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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Earth Observing-1 Advanced Land Imager: Imaging Performance On-Orbit

This report analyzes the on-orbit imaging performance of the Advanced Land Imager (ALI) on the Earth Observing-1 satellite. The pre-flight calibrations are first summarized. The methods used to reconstruct and geometrically correct the image data from this push-broom sensor are described. The method used here does not refer to the position and attitude telemetry from the spacecraft. Rather, it is assumed that the image of the scene moves across the focal plane with a constant velocity, which can be ascertained from the image data itself. Next, an assortment of the images so reconstructed is presented. Color images sharpened with the 10-m panchromatic band data are shown, and the algorithm for producing them from the 30-m multispectral data is described. The approach taken for assessing spatial resolution is to compare the sharpness of features in the on-orbit image data with profiles predicted on the basis of the pre-flight calibrations. A large assortment of bridge profiles is analyzed, and very good fits to the predicted shapes are obtained. Lunar calibration scans are analyzed to examine the sharpness of the edge-spread function at the limb of the moon. The darkness of the space beyond the limb is better for this purpose than anything that could be simulated on the ground. From these scans, we find clear evidence of scattering in the optical system, as well as some weak ghost images. Scans of planets and stars are also analyzed. Stars are useful point sources of light at all wavelengths, and delineate the point-spread functions of the system. From a quarter-speed scan over the Pleiades, we find that the ALI can detect 6th magnitude stars. The quality of the reconstructed images verifies the capability of the ALI to produce Landsat-type multi spectral data. The signal-to-noise and panchromatic spatial resolution are considerably superior to those of the existing Landsat sensors. The spatial resolution is confirmed to be as good as it was designed to be.

ALI (ADVANCED LAND IMAGER)↗
NASA NTRS2012

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 ~m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

Platnick, Steven↗
NASA NTRS2020

Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) Mission Integration and Testing

This paper describes the plans, flows, key facilities, components and equipment necessary to fully integrate, functionally test and qualify the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Observatory. PACE is currently in the design phase of mission implementation. It is scheduled to launch in 2022, extending and improving NASA's twenty-year record of satellite observations of global ocean biology, aerosols and clouds. PACE will advance the assessment of ocean health by measuring the distribution of phytoplankton, which are small plants and algae that sustain the marine food web. It will also continue systematic records of key atmospheric variables associated with air quality and the Earth's climate. The PACE observatory is comprised of the spacecraft and three instruments, an Ocean Color Instrument (OCI) and two polarimeters, the Hyper-Angular Rainbow Polarimeter 2 (HARP2) and the Spectro-Polarimeter for Exploration (SPEXone). The spacecraft and the OCI, which is the primary instrument, are developed and integrated at the NASA Goddard Space Flight Center (GSFC). The OCI is a hyper-spectral scanning (HSS) radiometer designed to measure spectral radiances from the ultraviolet to shortwave infrared (SWIR) to enable advanced ocean color and heritage cloud and aerosol particle science. The HARP2 and SPEXone are secondary instruments on the PACE observatory, acquired outside of GSFC. The Hyper-Angular Rainbow Polarimeter instrument (HARP2) is a wide swath imaging polarimeter that is capable of characterizing atmospheric aerosols for purposes of sensor atmospheric correction as well as atmospheric science. The SPEXone provides atmospheric aerosol and cloud data at high temporal and spatial resolution. This paper will focus on the Integration and Test (I&T) activities for the PACE mission at NASA GSFC. This I&T phase consists of mechanical, electrical and thermal integration and test of all the spacecraft subsystems and the integration of the instruments with the spacecraft. The PACE observatory environmental tests include electromagnetic interference (EMI)/electromagnetic compatibility (EMC), vibration, acoustics, shock, thermal balance, thermal vacuum, mass properties and center of gravity. This paper will also discuss the observatory shipment to the launch site as well as the launch site processing.

Petro, Susanna↗
NASA NTRS1988

Geological and vegetational applications of Shuttle Imaging Radar-B, Mineral County, Nevada

Multiple-incidence angle and multi-azimuth radar data were acquired from a Shuttle platform over test sites in Nevada in October 1984. An attempt was made to correlate these data with ground features for the purpose of evaluating the use of such data for geological and vegetational assessment. Standard ecological parameters with respect to the flora (community composition, dominance, and relative cover) were recorded in the field at the time of overflight. Although a total of 33 species representing 11 plant families were recognized, and plant cover ranged from 13 to 26 percent, radar data could not be used to separate plant communities. The signal return is more a function of abiotic conditions than vegetative characteristics. Illumination geometry plays an important role in the ability to detect strike-slip and dip-slip faults. Local incidence angle is the most important parameter, and SIR-B data takes with small incidence angles are superior for identifying certain styles of faulting. Look direction is critical for detecting faults with a dip-slip component. New structural features were not observed. Problems with radar antenna power and recording significantly affected data quality.

