when their
boundaries are
similar
3 km
Weighted mean of cloud tops of two
groups: “Low cloud top”
Weighted mean of cloud bases of two
groups: “Low cloud base”
"  If there are two cloud layers below 3-km altitude, then cloud top of uppermost
layer and cloud base of lowermost layer are used.
"  Once cloud top and base of low clouds (< 3km) are obtained, within these
boundaries, cloud absorption and flux deposition are computed.
Cloud Properties of Objects (Cloud Fraction 99-100%)
Non-­‐precipita&ng clouds Precipita&ng clouds Cloud top height Cloud top height Cloud base height Rain rate Op&cal thickness Par&cle size Cloud base height Op&cal thickness Rain rate Par&cle size Cloud Absorption and Flux Deposition
Compute radiative flux profiles for precipitating clouds and non-precipitating clouds
"  Cloud Absorption (W m-2)
F2# - F2$ - F1# + F1$
"  Flux deposition at a cloud layer (W m-2 km-1)
(F2# - F2$ - F1# + F1$) / Δz
F2$
F 2#
F1$
F 1#
z2
Δz
z1
Irradiance Profiles (Cloud Fraction 99-100%)
L > 300 km
Solid line: Non-­‐precipita&ng clouds Dashed line: Precipita&ng clouds Cloud Absorption and Flux Deposition
(Cloud Fraction 99-100%)
Non-­‐precipita&ng clouds Precipita&ng clouds Precipita&ng cloud, which have a higher cloud top height, a larger op&cal thickness, and larger par&cle size, have more SW absorp&on and less LW cooling by clouds As a result, precipita&ng clouds are warmed by radia&on (SW+LW). Cloud Absorption and Flux Deposition
(Cloud Fraction 99-100%)
Non-­‐precipita&ng clouds Precipita&ng clouds Summary •  According to CloudSat 2C-­‐RAIN-­‐PROFILE, ~20% of solid stratus precipitate •  Stratus with higher cloud top height tend to have a larger op&cal thickness, and a larger par&cle size, net warming by radia&on, and tend to precipitate for all cloud object sizes •  The result does not contradict with an adiaba&c cloud model •  Does CloudSat sampling affect this result? Effect of CloudSat sampling •  CloudSat misses clouds below ~1.2 km because of the surface clucer (Marchand et al. 2008). •  If CloudSat misses clouds below 1.2 km and precipita&on, this leads to overes&mate precipita&ng cloud top height •  To check the effect of CloudSat sampling, we use only clouds detected by CloudSat and repeat the analysis. CloudSat + CALIPSO for CCCM Cloud Top Height
Use all available cloud top height information for all cloud groups in one object.
Because one object is composed of several number of CERES footprint, there are
more than 16 groups in one cloud object. The cloud groups are merged if the number
of layers of the group is same and their heights are similar to other cloud group. The
merging process is repeated until the total number of cloud groups is smaller than 16.
The cloud top height of the merged cloud groups are eventually used for obtaining low
cloud fraction and low cloud top, which is explained in the next slide.
CloudSat Only for CCCM Cloud Top Height
Use cloud top height information only if 1) the cloud top height is above 1 km, and 2)
cloud top height is from CloudSat (cloud_top_source_flag is 13, 22, 23, or 24).
Note that only few portion of clouds within one object can have cloud top information
from CloudSat. Therefore, the case is selected if CloudSat-only cloud top height
information is available for more than 70% of cloud area. Otherwise, the object is
excluded for the analysis of cloud top height. When CloudSat-only cloud top height is
available for more than 70% of area, cloud area of groups is rescaled for filling missing
cloud area by CloudSat. For example, total cloud area is 90%, and only 70% of cloud
area is observed by CloudSat. In this case, area of cloud groups within the 70% is
rescaled by 90%/70%, and the cloud top information for the remaining 20% is not used for
the analysis.
The merging process of cloud groups is as the same as described above.
Cloud Properties of Objects (Cloud Fraction 40-99%)
CCCM Cloud Top Height either from CALIPSO or CloudSat
CCCM Cloud Top Height from CloudSat Only
Summary and future work •  CloudSat sampling does not affect the result that precipita&ng solid stratus a have higher cloud top height than non-­‐precipita&ng solid stratus. •  Analyze radia&on, precipita&on, and cloud property rela&onships as a func&on of sea surface temperature. •  Analyze smaller size (< 100 km) cloud objects •  Analyze how oeen adiaba&c liquid water pass occurs Back-­‐up Definition of ‘low cloud fraction’
Portion of low clouds with their tops between 0 km and 3 km, within an object
Definition of ‘low cloud top’
Weighted mean of cloud top of upper most clouds below 3 km, within an object
4 km
3 km
2 km
1 km
Low cloud frac&on = 70% Low cloud top = (2.5 km x 50% + 1.5 km x 20%)/70%= 2.21 km Cloud Absorption and Flux Deposition
(Cloud Fraction 40-99%)
Precipitating clouds show smaller longwave cooling, which results in larger SW
+LW heating.
Cloud Absorption and Flux Deposition
(Cloud Fraction 99-100%)