observations 1: an introduction to water vapour

TheRoleofWaterVapour intheClimateSystem,

COSTSummerSchoolCargese,Sept14-26th2009

Observations1:

AnIntroductiontoWaterVapourObservationsinOperationalNumericalWeatherPrediction(NWP)

W.Bell

Acknowledgements:P.Bauer,S.Healy,D.Dee,P.Poli,A.BodasSalcedoA.Geer.



Overview: Observations 1, 3 & 4

Observations 1: An introduction to water vapour observations inNumerical Weather Prediction (NWP)

What are the most important data sources in NWP ? How are observations used in data assimilation systems ?

Observations 2: Observations in Operational NWP. Introduction to data assimilation Observation operators Radiative transfer: IR vs MW

Observations 3: Observations in Operational NWP What’s the relationship between NWP, Re-analysis and

Climate? Applications: cloud and rain affected observations



•NWPmodelsanddataassimilation

•Theglobalobservingsystem

•SatelliteObservations:

•Microwavesounders&imagers•Infraredsounders•GPSROandgroundbasedGPS•NearIRobservations(MERIS)

Observations 1: Outline



ECMWF global model:

Resolution: Currently T799 (25km). T1279 (15km) due late 2009. L91Assimilation system: 4D-Var.

The ECMWF Operational Model



Improvement in Forecast Accuracy



The observations are used to correct errors in the shortforecast from the previous analysis time.

Every 12 hours we assimilate 4 – 8,000,000 observations tocorrect the 100,000,000 variables that define the model’svirtual atmosphere.

This is done by a careful 4-dimensional interpolation in spaceand time of the available observations; this operation takesas much computer power as the 10-day forecast.

The Analysis: Providing Initial Conditions



NWP data assimilation:observation distributions00UTC 6 February 2009 ±3h

Radiosondes

GPSRO

Aircraft

Sounders

IR: 15 _m CO2MW: 50 GHz O2



0

10

20

30

40

50

60

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

SMOS

TRMM

CHAMP/GRACE

COSMIC

METOP

FY-3A

FY-2C winds

MTSAT rad

MTSAT winds

JASON

GOES rad

METEOSAT rad

GMS winds

GOES winds

METEOSAT winds

AURA

AQUA

TERRA

QSCAT

ENVISAT

ERS

DMSP

NOAA

Satellite observing system



0

5

10

15

20

25

30

1996 1997 1998 1999 2000 20012002 2003 2004 2005 2006 2007 2008 2009 2010

TOTAL

CONV+AMV

Million

Satellite data volume



What types of satellites are used in NWP?

Geostationary satellites (GEO)

Low-Earth observing satellites (LEO)



What types of satellites are used in NWP?

Advantages Disadvantages

GEO - large regional coverage - no global coverage by single satellite

- very high temporal resolution - moderate spatial resolution (VIS/IR)> short-range forecasting/nowcasting > 5-10 km for VIS/IR> feature-tracking (motion vectors) > much worse for MW> tracking of diurnal cycle (convection)

LEO - global coverage with single satellite - low temporal resolution

- high spatial resolution>best for NWP!



Operational Satellite Sounding Instruments



‘Research’ platforms not shown, eg: Windsat, AMSR, TMI, GCOM-W, GMI

Operational MW Imagers



(Thomas and Stamnes, Radiative transfer in the atmosphere and ocean, 2002. Fig 11.2)

Abs

orpt

ance

(%)

NIReg MERIS

MIReg AIRS/IASI

EM spectrum : 100nm - 100µmAtmospheric transmission / water vapour absorption



Moist H2ORotationlines +Watervapourcontiuum

Dry O2RotationLines+Dryaircontinuum

The Microwave Spectrum

Regioncoveredbyoperationalmicrowavesensors

EM spectrum : 5 – 500 GHz ( 6cm - 600 μm)Atmospheric transmission / water vapour absorption



Microwave Sounders

(MSU, AMSU-A, AMSU-B,MHS, ATMS)

and

Microwave Imagers

(SSMI, SSMIS, AMSR-E, TMI, Windsat, MIS …)



Microwave Sounders in operational systems

N

MetOp-A

N16

N18

F-16 SSMISN-15

EOS-AQUA

Met Office ECMWF

• T information from 50-60 GHz O2

absorption

• Q information from 183 GHz H2Oabsorption, and window channels at(19, 22, 37, 89 and 150 GHz)

N19

F-17 SSMIS



AMSU – A cross track microwave sounder

AMSU A1 AMSU A2 AMSU B

The use of small (< 30cm) apertures limits horizontal resolution, but improves radiometric performance - this is critical for NWP !

