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Assimilation of ATOVS level1C radiance and MODIS polar winds at JMA. Masahiro Kazumori Japan Meteorological Agency / EMC Visiting scientist. RSM. MSM. GSM. Global Model (GSM). Regional Model (RSM). Meso-scale Model (MSM). Purpose:. 3-7day forecast Boundary for RSM. 1-2day forecast

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Assimilation of atovs level1c radiance and modis polar winds at jma

Assimilation of ATOVS level1C radiance and MODIS polar winds at JMA

Masahiro Kazumori

Japan Meteorological Agency / EMC Visiting scientist

EMC Sack Lunch Seminar


Introduction of jma nwp models

RSM at JMA

MSM

GSM

Global Model (GSM)

Regional Model (RSM)

Meso-scale Model (MSM)

Purpose:

3-7day forecast

Boundary for RSM

1-2day forecast

Boundary for MSM

Disaster prevention

information

Resolution, Forecast time:

55km, 40levels (0.4hPa)

90 hours (00UTC)

216 hours(12UTC)

20km, 40levels (10hPa)

51 hours (00,12UTC)

10km, 40levels (10hPa)

18 hours (00,06,12,18UTC)

Assimilation system:

4D-Var (Since Feb. 2005)

4D-Var (Since 2003)

4D-Var (Since 2002)

Introduction of JMA NWP models

EMC Sack Lunch Seminar


Satellite data in jma global data assimilation system
Satellite data in JMA global data assimilation system at JMA

Now using operationally

Now testing

  • Radiance

  • AIRS (Aqua)

  • SSMI,TRMM,AMSR-E

  • GOES-9,METEOSAT,MTSAT-1R

  • Wind

  • METEOSAT(8),MTSAT-1R

  • SSMIS(DMSP-16)

  • HIRS,AMSU-A,HSB(NOAA-18)

  • IASI (Metop)

  • ASCAT(Metop)

  • Radiance

  • AMSU-A(NOAA15/16, Aqua)

  • AMSU-B(NOAA15/16/17)

  • Wind

  • GOES(9/10/12),METEOSAT(5/7)

  • MODIS(Terra/Aqua)

  • QuikSCAT

Planning

EMC Sack Lunch Seminar


Progress on global data assimilation in 2004 2005
Progress on global data assimilation in 2004-2005 at JMA

  • May 2004 :

    • Assimilation of polar winds from Terra/MODIS and Aqua/MODIS in the north polar region started.

  • Sep. 2004 :

    • Assimilation of polar winds from Terra/MODIS and Aqua/MODIS in the south polar region started.

MODIS polar winds

  • Dec. 2004 :

    • Direct assimilation of ATOVS level-1C data replaced that of level-1D data

    • The radiative transfer model for the radiance assimilation was upgraded from RTTOV-6 to RTTOV-7

  • Feb. 2005 :

    • Introduction of 4D-Var in operational system

  • March. 2005:

    • Start of Aqua/AMSU-A radiance data assimilation

ATOVS level 1C radiance

4D-Var

EMC Sack Lunch Seminar


Assimilation of atovs level 1c radiance
Assimilation of ATOVS level 1C radiance at JMA

Masahiro Kazumori

Hiromi Owada

Kazuyo Fukuda

Numerical Prediction Division

Japan Meteorological Agency

EMC Sack Lunch Seminar


Atovs level 1c radiance data
ATOVS level 1C radiance data at JMA

Since May 2003, ATOVS radiance data have been assimilated directly into the global model with JMA 3D-Var system.

But…, it had been using ATOVS level 1D radiance data

  • Dec. 2004

  • ATOVS data was changed from level-1D data(NESDIS pre-processed data) to level-1C data(unmapped instrument data)

  • At the same time, RTM upgrade was performed.

  • JMA uses RTTOV (Saunders et al. 1998) as RTM

  • The update was from RTTOV-6 to RTTOV-7

  • RTTOV-7 treats each sensor separately

  • RTTOV-7 has an ability to calculate AIRS radiance

EMC Sack Lunch Seminar


Aapp msc direct read out data
AAPP & MSC direct read out data at JMA

AAPP(ATOVS and AVHRR Processing Package)

Direct broadcast data are received at JMA Meteorological Satellite Center.

JMA

Global level 1B data from NESDIS

Level 1C radiance

AAPP

Direct read out data (HRPT) at MSC

Level 1D radiance

decode

Data coverage of ATOVS level 1c for early analysis.

Blue points are the global data from NESDIS and red points are direct read out data at MSC at JMA. 12UTC 31 July 2004.

The limit of data receiving.

