METEOROLOGICAL SATELLITE CENTER TECHNICAL NOTE, No.61, MARCH, 2016
METEOROLOGICAL SATELLITE CENTER TECHNICAL NOTE, No.61, MARCH, 2016
（二行）
Algorithm Theoretical
BasisInformation
for Himawari-8
Cloud
Mask
Product data
High-resolution
Cloud Analysis
derived
from
Himawari-8
（二行）
IMAI Takahito* and YOSHIDA Ryo**
（三行）
SUZUE Hiroshi*, IMAI Takahito** and MOURI Kouki*
Abstract
This paper describes the algorithm theoretical basis for the Himawari-8 Cloud Mask Product
(CMP) developed by the Meteorological Satellite
Center. CMP is part of the Fundamental Cloud
Abstract
Product,
which
incorporates
cloud
phase,
type
and
top
Himawari-8/AHI
has been
The Meteorological Satellite Center (MSC) of thealtitude
Japan from
Meteorological
Agencyand
(JMA)
has
operational
since 7 July
2015.
developed
a product
called
High-resolution Cloud Analysis Information (HCAI) as the successor to
The Cloud
CMP algorithm
is based on
the(SCGID).
cloud mask
technique
NWC-SAF
for MSG/SEVIRI
and
Satellite
Grid Information
Data
The
product,ofwhich
has been
provided to JMA
NOAA/NESDIS
for
GOES-R/ABI.
Most
cloud
detection
tests
involve
threshold
methods
based
on
meteorological observatories and other users since 7 July 2015, is composed of five elements: cloud
radiative
transfer
calculation
using
NWP
data
as
atmospheric
profiles.
The
thresholds
are
modified
mask (including dust mask), snow ice mask, cloud type, cloud top height and quality control
using offsets
determined
on the basis
of comparison
with in
theboth
MODIS
cloud
product.
Initial
information.
The
spatial resolution
of each
element is 0.02°
latitude
andmask
longitude,
making
it
higher
that that
of the
SCGID
longitude).
Eachwas
element
is calculated
resultsthan
showed
CMP(0.20°
hit ratiolatitude,
derived 0.25°
from such
comparison
more than
85%. The using
CMP
observational
dataapplied
from Himawari-8
Fundamental
Cloud hit
Product
algorithm was
to SEVIRI and
data,the
with
results showing
ratios(FCP).
with the MODIS product
This
high 85%
resolution
HCAI to report local cumulonimbus clouds that are not highlighted
were
around
for allallows
seasons.
in SCGID. It also reports the cloud top surface（三行）
clearly and supports a reduced incidence of stratus or
fog being erroneously identified as stratocumulus.
1. Introduction
（一行）
Himawari-8 is the new geostationary satellite of the
1 Introduction
Japan Meteorological Agency (JMA). It was launched on
7 October 2014 and began operation on 7 July 2015. The
Satellite Cloud Grid Information Data (SCGID)
satellite carries the Advanced Himawari Imager (AHI),
(Tokuno,
2002)improved
developed
Meteorological
which
is greatly
over by
past the
imagers
in terms of
Satellite
(MSC)
of temporal/special
the Japan Meteorological
its
numberCenter
of bands
and its
resolution
Agency (JMA)
was2016).
first provided
JMA meteorological
(Bessho
et al.
Using to AHI
data, JMA’s
Meteorological
Satellite
Center
(MSC)
developed
the
observatories to support operational weather forecasting
Himawari-8
Cloud Mask
Product conditions
(CMP).
and determination
of weather
(e.g., sunny,
Cloud mask is used to discriminate cloudy pixels
cloudy, etc.) in 1999. Until 7 July 2015, it was produced
from clear ones in satellite data. Numerous satellite
using Multi-functional Transport Satellite (MTSAT)
products require cloud mask information. By way of
series data.Sea
It covered
area from (SST)
52ºN to
the equator
example,
Surface the
Temperature
(Yasuda
and
and from 114ºE
180ºE,Sky
andRadiance
had a spatial
resolution
of
Shirakawa
1999),to Clear
(CSR)
(Uesawa
began operation.
This paper describes the algorithm theoretical basis for
CMP.
Observational data from Himawari-8, which started
（一行）
operation on 7 July 2015, have a higher spatial resolution
2. Algorithm
and more bands (Table 1) than the MTSAT series
(Bessho
et al., 2016). Against such a background,
2.1 Overview
JMA/MSC
developed
called High-resolution
Cloud detection
in atheproduct
CMP algorithm
is based on
Cloud
Analysis
to make
use
comparison
of Information
observation (HCAI)
data and
clear optimal
sky data
calculated
from
numerical
weather
prediction
(NWP)
of these data and launched it on 7 July 2015.
data.
If observation
differ from
clear sky data,
the
Before
HCAI is data
produced,
the Fundamental
Cloud
pixel is cloudy. To discriminate between cloudy and clear
Product (FCP) (Imai and Yoshida, 2016; Mouri et al.,
pixels, it is desirable for observation variables in clear
2016a,b) is produced from Himawari-8 data and
and cloudy conditions to differ and for the physical
Numerical
Weather
of JMA.(e.g.,
FCP
reason behind
the Prediction
difference(NWP)
to bedataexplicit
is a level-2 product
created
each infrared
temperature,
reflectance
andfor
emissivity
of theband
top pixel
and
of Himawari-8relating
data. It consists
cloudthe
mask
(including
0.20° and
in latitude
0.25° in
longitude.
transmittance
to cloudsof and
atmosphere).
2009)
Aerosoland
Detection
(Okawara
et al.SCGID
2003) was
are
Rather
than
encompassing
retrieval
of
these
five
derived
in
clear
pixels.
Conversely,
Cloud
Grid
surface
condition
data),
cloud
type
composed of five elements: total cloud amount, upper
variables,
most
of
the
tests
in
the
CMP
algorithm
involve
Information
(Tokuno
2002)
is
processed
in
cloudy
pixels.
