Development of a fast and accurate PCRTM radiative transfer model in the solar spectral region.

A fast and accurate principal component-based radiative transfer model in the solar spectral region (PCRTM-SOLAR) has been developed. The algorithm is capable of simulating reflected solar spectra in both clear sky and cloudy atmospheric conditions. Multiple scattering of the solar beam by the multilayer clouds and aerosols are calculated using a discrete ordinate radiative transfer scheme. The PCRTM-SOLAR model can be trained to simulate top-of-atmosphere radiance or reflectance spectra with spectral resolution ranging from 1 cm-1 resolution to a few nanometers. Broadband radiances or reflectance can also be calculated if desired. The current version of the PCRTM-SOLAR covers a spectral range from 300 to 2500 nm. The model is valid for solar zenith angles ranging from 0 to 80 deg, the instrument view zenith angles ranging from 0 to 70 deg, and the relative azimuthal angles ranging from 0 to 360 deg. Depending on the number of spectral channels, the speed of the current version of PCRTM-SOLAR is a few hundred to over one thousand times faster than the medium speed correlated-k option MODTRAN5. The absolute RMS error in channel radiance is smaller than 10-3 mW/cm2/sr/cm-1 and the relative error is typically less than 0.2%.

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.

Principal component-based radiative transfer model for hyperspectral sensors: theoretical concept.

Modern infrared satellite sensors such as the Atmospheric Infrared Sounder (AIRS), the Cross-Track Infrared Sounder (CrIS), the Tropospheric Emission Spectrometer (TES), the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS), and the Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, superfast radiative transfer models are needed. We present a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the principal component-based radiative transfer model (PCRTM) predicts the principal component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from the properties of PC scores and instrument line-shape functions. The PCRTM is accurate and flexible. Because of its high speed and compressed spectral information format, it has great potential for superfast one-dimensional physical retrieval and for numerical weather prediction large volume radiance data assimilation applications. The model has been successfully developed for the NAST-I and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.

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.

Thermodynamic product retrieval methodology and validation for NAST-I.

The National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed (NAST) consists of two passive collocated cross-track scanning instruments, an infrared interferometer (NAST-I) and a microwave radiometer (NAST-M), that fly onboard high-altitude aircraft such as the NASA ER-2 at an altitude near 20 km. NAST-I provides relatively high spectral resolution (0.25-cm(-1)) measurements in the 645-2700-cm(-1) spectral region with moderate spatial resolution (a linear resolution equal to 13% of the aircraft altitude at nadir) cross-track scanning. We report the methodology for retrieval of atmospheric temperature and composition profiles from NAST-I radiance spectra. The profiles were determined by use of a statistical eigenvector regression algorithm and improved, as needed, by use of a nonlinear physical retrieval algorithm. Several field campaigns conducted under varied meteorological conditions have provided the data needed to verify the accuracy of the spectral radiance, the retrieval algorithm, and the scanning capabilities of this instrumentation. Retrieval examples are presented to demonstrate the ability to reveal fine-scale horizontal features with relatively high vertical resolution.