Global and regional oses at jma
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Global and regional OSEs at JMA. Ko KOIZUMI Numerical Prediction Division Japan Meteorological Agency. Contents. Experiments with Global Spectral Model Asia-Pacific RARS and EARS MTSAT-1R Clear-Sky Radiance BUFR AMV (incl. MTSAT-1R Hourly AMV) instead of SATOB

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Global and regional OSEs at JMA

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Global and regional oses at jma

Global and regional OSEs at JMA

Ko KOIZUMI

Numerical Prediction Division

Japan Meteorological Agency


Contents

Contents

  • Experiments with Global Spectral Model

    • Asia-Pacific RARS and EARS

    • MTSAT-1R Clear-Sky Radiance

    • BUFR AMV (incl. MTSAT-1R Hourly AMV) instead of SATOB

  • Experiments with Meso-Scale Model

    • BUFR AMV (incl. MTSAT-1R Hourly AMV) instead of SATOB

    • Doppler radar radial wind

    • Ground-based GPS


Global experiments specification

Global Experiments Specification

  • Model: Global Spectral Model TL319L40

  • Assimilation:

    • 4D-Var method

    • Inner model resolution: T106L40

    • Assimilation window: six hours

    • Six-hourly cycle

  • Experiment period: one month each for summer and winter

  • Forecasts: 216 hour forecasts once a day at 12 UTC


Atovs used in global analysis

ATOVS used in Global Analysis

Early Analysis

Data cut-off time : 2h20min.

Cycle Analysis

Data cut-off time :

11h35min.(00 and 12 UTC)

5h35min.(06 and 18 UTC)


Coverage of rars data

Coverage of RARS data

EARS

AP-RARS

2008.5.12


Analysis difference of 20hpa height early analysis cycle analysis

Analysis difference of 20hPa height(Early analysis – Cycle analysis)

w/o AP-RARS

06 UTC 25 Sep. 2006

Data from Beijing and Crib Point were provided by AP-RARS

with AP-RARS


Comparison of rmse scores winning among 30 forecasts in september 2006

Comparison of RMSE scores(winning % among 30 forecasts in September 2006)

(forecast hours)

Almost neutral for scores of troposphere


Ears eumetsat advanced retransmission service

EARS (EUMETSAT Advanced Retransmission Service)

EARS data (AMSU-A)

at 12 UTC 17 June 2007

EARS data (AMSU-B)

at 12 UTC 17 June 2007

Analysis difference of 500hPa height

w/o EARS

with EARS


Comparison of rmse scores winning among 30 forecasts in june 2007

Comparison of RMSE scores(winning % among 30 forecasts in June 2007)

(forecast hours)

  • Positive impacts mainly on early hours of forecasts

  • Difference of impacts of AP-RARS and EARS might be due to the difference of data amount


Mtsat 1r clear sky radiance

MTSAT-1R Clear-Sky Radiance

  • Infrared 3 channel (6.5-7.0 μm)

  • Averaging radiances of cloud-free pixels in a 16 x 16 pixel region (60km x 60km at nadir)

  • Thinned to 2 x 2 degree longitude/latitude and to every two hours

  • Variational bias correction applied


Comparison of rmse scores winning among 31 forecasts in aug 2006 and jan 2007

Comparison of RMSE scores(winning % among 31 forecasts in Aug. 2006 and Jan. 2007)

August 2006

January 2007


Typhoon track forecasts typhoon center position errors in august 2006

Typhoon track forecasts(Typhoon center position errors in August 2006)

RED: w/o MTSAT-1R CSR

BLUE: with MTSAT-1R CSR


Amv in bufr format instead of satob

AMV in BUFR format (instead of SATOB)

  • Larger amount of data, including hourly reports of MTSAT-1R AMV, are available

  • Data selection using Quality Indicator (contained in the reports) is possible

More strict data selection from larger amount of candidates improves the forecasts


Data selection strategy

Data selection strategy

Thinning:

One datum in a 2 degree x 2 degree box in the assimilation window (6 hours)

Data not used mainly due to irremovable biases of data (or model)

QI threshold


Comparison of rmse scores winning among 30 forecasts in sep 2005 and jan 2006

Comparison of RMSE scores(winning % among 30 forecasts in Sep. 2005 and Jan. 2006)

September 2005

January 2006


Typhoon track forecasts typhoon center position errors in sep 2005

Typhoon track forecasts(Typhoon center position errors in Sep. 2005)

RED: with BUFR AMVs

BLUE: with SATOB AMVs


Regional experiments specification except for gps experiment

Regional Experiments Specification(except for GPS experiment)

  • Model: MesoScale Model

    • Non-hydrostatic grid model with 5km grid distance

  • Assimilation:

    • 4D-Var system based on a hydrostatic spectral model (former operational model)

    • Outer/ Inner resolution: 10km/20km

    • Assimilation window: six hours

    • Three-hourly cycle

  • Experiment period: one or two weeks in a rainy season

  • Forecasts: 33 hour forecasts were made six-hourly (03, 09, 15 and 21 UTC initials)


Data selection strategy1

Data selection strategy

Data not used mainly due to irremovable biases of data (or model)

QI threshold

  • Thinning:

  • One datum in a 200 km x 200 km box,

  • in 6-hour assimilation window (test 1)

  • in every one hour (test 2)


