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The top-of-atmosphere (TOA) radiative fluxes are critical components to advancing our understanding of the Earth's radiative energy balance, radiative effects of clouds and aerosols, and climate feedback. The Clouds and the Earth's Radiant Energy System (CERES) instruments provide broadband shortwave and longwave radiance measurements. These radiances are converted to fluxes by using scene-type-dependent angular distribution models (ADMs). This paper describes the next-generation ADMs that are developed for Terra and Aqua using all available CERES rotating azimuth plane radiance measurements. Coincident cloud and aerosol retrievals, and radiance measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from Goddard Earth Observing System (GEOS) data assimilation version 5.4.1 are used to define scene type. CERES radiance measurements are stratified by scene type and by other parameters that are important for determining the anisotropy of the given scene type. Anisotropic factors are then defined either for discrete intervals of relevant parameters or as a continuous functions of combined parameters, depending on the scene type. Significant differences between the ADMs described in this paper and the existing ADMs are over clear-sky scene types and polar scene types. Over clear ocean, we developed a set of shortwave (SW) ADMs that explicitly account for aerosols. Over clear land, the SW ADMs are developed for every 1° latitude×1° longitude region for every calendar month using a kernel-based bidirectional reflectance model. Over clear Antarctic scenes, SW ADMs are developed by accounting the effects of sastrugi on anisotropy. Over sea ice, a sea-ice brightness index is used to classify the scene type. Under cloudy conditions over all surface types, the longwave (LW) and window (WN) ADMs are developed by combining surface and cloud-top temperature, surface and cloud emissivity, cloud fraction, and precipitable water. Compared to the existing ADMs, the new ADMs change the monthly mean instantaneous fluxes by up to 5Wm–2 on a regional scale of 1° latitude×1° longitude, but the flux changes are less than 0.5Wm–2 on a global scale. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present the Monte Carlo code McRALI that provides simulations under multiple-scattering regimes of polarized high-spectral-resolution (HSR) lidar and Doppler radar observations for a three-dimensional (3D) cloudy atmosphere. The effects of nonuniform beam filling (NUBF) on HSR lidar and Doppler radar signals related to the EarthCARE mission are investigated with the help of an academic 3D box cloud characterized by a single isolated jump in cloud optical depth, assuming vertically constant wind velocity. Regarding Doppler radar signals, it is confirmed that NUBF induces a severe bias in velocity estimates. The correlation of the NUBF bias of Doppler velocity with the horizontal gradient of reflectivity shows a correlation coefficient value around 0.15 m s -1 (dBZ km -1)-1 , close to that given in the scientific literature. Regarding HSR lidar signals, we confirm that multiple-scattering processes are not negligible. We show that NUBF effects on molecular, particulate, and total attenuated backscatter are mainly due to unresolved variability of cloud inside the receiver field of view and, to a lesser extent, to the horizontal photon transport. This finding gives some insight into the reliability of lidar signal modeling using independent column approximation (ICA). [ABSTRACT FROM AUTHOR]

Particle depolarization ratio retrieved from lidar measurements are commonly used for aerosol-typing studies, microphysical inversion, or mass concentration retrievals. The particle depolarization ratio is one of the primary parameters that can differentiate several major aerosol components but only if the measurements are accurate enough. The accuracy related to the retrieval of particle depolarization ratios is the driving factor for assessing and improving the uncertainties of the depolarization products. This paper presents different depolarization calibration procedures used to improve the quality of the depolarization data. The results illustrate a significant improvement of the depolarization lidar products for all the selected lidar stations that have implemented depolarization calibration procedures. The calibrated volume and particle depolarization profiles at 532 nm show values that fall within a range that is generally accepted in the literature. [ABSTRACT FROM AUTHOR]

