Abstract Climate services are largely supported by climate reanalyses and by satellite Fundamental (Climate) Data Records (F(C)DRs). This paper demonstrates how the development and the uptake of F(C)DR benefit from radiance simulations, using reanalyses and radiative transfer models. We identify three classes of applications, with examples for each application class. The first application is to validate assumptions during F(C)DR development. Hereto we show the value of applying advanced quality controls to geostationary European (Meteosat) images. We also show the value of a cloud mask to study the spatio‐temporal coherence of the impact of the Mount Pinatubo volcanic eruption between Advanced Very High Resolution Radiometer (AVHRR) and the High‐resolution Infrared Radiation Sounder (HIRS) data. The second application is to assess the coherence between reanalyses and observations. Hereto we show the capability of reanalyses to reconstruct spectra observed by the Spektrometer Interferometer (SI‐1) flown on a Soviet satellite in 1979. We also present a first attempt to estimate the random uncertainties from this instrument. Finally, we investigate how advanced bias correction can help to improve the coherence between reanalysis and Nimbus‐3 Medium‐Resolution Infrared Radiometer (MRIR) in 1969. The third application is to inform F(C)DR users about particular quality aspects. We show how simulations can help to make a better‐informed use of the corresponding F(C)DR, taking as examples the Nimbus‐7 Scanning Multichannel Microwave Radiometer (SMMR), the Meteosat Second Generation (MSG) imager, and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Water Vapor Profiler (SSM/T‐2).

Abstract. This paper describes a new gas optical depth parameterisation implemented in the most recent release, version 13, of the radiative transfer model RTTOV (Radiative Transfer for TOVS). RTTOV is a fast, one-dimensional radiative transfer model for simulating top-of-atmosphere visible, infrared, and microwave radiances observed by downward-viewing space-borne passive sensors. A key component of the model is the fast parameterisation of absorption by the various gases in the atmosphere. The existing parameterisation in RTTOV has been extended over many years to allow for additional variable gases in RTTOV simulations and to account for solar radiation and better support geostationary sensors by extending the validity to higher zenith angles. However, there are limitations inherent in the current approach which make it difficult to develop it further, for example by adding new variable gases. We describe a new parameterisation that can be applied across the whole spectrum, that allows for a wide range of zenith angles in support of solar radiation and geostationary sensors, and for which it will be easier to add new variable gases in support of user requirements. Comparisons against line-by-line radiative transfer simulations and against observations in the ECMWF operational system yield promising results, suggesting that the new parameterisation generally compares well with the old one in terms of accuracy. Further validation is planned, including testing in operational numerical weather prediction data assimilation systems.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).CORRESPONDING AUTHOR: Vinia Mattioli, vinia.mattioli@eumetsat.int

The fast radiative transfer model RTTOV offers different ice cloud models to simulate observations from hyperspectral infrared instruments such as AIRS, IASI or CrIS. Since the last RTTOV version 12 there are two ice cloud models: the first one is an ice water content and temperature parameterization of a large dataset of ice cloud optical properties coming from the Met Office, and the second one is based on the ice crystal size dependent ice cloud optical properties database provided by SSEC. In order to compare these two ice cloud models, we used collocated data from the A-Train during two weeks of global observations. The ice cloud profiles description (ice water content and effective size of ice crystals) used as inputs for RTTOV is provided by the synergetic retrieval from active sensors (CloudSat and CALIOP/CALIPSO) named the 2C-ICE product. The RTTOV top of atmosphere simulations using these ice cloud profiles are then compared with collocated infrared observations from the IIR radiometer that is onboard CALISPO and has three infrared window channels. We found that RTTOV-12 is able to reproduce observations with nearly no biases and standard deviation below 7 K in window channels. The results show also the strong impact of the knowledge of the ice crystal size that is not currently information predicted by NWP models. By using hyperspectral infrared instruments, the spectral consistency of these two ice cloud models is also preliminary discussed.

The highly accurate measurements of the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) are used in numerical weather prediction (NWP), atmospheric chemistry and climate monitoring. As the second generation of the European Polar System (EPS-SG) is being developed, a new generation of IASI instruments has been designed to fly on board the MetOp-SG constellation: IASI New Generation (IASI-NG). In order to prepare the arrival of this new instrument, and to evaluate its impact on NWP and atmospheric chemistry applications, a set of IASI and IASING simulated data was built and made available to the public to set a common framework for future impact studies. This paper describes the information available in this database and the procedure followed to run the IASI and IASI-NG simulations. These simulated data were evaluated by comparing IASI-NG to IASI observations. The result is also presented here. Additionally, preliminary impact studies of the benefit of IASI-NG compared to IASI on the retrieval of temperature and humidity in a NWP framework are also shown in the present work. With a channel dataset located in the same wave numbers for both instruments, we showed an improvement of the temperature retrievals throughout the atmosphere, with a maximum in the troposphere with IASI-NG and a lower benefit for the tropospheric humidity.