(opaque/semi-transparent/fractional, etc.), cloud phase
cloud amount, convective cloud amount, cloud top
the use of brightness temperature or reflectance data with
There were no MSC cloud 1mask
products
before
the
2
(ice/water/mixed) and cloud top height (every 100
height and cloud type (clear , cumulonimbus, cirrus ,
similar tendencies. Cloud mask tests are based on the
start of Himawari-8’s operation; each satellite product
middle cloud, cumulus, stratocumulus, stratus/fog and
meters). HCAI is produced using Himawari-8 and FCP
cloud mask algorithm of the NoWCasting (NWC)
had its own3 cloud mask process. As cloud mask is also
).
dense cloud
data.
Satellite
Application Facility (SAF) (Meteo-France,
required
for most
Himawari-8 products, MSC decided to
2012)
and
the National Oceanic and Atmospheric
develop
CMP
as
a
resource
available
for
Himawari-8
1
No cloud
Administration
(NOAA)/National
Environmental
products
in common. CMP is a part of the Fundamental
2
Semi-transparent upper cloud
3
Satellite,
Data,
and
Information
Service
(NESDIS)
Cloud
Product
(FCP),
which
contains
cloud
phase,
type
Opaque upper cloud
(Heidinger and Straka III, 2012).
and top height for Himawari-8/AHI pixels (Mouri et al.
* System
Engineering
Processing
Department,
Meteorological
Satellite Center
Radiative
transfer calculation using NWP data for
2016a,
2016b).
FCP Division,
has beenData
produced
since
Himawari-8
** Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency
September 1,
2015, Accepted
4, 2015)
*(Received
Office of Observation
Systems
Operation,November
Observation
Department, Japan Meteorological Agency
** System Engineering Division, Data Processing Department, Meteorological Satellite Center
--43
(Received September 1, 2015, Accepted 20 November 2015)
1 --
－ 43 －
METEOROLOGICAL
SATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICAL
SATELLITE
CENTER
TECHNICAL
NOTE,
MARCH,
2016
Table 1 AHI specifications
2.2 Data Utilized
（二行）
Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product
（二行）
The following data are used for HCAI:
・Brightness Temperature (BT) of bands 08 (6.2 μm),
IMAI Takahito* and YOSHIDA
Ryo**
10 (7.3
μm) and 13 (10.4 μm) of the Advanced
（三行）
Himawari Imager (AHI) on board Himawari-8
・FCP (cloud mask (including surface condition data),
Abstract cloud type and cloud top height)
This paper describes the algorithm theoretical basis for the Himawari-8 Cloud Mask Product
(CMP) developed by the Meteorological Satellite Center.
CMP is part
of the Fundamental
Cloud
2.3 Calculation
Meteorological
Parameters
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
operational since 7 July 2015.
The product
incorporates
following meteorological
The CMP algorithm is based on the cloud mask technique
of NWC-SAF
forthe
MSG/SEVIRI
and
NOAA/NESDIS for GOES-R/ABI. Most cloud detection
tests involve threshold methods based on
parameters:
radiative transfer calculation using NWP data as atmospheric
The thresholds
are modified
・Cloudprofiles.
mask (including
dust mask)
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
(presence or absence of cloud/dust)
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
absence
of snow/ice)
algorithm was applied to SEVIRI data, with results ・Snow
showing ice
hit mask
ratios(presence
with the or
MODIS
product
were around 85% for all seasons.
・Cloud type (clear (Clr), cumulonimbus (Cb), cirrus
（三行）
1. Introduction
(CH),
middle
cloud
(CM),
cumulus
(Cu),
stratocumulus (Sc), stratus/fog (St/Fg) and dense
begancloud
operation.
(Dense))
This
paper
describes
the algorithm
theoretical basis for
・Cloud top
height (every
100 meters)
CMP.
・Quality control information (effects of stray light,
（一行）
quality
of
cloud
mask,
etc.)
2. Algorithm
（一行）
2 Product Specifications
Himawari-8 is the new geostationary satellite of the
Japan Meteorological Agency (JMA). It was launched on
Coverage
Resolution
72.1October
2014and
andSpatial
began operation
on 7 July 2015. The
satellite carries the Advanced Himawari Imager (AHI),
HCAI
covers improved
the area from
60°Nimagers
to 60°S
2.4
Sample Products
which
is greatly
over past
in and
termsfrom
of
2.1 Overview
Cloud detection in the CMP algorithm is based on
its
number
of bands
and its temporal/special resolution
80°E
to 160°W
(Fig. 1).
comparison
of observation
dataand
anda sample
clear sky
data
(Bessho
et al.
2016). ofUsing
AHIis data,
JMA’s
The spatial
resolution
each grid
0.02° in
both
AHI imagery
(Fig. 2 (a), (b))
of HCAI
calculated
from
numerical
weather
prediction
(NWP)
Meteorological
Satellite
Center
(MSC)
developed
the
latitude and longitude, making a total of 6,001 grid
(Fig. 2 (c) – (f)) for 0200 UTC on 10 April 2015 are
data. If observation data differ from clear sky data, the
Himawari-8 Cloud Mask Product (CMP).
boxes for each.
given below.
pixel is cloudy. To discriminate between cloudy and clear
Cloud mask is used to discriminate cloudy pixels
pixels, it is desirable for observation variables in clear
from clear ones in satellite data. Numerous satellite
and cloudy conditions to differ and for the physical
products require cloud mask information. By way of
reason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda and
temperature, reflectance and emissivity of the top and
Shirakawa 1999), Clear Sky Radiance (CSR) (Uesawa
transmittance relating to clouds and the atmosphere).
2009) and Aerosol Detection (Okawara et al. 2003) are
Rather than encompassing retrieval of these five
derived in clear pixels. Conversely, Cloud Grid
variables, most of the tests in the CMP algorithm involve
Information (Tokuno 2002) is processed in cloudy pixels.
the use of brightness temperature or reflectance data with
There were no MSC cloud mask products before the
similar tendencies. Cloud mask tests are based on the
start of Himawari-8’s operation; each satellite product
cloud mask algorithm of the NoWCasting (NWC)
had its own cloud mask process. As cloud mask is also
Satellite Application Facility (SAF) (Meteo-France,
required for most Himawari-8 products, MSC decided to
2012) and the National Oceanic and Atmospheric
develop CMP as a resource available for Himawari-8
Administration
(NOAA)/National
Environmental
products in common. CMP is a part of the Fundamental
Satellite, Data, and Information Service (NESDIS)
Cloud Product (FCP), which contains cloud phase, type
(Heidinger and Straka III, 2012).
and top height for Himawari-8/AHI pixels (Mouri
al.
