• Title of article

    A reprocessing for climate of sea surface temperature from the along-track scanning radiometers: A new retrieval scheme

  • Author/Authors

    Embury، نويسنده , , Owen and Merchant، نويسنده , , Christopher J.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2012
  • Pages
    15
  • From page
    47
  • To page
    61
  • Abstract
    We present a new coefficient-based retrieval scheme for estimation of sea surface temperature (SST) from the Along Track Scanning Radiometer (ATSR) instruments. The new coefficients are banded by total column water vapour (TCWV), obtained from numerical weather prediction analyses. TCWV banding reduces simulated regional retrieval biases to < 0.1 K compared to biases ~ 0.2 K for global coefficients. Further, detailed treatment of the instrumental viewing geometry reduces simulated view-angle related biases from ~ 0.1 K down to < 0.005 K for dual-view retrievals using channels at 11 and 12 μm. A novel analysis of trade-offs related to the assumed noise level when defining coefficients is undertaken, and we conclude that adding a small nominal level of noise (0.01 K) is optimal for our purposes. pplied to ATSR observations, some inter-algorithm biases appear as TCWV-related differences in SSTs estimated from different channel combinations. The final step in coefficient determination is to adjust the offset coefficient in each TCWV band to match results from a reference algorithm. This reference uses the dual-view observations of 3.7 and 11 μm. The adjustment is independent of in situ measurements, preserving independence of the retrievals. The choice of reference is partly motivated by uncertainty in the calibration of the 12 μm of Advanced ATSR. , we model the sensitivities of the new retrievals to changes to TCWV and changes in true SST, confirming that dual-view SSTs are most appropriate for climatological applications.
  • Keywords
    ATSR , Remote sensing , sea surface temperature , climate
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2012
  • Journal title
    Remote Sensing of Environment
  • Record number

    1631398