Borengasser, M. X.↗
NASA NTRS2022

QWIP: A Quantitative Metric for Quality Control of Aquatic Reflectance Spectral Shape using the Apparent Visible Wavelength

The colors of the ocean and inland waters span clear blue to turbid brown, and the corresponding spectral shapes of the waterleaving signal are diverse depending on the various types and concentrations of phytoplankton, sediment, detritus and colored dissolved organic matter. Here we present a simple metric developed from a global dataset spanning blue, green and brown water types to assess the quality of a measured or derived aquatic spectrum. The Quality Water Index Polynomial (QWIP) is founded on the Apparent Visible Wavelength (AVW), a one-dimensional geophysical metric of color that is inherently correlated to spectral shape calculated as a weighted harmonic mean across visible wavelengths. The QWIP represents a polynomial relationship between the hyperspectral AVW and a Normalized Difference Index (NDI) using red and green wavelengths. The QWIP score represents the difference between a spectrum’s AVW and NDI and the QWIP polynomial. The approach is tested extensively with both raw and quality controlled field data to identify spectra that fall outside the general trends observed in aquatic optics. For example, QWIP scores less than or greater than 0.2 would fail an initial screening and be subject to additional quality control. Common outliers tend to have spectral features related to: 1) incorrect removal of surface reflected skylight or 2) optically shallow water. The approach was applied to hyperspectral imagery from the Hyperspectral Imager for the Coastal Ocean (HICO), as well as to multispectral imagery from the Visual Infrared Imaging Radiometer Suite (VIIRS) using sensor-specific extrapolations to approximate AVW. This simple approach can be rapidly implemented in ocean color processing chains to provide a level of uncertainty about a measured or retrieved spectrum and flag questionable or unusual spectra for further analysis.

remote sensing reflectance↗
NASA NTRS1995

Extraction of ozone and chlorophyll-A distribution from AVIRIS data

The potential of airborne imaging spectrometry for assessing and monitoring natural resources is studied. Therefore, an AVIRIS scene of the NASA's MacEurope 1991 campaign - acquired in Central Switzerland - is used. The test site consists of an urban area, the Lake Zug with its surrounding fields, the Rigi mountain in the center of the test site, and the Lake of Four Cantons. The region is covered by the AVIRIS flight #910705, run 6 and 7 of the NASA ER-2 aircraft resulting in an average nominal pixel size of about 18 m. Simultaneous to the ER-2 overflight spectroradiometric measurements have been taken in various locations. Preselected reference targets were measured in the field with a GER Mark V spectroradiometer, and radiance measurements were taken to the lake using a Li-Cor LI 1800UW specroradiometer below and above the water surface. A comprehensive meteorological data set was obtained by joining the POLLUMET experiment which carried out measurements to investigate the summer smog in Switzerland on the same day. The quality assessment for the actual data set can be found in detail in Meyer et al. A parametric approach calculating the location of the airplane was used to simulate the observation geometry. This parametric preprocessing procedure, which takes care of effects of flight line and attitude variations as well as the pixel-by-pixel topographic corrections is described in Meyer.

Schaepman, M.↗
NASA NTRS2014

Ocean Color Measurements from Landsat-8 OLI using SeaDAS

The Operational Land Imager (OLI) is a multi-spectral radiometer hosted on the recently launched Landsat-8 satellite. OLI includes a suite of relatively narrow spectral bands at 30-meter spatial resolution in the visible to shortwave infrared that make it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in SeaDAS, which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of satellite-based multi-spectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote-sensing reflectance (Rrs; sr exp 1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents such as the concentration of the phytoplankton pigment chlorophyll a.

ocean color↗
DOE OSTI2021

Development of a Miniaturized Mobile Mapping System for In-Row, Under-Canopy Phenotyping