Fig. et
1 Product
coverage
Radiative transfer calculation using NWP data for
2016a, 2016b). FCP has been produced since Himawari-8
* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency
** System Engineering Division, Data Processing Department, Meteorological Satellite Center
--44
(Received September 1, 2015, Accepted 20 November 2015)
1 --
－ 44 －
METEOROLOGICAL
SATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICAL
SATELLITE
CENTER
TECHNICAL
NOTE,
MARCH,
2016
（二行）
Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product
（二行）
IMAI Takahito* and YOSHIDA Ryo**
（三行）
Abstract
This paper describes the algorithm theoretical basis for the Himawari-8 Cloud Mask Product
(CMP) developed by the Meteorological Satellite Center. CMP is part of the Fundamental Cloud
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
operational since 7 July 2015.
The CMP algorithm is based on the cloud mask technique of NWC-SAF for MSG/SEVIRI and
NOAA/NESDIS for GOES-R/ABI. Most cloud detection tests involve threshold methods based on
radiative transfer calculation using NWP data as atmospheric profiles. The thresholds are modified
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
algorithm was applied to SEVIRI data, with results showing hit ratios with the MODIS product
were around 85% for all seasons.
（三行）
1. Introduction
began operation.
（一行）
This paper describes the algorithm theoretical basis for
Himawari-8 is the new geostationary satellite of the
CMP.
Japan Meteorological Agency (JMA). It was launched on
（一行）
7 October 2014 and began operation on 7 July 2015. The
2. Algorithm
satellite carries the Advanced Himawari Imager (AHI),
which is greatly improved over past imagers in terms of
2.1 Overview
Cloud detection in the CMP algorithm is based on
its number of bands and its temporal/special resolution
comparison of observation data and clear sky data
(Bessho et al. 2016). Using AHI data, JMA’s
calculated from numerical weather prediction (NWP)
Meteorological Satellite Center (MSC) developed the
data. If observation data differ from clear sky data, the
Himawari-8 Cloud Mask Product (CMP).
pixel is cloudy. To discriminate between cloudy and clear
Cloud mask is used to discriminate cloudy pixels
pixels, it is desirable for observation variables in clear
from clear ones in satellite data. Numerous satellite
and cloudy conditions to differ and for the physical
products require cloud mask information. By way of
reason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda and
temperature, reflectance and emissivity of the top and
Shirakawa 1999), Clear Sky Radiance (CSR) (Uesawa
transmittance relating to clouds and the atmosphere).
2009) and Aerosol Detection (Okawara et al. 2003) are
Rather than encompassing retrieval of these five
derived in clear pixels. Conversely, Cloud Grid
variables, most of the tests in the CMP algorithm involve
Information (Tokuno 2002) is processed in cloudy pixels.
the use of brightness temperature or reflectance data with
There were no MSC cloud mask products before the
similar tendencies. Cloud mask tests are based on the
start of Himawari-8’s operation; each satellite product
cloud mask algorithm of the NoWCasting (NWC)
had its own cloud mask process. As cloud mask is also
Satellite Application Facility (SAF) (Meteo-France,
required for most Himawari-8 products, MSC decided to
2012) and the National Oceanic and Atmospheric
develop CMP as a resource available for Himawari-8
Administration
(NOAA)/National
Environmental
products in
common.
CMP
is a part
of03
the(0.64
Fundamental
Fig.
2 (a) AHI
imagery,
band
μm), (b) AHI imagery,
band 13, (c)
cloud mask,
Satellite, Data, and Information Service (NESDIS)
Cloud Product (FCP), which contains cloud phase, type
(d) snow ice mask, (e) cloud type and (f) cloud top height for 0200 UTC on 10 April 2015
(Heidinger and Straka III, 2012).
and top height for Himawari-8/AHI pixels (Mouri et al.
Radiative transfer calculation using NWP data for
2016a, 2016b). FCP has been produced since Himawari-8
* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency
** System Engineering Division, Data Processing Department, Meteorological Satellite Center
--45
(Received September 1, 2015, Accepted 20 November 2015)
1 --
－ 45 －
METEOROLOGICAL
SATELLITE
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No.61,No.61,
MARCH,
2016
METEOROLOGICAL
SATELLITE
CENTER
TECHNICAL
NOTE,
MARCH,
2016
3 HCAI Formulation Process
3.2 Determination of Cloud Type
（二行）
Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product
3.1 Calculation of Cloud Mask, Snow Ice Mask and
Cloud Top Height
（二行）
FCP cloud types include opaque, semi-transparent and
fractional, while those in HCAI are expressed as
IMAI Takahito* and YOSHIDA
Ryo** dense cloud and the like. That is, FCP
cumulonimbus,
（三行）
HCAI cloud mask, snow ice mask and cloud top
cloud types are based on optical or radiative properties,
height are derived from FCP via projection conversion.
while those of HCAI are based on meteorological
HCAI is produced from such conversion (for normalized
properties. Thus, the physical meanings of these cloud
Abstract
paper describes
the algorithm
theoretical type
basis expressions
for the Himawari-8
Cloud such
Maska Product
geostationary This
projection)
into equidistant
cylindrical
differ. Against
background, and
(CMP)
developed
by
the
Meteorological
Satellite
Center.
CMP
is
part
of
the
Fundamental
Cloud types for
projection using the nearest-neighbor approach.
algorithm was developed to classify cloud
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
Quality flags
for cloud
cloud top height
HCAI. This element is produced using data such as FCP
operational
sincemask
7 Julyand
2015.
include quality
information
foron HCAI
asmaskcloud
type and
AHI brightness
temperature (bands
Thecontrol
CMP algorithm
is based
the cloud
technique
of NWC-SAF
for MSG/SEVIRI
and 08, 10
for GOES-R/ABI. Most cloud detection
tests involve threshold methods based on
discussed inNOAA/NESDIS
3.3 below.
and 13).
radiative
transfer
calculation
using
NWP
data
as
atmospheric
profiles.
