A new Infrared Atmospheric Sounding Interferometer channel selection and assessment of its impact on Met Office NWP forecasts

Abstract

A new set of Infrared Atmospheric Sounding Interferometer (IASI) channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis (1D-Var) for the Unified Model (UM) data assimilation system at the Met Office, using the channel score index (CSI) as a figure of merit. Then, 200 channels were selected in order by counting each individual channel's CSI contribution. Compared with the operationally used 183 channels for the UM at the Met Office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach. Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum.In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.

The evaluation of FY4A's Geostationary Interferometric Infrared Sounder (GIIRS) long‐wave temperature sounding channels using the GRAPES global 4D‐Var

“…Obviously, the PDF of the differences between observations and simulations is closer to the unbiased Gaussian distribution after bias correction, which satisfies the assumption of variational assimilation. Equivalent channels 6, 27 and 87 are commonly selected and used in NWP variational assimilation systems in most weather centres (Collard, ; Eresmaa et al ., ; Noh et al ., ).…”

Assimilation of FY-3D and FY-3E Hyperspectral Infrared Atmospheric Sounding Observation and Its Impact on Numerical Weather Prediction during Spring Season over the Continental United States

“…Observations from hyperspectral infrared sounders, e.g., the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI) and the Crosstrack Infrared Sounder (CrIS), can improve the accuracy of numerical weather prediction (NWP) in both global and regional scales. Studies have proved that this improvement derives from the decrease of the initial condition's systematic and random error, benefiting from the assimilation of hyperspectral infrared sounding data [1][2][3][4][5][6][7][8][9][10]. Observing simulated system experiments (OSSE) also illustrates that observations from more-advanced hyperspectral infrared sounders, e.g., IASI New Generation (IASI-NG), can be more influential if they are assimilated in NWP systems [11].…”

An Infrared Atmospheric Sounding Interferometer – New Generation (IASI‐NG) channel selection for numerical weather prediction

“…Several channel selection methods have been developed in the last two decades. Some of them are based on statistical analysis and information content theory (Rabier et al ., 2002; Fourrié and Thépaut 2003; Collard 2007; Ventress and Dudhia 2014; Noh et al ., 2017). Some others rely on evaluating the radiances' response to the perturbation of specific chemical species and atmospheric variables, which allows the detection of spectral sensitivity features (Susskind et al ., 2003; Gambacorta and Barnet 2012).…”