CGMS-40, JMA-WP-09
Prepared by JMA
Agenda Item: II/8
Discussed in WG II
CLOUD AND VOLCANIC ASH PRODUCT
This paper reports on JMA’s cloud and volcanic ash
product.
In 2012, JMA started providing convective clouds
information as a nowcasting product to support aviation
safety in addition to three rapid scan imagery products
provided since 2011.
JMA started developing advanced cloud product.
JMA also started developing volcanic ash product.
CGMS-40, JMA-WP-09
Prepared by JMA
Agenda Item: II/8
Discussed in WG II
1
RAPID SCAN OPERATION AND CONVECTIVE CLOUDS INFORMATION
PRODUCT
1.1 SUMMARY OF RAPID SCAN OPERATION
JMA began rapid scan operation using MTSAT-1R in 2011 to capture short-lived but
severe weather phenomena so that aviation users can be informed of them in
advance. As shown in Table 1, observations are made in a small area around Japan
from 00 UTC to 09 UTC at five-minute intervals in the summer season during
operation.
JMA observed a number of heat thunderstorms in 2011 and verified the accuracy of
the derived product. Following this validation, the Agency began providing a new
nowcast product derived from rapid scan data on 1 June, 2012.
Table 1 Specifications of rapid-scan operation
Observation interval
Time
Period
Objective
Observation area
5 minutes
Daytime only (00:00 to 09:00 UTC)
Summer only (1 June to 30 September)
To provide information for aviation safety
Bounding box around Japan
1.2 RAPID SCAN IMAGERY PRODUCTS FOR AVIATION USERS
JMA now provides four imagery products as shown in Figure 1 for aviation users.
Three of these ((a) visible images, (b) visible and infrared color composite images,
and (c) cloud top height images) have been provided since 2011. In addition, the
provision of (d) convective clouds information began in 2012. This new product is
described in the next section.
Page 1 of 6
CGMS-40, JMA-WP-09
Prepared by JMA
Agenda Item: II/8
Discussed in WG II
(a) Visible images
(b) Visible and infrared color composite
images
(c) Cloud top height images
(d) Convective clouds information
(a) Black-and-white images of visible albedo data
(b) Color composite images generated by overlaying yellow visible albedo data
and blue 10.8-μm IR brightness temperature data
(c) Cloud top height calculated from 10.8-μm infrared brightness temperature data
with reference to NWP forecast fields
(d) Three detected convective cloud areas are shown in the visible albedo data
images.
Figure 1 Rapid scan imagery products for aviation users
1.3 CONVECTIVE CLOUDS INFORMATION FOR AVIATION USERS
As detailed above, JMA began providing convective clouds information on 1 June,
2012. The product shows (a) rapidly developing cumulus areas (RDCAs), (b)
cumulonimbus areas, and (c) mid/low unknown cloud areas. RDCAs indicate the
potential for heavy rainfall, and the others show mature convective cloud. A key
technique in RDCA identification involves detecting temporal increases in the
asperity and altitude of the cloud top surface. VIS data are especially fundamental for
checking for temporal increases in asperity at the cloud top surface. Figure 2 shows
a schematic diagram of these elements.
Page 2 of 6
CGMS-40, JMA-WP-09
Prepared by JMA
Agenda Item: II/8
Discussed in WG II
The results of RDCA evaluation performed in summer 2011 in relation to lightning
observation are shown in Figure 3. The hit rate (derived from dividing the number of
hits by the sum of the number of hits and false alarms) was almost 70% while heatlightning was very active, and was close to 40% when frontal zone cloud brought
lightning. Figure 4 shows a good example of the former case. Lightning was
observed 20 to 40 minutes after the detection of areas of A, B and C, marked by a
yellow oval in the upper-left image. This indicates that RDCAs can highlight potential
thunderstorm areas at least 20 minutes before cumulus clouds develop into
cumulonimbus.
14 Jul.
Figure 2 Schematic diagram showing
convective clouds information
(a) Rapidly developing cumulus area
(RDCA)
(b) Cumulonimbus area
(c) Mid/low cloud unknown area
Extensive
heat-lightning
Frontal zone
Extensive
heat-lightning
Figure 3 Time series showing numbers of hits and false alarms
Images from 14 July, 2011 (green arrow) are shown in Figure 4.
