This study presents a first-of-its-kind comprehensive data fusion approach combining hyperspectral microwave (HMW) with backscatter lidar (BSL) measurements for improved atmospheric thermodynamic sounding, with particular emphasis on the Earth’s Planetary Boundary Layer (PBL). This is a simulation-based trade study to demonstrate the enhancement of HMW over traditional microwave (MW) only measurements and the additional benefits of incorporating BSL with both approaches. This pioneering HMW+BSL fusion methodology represents a major advancement, achieving superior performance compared to traditional thermodynamic remote sensing approaches. Specifically, this configuration demonstrates significant enhancement in PBL temperature bias vertical stability and reduces standard deviation error (SDV) by 30% compared to traditional MW-only performance. Water vapor retrievals show similar improvements, with SDV reductions of 50% in the PBL and bias values consistently maintained below the 10% requirement threshold of the PBL DSI program, compared to PoR errors exceeding 30% bias in challenging cloudy regimes. Case studies across diverse oceanic regions reveal particular advantages of this data fusion approach in complex atmospheric conditions, especially in regions dominated by marine stratocumulus clouds and strong temperature inversions where conventional passive-only retrievals are challenging. Beyond thermodynamic profile improvements, our analysis demonstrates remarkable advances in the detection of PBL height (PBLH), with the HMW+BSL configuration achieving mean absolute errors within the 100 meter requirement threshold of the PBL DSI program, representing a step-change improvement over passive-only approaches. This work directly addresses observational gaps identified in the 2017 Earth Science Decadal Survey, positioning our integrated sensing approach as both a near-term enhancement to existing Earth observation capabilities and a pathfinder for future PBL mission architectures.

We present an overview of the 2024 West-Coast Hyperspectral Microwave Sensor Intensive Experiment (WHyMSIE). WHyMSIE is a joint NASA-NOAA multi-sensor airborne experiment, embracing passive and active sensors from the Program of Record (PoR) along with novel technology funded through the NASA ESTO Instrument Incubation Program. At the core of this effort is the demonstration of the Conical Scanning Millimeter-wave Imaging Radiometer Hyperspectral (CoSMIR-H) instrument, a PBL DSI funded effort to develop hyperspectral sounding capability in the thermal microwave domain finalized to improved temperature and water vapor soundings in the Earth’s Planetary Boundary Layer (PBL). An overview of the field campaign design, instrument payload and validation plan is presented here.

We present a comprehensive Earth Planetary Boundary Layer temperature and water vapor retrieval improvement demonstration by the use of hyperspectral microwave measurements. Our results indicate that the use of a hyperspectral sampling in the oxygen and water vapor sounding lines alone provides significant improvements in the lower and free tropospheric thermodynamic fields (up to 40%), when compared against the program of record (i.e., the Advanced Technology Microwave Sounder, ATMS). Our experiments also demonstrate the essential role played by extending the coverage in the so called spectral window regions, leading to an overall PBL temperature and water vapor improvement of up to 50%.

Characterizing the complex three-dimensional (3D) thermodynamic structure of the Planetary Boundary Layer (PBL) from a global perspective remains a challenge. As identified by the 2017 Decadal Survey and the NASA PBL Incubation Study Team Report (STR), enhanced horizontal and vertical resolution in PBL thermodynamic structure and PBL height from space-based sensors will facilitate major advances in Earth System science across a wide array of disciplines. Current Program of Record (POR) space-borne passive sounders (infrared, microwave) were not designed with a specific PBL focus. Consequently, current operational retrieval methods have limitations that preclude them from profiling PBL temperature and water vapor with the requirements expressed in the NASA PBL Incubation Study Team Report (STR). To that end, the report highlights the need for investing in optimal combinations of different remote sensing approaches and technologies spanning the active and passive field. In this framework, the study lists hyperspectral microwave sensors as an "Essential Component" of the future global PBL observing system, to provide accurate PBL and free tropospheric 3D temperature and water vapor structure context to active measurements (e.g., lidars and radars) and in combination with other passive sensors (e.g., infrared and radio occultation).

We have developed a process for evaluating future satellite-based hyperspectral microwave sensor designs using deep neural networks (DNN). Our approach combines a sophisticated simulated data product with a hierarchical deep neural network capable of comparing the relative performance of a variety of different microwave sounder configurations. These configurations include both spectral band coverage and resolution which allows for a thorough investigation of the solution space. The relative performance between these configurations as tested on the prediction of the planetary boundary layer height (PBLH) is used to perform the evaluation. We plan to extend this method to the prediction of entire temperature and water profiles to further refine this process.

This paper presents an overview of the Hyperspectral Microwave Photonic Instrument (HyMPI), a 2021 NASA Instrument Incubation Proposal funded project aimed at developing the very first hyperspectral microwave sensor to augment thermodynamic sounding capability from space, with a focus on the Earth's Planetary Boundary Layer. This research responds to the recommendation expressed in the 2018 National Academies of Sciences decadal survey to accelerate the readiness of high-priority PBL observables not feasible for cost-effective spaceflight in 2017–2027. This paper provides an overview on HyMPI's design, configured as the objective instrument concept needed to fly in the future PBL mission and presents preliminary trade studies aim at demonstrating HyMPI's enhanced thermodynamic sounding skill in the Earth's Planetary Boundary Layer over conventional microwave sounders from the current Program of Record.

