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Satellite-based observations of free-tropospheric water vapour isotopologue ratios (HDO / H 2 O, expressed in form of the δ value δ D) with good global and temporal coverage have become available recently. We investigate the potential of these observations for constraining the uncertainties of the atmospheric analyses fields of specific humidity (q), temperature (T), and δ D and of variables that capture important properties of the atmospheric water cycle, namely the vertical velocity (ω), the latent heating rate (Q2), and the precipitation rate (Prcp). Our focus is on the impact of the δ D observations relative to the impact achieved by the observation of q and T , which are much more easily observed by satellites and are routinely in use for atmospheric analyses. For our investigations we use an Observing System Simulation Experiment; i.e. we simulate the satellite observations of q , T , and δ D with known uncertainties and coverage (e.g. observations are not available for cloudy conditions, i.e. at locations where the atmosphere is vertically unstable). Then we use the simulated observations within a Kalman-filter-based assimilation framework in order to evaluate their potential for improving the quality of atmospheric analyses. The study is made for low latitudes (30° S to 30° N) and for 40 d between mid-July and the end of August 2016. We find that q observations generally have the largest impacts on the analyses' quality and that T observations have stronger impacts overall than δ D observations. We show that there is no significant impact of δ D observations for stable atmospheric conditions; however, for very unstable conditions, the impact of δ D observations is significant and even slightly stronger than the respective impact of T observations. Very unstable conditions are rare but are related to extreme events (e.g. storms, flooding); i.e. the δ D observations significantly impact the analyses' quality of the events that have the largest societal consequences. The fact that no satellite observations are available at the location and time of the unstable conditions indicates a remote impact of δ D observations that are available elsewhere. Concerning real-world applications, we conclude that the situation of δ D satellite observations is very promising but that further improving the model's linkage between convective processes and the larger-scale δ D fields might be needed for optimizing the assimilation impact of real-world δ D observations. [ABSTRACT FROM AUTHOR]

We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the tnzuncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.

The cross-comparison of different techniques for atmospheric integrated water vapour (IWV) measurements is the essential part of their quality assessment protocol. We inter-compare the synchronised data sets of IWV values measured by the Bruker 125 HR Fourier-transform infrared spectrometer (FTIR), RPG-HATPRO microwave radiometer (MW), and Novatel ProPak-V3 global navigation satellite system receiver (GPS) at the St. Petersburg site between August 2014 and October 2016. As the result of accurate spatial and temporal matching of different IWV measurements, all three techniques agree well with each other except for small IWV values. We show that GPS and MW data quality depends on the atmospheric conditions; in dry atmosphere (IWV smaller than 6 mm), these techniques are less reliable at the St. Petersburg site than the FTIR method. We evaluate the upper bound of statistical measurement errors for clear-sky conditions as 0.29±0.02mm (1.6±0.3%), 0.55±0.02mm (4.7±0.4%), and 0.76±0.04mm (6.3±0.8%) for FTIR, GPS, and MW methods, respectively. We propose the use of FTIR as a reference method under clear-sky conditions since it is reliable on all scales of IWV variability. [ABSTRACT FROM AUTHOR]

We present atmospheric ozone (O3) profiles measured over central Mexico between November 2012 and February 2014 from two different ground-based FTIR (Fourier transform infrared) solar absorption experiments. The first instrument offers very high-resolution spectra and contributes to NDACC (Network for the Detection of Atmospheric Composition Change). It is located at a mountain observatory about 1700m above the Mexico City basin. The second instrument has a medium spectral resolution and is located inside Mexico City at a horizontal distance of about 60 km from the mountain observatory. It is documented that the retrieval with the high- and medium-resolution experiments provides O3 variations for four and three independent atmospheric altitude ranges, respectively, and the theoretically estimated errors of these profile data are mostly within 10%. The good quality of the data is empirically demonstrated above the tropopause by intercomparing the two FTIR O3 data, and for the boundary layer by comparing the Mexico City FTIR O3 data with in situ O3 surface data. Furthermore, we develop a combined boundary layer O3 remote sensing product that uses the retrieval results of both FTIR experiments, and we use theoretical and empirical evaluations to document the improvements that can be achieved by such a combination. [ABSTRACT FROM AUTHOR]

The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) has shown that the sensor IASI aboard the satellite MetOp can measure the free tropospheric {H2O,δD} pair distribution twice per day on a quasi-global scale. Such data are very promising for investigating tropospheric moisture pathways, however, the complex data characteristics compromise their usage in the context of model evaluation studies. Here we present a tool that allows for simulating MUSICA MetOp/IASI {H2O,δD} pair remote sensing data for a given model atmosphere, thereby creating model data that have the remote sensing data characteristics assimilated. This model data can then be compared to the MUSICA data. The retrieval simulation method is based on the physical principles of radiative transfer and we show that the uncertainty of the simulations is within the uncertainty of the MUSICA MetOp/IASI products, i.e. the retrieval simulations are reliable enough.We demonstrate the working principle of the simulator by applying it to ECHAM5-wiso model data. The few case studies clearly reveal the large potential of the MUSICA MetOp/IASI {H2O,δD} data pairs for evaluating modelled moisture pathways. The tool is made freely available in form of MATLAB and Python routines and can be easily connected to any atmospheric water vapour isotopologue model. [ABSTRACT FROM AUTHOR]

In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products. [ABSTRACT FROM AUTHOR]

