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

Algorithm Theoretical Basis Document（二行） for Cloud Top Height Product
Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product
MOURI Kouki*, SUZUE Hiroshi*, YOSHIDA Ryo* and IZUMI Toshiharu**（二行）

IMAI Takahito* and YOSHIDA Ryo**（三行）

Abstract

The cloud top height product is an element of the fundamental cloud product, which
incorporates cloud mask, cloud type/phase andcloud top height. The Meteorological Satellite Center
Abstract(MSC)Thisof JapanMeteorological
Agency(JMA)
separatedcloud type/phaseandProductcloud top
paper describes the algorithm theoretical basis cloud
for themask,
Himawari-8
Cloud Mask
height,which
werecontained
inmiscellaneouslevel
2
products
intheHimawari-7
era,
andput them(CMP) developed by the Meteorological Satellite Center. CMP is part of the Fundamental Cloud
togetheras awhichfundamental
cloudcloud
product.
Thetypecloud
product
the threeelements
Product,
incorporates
phase,
andtoptopheight
altitudefrom incorporates
Himawari-8/AHI
and hasbeen ofcloud
topheight,temperatureandpressure,anditsalgorithm
is
based
on
EUMETSAT’s
NoWCasting
operational since 7 July 2015.
Satellite
Application
Facility
satelliteofdata
from Advanced
Himawari Imager
The
CMP algorithmis (NWCSAF).
based on the The
cloudinputs
maskaretechniqueNWC-SAFfor MSG/SEVIRI
and
(AHI)
observations,verticalprofiledata
fromaradiative
transfer
model
and
cloud
type
data fromcloud
NOAA/NESDIS for GOES-R/ABI. Most cloud detection tests involve threshold methods
baseda on
type/phaseof two profiles.
weeks from20 July to are
2 August
2015
radiativeproduct.
transfer Evaluation
calculation conductedusing NWPoverdataaasperiodatmospheric
The thresholds
modifiedshowed
that
cloud
top
heightwasunderestimatedincomparison
tocorresponding
valuesfrom
MODIS
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial(theresults
Moderate
Resolution
Imaging
Spectroradiometer)
andcomparison
Calipso (Cloud-Aerosol
and CMPInfrared
showedthat the CMP
hit ratio
derived from such
was more than Lidar
85%. The
Pathfinder
Satellite
Observation).
algorithm was applied to SEVIRI data, with results showing hit ratios with the MODIS productwere around 85% for all seasons.

（三行）

1. Introduction（一行）
Himawari-8 is the new geostationary satellite of the
The cloud top height product provides some of the basic
Japan Meteorological Agency (JMA). It was launched on
information for level-2 products, and some cloud
7 October 2014 and began operation on 7 July 2015. The
products carriesof the Meteorological
Satellite Centerofsatellite
the Advanced Himawari
Imager(MSC)(AHI),
Japan isMeteorological
Agency(JMA)
has intheir
which
greatly improved
over past
imagers
termsownofindividual
top andheightretrieval procedure.
Since
its
number cloudof bands
its temporal/special
resolution(Besshoet wasal. launched2016). inUsingdata, operation
JMA’s
Himawari-8
2014 AHIand began
Meteorological
Satellite
Center(MSC)
developedtheon 7 July 2015, MSC has separated cloud mask, cloudHimawari-8 Cloud Mask Product (CMP).
type/phase and cloud top height from miscellaneous
Cloud mask is used to discriminate cloudy pixels
cloud products and put them together into a single output
from clear ones in satellite data. Numerous satellite
calledtherequire
fundamental
cloud information.
product. It isByrational
products
cloud mask
way ofto
createlevel-2
using existing(SST)
cloud(Yasuda
mask, cloud
example,Sea products
Surface Temperatureandtype/phaseand cloud
top Radianceheight information.
The
Shirakawa 1999),
Clear Sky
(CSR) (Uesawa
2009) and Aerosolal. 2003)
arefundamental
cloudDetection
product (Okawara
is also etusedfor High
derivedinclear
pixels.
Conversely,
Cloud
Grid
Resolution Cloud Analysis Information (Suzue et al.
Information(Tokunois processedcloudy2016),
which
is a 2002)
level-2
product. inWith
16 pixels.
bands,
There were no MSC cloud mask products before theHimawari-8 additionally has better observation
start of Himawari-8’s operation; each satellite productperformance
than Himawari-7
As aisresult,
had its own cloudmask process.(MTSAT-2).
As cloud mask
alsoprevious
cloud
topheightestimation
data
from
required for most Himawari-8 products, MSC decided to
Himawari-7
canasnoalonger
be putto practicaluse by MSC.
develop CMP
resource
availablefor Himawari-8
products in common.
CMP isdata
a partfromof the Fundamental
Multi-band
observation
geostationary
Cloud
Product(FCP),
which
contains
cloudphase, typemeteorological satellites (e.g., Cloud Top Temperatureand top height for Himawari-8/AHI pixels (Mouri et al.
2016a, 2016b). FCP has been produced since Himawari-8

began
operation.
and Height(Meteo France 2012) and the ABI Cloud
This
paper
describes
the algorithm
theoretical
Height Algorithm(Heidinger2012))
were basis
used forin
CMP.
previous studies. MSC uses the algorithm adopted for（一行）
Cloud Top Temperature and Height (Meteo France 2012)
2. Algorithm
because it is well established and relatively easy tounderstand.
2.1
OverviewThis
document
outlines
theCMP
cloudalgorithm
top heightisproductClouddetectionin thebased andoncomparison
data andclear skydata
its algorithm.ofTheobservation
product includes
information
on cloudcalculated
fromnumerical
weather
prediction(NWP)
top height, cloud top temperature and cloud top pressure.
data. If observation data differ from clear sky data, theThe document also describes the required input data,
pixel is cloudy. To discriminate between cloudy and clear
practical considerations and related evaluation. The
pixels, it is desirable for observation variables in clear
procedure
the product’s
derivation
is basedon theandcloudyforconditions
to differ
and forthe physical
NWCSAFalgorithm
Francereasonbehindthe (Meteo
difference
to 2012).
be explicit (e.g.,temperature, reflectance and emissivity of the top andtransmittance1.1. Content relating to clouds and the atmosphere).
Rather than encompassing retrieval of these fivevariables,
mostof the tests
in the CMP
algorithm
involve
This is the
Algorithm
Theoretical
Basis
Documentforthe use of brightness temperature or reflectance data withcloud top height, temperature and pressure. It describes
similar tendencies. Cloud mask tests are based on thescientificconsiderations,and other aspects
cloud
mask
algorithm limitationsof the NoWCasting(NWC)ofthe algorithm
used.
Satellite
Application
Facility (SAF) (Meteo-France,2012) and the National Oceanic and Atmospheric
Administration(NOAA)/National
Environmental
1.2. Definitions, acronyms
and abbreviations
Satellite, Data, and Information Service (NESDIS)(Heidinger and Straka III, 2012).
Radiative transfer calculation using NWP data for* System Engineering Division, Data Processing Department, Meteorological Satellite Center** Meteorological Satellite and Observation System Research Department, Meteorological Research Institute* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency(Received August 31, 2015, Accepted November 20, 2015)** System Engineering Division, Data Processing Department, Meteorological Satellite Center(Received September 1, 2015, Accepted 20 November 2015)
-- 33
1 --

