Data Assimilation of Side-looking Radio Occultation by

Observing System Simulation Experiment

Hiromu Seko (MRI) , Toshitaka Tsuda and Naoto Yoshida (Kyoto Univ.)

and

Y.-H. Kuo (UCAR)

Low Earth Orbit Satellite

GPS Satellite

Tangent point

P1

T2

T3

P3P2

• Low earth orbit satellite (LEO) observes the signal of GPS satellite from the moving direction of the LEO satellite, because the short shift of the tangent point is required for the precise estimation of the tangent point profiles.

T1P2P3

Forward/backward-looking

Concept of the side-looking observation

GPS Satellite

Tangent point

P1

T2

T3

P3P2

• Low earth orbit satellite (LEO) observes the signal of GPS satellite from the moving direction of the LEO satellite, because the short shift of the tangent point is required for the precise estimation of the tangent point profiles.

• If slant path data is used in the assimilation, it is not necessary to use the data which have the small angle from the moving direction of LEO satellite.

T1P2P3

Forward/backward-looking

Concept of the side-looking observationLow Earth Orbit Satellite

GPS Satellite

• In general, impact of RO data is weak because the slant path data extends several hundred kilometers. For this reason, the total amount of assimilated data should be increased by using ‘side-looking’ data.

Forward/backward-looking

Side-looking

Concept of the side-looking observationLow Earth Orbit Satellite

GPS Satellite

• In general, impact of RO data is weak because the slant path data extends several hundred kilometers. For this reason, the total amount of assimilated data should be increased by using ‘side-looking’ data.

• In this study, the assimilation experiment of side-looking data is performed by ‘Observing System Simulation Experiment’.

Forward/backward-looking

Side-looking

Concept of the side-looking observationLow Earth Orbit Satellite

• We have focused on the intense rainfall that occurred in the city of Kobe.

• Intense rainfall raised the water level of Toga river, and five people drowned in the riverside park.

Intense rainfall occurred in the city of Kobe

Kobe

03-06UTC 28 July 2008

Initial: Operational Meso-analysis 18UTC 27 July

Boundary: GSM output

Conventional data

Conventional data

18UTC 27 July

21UTC00 UTC28 July

Analysis => initial condition

Boundary: GSM output

Flow chart of Assimilation of conventional data

JMA-NHM(x=10km)

Meso-4DVar systemGSM

MSM

NoRO (Conventional data)

FT=3

-6ho

urFT

=0-3

hour

Conventional data is not enough to reproduce the intense rainfall.

Assimilation results using conventional dataFT

=3-6

hour

FT=0

-3ho

urObservation

Initial: Operational Meso-analysis 18UTC 26 July

Boundary: GSM output

Conventional data

Conventional data + Simulated occultation data (slant path data)

18UTC 27 July

21UTC00 UTC28 July

Analysis => initial condition

Boundary: GSM output

Flow chart of Observation System Simulation Experiment

JMA-NHM(x=10km)True dataFirst guess

Meso-4DVar systemGSM

MSM

Number of OC All received data(28 July 2008)

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

Angle (degree)

Angle (degree)

We checked the occultation data.-Signal of data of which the angles from the moving direction are less than 60 degrees are received.

-However data was not received properly in half of data where the angles were larger than 50 degrees.

0

20

40

60

80

100

120

140

160

-10 0 10 20 30 40 50 60 70 80 90

14%

11%

73%

Angle (degree)

Angle (degree)

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

Number of OC obtained from satellite positions(28 July 2008)

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.

Because half of the data where the angles of 50-60 degrees are not received properly, the data that is expected to be increased byside-looking observation becomes about 18%.

SHAO

CHAN

DAEJSUWN

YSSK

tnmltwtf

bjfs

osn2

Assimilation of ground GPS ( Shoji et al. 2009)

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)

Intense rainfall reproduced when GPS data were assimilated.

Analyzed fields were used as

true data

Observation NoGPS (only Convection data)

GPS+Convection data

FT=0-3h FT=3-6h

FT=0-3h FT=3-6h

03UTC 28 06UTC 28

There are several occultations of which the angle from moving direction were larger than 60 degrees.

Positions of Occultations during 12-15 UTC 13 September 2006

There are several occultations of which the angle from moving direction were larger than 60 degrees.

These occultation data were shifted to Japan.

Positions of Occultations during 12-15 UTC 13 September 2006

0km Sat_dir 65

10km0km10km Sat_dir 65

65deg.

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

10km10km

True data - NoROwater vapor at lowest layer Enlarged map

Below the height of 3km, path-averaged refractivity of true data is larger than that of first guess.

The enhancement of the rainfalls is expected, when this data is assimilated.

0.9km

10km1.3km10km

True data - NoROwater vapor at lowest layer

Vertical profiles of D-value (Simulated - First guess)

10km10km

D-value (N)

Hei

ght (

km)

FT=3

-6ho

ur

FT=0

-3ho

urFT

=3-6

hour

FT=0

-3ho

ur

NoRO (Conventional data )

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 by assimilation of conventional data and occultation data.

FT=3

-6ho

ur

FT=0

-3ho

urFT

=3-6

hour

FT=0

-3ho

ur

Observation Conventional data +

Occultation data

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

+Occultation datalowest data:

0km

FT=3-6hour

FT=0-3hourConventional data (NoRO)

Conventional data (NoRO) 1km

+Occultation datalowest data: about 0 km

1km

2km

2km

3km

3km

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

+Occultation datalowest height:

0km

FT=0-3hourConventional data (NoRO)

1km

+Occultation datalowest height:

0 km

1km

2km

2km

3km

3km

Increment of lowest water vapor

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. Assimilation of side-looking occultation data are expected as the useful method because it improves the numerical forecast.

3. However, the problems including hardware are not considered.So, more experiments are needed under the more actual condition.

Thank you for your kind attention.