The unambiguous retrieval of cloud phase from polarimetric lidar observations is dependent on the assumption that only cloud scattering processes affect polarization measurements. A systematic bias of the traditional lidar depolarization ratio can occur due to a lidar system's inability to accurately measure the entire backscattered signal dynamic range, and these biases are not always identifiable in traditional polarimetric lidar systems. This results in a misidentification of liquid water in clouds as ice, which has broad implications on evaluating surface energy budgets. The Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland employs multiple planes of linear polarization, and photon counting and analog detection schemes, to self evaluate, correct, and optimize signal combinations to improve cloud classification. Using novel measurements of diattenuation that are sensitive to both horizontally oriented ice crystals and counting system nonlinear effects, unambiguous measurements are possible by over constraining polarization measurements. This overdetermined capability for cloud-phase determination allows for system errors to be identified and quantified in terms of their impact on cloud properties. It is shown that lidar system dynamic range effects can cause errors in cloud-phase fractional occurrence estimates on the order of 30% causing errors in attribution of cloud radiative effects on the order of 10-30 %. This paper presents a method to identify and remove lidar system effects from atmospheric polarization measurements and uses colocated sensors at Summit to evaluate this method. Enhanced measurements are achieved in this work with non-orthogonal polarization retrievals as well as analog and photon counting detection facilitating a more complete attribution of radiative effects linked to cloud properties. [ABSTRACT FROM AUTHOR]

Aerosol particles are important and highly variable components of the terrestrial atmosphere, and they affect both air quality and climate. In order to evaluate their multiple impacts, the most important requirement is to precisely measure their characteristics. Remote sensing technologies such as lidar (light detection and ranging) and sun/sky photometers are powerful tools for determining aerosol optical and microphysical properties. In our work, we applied several methods to joint or separate lidar and sun/sky-photometer data to retrieve aerosol properties. The Raman technique and inversion with regularization use only lidar data. The LIRIC (LIdar-Radiometer Inversion Code) and recently developed GARRLiC (Generalized Aerosol Retrieval from Radiometer and Lidar Combined data) inversion methods use joint lidar and sun/sky-photometer data. This paper presents a comparison and discussion of aerosol optical properties (extinction coefficient profiles and lidar ratios) and microphysical properties (volume concentrations, complex refractive index values, and effective radius values) retrieved using the aforementioned methods. The comparison showed inconsistencies in the retrieved lidar ratios. However, other aerosol properties were found to be generally in close agreement with the AERONET (AErosol RObotic NETwork) products. In future studies, more cases should be analysed in order to clearly define the peculiarities in our results. [ABSTRACT FROM AUTHOR]

Estimates of top-of-the-atmosphere (TOA) radiative flux are essential for the understanding of Earth's energy budget and climate system. Clouds, aerosols, water vapor, and ozone (O3) are among the most important atmospheric agents impacting the Earth's shortwave (SW) radiation budget. There are several sensors in orbit that provide independent information related to these parameters. Having coincident information from these sensors is important for understanding their potential contributions. The A-train constellation of satellites provides a unique opportunity to analyze data from several of these sensors. In this paper, retrievals of cloud/aerosol parameters and total column ozone (TCO) from the Aura Ozone Monitoring Instrument (OMI) have been collocated with the Aqua Clouds and Earth's Radiant Energy System (CERES) estimates of total reflected TOA outgoing SW flux (SWF). We use these data to develop a variety of neural networks that estimate TOA SWF globally over ocean and land using only OMI data and other ancillary information as inputs and CERES TOA SWF as the output for training purposes. OMI-estimated TOA SWF from the trained neural networks reproduces independent CERES data with high fidelity. The global mean daily TOA SWF calculated from OMI is consistently within ±1 % of CERES throughout the year 2007. Application of our neural network method to other sensors that provide similar retrieved parameters, both past and future, can produce similar estimates TOA SWF. For example, the well-calibrated Total Ozone Mapping Spectrometer (TOMS) series could provide estimates of TOA SWF dating back to late 1978. [ABSTRACT FROM AUTHOR]

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an airborne infrared limb imager combining a two-dimensional infrared detector with a Fourier transform spectrometer. It was operated aboard the new German Gulfstream G550 High Altitude LOng Range (HALO) research aircraft during the Transport And Composition in the upper Troposphere/lowermost Stratosphere (TACTS) and Earth System Model Validation (ESMVAL) campaigns in summer 2012. This paper describes the retrieval of temperature and trace gas (H2O, O3, HNO3) volume mixing ratios from GLORIA dynamics mode spectra that are spectrally sampled every 0.625 cm-1. A total of 26 integrated spectral windows are employed in a joint fit to retrieve seven targets using consecutively a fast and an accurate tabulated radiative transfer model. Typical diagnostic quantities are provided including effects of uncertainties in the calibration and horizontal resolution along the line of sight. Simultaneous in situ observations by the Basic Halo Measurement and Sensor System (BAHAMAS), the Fast In-situ Stratospheric Hygrometer (FISH), an ozone detector named Fairo, and the Atmospheric chemical Ionization Mass Spectrometer (AIMS) allow a validation of retrieved values for three flights in the upper troposphere/lowermost stratosphere region spanning polar and sub-tropical latitudes. A high correlation is achieved between the remote sensing and the in situ trace gas data, and discrepancies can to a large extent be attributed to differences in the probed air masses caused by different sampling characteristics of the instruments. This 1-D processing of GLORIA dynamics mode spectra provides the basis for future tomographic inversions from circular and linear flight paths to better understand selected dynamical processes of the upper troposphere and lowermost stratosphere. [ABSTRACT FROM AUTHOR]