EMC Sack Lunch Seminar


Difference of atovs data between level 1c and level 1d
Difference of ATOVS data between level 1C and level 1D at JMA

Level 1D data

Level 1D data

No high latitude data.

Thinned and removed by NESDIS

NESDIS provide some quality flag for observation

Level 1C data

Blue:NOAA15Red:NOAA16

Level 1C data

All observation data are available.

thinning and quality check are needed.

EMC Sack Lunch Seminar


Difference of atovs data between level 1c and level 1d1
Difference of ATOVS data between level 1C and level 1D at JMA

Level 1D data

Level 1D data

No high latitude data.

Thinned and removed by NESDIS

Level 1C data

Level 1C data

All observation data are available.

Original data thinning and quality check are needed.

EMC Sack Lunch Seminar


Mapping computing sounder data to another sounder grid
Mapping at JMA(computing sounder data to another sounder grid)

FOV

HIRS

AMSU-A

In level 1D data,

Mapping of AMSU-A FOV to HIRS FOV are conducted.

In level 1C data,

We can assimilative those data in their original observation points.

EMC Sack Lunch Seminar


Assimilation scheme of atovs 1c radiance
Assimilation scheme of ATOVS 1C radiance at JMA

  • Data thinning

    • 240km for AMSU-A, 180km for AMSU-B

    • Land sea decision: 0.25*0.25degree map and considering the maximum size of FOV for each sensor.

  • Quality Control

    • Rain detection ( based on scattering index)

    • Cloud detection( based on amount of cloud liquid water)

  • Observation error

    • Remove the adjustment for each FOV

  • Bias correction

    • Scan bias correction ( fixed for each channel)

    • Air mass correction (fixed for all season)

      • Predictor: Calculated brightness temperature of AMSU-A Ch5,7,10, Surface temperature.

      • Coefficient was calculated from collocated data set with RAOB

discontinued

EMC Sack Lunch Seminar


Land sea mask based on fov

AMSU-A CH4 Departure(monthly mean) at JMA

A Observation point

Land

[K]

0.25degree

Sea

Contamination by land

0.25degree

Land sea grid

Field of View

Land Sea Mask based on FOV

Land sea mask are modified based on FOV size for each sensor.

EMC Sack Lunch Seminar


Results of cloud rain detection
Results of cloud, rain detection at JMA

Level 1C

Clear →Thin cloud

For level 1C,

HIRS can not be used for cloud detection (no mapping)

Used Retrieval Algorithm for QC

CLW from AMSU-A (English et al. 1997)

> 100g/m^2 rejected

RAIN (Scattering index method)

AMSU-A (over ocean)

SI = ETB15 – TB15 >10 rejected

AMSU-B ( over ocean)

SI = TB1-TB2>3 and Median filter QC for CH1

Level 1D

Level 1C data

There are many rain observation

(Level 1C have original all observation data)

Many cloud around high latitude in winter.

EMC Sack Lunch Seminar


Mean departure for each scan position
Mean departure for each scan position at JMA

Level1C (AMSU-A)

Level1D (AMSU-A)

Stop the use of

Ch14

Red:W Bias correction

Blue:W/O Bias correction

Level 1D data has an effect of mapping to HIRS field of view

EMC Sack Lunch Seminar


Difference between level 1c and level 1d
Difference between level 1C and level 1D at JMA

  • Example: AMSU-A Channel 7(2004/10/07/12UTC)

Level 1C

Level 1C data

All observation data are available.

Data thinning and quality check should be done by ourselves.

Level 1D

Level 1C data

No high latitude data.

Thinned and removed by NESDIS

(NESDIS pre-processed data)

EMC Sack Lunch Seminar


Monthly mean o b distribution amsu a
Monthly mean O-B distribution (AMSU-A) at JMA

level1C

level1D

The bias of level1C seems smaller than 1D

It means the QC of level 1C works better.

EMC Sack Lunch Seminar


Assimilation experiment of atovs 1c
Assimilation experiment of ATOVS 1C at JMA

  • Period:

    • Summer:From July 13, 2004 To September 9, 2004

      • Verification Period: From July 26, 2004 to August 31, 2004

    • Winter: From December 27 2003 to February 2004

      • Verification Period: From January 1,2004 to January 31 2004

  • Setting of experiments

    Analysis:Global 3D-Var, Forecast:T213L40GSM0407NAPEXR111

    CNTL: same with operational(For summer, with MODIS polar winds in the S.H.)