We present an overview of the Hyperspectral Microwave Photonic Instrument (HyMPI), a NASA Instrument Incubation Proposal funded research project aimed at developing a hyperspectral microwave instrument intended for enhanced remote sensing of atmospheric temperature and water vapor from space. This paper provides preliminary results on HyMPI's spectral and noise characteristics and a preliminary demonstration of its enhanced water vapor sensitivity and vertical resolution, with a particular focus on the Earth's Planetary Boundary Layer.

This paper describes the Atmospheric Infrared Sounder (AIRS) Science Team Version 5 retrieval algorithm in terms of its three most significant improvements over the methodology used in the AIRS Science Team Version 4 retrieval algorithm: the use of AIRS clear-column radiances in the entire 4.3-μm CO2absorption band in the retrieval of temperature profiles T(p) during both day and night, with tropospheric sound ing of 15-μm CO2observations now being used primarily in the generation of clear-column radiances R̂ifor all channels; development of a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances and their use in a new approach for quality control; and an approach to provide AIRS soundings in partially cloudy conditions that does not require use of any microwave data. This new AIRS-only sounding methodology, referred to as AIRS Version 5 AO, was developed as a backup to AIRS Version 5 should the Advanced Microwave Sounding Unit (AMSU)-A instrument fail. Results are shown that compare the relative performance of the AIRS Version 4, Version 5, and Version 5 AO. Results using Version 5 retrievals in conjunction with different quality control thresholds are also shown for a recent period to demonstrate that empirical coefficients continue to be applicable in later time periods. The Goddard Data and Information Services Center (DISC) is now generating and distributing products derived using the AIRS Science Team Version 5 retrieval algorithm. This paper describes the quality control flags contained in the DISC AIRS/AMSU retrieval products and their intended use for scientific purposes.

AIRS was launched on EOS Aqua on May 4, 2002 together with ASMU-A and HSB to form a next generation polar orbiting infrared and microwave atmosphere sounding. The AIRS Science Team Version 6 retrieval system uses only shortwave CO2channels to determine temperature profile, and only window observations in the shortwave window region, 4.0 μm - 3.76 μm, to determine both surface skin temperatures and shortwave surface spectral emissivities. The current use of only shortwave AIRS channels in the retrieval of both atmospheric and surface parameters has resulted in significant improvement in the ability to obtain accurate temperature profiles and surface skin temperatures under more stressing partial cloud cover conditions than achieved previously. In this paper, we will show the improvement in retrieved Quality Controlled values of sea surface temperature and ocean spectral surface emissivity compared to those obtained using the AIRS Version-5 retrieval algorithm which used longwave and shortwave window observations simultaneously to determine surface parameters.

This paper presents the standard and research products from Atmospheric Infrared Sounder (AIRS) and their current accuracies as demonstrated through validation efforts. It also summarizes ongoing research using AIRS data for weather prediction and improving climate models.

New state-of-the-art methodology is described to analyze the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit/Humidity Sounder for Brazil (AIRS/AMSU/HSB) data in the presence of multiple cloud formations. The methodology forms the basis for the AIRS Science Team algorithm, which will be used to analyze AIRS/AMSU/HSB data on the Earth Observing System Aqua platform. The cloud-clearing methodology requires no knowledge of the spectral properties of the clouds. The basic retrieval methodology is general and extracts the maximum information from the radiances, consistent with the channel noise covariance matrix. The retrieval methodology minimizes the dependence of the solution on the first-guess field and the first-guess error characteristics. Results are shown for AIRS Science Team simulation studies with multiple cloud formations. These simulation studies imply that clear column radiances can be reconstructed under partial cloud cover with an accuracy comparable to single spot channel noise in the temperature and water vapor sounding regions; temperature soundings can be produced under partial cloud cover with RMS errors on the order of, or better than, 1 K in 1-km-thick layers from the surface to 700 mb, 1-km layers from 700-300 mb, 3-km layers from 300-30 mb, and 5-km layers from 30-1 mb; and moisture profiles can be obtained with an accuracy better than 20% absolute errors in 1-km layers from the surface to nearly 200 mb.

The apodization of an interferogram corresponds to a linear transformation in spectral space between unapodized and apodized radiances. Many apodization functions have well-behaved numerical inverse transformations, and we show an analytic inverse for the Hamming apodization function. The inverse transformation has many practical uses for remote sensing applications and can also be used theoretically to show the equivalence between unapodized spectra and properly apodized spectra. The inverse transformation, which is a representation of the discrete convolution theorem, can be used to readily convert computed apodized spectra to spectra computed for other symmetric apodization functions (including unapodized), which may have poorer characteristics with regard to calculating channel-transmittance parameters or radiances. We also show a quantitative method for comparing apodization functions of different mathematical forms.