METEOROLOGICAL SATELLITE CENTER TECHNICAL NOTE, No.61, MARCH, 2016

METEOROLOGICAL SATELLITE CENTER TECHNICAL NOTE, No.61, MARCH, 2016

（二行）

Algorithm Theoretical
BasisInformationfor Himawari-8
Cloud
Mask
Product data
High-resolution
Cloud Analysis
derivedfrom
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
cloudphase,
type
and
top
Himawari-8/AHI
has been
The Meteorological Satellite Center (MSC) of thealtitude
Japan from
Meteorological
Agencyand(JMA)
has
operational
since 7 July2015.
developed
a product
calledHigh-resolution Cloud Analysis Information (HCAI) as the successor to
The Cloud
CMP algorithm
is based onthe(SCGID).
cloud mask
techniqueNWC-SAFfor MSG/SEVIRI
andSatellite
Grid Information
Data
The
product,ofwhich
has been
provided to JMA
NOAA/NESDISfor
GOES-R/ABI.
Most
cloud
detection
tests
involvethresholdmethods
basedonmeteorological observatories and other users since 7 July 2015, is composed of five elements: cloudradiative
transfer
calculation
using
NWP
data
as
atmosphericprofiles.
The
thresholds
aremodifiedmask (including dust mask), snow ice mask, cloud type, cloud top height and quality control
using offsets
determinedon the basisof comparison
with in
thebothMODIS
cloud
product.
Initialinformation.
The
spatial resolutionof eachelement is 0.02°
latitudeandmask
longitude,
makingithigherthat thatof theSCGIDlongitude).
Eachwaselement
is calculated
resultsthan
showedCMP(0.20°
hit ratiolatitude,derived 0.25°
from suchcomparison
more than
85%. The using
CMP
observational
dataapplied
from Himawari-8
Fundamental
Cloud hit
Product
algorithm was
to SEVIRI anddata,thewithresults showing
ratios(FCP).
with the MODIS productThishigh 85%
resolution
HCAI to report local cumulonimbus clouds that are not highlighted
werearoundfor 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
Meteorologicalwhich
is greatly
over bypast theimagers
in terms ofSatellite(MSC)
of temporal/special
the Japan Meteorologicalits
numberCenterof 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
theobservatories to support operational weather forecasting
Himawari-8
Cloud Mask
Product conditions(CMP).
and determinationof 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 ofseries data.Sea
It covered
area from (SST)
52ºN tothe equator
example,Surface theTemperature(Yasudaandand from 114ºE
180ºE,Sky
andRadiance
had a spatial
resolutionofShirakawa
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 makeusecomparisonof Information
observation (HCAI)
data andclear optimal
sky data
calculated
fromnumerical
weather
prediction(NWP)
of these data and launched it on 7 July 2015.
data.
If observationdiffer fromclear sky data,the
BeforeHCAI is data
produced,
the Fundamental
Cloudpixel 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 andand cloudy conditions to differ and for the physicalNumerical
Weatherof JMA.(e.g.,
FCPreason behind
the Prediction
difference(NWP)
to bedataexplicit
is a level-2 productcreatedeach infrared
temperature,reflectanceandforemissivityof theband
top pixel
andof Himawari-8relating
data. It consists
cloudthemask(including
0.20° andin latitude
0.25° inlongitude.
transmittanceto cloudsof andatmosphere).
2009)
Aerosoland
Detection(Okawara
et al.SCGID
2003) wasareRatherthanencompassing
retrieval
of
these
five
derivedinclear
pixels.
Conversely,
Cloud
Grid
surfaceconditiondata),
cloud
type
composed of five elements: total cloud amount, uppervariables,
most
of
the
tests
in
the
CMP
algorithm
involve
Information(Tokuno2002)
isprocessedincloudypixels.
(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
beforethe2(ice/water/mixed) and cloud top height (every 100
height and cloud type (clear , cumulonimbus, cirrus ,similar tendencies. Cloud mask tests are based on thestart of Himawari-8’s operation; each satellite productmiddle cloud, cumulus, stratocumulus, stratus/fog andmeters). 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 clouddata.
Satellite
Application Facility (SAF) (Meteo-France,
requiredfor most
Himawari-8 products, MSC decided to
2012)
and
the National Oceanic and AtmosphericdevelopCMP
asaresource
available
for
Himawari-8
1
No cloud
Administration(NOAA)/National
Environmental
productsin common. CMP is a part of the Fundamental
2
Semi-transparent upper cloud3
Satellite,
Data,
and
Information
Service(NESDIS)Cloud
Product(FCP),
which
contains
cloudphase,
type
Opaque upper cloud(Heidinger and Straka III, 2012).
and top height for Himawari-8/AHI pixels (Mouri et al.
* SystemEngineering
Processing
Department,
Meteorological
Satellite Center
Radiative
transfer calculation using NWP data for
2016a,
2016b).
FCP Division,
has beenData
producedsince
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 －