This paper presents the tools and methodology for performing a routine comprehensive monitoring of consistency and quality of IASI (Infrared Atmospheric Sounding Interferometer) trace gas Level 2 (L2) products (O3, CO, N2O, CH4, and CO2) generated at EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) using ground-based observations at the Izaña Atmospheric Observatory (IZO, Tenerife). As a demonstration the period 2010-2014 was analysed, covering the version 5 of the IASI L2 processor. Firstly, we assess the consistency between the total column (TC) observations from the IASI sensors on board the EUMETSAT Metop-A and Metop-B meteorological satellites (IASI-A and IASI-B respectively) in the subtropical North Atlantic region during the first 2 years of IASI-B operations (2012-2014). By analysing different timescales, we probe the daily and annual consistency of the variability observed by IASI-A and IASI-B and thereby assess the suitability of IASI-B for continuation of the IASI-A time series. The continuous intercomparison of both IASI sensors also offers important diagnostics for identifying inconsistencies between the data records and for documenting their temporal stability. Once the consistency of IASI sensors is documented we estimate the overall accuracy of all the IASI trace gas TC products by comparing to coincident ground-based Fourier transform infrared spectrometer (FTS) measurements performed at IZO from 2010 to 2014. The IASI L2 products reproduce the ground-based FTS observations well at the longest temporal scales, i.e. annual cycles and long-term trends for all the trace gases considered (Pearson correlation coefficient, R, larger than 0.95 and 0.75 for long-term trends and annual cycles respectively) with the exception of CO2. For CO2 acceptable agreement is only achieved for long-term trends (R~0.70). The differences observed between IASI and FTS observations can be in part attributed to the different vertical sensitivities of the two remote sensing instruments and also to the degree of maturity of the IASI products: O3 and CO are pre-operational, while N2O, CH4, and CO2 are, for the period covered by this study, aspirational products only and are not considered mature. Regarding shorter timescales (single or daily measurements), only the O3 product seems to show good sensitivity to actual atmospheric variations (R~0.80), while the CO product is only moderately sensitive (R~0.50). For the remainder of the trace gases, further improvements would be required to capture the day-to-day real atmospheric variability. [ABSTRACT FROM AUTHOR]

The thermal And near infrared sensor for carbon observations Fourier transform spectrometer (TANSO-FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) applies the normal nadir mode above the land ("land data") and sun glint mode over the ocean ("ocean data") to provide global distributions of column-averaged dry-air mole fractions of CO2 and CH4, or XCO2 and XCH4. Several algorithms have been developed to obtain highly accurate greenhouse gas concentrations from TANSO-FTS/GOSAT spectra. So far, all the retrieval algorithms have been validated with the measurements from ground-based Fourier transform spectrometers from the Total Carbon Column Observing Network (TCCON), but limited to the land data. In this paper, the ocean data of the SRPR, SRFP (the proxy and full-physics versions 2.3.5 of SRON/KIT's RemoTeC algorithm), NIES (National Institute for Environmental Studies operational algorithm version 02.21) and ACOS (NASA's Atmospheric CO2 Observations from Space version 3.5) are compared with FTIR measurements from five TCCON sites and nearby GOSAT land data. For XCO2, both land and ocean data of NIES, SRFP and ACOS show good agreement with TCCON measurements. Averaged over all TCCON sites, the relative biases of ocean data and land data are -0.33 and -0.13 % for NIES, 0.03 and 0.04% for SRFP, 0.06 and -0.03 % for ACOS, respectively. The relative scatter ranges between 0.31 and 0.49%. For XCH4, the relative bias of ocean data is even less than that of the land data for the NIES (0.02 vs. -0.35 %), SRFP (0.04 vs. 0.20%) and SRPR (-0.02 vs. 0.06%) algorithms. Compared to the results for XCO2, the XCH4 retrievals show larger relative scatter (0.65-0.81 %). [ABSTRACT FROM AUTHOR]

The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of At-mospheric water) integrates tropospheric water vapour iso-topologue remote sensing and in situ observations. This pa-per presents a first empirical validation of MUSICA's H2O and δD remote sensing products, generated from ground-based FTIR (Fourier transform infrared), spectrometer and space-based IASI (infrared atmospheric sounding interferometer) observation. The study is made in the area of the Canary Islands in the subtropical northern Atlantic. As reference we use well calibrated in situ measurements made aboard an aircraft (between 200 and 6800 m a.s.l.) by the dedicated ISOWAT instrument and on the island of Tenerife at two different altitudes (at Izaña, 2370 m a.s.l., and at Teide, 3550 m a.s.l.) by two commercial Picarro L2120-i water isotopologue analysers. The comparison to the ISOWAT profile measurements shows that the remote sensors can well capture the varia-tions in the water vapour isotopologues, and the scatter with respect to the in situ references suggests a δD random un-certainty for the FTIR product of much better than 45 ‰ in the lower troposphere and of about 15 ‰ for the middle tro-posphere. For the middle tropospheric IASI δD product the study suggests a respective uncertainty of about 15 ‰. In both remote sensing data sets we find a positive δD bias of 30-70 ‰. Complementing H2O observations with δD data allows moisture transport studies that are not possible with H2O observations alone. We are able to qualitatively demonstrate the added value of the MUSICA δD remote sensing data. We document that the δD-H2O curves obtained from the different in situ and remote sensing data sets (ISOWAT, Picarro at Izaña and Teide, FTIR, and IASI) consistently identify two different moisture transport pathways to the subtropical north eastern Atlantic free troposphere. [ABSTRACT FROM AUTHOR]

Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2:5/ at the global scale. Satellite remote sensing offers a promising approach to provide information on both short- and long-term exposure to PM2:5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2:5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2:5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2:5 and PM10, are highly autonomous. Hourly PM2:5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, watersoluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2:5 estimates used for assessing the health effects of aerosols. Mean PM2:5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2:5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency. [ABSTRACT FROM AUTHOR]