－ 33 －

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

ABI: Advanced Baseline Imager (mounted on the（二行） in the same way.
GOES-R satellite).
AHI:

Advanced

Algorithm
Theoretical Basis for Himawari-8
Cloud Mask Product
Himawari Imager (mounted on
2. Cloud top height product outline（二行）

Himawari-8 for observation with 16 bands; central
IMAI* and YOSHIDA
Ryo**height product provides data on cloud top
wavelengths: 0.47, 0.51, 0.64, 0.86, 1.6,
2.3,Takahito
3.9, 6.2,
The cloudtop
6.9, 7.3, 8.6, 9.6, 10.4, 11.2, 12.4, 13.3 microns) .

（三行）

height, cloud top temperature and cloud top pressure as

Calipso: Cloud-Aerosol Lidar and Infrared Pathfinder

calculated using the algorithm adopted for NWCSAF

Satellite Observation.
cloud top height. The cloud type from the Cloud
Abstract
This paper
describes
the algorithm
theoretical Type/Phasebasis for the product
Himawari-8
Cloud
Product
CT: JMA’s CloudType
product,
which includes(Mouriet Maskal. 2016)
is important(CMP)
developedbytheMeteorological
Satellite
Center.
CMP
is
part
of
the
Fundamental
Cloud
information on cloud type and cloud phase. The cloud
because it is used to determine one of three height
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
top heightoperational
product requires
in order toretrieval methods (see Subsection 2.2).
since 7 CT
Julyinformation
2015.
switch methods
cloud
top heightcalculation.
TheforCMP
algorithm
is basedon the cloud mask technique of NWC-SAF for MSG/SEVIRI and
for GOES-R/ABI.
Most cloud detection
testsdata
involve threshold methods based onemissivity of wavelength.
Cloud emissivity
2.1. Inputε(𝜆𝜆𝜆𝜆): CloudNOAA/NESDIS
radiative
transfer
calculation
using
NWP
data
as
atmosphericprofiles.
The thresholds are modified
is the ratio of radiation to black body in a temperature.
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
GOES-R: Geostationary Operational Environmental
i. AHI observation data (6.2, 7.3, 11.2 and 13.3 microns)
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMPSatellite -R
Series. was applied to SEVIRI data, with resultsRadiance
are required
for the cloudalgorithm
showing data
hit ratioswith the MODIS
producttop height
GSM: Global
Spectral
Model(JMA’sNWP model).
product. The spatial resolution is 2 km at the sub-satellite
werearound85% forall seasons.
JMA: Japan Meteorological Agency.

（三行）
point, and normalized geostationary projection (Japan

MODIS:
Moderate
Resolution
Imaging
1. Introduction
Spectroradiometer (mounted on NASA’s Aqua and（一行）
Terra satellites).
Himawari-8 is the new geostationary satellite of the
MSC: Meteorological Satellite Center.
Japan Meteorological Agency (JMA). It was launched on
Numerical
Weather
7NWP:
October
2014 andbegan Prediction.
operation on 7 July 2015. The
NASA: National
Aeronautics
Space Administration.
satellite
carries theAdvancedand
Himawari
Imager (AHI),λ(lambda):
CenterwavelengthofAHI
bands.
which is greatly improved over past imagers in terms of
its
numberbands andits temporal/special
resolution
LRC:
Localofradiative
center.
This is the maximumε(λ)(Bessho
et al. via
2016).
data, from
JMA’s
pixel accesseda largeUsing
adjacentAHI
ε(λ) pixel
theMeteorological
Satellite
Center(MSC)
developed
thetarget pixel. In this cloud top height product, λ is set as
Himawari-8 Cloud Mask Product (CMP).
11.2 microns for LRC calculation. When a target pixel
Cloud mask is used to discriminate cloudy pixels
is cloudy, the LRC is a thick part in the cloud area.
from clear ones in satellite data. Numerous satelliteThis concept
utilized
to judgethe cloudBy
drop
phase
products
requireis cloud
mask
information.
way
of
at
the
edge
of
a
cloud
area,
and
is
incorporated
intotheexample, Sea Surface Temperature (SST) (Yasuda andShirakawa
Clear Sky
Radiance(CSR) (Uesawa
GOES-R 1999),
ABI algorithm(Heidinger2012).
measuredradiance,
𝑅𝑅𝑅𝑅𝑚𝑚𝑚𝑚 represents
𝑅𝑅𝑅𝑅{𝑚𝑚𝑚𝑚,𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜,𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
2009)
and Aerosol(Okawara
et al. 2003)
are𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐} (𝜆𝜆𝜆𝜆):Detection
opaquecloud radiancean
𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜in represents
derivedclear pixels.
Conversely,
Cloud atGrid
arbitrarylevel
ascalculatedusingaradiative
transfer
Information (Tokuno 2002) is processed in cloudy pixels.
model,and no𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐MSC
radiance
via
𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 represents
There werecloud masksurface
products
before theclear air as calculated using a radiative transfer model.
start of Himawari-8’s operation; each satellite product
RTTOV:
code
developedby
had its ownRadiative
cloud masktransfer
process. As
cloudmask is also
EUMETSAT(Eyre1991). products, MSC decided torequiredfor most
Himawari-8
SST: SeaCMP
surfacedevelopastemperature.
a resource available for Himawari-8
productsin common.
CMP is ata partof thewavelength
Fundamentalλ.
𝑇𝑇𝑇𝑇(𝜆𝜆𝜆𝜆): Brightness
temperature
the center
Cloud
Product(FCP),
which
contains
cloudtype
The brightness temperature of other bands phase,is expressed
and top height for Himawari-8/AHI pixels (Mouri et al.
2016a, 2016b). FCP has been produced since Himawari-8

