Nitric acid is a key gas for understanding the processes leading to ozone depletion in Antarctica. The Antarctica ozone hole is a cyclic phenomenon that begins in early September when the region exits the polar night and fully develops in October-November. Nitric acid is the primary constituent of stratospheric aerosol. In the Antarctic region, when the temperature gets below 195K, it condenses from the gas phase to NAT or nitric acid trihydrate (HNO3·3H2O) in the form of ice crystals. Recently, we have developed a new forward/inverse model capable of computing the top-ofatmosphere infrared spectral radiance in all-sky conditions (clear/cloudy, day/night) and surface type (land or ocean). The new forward/inverse system has been applied to IASI (infrared Atmospheric Sounder interferometer) to retrieve O3 and HNO3 simultaneously. We have analyzed data for September 2021 and 2023, and HNO3 column retrievals have been compared to those observed with the MLS (Microwave Limb Sounder) instrument to check the capability of IASI to estimate HNO3. The paper also addresses the relationship between HNO3 and O3, especially at the onset of the ozone hole in the early spring. It will be shown that ozone depletion is paralleled by a consistent diminishing of HNO3 from the gas phase.
A Cloud Identification and Classification algorithm named CIC is illustrated. CIC is a machine learning method used for the classification of far and mid infrared radiances which allows to classify spectral observations by relying on small size training sets. The code is flexible meaning that can be easily set up and can be applied to diverse infrared spectral sensors on multiple platforms. Since its definition in 2019, the CIC has been applied to many observational geometries (airborne, satellite and ground-based) and is currently adopted as the scene classificator of the end-2-end simulator of the next ESA 9th Earth Explorer, the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) which will spectrally observe the far infrared part of the spectrum with unprecedent accuracy. The algorithm has been recently improved to enhance its sensitivity to thin clouds (and also to surface features) and to increase the cloud hit rates in challenging conditions such as those characterizing the polar regions. The newly introduced metric is presented in details and the set-up procedures are discussed since they are critical for a correct application of the code. We illustrate the definition of the metric, the calibration process and the code optimization. The issues related to the definition of the reference training sets and to the classification of multiple classes are also presented.
The new σ-IASI/F2N radiative transfer model is an advancement of the σ-IASI model, introduced in 2002. It enables rapid simulations of Earth-emitted radiance and Jacobians under various sky conditions and geometries, covering the spectral range of 3-100μm. Successfully utilized in δ-IASI, the advanced Optimal Estimation tool tailored for the IASI MetOp interferometer, its extension to the Far Infrared (FIR) holds significance for the ESA Earth Explorer FORUM mission, necessitating precise cloud radiative effect treatment, crucial in regions with dense clouds and temperature gradients. The model's update, incorporating the "linear-in-T" correction, addresses these challenges, complementing the "linear-in-tau" approach. Demonstrations highlight its effectiveness in simulating cloud complexities, with the integration of the "linear-in-T" and Tang correction for the computation of cloud radiative effects. The results presented will show that the updated σ-IASI/F2N can treat the overall complexity of clouds effectively and completely, at the same time minimizing biases.
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