Page 3 of 6
CGMS-40, JMA-WP-09
Prepared by JMA
Agenda Item: II/8
Discussed in WG II
Figure 4 Example of a rapidly developing cumulus area and lightning detection
on 14 July, 2011
The green areas in the upper-left figure are the results of RDCA plotting
on a visible image. Lightning was observed at B and C 20 minutes after
the area was detected, and at A 40 minutes after. Cloud area D was a
false alarm. CC and CG stand for cloud-to-cloud discharge and cloud-toground discharge, respectively.
Page 4 of 6
CGMS-40, JMA-WP-09
Prepared by JMA
Agenda Item: II/8
Discussed in WG II
2
CLOUD PRODUCT
JMA has produced an objective cloud product analyzing cloud type, cloud amount
and cloud top height from GMS-5 and MTSAT satellite images since 1999. The
product is used for the aid of weather watch and automatic weather analysis.
JMA’s next generation satellites Himawari-8/9 will carry the advanced imager called
AHI, which has capability to observe with 16 channels and 2.5-minute intervals.
Using Himawari-8/9’s images, the generation of advanced cloud product is expected.
To develop the advanced product, JMA is studying the similar product for Meteosat
Second Generation (MSG) developed by EUMETSAT/NWC SAF and GOES-R by
NOAA/NESDIS. The new cloud product is expected to be used not only for weather
analysis but also as a fundamental product to compute atmospheric motion vectors
for height assignment and sea surface temperature (SST), clear sky radiance (CSR)
and aerosol contents for cloud masking.
3
VOLCANIC ASH
Volcanic ash directly affects airplane flight plans, and is monitored by JMA’s Tokyo
Volcanic Ash Advisory Center (VAAC). Currently, differences between MTSAT 10.8 m
and 12.0 m images are used for monitoring the spread of ash. However, quantitative
information is also required.
From Himawari-8/9 observations, quantitative data such as ash density and height are
expected. JMA plans to develop the product based on a EUMETSAT METEOSAT
algorithm and a NOAA/NESDIS GOES-R algorithm. The Agency has already started a
review of both methods, and will continue related research.
In the GOES-R algorithm, single scattering calculation results are examined to be
used in order to distinct types of aerosol. JMA tries to compute single scattering
parameters for various types of aerosol. The calculation is performed
monochromatically for the central wavelength of HIMAWAI-8/9 infrared channels as 8.5
m, 11.2 m and 12.3 m. The shape of aerosol particle is spherical, and log-normal
distribution of radius is assumed. Using complex refractive index data by Hale et.al.
1973, Pollack et.al. 1973, Roush et.al. 1991, Warren et.al. 2008 and WMO 1983
(Figure 5), extinction cross-section ext, single scatter albedo  and asymmetry
parameter g are calculated for effective radius from 1m to 12 m with 1 m intervals.
Figure 6 shows the 2-dimentonal diagram of beta-ratio between 12.3 m and 11.2 m
of scaled extinction cross section (1 g ext versus that between 8.5 m and 11.2
m. The left figure shows the JMA calculation and the right figure shows GOES-R
ATBD (NOAA/NESDIS, 2010). These figures indicate the use of 8.5 m in addition to
11.2 m and 12.3 m data enhances discrimination of aerosol types. The apparent
difference between the two charts is recognized for “Dust (kaolinite)”.
Page 5 of 6
CGMS-40, JMA-WP-09
Prepared by JMA
Agenda Item: II/8
Discussed in WG II
Figure 5 Complex refractive index
The left chart shows real part and the right chart shows imaginary part. The horizontal axis
shows wavelength (m)
Figure 6 2-dimentional diagram of beta-ratios
The left chart shows JMA calculation result, and the right chart is from GOES-R ATBD.
References
NOAA NESDIS, (2010): GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical
Basis Document for volcanic Ash (Detection and Height), 84pp, Version 2.0, September
15, 2010.
Hale, G.M., M.R.Querry, (1973), Appl. Opt., 12:555-563.
Pollack, J.B., O.B. Toon, B.N. Khare, (1973), Icarus, 19:372-389.
Roush, T., J. Pollack, J. Orenberg, (1991), Icarus, 94:191-208.
Warren, S.G., R.E. Brandt, (2008), J. Geophys. Res., 113:
14220,doi:10.1029/2007JD009744.
WMO, (1983), Report of the Experts Meeting on Aerosols and Their Climatic Effects 107pp
WCP-55.
Page 6 of 6