utilization of gps radio occultation data for the studies ... · project leader: prof. toshitaka...

Utilization of GPS Radio Occultation Data for the Studies

of Atmosphere Dynamics

Toshitaka TsudaRISH, Kyoto University

The First International Workshop on Prevention and Mitigation of Meteorological Disasters in Southeast Asia3-5 March 2008, Kyoto

Outline• Basic concept of GPS radio occultation (RO)

technique• A project of GEOSS on utilization of GPS RO data• Validation of GPS RO profiles with ground-based

observations • Data assimilation into a meso-scale weather

prediction model• Scientific applications• Current and Future GPS RO missions

Occultation (solar eclipse, lunar eclipse)

Radio occultation technique

Exploration of planetary atmosphere and ionosphere by analyzing radio signals emitted from an interplanetary spacecraft.

Mariner IV: Mars, 1965Mariner V: Venus, 1967Voyager: Saturn, Jupiter

Application of the radio occultation to the Earth’s atmosphere was studied in 1980’s in US and Russia. It was realized by the GPS/MET project in 1995-7 by using a stable GPS radio signal and accurate orbital elements of a satellite (position: 10cm, speed: 0.1mm/s)

Radio and optical ray path bends at an interface of two layers with different refractive index values.

n1

n2

a

b

Snell’s Lown1sin a = n2 sin b

Typical Geometry for Precise Orbit Determination

Modified from a PPT file by Dr. T.P. Yunck

Onion Skin Model

Partial bending angle in individual layer can be related to the refractive index gradient in the corresponding layer by a triangular matrix. (iteration method)

Snell’s law must be satisfied at the interface between the layers.

Because of motion of LEO satellite, time variation of the bending angle is obtained.

GPS Signals received on a low earth orbiting (LEO) satellite are used for an active limb sounding of the atmosphere and ionosphere.

During a rising or setting of a GPS satellite (occultation), the radio rays between the GPS and LEO satellites successively scan the atmosphere (and the ionosphere) from the receiver height down to the surface. A refractive index profile can be retrieved from the time variations of the ray bending angles.

Bending AngleLEO Satellite

Tangent Point

GPS Satellite

Propagation Delay of GPS Signals

Determination of LEO Orbit

Bending of Radio Ray Path

Refractive Index Profile near the Tangent Point

Humi-dity

Tempe-rature

ElectronDensity

Data Assimilation Into NWP models

Basic Concept of GPS Occultation Measurement

GEOSS (Global Earth Observation System of Systems) in JapanTheme 2 : Water cycle and climate changes in the Asia-monsoon region

22-03 Application of GPS radio occultation (RO) data to the studies oftemperature and humidity variations in the tropical troposphere

Project Leader: Prof. Toshitaka Tsuda (RISH, Kyoto University)

22-03 Application of GPS radio occultation (RO) data to the studies oftemperature and humidity variations in the tropical troposphere

Project Leader: Prof. Toshitaka Tsuda (RISH, Kyoto University)

(1) Development of retrieval algorithm for GPS RO dataY. Murayama (NICT; National institute of information and Communications Technology), Y. Aoyama (NIPR: National Institute of Polar Research), H. Hayashi, J. Furumoto (RISH, Kyoto Univ.)

(2) Assimilation of GPS RO data into a meso-scale numerical weather prediction modelY. Shoji, H. Seko, T. Kawabata, K. Aonashi, M. Kunii(MRI; Meteorological Research Institute)

(3) Validation and scientific application of GPS RO dataT. Tsuda, M. Shiotani, T. Nakamura, T. Horinouchi, H. Hayashi, J. Furumoto (RISH; Research Institute for Sustainable Humanosphere, Kyoto University), S. Yoden, N. Nishi (Dep. Earth and Planetary Sci., Kyoto University)

(1) Retrieval of refractive index (n) with a good height resolution

(1) 1D-Var analysis of temperature (T) and humidity (q)

(2) Assimilation of φ and n into MSM for a better prediction of severe weather, including typhoon