This paper revisits the data collected by early sounders Nimbus-4 IRIS (1970) and Nimbus-6 HIRS (1975), after recovery of ageing tapes by NASA GES DISC. New quality controls are proposed to screen out erroneous or suspicious mission data, based on instrument health status data records and other inspection of the data. Radiative transfer coefficients are derived for the fast computation of clear sky radiative transfer simulations. Atmospheric profiles from ERA-40 and ERA-20C reanalyses are used in input. These spatiotemporally complete datasets are interpolated to each sounding location, using the closest estimate in time. A modern cloud detection method derived for current hyperspectral sounders is applied to IRIS and yields maps of cloud cover that are in line with current knowledge of cloud climatology. For clear scenes, the standard deviation of brightness temperature differences between IRIS observations and simulations from ERA-20C is around 1 K for the lower-peaking temperature channels of the 15 mu m CO2 band, and lower than 1 K for simulations from ERA-40. The IRIS and HIRS instrumental data records are projected in a common sub-space to alleviate issues with different field-of-view resolutions and spectral resolutions. A proxy cloud detection scheme screens out clouds in the same manner in both data records. Considering the month of August, common to both missions, a detailed analysis of the departures from observations suggests that ERA-40 suffers from spurious tropospheric warming, possibly caused by changes in the observation input during the 1970s including a known error in ERA-40 radiance assimilation bias correction. This result, confirmed by considering a climate model integration, demonstrates that it is possible to exploit early sounder data records to derive detailed insight from reanalyses, such as attempting to qualify separately random and systematic errors in reanalyses, even at times when few other independent observation data are available. (C) 2018 COSPAR. Published by Elsevier Ltd.

Abstract. The aim of this paper is to present a method to retrieve nitrous oxide (N2O) vertical profiles from the Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp platform. We retrieved N2O profiles using IASI clear sky radiances in 2 spectral bands: B1 and B2 centered at ∼ 1280 cm−1 and ∼ 2220 cm−1, respectively. Both retrievals in B1 and B2 (hereafter referred to as N2O_B1 and N2O_B2, respectively) are sensitive to the mid-to-upper troposphere with a maximum of sensitivity at around 309 hPa. The degrees of freedom for N2O_B1 and N2O_B2 are 1.38 and 0.93, respectively. We validated the retrievals using the High-performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations (HIPPO). The comparisons between HIPPO and the two retrieved datasets show relatively low standard deviation errors around 1.5 % (∼ 4.8 ppbv) and 1.0 % (∼ 3.2 ppbv) for N2O_B1 and N2O_B2, respectively. However, the impact of H2O contamination on N2O_B1 due to its strong absorption bands in B1 significantly degrades the quality of the retrievals in tropical regions. We analysed the scientific consistency of the retrievals at 309 hPa with a focus on the long-range transport of N2O especially during the Asian summer monsoon. Over the mid-latitude regions, both variations of N2O_B1 and N2O_B2 at 309 hPa are influenced by the stratospheric N2O-depleted air because of the relative coarse shape of the averaging kernel. The analysis of N2O_B2 using results from backtrajectories exhibits the capacity of these retrievals to capture long-range transport of air masses from Asia to northern Africa via the summer monsoon anticyclone on a daily basis. Thus, N2O_B1 and N2O_B2 offer an unprecedented possibility to study global upper tropospheric N2O on a daily basis.

Abstract. The aim of this paper is to present a method to retrieve nitrous oxide (N2O) vertical profiles from the Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp platform. We retrieved N2O profiles using IASI clear sky radiances in 2 spectral bands: B1 and B2 centered at ∼ 1280 cm−1 and ∼ 2220 cm−1, respectively. Both retrievals in B1 and B2 (hereafter referred to as N2O_B1 and N2O_B2, respectively) are sensitive to the mid-to-upper troposphere with a maximum of sensitivity at around 309 hPa. The degrees of freedom for N2O_B1 and N2O_B2 are 1.38 and 0.93, respectively. We validated the retrievals using the High-performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations (HIPPO). The comparisons between HIPPO and the two retrieved datasets show relatively low standard deviation errors around 1.5 % (∼ 4.8 ppbv) and 1.0 % (∼ 3.2 ppbv) for N2O_B1 and N2O_B2, respectively. However, the impact of H2O contamination on N2O_B1 due to its strong absorption bands in B1 significantly degrades the quality of the retrievals in tropical regions. We analysed the scientific consistency of the retrievals at 309 hPa with a focus on the long-range transport of N2O especially during the Asian summer monsoon. Over the mid-latitude regions, both variations of N2O_B1 and N2O_B2 at 309 hPa are influenced by the stratospheric N2O-depleted air because of the relative coarse shape of the averaging kernel. The analysis of N2O_B2 using results from backtrajectories exhibits the capacity of these retrievals to capture long-range transport of air masses from Asia to northern Africa via the summer monsoon anticyclone on a daily basis. Thus, N2O_B1 and N2O_B2 offer an unprecedented possibility to study global upper tropospheric N2O on a daily basis.