Theclassification
thresholds arealgorithm
modified for cloud
Snow ice mask is produced from FCP surface
A flowchart
of the
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
condition data. Snow ice is detected using the last four
type is shown below (Fig. 3), with BT(B10) and
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
days of dataalgorithm
and a snow
product
deriveddata,
fromwith
data results
BT(B08)
thethebrightness
temperature of
wasdepth
applied
to SEVIRI
showingrepresenting
hit ratios with
MODIS product
collected bywere
microwave
sensors
low-earth-orbit
bands 10 and 08, respectively. maxBT(B13) and
around 85%
for on
all board
seasons.
（三行）
(LEO) satellites. Accordingly, snow ice mask can
minBT(B13) are the maximum and minimum brightness
provide data on snow ice below cloud levels.
temperatures of band 13 around the HCAI grid,
began operation.
1. Introduction
respectively.
（一行）
This paper describes the algorithm theoretical basis for
Himawari-8 is the new geostationary satellite of the
CMP.
Japan Meteorological Agency (JMA). It was launched on
（一行）
7 October 2014 and began operation on 7 July 2015. The
2. Algorithm
satellite carries the Advanced Himawari Imager (AHI),
which is greatly improved over past imagers in terms of
2.1 Overview
Cloud detection in the CMP algorithm is based on
its number of bands and its temporal/special resolution
comparison of observation data and clear sky data
(Bessho et al. 2016). Using AHI data, JMA’s
calculated from numerical weather prediction (NWP)
Meteorological Satellite Center (MSC) developed the
data. If observation data differ from clear sky data, the
Himawari-8 Cloud Mask Product (CMP).
pixel is cloudy. To discriminate between cloudy and clear
Cloud mask is used to discriminate cloudy pixels
pixels, it is desirable for observation variables in clear
from clear ones in satellite data. Numerous satellite
and cloudy conditions to differ and for the physical
products require cloud mask information. By way of
reason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda and
temperature, reflectance and emissivity of the top and
Shirakawa 1999), Clear Sky Radiance (CSR) (Uesawa
transmittance relating to clouds and the atmosphere).
2009) and Aerosol Detection (Okawara et al. 2003) are
Rather than encompassing retrieval of these five
derived in clear pixels. Conversely, Cloud Grid
variables, most of the tests in the CMP algorithm involve
Information (Tokuno 2002) is processed in cloudy pixels.
the use of brightness temperature or reflectance data with
There were no MSC cloud mask products before the
similar tendencies. Cloud mask tests are based on the
start of Himawari-8’s operation; each satellite product
cloud mask
algorithm of the NoWCasting (NWC)
had its own cloud mask process. As cloud
is type
also classification
Fig. 3mask
Cloud
flowchart
Satellite Application Facility (SAF) (Meteo-France,
required for most Himawari-8 products, MSC decided to
2012) and the National Oceanic and Atmospheric
develop CMP as a resource available for Himawari-8
Administration
(NOAA)/National
Environmental
products in common. CMP is a part of the Fundamental
Satellite, Data, and Information Service (NESDIS)
Cloud Product (FCP), which contains cloud phase, type
(Heidinger and Straka III, 2012).
and top height for Himawari-8/AHI pixels (Mouri et al.
Radiative transfer calculation using NWP data for
2016a, 2016b). FCP has been produced since Himawari-8
* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency
** System Engineering Division, Data Processing Department, Meteorological Satellite Center
--46
(Received September 1, 2015, Accepted 20 November 2015)
1 --
－ 46 －
METEOROLOGICAL
SATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICAL
SATELLITE
CENTER
TECHNICAL
NOTE,
MARCH,
2016
3.3 Quality Control Information
reported in SCGID even though convective cloud
（二行）
amount (cumulonimbus) is one of its elements (not
Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product
Quality control information provides quality flags
shown). Meanwhile, local cumulonimbus
（二行）
was
based on Himawari Standard Data (HSD) and FCP data.
determined in Gunma, Fukushima and Miyagi
IMAIofTakahito
* and YOSHIDA
Ryo
HSD quality flags such as validity
quality,
prefectures
in**HCAI thanks to its high spatial resolution
（三行）
sun-related data degradation (e.g., sun avoidance, stray
(0.02° in both latitude and longitude). This indicates that
light), moon-related data degradation, solar calibration
HCAI enabled detection of local cumulonimbus that was
and solar eclipse are used for this information. FCP
missed by SCGID.
Abstract
Thisaspaper
the algorithm
basis for the Himawari-8 Cloud Mask Product
quality flags such
clouddescribes
mask, cloud
type and theoretical
cloud
(CMP)
developed
by
the
Meteorological
Satellite
Center.
CMP is part of the Fundamental Cloud
top height are also used.
4.2 Stratus/Fog
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
Quality control
information
data2015.
are stored in each
operational
since 7 July
HCAI grid square
single
bytes (eight
bits).
Figure of
5 NWC-SAF
(a) provides
imagery showing
AHI
The in
CMP
algorithm
is based
on As
the shown
cloud mask technique
for MSG/SEVIRI
and
for selected
GOES-R/ABI.
Most cloud
tests involve
on including
in Table 2, NOAA/NESDIS
eight elements are
and allocated
in detection
differences
betweenthreshold
bands 07methods
(3.9 μm)based
and 13
radiative
transfer
calculation
using
NWP
data
as
atmospheric
profiles.