The upper troposphere/lower stratosphere (UTLS) represents an important part of the climate system. Even small changes in the composition and dynamic structure of this region have significant radiative effects. Quantifying the underlying physical and chemical processes therefore represents a crucial task. Currently, there is a lack of UTLS observations with sufficient three-dimensional resolution. The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) aircraft instrument addresses this observational lack by providing observations of numerous trace constituents as well as temperature and cloud structures with an unprecedented combination of vertical resolution (up to 300 m) and horizontal resolution (about 30km×30km). As a result, important scientific questions concerning stratosphere-troposphere exchange, the occurrence of subvisible cirrus clouds in the lowermost stratosphere (LMS), polar chemistry, and gravity wave processes can be addressed, as reviewed in this paper. [ABSTRACT FROM AUTHOR]

The complete data fusion (CDF) method is applied to ozone profiles obtained from simulated measurements in the ultraviolet and in the thermal infrared in the framework of the Sentinel 4 mission of the Copernicus programme. We observe that the quality of the fused products is degraded when the fusing profiles are either retrieved on different vertical grids or referred to different true profiles. To address this shortcoming, a generalization of the complete data fusion method, which takes into account interpolation and coincidence errors, is presented. This upgrade overcomes the encountered problems and provides products of good quality when the fusing profiles are both retrieved on different vertical grids and referred to different true profiles. The impact of the interpolation and coincidence errors on number of degrees of freedom and errors of the fused profile is also analysed. The approach developed here to account for the interpolation and coincidence errors can also be followed to include other error components, such as forward model errors. [ABSTRACT FROM AUTHOR]

Linear depolarization measurement capabilities were added to the CANDAC Rayleigh-Mie-Raman lidar (CRL) at Eureka, Nunavut, in the Canadian High Arctic in 2010. This upgrade enables measurements of the phases (liquid versus ice) of cold and mixed-phase clouds throughout the year, including during polar night. Depolarization measurements were calibrated according to existing methods using parallel- and perpendicular-polarized profiles as discussed in McCullough et al. (2017). We present a new technique that uses the polarization-independent Rayleigh elastic channel in combination with one of the new polarizationdependent channels, and we show that for a lidar with low signal in one of the polarization-dependent channels this method is superior to the traditional method. The optimal procedure for CRL is to determine the depolarization parameter using the traditional method at low resolution (from parallel and perpendicular signals) and then to use this value to calibrate the high-resolution new measurements (from parallel and polarization-independent Rayleigh elastic signals). Due to its use of two high-signal-rate channels, the new method has lower statistical uncertainty and thus gives depolarization parameter values at higher spatial-temporal resolution by up to a factor of 20 for CRL. This method is easily adaptable to other lidar systems which are considering adding depolarization capability to existing hardware. [ABSTRACT FROM AUTHOR]

The number concentration of cloud condensation nuclei (CCN) plays a fundamental role in cloud physics. Instrumentations of direct measurements of CCN number concentration (NCCN) based on chamber technology are complex and costly; thus a simple way for measuring NCCN is needed. In this study, a new method for NCCN calculation based on measurements of a three-wavelength humidified nephelometer system is proposed. A three-wavelength humidified nephelometer system can measure the aerosol light-scattering coefficient (σsp) at three wavelengths and the light-scattering enhancement factor (fRH). The Ångström exponent (Å) inferred from σsp at three wavelengths provides information on mean predominate aerosol size, and hygroscopicity parameter (κ) can be calculated from the combination of fRH and Å. Given this, a lookup table that includes σsp, κ and Å is established to predict NCCN. Due to the precondition for the application, this new method is not suitable for externally mixed particles, large particles (e.g., dust and sea salt) or fresh aerosol particles. This method is validated with direct measurements of NCCN using a CCN counter on the North China Plain. Results show that relative deviations between calculated NCCN and measured NCCN are within 30 % and confirm the robustness of this method. This method enables simplerNCCN measurements because the humidified nephelometer system is easily operated and stable. Compared with the method using a CCN counter, another advantage of this newly proposed method is that it can obtain NCCN at lower supersaturations in the ambient atmosphere. [ABSTRACT FROM AUTHOR]

