egu 2009 vienna 19 – 24 apr 2009 ice on ir sensors: mipas case ice contamination on satellite ir...

EGU 2009Vienna

19 – 24 Apr 2009

Ice on IR Ice on IR sensors: sensors:

MIPAS caseMIPAS case

Ice contamination on satellite IR Ice contamination on satellite IR sensors: the MIPAS casesensors: the MIPAS case

F. NiroF. Niro(1)(1), T. Fehr, T. Fehr(2)(2), A. Kleinert, A. Kleinert(3)(3), H. Laur, H. Laur(2)(2), P. Lecomte, P. Lecomte(2)(2) and G. Perronand G. Perron(4)(4)

(1) Serco S.p.A., Via Sciadonna, 24, 00044 Frascati, Italy(2) European Space Agency (ESA) - ESRIN, Via Galileo Galilei, 00044 Frascati, Italy

(3) Forschungszentrum Karlsruhe GmbH, Institut für Meteorologie und Klimaforschung (IMK), P.O. Box 3640, 76021 Karlsruhe, Germany

(4) ABB Bomem Inc., 585 Blvd. Charest East, Québec, G1K 9H4, Canada

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 2

ContentsContents

IntroIntro

Intro

MIPAS on ENVISAT: instrument overview and status

Calibration

MIPAS Calibration strategy and requirements

Focus on the radiometric calibration: the gain function

Ice effects

The ice effects on MIPAS

Ice on AATSR and SCIAMACHY

Summary

Summary and lessons learned

What’s next

The ENVISAT and MIPAS mission extension beyond 2010

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 3

MIPAS on ENVISAT MIPAS on ENVISAT MIPAS is a FTS measuring the limb atmospheric emission in the mid-IR

spectral range, 4.15 µm – 14.5 µm, 685 – 2410 cm-1 The INT is a dual slide. The two output ports are directed to two sets of

four duplicated detectors. This allows for redundancy and for enhanced radiometric performances

The detectors and their fore optics are stored in the FPS and cooled down to 70K with a pair of Stirling-cycle coolers

IntroIntro

Spectral range: 685 - 2410 cm-1

(5 bands)

1020-1170

AB1215-1500

B1570-1750

C1820-2410

D685-970

Acm-1

Spectral range: 685 - 2410 cm-1

(5 bands)Spectral range: 685 - 2410 cm-1

(5 bands)

1020-1170

AB1020-1170

AB1215-1500

B1215-1500

B1570-1750

C1570-1750

C1820-2410

D1820-2410

D685-970

Acm-1685-970

Acm-1

Fourier Transform IR (FTIR) Limb Sounding Spectrometer

day and night measurements

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 4

““Optimized Resolution” missionOptimized Resolution” mission On March 2004 after an increase of INT velocity errors (speed of one or

both slides exceeds 20% of the nominal speed) the MIPAS mission was suspended and several tests made to find the best configuration

The new scenario started on Jan 2005 with: Spectral resolution was reduced to 41% of the original one (0.0625 cm-

1 instead of 0.025 cm-1) Vertical and horizontal sampling of the atmosphere was increased

owing to the shorter measurement time Duty cycle reduced to about 40% in order to reduce INT errors

IntroIntro

Increase of vertical samplingIncrease of horizontal sampling from FR (red) to OR (blue)

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 5

MIPAS instrument statusMIPAS instrument status High number of INT velocity errors were still observed during 2005 – 2006 The errors type was analyzed in details it was found that it depends on

Temp (beam-splitter), friction (bearings) and # of initialization (start-up) Corrective actions were undertaken that allow to decrease the number of

errors and increase duty cycle up to 100% since Dec 2007

Mipas instrument availability since launch

0%

20%

40%

60%

80%

100%

Nov-02

Mar-03

Jul-03

Nov-03

Mar-04

Jul-04

Nov-04

Mar-05

Jul-05

Nov-05

Mar-06

Jul-06

Nov-06

Mar-07

Jul-07

Nov-07

Mar-08

Jul-08

Nov-08

IntroIntro

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 6

MIPAS products and calibrationMIPAS products and calibration The MIPAS operational products are:

Level 1: Calibrated atmospheric emission spectra Level 2: atmospheric profiles of p-T and main target species (O3, H2O,

CH4, N2O, HNO3, NO2) The L1 calibration process consists of:

Radiometric calibration: The process of assigning absolute values in radiance units (W/(cm2 sr cm−1)) to the intensity axis (y-axis)

Spectral calibration: The process of assigning absolute values in cm−1 to the wavenumber axis (x-axis)

LOS calibration: The process of assigning an absolute LOS pointing value to a given atmospheric spectrum

CalibrationCalibration

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 7

MIPAS L1 radiometric MIPAS L1 radiometric calibrationcalibration

The radiometric calibration is a crucial step of the L1 processing since an error in this calibration directly translates into an error in the retrieved profiles. The radiometric calibration requires: Deep space (DS) measurements to correct the scene for self-

emission of the instrument. DS measurements are done frequently to account for variation of the instrument Temp along the orbit

Blackbody (BB) measurements followed by an equivalent number of DS measurements to calculate the radiometric gain function.

