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The Measurements of Pollution in the Troposphere (MOPITT) instrument is the only satellite-borne sensor in operation that uses both thermal (TIR) and near-infrared (NIR) channels to estimate CO profiles. With more than 15 years (2000 to present) of validated multispectral observations, MOPITT provides the unique capability to separate CO in the lowermost troposphere (LMT, surface to 3 km (∼ 700 hPa)) from the free-tropospheric abundance. To extend this record, a new, hyper-spectral approach is presented here that will provide CO data products exceeding the capabilities of MOPITT by combining the short-wavelength infrared (SWIR, equivalent to the MOPITT NIR) channels from the TROPOspheric Monitoring Instrument (TROPOMI) to be launched aboard the European Sentinel 5 Precursor (S5p) satellite in 2016 and the TIR channels from the Cross-track Infrared Sounder (CrIS) aboard the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite. We apply the MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSES) retrieval algorithm to quantify the potential of this joint CO product. CO profiles are retrieved from a single-footprint, full-spectral-resolution CrIS transect over Africa on 27–28 August 2013 coincident with significant biomass burning. Comparisons of collocated CrIS and MOPITT CO observations for the LMT show a mean difference of 2.8 ± 24.9 ppb, which is well within the estimated measurement uncertainty of both sensors. The estimated degrees of freedom (DOF) for CO signals from synergistic CrIS–TROPOMI retrievals are approximately 0.9 in the LMT and 1.3 above the LMT, which indicates that the LMT CO can be distinguished from the free troposphere, similar to MOPITT multispectral observations (0.8 in the LMT, and 1.1 above the LMT). In addition to increased sensitivity, the combined retrievals reduce measurement uncertainty, with ∼ 15 % error reduction in the LMT. With a daily global coverage and a combined spatial footprint of 14 km, the joint CrIS–TROPOMI measurements have the potential to extend and improve upon the MOPITT multispectral CO data records for the coming decade.

CO total column data are presented from three space sounders and two ground-based spectrometers in Moscow and its suburbs during the forest and peat fires that occurred in Central Russia in July–August 2010. Also presented are ground-based in situ CO measurements. The Moscow area was strongly impacted by the CO plume from these fires. Concurrent satellite- and ground-based observations were used to quantify the errors of CO top-down emission estimates. On certain days, CO total columns retrieved from the data of the space-based sounders were 2–3 times less than those obtained from the ground-based sun-tracking spectrometers. The depth of the polluted layer over Moscow was estimated using total column measurements compared with CO volume mixing ratios in the surface layer and on the TV tower and found to be around 360 m. The missing CO that is the average difference between the CO total column accurately determined by the ground spectrometers and that retrieved by AIRS, MOPITT, and IASI was determined for the Moscow area between 1.6 and 3.3 × 1018 molec cm−2. These values were extrapolated onto the entire plume; subsequently, the CO burden (total mass) over Russia during the fire event was corrected. A top-down estimate of the total emitted CO, obtained by a simple mass balance model increased by 40–100 % for different sensors due to this correction. Final assessments of total CO emitted by Russian wildfires obtained from different sounders are between 34 and 40 Tg CO during July–August 2010.

A fast pseudo-monochromatic radiative transfer package using a singular value decomposition (SVD) compressed atmospheric optical depth database has been developed, primarily for simulating radiances from hyperspectral sounding instruments (resolution ≥0.1 cm−1). The package has been tested extensively for clear-sky radiative transfer cases, using field campaign data and satellite instrument data. The current database uses HITRAN 2016 line parameters and is primed for use in the spectral region spanning 605 to 2830 cm−1. Optical depths for other spectral regions (15–605 and 2830–45 000 cm−1) can also be generated for use by kCARTA. The clear-sky radiative transfer model computes the background thermal radiation quickly and accurately using a layer-varying diffusivity angle at each spectral point; it takes less than 30 s (on a 2.8 GHz core using four threads) to complete a radiance calculation spanning the infrared. The code can also compute non-local thermodynamic equilibrium effects for the 4 µm CO2 region, as well as analytic temperature, gas and surface Jacobians. The package also includes flux and heating rate calculations and an interface to an infrared scattering model.