Accurate gas velocity measurements in emission plumes are highly desirable for various atmospheric remote sensing applications. The imaging technique of UV SO2 cameras is commonly used to monitor SO2 emissions from volcanoes and anthropogenic sources (e.g. power plants, ships). The camera systems capture the emission plumes at high spatial and temporal resolution. This allows the gas velocities in the plume to be retrieved directly from the images. The latter can be measured at a pixel level using optical flow (OF) algorithms. This is particularly advantageous under turbulent plume conditions. However, OF algorithms intrinsically rely on contrast in the images and often fail to detect motion in low-contrast image areas. We present a new method to identify ill-constrained OF motion vectors and replace them using the local average velocity vector. The latter is derived based on histograms of the retrieved OF motion fields. The new method is applied to two example data sets recorded at Mt Etna (Italy) and Guallatiri (Chile). We show that in many cases, the uncorrected OF yields significantly underestimated SO2 emission rates. We further show that our proposed correction can account for this and that it significantly improves the reliability of optical-flow-based gas velocity retrievals. In the case of Mt Etna, the SO2 emissions of the north-eastern crater are investigated. The corrected SO2 emission rates range between 4.8 and 10.7 kg s-1 (average of 7.1 ± 1.3 kg s-1) and are in good agreement with previously reported values. For the Guallatiri data, the emissions of the central crater and a fumarolic field are investigated. The retrieved SO2 emission rates are between 0.5 and 2.9 kg s-1 (average of 1.3 ± 0.5 kg s-1) and provide the first report of SO2 emissions from this remotely located and inaccessible volcano. [ABSTRACT FROM AUTHOR]

This study assesses the potential of 2 to 10 km resolution imagery of CO2 concentrations retrieved from the shortwave infrared measurements of a space-borne passive spectrometer for monitoring the spatially integrated emissions from the Paris area. Such imagery could be provided by missions similar to CarbonSat, which was studied as a candidate Earth Explorer 8 mission by the European Space Agency (ESA). This assessment is based on observing system simulation experiments (OSSEs) with an atmospheric inversion approach at city scale. The inversion system solves for hourly city CO2 emissions and natural fluxes, or for these fluxes per main anthropogenic sector or ecosystem, during the 6 h before a given satellite overpass. These 6 h correspond to the period during which emissions produce CO2 plumes that can be identified on the image from this overpass. The statistical framework of the inversion accounts for the existence of some prior knowledge with 50% uncertainty on the hourly or sectorial emissions, and with ~25% uncertainty on the 6 h mean emissions, from an inventory based on energy use and carbon fuel consumption statistics. The link between the hourly or sectorial emissions and the vertically integrated column of CO2 observed by the satellite is simulated using a coupled flux and atmospheric transport model. This coupled model is built with the information on the spatial and temporal distribution of emissions from the emission inventory produced by the local air-quality agency (Airparif) and a 2 km horizontal resolution atmospheric transport model. Tests are conducted for different realistic simulations of the spatial coverage, resolution, precision and accuracy of the imagery from sun-synchronous polar-orbiting missions, corresponding to the specifications of CarbonSat and Sentinel- 5 or extrapolated from these specifications. First, OSSEs are conducted with a rather optimistic configuration in which the inversion system is perfectly informed about the statistics of the limited number of error sources. These OSSEs indicate that the image resolution has to be finer than 4 km to decrease the uncertainty in the 6 h mean emissions by more than 50 %. More complex experiments assess the impact of more realistic error estimates that current inversion methods do not properly account for, in particular, the systematic measurement errors with spatially correlated patterns. These experiments highlight the difficulty to improve current knowledge on CO2 emissions for urban areas like Paris with CO2 observations from satellites, and call for more technological innovations in the remote sensing of vertically integrated columns of CO2 and in the inversion systems that exploit it. [ABSTRACT FROM AUTHOR]