The
thresholds
are
modified
order from the least significant bit. Quality is represented
surface synoptic observations (SYNOP) when stratus or
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
as zero (potentially high quality) or one (potentially low
fog appeared over the eastern Sakhalin sea from the Sea
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
quality) for algorithm
each bit. was applied to SEVIRI data, with results
of showing
Japan to the
northwest
the Hidaka
and Kushiro
hit ratios
withand
the in
MODIS
product
were around 85% for all seasons.
offings for 1200 UTC on 16 June 2015. Stratus or fog
Table 2 Details of quality control information
（三行）
pushed into the interior of Hokkaido and China, and fog
1. Introduction
（一行）
Himawari-8 is the new geostationary satellite of the
Japan Meteorological Agency (JMA). It was launched on
7 October 2014 and began operation on 7 July 2015. The
satellite carries the Advanced Himawari Imager (AHI),
which is greatly improved over past imagers in terms of
its number of bands and its temporal/special resolution
(Bessho et al. 2016). Using AHI data, JMA’s
Meteorological Satellite Center (MSC) developed the
Himawari-8 Cloud Mask Product (CMP).
4 Characteristics of Cloud Type Determination
Cloud mask is used to discriminate cloudy pixels
from clear ones in satellite data. Numerous satellite
4.1 Cumulonimbus
products
require cloud mask information. By way of
example, Sea Surface Temperature (SST) (Yasuda and
Shirakawa
Clearimagery
Sky Radiance
(CSR)
(Uesawa
Figure 4 1999),
shows AHI
from band
03 (0.64
μm)
2009)
and echo
Aerosol
Detection
(Okawara
et al.
2003)
(a), radar
imagery
(b), SCGID
cloud
type
(c), are
and
derived
in
clear
pixels.
Conversely,
Cloud
Grid
HCAI cloud type (d) for every hour from 0600 to 0800
Information (Tokuno 2002) is processed in cloudy pixels.
UTC, when gusting winds caused damage in the
There were no MSC cloud mask products before the
Isesaki-shi area of Japan’s Gunma Prefecture on 15 June
start of Himawari-8’s operation; each satellite product
2015.itsThe
03 mask
imagery
and radar
echo data
had
ownband
cloud
process.
As cloud
maskfacilitate
is also
understanding
of
how
cumulonimbus
developed.
required for most Himawari-8 products, MSC decided to
develop
as a resource
available
for Himawari-8
Local CMP
cumulonimbus
was not
determined
in SCGID
products
common.
is a part
of theinFundamental
due to itsinlow
spatialCMP
resolution
(0.20°
latitude and
Cloud
Product
(FCP),
which
contains
cloud
0.25° in longitude). Cumulonimbus wasphase,
also type
not
and top height for Himawari-8/AHI pixels (Mouri et al.
2016a, 2016b). FCP has been produced since Himawari-8
or mist was recorded in surface observation. The
began operation.
temperature
in Kushiro was 13.1°C and the dew point
This
paper
the algorithm
theoreticalsignificant
basis for
temperature describes
was 13.0°C,
indicating
CMP.
atmospheric dampness. Figure 5 (b) shows an emagram
（一行）
of
sonde
observation
at
Kushiro for the same location as
2. Algorithm
Fig. 5 (a). It indicates that an inversion layer formed
fromOverview
the ground toward the vicinity of 930 hPa, and that
2.1
the Fog
CMPwas
algorithm
is form
basedwith
on
the Cloud
lower detection
layer wasinwet.
likely to
comparison
of observation data and clear sky data
these conditions.
calculated
from
numerical
weather
(NWP)
Figures 5 (c) and
(d) show
SCGIDprediction
and HCAI
cloud
data. If observation data differ from clear sky data, the
types, respectively, for the same location as Fig. 5 (a). In
pixel is cloudy. To discriminate between cloudy and clear
general,it SCGID
tends
suggest variables
the presence
of
pixels,
is desirable
for to
observation
in clear
stratocumulus
around stratus
grid squares.
seen in
and
cloudy conditions
to differ
and for This
the is
physical
Fig. 5 (c),
whichthe
indicates
stratocumulus
in the vicinity
reason
behind
difference
to be explicit
(e.g.,
temperature,
reflectance the
andsmooth
emissivity
of region
the topin and
of Kushiro. Meanwhile,
white
Fig.
transmittance
relatingastostratus
clouds orandfogtheinatmosphere).
5 (a) is identified
Fig. 5 (d).
Rather
than
encompassing
retrieval
of
these infive
According to the latter, stratus or fog is present
the
variables, most of the tests in the CMP algorithm involve
vicinity of Kushiro, which corresponds closely to the
the use of brightness temperature or reflectance data with
results of surface observation and the emagram.
similar tendencies. Cloud mask tests are based on the
It should
noted that of
it isthe
difficult
to determine
from
cloud
maskbealgorithm
NoWCasting
(NWC)
satellite observation
the cloud
is grounded.
Satellite
Applicationwhether
Facility
(SAF)base
(Meteo-France,
2012) and the National Oceanic and Atmospheric
Administration
(NOAA)/National
Environmental
Satellite, Data, and Information Service (NESDIS)
(Heidinger and Straka III, 2012).
Radiative transfer calculation using NWP data for
* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency
** System Engineering Division, Data Processing Department, Meteorological Satellite Center
--47
(Received September 1, 2015, Accepted 20 November 2015)
1 --
－ 47 －
METEOROLOGICAL
SATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICAL
SATELLITE
CENTER
TECHNICAL
NOTE,
MARCH,
2016
（二行）
Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product
（二行）
IMAI Takahito* and YOSHIDA Ryo**
（三行）
Abstract
This paper describes the algorithm theoretical basis for the Himawari-8 Cloud Mask Product
(CMP) developed by the Meteorological Satellite Center. CMP is part of the Fundamental Cloud
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
operational since 7 July 2015.
The CMP algorithm is based on the cloud mask technique of NWC-SAF for MSG/SEVIRI and
NOAA/NESDIS for GOES-R/ABI. Most cloud detection tests involve threshold methods based on
radiative transfer calculation using NWP data as atmospheric profiles. The thresholds are modified
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
algorithm was applied to SEVIRI data, with results showing hit ratios with the MODIS product
were around 85% for all seasons.
（三行）
1. Introduction
began operation.
（一行）
This paper describes the algorithm theoretical basis for
Himawari-8 is the new geostationary satellite of the
CMP.