This paper focuses on the development of a miniaturized mobile mapping platform with advantages over current agricultural phenotyping systems in terms of acquiring data that facilitate under-canopy plant trait extraction. The system is based on an unmanned ground vehicle (UGV) for in-row, under-canopy data acquisition to deliver accurately georeferenced 2D and 3D products. The paper addresses three main aspects pertaining to the UGV development: (a) architecture of the UGV mobile mapping system (MMS), (b) quality assessment of acquired data in terms of georeferencing information as well as derived 3D point cloud, and (c) ability to derive phenotypic plant traits using data acquired by the UGV MMS. The experimental results from this study demonstrate the ability of the UGV MMS to acquire dense and accurate data over agricultural fields that would facilitate highly accurate plant phenotyping (better than above-canopy platforms such as unmanned aerial systems and high-clearance tractors). Plant centers and plant count with an accuracy in the 90% range have been achieved.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Assessment of Sensor Footprint Size and Comparison of Commercial Smallsat Images

Science users of commercial satellite data build their studies on the properties of the satellite data they work with, pixel size being one of the determining factors. However, pixel size and nominal image footprint size can be different, impacting the scale of features discernable in the satellite images. Here, we assess geometric properties such as nominal image footprint size for Planet Labs' SuperDove series, MAXAR's WorldView series, and potentially BlackSky. Additionally, we assess temporal change in nominal footprint size for the SuperDove series. Nominal Image footprint size is assessed over the CalVal sites in Baotou, China; Shadnagar, India; and Big Spring, TX. Edge spread functions are constructed along the black/white transitions, from which the line spread functions are constructed and modulation transfer functions of the scene are estimated. Scene full width half maximum (FWHM), which represents sensor footprint size, is estimated from the line spread function. The average nominal footprint size is 3.3 pixels for SuperDove series, 1.5 pixels for WorldView-2, and 1.3 pixels for WorldView-3. The SuperDove series nominal footprint size improves with time in orbit, from an average of 3.4 pixels soon after launch to an average of 3.2 pixels one or more years after launch.

PlanetScope↗
DOE OSTI2025

Experimental Evaluation of Interfacial Bonding Strength Between 304 Stainless Steel Substrate and Electrodeposited Nickel Coating Using Mesoscale Mechanical Testing Methods

Electrodeposition is a commonly used method for depositing a metal layer on a metallic substrate, to provide a decorative finish or for functional purposes including wear and corrosion resistance. The interfacial bonding strength is a critical factor in determining the quality of electrodeposition, as it ensures the adhesion of the deposited layer to the substrate. Despite its importance, there has not previously been a suitable mechanical testing method to quantitatively characterize the bonding strength between the electrodeposited layers and the substrate, due to the high strength of the materials and to restrictions imposed by the geometry (due to the small thickness of the plating layer) to manufacture tensile bars. In this study, we introduce a novel mesoscale mechanical testing method to overcome these limitations. This technique was applied to assess the bonding strength between a 304 stainless steel (SS) substrate and electrodeposited nickel with three different plating formulae (nickel sulfamate, Watts bath, and hard nickel). The thickness of the pure nickel coatings achieved for each of the three electrolyte solutions was approximately 1 mm on each side of the substrate. Mesoscale tensile bars of 1 mm length were manufactured by a femtosecond laser, with the material interface at the center of the gauge section, and then tensile-tested with digital image correlation. Further, the results proved that the electrodeposition technique is able to produce a very high bonding strength that is close to the yield strength of both the substrate material and the electrodeposited nickel layer. Additionally, in the case of the Watts bath formula, the interfacial bonding strength between the SS 304 and electrodeposited nickel can exceed that of the nickel layer. This method is expected to be useful for quantifying the interfacial bonding strength in numerous applications.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Ocean Color Measurements with the Operational Land Imager on Landsat-8: Implementation and Evaluation in SeaDAS

The Operational Land Imager (OLI) is a multispectral radiometer hosted on the recently launched Landsat8 satellite. OLI includes a suite of relatively narrow spectral bands at 30 m spatial resolution in the visible to shortwave infrared, which makes it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS), which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of spaceborne multispectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote sensing reflectance (Rrs; sr−1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents, such as the concentration of the phytoplankton pigment chlorophyll a.