GPS Radio Occultation with CHAMP, SAC-C and COSMIC

(3) Validation of n, Tand q with ground-based and satellite data, and comparison with objective analysis

(3) Ground-based observations at validation sites: balloon, lidar etc

Satellite data: AQUA-AIRS

Objective analysis, JMA

(3) Time and spatial variations of n, T and q in the Asian monsoon region

(2) Development of 4D-Var assimilation system of MSM, and expansion of the MSM area toward the equatorial region

JMA: RSM, GSM

Initial value Initial

value

NICT

MRI

Kyoto-U

(1)Development of data analysis system

(2)Assimilation of GPS RO data to MSM

(3)Validation of GPS RO data and application to scientific subjects

Fundamental data-sets: phase delay (φ）, bending angle（α）

(4) MST Radar Observatory Gadanki, India (13.5N, 9.2E)ISRO-NARL

(4) MST Radar Observatory Gadanki, India (13.5N, 9.2E)ISRO-NARL

(2) Okinawa Obs., Ogimi, Japan (26.7N, 128.1E9) NICT

(1) The MU Radar Obs., Shigaraki, Japan (34.8N, 136.1E) RISH

Main Ground-Based Validation Sites in the Asia Monsoon Region in our ProjectMain Ground-Based Validation Sites in the Asia Monsoon Region in our Project

Ground-based validation sites

(3) Equatorial Atmosphere Radar (EAR), Koto Tabang, Indonesia (0.2S, 100.3E), RISH and LAPAN

(3) Equatorial Atmosphere Radar (EAR), Koto Tabang, Indonesia (0.2S, 100.3E), RISH and LAPAN

46.5 MHz, 1MW, 103mφ 475 Yagi antenna array

LIDAR (Raman, Rayleigh)

The Middle and Upper (MU) Atmosphere Radar, RISH, Kyoto Univ (34.8N, 136.1E)

(1)(1)

★VHF (47MHz) wind profiler Antenna array (110 m in diameter): 560 sets of 3-elements Yagiantennas.Peak transmitting power: 100 kW.

Equatorial Atmosphere Radar (EAR), West Sumatra, Indonesia (0.2S, 100.3E)

Equatorial Atmosphere Radar (EAR), West Sumatra, Indonesia (0.2S, 100.3E)

RadiosondeLidarsRASSX-band radarMicro rain radarOptical rain gaugeCeilometerRadiometerDisdrometerGPS receiver

(3)(3)

Gadanki MST radar facility (13.5N, 79.2E)National Atmosphere Research Laboratory (NARL), Indian Space Research Organization (ISRO)

VHF wind profiler 53 MHz, 1MW, 100mx100 m, Yagi antenna array

Raman and Rayleigh lidars

Intensive radiosodesoundingsVAISALA: RS80, RS92daily at 12 GMT from Apr 10 - Sep 25176 profiles

(4)(4)

India, GadankiMST radar obs.

Malaysia (7 sites), Vietnam (3 sites), Singapore Met.

Offices

NICT, Okinawa

obs.

Kyoto-U, ShigarakiMU obs.

High resolution radiosonde data by routine and campaign soundings

Kyoto-U/LAPAN Equatorial

Atmosphere Radar (EAR), Indonesia

Ground-based validation sites

Japan Meteorol. Agency (JMA)

18 stations, 2/day

We obtain original records of routine radiosondesoundings at meteorological agencies (twice daily at 0 and 12 GMT) with sampling interval of 2-5 seconds (10-30 meter height resolution)

Japan (JMA): 18 sitesMalaysia: 7 sitesSingapore: 1 siteVietnam: 3 sites

Refractive index: n (n-1)x106=77.6p/T + 3.73x105q/T2

atmospheric temperature: T (K)pressure: p (hPa)partial pressure of water vapor: q (hPa)

For a dry atmosphere, the second term of n can be neglected. Assuming ideal gas law, p = ρRT

(n-1)x106=77.6ρR

i.e., n is uniquely related to the atmospheric density, ρ(kg/m3)).By using hydrostatic equilibrium (dp/dz=-gρ), pressure (p) can be integrated. Then, by employing equation of state, a T profile is derived.

