OBS 16: Traditional and new Radio Occultation Sensors

COST 723 UTLS Summerschool

Cargese, Corsica, Oct. 3-15, 2005

Stefan A. Buehler

Institute of Environmental Physics

University of Bremen

www.sat.uni-bremen.de

OBS 16: Traditional and new Radio Occultation Sensors

Stefan Buehler, COST 723 UTLS Summerschool, Cargese, Oct. 3-15, 2005

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Outline

Motivation / Scientific goals

“Classical” GPS radio occultation

Future radio occultation with transmission measurements

Summary and Outlook

Acknowledgements:

Axel von Engeln

ACE+ Mission Advisory Group (in particular Gottfried Kirchengast und Tobias Wehr)


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Outline




Summary and Outlook


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IPCC 2001:“The globally averaged surface temperature is projected to increase by ~1.4–5.8°C over the period 1990 to 2100.” (= average increase ~0.1°C to 0.5°C per decade)

Temperature Variability and Trends

(Figures: IPCC 2001)


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Water vapour is the most important greenhouse gas.But radiative forcing and feedbacks associated with water vapour changes remain disputed and uncertain.Water vapour abundance is most unknown in the upper troposphere.

Hydrological cycle for doublingCO2, IPCC scenario (simulation)

Water Vapour and Climate Change


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Outline




Summary and Outlook


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“Classical” Radio OccultationSee posters by M. Borsche and S. Schweitzer

Use GPS satellite signals at 1.6 and 1.2 GHz

Receiver on satellite (CHAMP, GRASS on Metop) or ground

Measures phase delay (time measurement)

Phase delay related to speed of propagation in atmosphere

catmosphere = cvacuum / n

Refractive index


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The Huygens-Fresnel Principle

Christiaan Huygens 1629-1695

Augustin Fresnel 1788-1827

(Gerthsen-Kneser-Vogel)

sinsin

n2

n1

c1

c2

Secondary waves at every point along the wave front

Wave travels more slowly in medium

Ray bends

c1, n

1

c2, n

2

c: speed of light


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Snell´s Law

Willebrord Snel van Royen (Snellius) 1580-1626

n1≈1 (e.g., air)

n2>1 (e.g., water)

α1

α2

sin 1

sin 2

n2

n1

n: Refractive index


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Refraction of Visible Light


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Refractive index n (surface: 1.000300)

Refractivity N = 106(n − 1) (surface: 300)

Refractivity for low frequencies:

N = 77.6 p T-1 + 3.73 · 105 e T-2

pressure temperature water vapor pressure

Atmosphere refraction exponentially decreases with altitude

Snell’s law gives direction modification of ray

Refractive Index and Refractivity in the Atmosphere


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Ray Bending


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Radio Occultation Geometry

(Figure courtesy Axel von Engeln and/or University of Graz)

Phase delay (time measurement)

Bending angle

Refractivity


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Influence of humidity negligible in stratosphere With assumption of hydrostatic balance sensor can measure temperature

Refractivity depends on pressure, temperature, and humidity


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Humidity and temperature both important in troposphere Can (in principle) retrieve humidity if temperature is

known from GCM analysis (or vice versa)

CHAMP RO data over Hawaii

Figure courtesy Grace Peng < grace.s.peng@ aero.org >


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Ground Based Receivers

Path delay due to dry atmosphere practically constant (about 2m)

Path delay due to water vapor (about 1/10 of the dry delay) highly variable Can be used to retrieve total column water vapor

Absolute measurement accuracy of about 1 kg/m2

Very good relative accuracy in tropics, not good for extremely dry locations

Note: All numbers here are from the top of my head and very uncertain. Better check for yourself before using them!


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CHAMP / GRASS

CHAMP is a German managed radio occultation instrument (GFZ)

Launch: July 15, 2000

Provides measurements of stratospheric temperature and tropopause altitude.

Mixed T/humidity product in troposphere

Height of planetary boundary layer (by-product from altitude where signal is lost)

GRASS will be the RO instrument on Metop, with capabilities broadly similar to Champ


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Errors of retrieved temperature profilestemperature error [K] temperature error [K] temperature error [K]

he

igh

t [k

m]

he

igh

t [k

m]

he

igh

t [k

m]

Low-latitude ensemble Mid-latitude ensemble High-latitude ensemble

Absolute errors of specific humidity profilesabs. spec. hum. error [g/kg] abs. spec. hum. error [g/kg] abs. spec. hum. error [g/kg]

he

igh

t [k

m]

he

igh

t [k

m]

he

igh

t [k

m]

ECMWF Analysis CasesStatistics of retrieval results versus requirements

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GNSS-LEO Performance GPS occultation well demonstrated GPS/MET, CHAMP, SAC-C Important climate parameters with respect to GNSS-LEO are: refractivity, geopotential height, dry temperature, humidity (< 5–8 km)

Dry temperature accuracy from example end-to-end simulation; each average profile (every 10-deg lat.) involves ~50 simulated individual GNSS-LEO occultation profiles sampled by ACE+ constellation within a full summer season (June-July-August).

