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Most radiation schemes in weather and climate models use the “correlated k distribution” (CKD) method to treat gas absorption, which approximates a broadband spectral integration by N pseudo-monochromatic calculations. Larger N means more accuracy and a wider range of gas concentrations can be simulated but at greater computational cost. Unfortunately, the tools to perform this efficiency–accuracy trade-off (e.g. to generate separate CKD models for applications such as short-range weather forecasting to climate modelling) are unavailable to the vast majority of users of radiation schemes. This paper describes the experimental protocol for the Correlated K-Distribution Model Intercomparison Project (CKDMIP), whose purpose is to use benchmark line-by-line calculations: (1) to evaluate the accuracy of existing CKD models, (2) to explore how accuracy varies with N for CKD models submitted by CKDMIP participants, (3) to understand how different choices in the way that CKD models are generated affect their accuracy for the same N, and (4) to generate freely available datasets and software facilitating the development of new gas-optics tools. The datasets consist of the high-resolution longwave and shortwave absorption spectra of nine gases for a range of atmospheric conditions, realistic and idealized. Thirty-four concentration scenarios for the well-mixed greenhouse gases are proposed to test CKD models from palaeo- to future-climate conditions. We demonstrate the strengths of the protocol in this paper by using it to evaluate the widely used Rapid Radiative Transfer Model for General Circulation Models (RRTMG).

All-sky assimilation of infrared (IR) radiances has not yet become operational at any weather forecasting centre, but it promises to bring new observations in sensitive areas and avoid the need for cloud detection. A new all-sky IR configuration gives results comparable to (and in some areas better than) clear-sky assimilation of the same data, meaning that operational implementation is now feasible. The impact of seven upper-tropospheric water vapour (WV) sounding channels from the Infrared Atmospheric Sounding Interferometer (IASI) is evaluated in both all-sky and clear-sky approaches. All-sky radiative transfer simulations (and the forecast model's cloud fields) are now sufficiently accurate that systematic errors are comparable to those of clear-sky assimilation outside of a few difficult areas such as deep convection. All-sky assimilation brings 65 % more data than clear-sky assimilation globally, with the biggest increases in midlatitude storm tracks and tropical convective areas. However, all-sky gives slightly less weight to any one observation than in the clear-sky approach. In the midlatitudes, all-sky and clear-sky assimilation have similarly beneficial impact on mid- and upper-tropospheric dynamical forecast fields. Here the addition of data in cloudy areas is offset by the slightly lower weight given to the observations. But in the tropics, all-sky assimilation is significantly more beneficial than clear-sky assimilation, with improved dynamical short-range forecasts throughout the troposphere and stratosphere.

This paper gives an update of the RTTOV (Radiative Transfer for TOVS) fast radiative transfer model, which is widely used in the satellite retrieval and data assimilation communities. RTTOV is a fast radiative transfer model for simulating top-of-atmosphere radiances from passive visible, infrared and microwave downward-viewing satellite radiometers. In addition to the forward model, it also optionally computes the tangent linear, adjoint and Jacobian matrix providing changes in radiances for profile variable perturbations assuming a linear relationship about a given atmospheric state. This makes it a useful tool for developing physical retrievals from satellite radiances, for direct radiance assimilation in NWP models, for simulating future instruments, and for training or teaching with a graphical user interface. An overview of the RTTOV model is given, highlighting the updates and increased capability of the latest versions, and it gives some examples of its current performance when compared with more accurate line-by-line radiative transfer models and a few selected observations. The improvement over the original version of the model released in 1999 is demonstrated.

Several recent studies have observed systematic differences between measurements in the 183.31 GHz water vapor line by space-borne sounders and calculations using radiative transfer models, with inputs from either radiosondes (radiosonde observations, RAOBs) or short-range forecasts by numerical weather prediction (NWP) models. This paper discusses all the relevant categories of observation-based or model-based data, quantifies their uncertainties and separates biases that could be common to all causes from those attributable to a particular cause. Reference observations from radiosondes, Global Navigation Satellite System (GNSS) receivers, differential absorption lidar (DIAL) and Raman lidar are thus overviewed. Biases arising from their calibration procedures, NWP models and data assimilation, instrument biases and radiative transfer models (both the models themselves and the underlying spectroscopy) are presented and discussed. Although presently no single process in the comparisons seems capable of explaining the observed structure of bias, recommendations are made in order to better understand the causes.