A monthly mean land and snow Bidirectional Reflectance Distribution Function (BRDF) atlas for visible and near infrared parts of the spectrum has been developed for Radiative Transfer for Television Infrared Observation Satellite (TIROS) Operational Vertical sounder (TOVS) (RTTOV). The atlas follows the methodology of the RTTOV University of Wisconsin infrared land surface emissivity (UWIREMIS) atlas, i.e., it combines satellite retrievals and a principal component analysis on a dataset of hyper-spectral surface hemispherical reflectance or albedo. The current version of the BRDF atlas is based on the Collection 5 of the Moderate Resolution Imaging (MODIS) MCD43C1 Climate Modeling Grid BRDF kernel-driven model parameters product. The MCD43C1 product combines both Terra and Aqua satellites over a 16-day period of acquisition and is provided globally at 0.05° of spatial resolution. We have improved the RTTOV land surface BRDF atlas by using the last Collection 6 of MODIS product MCD43C1. We firstly found that the MODIS C6 product improved the quality index of the BRDF model as compared with that of C5. When compared with clear-sky top of atmosphere (TOA) reflectance of Spinning Enhanced Visible and InfraRed Imagers (SEVIRI) solar channels over snow-free land surfaces, we showed that the reflectances are simulated with an absolute accuracy of 3% to 5% (i.e., 0.03–0.05 in reflectance units) when either the satellite zenith angle or the solar zenith angle is below 70°, regardless of the MODIS collection. For snow-covered surfaces, we showed that the comparison with in situ snow spectral albedo is improved with C6 with an underestimation of 0.05 in the near infrared.

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.

RGB pseudo composite imagery is a robust and fast processing technique for satellite observations to provide near real-time synthesized weather information to forecasters. The technique consists of superposing three images resulting from a linear combination of multi-spectral observations and corresponding them to red, green and blue. A new algorithm for the detection of snow during daytime has recently been developed for the Suomi-NPP VIIRS instruments. The algorithm uses five VIIRS bands including that centered at 2.25μm to enhance snow detection and that centered at 1.24μm to highlight the temporal variability of the snow cover. Furthermore, this paper shows the capability of the algorithm to detect snow under thin cloud conditions. This product is already provided in near real-time to forecasters of the French national weather service, Météo-France.

Today's satellite data rescue activities uncover dormant records of our recent past and enable users to access, assess, and utilize early images and soundings for climate studies.

The Laser Megajoule (LMJ) facility located at CEA/CESTA started to operate in the early 2014 with two quadruplets (20 kJ at 351 nm) focused on target for the first experimental campaign. We present here the first set of gated x-ray imaging (GXI) diagnostics implemented on LMJ since mid-2014. This set consists of two imaging diagnostics with spatial, temporal, and broadband spectral resolution. These diagnostics will give basic measurements, during the entire life of the facility, such as position, structure, and balance of beams, but they will also be used to characterize gas filled target implosion symmetry and timing, to study x-ray radiography and hydrodynamic instabilities. The design requires a vulnerability approach, because components will operate in a harsh environment induced by neutron fluxes, gamma rays, debris, and shrapnel. Grazing incidence x-ray microscopes are fielded as far as possible away from the target to minimize potential damage and signal noise due to these sources. These imaging diagnostics incorporate microscopes with large source-to-optic distance and large size gated microchannel plate detectors. Microscopes include optics with grazing incidence mirrors, pinholes, and refractive lenses. Spatial, temporal, and spectral performances have been measured on x-ray tubes and UV lasers at CEA-DIF and at Physikalisch-Technische Bundesanstalt BESSY II synchrotron prior to be set on LMJ. GXI-1 and GXI-2 designs, metrology, and first experiments on LMJ are presented here.

A prototype of a picosecond x-ray streak camera has been developed and tested by Commissariat à l'Énergie Atomique et aux Énergies Alternatives to provide plasma-diagnostic support for the Laser Megajoule. We report on the measured performance of this streak camera, which almost fulfills the requirements: 50-μm spatial resolution over a 15-mm field in the photocathode plane, 17-ps temporal resolution in a 2-ns timebase, a detection threshold lower than 625 nJ/cm2 in the 0.05-15 keV spectral range, and a dynamic range greater than 100.

