ECMWF/EUMETSAT NWP-SAF Satellite data assimilation Training Course 1 to 4 July 2013

ECMWF/EUMETSAT NWP-SAF Satellite data assimilation Training Course The infrared spectrum, measurement, modelling and information content ECMWF/EUMETSAT NWP-SAF Satellite data assimilation Training Course

Sensors

High Spectral Resolution IR sounders on Polar Spacecraft (GEO covered in winds lecture)

What do we mean by high spectral resolution ?

Why is high spectral resolution important ? HIRS 19 channels IASI 8461 HIRS IASI

AIRS IASI CrIS 15 um 6 um 4 um

IASI v CrIS

(CrIS) Infrared Atmospheric Sounding Interferometer (IASI) Cross-track Infrared Sounder (CrIS) Infrared Atmospheric Sounding Interferometer (IASI)

IASI has higher spectral resolution compared to CrIS

IASI has higher instrument noise compared to CrIS

CrIS has stronger inter-channel correlations than IASI Observation error (K) Observation error (K) IASI CrIS Inter-channel correlation Inter-channel correlation

The assimilation of IASI Case study: The assimilation of IASI

The assimilation of IASI results in a significant reduction of forecast error NH EU SH US

(and what do we assimilate) What does IASI measure (and what do we assimilate)

The infrared spectrum of atmospheric radiation

The infrared spectrum of atmospheric radiation The long-wave temperature sounding band 9.6 um 3.7 um 15 um 6.4 um 4.2um ~ 200 channels assimilated

Zoom of long-wave temperature sounding channel usage for IASI

The infrared spectrum of atmospheric radiation The long-wave ozone sounding band 9.6 um 3.7 um 15 um 6.4 um 4.2um ~ 20 channels assimilated

The infrared spectrum of atmospheric radiation The long-wave water vapour sounding band 9.6 um 3.7 um 15 um 6.4 um 4.2um ~ 10 channels assimilated

The infrared spectrum of atmospheric radiation The short-wave temperature sounding band 9.6 um 3.7 um 15 um 6.4 um 4.2um ~ 0 channels assimilated – IASI noise high

The infrared spectrum of atmospheric radiation The surface sensing channels (window channels) 9.6 um 3.7 um 15 um 6.4 um 4.2um channels mostly used for cloud detection

Issues specific to IR Ambiguity Nonlinearity Clouds Channel selection (PC)

Ambiguity in infrared radiance observations

When the absorbing gas is itself a variable

AMBIGUITY BETWEEN GEOPHYSICAL VARIABLES When the primary absorber in a sounding channel is a well mixed gas (e.g. oxygen) the radiance essentially gives information about variations in the atmospheric temperature profile only. When the primary absorber is not well mixed (e.g. water vapour, ozone or CO2) the radiance gives ambiguous information about the temperature profile and the absorber distribution. This ambiguity must be resolved by : differential channel sensitivity synergistic use of well mixed channels (constraining the temperature) the background error covariance (+ physical constraints)

When sounding channels are sensitive to the surface

Atmospheric sounding channels …selecting channels where there is no contribution from the surface…. Surface reflection/ scattering Surface emission Cloud/rain contribution + + + + ...

Surface sensing Channels (passive) …selecting channels where there is no contribution from the atmosphere…. Surface reflection/ scattering Surface emission Cloud/rain contribution + + + + ... Screen data to remove clouds / rain

BUT … AMBIGUITY WITH SURFACE AND CLOUDS By placing sounding channels in parts of the spectrum where the absorption is weak we obtain temperature (and humidity) information from the lower troposphere (low peaking weighting functions). BUT … These channels (obviously) become more sensitive to surface emission and the effects of cloud and precipitation. In most cases surface or cloud contributions will dominate the atmospheric signal in these channels and it is difficult to use the radiance data safely (i.e. we may alias a cloud signal as a temperature adjustment) K(z)

Practical session

Metview web pages: https://software.ecmwf.int/metview Download (Open Source) Documentation and tutorials available Metview articles in recent ECMWF newsletters email: Metview: metview@ecmwf.int -Several tutorials available: metview, odb, ogc, macro,… Copyright ECMWF 2010

RTTOV Radiative Transfer Model Y radiances X (z)

Task 1: Overlay Tropical and Polar IASI spectra View the map of TCWV (visualise PLOT_TCWV) Select a Tropical profile ( edit / save profile extractor) Select a Polar profile ( edit / save profile extractor) Edit / visualise IASI SPECTRUM (with tropical.nc) Edit / drop IASI SPECTRUM (with polar.nc)

Task 1: Overlay Tropical and Polar IASI spectra

Task 2: Overlay Tropical and Polar IASI channel 272 weighting function Edit / visualise IASI JACOBIAN (with tropical.nc) Edit / drop IASI JACOBIAN (with polar.nc) Change channels and do similar ?

Task 3: Tropical and Polar IASI weighting functions

Task 3: Overlay Tropical and Polar IASI matrix of jacobians Edit / visualise IASI MATRIX JAC (with tropical.nc) Edit / drop IASI MATRIX JAC (with polar.nc)

Task 3: Overlay Tropical and Polar IASI matrix of jacobians

End… Questions ?