Expected 25-year temperature trends 2001–2025 (Model: Hamburg ECHAM5 at T42L39 resolution).


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Atmospheric Refractivityan indicator for climate change

Atmospheric refractivity is particularly sensitive to climate change,similar to the geopotential height of pressure levels

15 km

5 km

15 km

5 km

Climate-induced refractivity variations Inter-annual refractivity variations

(Figures: Vedel & Stendel, DMI)


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Outline




Summary and Outlook


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The Refractive Index

Actually a complex quantity

Real part: Responsible for phase delay, measured by GPS systems

Imaginary part: Responsible for absorption, measured indirectly by most other remote sensing techniques

Re(n) spectrally flat for sum of many lines Must measure Im(n) to get trace gas signatures

Re(n)

Frequency

1

0

Im(n)

Behavior of complex refractive index near an absorption line


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H2O Spectrum

22 GHz line is also used for uplooking passive MW measurements (see poster by A. Haefele)

AMSU-B, UARS-MLS

Good for radio occultation

Take lowest frequency line to minimize impact of clouds and precip.


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What I will show now is from a concept for a RO mission involving several small satellites

Mission name: ACE+ (unrelated to Canadian ACE mission)

Phase A study in 2003/2004

Not selected, but similar proposals in current call


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GPS / GalileoL-Band Transmitter

2 ACE+ satellitesat ~800 km:

X/K-Band TransmitterL-Band Receiver

2 ACE+ satellites at ~650 km:

X/K-Band Receiver L-Band Receiver

Observation TechniqueGNSS-LEO Occultation Component






Exploits refraction of L-band signals between GPS/Galileo and ACE+ receiving satellites.

Measurements of phase delay bending angle real refractivity temperature, pressure (> ~8 km). Humidity, temperature, pressure with a priori information on temperature (< ~8 km).


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Observation Technique

Exploits refraction and absorption of X/K-band signals (~10, 17, 23 GHz at water vapour absorption line) between transmitting and receiving satellites (2 pairs 4 satellite constellation).

Measurements of phase delay & amplitude bending angle & transmission real & imaginary refractivity humidity, temperature, pressure (independently above ~2–6 km).

LEO-LEO Occultation Component







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Need two frequencies to separate humidity absorption from cloud absorption

Third frequency needed for dynamic range


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Large dynamic range required for receiver

Tan

gent

alti

tude

[km

]

Different curves = different frequencies


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Self-calibration of both refraction and transmission measurements


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Orbits

Sun-synchr. orbits at 9:30/21:30 local time

Altitudes: ~650 km (RX) and ~800 km (TX)

Inter-satellite phasing: 180o for TX; ~80o or 45o for RX

TX-RX pointing at each other to use simple and highly directive antennas

T1 T2

R1R2

Example LRO event timing


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ACE+ Geographical Coverage

LEO-LEO coverage 1 month(7203 occultations = 3601 setting [] + 3602 rising [])

1 day 1 month

LEO-LEO coverage 1 day (232 occultations = 116 setting [] + 116 rising [])

LEO-LEO coverage 1 month(7203 occultations = 3601 setting [] + 3602 rising [])

1 day 1 month

LEO-LEO coverage 1 day (232 occultations = 116 setting [] + 116 rising [])

1 day

GPS-LEO + Galileo-LEO coverage 1 day(4515 occultations = 2240 setting [] + 2275 rising [])

Coverage: LEO-LEO

~230 profiles/day ~7000 profiles/month

GNSS-LEO (GPS & Galileo) 24 GPS & 27 Galileo sats ~4500 profiles/day


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Satellites TX and RX satellites identical except for LRO electronics

Modular concept

Configuration driven by antenna accommodation and thermal stability

Star-tracker(s) tightly coupled to LRO antennas

Good attitude control performance: < 0.05o pointing accuracy, < 0.005o pointing drift over 30 s

Thermal stability for LRO electronics (RX: < 0.1o/minute)

Mass: ~160 kg

Power consumption: ~250 W

Data rate: ~250 Mb/orbit

Dimensions: < 1.3 m 0.8 m 0.7 m

nadir

flight direction

Earth limb

GRO antenna

LRO antennas

star-tracker


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Geophysical Products Performance Assessment

Performance Simulator

Observation Simulator

Geometry and signal propagation modelling

Instrument simulation

Retrieved atmosphere

Temperature, Humidity, Pressure, ...