Meteorological Agency 2013) is used. The output rate isbegan
operation.
one productper hour.
This paper describes the algorithm theoretical basis for
CMP.
ii. Radiative transfer data calculated from GSM output
（一行）
RTTOV
is
utilizedforradiative transfer calculation. The
2. Algorithm
variables acquired from RTTOV are radiances observedby Overview
the AHI for individual wavelengths based on the
2.1
Cloud detection
in body
the CMPalgorithm
is basedconditionsof a black
held inequilibriumwith onair
comparison
observationand clear levels.
sky data
temperature ofat thealtitudes dataof mandatoryThe
calculated
fromnumerical
weather
prediction(NWP)
wavelengths are 6.2, 7.3, 11.2 and 13.3 microns. The
data. If observation data differ from clear sky data, thevertical levels are 32 mandatory ones and the surface, but
pixel is cloudy. To discriminate between cloudy and clear
radiances up to the tropopause level are used in mostpixels, it is desirable for observation variables in clear
casescloudy
for height
estimation.
andconditions
to differ and for the physicalreason behind the difference to be explicit (e.g.,temperature,and emissivity of the top andiii. Cloud typereflectancedatatransmittanceto clouds
andtoptheheight
atmosphere).
CT data are relating
utilized forthe cloudproduct.
Ratherthanencompassing
retrieval
of
these
five
Only cloudy pixels and those for which the satellite
variables, most of the tests in the CMP algorithm involve
zenith angle is smaller than 84 degrees are processed in
the use of brightness temperature or reflectance data withthe product. For satellite zenith angle limitation, an angle
similar tendencies. Cloud mask tests are based on theslightlymask
smallerthan theoflimitationof 85 degrees
for
cloud
algorithm
the NoWCasting(NWC)
RTTOV isApplication
set.
Satellite
Facility (SAF) (Meteo-France,2012) and the National Oceanic and Atmospheric
Administration(NOAA)/National
Environmental
iv. Altitude and temperatureof mandatorylevels andSatellite,
Data,
and
Information
Service(NESDIS)surface(Heidinger and Straka III, 2012).
Radiative transfer calculation using NWP data for* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency- 34 ** System Engineering Division, Data Processing Department, Meteorological
Satellite Center(Received September 1, 2015, Accepted 20 November 2015)-1-－ 34 －

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

The relevant altitudes and temperatures are acquired（二行）Under such conditions, application of the intercept
from NWP data.

method results in correction of lower-layer radiation, andAlgorithm Theoretical Basis for Himawari-8 Cloud Mask Productis suitable for single-layered semi-transparent cloud like（二行）

2.2. Process flow of the cloud top height productcirrus.If the intercept method does not produce suitable
IMAI Takahito* and YOSHIDA
Ryo**
results, theradiance
ratioing method is applied; if this（三行）

Cloud top height estimation involves one of thealso fails to produce suitable results, the interpolation

following:

method is utilized. When the radiance ratioing method or
the interpolation method is applied after the intercept
Abstract

This method
paper describes the algorithm theoretical method,basis for LRC
the Himawari-8
Cloud
Maskestimation.
Product This is
i. The interpolation
is utilized forradiance(CMP)
developedbytheMeteorological
Satellite
Center.
CMP
is
part
of
the
Fundamental
ii. The radiance ratioing method
also used for fractional cloud. For opaqueCloudand fractional
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has beeniii. The intercept
methodsince 7 July 2015.
cloud, the interpolation method is utilized. Such cloud isoperationaland only forradiationfrom theandcloud top is
The CMP algorithm is based on the cloud maskopticallytechniquethick,of NWC-SAF
MSG/SEVIRINOAA/NESDIS
Most
tests
threshold methods based on
These methods
are describedforinGOES-R/ABI.
the next chapter(seecloudFig. detection
observed
byinvolve
the AHI.
radiative
transfer
calculation
using
NWP
data
as
atmosphericprofiles.
The
thresholds
are modified
When an inversion layer
is present,
cloud is set at its
1 for the process flow), and their selection depends on theusing offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
upper side. This procedure is also applied for opaque
CT cloud type. For semi-transparent cloud, the intercept
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
cloud
belowhit
theratios
middlelevel
discriminatedby CT.
method is used.
Such cloudis opticallythin, anddata,radiation
algorithm
was applied
to SEVIRI
with results
showingwiththeasMODIS
productfrom the lower
is alsoobserved
by the AHI with thiswerelayer
around85%
for all seasons.
type.

（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 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 topfor Himawari-8/AHI(Mouriet al.
Fig.height
1 Processflow of the cloud pixels
top height
product
opaqueor semi-transparent
cloud is derived Radiativefrom the cloudtype calculation
product. using NWP data fortransfer
2016a,Information
2016b). FCPonhas
been produced
since Himawari-8* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency- 35 ** System Engineering Division, Data Processing Department, Meteorological
Satellite Center(Received September 1, 2015, Accepted 20 November 2015)-1-－ 35 －

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

2.3. Output data（二行）

Algorithm Theoretical Basis for Himawari-8 Cloud Mask Producti. Cloud top height (m)ii. Cloud top temperature (K)iii. Cloud top pressure (hPa)iv. Quality flags（二行）

IMAI Takahito* and YOSHIDA Ryo**（三行）

Chapter 4 provides information on the format of these
Abstract
describes
the algorithm
basis for the Himawari-8 Cloud Mask Productdata, which allThis
havepapera spatial
resolutionof 2 km theoreticalat the(CMP)
developedbytheMeteorological
Satellite
Center.
CMP is part of the Fundamental Cloudsub-satellite point. The output rate is one product per hour.
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has beenFig. 2 Outline of the interpolation method
Cloudy pixels
contain valid
fine pixels contain
operational
since data
7 Julyand2015.
invalid (-9999)The
data.
Pixelswith a issatellite
zenithanglemask technique of NWC-SAF for MSG/SEVIRI and
CMP
algorithm
based onthe cloudfor GOES-R/ABI. Most cloud detection
tests involvethresholdmethods based on
smaller thanNOAA/NESDIS
84 degrees are contained.
3.2. Radianceratioing
methodradiative 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
3. Cloud top height product algorithm
This approach is also known as the CO2 absorption
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
method(Menzelet al with1983)theand
the COproduct2-slicing method.
algorithm was applied to SEVIRI data, with results
showing
hit ratios
MODIS
If cloud is assumed to be a single layer, radiance as
3.1. Interpolation
methodwere around
85% for all seasons.
（三行）
determined by the AHI is formulated as