The IASI (Infrared Atmospheric Sounding Interferometer) nadir-looking thermal infrared sounder onboard MetOp-A enables the monitoring of atmospheric constituents on a global scale. This paper presents a quality assessment of IASI CO profiles retrieved by the two different retrieval algorithms SOFRID and FORLI, by an intercomparison with airborne in-situ CO profiles from the MOZAIC program for the 2008–2009 period. Lower (surface–480 hPa) and upper tropospheric partial column (480–225 hPa) comparisons as well as profile comparisons are made. The retrieval errors of the IASI products are less than 21% in the lower troposphere and less than 10% in the upper troposphere. A statistical analysis shows similar correlation coefficients for the two retrieval algorithms and smoothed MOZAIC of r ~ 0.8 and r ~ 0.7 in the lower and upper troposphere respectively. Comparison with smoothed MOZAIC data of the temporal variation of the CO profiles at the airports of Frankfurt and Windhoek demonstrates that the IASI products are able to capture the seasonal variability at these sites. At Frankfurt SOFRID (respectively FORLI) is positively biased by 10.5% (13.0%) compared to smoothed MOZAIC in the upper (lower) troposphere, and the limited sensitivity of the IASI instrument to the boundary layer when thermal contrast is low is identified. At Windhoek, the impact of the vegetation fires in Southern Africa from July to November is captured by both SOFRID and FORLI, with an overestimation of the CO background values (fire maxima) by SOFRID (FORLI) by 12.8% (10%). Profile comparisons at Frankfurt and Windhoek show that the largest discrepancies are found between the two IASI products and MOZAIC for the nighttime retrievals.

The ozone (O3) variability over south Asia during the 2008 post-monsoon season has been assessed using measurements from the MetOP-A/IASI instrument and O3 profiles retrieved with the SOftware for a Fast Retrieval of IASI Data (SOFRID). The information content study and error analyses carried out in this paper show that IASI Level 1 data can be used to retrieve tropospheric O3 columns (TOC, surface-225 hPa) and UTLS columns (225–70 hPa) with errors smaller than 20%. Validation with global radiosonde O3 profiles obtained during a period of 6 months show the excellent agreement between IASI and radiosonde for the UTLS with correlation coefficient R > 0.91 and good agreement in the troposphere with correlation coefficient R > 0.74. For both the UTLS and the troposphere Relative Standard Deviations (RSD) are lower than 23%. Comparison with in-situ measurements from the MOZAIC program around Hyderabad demonstrates that IASI is able to capture the TOC inter and intra-seasonal variability in central India. Nevertheless, the agreement is mitigated by the fact that the smoothing of the true O3 profiles by the retrieval results in a reduction of the TOC variability detected by IASI relative to the variability observed by in situ instruments. The post-monsoon temporal variability of the vertical profile of O3 around Hyderabad has been investigated with MOZAIC observations. These observations from airborne instruments show that tropospheric O3 is steadily elevated during most of the studied period with the exception of two sharp drops following the crossing of tropical storms over India. Lagrangian simulations with the FLEXPART model indicate that elevated O3 concentrations in the middle troposphere near Hyderabad are associated with the transport of UTLS air-masses that have followed the Subtropical Westerly Jet (SWJ) and subsided over northern India together with boundary layer polluted air-masses transported from the Indo-gangetic plain by the north-easterly trades. Low O3 concentrations result from the uplift and westward transport of pristine air-masses from the marine boundary layer of the Bay of Bengal by tropical storms. In order to extend the analysis of tropospheric O3 variability to the whole of south Asia, we have used IASI-SOFRID O3 data. We show that IASI O3 data around Hyderabad were able to capture the fast variability revealed by MOZAIC. Furthermore, their spatio-temporal coverage demonstrates that the behaviour of tropospheric O3 observed near Hyderabad extended over most of central and south India and part of the Bay of Bengal. This result highlights the ability of the IASI sensor to capture fast changes in chemical composition related to dramatic tropical weather conditions.