Ground footprint (diffraction) limited by antenna size: θ ~λ /D



MainReflector

ColdCalibrationReflectorWarm LoadFeedhorns

Special Sensor Microwave Imager/Sounder (SSMIS)

SSMIS – A conical microwave sounder

F16 launched October 2003F17 launched November 2006F18 – F20 : 2008 – 2015(NPOESS MIS – conical scanner)



SSM/I observations

(M.Rodwell)



SSM/I observation-model

(M.Rodwell)



Trenberth, K.E., Trends and Variability in Column Integrated Water Vapour, Climate Dynamics, 2005.

Trends in column integrated water vapour



Infrared (IR) Sounders

(HIRS)

and

Advanced IR Sounders

(AIRS, IASI)



IR Sounders

HIRS• Flown on NOAA / MetOp platforms as part of ATOVS suite• 20 channel filter based radiometer• 2 LW WV sounding channels at 7.33 & 6.52 μm• Spectral resolution (channel dependant) : 3 – 55 cm-1



Advanced IR Sounders

• AIRS launched 2002 (Aqua)• grating spectrometer• spectral range: 3.74-15.4μm• resolving power λ/Δλ ~1200 (eg ~1cm-1 at 1200 cm-1)

• IASI launched 2006 (Metop-A)• Interferometer• Spectral range: 3.6-15.5 μm• Resolution 0.35 cm-1



Water continuumabsorptionimportant here

IASI / AIRS water vapour channels assimilated

(A.Collard)



Global Positioning System Radio Occultation(GPSRO) Measurements

and

Ground based GPSMeasurements



Refractive index: Speed of an electromagnetic wave in a vacuumdivided by the speed through a medium.

Snell’s Law of refraction

vcn =

2211 sinsin inin =

1n

2n

1i

2i

Global positioning System Radio Occultation (GPSRO) Measurements: Some basic physics



Measurements made using GPS signals

GPS

GPS Radio Occultation (Profile information)

Ground-based GPS (Column integrated water vapour)

LEO

GPS receiveron the ground

GPS Receiver placed on satellite



Radio Occultation: Background

Radio occultation (RO) measurements have been used to studyplanetary atmospheres, such as Mars and Venus, since the1960’s. Its an active technique. We simply look at how the pathsof radio signals are bent by refractive index gradients in theatmosphere.

The use of RO measurements in the Earth’s atmosphere wasoriginally proposed in 1965, but required the advent of the GPSconstellation of satellites to provide a suitable source of radiosignals.

In 1996 the proof of concept “GPS/MET” experimentdemonstrated useful temperature information could be derivedfrom the GPS RO measurements.



GPS RO: Basic idea

The GPS satellites are primarily a tool for positioning and navigationThese satellites emit radio signals at L1= 1.57542 GHz andL2=1.2276GHz (~20 cm wavelength).

The GPS signal velocity is modified in the ionosphere and neutralatmosphere because the refractive index is not unity, and the path isbent because of gradients in the refractive index.

GPS RO is based on analysing the bending caused by the neutralatmosphere along ray paths between a GPS satellite and a receiverplaced on a low-earth-orbiting (LEO) satellite.



GPS transmitter

LEO receiver“eg, GRAS”

α

Setting occultation: as the LEO moves behind the earthwe obtain a profile of bending angles, α, as a function ofimpact parameter, . The impact parameter is thedistance of closest approach for the straight line path. Itsdirectly analogous to angular momentum of a particle.

20,200km

800km

a

a

Tangent point

The motion of LEO results in sounding progressively lower regions of the atmosphere.