Japan Meteorological Agency (JMA). It was launched on
（一行）
7 October 2014 and began operation on 7 July 2015. The
2. Algorithm
satellite carries the Advanced Himawari Imager (AHI),
which is greatly improved over past imagers in terms of
2.1 Overview
Cloud detection in the CMP algorithm is based on
its number of bands and its temporal/special resolution
comparison of observation data and clear sky data
(Bessho et al. 2016). Using AHI data, JMA’s
calculated from numerical weather prediction (NWP)
Meteorological Satellite Center (MSC) developed the
data. If observation data differ from clear sky data, the
Himawari-8 Cloud Mask Product (CMP).
pixel is cloudy. To discriminate between cloudy and clear
Cloud mask is used to discriminate cloudy pixels
pixels, it is desirable for observation variables in clear
from clear ones in satellite data. Numerous satellite
and cloudy conditions to differ and for the physical
products require cloud mask information. By way of
reason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda and
temperature, reflectance and emissivity of the top and
Shirakawa 1999), Clear Sky Radiance (CSR) (Uesawa
transmittance relating to clouds and the atmosphere).
2009) and Aerosol Detection (Okawara et al. 2003) are
Rather than encompassing retrieval of these five
derived in clear pixels. Conversely, Cloud Grid
variables, most of the tests in the CMP algorithm involve
Information (Tokuno 2002) is processed in cloudy pixels.
the use of brightness temperature or reflectance data with
There were no MSC cloud mask products before the
similar tendencies. Cloud mask tests are based on the
start of Himawari-8’s operation; each satellite product
cloud mask algorithm of the NoWCasting (NWC)
had its own cloud mask process. As cloud mask is also
Satellite Application Facility (SAF) (Meteo-France,
required for most Himawari-8 products, MSC decided to
Fig.a 4resource
(a) AHI imagery
03, (b) radar2012)
echo imagery,
SCGID cloud
type and
and the(c)National
Oceanic
and Atmospheric
develop CMP as
availablefrom
for band
Himawari-8
Environmental
products in common. (d)
CMP
is a cloud
part oftype
the for
Fundamental
HCAI
the period from Administration
0600 to 0800 UTC (NOAA)/National
on 15 June 2015
Satellite, Data, and Information Service (NESDIS)
Cloud Product (FCP), which contains cloud phase, type
(Heidinger and Straka III, 2012).
and top height for Himawari-8/AHI pixels (Mouri et al.
Radiative transfer calculation using NWP data for
2016a, 2016b). FCP has been produced since Himawari-8
* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency
** System Engineering Division, Data Processing Department, Meteorological Satellite Center
--48
(Received September 1, 2015, Accepted 20 November 2015)
1 --
－ 48 －
METEOROLOGICAL
SATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICAL
SATELLITE
CENTER
TECHNICAL
NOTE,
MARCH,
2016
（二行）
Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product
（二行）
IMAI Takahito* and YOSHIDA Ryo**
（三行）
Abstract
This paper describes the algorithm theoretical basis for the Himawari-8 Cloud Mask Product
(CMP) developed by the Meteorological Satellite Center. CMP is part of the Fundamental Cloud
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
operational since 7 July 2015.
The CMP algorithm is based on the cloud mask technique of NWC-SAF for MSG/SEVIRI and
NOAA/NESDIS for GOES-R/ABI. Most cloud detection tests involve threshold methods based on
radiative transfer calculation using NWP data as atmospheric profiles. The thresholds are modified
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
algorithm was applied to SEVIRI data, with results showing hit ratios with the MODIS product
were around 85% for all seasons.
（三行）
1. Introduction
began operation.
（一行）
This paper describes the algorithm theoretical basis for
Himawari-8 is the new geostationary satellite of the
CMP.
Japan Meteorological Agency (JMA). It was launched on
（一行）
7 October 2014 and began operation on 7 July 2015. The
2. Algorithm
satellite carries the Advanced Himawari Imager (AHI),
which is greatly improved over past imagers in terms of
2.1 Overview
Fig. 5 (a) Imagery showing AHI differences between bands 07 and 13 including SYNOP, (b) emagram for Kushiro,
Cloud detection in the CMP algorithm is based on
its number of bands and its temporal/special resolution
(c)
SCGID
cloud
type
and
(d)
HCAI
cloud
type
for
1200
UTC on 16
2015
comparison
of June
observation
data and clear sky data
(Bessho et al. 2016). Using AHI data, JMA’s
calculated from numerical weather prediction (NWP)
Meteorological Satellite Center (MSC) developed the
data. If observation data differ from clear sky data, the
Himawari-8 Cloud Mask Product (CMP).
The data are for 0000 UTC on 17 June 2015 after
5 Conclusions
pixel is cloudy. To discriminate between cloudy and clear
Cloud mask is used to discriminate cloudy pixels
sunrise.
Figures
(a) satellite
and (b) indicate
that the vicinity
of
pixels, it is desirable for observation variables in clear
from
clear
ones6 in
data. Numerous
satellite
Kushiro was
covered
with
low information.
cloud with a By
smooth
productto– differ
the successor
SCGID
andMSC’s
cloudyHCAI
conditions
and for tothethephysical
products
require
cloud
mask
way top.
of
The surface
data for Kushiro
in Fig. 6and
(a)
product behind
– is the
baseddifference
on observational
data (e.g.,
from
reason
to be explicit
example,
Seaobservation
Surface Temperature
(SST) (Yasuda
temperature,
reflectance
emissivitythe
of five
the elements
top and
Shirakawa
1999),
Clear
Sky Radiance
indicate that
the fog
cleared.
However,(CSR)
mist (Uesawa
was still
Himawari-8 and
FCP, andand
incorporates
transmittance
to clouds
and the
atmosphere).
2009)
andand
Aerosol
Detection
al.stratus
2003) was
are
observed
produced
poor (Okawara
visibility, et
and
of cloud maskrelating
(including
dust mask),
snow
ice mask,
Rather
than
encompassing
retrieval
of
these
five
derived
in
clear
pixels.