Derivation of atmospheric temperature and humidity from a refractive index profile observed with GPS occultation

In a moist atmosphere, T and q are separated from n by applying 1D-Var analysis with NWPM values as the initial value.

Comparison of temperature profiles between the COSMIC GPS RO result (#49 and #50) and radiosonde at Kuching, Malaysia.Profiles are shifted by 5K each.

Temperature profiles with GPS RO have a height resolution comparable to a radiosonde, which is useful for the studies of the detailed structure of the tropopause, perturbations with atmospheric waves, etc.

#50

#49

Kuching

#50

#49

Kuching

Comparison of temperature profiles between the COSMIC GPS RO result (#49; Blue and Green) and radiosonde (Orange).Profiles are shifted by 5K each.

Retrieval at UCAR (Blue):Geometric Optics and FSIabove/below 10.6 km

Retrieved at RISH (Green): FSI below 30.5 km

(We will open the RISH data-base to public. Coming soon!)

Comparison of temperature profiles between the COSMIC GPS RO result (Green) and other satellites.

Limb sounding: HIRDLS (Blue, solid) SABER (Blue, dotted).

Nadir: AIRS (Red).

A nearby radiosondeprofile (Orange)

Black dashed: GSM forecast, Black solid: our 1D-Var

analysisBlue dashed: NCEP-AVN, Blue solid: UCAR’s 1D-Var

analysisOrange: NCEP/NCAR

reanalysisRed: radiosonde result at

Yonago, Japan.

Comparison between 1D-Var analysis of T (left) and q (right) from COSMIC GPS RO data with a nearby radiosonde sounding at the JMA Yonago station on 17 November 2006

Good agreement between GPS RO(1D-Var) and radiosonde

Kuala Lumpur International Airport(2.73N, 101.7E), Malaysia

0 2 4 6 8 10 12 14 16 18 200

2

4

6

8

10 Cosmic Radio Sonde

Hei

ght (

km)

Water vapor (g/kg)

Airs

28 September 2006Radio Sonde : Latitude 2.73 N, Longitude 101.7 E

1130 UT

0 2 4 6 8 10 12 14 16 18 200

2

4

6

8

10 Cosmic Radio Sonde

Hei

ght (

km)

Water vapor (g/kg)

Airs

18 September 2006Radio Sonde : Latitude 2.73 N, Longitude 101.7 E

1130 UT

0

2

4

6

8

10

-4 -2 0 2 4

Statistical Comparison between COSMIC and Radio sonde at Klia

Latitude 2.73o N, Longitude 101.70o E

Mean (WVCOSMIC -WVRad) (g/kg)

Hei

ght (

km)

No. of Occultations =5 (>2.0 km)4 - (1.2 - 1.9 km)3 - (0.8 - 1.1 km)2 - (0.1 - 0.7 km)

No. of Occultations =5

In a moist atmosphere, temperature (T) and humidity (q) are separated from n by applying 1D-Var analysis with NWPM values as the initial value. Profiles of q with COSMIC GPS RO are compared with radiosonde results.

In a dry atmosphere (>10km） temperature can be determined with a good height resolution. Detailed thermal structure around the tropopause is seen.

In a moist atmosphere humidity can be delineated with 1D-Var analysis by referring to model results and/or satellite data.

(6.9S,107.6E) Radiosonde

GPS occultation

= Good vertical resolution superior to conventional satellite radiometer measurements: 0.4-1.5 km with geometrical optics, and 0.1 km with advanced algorithm= Accurate profiles comparable to balloon soundings over both land and oceans

Advantages

= Data assimilation in to both global and meso-scale numerical weather prediction models to improve prediction accuracy= Studies of detailed temperature and humidity variations by taking advantages of good height resolution and accuracy