GPS RO geometry


COSTSummerSchoolCargese,Sept14-26th2009 ∫∞

−−=

a

dxaxdxnd

aa22

ln2)(α

Assuming spherical symmetry the ionospheric correctedbending angle can be written as:

We can use an Abel transform to derive a refractive index profile

Convenient variable (x=nr)(refractive index * radius)

Corrected Bending angle as a function of impactparameter

−= ∫

∞

a

daxa

axn22

)(1exp)( απ

Note the upper-limitof the integral! A priori needed.

Deriving the refractive index profiles



221

6 )1(10

TPc

TPcnN

w+=

−=

The refractive index (or refractivity) is related to the pressure,temperature and vapour pressure using two experimentallydetermined constants (from the 1950’s and 1960’s!)

If the water vapour is negligible, the 2nd term = 0, and therefractivity is proportional to the density

ρRcTPcN 11 =≈

refractivityThis is two term expression isprobably the simplestformulation for refractivity, butit is widely used in GPSRO.We are testing alternativeformulations.

So we have derived a vertical profile of density!

Refractivity and Pressure/temperature profiles:“Classical retrieval”



GPSRO Data Coverage 15th April, 2009 (00Z)



1D-Var information content (Collard+Healy, 2003)QJRMS, 2003, v129, 2741-2760

RO provides good temperature informationbetween 300-50hPa. IASI retrieval performedwith 1000 channels, RO has 120 refractivityvalues. (Refractivity errors are verticallycorrelated because of the Abel transform).

In theory RO should provide useful humidityinformation in the troposphere. Further workneeded to demonstrate the value of watervapour derived from GPSRO.

RO provides very little humidity informationabove 400hPa. The “wet” refractivity is smallcompared to the assumed observation error.



Vertical resolution (1D-Var averaging kernels – how well a retrieval canreproduce a spike)



dzTPc

TPc

TPcZTD ww∫

∞

++=

02

3'21

“Hydrostatic delay” “wet delay”

Information contentThe “hydrostatic delay” is large (90% of total), but it is only reallysensitive to the surface pressure value at the receiver.

The “wet delay” is smaller, but more variable. The wet delay isrelated to the vertical integral of the water vapour density.

(See Bevis et al, (1992), JGR, vol. 97, 15,787-15,801, for theclassical retrieval of integrated water vapour. )

Typically 2.3 m

ECMWF monitors zenith total delay



Near Infrared Observations

Differential Absorption Measurementsfrom MERIS



Assimilation of Envisat MERIS Total Column Water Vapour (TCWV)

Spatialresolution:300or1200mSwathwidth:1150km(3-dayrepeatcycle)



Envisat

MIPAS:MichelsonInterferometerforPassiveAtmosphericSounding

SCIAMACHY:ScanningImagingAbsorptionSpectrometerforAtmosphericChartography

GOMOS:GlobalOzoneMonitoringbyOccultationofStars

MERIS:MediumResolutionImagingSpectrometer

ASAR:AdvancedSyntheticApertureRadar

RA-2:RadarAltimeter

MWR:MicrowaveRadiometer

AATSR:AdvancedAlong-TrackScanningRadiometer

DORIS:DopplerOrbitographyandRadioPositioningIntegratedbySatellite

LRR:LaserRetro-Reflector



MERIS & MODIS

MERISchannels

MODISchannels

(Albert2004)



Data product & ExperimentsSensitivitytowatervapour Sensitivitytosensornoise

MERIS MODIS

Retrievalerrorestimate

(Albert2004)



Data coverage

MeanobservedTCWV[kgm-2]:

Meanfirst-guessdeparture[kgm-2]:

Meandailydatanumber:

Experiments:• CY35R2+VarBC• 07-09/2006• 5km→50kmdatasampling

kgm-2

kgm-2

#



MERIS data: Analysis impact

August2006

MeanANTCWV MeanAN-differenceTCWV[%]



January-February2008

MeanANTCWV MeanAN-differenceTCWV[%]

MERIS data: Analysis impact



MERIS data: Evaluation with radiosondes

(A.Garcia-Mendez)



Allsondes August2006 VaisalaRS92


Australia

Arabia

S.Africa

MERISCTRL



Allsondes August2006 VaisalaRS92


N.Africa

S.America

MERISCTRL

observations 1: an introduction to water vapour

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