METEOROLOGICALSATELLITE
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2016
METEOROLOGICALSATELLITE
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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 (7.3μm) 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 partof the Fundamental
Cloud
2.3 Calculation
MeteorologicalParameters
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
operational since 7 July 2015.
The productincorporates
following meteorological
The CMP algorithm is based on the cloud mask technique
of NWC-SAF
fortheMSG/SEVIRIandNOAA/NESDIS for GOES-R/ABI. Most cloud detection
tests involve threshold methods based onparameters:
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
absenceof snow/ice)algorithm was applied to SEVIRI data, with results ・Snowshowing ice
hit mask
ratios(presencewith 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 theJapan Meteorological Agency (JMA). It was launched on
Coverage
Resolution
72.1October
2014and
andSpatial
began operationon 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 pastin andtermsfromof
2.1 Overview
Cloud detection in the CMP algorithm is based on
its
numberof bands
and its temporal/special resolution
80°E
to 160°W(Fig. 1).
comparisonof observation
dataand
anda sample
clear skydata(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
fromnumerical
weather
prediction(NWP)
Meteorological
Satellite
Center(MSC)
developed
thelatitude and longitude, making a total of 6,001 grid(Fig. 2 (c) – (f)) for 0200 UTC on 10 April 2015 aredata. If observation data differ from clear sky data, theHimawari-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 physicalproducts require cloud mask information. By way ofreason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda andtemperature, reflectance and emissivity of the top andShirakawa 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 Gridvariables, 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 thesimilar tendencies. Cloud mask tests are based on thestart of Himawari-8’s operation; each satellite productcloud 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 to2012) and the National Oceanic and Atmosphericdevelop 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 (Mourial.
Fig. et1 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 －

METEOROLOGICALSATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICALSATELLITE
CENTERTECHNICALNOTE,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 andNOAA/NESDIS for GOES-R/ABI. Most cloud detection tests involve threshold methods based onradiative 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 productwere 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 thedata. If observation data differ from clear sky data, theHimawari-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 physicalproducts require cloud mask information. By way ofreason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda andtemperature, reflectance and emissivity of the top andShirakawa 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 Gridvariables, 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 thesimilar tendencies. Cloud mask tests are based on thestart of Himawari-8’s operation; each satellite productcloud 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 to2012) and the National Oceanic and Atmosphericdevelop CMP as a resource available for Himawari-8
Administration(NOAA)/National
Environmental
products incommon.
CMP
is a partof03
the(0.64
FundamentalFig.
2 (a) AHI
imagery,bandμm), (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 －

METEOROLOGICALSATELLITE
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NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICALSATELLITE
CENTERTECHNICALNOTE,MARCH,
2016

3 HCAI Formulation Process

3.2 Determination of Cloud Type（二行）

Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product3.1 Calculation of Cloud Mask, Snow Ice Mask andCloud Top Height（二行）