Radiance observed by the AHI and the vertical profile of
1. Introduction
black
body radiance as calculated using the RTTOV
radiative transfer model（一行）are compared in this approach,
Himawari-8 is the new geostationary satellite of theand the two mandatory levels sandwiching the observed
Japan Meteorological Agency (JMA). It was launched on
The ration
7radiance
October are
2014determined.
and began operation
on 7ofJulyinterpolation
2015. Thebetween carries
the radiancesof theseHimawari
levels is linearly
derivedsatellite
the Advanced
Imager (AHI),
based ison
the improved
observed
Forin terms
pressurewhich
greatly
overradiance.
past imagers
ofits
number of abands
and its
temporal/special
resolution
interpolation,pressure
logarithm
is utilized.
Height,(Bessho
et al.temperature2016). Using
AHI data,from
JMA’spressure andare determinedtheMeteorological
Satellite
Center(MSC)
developed
theinterpolation ratio and the two mandatory levels. This
Himawari-8 Cloud Mask Product (CMP).
method is applicable for levels below the tropopause layer.
Cloud mask is used to discriminate cloudy pixels
When an inversion layer is present, cloud is set at its
from clear ones in satellite data. Numerous satellite
upper
siderequirein the cloud
MSC algorithm.
A wavelengthof 11.2
products
mask information.
By wayofmicronsisadopted,asthisrepresentsawindow
regionexample, Sea Surface Temperature (SST) (Yasuda andShirakawa
1999), This
Clear approach
Sky Radiance(CSR)to(Uesawa
forwater vapor.
is similar
window2009) andestimation
Aerosol Detection
et al.
arechannel(Neiman (Okawara
et al 1993)
and2003)
radiance
derivedinclear
pixels.
Conversely,
Cloud
Grid
fitting (Hamman et al 2014). Figure 2 shows an example
Information (Tokuno 2002) is processed in cloudy pixels.
of pressure determination using this method. The vertical
There were no MSC cloud mask products before theprofile of radiance at 11.2 microns is calculated using
start of Himawari-8’s operation; each satellite productradiative
transfermodel.
The Asinterpolationof
had its own
cloud mask
process.
cloud maskratio
is alsoradiance
betweenthe two products,
levels sandwichingrequired formost Himawari-8
MSC decided thetodevelop CMP
as a resource
availablefor Himawari-8
observed
radiancereflects theinterpolatedpressure
products thein common.
CMP
a part ofshows
the Fundamental
betweentwo levels.
Thisisexample
an observed
Cloud
Product(FCP),
which
contains
cloudphase,
typeradiance of 85.2 mW converted to 591.4 hPa.
and top height for Himawari-8/AHI pixels (Mouri et al.
2016a, 2016b). FCP has been produced since Himawari-8

began= 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 (𝜆𝜆𝜆𝜆) + (1 − 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁)𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 (𝜆𝜆𝜆𝜆) (1)
𝑅𝑅𝑅𝑅𝑚𝑚𝑚𝑚 (𝜆𝜆𝜆𝜆)operation.
This paper describes the algorithm theoretical basis for
CMP.
where N is the cloud amount. If 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 is known,（一行）
heightcanbeestimatedusing the approach of the
2. Algorithm
interpolation method. Equation (1) is transformed toEquation(2).
2.1
Overview
Cloud detection in the CMP algorithm is based oncomparison
andclear sky(𝜆𝜆𝜆𝜆) observation(𝜆𝜆𝜆𝜆) − 𝑅𝑅𝑅𝑅
𝑅𝑅𝑅𝑅𝑚𝑚𝑚𝑚 (𝜆𝜆𝜆𝜆) − 𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐of= 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 �𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜data(2) data
𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 (𝜆𝜆𝜆𝜆)�
calculated from numerical weather prediction (NWP)
data. If observation data differ from clear sky data, theCloud top pressure is estimated from the ratio of radiancepixel is cloudy. To discriminate between cloudy and clear
between two wavelengths (Chahine 1974, Smith and Plattpixels, it is desirable for observation variables in clear
1978).
andcloudy conditions to differ and for the physicalreason behind the difference to be explicit (e.g.,(𝜆𝜆𝜆𝜆1 )−𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 (𝜆𝜆𝜆𝜆
𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁1 �𝑅𝑅𝑅𝑅and(𝜆𝜆𝜆𝜆1 )𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜
𝑅𝑅𝑅𝑅𝑚𝑚𝑚𝑚 (𝜆𝜆𝜆𝜆1 )−𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐reflectancetemperature,emissivityof1)�the top and
=
(3)
(𝜆𝜆𝜆𝜆
)−𝑅𝑅𝑅𝑅
(𝜆𝜆𝜆𝜆
)
𝑅𝑅𝑅𝑅
(𝜆𝜆𝜆𝜆
)−𝑅𝑅𝑅𝑅(𝜆𝜆𝜆𝜆
𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁
�𝑅𝑅𝑅𝑅
𝑚𝑚𝑚𝑚
2
𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
𝑐𝑐𝑐𝑐
𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
2
𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
transmittance relating 2 to𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜
clouds2 andthe2)�atmosphere).
Rather than encompassing retrieval of these fivevariables,
mostofof thethe tests
in the CMP
involve
The valueleft-handside algorithm
is derived
once
the
use
of
brightness
temperatureorreflectancedata
𝑅𝑅𝑅𝑅𝑚𝑚𝑚𝑚 (𝜆𝜆𝜆𝜆1 ) , 𝑅𝑅𝑅𝑅𝑚𝑚𝑚𝑚 (𝜆𝜆𝜆𝜆2 ) , 𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 (𝜆𝜆𝜆𝜆1 ) and 𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 (𝜆𝜆𝜆𝜆2 ) witharesimilar tendencies. Cloud mask tests are based on thedetermined. The value of 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 (𝜆𝜆𝜆𝜆1 ) and 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 (𝜆𝜆𝜆𝜆2 )cloud mask algorithm of the NoWCasting (NWC)
on the right-hand side depend on the vertical profile. As
Satellite Application Facility (SAF) (Meteo-France,
almost equal:
𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁
1 and
2012)
and𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁2theareNational
Oceanic and Atmospheric
Administration(NOAA)/National
Environmental
𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁1≈ 1 Data, and Information Service (NESDIS)(4)
Satellite,
𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁2(Heidinger and Straka III, 2012).
Radiative transfer calculation using NWP data for* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency- 36 ** System Engineering Division, Data Processing Department, Meteorological
Satellite Center(Received September 1, 2015, Accepted 20 November 2015)-1-－ 36 －

METEOROLOGICAL SATELLITE CENTER TECHNICAL NOTE, No.61, MARCH, 2016(251.6 hPa for the 11.2(B14)/6.2(B08)-micron pair, 257.5（二行）
Equation (3) can be written as

hPa for the 11.2(B14)/7.3(B10)-micron pair, and 261.8

Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product(𝜆𝜆𝜆𝜆 )−𝑅𝑅𝑅𝑅(𝜆𝜆𝜆𝜆 )𝑅𝑅𝑅𝑅
𝑅𝑅𝑅𝑅𝑚𝑚𝑚𝑚 (𝜆𝜆𝜆𝜆1 )−𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 (𝜆𝜆𝜆𝜆1 )= 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜(𝜆𝜆𝜆𝜆1)−𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐(𝜆𝜆𝜆𝜆1)
𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 2
𝑅𝑅𝑅𝑅𝑚𝑚𝑚𝑚 (𝜆𝜆𝜆𝜆2 )−𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 (𝜆𝜆𝜆𝜆2 )𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 2

hPa for the 11.2(B14)/13.3(B16)-micron pair. The final（二行）

retrieved cloud top height is the minimum pressure (at the(5)
IMAI Takahito* and YOSHIDA
Ryo** determined from one of the three band
highest altitude)（三行）

Values of 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 (𝜆𝜆𝜆𝜆1 ) and 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 (𝜆𝜆𝜆𝜆2 ) satisfying

pairs. This follows the intercept approach of NWCSAF.