    TEST:CNTL + replace of ATOVS data ( from 1D to 1C)

    Update of RTM from RTTOV-6 to RTTOV-7

  • Used level1C

    NOAA15,16 AMSU-A,B, NOAA17AMSU-B

  • Discontinued level 1D data

    NOAA15,16AMSU-A,B, NOAA16 HIRS

EMC Sack Lunch Seminar


CNTL GUESS at JMA

TEST-CNTL

TEST GUESS

TEST ANAL

CNTL ANAL

TEST-CNTL

ANAL-GUESS

ANAL-GUESS

Summer Z500

EMC Sack Lunch Seminar


Impact on analysis
Impact on analysis at JMA

  • TEST:

    • ATOVS level 1C data

    • RTTOV-7

  • CNTL:

    • ATOVS level 1D data

    • RTTOV-6

Zonal mean difference of Temperature for August 2004

TEST-CNTL

Change at the high latitudes in the troposphere

And large change in the stratosphere.

EMC Sack Lunch Seminar


2004 Aug. N.H. at JMA

2004 Aug.S.H.

2004 Jan.S.H.

2004 Jan.N.H.

Impacts on forecast

Z500RMSE

level 1C

level 1D

Operational use of level 1C data started on 2 Dec. 2004

Improvement of RMSE of 500hPa Geopotential height

EMC Sack Lunch Seminar


Where can i find the improvements
Where can I find the improvements? at JMA

Difference of RMSE between TEST and CNTL (blue color means improvement)

summer

winter

1day

S.H. and the polar region were improved.

3day

5day

EMC Sack Lunch Seminar


Comparison of typhoon track prediction
Comparison of typhoon track prediction at JMA

  • Target

    The 11 typhoon in the summer test period ( maximum sample number 62 )

    red:TEST, green:CNTL

T0409

T0410

T0411

T0412

T0413

T0414

T0415

T0418

T0416

T0417

There are some difference between TEST and CNTL.

But, statistically, the impact was almost neutral.

T0419

EMC Sack Lunch Seminar


Summary
Summary at JMA

JMA use ATOVS level-1C radiance since Dec. 2004 operationally.

The use of ATOVS level-1D radiance was discontinued.

  • Land sea mask are modified for each sensor.

  • Cloud, rain detection scheme are introduced.

  • Use of direct read out data received at MSC/JMA

  • Change of the RTM from RTTOV-6 to RTTOV-7.

  • OSE showed the improvement of forecast score on 500hPa height.

EMC Sack Lunch Seminar


Plan for 2005 on atovs at jma
Plan for 2005 on ATOVS at JMA at JMA

KMA and JMA are going to exchange the direct received ATOVS data.

Red: JMA(Tokyo)

Blue:KMA(Seoul)

For Early analysis,

These data make the data coverage expand.

Data will be available within 50 min. after the observation

At present, data impact study is being conducted.

EMC Sack Lunch Seminar


Plan for 2005 on atovs at jma1
Plan for 2005 on ATOVS at JMA at JMA

Japan has a ground station(ice station) in the Antarctic. SHOWA-kichi

JMA is getting the direct received ATOVS data in the Antarctic through National Institute of Polar Research (NIPR).

The data is available within 50 min. after observation.

The data is coming through International Mobile Satellite Organization.

Data acquisition is going well.

EMC Sack Lunch Seminar


Exchange of atovs direct broadcast data in eastern asia
Exchange of ATOVS Direct Broadcast Data in Eastern Asia at JMA

  • JMA will contribute to establish a RARS together with the associated inter-regional data exchange mechanisms;

  • - JMA is willing to perform its part of the re-transmission functions through the GTS and/or the Internet, in co-operation with CMA, ABoM and other centres;

  • - The APSDEU forum should be used to co-ordinate the Asian RARS activities;

  • - Responsibility for implementation of functions and operations to be shared between centres.

Reference:CGMS/WMO REGIONAL ATOVS RE-TRANSMISSION SYSTEM(RARS) WORKSHOP REPORT

EMC Sack Lunch Seminar


Data coverage
Data coverage at JMA

EARS(EUMETSAT ATOVS Retransmission Service )

RARS(Eastern Asia)

http://www.eumetsat.int/en/dps/atovs/images/coverage.gif

If we use both, we will get much data in Early analysis.

EMC Sack Lunch Seminar


Next… at JMA

EMC Sack Lunch Seminar


Assimilation of modis polar winds at jma
Assimilation of MODIS polar winds at JMA at JMA

Masahiro Kazumori

Yoshiyuki Nakamura

Numerical Prediction division

Japan Meteorological Agency

EMC Sack Lunch Seminar


Modis polar winds

N.H. at JMA

S.H.