Measurements↗
NASA NTRS2016

The Role of Cloud Contamination, Aerosol Layer Height and Aerosol Model in the Assessment of the OMI Near-UV Retrievals Over the Ocean

Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD less than 0.3, 30% for AOD greater than 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm approximately less than 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (less than 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that the spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. In addition, it is demonstrated in an example how an incorrect assumption of the aerosol height can lead to an underestimate. Nevertheless, this is not as significant as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

aerosols↗
DOE OSTI2021

Transverse mode analysis for free-space laser beams using Bayesian analysis

Reliable and rapid assessment of the transverse mode quality of a free-space laser beam has a wide range of applications in laser development, research, and utilization. It has become even more important with recent advances in developing orbital angular momentum photon beams across a broad spectral region. In this work, a general modal analysis method for a free-space multimode laser beam has been developed based on Bayesian analysis. After transforming mode decomposition into a linear system problem, a Gaussian probabilistic model is used to find a closed-form solution. The method is found to be robust with the presence of Gaussian noise. Prior knowledge about the mode content can be incorporated into the method to improve the solution for situations when coherent disturbances or contamination are present in the laser beam. This method can be used to analyze the mode content for laser beams in different bases, such as Hermite–Gaussian (HG) modes and Laguerre–Gaussian (LG) modes. Three applications of this method are presented: a detailed modal analysis of the beam image from the incoherent intensity addition of HG modes and two examples of mode decomposition using the complex wavefront from the coherent superposition of HG and LG modes. The feasibility of this method is demonstrated using various simulation results. Based on digital images of a laser beam recorded without complex wavelength-limiting optics, in principle, this method can be used in a wide wavelength range from infrared to ultraviolet, and possibly x ray.

Liu, Peifan (ORCID:0000000273816153)↗
DOE OSTI2023

Crystallographic variant mapping using precession electron diffraction data

In this work, we developed three methods to map crystallographic variants of samples at the nanoscale by analyzing precession electron diffraction data using a high-temperature shape memory alloy and a VO2 thin film on sapphire as the model systems. The three methods are (I) a user-selecting-reference pattern approach, (II) an algorithm-selecting-reference-pattern approach, and (III) a k-means approach. In the first two approaches, Euclidean distance, Cosine, and Structural Similarity (SSIM) algorithms were assessed for the diffraction pattern similarity quantification. We demonstrated that the Euclidean distance and SSIM methods outperform the Cosine algorithm. We further revealed that the random noise in the diffraction data can dramatically affect similarity quantification. Denoising processes could improve the crystallographic mapping quality. With the three methods mentioned above, we were able to map the crystallographic variants in different materials systems, thus enabling fast variant number quantification and clear variant distribution visualization. The advantages and disadvantages of each approach are also discussed. We expect these methods to benefit researchers who work on martensitic materials, in which the variant information is critical to understand their properties and functionalities.

Crystallographic variant mapping↗
NASA NTRS1999

Impact of a Merged Precipitation Data on Global Soil Moisture Variability

Accurate soil moisture information has proved to be important to climate simulations and climate and weather forecasts. However, many difficulties exist that limit our understanding of soil moisture distribution and variability. One of them is the lack of accurate precipitation with appropriate spatial and temporal resolution. Precipitation as an input forcing to the land surface greatly influences soil moisture characteristics and variability. To improve precipitation data quality, an algorithm has been developed to generate a spatially and temporally continuous 3-hourly global precipitation data for the period of 1987 to present. This precipitation product is a combination of the precipitation from Special Sensor Microwave Imager (SSMI) with the Goddard Earth Observing System-1 Data Assimilation System (GEOS-1 DAS) employing a Physical-space Statistical Analysis System (PSAS). In this study we investigate the impact of this merged/analyzed precipitation data on the global soil moisture variability using an Off-line Land-surface GEOS Assimilation (OLGA) system. Two OLGA integrations starting from 1987 to 1993 are performed forced with the analyzed and GEOS-1 DAS precipitation respectively. We examine the spatial and temporal characteristics of soil moisture variability in response to the analyzed precipitation. The influence of this merged precipitation on the soil moisture variability and regional hydrological budget is estimated throughout the comparison with the results forced with the GEOS-1 DAS precipitation only. In the OLGA the sut@-grid scale horizontal heterogeneity is explicitly represented on the tile space. This provides a means to assess the role of the surface moisture heterogeneity in the interaction with the surface atmosphere and surface hydrological budget, and to validate OLGA results at tile space with in situ observation. ABRACOS (Anglo-Brazilian Amazonian Climate Observation Study), FIFE (First ISLSCP Field Experiment) I and HAPEX data will be used in the validation.

