Search

The Infrared Sounder (IRS) is an infrared Fourier transform spectrometer that will be on board the Meteosat Third Generation series of the future European Organization for the Exploitation of Meteorological Satellites geostationary satellites and will have a unique four‐dimensional look at the atmosphere. After its planned launch in 2024, it will be able to measure the radiance emitted by the Earth at the top of the atmosphere using 1,960 channels in two spectral bands between 680–1,210 cm−1$$ {}^{-1} $$ (long‐wave infrared) and 1,600–2,250 cm−1$$ {}^{-1} $$ (mid‐wave infrared) at a spectral sampling of 0.6 cm−1$$ {}^{-1} $$. It will perform measurements over the full Earth disk with high spatial and temporal resolution of 4 km at nadir and 30 min over Europe. Thus, the huge amount of data from IRS will present challenges, particularly in data transmission, data storage, and assimilation into numerical weather prediction (NWP) models. To reduce the volume of data, various methods are available, including spatial sampling, principal component analysis, and channel selection. The latter technique will be discussed in this paper by proposing general channel selection to provide NWP models. The objective of this selection is to improve essential variables for NWP such as temperature, humidity, skin temperature, and ozone. This work has required the development of a large observation database and takes into account the main developments in assimilation techniques, including the use of full observation‐error covariance matrices or the assimilation of ozone in global models, for example. This study performs a specific analysis of the sensitivity of IRS observations and proposes a first general selection of 300 channels for NWP models. This selection allows us to reduce the analysis error in the troposphere by 48% in temperature, 65% in humidity, and 17% in ozone. [ABSTRACT FROM AUTHOR]

In the framework of the EUMETSAT Polar System–Second Generation (EPS‐SG) preparation, a new generation of the Infrared Atmospheric Sounding Interferometer (IASI) instrument has been designed. The IASI‐New Generation (IASI‐NG) will measure radiances at a doubled spectral resolution compared to its predecessor and with a signal‐to‐noise ratio improved by a factor of 2. The large amount of data arising from IASI‐NG will present many challenges for data transmission, storage and assimilation. Moreover, the full set of measured radiances will not be exploitable in an operational numerical weather prediction (NWP) context. For these reasons, an appropriate IASI‐NG channel selection in needed, aiming to select the most informative channels for NWP models. Therefore, the standard iterative channel selection methodology, based on the optimal linear estimation theory and assuming spectrally correlated errors, has been applied to a set of simulated data of the IASI‐NG spectrum. The entire simulated IASI‐NG spectrum has been first investigated, while finally focusing the channel selection procedure on the most interesting wavelength ranges for the assimilation. Through this process, a total of 500 channels have been chosen to serve as a basis for future channel selections to be provided to NWP centres – 277 temperature, 23 surface‐sensitive and 200 water vapour channels. One‐dimensional variational (1D‐Var) assimilation experiments show that using this selected set of channels leads to a reduction of the standard deviation of the error in temperature (up to 30%) and water vapour (up to 50%) profiles with respect to the apriori information. [ABSTRACT FROM AUTHOR]

Nowadays, the assimilation of satellite observations, particularly radiances from infrared sounders, into numerical weather prediction (NWP) models plays a dominant role in improving weather forecasts. One of the keys to make optimal use of radiances is to simulate them with a radiative transfer model (RTM). At Météo‐France, the RTTOV RTM is used for NWP models. Currently, simulations are carried out taking into account single chemical profiles. However, neglecting the spatial and temporal variability of these gases can affect the accuracy of the simulations and thus the quality of the subsequent analyses and forecasts. To reduce the impact of this assumption on weather forecasts, we use a variational bias correction but it would be more appropriate to correct the bias directly at the source. Ozone is one of the atmospheric constituents with significant impacts on spectral radiances measured by hyperspectral infrared sounders. Thus, the objective of this paper is to replace the use of a single ozone profile with a realistic and variable ozone field in RTTOV for the simulation of infrared observation. The results show that the use of a variable ozone allows us to further reduce biases in simulation of ozone‐sensitive channels but also of channels sensitive mainly to other parameters such as CO2 for example. This has positive effects on the analyses and improves the fit of the short‐range forecasts (or analyses) to other observations such as radiosondes, microwave radiances, GNSS‐RO bending angles, etc. All of these positive impacts allow us to significantly improve weather forecasts. [ABSTRACT FROM AUTHOR]

