Itsc 12
Download
1 / 20

- PowerPoint PPT Presentation


  • 104 Views
  • Uploaded on

ITSC -12. Cloud processing in IASI context Lydie Lavanant Météo-France, Centre de Météorologie Spatiale, BP 147, 22300 Lannion Cedex France Purpose: Retrieval of cloud information and atmospheric profiles in cloudy conditions Steps : Test case description CO 2 -slicing method

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about '' - isadora


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
Itsc 12 l.jpg
ITSC-12

Cloud processing in IASI context

Lydie Lavanant

Météo-France, Centre de Météorologie Spatiale, BP 147, 22300

Lannion Cedex France

Purpose:

Retrieval of cloud information and atmospheric profiles in cloudy conditions

Steps:

  • Test case description

  • CO2-slicing method

  • Avhrr cloud description in IASI fov

  • IASI channel selection in cloudy conditions

  • Preliminary results of profile retrieval in cloudy conditions

01/03/02


Test case l.jpg
Test Case

  • Global IASI orbit simulation. Feb. 1996

    • 13000 situations with:

      • simulated IASI cloudy and noisy spectra 0.25 cm-1 (R. Rizzi model)

  • Colocated atmospheric profiles:

    • NWP analyses in T, Q, O on RTIASI levels

  • Cloud description (cover, CLWV, CIWV) on 31 NWP levels

  • Dataset provided by Eumetsat (ISSWG)


  • Co 2 slicing method l.jpg
    CO2 slicing method

    Ref: Menzel and Stewart 1983, Smith and Frey 1990

    [(Rclr – Rmeas)k / (Rclr – Rmeas)ref] – [Nek (Rclr - Rcld)k / Neref(Rclr - Rcld)ref]= fpc

    Rmeas: measured radiance

    Rclr: clear radiance computed from the colocated forecast

    Rcld: black-body radiance at the cloud level n

    k= channel from 690 cm-1 to 810 cm-1

    Ref= reference channel = 899.75 cm-1

    For each channel k: cloud pressure= pressure which minimises equation

    P_co2 = S (p_co2(k) w2(k)) / Sw2

    W = dfpc / dlnp

    Ne = (Rclr – Rmeas)ref / (Rclr - Rcld)ref

    Assumption: one thin cloud layer

    Rejections: (Rclr – Rmeas) < sqrt(2)*radiometric noise

    Ne < 0



    Slide5 l.jpg

    Method:

    Adapt RTIASI for implementing RTTOV7 cloudy routines developed by F. Chevallier and al. (2001)

    Simulate cloudy noisy IASI spectra Rmeas for all CDS situations using:

    NPW profiles (T,H2O,.., CC, CLWV, CIWV)

    radiometric noise

    Compute clear noisy radiances Rclr for the same fov using:

    RTIASI clear

    noisy NWP profiles (apply forecast errors)

    Apply CO2-slicing method




    Variation with emissivity l.jpg
    Variation with emissivity

    1 cloud layer

    RTIASI cloudy + noise

    Profile= analysis

    24 channels. resolution:5cm-1


    Variation with emissivity9 l.jpg
    Variation with emissivity

    Several cloud layers

    RTIASI cloudy + noise

    Profile= analysis


    Variation with emissivity10 l.jpg
    Variation with emissivity

    1 cloud layer

    RTIASI cloudy

    Profile=forecast


    P co2 e co2 l.jpg
    P_Co2, e_Co2

    s = 0.2 - 0.25

    1 cloud layer

    RTIASI cloudy + noise

    Profile=forecast


    Cloud top pressure l.jpg
    Cloud top pressure

    CDS dataset cloud pressure

    CO2 retrieved cloud pressure


    Avhrr cloud mask in iasi fov l.jpg
    AVHRR Cloud mask in IASI fov

    • Operational routine for HIRS fov

    • (inside AAPP)

      • Based on a threshold technique applied

      • . every AVHRR pixel in sounder fov

      • . to various combinations of channels

    • Combinations of channels depend on:

      • . geographical location of the pixel

      • . solar illumination and viewing geometry

      • Thresholds computed in-line with:

      • . constant values from experience

      • . tabulated functions defined off-line

      • through RTTOV simulations on

      • climatological data-set

        • . TWVC retrieved from colocated AMSU-A

    • Current products:

      • percentage clear AVHRR in FOV

      • surface temperature from AVHRR

      • split-window

      • black body cloud coverage inFOV

      • cloud top temperature for the black

      • body layer

      • clear/cloudy flag for each AVHRR

      • pixel

      • Next version:

      • Ts, Tcld, Cloud type for each Avhrr

      • pixel

      • -> number of clouds



    Avhrr cloud mask in iasi fov validation over europe l.jpg
    AVHRR Cloud mask in IASI fovValidation over Europe

    7007 targets of 5x5 AVHRR pixels

    Noaa12, 14, 15 for 3 years

    38 cloud types

    Mask comparison with visual analysis of satellite imagery by CMS nephanalysts

    Comparison of satellite obs. and Hirs 8 RTTOV6 Tbs using:

    * NWP profile,

    * AVHRR clear cover +Ts,

    * AVHRR black-body cloud cover +Tn


    Channels selection and retrieval in clear conditions on cds l.jpg
    Channels selection and retrieval in clear conditions on CDS

    the 300 most informative channels

    Clear situations

    nbsit= 187 (1/10)

    • Rodgers DFS selection

    • Guess error matrix = forecast

    • Use a mean profile for mid-latitude conditions


    Channels selection above the cloud l.jpg
    Channels selection above the cloud

    Select channels from the 300 most informative channels in clear conditions

    Ex: for p_cloud=850 hPa

    . uncontaminated channels above the cloud top level: about 65% channels selected

    . cloud contaminated channels with(Tbobs – Tbgucld)< 0.3K:about85% channels selected


    Profile retrieval in cloudy conditions cds dataset un contaminated channels above the cloud l.jpg
    Profile retrieval in cloudy conditions. CDS dataset un-contaminated channels above the cloud

    600 < p_cloud < 700

    Nbsit= 132 (1/3)

    700 < p_cloud < 800

    Nbsit= 146 (1/4)

    800 < p_cloud < 900

    Nbsit= 138 (1/7)

    900 < p_cloud < 1000

    Nbsit= 166 (1/5)


    Profile retrieval in cloudy conditions with cloud information as control variable l.jpg
    Profile retrieval in cloudy conditions with cloud information as control variable

    Cloud control variables: ln(p_cld), e_cld

    Cloud guess: CO2 p_cld and e_cld

    selected channels: Tbobs – Tbgucld < 0.3K

    -> more than 80% channels selected

    all P_cld > 800hPa

    1807 situations (15% of situations)

    P_cld

    before 1d_var

    forecastas background

    after

    1d_var

    with un-contaminated channels above cloud:

    1DVar in clear conditions

    e_cld

    all selected channels: 1DVar cloudy


    Slide20 l.jpg

    Summary:

    Create IASI cloudy spectra using NWP analyses (T,H2o,.., CC, CLWV, CIWV)

    Use CO2 method to determine the cloud top pressure and emissivity

    Retrieve temperature profile in cloudy condition with CO2 cloud parameters as guess

    validate on CDS dataset

    Future:

    Consolidate the results on recent NWP data (with cloud profile information on 60 levels) -> package

    add the water vapor profile

    Combine IASI, AVHRR and AMSU information

    Validate on AIRS observations

    Adapt the method to the IASI stand-alone package

    Test a cloud-clearing method (J. Joiner)