Equation (5) are then derived from the vertical profile of

3.3. Intercept method
Abstract
𝑅𝑅𝑅𝑅𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 is essentially surface radianceThis paper describes the algorithm theoretical basis for the Himawari-8 Cloud Mask Productcalculated using
radiativeby transfer
model, butSatellite
its(CMP)thedeveloped
the MeteorologicalCenter.
CMP is method
part of theFundamental
Cloudis adopted
The Intercept(Schmetz
et al. 1993)
accuracy may
be limited
in incorporates
association withof water
Product,which
cloudthatphase,
type and top altitude from Himawari-8/AHI and has beenfor semi-transparent clouds. In the NWCSAF procedure,
operational
sinceAccordingly,
7 July 2015. measured clear
vapor estimation
in NWP.
a linear expression is first set up via the least square
CMPifalgorithm
is basedon theincloudsky radiance is The
adoptedclear pixels
are present
the 3mask technique of NWC-SAF for MSG/SEVIRI andNOAA/NESDIS for GOES-R/ABI. Most cloud detection
testsininvolvethresholdbasedradiancesonapproacha scatter
diagrammethodsof observedforx 3 pixel array centered on the target pixel. MSC uses
radiative transfer calculation using NWP data as atmosphericprofiles.
The
thresholds
aremodified
two bands. The data contained in the diagram arethree bandusingpairs(11.2(B14)/6.2(B08)-micron
pair,
offsets
determined on the basis of comparison
with the MODIS cloud mask product. Initialradiances of 16 or so pixels around the target pixel, and a
11.2(B14)/7.3(B10)-micron
pair
andfrom such comparison was more than 85%. The CMP
results showed that the CMP
hit ratio derived
33 showing
x 33-pixel
is formed.
There productare no limitations
algorithm was appliedwith results
hittemplate
ratios with
the MODIS
11.2(B14)/13.3(B16)-micronpair)to SEVIRI
in thedata,related
on surface type when the template is made. Next, thewere around 85% for all seasons.
algorithm. Figure 3 shows an example of pressure（三行）
intersection of the black body radiance curve for each
retrieval using this method. The horizontal axis represents
level is derived, along with the relevant linear expression.
pressure (hPa), and the vertical axis shows the value of
began
operation.channel’s radiance at the intersection
1. Introduction
The window
the left-hand side (measured ratio) minus the right hand
（一行）
This
paper
algorithm theoreticalbasis
indicates
the describes
height ofthesemi-transparent
cloud
in for
thesideHimawari-8(simulated ratio)ofEquation(5).
is the new geostationary satellite of the
CMP.
troposphere. The cloud top height is then retrieved as inJapan Meteorological Agency (JMA). It was launched on（一行）
theinterpolation
method.
There are three band pairs in
7 October 2014 and began operation on 7 July 2015. The
2. Algorithm
this algorithm (11.2/6.2 microns, 11.2/7.3 microns andsatellite carries the Advanced Himawari Imager (AHI),
11.2/13.3
microns). The minimum pressure (at the highest
which is greatly improved over past imagers in terms of
2.1
Overview
Cloudisdetectionin theamong
CMP thealgorithm
is basedon4
its number of bands and its temporal/special resolution
altitude)selected fromthree pairs.
Figurecomparisonof observation
data andclear sky
(Bessho et al. 2016). Using AHI data, JMA’s
shows an exampleof how pressure
is retrieved
usingdata
thiscalculated
fromnumerical
weather
prediction(NWP)
Meteorological Satellite Center (MSC) developed themethod. The retrieved radiance of 11.2 microns for thedata. If observation data differ from clear sky data, theHimawari-8 Cloud Mask Product (CMP).
11.2/6.2-micron pair, for example, is 17 mW (Fig. 4 (a)),
pixel is cloudy. To discriminate between cloudy and clear
Cloud mask is used to discriminate cloudy pixels
that for ittheis 11.2/7.3-micron
pair is 23.9variables
mW (Fig.
(b)),
pixels,desirable for observationin 4clearfrom clear ones in satellite data. Numerous satellite
and thatfor the11.2/13.3-micron
16.0themW(Fig. 4andcloudyconditions
to differ pairandisforphysicalproducts require cloud mask information. By way of(c)). Figure
4 (d)that tocloud
pressurereasonbehindthe showsdifference
be topexplicit(e.g.,isexample, Sea Surface Temperature (SST) (Yasuda andtemperature,reflectanceand emissivityof 11.2
the topand
Shirakawa
1999),Clear
Sky Radiance(CSR) (Uesawa
determined fromthe retrieved
radiance of
microns.
Fig. 3 Outlineof theradiance
ratioing method
transmittance
relatingforto11.2
cloudsand istheatmosphere).
2009)
and Aerosol
Detection (Okawara
al. 2003) are
B14:B16
is 11.2/13.3-micron
pair,et B14:B10
is
The radiance profile
microns
calculatedusing
11.2/7.3-micronand B14:B08
is 11.2/6.2-micron
Ratherthanencompassing
retrieval
of
these
five
derivedin clearpair,
pixels.
Conversely,
Cloud Grid
RTTOV. The retrieved radiances of the three pairs
pair.
variables, most of the tests in the CMP algorithm involve
Information (Tokuno 2002) is processed in cloudy pixels.
indicate individual pressure levels in the vertical profile.
the use of brightness temperature or reflectance data with
There were no MSC cloud mask products before theIn this case, 17 mW marks 95.16 hPa for thesimilar tendencies. Cloud mask tests are based on thestartoperation;
eachindicatessatellite product
The of Himawari-8’s
dashedline
the11.2/6.2-micronpair. ofIn thetheNoWCastingsame way,thecloudmask algorithm(NWC)
had its own cloud mask process.
As cloud11.2(B14)/13.3(B16)-micronpair,
the mask
chainis also
line
11.2/7.3-micron
pair Facility
indicates (SAF)
139.5 (Meteo-France,hPa and theSatellite
Application
required forthe
mostHimawari-8 products, MSC
decidedtorepresents
11.2(B14)/7.3(B10)-micronpair,
and the2012)
and the pairNational
Oceanic
develop CMP as a resource available for Himawari-8
11.2/13.3-micron
indicates
95.11 andhPa. Atmospheric
The value ofsolid line represents the 11.2(B14)/6.2(B08)-micron pair.
Administration
products in common. CMP is a part of the Fundamental
95.11 hPa from the(NOAA)/National
11.2/13.3-micron pairEnvironmental
is adopted as
The arrows show the point of intersection with the zero
Satellite,
Data,
and
Information
Service
Cloud Product (FCP), which contains cloud phase, typethe cloud top pressure, as it is the lowest level. (NESDIS)
line
of
the
measured-simulated
ratio
and
each
pair
line
(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
radiance.

* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency- 37 ** System Engineering Division, Data Processing Department, Meteorological
Satellite Center(Received September 1, 2015, Accepted 20 November 2015)-1-－ 37 －

METEOROLOGICAL SATELLITE CENTER TECHNICAL NOTE, No.61, 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 andFig. 4 1999),
OutlineClearof theSky
intercept
methodtemperature, reflectance and emissivity of the top andShirakawa
Radiance(CSR) (Uesawa
Thehorizontal
axis
shows
the
observed
radiancefor11.2
microns, and relating
the verticalaxis represents
observed
to clouds
and thethe
atmosphere).
2009) and Aerosol Detection (Okawara et al. -22003)
are-1 -1 transmittance
-1
sr
(cm
)
.
radianceofband
pairs.
The
unit
is
mW
m
Rather than encompassing retrieval of these five
derived in clear pixels. Conversely, Cloud Grid(a) Scatter diagram of 11.2 and 6.2 micron observed radiances.
variables,in theisCMP
Information
2002)
is redprocessed
cloudy pixels.
The(Tokuno
curve (thesolidline) ofinradiativetransfer calculation
formost11.2 ofandthe6.2tests
microns
also algorithm
shown. involve
the
use
of
brightness
temperatureorreflectancedata with
There
were
no
MSC
cloud
mask
products
beforethe(b) Scatter diagram and curve for 11.2 and 7.3 microns (as per Fig. 4 (a))
start ofeach
satellite
product(c) Himawari-8’s
Scatter diagramoperation;for 11.2 and13.3
microns(as per Fig. similar
4 (a)) tendencies. Cloud mask tests are based on the(d)ownSimulatedradiance
profileAsforcloud
11.2 mask
microns
as calculated
using
RTTOV
cloud
mask
algorithm of the NoWCasting (NWC)
had its
cloud mask
process.
is alsoSatellite 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- 38 ** System Engineering Division, Data Processing Department, Meteorological
Satellite Center(Received September 1, 2015, Accepted 20 November 2015)-1-－ 38 －

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

4. Input/output data
4.1. Input data
i. AHI data（二行）

Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product（二行）

IMAI Takahito* and YOSHIDA Ryo**（三行）

Brightness temperatures and radiances at 6.2, 7.3, 11.2
and 13.3 microns are observed by the AHI.

Abstract

Fig. 5 File format and pixel order
Thiscalculated
paper describes
the RTTOV
algorithm
theoretical basis for the Himawari-8 Cloud Mask Productii. Vertical profiles
using theradiative
Data are written in flat binary format.
transfer code(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
The verticalprofiles sinceof brightness
temperatures and5. Data provision for general users
operational
7 July 2015.
radiances are calculated
RTTOV.
The onwavelengths
The CMP using
algorithm
is based
the cloud mask technique of NWC-SAF for MSG/SEVIRI and
GOES-R/ABI. Most cloud detection
tests involvethresholdmethods
basedon
are the sameNOAA/NESDIS
as those of AHI fordata.
The cloud
top height
product
is usedexclusivelybyradiative transfer calculation using NWP data as atmosphericprofiles.
The
thresholds
aremodified
MSC and is not provided to external users.
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initialiii. Cloud type product results
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
Cloud typealgorithm
information
required.to SEVIRI data, with results
6. Cloudtophitheight
wasis applied
showingratiosproductwith theevaluation
MODIS productwere around 85% for all seasons.
4.2. Output data

（三行）Evaluation was carried out over a period of two weeks

from 20 July to 2 August 2015. The cloud top height
began
productoperation.
was compared to its MODIS counterpart (Baum
This
paper
the algorithm
theoreticalbasis
et al. 2012) describes
and Calipso(Winker et
al. 2006).
In forthe
CMP.
match-up process, pixels within 2 km and within 5（一行）
minutesofthescanning
time between cloud top height
2. Algorithm
product data and MODIS or Calipso data were picked up.

1. Cloud
Introductioni.
top pressure, cloud top altitude and cloud top（一行）
temperature
Himawari-8 is the new geostationary satellite of the
These data are output in flat binary form at 1 byte per
Japan Meteorological Agency (JMA). It was launched on
pixel.
Figure5 shows
the pixel
order,onandTable
1 shows
7 October2014
and began
operation
7 July
2015.
The
the
specifications
cloud toppressure,
altitude
andsatellite
carries the forAdvanced
Himawari
Imager(AHI),
temperature.
Theimproved
start countover
is minus
127 in allincases,
Table
3 shows the results of evaluation for the cloud top
which is greatly
past imagers
terms andof
2.1
Overview
Clouddetectionin theandCMP
algorithm
basedon
its number
bands isand
its temporal/special
resolution
thephysicalof
quantity
determinedusing
heightproductof MODIS
Calipsoduringisthis
period.
comparisonof observation
datarepresentationand clear sky
data(Bessho et al. 2016). Using AHI data, JMA’s
Figure 6 showsa time-seriesof meancalculated
fromnumerical
weather
prediction(NWP)
Meteorological
Satellite
Center(MSC)
developedthePhysical quantity = slope × (𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 + 127)
errors and root mean square errors for cloud top height. In
data. If observation data differ from clear sky data, theHimawari-8 Cloud Mask Product (CMP).
the cloud top height product, cloud top height was
pixel is cloudy. To discriminate between cloudy and clear
Cloud mask is used to discriminate cloudy pixels
ii. Quality flag data
underestimatedin comparison
to corresponding
pixels,it is desirable
for observation
variables in values
clear
from clear ones in satellite data. Numerous satellite
These data
are also
outputin information.
flat binary form
1 bytefrom cloudy
MODISconditions
and Calipsotothroughout
anddiffer andtheforperiod.
the physicalproducts
requirecloudmask
By atwayofperpixel. Table
2 detailsTemperature
quality information
per pixel.andreason behind the difference to be explicit (e.g.,
example,Sea Surface(SST) (Yasuda
temperature, reflectance and emissivity of the top andShirakawa 1999), Clear Sky Radiance (CSR) (Uesawa
transmittanceto clouds and the atmosphere).
2009) and Aerosol(Okawara et foral. cloud2003)top
arepressure,
Table 1Detection
Output specifications
altitude andrelating
temperature
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.
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- 39 ** System Engineering Division, Data Processing Department, Meteorological
Satellite Center(Received September 1, 2015, Accepted 20 November 2015)-1-－ 39 －