Since data from the Infrared Atmospheric Sounding Interferometer (IASI) became available in 2007, a number of papers have appeared in the literature which have reported relatively large discrepancies between IASI spectra and forward calculations in the centre of the CO2 Q-branch at 667 cm−1. In this paper we show that these discrepancies are primarily due to errors in the temperature profiles used in the forward calculations. In particular, we have used forecasts of temperature profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF) to demonstrate that, for the case study considered in this paper, these profiles are affected by systematic errors of the order of ≈10 K at the level of the stratopause. To derive the magnitude and the spatial location of the systematic errors in the temperature profile, we have carried out forward/inverse calculations for a number of clear-sky, daytime, IASI tropical soundings over the sea. The forward calculations have been performed using atmospheric state vectors which have been obtained either from the direct inversion of the IASI radiances or from space-time co-located profiles derived from radiosonde observations and from the ECMWF model. To rule out any effect due to the accuracy of the forward model, we have performed the forward calculations using two independent models. The sensitivity of the temperature biases to the variability of the CO2 profile and to spectroscopy errors has also been studied.

Retrieval products for temperature, water vapour and ozone have been obtained from spectral radiances measured by the Infrared Atmospheric Sounding Interferometer flying onboard the first European Meteorological Operational satellite. These products have been used to check the consistency of the forward model and its accuracy and the expected retrieval performance. The study has been carried out using a research-oriented forward-inverse methodology, called φ-IASI, that the authors have specifically developed for the new sounding interferometer. The performance of the forward-inversion strategy has been assessed by comparing the retrieved profiles to profiles of temperature, water vapour and ozone obtained by co-locating in space and time profiles from radiosonde observations and from the European Centre for Medium-Range Weather Forecasts analysis. Spectral residuals have also been computed and analyzed to assess the quality of the forward model. Two versions of the high-resolution transmission molecular absorption database have been used, which mostly differ for ozone absorption line parameters, line and continuum absorption of both CO2 and H2O molecules. Their performance has been assessed by inter-comparing the results, and a consistent improvement in the spectral residual has been found when using the most updated release.

IASI measurements of spectral radiances made between the 1st April 2008 and the 15th April 2008 are compared with simulations performed using the RTTOV fast radiative transfer model utilizing regression coefficients based on different line-by-line models. The comparisons are performed within the framework of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System using fields of temperature, water vapour and ozone obtained from short-range forecasts. Simulations are performed to assess the accuracy of the RTTOV computations and investigate relative differences between the line-by-line models and the quality of the spectroscopic databases on which the RTTOV coefficients are based.

A retrieval algorithm that uses a statistical strategy based on dimension reduction is proposed. The methodology and details of the implementation of the new algorithm are presented and discussed. The algorithm has been applied to high resolution spectra measured by the Infrared Atmospheric Sounding Interferometer instrument to retrieve atmospheric profiles of temperature, water vapour and ozone. The performance of the inversion strategy has been assessed by comparing the retrieved profiles to the ones obtained by co-locating in space and time profiles from the European Centre for Medium-Range Weather Forecasts analysis.

In this paper we use the total columns of nitrous oxide (N2O) as retrieved from the radiance spectra as measured by the Infrared Atmospheric Sounding Interferometer (IASI) instrument aboard the MetOp-A platform and distributed by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) during the March–May (MAM) 2008 period. Since the total column of N2O reflects concentrations in the middle troposphere, cloud-free columnar N2O measurements are used to assess transport processes in the equatorial band (10° S–10° N). We compare the measured data set with the outputs produced by the 3-D chemical-transport model MOCAGE during the period MAM 2002–2004. To reflect MAM 2008 concentrations, MOCAGE results have been scaled by a factor 1.0125 in order to represent the change in concentration of N2O since 2004. IASI N2O equatorial measurements show a maximum over Africa (4.96×10−3 kg m−2) and a minimum over South America (4.86×10−3 kg m−2) in reasonable agreement with the outputs from MOCAGE despite the fact that emissions of N2O are more intense over America than over Africa. The amplitude of the longitudinal variation of total column N2O along the equatorial band is twice as intense in the measurements (~1.6%) than as in the model calculations (~0.8%), and much greater than the IASI mean random error (0.16–0.33%). A difference between the two data sets is observed above the Western Pacific (110° E–150° E) with a marked minimum in IASI compared to MOCAGE. Recent theoretical studies (Ricaud et al., 2007 and 2009) have shown the potentially important effect of the Walker and the Hadley cells on the tropospheric distribution of N2O in producing a local maximum in N2O above Africa. Based on equatorial total columns of N2O retrieved from IASI, our results are consistent with the fact that Africa is a zone of convergence of airmasses coming from different convective regions whilst Western Pacific behaves more like a divergence zone.