Streak cameras are widely used to record the spatio-temporal evolution of laser-induced plasma. A prototype of picosecond X-ray streak camera has been developed and tested by Commissariat à l’Énergie Atomique et aux Énergies Alternatives to answer the Laser MegaJoule specific needs. The dynamic range of this instrument is measured with picosecond X-ray pulses generated by the interaction of a laser beam and a copper target. The required value of 100 is reached only in the configurations combining the slowest sweeping speed and optimization of the streak tube electron throughput by an appropriate choice of high voltages applied to its electrodes.

A new ice cloud optical property database in the thermal infrared has been parameterized for the RTTOV radiative transfer model. The Self-Consistent Scattering Model (SCSM) database is based on an ensemble model of ice crystals and a parameterization of the particle size distribution. This convolution can predict the radiative properties of cirrus without the need of a priori information on the ice particle shape and an estimate of the ice crystal effective dimension. The ice cloud optical properties are estimated through linear parameterizations of ambient temperature and ice water content. We evaluate the new parameterization against existing parameterizations used in RTTOV. We compare infrared observations from Imaging Infrared Radiometer, on board CALIPSO, against RTTOV simulations of the observations. The simulations are performed using two different products of ice cloud profiles, retrieved from the synergy between space-based radar and lidar observations. These are the 2C-ICE and DARDAR products. We optimized the parameterization by testing different SCSM databases, derived from different shapes of the particle size distribution, and weighting the volume extinction coefficient of the ensemble model. By selecting a large global data set of ice cloud profiles of visible optical depths between 0.03 and 4, we found that the simulations, based on the optimized SCSM database parameterization, reproduces the observations with a mean bias of only 0.43K and a standard deviation of 6.85K. The optimized SCSM database parameterization can also be applied to any other radiative transfer model.

Commissariat à l'Énergie Atomique et aux Énergies Alternatives has developed the ARGOS X-ray framing camera to perform two-dimensional, high-timing resolution imaging of an imploding target on the French high-power laser facility Laser MegaJoule. The main features of this camera are: a microchannel plate gated X-ray detector, a spring-loaded CCD camera that maintains proximity focus in any orientation, and electronics packages that provide remotely-selectable high-voltages to modify the exposure-time of the camera. These components are integrated into an "air-box" that protects them from the harsh environmental conditions. A miniaturized X-ray generator is also part of the device for in situ self-testing purposes.

Nowadays, most data assimilated in numerical weather prediction come from satellite observations. However, the exploitation of satellite data is still sub-optimal with only 10 to 15% of these data assimilated operationally. Keeping in mind that about 80% of infrared data are affected by clouds, it is a priority to develop the assimilation of cloud-affected satellite data. The hyperspectral infrared sounder IASI has already contributed to the improvement of weather forecasts thanks to its far better spectral resolution and information content compared to previous instruments (Hilton et al 2011). Currently, very few cloudy observations from the hyperspectral sounder IASI are assimilated over sea. A simple approach assuming single layers of opaque clouds defined by two cloud parameters (cloud top pressure and effective cloud fraction) is often used in the operations (Pavelin et al, 2008 McNally, 2009, Guidard et al, 2011). The context of this study is the HyMeX campaign (Ducrocq, et al 2013) aiming at a better understanding of the hydrological cycle over the Mediterranean Sea. We propose to use microphysical variables (liquid water content LWC, ice water content IWC) provided by the convective scale model AROME (2.5 km) to improve the assimilation of IASI cloudy radiances. The advanced interface RTTOV-CLD (Hocking 2010), included in RTTOV, using cloud microphysical properties (LWC, IWC and cloud fraction) from the model forecast has been evaluated in a previous study (Martinet et al, 2013). The use of such radiative transfer model is necessary with the view of adding the cloud variables into the state vector of the variational assimilation system.

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.

A new ice cloud optical properties database in the thermal infrared has been parameterized for RTTOV version 11. The database combines an ensemble model of ice crystals, and a particle size distribution scheme that can predict the radiative properties of cirrus cloud without the need of a priori information on the ice particle shape and an estimate of the ice crystal effective dimension, obtained through empirical parametrization. The ice cloud optical properties (absorption and scattering coefficients and fraction of backscattering radiation) are estimated through linear parametrizations of in-cloud temperature and ice water content. We performed comparisons with infrared observations at 8.65, 10.6 and 12.05 microns (from IIR onboard CALIPSO) with RTTOV simulations in the presence of single-layer ?ice clouds by using the different RTTOV parametrizations and ice water content profiles retrieved from CLOUDSAT and CALIOP synergy (2C-ICE product). We also tested parametrizations from modified ensemble model ice cloud bulk optical property databases, based on different shapes of the particle size distribution, determined by assuming different pre-factors in the Mass-diameter law to improve the comparisons.