Yang, Runhua↗
DOE OSTI2020

Candidate Periodically Variable Quasars from the Dark Energy Survey and the Sloan Digital Sky Survey

Periodically variable quasars have been suggested as close binary supermassive black holes. We present a systematic search for periodic light curves in 625 spectroscopically confirmed quasars with a median redshift of 1.8 in a 4.6 deg 2 overlapping region of the Dark Energy Survey Supernova (DES-SN) fields and the Sloan Digital Sky Survey Stripe 82 (SDSS-S82). Our sample has a unique 20-year long multi-color ( griz ) light curve enabled by combining DES-SN Y6 observations with archival SDSS-S82 data. The deep imaging allows us to search for periodic light curves in less luminous quasars (down to r ~23.5 mag) powered by less massive black holes (with masses ≳ 10 8.5 M ⊙ ) at high redshift for the first time. We find five candidates with significant (at >99.74% single-frequency significance in at least two bands with a global p-value of ~7 × 10 -4 –3× 10 -3 accounting for the look-elsewhere effect) periodicity with observed periods of ~3–5 years (i.e., 1–2 years in rest frame) having ~4–6 cycles spanned by the observations. If all five candidates are periodically variable quasars, this translates into a detection rate of |${\sim }0.8^{+0.5}_{-0.3}$| % or |${\sim }1.1^{+0.7}_{-0.5}$| quasar per deg 2 . Our detection rate is 4–80 times larger than those found by previous searches using shallower surveys over larger areas. This discrepancy is likely caused by differences in the quasar populations probed and the survey data qualities. Furthermore, we discuss implications on the future direct detection of low-frequency gravitational waves. Additionally, continued photometric monitoring will further assess the robustness and characteristics of these candidate periodic quasars to determine their physical origins.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1992

SeaWiFS technical report series. Volume 1: An overview of SeaWiFS and ocean color

The purpose of this series of technical reports is to provide current documentation of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project activities, instrument performance, algorithms, and operations. This documentation is necessary to ensure that critical information related to the quality and calibration of the satellite data is available to the scientific community. SeaWiFS will bring to the ocean community a welcomed and improved renewal of the ocean color remote sensing capability lost when the Nimbus-7 Coastal Zone Color Scanner (CZCS) ceased operating in 1986. The goal of SeaWiFS, scheduled to be launched in August 1993, is to examine oceanic factors that affect global change. Because of the role of phytoplankton in the global carbon cycle, data obtained from SeaWiFS will be used to assess the ocean's role in this cycle, as well as other biogeochemical cycles. SeaWiFS data will be used to help elucidate the magnitude and variability of the annual cycle of primary production by marine phytoplankton and to determine the distribution and timing of spring blooms. The observations will help to visualize the dynamics of ocean and costal currents, the physics of mixing, and the relationships between ocean physics and large-scale patterns of productivity. The data will help fill the gap in ocean biological observations between those of the CZCS and the upcoming Moderate Resolution Imaging Spectrometer (MODIS) on the Earth Observing System-A (EOS-A) satellite.

Hooker, Stanford B.↗
NASA NTRSDate not supplied

Evaluation of Aerosol Data Assimilation and Forecasts in the NASA GEOS Model during the ASIA-AQ Campaign

Fine particulate matter (PM2.5) poses significant risks to human health and the environment by penetrating the lungs and causing respiratory and cardiovascular diseases, making it crucial to understand its sources and behavior for effective air quality management. The Goddard Earth Observing System (GEOS) Forward Processing (FP) system model, operated by the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center, provides real-time weather and aerosol analyses and forecasts. In addition to meteorological data assimilation, the GEOS-FP system also assimilates aerosol using Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and Aerosol Robotic Network (AERONET) AOD data. In this study, the aerosol data assimilation and forecasts performance of the GEOS-FP model were evaluated for predicting PM2.5 in Korea using observations from the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign. The ASIA-AQ campaign, an international collaborative field study initiative, aims to enhance understanding of local air quality issues and address common challenges in interpreting satellite data and air quality modeling. Conducted in South Korea from February 15 to March 13, 2024, during the high PM2.5 concentration winter season, this campaign provided extensive airborne and ground observations for intensive analysis of PM2.5 model simulations. We demonstrate how the assimilation runs and the forecasting performance of PM2.5 at 24-hour and 48-hour intervals vary. Additionally, we analyzed the differences and characteristics of PM2.5 composition in cases of long-range transport and local emissions. Using ASIA-AQ airborne data, we also examined the vertical profile of fine particulate matter. Through the intensive observations of this campaign, the GEOS model was assessed over South Korea using both in situ and airborne measurements to establish a baseline and identify priorities for future development.

Seunghee Lee↗