Temperature, H2O, and O3 profiles, as well as CO2, N2O, CH4, chlorofluorocarbon-12 (CFC-12), and sea surface temperature (SST) scalar anomalies are computed using a clear subset of AIRS observations over ocean for the first 16 years of NASA's Earth-Observing Satellite (EOS) Aqua Atmospheric Infrared Sounder (AIRS) operation. The AIRS Level-1c radiances are averaged over 16 d and 40 equal-area zonal bins and then converted to brightness temperature anomalies. Geophysical anomalies are retrieved from the brightness temperature anomalies using a relatively standard optimal estimation approach. The CO2, N2O, CH4, and CFC-12 anomalies are derived by applying a vertically uniform multiplicative shift to each gas in order to obtain an estimate for the gas mixing ratio. The minor-gas anomalies are compared to the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) in situ values and used to estimate the radiometric stability of the AIRS radiances. Similarly, the retrieved SST anomalies are compared to the SST values used in the ERA-Interim reanalysis and to NOAA's Optimum Interpolation SST (OISST) product. These intercomparisons strongly suggest that many AIRS channels are stable to better than 0.02 to 0.03 K per decade, well below climate trend levels, indicating that the AIRS blackbody is not drifting. However, detailed examination of the anomaly retrieval residuals (observed – computed) shows various small unphysical shifts that correspond to AIRS hardware events (shutdowns, etc.). Some examples are given highlighting how the AIRS radiance stability could be improved, especially for channels sensitive to N2O and CH4. The AIRS shortwave channels exhibit larger drifts that make them unsuitable for climate trending, and they are avoided in this work. The AIRS Level 2 surface temperature retrievals only use shortwave channels. We summarize how these shortwave drifts impacts recently published comparisons of AIRS surface temperature trends to other surface climatologies.

One-dimensional variational retrievals of temperature and moisture fields from hyperspectral infrared (IR) satellite sounders use cloud-cleared radiances (CCRs) as their observation. These derived observations allow the use of clear-sky-only radiative transfer in the inversion for geophysical variables but at reduced spatial resolution compared to the native sounder observations. Cloud clearing can introduce various errors, although scenes with large errors can be identified and ignored. Information content studies show that, when using multilayer cloud liquid and ice profiles in infrared hyperspectral radiative transfer codes, there are typically only 2–4 degrees of freedom (DOFs) of cloud signal. This implies a simplified cloud representation is sufficient for some applications which need accurate radiative transfer. Here we describe a single-footprint retrieval approach for clear and cloudy conditions, which uses the thermodynamic and cloud fields from numerical weather prediction (NWP) models as a first guess, together with a simple cloud-representation model coupled to a fast scattering radiative transfer algorithm (RTA). The NWP model thermodynamic and cloud profiles are first co-located to the observations, after which the N-level cloud profiles are converted to two slab clouds (TwoSlab; typically one for ice and one for water clouds). From these, one run of our fast cloud-representation model allows an improvement of the a priori cloud state by comparing the observed and model-simulated radiances in the thermal window channels. The retrieval yield is over 90 %, while the degrees of freedom correlate with the observed window channel brightness temperature (BT) which itself depends on the cloud optical depth. The cloud-representation and scattering package is benchmarked against radiances computed using a maximum random overlap (RMO) cloud scheme. All-sky infrared radiances measured by NASA's Atmospheric Infrared Sounder (AIRS) and NWP thermodynamic and cloud profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model are used in this paper.