Results of an experiment in 1 15 july 2007

Results of an experiment in 1-15 July 2007

Threat scores of 3-hour precipitation forecast against analyzed precipitation

RMSE of wind speed forecasts at ft=3 against radiosonde observation in Japan

RED: with SATOB AMVs

GREEN: with BUFR AMVs (one datum per six hours)

BLUE: with BUFR AMVs (one datum per one hour)


Weather radars of jma

Sapporo

Kushiro

Hakodate

Akita

Niigata

Sendai

Fukui

Matsue

Tokyo

Hiroshima

Nagano

Fukuoka

Shizuoka

Nagoya

Tanegashima

Oosaka

Murotomisaki

Naze

Okinawa

Ishigaki-jima

Weather Radars of JMA

Doppler radar used in the analysis for MesoScale Model

PINK

YELLOW

Doppler radar planned to be used in the analysis for MesoScale Model

CYAN

Not yet Doppler-ized


Preprocessing of the data

Preprocessing of the data

  • Original data

  • 3D volume scan

  • (resolution)

  • 500m (radius)

  • 0.7deg.(azimuth)

  • 15 pre-set elevation angles

Thinning

&

Quality control

  • Averaged data

  • (resolution)

  • 5km (radius)

  • 5.625 deg.(azimuth)

  • 15 pre-set elevation angles


Thinning 2d or 3d

All data2D thinning3D thinning

Thinning (2D or 3D)

Considering only two-dimensional data distribution on a cone of an elevation angle

Easy to implement but too dense near the radar

Considering three-dimensional distribution of all data

20km horizontally

0.5km vertically


Quality control

Quality Control

Following data are rejected

  • Number of samples in an averaging volume is smaller than or equal to 10

  • Range of velocity in an averaging volume is larger than 10m/s

  • Departure from first-guess is larger than 10m/s

  • Velocity is lower than 5m/s

    • Coherent MTI algorithm sometimes works wrong with slow-moving particles

  • Within 10km from the radar

    • To avoid backscattering noise

  • Elevation angle is larger than 5.9 degree

    • To avoid contamination from raindrop falling


Statistical scores 8 17 june 2006

Statistical scores(8-17 June 2006)

Threat scores of 3-hour precipitation

RMSE of wind speed of six-hour forecasts against radiosondes

Height (hPa)

Threshold value (mm/3hour)

RMSE (m/s)

Green: with Doppler velocity of Tokyo radar (w. 3D thinning)

Red: w/o Doppler velocity of Tokyo radar


Impact of different thinning method

Impact of different thinning method

Threat scores of 3-hour precipitation

Green: 3D thinning

Red: 2D thinning

Threshold value (mm/3hour)


Global and regional oses at jma

An example of 3-hour precipitation forecast

w. Tokyo radar Doppler vel.

(3D thinning)

Observation

w/o Tokyo radar Doppler vel.

FT=9

Observation

w. Tokyo radar Doppler vel.

(3D thinning)

w/o Tokyo radar Doppler vel.

FT=12


Ground based gps observation

Ground-based GPS observation

  • Over 1,000 GPS receivers are owned by Geographical Survey Institute

  • A real-time analysis system of ZTD and PW has been installed in JMA headquarter.


Global and regional oses at jma

GPS real-time analysis shows good agreement with radiosonde observation(August 2005 and January 2006)


Quality control etc

C

B

A

Model topography

Actual topography

Quality control etc.

  • PW value is modified according to model topography

  • PW smaller than 1mm or larger than 90mm is rejected

  • A datum is rejected when the departure from first guess is larger than 8mm

  • A datum is rejected when the departure is larger than 5mm and differs from the averaged departures of surrounding data (within 20km) for 5mm or larger

  • No thinning applied


Statistical scores for 3 hour precipitation 1 to 13 sep 2006

Statistical scores for 3-hour precipitation(1 to 13 Sep. 2006)

The experiment was performed with the hydrostatic spectral version of MSM and the same 4D-Var as in the other experiments except for 3-hour assimilation window

Positive impact at FT=9 and after

Precipitation is suppressed in early stage


An example of 3 hour precipitation forecast ft 6 9 from 00 utc 6 sep 2006

mm

An example of 3-hour precipitation forecast(FT=6-9 from 00 UTC 6 Sep. 2006)

Observation

with GPS PW

w/o GPS PW

Seems good, however …

When an integrated value is assimilated, the increment distribution depends on the system

Analysis increments of specific humidity

(for positive departure of PW)

Height (km)

0 2 4 6 8 10

insufficient(?)

-6 -4 -2 0 2 4 6 8 (g/kg)


Summary

Summary

  • RARS

    • Improve the operational forecast

    • Impact depends on the amount of available data

  • CSR of MTSAT-1R

    • Improve the forecast especially in boreal summer

    • Improve typhoon track forecast

  • BUFR AMV

    • Advantage to SATOB AMV in data amount and QI

    • “more strict data selection from larger volume of candidates” is preferable to the forecast

  • Doppler velocity

    • Impact is sensitive to data thinning

  • Ground-based GPS

    • Positive impact can be acquired even from the near real-time data

    • Since the vertical distribution of analysis increment from vertically integrated observation (such as ZTD or PW) depends on the assimilation system, some modifications to the assimilation system might be able to enhance the impacts of the data


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