Conversely,
Cloud
Grid
observed in the sky. The emagram in Fig. 6 (c) suggests
cloud type, cloud top height and quality control
variables, most of the tests in the CMP algorithm involve
Information (Tokuno 2002) is processed in cloudy pixels.
that the inversion layer dissolved and wetness was low in
information. Its maximum coverage is from 60°N to
the use of brightness temperature or reflectance data with
There were no MSC cloud mask products before the
the lower layer.
60°S and from 80°E to 160°W, and its spatial resolution
similar tendencies. Cloud mask tests are based on the
start of Himawari-8’s operation; each satellite product
SCGID
cloud
data As
in Fig.
(d) indicate
is 0.02°mask
in both
latitude of
and the
longitude.
It is capable
of
cloud
algorithm
NoWCasting
(NWC)
hadThe
its own
cloud
masktype
process.
cloud6mask
is also
cumulus for
andmost
stratocumulus
Kushiro.
However,
reporting Application
local cumulonimbus
stratus/fog
that are
Satellite
Facility and
(SAF)
(Meteo-France,
required
Himawari-8near
products,
MSC
decided the
to
2012)
the National
Oceanic
and Atmospheric
develop
CMP
as a6 resource
HCAI data
in Fig.
(e) showavailable
stratus orfor
fogHimawari-8
in the area,
missed and
by SCGID,
and is used
for operational
weather
Administration
(NOAA)/National
Environmental
products
in common.
CMP with
is a part
of the
Fundamental
which corresponds
closely
surface
observation
and
forecasting.
Satellite,
Data,
and
Information
Service
(NESDIS)
Cloud
Product
(FCP),
which
contains
cloud
phase,
type
the emagram for Kushiro.
(Heidinger and Straka III, 2012).
and top height for Himawari-8/AHI pixels (Mouri et al.
Radiative transfer calculation using NWP data for
2016a, 2016b). FCP has been produced since Himawari-8
* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency
** System Engineering Division, Data Processing Department, Meteorological Satellite Center
--49
(Received September 1, 2015, Accepted 20 November 2015)
1 --
－ 49 －
METEOROLOGICAL
SATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICAL
SATELLITE
CENTER
TECHNICAL
NOTE,
MARCH,
2016
（二行）
Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product
（二行）
IMAI Takahito* and YOSHIDA Ryo**
（三行）
Abstract
This paper describes the algorithm theoretical basis for the Himawari-8 Cloud Mask Product
(CMP) developed by the Meteorological Satellite Center. CMP is part of the Fundamental Cloud
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
operational since 7 July 2015.
The CMP algorithm is based on the cloud mask technique of NWC-SAF for MSG/SEVIRI and
NOAA/NESDIS for GOES-R/ABI. Most cloud detection tests involve threshold methods based on
radiative transfer calculation using NWP data as atmospheric profiles. The thresholds are modified
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
algorithm was applied to SEVIRI data, with results showing hit ratios with the MODIS product
were around 85% for all seasons.
（三行）
1. Introduction
began operation.
（一行）
This paper describes the algorithm theoretical basis for
Fig. 6 (a) AHI imagery from band 03 including SYNOP, (b) AHI imagery for band 13, (c) emagram for Kushiro,
Himawari-8 is the new geostationary satellite of the
CMP.
(d) SCGID cloud type and (e) HCAI cloud type for 0000 UTC on 17 June 2015
Japan Meteorological Agency (JMA). It was launched on
（一行）
7 October 2014 and began operation on 7 July 2015. The
2. Algorithm
References
satellite
carries the Advanced Himawari Imager (AHI),
which is greatly improved over past imagers in terms of
2.1 Overview
Cloud
CMP and
algorithm
is based
on
its
number
its temporal/special
Bessho,
K., ofK.bands
Date, and
M. Hayashi,
A. Ikeda, T.resolution
Imai, H.
Mouri,
K.,detection
T. Izumi,inH.theSuzue,
R. Yoshida,
2016a:
comparison
of Theoretical
observation Basis
data and
clear sky
data
(Bessho
2016). T.Using
AHI H.
data,
JMA’sT.
Inoue,et Y.al.Kumagai,
Miyakawa,
Murata,
Algorithm
Document
of Cloud
calculated
from
numerical
weather
prediction
(NWP)
Meteorological
Satellite
Center
(MSC)
developed
the
Ohno, A. Okuyama, R. Oyama, Y. Sasaki, Y.
Type/Phase Product. Meteorological Satellite
data. If observation data differ from clear sky data, the
Himawari-8 Cloud Mask Product (CMP).
Shimazu, K. Shimoji, Y. Sumida, M. Suzuki, H.
Center Technical Note, 61, 19-31.
pixel is cloudy. To discriminate between cloudy and clear
Cloud mask is used to discriminate cloudy pixels
D. Uesawa,
Yokota,
Mouri, itK.,is H.
Suzue, for
R. Yoshida,
andvariables
T. Izumi,in2016b:
pixels,
desirable
observation
clear
from Taniguchi,
clear onesH.inTsuchiyama,
satellite data.
NumerousH. satellite
and require
R. Yoshida,
2016:
An introduction
Algorithm
Theoretical
Basisand
Document
Cloud
and cloudy
conditions
to differ
for the of
physical
products
cloud mask
information.
By way ofto
Himawari-8/9
Japan's (SST)new-generation
top behind
height product.
Meteorological
reason
the difference
to be Satellite
explicit Center
(e.g.,
example,
Sea Surface Temperature
(Yasuda and
temperature,
and emissivity of the top and
Shirakawa
1999), Clear
Sky Radiance
(CSR)J.(Uesawa
geostationary
meteorological
satellites.
Meteor.
Technicalreflectance
Note, 61, 33-42.
transmittance
to clouds and
the atmosphere).
2009)Soc.
andJapan,
Aerosol
(Okawara et al. 2003) are
94,Detection
doi:10.2151/jmsj.2016-009.
Tokuno,
M., relating
2002: Advanced
Satellite
Cloud Grid
Rather
than
encompassing
retrieval
of
theseCenter
five
derived
in
clear
pixels.