FCP cloud types include opaque, semi-transparent andfractional, 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 typebasis expressions
for the Himawari-8
Cloud such
Maska Productgeostationary This
projection)
into equidistantcylindricaldiffer. Against
background, and(CMP)
developedbytheMeteorological
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 cloudcloud top height
HCAI. This element is produced using data such as FCP
operational
sincemask
7 Julyand2015.
include quality
information
foron HCAI
asmaskcloudtype andAHI brightness
temperature (bands
Thecontrol
CMP algorithm
is based
the cloudtechniqueof 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
atmosphericprofiles.
Theclassificationthresholds arealgorithm
modified for cloudSnow ice mask is produced from FCP surface
A flowchartof theusing offsets determined on the basis of comparison with the MODIS cloud mask product. Initialcondition data. Snow ice is detected using the last fourtype is shown below (Fig. 3), with BT(B10) andresults 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
appliedto SEVIRI
showingrepresenting
hit ratios with
MODIS productcollected bywere
microwave
sensors
low-earth-orbit
bands 10 and 08, respectively. maxBT(B13) andaround 85%
for onall 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 thedata. If observation data differ from clear sky data, theHimawari-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 physicalproducts require cloud mask information. By way ofreason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda andtemperature, reflectance and emissivity of the top andShirakawa 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 Gridvariables, 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 thesimilar tendencies. Cloud mask tests are based on thestart of Himawari-8’s operation; each satellite productcloud mask
algorithm of the NoWCasting (NWC)
had its own cloud mask process. As cloudis typealso classification
Fig. 3mask
Cloud
flowchart
Satellite Application Facility (SAF) (Meteo-France,
required for most Himawari-8 products, MSC decided to2012) and the National Oceanic and Atmosphericdevelop 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 －

METEOROLOGICALSATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICALSATELLITE
CENTERTECHNICALNOTE,MARCH,
2016

3.3 Quality Control Information

reported in SCGID even though convective cloud（二行）
amount (cumulonimbus) is one of its elements (notAlgorithm Theoretical Basis for Himawari-8 Cloud Mask ProductQuality control information provides quality flags
shown).

（二行）

Meanwhile,

local

cumulonimbus

wasbased on Himawari Standard Data (HSD) and FCP data.
determined in Gunma, Fukushima and Miyagi
IMAIofTakahito* and YOSHIDARyo
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 thatlight), moon-related data degradation, solar calibration

HCAI enabled detection of local cumulonimbus that wasand solar eclipse are used for this information. FCP
missed by SCGID.
Abstract
Thisaspaper
the algorithm
basis for the Himawari-8 Cloud Mask Productquality flags suchclouddescribes
mask, cloudtype and theoretical
cloud
(CMP)
developedbytheMeteorological
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
singlebytes (eightbits).
Figure of
5 NWC-SAF(a) provides
imagery showing
AHI
The inCMPalgorithm
is basedon As
the showncloud mask techniquefor MSG/SEVIRI
andfor selected
GOES-R/ABI.
Most cloud
tests involveon includingin Table 2, NOAA/NESDIS
eight elements are
and allocatedin detection
differences
betweenthresholdbands 07methods(3.9 μm)based
and 13
radiative
transfer
calculation
using
NWP
data
as
atmosphericprofiles.
The
thresholds
aremodifiedorder 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 resultsof showing
Japan to thenorthwest
the Hidaka
and Kushiro
hit ratios
withandthe inMODIS
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 theJapan 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 theHimawari-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 andShirakawa
Clearimagery
Sky Radiance(CSR)(Uesawa
Figure 4 1999),
shows AHI
from band
03 (0.64μm)
2009)
and echo
Aerosol
Detection(Okawara
et al.
2003)(a), radar
imagery(b), SCGID
cloud
type
(c), areandderivedinclear
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 theIsesaki-shi area of Japan’s Gunma Prefecture on 15 June
start of Himawari-8’s operation; each satellite product2015.itsThe
03 mask
imagery
and radarecho data
hadownbandcloud
process.
As cloudmaskfacilitateis alsounderstandingofhow
cumulonimbus
developed.
required for most Himawari-8 products, MSC decided todevelopas a resource
availablefor Himawari-8
Local CMP
cumulonimbus
was not
determined
in SCGID
products
common.
is a partof theinFundamental
due to itsinlow
spatialCMP
resolution(0.20°
latitude andCloud
Product(FCP),
which
contains
cloud
0.25° in longitude). Cumulonimbus wasphase,
also typenotand 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 fortemperature describes
was 13.0°C,
indicating
CMP.
atmospheric dampness. Figure 5 (b) shows an emagram
（一行）
of
sonde
observation
atKushiro 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
CMPwasalgorithm
is formbasedwithon
the Cloudlower detection
layer wasinwet.
likely tocomparisonof observation data and clear sky data
these conditions.
calculated
fromnumerical
weather(NWP)
Figures 5 (c) and(d) show
SCGIDpredictionand HCAI
cloud
data. If observation data differ from clear sky data, thetypes, 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 presenceofpixels,is desirable
for toobservationin clearstratocumulus
around stratus
grid squares.
seen inandcloudy conditions
to differ
and for This
the isphysicalFig. 5 (c),whichtheindicates
stratocumulus
in the vicinity
reasonbehinddifference
to be explicit(e.g.,
temperature,reflectance theandsmoothemissivityof region
the topin andof Kushiro. Meanwhile,
white
Fig.
transmittance
relatingastostratus
clouds orandfogtheinatmosphere).
5 (a) is identified
Fig. 5 (d).
Ratherthanencompassing
retrievalofthese infive
According to the latter, stratus or fog is present
thevariables, most of the tests in the CMP algorithm involve
vicinity of Kushiro, which corresponds closely to thethe use of brightness temperature or reflectance data withresults of surface observation and the emagram.
similar tendencies. Cloud mask tests are based on the
It should
noted that of
it isthedifficultto determine
from
cloud
maskbealgorithm
NoWCasting(NWC)
satellite observation
the cloudis 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 －

METEOROLOGICALSATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICALSATELLITE
CENTERTECHNICALNOTE,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 andNOAA/NESDIS for GOES-R/ABI. Most cloud detection tests involve threshold methods based onradiative 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 productwere 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 thedata. If observation data differ from clear sky data, theHimawari-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 physicalproducts require cloud mask information. By way ofreason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda andtemperature, reflectance and emissivity of the top andShirakawa 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 Gridvariables, 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 thesimilar tendencies. Cloud mask tests are based on thestart of Himawari-8’s operation; each satellite productcloud 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 toFig.a 4resource(a) AHI imagery
03, (b) radar2012)
echo imagery,
SCGID cloudtype andand the(c)National
Oceanic
and Atmosphericdevelop CMP asavailablefrom
for band
Himawari-8
Environmental
products in common. (d)CMP
is a cloudpart oftype
the forFundamental
HCAI
the period from Administration
0600 to 0800 UTC (NOAA)/Nationalon 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 －

METEOROLOGICALSATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICALSATELLITE
CENTERTECHNICALNOTE,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 andNOAA/NESDIS for GOES-R/ABI. Most cloud detection tests involve threshold methods based onradiative 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 productwere 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
comparisonof Juneobservation
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 thedata. If observation data differ from clear sky data, theHimawari-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) satelliteand (b) indicatethat the vicinityofpixels, it is desirable for observation variables in clear
from
clear
ones6 in
data. Numerous
satellite
Kushiro wascoveredwithlow information.
cloud with a Bysmoothproductto– differ
the successor
SCGID
andMSC’s
cloudyHCAI
conditions
and for tothethephysicalproducts
requirecloud
mask
way top.
of
The surface
data for Kushiro
in Fig. 6and(a)
product behind– is thebaseddifferenceon observational
data (e.g.,fromreasonto be explicit
example,Seaobservation
Surface Temperature(SST) (Yasuda
temperature,reflectanceemissivitytheof fivethe elements
top andShirakawa
1999),Clear
Sky Radianceindicate thatthe fog
cleared.
However,(CSR)
mist (Uesawa
was still
Himawari-8 and
FCP, andandincorporates
transmittanceto clouds
and theatmosphere).
2009)
andandAerosol
Detection
al.stratus2003) wasareobserved
producedpoor (Okawara
visibility, etandof cloud maskrelating(including
dust mask),snow
ice mask,
Ratherthanencompassing
retrieval
of
these
five
derivedinclear
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 tothe use of brightness temperature or reflectance data with
There were no MSC cloud mask products before thethe lower layer.
60°S and from 80°E to 160°W, and its spatial resolution
similar tendencies. Cloud mask tests are based on thestart of Himawari-8’s operation; each satellite product
SCGID
cloud
data Asin Fig.
(d) indicate
is 0.02°mask
in bothlatitude ofand thelongitude.
It is capableofcloud
algorithm
NoWCasting(NWC)
hadTheits owncloudmasktype
process.
cloud6mask
is alsocumulus forandmoststratocumulus
Kushiro.
However,reporting Application
local cumulonimbus
stratus/fog
that areSatellite
Facility and(SAF)(Meteo-France,
required
Himawari-8near
products,
MSC
decided theto2012)
the National
Oceanic
and AtmosphericdevelopCMP
as a6 resource
HCAI data
in Fig.
(e) showavailable
stratus orfor
fogHimawari-8
in the area,
missed andby SCGID,
and is used
for operational
weather
Administration(NOAA)/National
Environmental
productsin common.
CMP with
is a partof theFundamental
which corresponds
closely
surfaceobservation
andforecasting.
Satellite,
Data,
and
Information
Service(NESDIS)Cloud
Product(FCP),
which
contains
cloudphase,
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 －

METEOROLOGICALSATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICALSATELLITE
CENTERTECHNICALNOTE,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 andNOAA/NESDIS for GOES-R/ABI. Most cloud detection tests involve threshold methods based onradiative 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 productwere around 85% for all seasons.
（三行）

1. Introduction

began operation.
（一行）
This paper describes the algorithm theoretical basis forFig. 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 andalgorithm
is basedon
its
numberits temporal/special
Bessho,K., ofK.bands
Date, andM. Hayashi,
A. Ikeda, T.resolution
Imai, H.
Mouri,
K.,detection
T. Izumi,inH.theSuzue,
R. Yoshida,2016a:
comparisonof Theoreticalobservation Basisdata andclear skydata(Bessho2016). T.Using
AHI H.
data,
JMA’sT.
Inoue,et Y.al.Kumagai,
Miyakawa,
Murata,Algorithm
Documentof Cloudcalculated
fromnumerical
weather
prediction(NWP)
Meteorological
Satellite
Center(MSC)
developed
theOhno, A. Okuyama, R. Oyama, Y. Sasaki, Y.
Type/Phase Product. Meteorological Satellite
data. If observation data differ from clear sky data, theHimawari-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, forR. Yoshida,
andvariables
T. Izumi,in2016b:
pixels,desirable
observationclear
from Taniguchi,
clear onesH.inTsuchiyama,satellite data.
NumerousH. satellite
and require
R. Yoshida,2016:
An introduction
Algorithm
Theoretical
BasisandDocument
Cloudand cloudy
conditions
to differ
for the ofphysicalproducts
cloud mask
information.
By way ofto
Himawari-8/9
Japan's (SST)new-generation
top behindheight product.
Meteorologicalreasonthe difference
to be Satellite
explicit Center(e.g.,
example,Sea Surface Temperature(Yasuda andtemperature,and emissivity of the top andShirakawa
1999), Clear
Sky Radiance(CSR)J.(Uesawa
geostationary
meteorologicalsatellites.
Meteor.
TechnicalreflectanceNote, 61, 33-42.
transmittanceto clouds andthe 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
Ratherthanencompassing
retrievaloftheseCenter
fivederivedinclear
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 theMeteorological Satellite Center Technical Note, 61,
similar tendencies. Cloud mask tests are based on thestart of Himawari-8’s operation; each satellite product1-17.
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 to2012) and the National Oceanic and Atmosphericdevelop 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 －

METEOROLOGICALSATELLITE
CENTER TECHNICAL
NOTE,
No.61,No.61,
MARCH,
2016
METEOROLOGICALSATELLITE
CENTERTECHNICALNOTE,MARCH,
2016（二行）

Algorithm Theoreticalfor 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 CMPis 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 onradiative
transfer
calculation
using
NWP
data
as
atmosphericprofiles.
The
thresholds
aremodified
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
werearound 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 thedata. If observation data differ from clear sky data, theHimawari-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 physicalproducts require cloud mask information. By way ofreason behind the difference to be explicit (e.g.,
example, Sea Surface Temperature (SST) (Yasuda andtemperature, reflectance and emissivity of the top andShirakawa 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 Gridvariables, 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 thesimilar tendencies. Cloud mask tests are based on thestart of Himawari-8’s operation; each satellite productcloud 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 to2012) and the National Oceanic and Atmosphericdevelop 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--51(Received September 1, 2015, Accepted 20 November 2015)
1 --－ 51 －