This paper focuses on the simulation of satellite infrared passive observations for their assimilation in high horizontal resolution (2.5 km) numerical weather prediction systems. In order to better represent the sensitivity of the satellite measurement to the whole atmosphere within its footprint, new observation operators are designed. They aggregate the model information contained within the satellite field of view. The different observation operators are evaluated for the simulation of Infrared Atmospheric Sounding Interferometer (IASI) and Atmospheric Infrared Sounder (AIRS) observations over a whole month. The new observation operators are found to improve the simulation of water vapor channels and to have neutral to slightly negative impact for temperature channels. For most channels, the standard deviation of the observation minus guess departures is reduced. The modifications of the simulations are substantial for water vapor channels for which the weighting functions peak at pressures greater than 340 hPa for IASI and between 340 hPa and 800 hPa for AIRS. The most important ones appear where fine-scale humidity gradients occur in dry sounded layers. The new observation operators improve the simulation of IASI and AIRS observations by filtering out these fine-scale patterns that are not detected by the instruments. With improvements in observations minus guess reaching 2 K, the new observation operators may avoid the rejection of some observations by quality control procedures during the assimilation process. Single observation assimilation experiments are then carried out using the different observation operators. They show that even large modifications in the observation simulation have almost no impact on the final analysis.