Conversely,
Cloud
Grid
Imai, T., and R. Yoshida, 2016: Algorithm theoretical
Information Data. Meteorological Satellite
variables, most of the tests in the CMP algorithm involve
Information (Tokuno 2002) is processed in cloudy pixels.
basis for Himawari-8 Cloud Mask Product.
Technical Note, 40, 1-24.
the use of brightness temperature or reflectance data with
There were no MSC cloud mask products before the
Meteorological Satellite Center Technical Note, 61,
similar tendencies. Cloud mask tests are based on the
start of Himawari-8’s operation; each satellite product
1-17.
cloud mask algorithm of the NoWCasting (NWC)
had its
own cloud mask process. As cloud mask is also
Satellite Application Facility (SAF) (Meteo-France,
required for most Himawari-8 products, MSC decided to
2012) and the National Oceanic and Atmospheric
develop CMP as a resource available for Himawari-8
Administration
(NOAA)/National
Environmental
products in common. CMP is a part of the Fundamental
Satellite, Data, and Information Service (NESDIS)
Cloud Product (FCP), which contains cloud phase, type
(Heidinger and Straka III, 2012).
and top height for Himawari-8/AHI pixels (Mouri et al.
Radiative transfer calculation using NWP data for
2016a, 2016b). FCP has been produced since Himawari-8
* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency
** System Engineering Division, Data Processing Department, Meteorological Satellite Center
--50
(Received September 1, 2015, Accepted 20 November 2015)
1 --
－ 50 －
METEOROLOGICAL
SATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICAL
SATELLITE
CENTER
TECHNICAL
NOTE,
MARCH,
2016
（二行）
Algorithm Theoretical
for Himawari-8 Cloud Mask Product
ひまわりBasis
8 号による高分解能雲情報
（二行）
IMAI Takahito* and YOSHIDA Ryo**
鈴江
（三行）
寛史*、今井
崇人**、毛利
浩樹*
Abstract
This paper describes the algorithm theoretical basis for the Himawari-8 Cloud Mask Product
(CMP) developed by the Meteorological Satellite
要旨Center. CMP is part of the Fundamental Cloud
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
気象衛星センターでは、雲量格子点情報の後継プロダクトである高分解能雲情報を開
operational since 7 July 2015.
発し、2015
年 algorithm
7 月 7 日から各地の気象官署等への配信を開始した。このプロダクトは雲の
The CMP
is based on the cloud mask technique of NWC-SAF for MSG/SEVIRI and
有無（ダストの有無を含む）
、雪氷の有無、雲型、雲頂高度、品質情報の
つの要素から構
NOAA/NESDIS for GOES-R/ABI.
Most cloud detection tests involve threshold5 methods
based on
radiative
transfer
calculation
using
NWP
data
as
atmospheric
profiles.
The
thresholds
are
modified
成されている。各要素の空間分解能は 0.02°（緯度）×0.02°（経度）であり、これまでの 0.20°
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
（緯度）×0.25°（経度）よりも高分解能となっている。各要素はひまわり 8 号観測データ
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
や基本雲プロダクトを利用して算出される。
algorithm was applied to SEVIRI data, with results showing hit ratios with the MODIS product
高分解能になったことにより、これまで算出できなかったような小さい積乱雲を捉え
were
around 85% for all seasons.
（三行）
ることが可能となった。また、雲頂表面の凹凸を鮮明に捉えることが可能となり、層雲ま
たは霧域の周辺が層積雲と判別されることが少なくなった。
began operation.
1. Introduction
（一行）
This paper describes the algorithm theoretical basis for
Himawari-8 is the new geostationary satellite of the
CMP.
Japan Meteorological Agency (JMA). It was launched on
（一行）
7 October 2014 and began operation on 7 July 2015. The
2. Algorithm
satellite carries the Advanced Himawari Imager (AHI),
which is greatly improved over past imagers in terms of
2.1 Overview
Cloud detection in the CMP algorithm is based on
its number of bands and its temporal/special resolution
comparison of observation data and clear sky data
(Bessho et al. 2016). Using AHI data, JMA’s
calculated from numerical weather prediction (NWP)
Meteorological Satellite Center (MSC) developed the
data. If observation data differ from clear sky data, the
Himawari-8 Cloud Mask Product (CMP).
pixel is cloudy. To discriminate between cloudy and clear
Cloud mask is used to discriminate cloudy pixels
pixels, it is desirable for observation variables in clear
from clear ones in satellite data. Numerous satellite
and cloudy conditions to differ and for the physical
products require cloud mask information. By way of
reason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda and
temperature, reflectance and emissivity of the top and
Shirakawa 1999), Clear Sky Radiance (CSR) (Uesawa
transmittance relating to clouds and the atmosphere).
2009) and Aerosol Detection (Okawara et al. 2003) are
Rather than encompassing retrieval of these five
derived in clear pixels. Conversely, Cloud Grid
variables, most of the tests in the CMP algorithm involve
Information (Tokuno 2002) is processed in cloudy pixels.
the use of brightness temperature or reflectance data with
There were no MSC cloud mask products before the
similar tendencies. Cloud mask tests are based on the
start of Himawari-8’s operation; each satellite product
cloud mask algorithm of the NoWCasting (NWC)
had its own cloud mask process. As cloud mask is also
Satellite Application Facility (SAF) (Meteo-France,
required for most Himawari-8 products, MSC decided to
2012) and the National Oceanic and Atmospheric
develop CMP as a resource available for Himawari-8
Administration
(NOAA)/National
Environmental
products in common. CMP is a part of the Fundamental
Satellite, Data, and Information Service (NESDIS)
Cloud Product (FCP), which contains cloud phase, type
(Heidinger and Straka III, 2012).
and top height for Himawari-8/AHI pixels (Mouri et al.
* 気象衛星センターデータ処理部システム管理課
Radiative transfer calculation using NWP data for
2016a,
2016b). FCP has been produced since Himawari-8
** 気象庁観測部観測課観測システム運用室
* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency
** System Engineering Division, Data Processing Department, Meteorological Satellite Center
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(Received September 1, 2015, Accepted 20 November 2015)
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