Application

Advantages and Application of GPS Radio Occultation (RO) Data

Comparison of a temperature profile between GPS occultation (GPS/MET) and a nearby radiosonde in Indonesia




prediction model16:30 16:50 Masaru KUNII (MRI); Meso-Scale Data Assimilation Experiment in Low Latitudes

• Scientific applications• Current and Future GPS RO missions

Courtesy by E. Ozawa

Assimilation concept

Various methods for data assimilationVarious methods for data assimilation

Improvement of the initial field

Improvement of the forecast

Delay length by the atmosphereDelay length by the atmosphere

Bending angleBending angle

3 or 4D-Var data assimilation using GPS data

First guess

Analysis

Forecast experim

ents

TemperatureTemperature

Retrieval Procedure of GPS RO Data

No operator

operational use at JMA

Forward

Tangent Linear

Adjoint

RefractivityRefractivity

Courtesy by E. Ozawa (JMA)

4D4D--Var assimilation of LEOVar assimilation of LEO--GPS RO data into a global numerical prediction GPS RO data into a global numerical prediction model at JMA (Japan Meteorological Agency) model at JMA (Japan Meteorological Agency) CourtesyCourtesy by E. Ozawaby E. Ozawa

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CNTL+CHAMPレーダアメダス15-18時

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レーダアメダス15-18時レーダアメダス15-18時

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Prediction withGPS RO data.

4D-Var assimilation of CHAMP-GPS RO data in to a meso-scale numerical weather prediction model, H. Seko (MRI)

4D-Var assimilation of CHAMP-GPS RO data in to a meso-scale numerical weather prediction model, H. Seko (MRI)

CHAMP-GPS RO data

Prediction without GPS RO data.

Radar observations of precipitation during 15-18 LT on July 16, 2004.

図7 2007年7月27日9時の全球解析値(GA)、通常観測データを同化したメソ解析値(MA)、MAに加えGPS掩蔽データを同化したメソ解析値(MA-RO)を初期値とする台風予報実験のうちGAとMA-ROについての72、96時間後の気圧および降水分布。

GA

FT=72

FT=96

FT=72

MA-RO

FT=96

GA

MA

MA-RO

ベストトラック

図8 2007年7月27日9時の全球解析値(GA)、通常観測データを同化したメソ解析値(MA)、MAに加えGPS掩蔽データを同化したメソ解析値(MA-RO)を初期値とする台風予報実験のそれぞれについて、台風0705号の中心気圧の時系列を示したもの。

16:30-16:50 Masaru KUNII (MRI); Meso-Scale Data Assimilation Experiment in Low Latitudes

Prediction on development of a typhoon is greatly improved by assimilating GPS RO data with COSMIC into a meso-scale weather prediction model at MRI.

Active cloud convection in the tropics generates various atmospheric waves which propagate upward carrying wave energy and momentum.

COSMIC: 140E, 12 – 18 Dec 2006

Cloud convection in the tropics

Geostrophic adjustment of jet stream, planetary waves

Wind shear around jet

Meteorological disturbances

Wave – mean flow interactions

More PE equatorward of jet at ~10km may be due to wider range of generation frequencies. Low PE at jet core. Interaction between waves and background mean flow (NH). Large PE extends upward and poleward toward the polar night jet.

Topography

Tropopause

Red: NCEP 7-day averaged u, with solid eastward, dashed westward

Orographic sources too

Cloud top height /OLR(K)

Convective rain rate (mm) / TRMM-PR

Atmospheric wave energy Ep (J/kg) at 19-26 km

Dec 2003 / Jan-Feb 2004

In the northern winter months (Dec/Jan/Feb), intense cloud convections are located over Indonesia and western Pacific, which actively generates atmospheric gravity waves as well as Kelvin wave-like disturbances in the equatorial region.

Gravity wave potential energy (Ep) at 17–23 km altitude in winter 2006/07 (Dec-Feb) by using the COSMIC GPS RO temperature data.