As aerosol amount and type are key factors in the "atmospheric correction" required for remote-sensing chlorophyll a concentration (Chl) retrievals, the Multi-angle Imaging Spectro Radiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chlin situ < 1.5 mgm..3, the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-meansquare error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov- Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p > 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl < 1.5 mgm-3, MISR and MODIS show very good agreement: r D 0:96, MAED0.09, and RMSED0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo. [ABSTRACT FROM AUTHOR]

The SKYLIDAR algorithm was developed to estimate vertical profiles of aerosol optical properties from sky radiometer (SKYNET) and lidar (AD-Net) measurements. The solar heating rate was also estimated from the SKYLIDAR retrievals. The algorithm consists of two retrieval steps: (1) columnar properties are retrieved from the sky radiometer measurements and the vertically mean depolarization ratio obtained from the lidar measurements and (2) vertical profiles are retrieved from the lidar measurements and the results of the first step. The derived parameters are the vertical profiles of the size distribution, refractive index (real and imaginary parts), extinction coefficient, single-scattering albedo, and asymmetry factor. Sensitivity tests were conducted by applying the SKYLIDAR algorithm to the simulated sky radiometer and lidar data for vertical profiles of three different aerosols, continental average, transported dust, and pollution aerosols. The vertical profiles of the size distribution, extinction coefficient, and asymmetry factor were well estimated in all cases. The vertical profiles of the refractive index and single-scattering albedo of transported dust, but not those of transported pollution aerosol, were well estimated. To demonstrate the performance and validity of the SKYLIDAR algorithm, we applied the SKYLIDAR algorithm to the actual measurements at Tsukuba, Japan. The detailed vertical structures of the aerosol optical properties and solar heating rate of transported dust and smoke were investigated. Examination of the relationship between the solar heating rate and the aerosol optical properties showed that the vertical profile of the asymmetry factor played an important role in creating vertical variation in the solar heating rate. We then compared the columnar optical properties retrieved with the SKYLIDAR algorithm to those produced with the more established scheme SKYRAD.PACK, and the surface solar irradiance calculated from the SKYLIDAR retrievals was compared with pyranometer measurement. The results showed good agreements: the columnar values of the SKYLIDAR retrievals agreed with reliable SKYRAD.PACK retrievals, and the SKYLIDAR retrievals were sufficiently accurate to evaluate the surface solar irradiance. [ABSTRACT FROM AUTHOR]

Radio occultation (RO) measurements are sensitive to the small-scale irregularities in the atmosphere. In this study, we present a new technique to estimate tropospheric turbulence strength (namely, scintillation index) by analyzing RO amplitude fluctuations in impact parameter domain. GPS RO observations from the COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) satellites enabled us to calculate global maps of scintillation measures, revealing the seasonal, latitudinal, and longitudinal characteristics of the turbulent troposphere. Such information are both difficult and expensive to obtain especially over the oceans. To verify our approach, simulation experiments using the multiple phase screen (MPS) method were conducted. The results show that scintillation indices inferred from the MPS simulations are in good agreement with scintillation measures estimated from COSMIC observations. [ABSTRACT FROM AUTHOR]

Clouds are one of the main reasons of uncertainties in the forecasts of weather and climate. In part, this is due to limitations of remote sensing of cloud microphysics. Present approaches often use passive spectral measurements for the remote sensing of cloud microphysical parameters. Large uncertainties are introduced by three-dimensional (3-D) radiative transfer effects and cloud inhomogeneities. Such effects are largely caused by unknown orientation of cloud sides or by shadowed areas on the cloud. Passive ground-based remote sensing of cloud properties at high spatial resolution could be crucially improved with this kind of additional knowledge of cloud geometry. To this end, a method for the accurate reconstruction of 3-D cloud geometry from cloud radar measurements is developed in this work. Using a radar simulator and simulated passive measurements of model clouds based on a large eddy simulation (LES), the effects of different radar scan resolutions and varying interpolation methods are evaluated. In reality, a trade-off between scan resolution and scan duration has to be found as clouds change quickly. A reasonable choice is a scan resolution of 1 to 2°. The most suitable interpolation procedure identified is the barycentric interpolation method. The 3-D reconstruction method is demonstrated using radar scans of convective cloud cases with the Munich miraMACS, a 35 GHz scanning cloud radar. As a successful proof of concept, camera imagery collected at the radar location is reproduced for the observed cloud cases via 3-D volume reconstruction and 3-D radiative transfer simulation. Data sets provided by the presented reconstruction method will aid passive spectral ground-based measurements of cloud sides to retrieve microphysical parameters. [ABSTRACT FROM AUTHOR]