The gain function is calculated once per week, this allows to fulfill the requirement of gain accuracy (1%)

The radiometric gain G is calculated from the measured BB and DS radiances (SBB and SDS), and the theoretical BB radiance (LBB):

The measured radiance (LX) is calibrated using this gain function, the observed radiance of the scene (SX) and of the offset (Sc) closest in time

DSBB

BB

SS

LG

CalibrationCalibration

)( CXX SSGL

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 8

Weekly changes of gainWeekly changes of gain Changes in the gain function are caused mainly by changes in instrument

transmission, due to ice. The ice is somewhere in the optical path in the focal plane subsystem which is cooled to 70K

The ice is either on the edges of the entrance hole (of the focal plane subsystem) and/or on the dichroics (splitting the light to detectors) and/or the detector windows

Often the MLI (multi-layer insulator) may trap water from the air on-ground. This trapped water evaporate (outgassing) with increase of temperature and can deposit in coldest part of the instrument with formation of ice layer

Ice effectsIce effects

Ice absorbanceGain changes

Gerakines et al., Astronomy and Astrophysics 296, 810, (1995)

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 9

Gain variation in band AGain variation in band A Ice accumulates on optics with loss of signal at the detector, ice is

released after decontamination (cooler switch-off) The variation of position of ice maximum is due to variation of ice layer

thickness that can introduce other effects (e.g., ice scattering)


-20

0

20

40

60

80

100

120

140

160

Nov-01 Dec-02 Jan-04 Feb-05 Mar-06 Apr-07 Jun-08 Jul-09

Ga

in v

aria

tio

n b

and

A (

%)

750

800

850

900

950

Wa

ven

um

be

r (cm

-1)

Max gain change in band A

Spectral position of Max (cm-1)

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 10

Rate of gain variationRate of gain variation The requirement of 1% increase/week is fulfilled (dashed line) We observe an overall decrease of outgassing along the mission. We observe the very contaminated period of Jan – Jun 2005, due to the

fact that decontamination was not planned during Feb – Dec 2004


0

0.2

0.4

0.6

0 500 1000 1500 2000 2500

Days after launch

Max

ch

ang

e o

f g

ain

in

ban

d A

no

rma

lize

d b

y t

ime

(%

/ d

ays

)

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 11

Gain and NESRGain and NESR The NESR of the scene is defined as the standard deviation of the

measured single sweep spectral radiance taken over N measurements Gain and NESR variations are linearly correlated and similarly degraded

by ice contamination (loss of transmission)


EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 12

Gain and NESR variationGain and NESR variation NESR variation is linearly correlated to gain


-20

0

20

40

60

80

100

120

140

160

Nov-01 Dec-02 Jan-04 Feb-05 Mar-06 Apr-07 Jun-08 Jul-09

Re

lati

ve

va

ria

tio

n w

ith

re

sp

ec

t to

re

fere

nc

e (

%)

Max of Gain variation in band A

Max of NESR variation at 70 km in band A

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 13

Ice effects on L2 precisionIce effects on L2 precision Precision is proportional to NESR NESR varies due to ice

contamination, but it is also slightly dependent on signal higher radiances means higher NESR

Precision (random error due to noise) on VMR retrieval is inversely proportional to Temp (Planck function) Higher Temp Stronger signal Better precision

The impact of these two factors (ice and atmospheric temperature) on the time variation of L2 precision is complex (see C. Piccolo and A. Dudhia, ACP, 7, 1915–1923, 2007): In general L2 precision degrades proportionally to ice contamination In case of weak species the L2 precision is critically degraded by

increasing NESR In case of large seasonal variation of atmospheric temperature (polar

region) L2 precision is more driven by variation of temperature Furthermore ice contamination impacts directly accuracy of profiles:

An error in the gain function of 1% directly translates into a systematic error of 1% in the calibrated spectra and then in the profiles


EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 14

Ice in other ENVISAT instruments: Ice in other ENVISAT instruments: AATSR and SCIAMACHYAATSR and SCIAMACHY

Ice was also seen on other ENVISAT instruments, AATSR and SCIAMACHY

It may be that outgassing from other parts of ENVISAT lead to increased water vapor pressure around the satellite, this water vapor may reach the MIPAS detector unit

Ice effectsIce effectsSignal loss and ice deposition rate on AATSR

Courtesy of VEGA Courtesy of SOST-IFE

Signal loss on SCIAMACHY channel 8

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 15

Summary and lessons learnedSummary and lessons learned Water is trapped on-ground in some parts of the platform (e.g., MLI) and it

evaporates in flight (outgassing) forming ice around the coldest parts of the ENVISAT satellite, in particular IR (cold) sensors such as MIPAS, AATSR and SCIAMACHY IR channels

Ice formation determines loss of signal at the detector Outgassing is increasing with Temp during hottest period of the year Outgassing is decreasing along the mission since contaminants are

progressively removed from the instrument Periodic decontaminations should be performed, in order to avoid that the

decrease of signal-to-noise ratio impacts products quality The most critical part of the mission is the first year, when very strong

contamination was seen in all ENVISAT IR sensors Similar issues were also found during operations of other IR sensors in

different platform (e.g., IASI and ACE)

SummarySummary

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 16

MIPAS mission extensionMIPAS mission extension The inclination control will be switched-off starting from 2011 in order to

minimize the fuel consumption. We will loose the repeat orbit track away from the equator and a drifting Mean Local Solar Time (MLST)

Since 2011 the altitude will be lowered by 25 km and controlled, while the MLST will be left drifting until end of the mission (possibly 2014)

No showstoppers have been found for MIPAS (instrument and processing), however some care should be taken in order to avoid sun light entering the ESU/ASU

What’s nextWhat’s next

EGU 2009Vienna

19 – 24 Apr 2009



Intro

Calibration

Ice effects

Summary

What’s next

slide 17

Thank you for your attention !

AcknowledgmentM. Birk (DLR), G. Davies (VEGA), A. Dehn (Serco), A. Dudhia (Oxford

University)

Questions /

Answers

Questions /

Answers

egu 2009 vienna 19 – 24 apr 2009 ice on ir sensors: mipas case ice contamination on satellite ir...

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