Ice contamination on satellite ir sensors the mipas case
Sponsored Links
This presentation is the property of its rightful owner.
1 / 17

Ice contamination on satellite IR sensors: the MIPAS case PowerPoint PPT Presentation

  • Uploaded on
  • Presentation posted in: General

Ice contamination on satellite IR sensors: the MIPAS case. F. Niro (1) , T. Fehr (2) , A. Kleinert (3) , H. Laur (2) , P. Lecomte (2) and G. Perron (4) (1) Serco S.p.A ., Via Sciadonna , 24, 00044 Frascati , Italy

Download Presentation

Ice contamination on satellite IR sensors: the MIPAS case

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

Ice contamination on satellite IR sensors: the MIPAS case

F. Niro(1), T. Fehr(2), A. Kleinert(3), H. Laur(2), P. Lecomte(2) and G. Perron(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, InstitutfürMeteorologie und Klimaforschung (IMK), P.O. Box 3640, 76021 Karlsruhe, Germany

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


  • 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



  • 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


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

Increase of vertical sampling

“Optimized 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


MIPAS 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 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


MIPAS L1 radiometric calibration

  • 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


Weekly 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 effects

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

Gain changes

Ice absorbance

Gain 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)

Ice effects

Rate 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

Ice effects

Gain 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)

Ice effects

Gain and NESR variation

  • NESR variation is linearly correlated to gain

Ice effects

Ice 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

Ice effects

Ice in other ENVISAT instruments: AATSR 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 effects

Signal loss and ice deposition rate on AATSR

Signal loss on SCIAMACHY channel 8

Courtesy of SOST-IFE

Courtesy of VEGA

Summary 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)


MIPAS 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 next

Thank you for your attention !


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




  • Login