BackgroundNasal provocation testing (NPT) is a reference methodology to identify the culprit allergen in patients with allergic rhinitis. Selecting the right allergen for NPT is particularly difficult in poly-sensitized patients with seasonal allergic rhinitis (SAR). Predictors of NPT outcomes may facilitate the proper use of this test or even substitute it.ObjectiveTo identify predictors of grass pollen NPT outcome from an array of clinical data, e-diary outcomes, and allergy test results in poly-sensitized pediatric patients with SAR.MethodsPoly-sensitized, SAR patients with grass pollen allergy, participating in the @IT.2020 pilot project in Rome and Pordenone (Italy), participated in a baseline (T0) visit with questionnaires, skin prick testing (SPT), and blood sampling to measure total (ImmunoCAP, TFS, Sweden) and specific IgE antibodies to grass pollen extracts and their major allergenic molecules (ESEP, Euroimmun Labordiagnostika, Germany). During the pollen season, patients filled the AllergyMonitor® e-diary app measuring their symptoms, medication intake, and allergy-related well-being via the Visual Analogue Scale (VAS). After the pollen season (T1), patients answered clinical questionnaires and underwent a nasal provocation test (NPT) with grass pollen extract.ResultsWe recruited 72 patients (age 14.3 ± 2.8 years, 46 males) sensitized to grass and/or other pollens, including olive (63; 87.5%) and pellitory (49; 68.1%). Patients positive to grass pollen NPT (61; 84.7%), compared to the negative ones, had worse VAS values in the e-diary, larger SPT wheal reactions, and higher IgE levels, as well as specific activity to timothy and Bermuda grass extracts, rPhl p 5 and nCyn d 1. A positive NPT to grass pollen was predicted by an index combining the specific activity of IgE towards Phl p 5 and Cyn d 1 (AUC: 0.82; p

Abstract Digital health is an umbrella term which encompasses eHealth and benefits from areas such as advanced computer sciences. eHealth includes mHealth apps, which offer the potential to redesign aspects of healthcare delivery. The capacity of apps to collect large amounts of longitudinal, real‐time, real‐world data enables the progression of biomedical knowledge. Apps for rhinitis and rhinosinusitis were searched for in the Google Play and Apple App stores, via an automatic market research tool recently developed using JavaScript. Over 1500 apps for allergic rhinitis and rhinosinusitis were identified, some dealing with multimorbidity. However, only six apps for rhinitis (AirRater, AllergyMonitor, AllerSearch, Husteblume, MASK‐air and Pollen App) and one for rhinosinusitis (Galenus Health) have so far published results in the scientific literature. These apps were reviewed for their validation, discovery of novel allergy phenotypes, optimisation of identifying the pollen season, novel approaches in diagnosis and management (pharmacotherapy and allergen immunotherapy) as well as adherence to treatment. Published evidence demonstrates the potential of mobile health apps to advance in the characterisation, diagnosis and management of rhinitis and rhinosinusitis patients.

Abstract Background In all societies, the burden and cost of allergic and chronic respiratory diseases are increasing rapidly. Most economies are struggling to deliver modern health care effectively. There is a need to support the transformation of the health care system into integrated care with organizational health literacy. Main body As an example for chronic disease care, MASK (Mobile Airways Sentinel NetworK), a new project of the ARIA (Allergic Rhinitis and its Impact on Asthma) initiative, and POLLAR (Impact of Air POLLution on Asthma and Rhinitis, EIT Health), in collaboration with professional and patient organizations in the field of allergy and airway diseases, are proposing real-life ICPs centred around the patient with rhinitis, and using mHealth to monitor environmental exposure. Three aspects of care pathways are being developed: (i) Patient participation, health literacy and self-care through technology-assisted “patient activation”, (ii) Implementation of care pathways by pharmacists and (iii) Next-generation guidelines assessing the recommendations of GRADE guidelines in rhinitis and asthma using real-world evidence (RWE) obtained through mobile technology. The EU and global political agendas are of great importance in supporting the digital transformation of health and care, and MASK has been recognized by DG Santé as a Good Practice in the field of digitally-enabled, integrated, person-centred care. Conclusion In 20 years, ARIA has considerably evolved from the first multimorbidity guideline in respiratory diseases to the digital transformation of health and care with a strong political involvement.