Data Assimilation ofSide-looking Radio Occultation byObserving System Simulation Experiment
Hiromu Seko (MRI) , Toshitaka Tsuda and Naoto Yoshida (Kyoto Univ.)
andBill Kuo (UCAR)

Concept of the side-looking observation
Tangent point

Low Earth Orbit Satellite

T2
P3

P2

P1

T1

T3

Forward/backward-looking
P2

P3

GPSSatellite• Low earth orbit satellite (LEO) observes the signal of GPS satellite
from the moving direction of the LEO satellite, because the shortshift of the tangent point is required for the precise estimation of thetangent point profiles.
• If slant path data is used in the assimilation, it is not necessary touse the data which have the small angle from the moving direction ofLEO satellite.

Concept of the side-looking observation
Low Earth Orbit Satellite
Forward/backward-looking

Side-looking

GPSSatellite• In general, impact of RO data is weak because the slant path data
extends several hundred kilometers. For this reason, the total amountof assimilated data should be increased by using ‘side-looking’ data.
• In this study, the assimilation experiment of side-looking data isperformed by ‘Observing System Simulation Experiment’.

Intense rainfall occurred in the city of Kobe
03-06UTC 28July 2008

Kobe

• We have focused on the intense rainfall that occurredin the city of Kobe.
• Intense rainfall raised the water level of Toga river,and five people drowned in the riverside park.

Flow chart of Assimilation of conventional data
Initial: Operational Meso-analysis
18UTC 27 July

MSM

Boundary: GSM output
18UTC
27 July

21UTC

00 UTC
28 July

Meso-4DVar system

Conventional data
Conventional data

Analysis =>initial condition

GSM

Boundary: GSM output
JMA-NHM(x=10km)

Assimilation results using conventional data
FT=0-3hour

FT=0-3hour
FT=3-6hour

NoRO (Conventional data)

FT=3-6hour

Observation

Conventional data is not enough to reproduce the intense rainfall.

Flow chart of Observation System Simulation Experiment
Initial: Operational Meso-analysis
18UTC 27 July

MSM

Boundary: GSM output
18UTC
27 July21UTC

Meso-4DVar system

Conventional data
True data
First guess

00 UTC
28JulyAnalysis =>initial condition

GSM

Boundary: GSM output

Conventional data + JMA-NHM(x=10km)
Simulated occultation
data (slant path data)Number of OC
All received data(28 July 2008)
Angle (degree)

Number of OC
occ-type=44(28 July 2008)
Angle (degree)

We checked the occultation data.
-Signal of data of which the angles from the moving direction areless than 60 degrees are received.
-However the half of data, of which the angles were larger than 50
degrees, did not become the profile.

Number of OC
occ-type=44(28 July 2008)
Angle (degree)
160

73%

14014%

Number of OC
10080
obtained from60
satellite positions 4020(28 July 2008)
120

11%

0-100102030405060708090Angle (degree)

Number of occultation where the angle from moving direction is larger
than 60 degrees is about 11% when the same day’s data is used.
The data that is expected to be increased by side-looking observation
becomes about 18%.

Assimilation of ground GPS ( Shoji et al. 2009)
YSSK
CHAN

bjfs
SUWN osn2
DAEJ
SHAO

tnml
twtf

Assimilation period: 30hour (06UTC 27- 00UTC 28)
Assimilated data:
Conventional data , Analyzed rainfall,
PWV obtained by satellites, Wind profiler etc.
+ GPS (GEONET(blue triangles)+ Korean and Chinese GPS data(red dot)

Assimilation of ground GPS ( Shoji et al. 2009)NoGPS (only Convection data)

Observation

03UTC 2806UTC 28

FT=0-3h

FT=3-6h

GPS+Convection data

Intense rainfall reproduced
when GPS data wereassimilated.
 Analyzed fields were used astrue data


FT=0-3h

FT=3-6hPositions of Occultations
during 12-15 UTC 13 September 2006

There are several occultations of which the angle frommoving direction were larger than 60 degrees.
These occultation data were shifted to Japan.

True data - NoROwater vapor at lowest layer

Enlarged map

10km
10km

10km
10km
0km

0km

Sat_dir 65

Sat_dir 65

65deg.

Because the region where the occultations were shifted to arepositive, the rainfall is expected to be higher when this data is
assimilated.

10km
10km

10km
10km
0.9km

1.3km

Vertical profiles of D-value(Obs. - First guess)Height (km)True data - NoRO
water vapor at lowest layer

D-value (N)Below the height of 3km, path-averaged refractivity of true data islarger than that of first guess.
The enhancement of the rainfalls is expected, when the lowest levelof simulated slant path data is less than 2 km.

FT=0-3hour

FT=0-3hour

FT=3-6hour

FT=3-6hour

NoRO (Conventionaldata )Conventional data +Occultation data

As it is expected, the rainfall became more intense when the forecast
was performed from the analyzed fields, which were obtained byassimilation of conventional data and simulated occultation data.

Conventional data +Occultation data

FT=0-3hour

FT=0-3hour

FT=3-6hour

FT=3-6hour

Observation

Intensity and area of the heavy rainfall was similar to theobserved one, although the position shifted westward at
FT=0-3hour.

FT=0-3hour
Conventional
data (NoRO)+Occultation data
lowest data:
0km

1km

2km

3km

1km

2km

3km

FT=3-6hour +Occultation data
Conventional
data (NoRO)

lowest data:
about 0 km

In this case, the improvement of forecast is expected, if the lowest
data reached the height of 2km.

FT=0-3hour
Conventional
data (NoRO)+Occultation data
lowest height:
0km

1km

2km

3km

+Occultation data
lowest height:
0 km

1km

2km

3km

Increment oflowest watervapor

The improvement of rainfall was confirmed by the increment of water
vapor at the lowest layer of the model.

Summary of preliminary results
1. When the side-looking data, of which angles from the moving
direction of LEO are large, are included in assimilation data,
analyzed fields are further improved.
2. However, the problems including hardware are not considered.
So, more experiments are needed under the more actual condition.

Thank you for your kind attention.