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA), a Fourier-transform-spectrometer-based limb spectral imager, operates on high-altitude research aircraft to study the transit region between the troposphere and the stratosphere. It is one of the most sophisticated systems to be flown on research aircraft in Europe, requiring constant monitoring and human intervention in addition to an automation system. To ensure proper functionality and interoperability on multiple platforms, a flexible control and communication system was laid out. The architectures of the communication system as well as the protocols used are reviewed. The integration of this architecture in the automation process as well as the scientific campaign flight application context are discussed. [ABSTRACT FROM AUTHOR]

Within the NDACC (Network for the Detection of Atmospheric Composition Change), more than 20 FTIR (Fourier-transform infrared) spectrometers, spread worldwide, provide long-term data records of many atmospheric trace gases. We present a method that uses measured and modelled XCO2 for assessing the consistency of these NDACC data records. Our XCO2 retrieval setup is kept simple so that it can easily be adopted for any NDACC/FTIR-like measurement made since the late 1950s. By a comparison to coincident TCCON (Total Carbon Column Observing Network) measurements, we empirically demonstrate the useful quality of this suggested NDACC XCO2 product (empirically obtained scatter between TCCON and NDACC is about 4‰ for daily mean as well as monthly mean comparisons, and the bias is 25 ‰). Our XCO2 model is a simple regression model fitted to CarbonTracker results and the Mauna Loa CO2 in situ records. A comparison to TCCON data suggests an uncertainty of the model for monthly mean data of below 3 ‰.We apply the method to the NDACC/FTIR spectra that are used within the project MUSICA (multi-platform remote sensing of isotopologues for investigating the cycle of atmospheric water) and demonstrate that there is a good consistency for these globally representative set of spectra measured since 1996: the scatter between the modelled and measured XCO2 on a yearly time scale is only 3 ‰. [ABSTRACT FROM AUTHOR]

This study examines the possibility of groundbased remote-sensing ozone total column amounts (OTC) from spectral signatures at 3040 and 4030 cm-1. These spectral regions are routinely measured by the NDACC (Network for the Detection of Atmospheric Composition Change) ground-based FTIR (Fourier transform infraRed) experiments. In addition, they are potentially detectable by the TCCON (Total Carbon Column Observing Network) FTIR instruments. The ozone retrieval strategy presented here estimates the OTC from NDACC FTIR high-resolution spectra with a theoretical precision of about 2 and 5% in the 3040 and 4030 cm-1 regions, respectively. Empirically, these OTC products are validated by inter-comparison to FTIR OTC reference retrievals in the 1000 cm-1 spectral region (standard reference for NDACC ozone products), using an 8-year FTIR time series (2005–2012) taken at the subtropical ozone supersite of the Izaña Atmospheric Observatory (Tenerife, Spain). Associated with the weaker ozone signatures at the higher wave number regions, the 3040 and 4030 cm-1 retrievals show lower vertical sensitivity than the 1000 cm-1 retrievals. Nevertheless, we observe that the rather consistent variations are detected: the variances of the 3040 cm&-1 and the 4030 cm-1 retrievals agree within 90 and 75 %, respectively, with the variance of the 1000 cm-1 standard retrieval. Furthermore, all three retrievals show very similar annual cycles. However, we observe a large systematic difference of about 7% between the OTC obtained at 1000 and 3040 cm-1, indicating a significant inconsistency between the spectroscopic ozone parameters (HITRAN, 2012) of both regions. Between the 1000 cm and the 4030 cm-1 retrieval the systematic difference is only 2–3 %. Finally, the longterm stability of the OTC retrievals has also been examined, observing that both near-infrared retrievals can monitor the long-term OTC evolution, consistent with the 1000 cm-1 reference data. These findings demonstrate that recording the solar absorption spectra in the 3000 cm-1 spectral region at high spectral resolution (about 0.005 cm-1) might be useful for TCCON sites. Hence, both NDACC and TCCON groundbased FTIR experiments might contribute to global ozone databases. [ABSTRACT FROM AUTHOR]