Red contour: the winter mean NCEP u at 500–100 hPa in units of ms−1. Black contour: winter mean GPCP precipitation in mm day−1

Japan – separate large Ep: strong jet & orography

Himalayas & Tibet have large Ep – some orographic effects but also jet stream

Ep is low over Pacific

Large Eastern USA Ep associated with jet

Canadian Rockies have large Ep

First GPS Occultation Experiment was conducted by UCAR from April 1995 to February 1997 by using a small satellite (MicroLab-1). A total of 10,853 profiles were obtained, though the observation periods were limited to the period without anti-spoofing (A/S) encryption.

GPS/MET (GPS Meteorology) Experiment

Bull. Amer. Met. Soc., 77, 19-40, 1996.

1995 - 1997 . . . . . . 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

GPS/MET

CHAMP

SAC-CGRACE

FORMOSAT-3/COSMICMETOP

Ocean Sat/Mega Tropiques

CHINOOK(SWIFT+ARGO)

UCAR, Apr 95-Feb 97

GFZ, July 2000

Argentine + JPL, Nov 2000

UCAR + Taiwan-NSPO, Apr 2006

India-ISRO, 2008-2010 (low inclination)

Canada-CSA, 2011 (polar orbit)

EUMETSAT, 2006

Data rate 5,000/yr 150-200/day/Satellite 2,500/day 5,000/day

GPS radio occultation (RO) missionsGPS radio occultation (RO) missions

COSMIC-follow on (US), CIERTO (commercial), GEMSS (India), ….

Number of GPS RO data with CHAMP (top) and FORMOSAT-3/COSMIC (bottom)

4,500/month=150/day

CHAMPOne GPS ROantenna

COSMIC：6 LEO satellites2 GPS RO antennas

(It is expected to obtain 12 times larger data than CHAMP)

2,000/day

Climatological study (monthly mean) with CHAMP GPS RO data from May 2001- Dec 2005

Climatological study (monthly mean) with CHAMP GPS RO data from May 2001- Dec 2005

Distribution of the CHAMP GPS RO data in October 2002

COSMIC GPS RO data in 5 days on 18–22 September 2006

line: number of GPS data in each 10 deg, red dot: data rate normalized by the area

Preliminary case studies with COSMIC data after September 2006, with a better time and spatial resolution

Preliminary case studies with COSMIC data after September 2006, with a better time and spatial resolution

CHAMP / COSMIC Occultations

Comparison of data (temperature profiles) points between (LEFT) GPS RO with FORMOSAT-3/COSMIC and (RIGHT) Routine radiosonde stations.

Routine radiosonde atations（850 sites, 1-2 launches/day）

GPS RO data on 4 June 2007, 2081 points

Intensive ground validation sitesIndia, TirupatiMST radar obs.

Malyasia, Vietnam, Singapore, Indonesia

Met. Office

NICT, Okinawa obs.

Kyoto-U, ShigarakiMU obs.

Distribution of GPS occultation data

SUMMARY1. We developed a retrieval software for GPS RO data (refractive index; n)

with a good height resolution (about 100 m) comparable to a radiosonde.2. In the lower troposphere n is separated into temperature(T ) and humidity

(q) by applying 1D-Var analysis with GCM results as the initial value. 3. Through close international collaboration, we operate four validation sites

for GPS RO (Shigaraki and Okinawa, Japan; EAR, Indonesia, Gadanki, India), where observations with a wind profiler, lidar, etc are continued. We also use campaign and routine radiosonde results for comparison.

4. We found a very good consistency between GPS RO and radiosonderesults in the refractive index (n), temperature (T ) and humidity (q).

5. We have created a data-base of COSMIC GPS RO data for practical and scientific utilization. The data-base is very useful especially in the Asia monsoon region where routine balloon soundings are sparse.

6. Prediction accuracy of severe weather phenomena, such as a typhoon, a meso-scale weather prediction model as greatly been improved by assimilating GPS RO data.

7. GPS RO data (T and q) are useful for the studies of structure and perturbations of temperature and humidity at 0-40 km, such as stratospheric wave energy, details of the tropopause structures, thin layers in T and q profiles.

Thank you

utilization of gps radio occultation data for the studies ... · project leader: prof. toshitaka...

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