Wildfire-Induced CO Plume Observations From NAST-I During the FIREX-AQ Field Campaign

The fire influence on regional to global environments and air quality (FIREX-AQ) field campaign was conducted during August 2019 to investigate the impact of wildfire and biomass smoke on air quality and weather in the continental United States. One of the campaign's scientific objectives was to estimate the composition of emissions from wildfires. Ultraspectrally resolved infrared radiance measurements from aircraft and/or satellite observations contain information on tropospheric carbon monoxide (CO) as well as other trace species present in fire emissions. A methodology for retrieving tropospheric CO from such remotely sensed spectral data has been developed for the National Airborne Sounder Testbed-Interferometer (NAST-I) and is applied herein. Retrievals based on NAST-I measurements are used to demonstrate CO retrieval capability and characterize fire emissions. NAST-I remotely sensed CO from ER-2 flights are evaluated with concurrent in situ measurements from the differential absorption carbon monoxide measurements flown on the NASA DC-8 aircraft. Enhanced CO emissions along with plume evolution and transport from the fire ground site locations were captured by moderate vertical and high horizontal resolution observations obtained from the NAST-I IR spectrometer; these were intercompared and verified by the cloud physics lidar and the enhanced MODIS airborne simulator also hosted on the NASA ER-2 aircraft. This study will be beneficial to the science community for studying wildfire-related topics and understanding similar remotely sensed observations from satellites, along with helping to address the broader FIREX-AQ experiment objectives of investigating the impact of fires on air quality and climate.

Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from SCIAMACHY

High-quality observations have indicated the need for improved molecular spectroscopy for accurate atmospheric characterization. Line data provided by the new SEOM-IAS (Scientific Exploitation of Operational Missions—Improved Atmospheric Spectroscopy) database in the shortwave infrared (SWIR) region were used to retrieve CO total vertical columns from a selected set of nadir SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) observations. In order to assess the quality of the retrieval results, differences in the spectral fitting residuals with respect to the HITRAN 2016 (High-resolution TRANsmission molecular absorption) and GEISA 2015 (Gestion et Etude des Informations Spectroscopiques Atmosphériques) line lists were quantified and column-averaged dry-air CO mole fractions were compared to NDACC (Network for the Detection of Atmospheric Composition Change) and TCCON (Total Carbon Column Observing Network) ground-based measurements. In general, it was found that using SEOM-IAS line data with corresponding line models improve the spectral quality of the retrieval (smaller residuals) and increase the fitted CO columns, thereby reducing the bias to both ground-based networks.

Tropospheric CO observed with the NAST-I retrieval methodology, analyses, and first results

High-resolution infrared spectra from aircraft and space-based observations contain information about tropospheric carbon monoxide (CO) as well as other trace species. A methodology for retrieving tropospheric CO from such remotely sensed spectral data has been developed for the National Polar-Orbiting Operational Environmental Satellite System's Airborne Sounder Testbed-Interferometer (NAST-I). CO profiles of the troposphere, together with its thermodynamic properties, are determined by use of a three-stage retrieval approach that combines the algorithms of physically based statistical eigenvector regression, simultaneous and iterative matrix inversion, and single-variable error-minimization CO profile matrix inverse retrieval. The NAST-I is collecting data while it is aboard high-altitude aircraft throughout many field campaigns. Detailed retrieval analyses based on the NAST-I instrument system along with retrieval results from several recent field campaigns are presented to demonstrate NAST-I CO retrieval capability.