Geophysical RetrievalProcessor

Model atmosphere e.g. from climatology or ECMWF analyses

Temperature, Humidity, Pressure, ...

Instrument parameters

Background profiles(for retrievals withoutabsorption meas.) Temperature, ...

ACE+ Level 1bdata products Doppler shift

profiles Bending angle

profiles Transmission

profiles ...

Comparison


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ECMWF Analysis Cases

Input (“true”) atmosphere for simulation:

T511L60 ECMWF analysis (12 UTC analysis of Sept. 15, 2002; background shows integrated liquid water density)

Sampling of ACE+ LEO-LEO occ. in a day (including every 2nd event) Latitude bands of 30º each: low latitude, mid latitude, high latitude


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ECMWF Analysis Cases Input atmosphere: ECMWF analysis used for retrieval simulation (continued)

specific humidity temperature

liquid water density ice water density

Exemplary latitude-height cross sections at 0º longitude through the ECMWF analysis used in the simulations, indicating the variability of the relevant parameters.


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ECMWF Analysis CasesInput atmosphere: ECMWF temperature and humidity profiles (all profiles of ensemble)


specific humidity [g/kg] specific humidity [g/kg] specific humidity [g/kg]

temperature [K] temperature [K]temperature [K]

he

igh

t [k

m]

he

igh

t [k

m]

he

igh

t [k

m]

he

igh

t [k

m]

he

igh

t [k

m]

he

igh

t [k

m]


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ECMWF Analysis CasesStatistics of retrieval results versus requirements


Absolute errors of specific humidity profilesabs. spec. hum. error [g/kg] abs. spec. hum. error [g/kg] abs. spec. hum. error [g/kg]

he

igh

t [k

m]

he

igh

t [k

m]

he

igh

t [k

m]

Relative errors of specific humidity profiles

rel. spec. hum. error [%] rel. spec. hum. error [%] rel. spec. hum. error [%]

he

igh

t [k

m]

he

igh

t [k

m]

he

igh

t [k

m]

threshold requirement

target requirement

Errors of retrieved temperature profilestemperature error [K] temperature error [K] temperature error [K]

he

igh

t [k

m]

he

igh

t [k

m]

he

igh

t [k

m]

threshold requirement

target requirement


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Scintillations

Performance at low altitude is limited by scintillations (included in simulations shown)

Scintillations = random fluctuations of signal strength due to small scale refractivity variations associated with turbulence (also affects GOMOS on Envisat)

New mission proposal in the current call exploits pairs of channels at close frequencies to remove scintillations (use derivative of spectrum, same trick as in TDL hygrometer)


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Averaging window [days]

Global mean spec.humidity error, 300 hPa

Spe

cific

hum

idity

err

or [%

]


Global mean spec.humidity error, 500 hPa

Spe

cific

hum

idity

err

or [%

]

dominated by LEO-LEO data (sensitivity at high altitudes)

dominated by GNSS-LEO data (large number of measurements)

dominated by LEO-LEO data (sensitivity at high altitudes)

dominated by GNSS-LEO data (large number of measurements)


Global mean temperature error, 300 hPaAveraging window [days]

Global mean temperature error, 500 hPa

Averaging window [days] Averaging window [days]

Global mean spec.humidity error, 300 hPa Global mean spec.humidity error, 500 hPa

Spe

cific

hum

idity

err

or [%

]T

empe

ratu

re e

rror

[K]

Spe

cific

hum

idity

err

or [%

]T

empe

ratu

re e

rror

[K]

Climate Variability and Trends Measurement Performance

Global-mean (ACE+) climatological humidity and temperature accuracy as function of averaging interval and number of ACE+ satellites. Dotted lines: Desired climatological accuracy (to be achieved within < 30 days) for climate variability and trend analysis.


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Outline




Summary and Outlook


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Summary

“Classical” GPS RO provides stratospheric temperature with high absolute accuracy

Refractivity in the troposphere, a priori needed to separate humidity and temperature

Future RO with phase and amplitude measurement can provide accurate humidity throughout the free troposphere

Advantages: Self-calibrating, all-weather, well-understood measurement

Disadvantages:Sparse sampling with only 4 satellites, Poor horizontal resolution


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Outlook

Three (3!) RO transmission missions proposed in current call:

1: Combined with IR laser transmission measurement

2: Combined with water vapor lidar

3: Using channel pairs to remove scintillations

Fair chance that one of these goes to phase A.


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Thanks for your attention.Questions?

...


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ACE+ Mission Requirements

–

OBS 16: Traditional and new Radio Occultation Sensors

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