Ammonia (NH3) plays an increasingly important role in the global biogeochemical cycle of reactive nitrogen as well as in aerosol formation and climate. We present extensive and nearly continuous global ammonia measurements made by the Atmospheric Infrared Sounder (AIRS) from the Aqua satellite to identify and quantify major persistent and episodic sources as well as to characterize seasonality. We examine the 13-year period from September 2002 through August 2015 with a retrieval algorithm using an optimal estimation technique with a set of three, spatially and temporally uniform a priori profiles. Vertical profiles show good agreement (∼ 5–15 %) between AIRS NH3 and the in situ profiles from the winter 2013 DISCOVER-AQ (DISCOVER-Air Quality) field campaign in central California, despite the likely biases due to spatial resolution differences between the two instruments. The AIRS instrument captures the strongest consistent NH3 concentrations due to emissions from the anthropogenic (agricultural) source regions, such as South Asia (India/Pakistan), China, the United States (US), parts of Europe, Southeast (SE) Asia (Thailand/Myanmar/Laos), the central portion of South America, as well as Western and Northern Africa. These correspond primarily to irrigated croplands, as well as regions with heavy precipitation, with extensive animal feeding operations and fertilizer applications where a summer maximum and a secondary spring maximum are reliably observable. In the Southern Hemisphere (SH) regular agricultural fires contribute to a spring maximum. Regions of strong episodic emissions include Russia and Alaska as well as parts of South America, Africa, and Indonesia. Biomass burning, especially wildfires, dominate these episodic NH3 high concentrations.

We present in this paper an alternative retrieval algorithm for the Atmospheric Infrared Sounder (AIRS) tropospheric Carbon Monoxide (CO) products using the Optimal Estimation (OE) technique, which is different from the AIRS operational algorithm. The primary objective for this study was to compare AIRS CO, as well as the other retrieval properties such as the Averaging Kernels (AKs), the Degrees of Freedom for Signal (DOFS), and the error covariance matrix, against the Tropospheric Emission Spectrometer (TES) and the Measurement of Pollution in the Troposphere (MOPITT) CO, which were also derived using the OE technique. We also demonstrate that AIRS OE CO results are much more realistic than AIRS V5 operational CO, especially in the lower troposphere and in the Southern Hemisphere (SH). These products are validated with in situ profiles obtained by the Differential Absorption Carbon Monoxide Measurements (DACOM), which took place as part of NASA's Intercontinental Chemical Transport Experiment (INTEX-B) field mission that was conducted over the northern Pacific in Spring 2006. To demonstrate the differences existing in the current operational products we first show a detailed direct comparison between AIRS V5 and TES operational V3 CO for the global datasets from December 2005 to July 2008. We then present global CO comparisons between AIRS OE, TES V3, and MOPITT V4 at selected pressure levels as well as for the total column amounts. We conclude that the tropospheric CO retrievals from AIRS OE and TES V3 agree to within 5–10 ppbv or 5% on average globally and throughout the free troposphere. The agreements in total column CO amounts between AIRS OE and MOPITT V4 have improved significantly compared to AIRS V5 with global relative RMS differences now being 12.7%.

Atmospheric thermodynamic parameters, such as atmospheric temperature and moisture profiles, cloud optical/microphysical properties, and surface properties are basic meteorological variables for weather forecasting. In addition, they are critical parameters in tropospheric chemistry studies. A physical, geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiances observed with satellite ultraspectral infrared sounders has been developed to determine simultaneously surface, atmospheric thermodynamic, and cloud microphysical parameters. A one-dimensional variational (1-D Var.) multivariable inverse solution of the radiative transfer equation is used to iteratively improve a background state defined by eigenvector regression. This algorithm has been applied to data from the Infrared Atmospheric Sounding Interferometer (IASI) on the EUMETSAT Metop-A satellite. The IASI retrieved parameters presented herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, such as the NPOESS Airborne Sounder Testbed – Interferometer (NAST-I), in-situ measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here, IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features with high vertical resolution from satellite ultraspectral sounder radiance spectra.