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Overview

Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument: H 2 O retrieval from IASI cf S5 PM2. 28 February 2014, Bremen R.Siddans (RAL),. Overview. Water vapour (column) retrievals.

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Overview

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  1. Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument:H2O retrieval from IASI cf S5 PM2. 28 February 2014, BremenR.Siddans (RAL),

  2. Overview • Water vapour (column) retrievals. • Motivation for measurements in NIR band stronger if value added to S5 SWIR measurements and IASI-NG • Previous comparison of SWIR/NIR performance indicated SWIR performance slightly better over land • Benefit of NIR+SWIR vs IASI should be sensitivity to BL • NIR has some capability also over ocean (but sensitivity to bondarly layer may not be better than IASI) • Will remain motivation for NIR H2O for consistency with long time-series of observations from GOME/SCIA/GOME-2 • Here have performed simulations with ~Eumetsat operations T,H2O,O3 scheme to test sensitivity of IASI – with view to soon adding info from S5 • Requirements: • BL column: 10% (AQ) • FT column: 20% (AQ) • Tropospheric column: 10% (AQ) • Total column: 5% (Climate NRT) or 10%

  3. Retrieval Scheme • RAL implemented version of Eumetsat scheme for new study: “Optimal Estimation Method retrievals with IASI, AMSU and MHS measurements” • The scheme is based on optimal estimation. • A subset of 139 IASI measurements are used. Noise and other instrumental artefacts filtered using principal component analysis • Masurement covariance, from comparing measurements to simulations based on colocated ECMWF analysis • The state vector represents profiles of water vapour, ozone, temperature and surface temperature. • The forward model is RTTOV version 10.2. The internal surface emissivity models in RTTOV are used. • The first guess and a priori state are via a fast linear-regression scheme which uses IASI, MHS and AMSU radiances as predictors. • A priori covariance obtained by comparing first guess profiles to ECMWF analyses. • Linear simulations performed with this scheme for the study geophysical cenarios (extended over sea by bi-linear interpolation)

  4. Summary / Next steps • The operational IASI retrieval is shown to potential provide compliant retrievals even in the boundary layer, however this likely to be partly due to reliance on prior information (in terms of vertical structures and/or absolute variability). • Priori covariance may be misleading due to use of linear regression to define prior (which also uses IASI measurements). Errors however are comparable to ECMWF forecast background. • Next steps: • Test the impact of assuming a more relaxed prior constraint on the IASI performance • Assess also the information gained with S5 NIR observations are added. • Relies on input from Bremen describing NIR sensitivity (sample input for 1 profile already provided) • Whatever the result, heritage will remain an argument for keeping this observation.

  5. H2O NIR vs SWIR NIR for April only -2.28%, σx = 8.02% • Only Concept A offers H2O which is compliant with requirements but does not add (over land) to SWIR

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