MODIS polar winds

  • AMVs from Geostationary Satellites have been used at JMA

  • But, the polar regions have been remained as data poor regions because no winds from geostationary satellite for these regions. RAOB and Aircraft-network are also sparse. And ATOVS 1D data had no high latitude data.

  • Since July 2002, CIMSS(Cooperative Institute for Meteorological Satellite) at Univ. of Wisconsin have been produced AMVs from MODIS on Terra and Aqua for the polar regions.

Data distribution of AMVs from Satellite

Orange Terra

Green Aqua

MODIS polar winds fill the gap of observation and will improve the accuracy of analysis in the polar regions, and bring a better forecast in the mid-latitudes.

EMC Sack Lunch Seminar


Difference between cimss and nesdis
Difference between CIMSS and NESDIS at JMA

  • Terra/MODIS WV 400hPa N.H. Wind Speed O-B and number

CIMSS

NESDIS

O-B

Period:

From 27 December 2003

To 9 February 2004

Difference in Quality

And Coverage

Number

JMA use CIMSS MODIS winds.

EMC Sack Lunch Seminar


Quality of modis polar winds

ALL data at JMA

QC Pass

Quality of MODIS Polar Winds

  • BIAS and RMSE of Wind Speed against first guess

EMC Sack Lunch Seminar


Modis polar winds data assimilation experiments
MODIS polar winds data assimilation Experiments at JMA

  • Period of the experiments

    • From 27 June 2003 to 9 August 2003

    • From 27 December 2003 to 9 February 2004

  • Configurations

    JMA Global Spectral Model (GSM)+ 3D-Var T213L40

    CNTL the same as JMA operational run.

    MODIS polar winds were passively monitored.

    TEST CNTL+Terra/MODIS+Aqua/MODIS

  • Used MODIS polar winds (Only in the Arctic)

    Over oceanIR: above 700hPa WV: above 550hPa

    Over land IR,WV: above 400hPa.

  • Data thinning 150km(horizontal) 100hPa(vertical)

  • The data in the Antarctic have large bias. That degraded the forecast scores in another experiment.

EMC Sack Lunch Seminar


Impacts on analysis
Impacts on Analysis at JMA

  • Mean field

    • Temperature:Rise in the lower troposphere and fall in the upper troposphere ( about 0.5 degree in zonal mean)

    • 500hPa height:Increase over ocean and decrease over land, especially over Siberia area.

      • Comparison with Radiosonde observation(RAOB)

        • Analysis and first guess in the TEST became close to RAOB, especially over Siberia

        • Improvements on background bring better forecasts.

EMC Sack Lunch Seminar


Zonal mean difference of temperature
Zonal mean difference of Temperature at JMA

Monthly mean for July 2003

Monthly mean for January 2004

  • Rise in the lower troposphere and fall in the upper troposphere

    ( about 0.5 degrees in zonal mean)

hPa

EMC Sack Lunch Seminar


Impacts on analysis1
Impacts on Analysis at JMA

  • Mean field

    • Temperature:Rise in the lower troposphere and fall in the upper troposphere ( about 0.5 degree in zonal mean)

    • 500hPa height:Increase over ocean and decrease over land, especially over Siberia area.

      • Comparison with Radiosonde observation(RAOB)

        • Analysis and first guess in the TEST became close to RAOB, especially over Siberia.

        • Improvements on background bring better forecasts.

EMC Sack Lunch Seminar


Change of 500hpa z

TEST first guess against RAOB at JMA

CNTL first guess against RAOB

Change of 500hPa Z

Analysis (TEST-CNTL)

  • Monthly mean error for July 2003

(m)

(m)

(m)

(m)

First guess (TEST-CNTL)

Analysis and first guess in the TEST became close to RAOB, especially over Siberia.

EMC Sack Lunch Seminar


Impacts on forecast
Impacts on Forecast at JMA

  • Anomaly Correlation and RMSE at 500hPa

    • Large improvement for both seasons in the N.H.

    • Neutral for the Tropics and the S.H.

      (no MODIS assimilation in these regions in this test.)

    • Change in the Arctic spread to the lower latitudes.

  • RMS forecast error of wind vectors were reduced.

    • Especially, improvements at 500hPa was remarkable.

      ( 500hPa was the level with maximum data number)

  • Improvements on typhoon track prediction

    • Small, but positive impacts were found at the later stage in the forecasts.

EMC Sack Lunch Seminar


Anomaly correlation of 500hpa height
Anomaly at JMACorrelation of 500hPa height

MODIS polar winds assimilation in the Arctic

TEST:With MODIS

CNTL:Without MODIS

Large improvements were found for the forecast score.