Retrieval of CO from nadir remote-sensing measurements in the infrared by use of four different inversion algorithms

Four inversion schemes based on various retrieval approaches (digital gas correlation, nonlinear least squares, global fit adjustment, and neural networks) developed to retrieve CO from nadir radiances measured by such downward-looking satelliteborne instruments as the Measurement of Pollution in the Troposphere (MOPITT), the Tropospheric Emission Spectrometer (TES), and the Infrared Atmospheric Sounding Interferometer (IASI) instruments were compared both for simulated cases and for atmospheric spectra recorded by the Interferometric Monitor for Greenhouse Gases (IMG). The sensitivity of the retrieved CO total column amount to properties that may affect the inversion accuracy (noise, ancillary temperature profile, and water-vapor content) was investigated. The CO column amounts for the simulated radiance spectra agreed within 4%, whereas larger discrepancies were obtained when atmospheric spectra recorded by the IMG instrument were analyzed. The assumed vertical temperature profile is shown to be a critical parameter for accurate CO retrieval. The instrument's line shape was also identified as a possible cause of disagreement among the result provided by the groups of scientist who are participating in this study.

Retrieval of atmospheric-temperature and water-vapor profiles by use of combined satellite and ground-based infrared spectral-radiance measurements

A nonlinear sounding retrieval algorithm is used to produce vertical-temperature and water-vapor profiles from coincident observations taken by the airborne High-resolution Interferometer Sounder (HIS) and the ground-based Atmospheric Emitted Radiance Interferometer (AERI) during the SUbsonic Contrails and Clouds Effects Special Study (SUCCESS). Also, clear sky Geostationary Operational Environmental Satellite (GOES) and AERI radiance measurements, achieved on a daily real-time basis at the Department of Energy's Oklahoma CART (Cloud and Radiation Testbed) site, are used to demonstrate the current profiling capability by use of simultaneous geostationary satellite and ground-based remote sensing observations under clear-sky conditions. The discrepancy principle, a method to find the proper smoothing parameters from the minimum value between the normalized spectral residual norm and the a priori upper bound, is used to demonstrate the feasibility and effectiveness of on-line simultaneous tuning of the multiple weighting and smoothing parameters from the combined satellite/airborne and ground-based measurements for the temperature and water-vapor retrieval in this nonlinear-retrieval process. An objective method to determine the degrees of freedom (d.f.) of the observation signal is derived. The d.f. of the radiance signal for the combined GOES and AERI measurements is larger than that for either instrument alone; while the d.f. of the observation signal for the combined GOES and AERI measurements is larger than that for either instrument alone and of the combined GOES and AERI measurements. The use of simultaneous clear-sky AERI and GOES data now provides improved vertical temperature and moisture soundings on an hourly basis for use in the Atmospheric Radiation Measurement program [J. Appl. Meteorol. 37, 875 (1998)].

Cloud Detection and Clearing for the Earth Observing System Terra Satellite Measurements of Pollution in the Troposphere (MOPITT) Experiment

The Measurements of Pollution in the Troposphere (MOPITT) instrument, which was launched aboard the Earth Observing System (EOS) Terra spacecraft on 18 December 1999, is designed to measure tropospheric CO and CH(4) by use of a nadir-viewing geometry. The measurements are taken at 4.7 mum in the thermal emission and absorption for the CO mixing ratio profile retrieval and at 2.3 and 2.2 mum in the reflected solar region for the total CO column amount and CH(4) column amount retrieval, respectively. To achieve the required measurement accuracy, it is critical to identify and remove cloud contamination in the radiometric signals. We describe an algorithm to detect cloudy pixels, to reconstruct clear column radiance for pixels with partial cloud covers, and to estimate equivalent cloud top height for overcast conditions to allow CO profile retrievals above clouds. The MOPITT channel radiances, as well as the first-guess calculations, are simulated with a fast forward model with input atmospheric profiles from ancillary data sets. The precision of the retrieved CO profiles and total column amounts in cloudy atmospheres is within the expected ?10% range. Validations of the cloud-detecting thresholds with the moderate-resolution imaging spectroradiometer airborne simulator data and MOPITT airborne test radiometer measurements were performed. The validation results showed that the MOPITT cloud detection thresholds work well for scenes covered with more than 5-10% cloud cover if the uncertainties in the model input profiles are less than 2 K for temperature, 10% for water vapor, and 5% for CO and CH(4).