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

Table 2 Pixel quality information（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 Table
carries3 Mean
the Advanced
Himawari
Imager(AHI),
errors and root mean square errors for the period from 20 July to 2 Augustwhich 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(a)pixels, it (b)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
Fig. 6 Time-series representation of mean errors and root mean square errors(NOAA)/National
productsThein common.
a part ofthe
thedate,Fundamental
horizontalCMP
axis isrepresents
the left verticalAdministration
axis represents meanerror, and the rightEnvironmental
vertical axis
Satellite,
Data,
and
Information
Service (NESDIS)
Cloud Product(FCP),
which
contains
cloudphase,
type
represents root mean square error.
(Heidinger
Straka2012).
and top The
heightHimawari-8/AHI
pixels(Mourifor
et MODISal.
fig for(a) andthe fig (b) show
evaluation
andCalipsoand
cloud
top III,height,respectively.
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- 40 ** System Engineering Division, Data Processing Department, Meteorological
Satellite Center(Received September 1, 2015, Accepted 20 November 2015)-1-－ 40 －

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

7. Assumptions and limitations（二行） 2014: Remote sensing of cloud top pressure/heightfrom SEVIRI: analysis of ten current retrieval

Algorithm Theoretical Basis for Himawari-8 Cloud Mask Producti. The semi-transparent cloud top height algorithms are（二行）

algorithms. Atmos.Meas.Tech,2842-2943.

assumed for single-layer cloud rather than multi-layered
Heidinger A. K.,2012: ALGORITHM THEORETICALIMAI top
Takahito* and YOSHIDA**
cloud. The accuracy of semi-transparent cloudheightBASIS Ryo
DOCUMENTABI Cloud Height.
estimation is lower for multi-layered cloud.

（三行）

Japan Meteorological Agency, 2013: Himawari-8/9

ii. The accuracy of cloud top height estimation is lower

Himawari Standard Data User's Guide, 5.

if the cloud type is not properly classified. Cloud top
Meteo France, 2012: Algorithm Theoretical Basis
Abstract
This paper describes
the algorithm
theoreticalbasis
for the Himawari-8
Mask Productheight for semi-transparent
cloud classified
as opaqueinDocument
for “Cloud Cloud
Products”(CMa-PGE01
v3.2,
(CMP)
developedbytheMeteorological
Satellite
Center.
CMP
is
part
of
the
Fundamental
Cloud
the cloud type product is underestimated, while that for
CT-PGE02 v2.2 & CTTH-PGE03 v2.2).
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
opaque cloudcorrectly
Menzel W. P., W. L. Smith, and T. R. Stewart, 1983:
operational
since 7classified
July 2015.as opaque isoverestimated. The CMP algorithm is based on the cloud mask technique
Improvedof Cloud
MotionWind Vector andand Altitude
NWC-SAFfor MSG/SEVIRINOAA/NESDISGOES-R/ABI.
cloud detection
tests involvethresholdoniii. Accuracy
for fractional for
cloud
is lower if Most
the cloudAssignment
using
VAS. methods
Journal basedof Climate
andradiative
transfer
calculation
using
NWP
data
as
atmosphericprofiles.
The
thresholds
aremodified
does not fully cover the target pixel.
Applied meteorology, 22, 377-384.
using offsets determined on the basis of comparison with the MODIS cloud mask product. Initial
Mouri K., T. Izumi, H. Suzue, and R. Yoshida, 2016:
results showed that the CMP hit ratio derived from such comparison was more than 85%. The CMP
Acknowledgements:
Basis
Document
algorithm was applied to SEVIRI data, with results Algorithm
showing hit Theoreticalratios with the
MODIS
product of cloud
type/phase product. Meteorological Satellite Center
were around 85% for all seasons.
（三行） Technical Note, 61, 19-31.
The authors gratefully acknowledge the two anonymous

reviewers who provided helpful comments on this
1. Introduction
manuscript,
and also thank the NASA Langley Research（一行）
Center Atmospheric Science
Data Center for providing
Himawari-8 is the new geostationary satellite of thethe MODIS and Calipso data used in the study.
Japan Meteorological Agency (JMA). It was launched on
7 October 2014 and began operation on 7 July 2015. The
References:
satellite
carries the Advanced Himawari Imager (AHI),
which is greatly improved over past imagers in terms of
its
numberof W.
bands
and its R.
temporal/special
resolution
Baum,
B. A.,
P. Menzel,
A. Frey, D. Tobin,
R. E.
(Bessho2016). A.Using
AHI data,
Holz, S.etA. al.
Ackerman,
K. Heidinger,
and P.JMA’s
Yang,
Meteorological
Satellite
Center(MSC)
developed
2012: MODIS cloud top property refinements theforHimawari-8 Cloud Mask Product (CMP).
Collection 6. J. Appl. Meteor. Clim., 51, 1145-1163.
Cloud mask is used to discriminate cloudy pixels
Chahine, M. T. 1974: Remote sounding of cloudy
from clear ones in satellite data. Numerous satellite
atmospheres,
The mask
singleinformation.
cloud layer.ByJ. way
Atmos.
products
require I.cloudofSci.,31,233-243.
example, Sea Surface Temperature (SST) (Yasuda andShirakawaSkyradiative
Radiance(CSR) model(Uesawa
Eyre
J. R.,1999),
1991: Clear
A fasttransferfor
2009)
and Aerosolal. 2003)Dept.
aresatellitesoundingDetection
systems. (Okawara
ECMWF etResearch
derivedinclear
pixels.
Conversely,
Cloud
Grid
Tech. Memo. 176.
Information (Tokuno 2002) is processed in cloudy pixels.
Hamman.U., A. Walther, B. Baum, R. Bennartz, L.
There were no MSC cloud mask products before the
Bugliaro, M. Derrien, P. N. Francis, A. Heidinger, S.
start of Himawari-8’s operation; each satellite productA. Kniffka,
H. Le
Gleau,AsM.
Lockhoff,–J.
hadJoro,its own
cloud mask
process.
cloudmask isH.also
Luts, forJ. mostF. Meirink,
P. Minnis,
Plikonda,R.
required
Himawari-8
products, R.
MSC
decided todevelop
CMPA.asThoss,a resource
available
for and
Himawari-8
Roebeling,
S. Platnik,
P. Watts,
G. Wind,products in common. CMP is a part of the Fundamental
Cloud Product (FCP), which contains cloud phase, type
and top height for Himawari-8/AHI pixels (Mouri et al.
2016a, 2016b). FCP has been produced since Himawari-8