EMC Sack Lunch Seminar


Impacts on forecast by modis polar winds
Impacts on Forecast by MODIS polar winds at JMA

  • RMSE at 500hPa

    • Large improvement for both seasons in the polar region

    • Change in the polar regions spread to the lower latitudes.

RMS forecast error difference for 500hPa Z TEST minus CNTL

  • Monthly mean difference for July 2003

1day forecast

3day forecast

5day forecast

Positive Impacts of MODIS (negative difference) spread to mid-latitudes with procession of forecast.

EMC Sack Lunch Seminar


Impacts on forecast1
Impacts on Forecast at JMA

  • Anomaly Correlation and RMSE at 500hPa

    • Large improvement for both seasons by 9-day forecasts

    • Neutral for the tropics and the S.H.

      (no MODIS assimilation)

    • Change in the Arctic spread to the lower latitudes.

  • RMS forecast error of wind vectors were reduced.

    • Especially, improvements at 500hPa were remarkable.

      ( 500hPa was the level with maximum data number)

  • Improvements on typhoon track prediction

    • Small, but positive impacts were found at the later stage in the forecasts.

EMC Sack Lunch Seminar


Zonal mean of rmse of wind speed at 500hpa 5 day forecasts january2004
Zonal mean of RMSE of Wind Speed at 500hPa at JMA(5-day forecasts,January2004)

Improvement

Improvement

EMC Sack Lunch Seminar


Impacts on forecast2
Impacts on Forecast at JMA

  • Anomaly Correlation and RMSE at 500hPa

    • Large improvement for both seasons by 9-day forecasts

    • Neutral for the tropics and the S.H.

      (no MODIS assimilation)

    • Change in the Arctic spread to the lower latitudes.

  • RMS forecast error of wind vectors were reduced.

    • Especially, improvements at 500hPa was remarkable.

      ( 500hPa was the level with maximum data number)

  • Improvements on typhoon track prediction

    • Small, but positive impacts were found at the later stage in the forecasts.

EMC Sack Lunch Seminar


Mean positional error of typhoon track predictions
Mean positional error of typhoon track predictions at JMA

  • 22 events in July 2003

  • Neutral or slightly positive at the later stage in the forecast time.

EMC Sack Lunch Seminar


Summary1
Summary at JMA

  • The MODIS polar winds assimilation experiments were performed at JMA

    • Period:July 2003, January 2004

    • Used data:Aqua/MODIS,Terra/MODIS in the Arctic

    • QC

      • Over land, above 400hPa for IR and WV

      • Over ocean, above 700hPa for IR and 550hPa for WV

    • Data thinning 150km(horizontal) 100hPa(vertical)

  • Results

    • Improvements on the analysis and first guess in the Arctic.

    • Large positive impacts on forecasts for both seasons. ( height, temperature, wind fields)

    • Improvements on the typhoon track prediction.

Since 27 May 2004, operational use in the Arctic

Since 16 Sep 2004, operational use in the Antarctic

EMC Sack Lunch Seminar


The change of quality of modis polar winds
The change of Quality of MODIS polar winds at JMA

Wind speed comparison between CIMSS and NESDIS

After June 2004, both data became similar.

Same algorithm for retrieval, and same first guess for height assignment.

CIMSS changed the first guess for height assignment from NAVY model to GFS in June 2004.

EMC Sack Lunch Seminar


Next… at JMA

EMC Sack Lunch Seminar


Improvement of operational forecast score
Improvement of at JMAoperational forecast score

12-month average

Forecast score of JMA global model is rapidly improving.

EMC Sack Lunch Seminar


Rmse of 500hpa height against initial
RMSE of 500hPa height against initial at JMA

5day forecast

1day forecast

N.H.

N.H.

1day forecast

S.H.

5day forecast

S.H.

EMC Sack Lunch Seminar


Conclusion
Conclusion at JMA

  • ATOVS level 1C radiance data are used in JMA global data assimilation system operationally.

  • MODIS polar winds data are used in JMA global data assimilation system operationally.

  • In virtue of these data and 4D-Var system, operational forecast score of JMA global model is improving rapidly.

Filling data poor region(space) with satellite data make better analysis and better forecast.

Next step:

Effective data usage for 4D-Var. Intelligent data thinning and Quality control for 4D-Var time slot in the assimilation window.

Use of new satellite data (AIRS, SSMI, AMSR-E, SSMIS, etc…)

EMC Sack Lunch Seminar


Thank you
Thank you. at JMA

EMC Sack Lunch Seminar


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