This article focuses on the simulation and the assimilation of satellite infrared observations in convective-scale numerical weather prediction (NWP) systems. A radiative transfer model that includes profiles for liquid-water content, ice-water content and cloud fraction was used to simulate cloud-affected radiances as background equivalents. This approach avoids the use of cloud parameters (cloud-top pressure and effective cloud fraction) deduced from a CO2 slicing algorithm and the modelling of clouds by single-layer clouds. The advanced radiative transfer model was evaluated using infrared observations measured by the Infrared Atmospheric Sounding Interferometer (IASI). The observation-screening procedure that was developed to improve the selection of usable cloudy scenes led to a good agreement between observations and background equivalents. For that purpose, a radiance analysis of collocated Advanced Very High Resolution Radiometer (AVHRR) pixels inside each IASI field of view was used. The goal of this preliminary work is to assess the feasibility of adding the cloud variables (liquid and ice-water contents) to the state vector of the assimilation system. The approach is illustrated with one-dimensional variational (1D-Var) retrievals. The physical consistency of the 1D-Var adjustments is verified with real observations. Then observing-system simulation experiments (OSSE) are used to validate the 1D-Var retrievals. [ABSTRACT FROM AUTHOR]

Validation of ozone profiles measured from a nadir looking satellite instrument over Antarctica is a challenging task due to differences in their vertical sensitivity with ozonesonde measurements. In this paper, ozone observations provided by the Infrared Atmospheric Sounding Interferometer (IASI) instrument onboard the polar-orbiting satellite MetOp are compared with ozone profiles collected between August and October 2010 at McMurdo Station, Antarctica, during the Concordiasi measurement campaign. The main objective of the campaign was the satellite data validation. With this aim 20 zero-pressure sounding balloons carrying ozonesondes were launched during this period when the MetOp satellite was passing above McMurdo. This makes the dataset relevant for comparison, especially because the balloons covered the entire altitude range of IASI profiles. The validation methodology and the collocation criteria vary according to the availability of global positioning system auxiliary data with each electro-chemical cell ozonesonde observation. The relative mean difference is shown to depend on the vertical range investigated. The analysis shows a good agreement in the troposphere (below 10 km) and middle stratosphere (25-40 km), where the differences are lower than 10 %. However a significant positive bias of about 10- 26% is estimated in the lower stratosphere at 10-25 km, depending on altitude. The positive bias in the 10-25 km range is consistent with previously reported studies comparing in situ data with thermal infrared satellite measurements. This study allows for a better characterization of IASI-retrieved ozone over the polar region during ozone depletion/recovery processes. [ABSTRACT FROM AUTHOR]

The article presents a study on the intercomparison of ozone profiles in Antarctica to quantify ozone depletion or recovery. The study employed Infrared Atmospheric Sounding Interferometer (IASI) instrument, global positioning system (GPS) receiver, MetOp satellite collected at McMurdo Station, Antarctica, during the Concordiasi campaign. Results reveal that overestimation of ozone cannot be explained by the IASI to measure the high gradient because of zone depletion process.

In this study, IASI ozone‐sensitive channels have been assimilated in 1D‐Var data assimilation combined with realistic ozone background coming from a MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle) Chemistry Transport Model (CTM) as a first stage of coupling between Numerical Weather Prediction (NWP) and MOCAGE CTM at Météo‐France for global model ARPEGE (Action de Recherche Petite Echelle Grande Echelle). To evaluate the impact of ozone‐sensitive channels on analyses, databases of 161 temperatures, humidity, and ozone radiosondes across the globe during a 1‐year period have been considered. Ozone forecast from MOCAGE CTM was evaluated with radiosondes and used as input for the Radiative Transfer Model (RTM) RTTOV. Statistics of IASI observations minus simulations show that the use of ozone from MOCAGE CTM allows to better simulate IASI ozone‐sensitive channels. The Desroziers method is used to diagnose observation error covariance matrix and estimate realistic ozone observation standard errors taking into account cross‐correlations between IASI channels. The background error covariance matrix for ozone is estimated using radiosondes. A control run assimilating 123 IASI operational channels is compared to an experiment which assimilates, in addition, 15 IASI ozone‐sensitive channels. Results show potential benefits of IASI ozone‐sensitive channels combined with realistic ozone from MOCAGE CTM to improve temperature, humidity and ozone analyses simultaneously. This work is an encouraging first step for the enhancing of the coupling between the global model ARPEGE and MOCAGE CTM. Key Points: IASI ozone‐sensitive channels are also sensitive to temperature and humidityUsing a realistic ozone information input of the RTTOV RTM allows to better simulate IASI ozone‐sensitive channels radiancesA simplified framework such as the 1D‐Var data assimilation is used to prepare for an enhanced coupling between NWP and CTM [ABSTRACT FROM AUTHOR]