Nieman S. J., J. Schmetz, and W. P. Menzel, 1993: A
began
operation.of Several Techniques to Assign Heights
ComparisonThis
paperTracers.
describes
the algorithm
theoreticalbasis forto Cloud
Journalof Applied
Meteorology,
32,
CMP.
1560.
（一行）
Schmetz
J.,
K.
Holmlund,J. Hoffman, and B.Strauss,
2. Algorithm
1993: Operational cloud motion winds from Meteosat
images. Jounal of Applied Meteorology, 32,
2.1infrared
Overview
Cloud detection in the CMP algorithm is based on
1207-1225.
comparison
observation
data 1978:and clearsky data
Smith, W. L.,ofand
C. M. R. Platt,Intercomparison
calculated
fromnumerical
weather
predictionof radiosonde, ground based laser, and (NWP)
satellite
data. If observation data differ from clear sky data, thededuced cloud heights.
J. Appl. Meteor., 17,
pixel is cloudy. To discriminate between cloudy and clear
1796-1802.
pixels,it is desirable for observation variables in clear
Suzuecloudy
H., T. conditions
Imai, and K.
2016:forHigh-resolution
andto Mouri,differ andthe physicalCloud
Analysis
Information
derivedfrom
Himawari-8
reason behind the difference to be explicit(e.g.,
temperature,reflectance Satellite
and emissivity
the top Note,anddata. MeteorologicalCenter ofTechnical
transmittance61, 43-51. relating to clouds and the atmosphere).
Ratherthanof thesefiveWinker, D.
M., encompassing
C. A. Hostetler, retrieval
M. A. Vaughan,and A.
H.
variables, most of the tests in the CMP algorithm involve
Omar, 2006: Caliop Algtorithm Theoretical Basisthe use of brightness temperature or reflectance data with
Document Part 1: CALIOP Instrument, and Algorithms
similar tendencies. Cloud mask tests are based on the
Overveiw.
cloudmask 20-23.
algorithm of the NoWCasting (NWC)
Satellite Application Facility (SAF) (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- 41 ** System Engineering Division, Data Processing Department, Meteorological
Satellite Center(Received September 1, 2015, Accepted 20 November 2015)-1-－ 41 －

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

（二行）

雲頂高度アルゴリズム記述書
Algorithm Theoretical Basis for Himawari-8 Cloud Mask Product
（二行）

毛利

浩樹*、鈴江 寛史*、吉田 良*、泉IMAI Takahito* and YOSHIDA Ryo**

敏治**

（三行）

要旨
雲頂高度プロダクトは、基本雲プロダクトの一要素である。基本雲プロダクトは雲マスク、Abstract
雲タイプ、雲頂高度プロダクトからなる。気象庁気象衛星センターでは、ひまわり８号を機に、This paper describes the algorithm theoretical basis for the Himawari-8 Cloud Mask Product
様々な２次プロダクトが取り扱う雲マスク、雲タイプ・相、雲頂高度を独立させ、基本雲プロダ(CMP) developed by the Meteorological Satellite Center. CMP is part of the Fundamental Cloud
クトとしてまとめ上げた。高分解能雲情報が現在基本雲プロダクトを使用している。
Product, which incorporates cloud phase, type and top altitude from Himawari-8/AHI and has been
雲頂高度プロダクトは、雲頂高度、雲頂温度、雲頂気圧の３つの要素から成り、アルゴリズムはoperational since 7 July 2015.
欧州気象衛星機関のNWCSAFという枠組みで開発されたものを使用している。入力データはひThe CMP algorithm
is basedon the cloud mask technique of NWC-SAF for MSG/SEVIRI andまわり
8号に搭載されている
AHI（Advanced
Imager）によって観測されたデータ、放NOAA/NESDIS for GOES-R/ABI. Most cloudHimawari
detection tests
involve threshold methods based on
射伝達計算済みの鉛直プロファイルデータ、
radiative transfer calculation using NWP dataおよび雲タイププロダクトによって出力された雲タ
as atmospheric profiles. The thresholds are modified
イプデータである。
2015 年on
7月日から
8 月 2 日の with
2 週間における雲頂高度の評価では、
MODIS
using offsets determined
the20basisof comparison
the MODIS cloud mask product. Initial
雲頂高度およびCalipso
雲頂高度に対して、本プロダクトの雲頂高度はやや低い傾向であった。
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（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).
Cloud mask is used to discriminate cloudy pixels
from clear ones in satellite data. Numerous satellite
products require cloud mask information. By way of
example, Sea Surface Temperature (SST) (Yasuda andShirakawa 1999), Clear Sky Radiance (CSR) (Uesawa
2009) and Aerosol Detection (Okawara et al. 2003) are
derived in clear pixels. Conversely, Cloud Grid
Information (Tokuno 2002) is processed in cloudy pixels.
There were no MSC cloud mask products before thestart of Himawari-8’s operation; each satellite producthad its own cloud mask process. As cloud mask is also
required for most Himawari-8 products, MSC decided todevelop CMP as a resource available for Himawari-8
products in common. CMP is a part of the Fundamental
Cloud Product (FCP), which contains cloud phase, type
and top height for Himawari-8/AHI pixels (Mouri et al.
2016a, 2016b). FCP has been produced since Himawari-8

began operation.
This paper describes the algorithm theoretical basis for
CMP.
（一行）
2. Algorithm
2.1 Overview
Cloud detection in the CMP algorithm is based oncomparison of observation data and clear sky data
calculated from numerical weather prediction (NWP)
data. If observation data differ from clear sky data, thepixel is cloudy. To discriminate between cloudy and clear
pixels, it is desirable for observation variables in clear
and cloudy conditions to differ and for the physicalreason behind the difference to be explicit (e.g.,temperature, reflectance and emissivity of the top andtransmittance relating to clouds and the atmosphere).
Rather than encompassing retrieval of these fivevariables, most of the tests in the CMP algorithm involvethe use of brightness temperature or reflectance data withsimilar tendencies. Cloud mask tests are based on thecloud mask algorithm of the NoWCasting (NWC)
Satellite Application Facility (SAF) (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* 気象衛星センターデータ処理部システム管理課* Office of Observation Systems Operation, Observation Department, Japan Meteorological Agency** 気象研究所気象衛星・観測システム研究部- 34 ** System Engineering Division, Data Processing Department, Meteorological
Satellite Center(Received September 1, 2015, Accepted 20 November 2015)-1-－ 42 －