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NASA NTRS2007

Remote Sensing of the Radiative and Microphysical Properties of Clouds during TC4: Results from MAS, MASTER, MODIS, and MISR

The MODIS Airborne Simulator (MAS) and MODIS/ASTER Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.3 (12.9 m for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Clouds and Climate Coupling Experiment (TC4) conducted over Central America and surrounding Pacific and Atlantic Oceans between July 17 and August 8, 2007. Multispectral images in eight distinct bands were used to derive a confidence in clear sky (or alternatively the probability of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of this cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm as that implemented operationally to process MODIS cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER date in TC4, is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals used three distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to MISR data to infer the cloud optical thickness of liquid water clouds from MISR. Results of this analysis will be presented and discussed.

King, Michael D.↗
NASA NTRS2010

Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

King, Michael D.↗
NASA NTRS2008

The Time Series Technique for Aerosol Retrievals over Land from MODIS: Algorithm MAIAC

Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the 2.1 m channel (B7) for the purpose of aerosol retrieval. Obviously, the subsequent atmospheric correction will produce the same SR in the red and blue bands as predicted, i.e. an empirical function of 2.1. In other words, the spectral, spatial and temporal variability of surface reflectance in the Blue and Red bands appears borrowed from band B7. This may have certain implications for the vegetation and global carbon analysis because the chlorophyll-sensing bands B1, B3 are effectively substituted in terms of variability by band B7, which is sensitive to the plant liquid water. This chapter describes a new recently developed generic aerosol-surface retrieval algorithm for MODIS. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm simultaneously retrieves AOT and surface bi-directional reflection factor (BRF) using the time series of MODIS measurements.

Lyapustin, Alexei↗
NASA NTRS2021

Calibration of the DSCOVR EPIC Visible and NIR Channels using Multiple LEO Radiometers

The first five years of operation of the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) at the Lagrange one point have produced results that uniquely complement the data from currently operating low orbit Earth-observing instruments. In this paper we describe an updated unified approach to EPIC calibration. In this approach, calibration coefficients and their trends were obtained by comparing EPIC observations to the measurements from polar orbiting radiometers. In this study L1B reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua and Terra satellites, Multi-angle Imaging Spectroradiometer (MISR) onboard Terra and Visible Infrared Imaging Radiometer (VIIRS) onboard the Suomi National Polar-orbiting Partnership (Suomi NPP) spacecraft were used to infer calibration coefficients for four EPIC visible and near-infrared channels: 443 nm, 551 nm, 680 nm, and 780 nm. EPIC Version three measurements made between June 2015 and August 2020 were used for comparison. The calibration procedure identifies the most homogeneous low Earth orbit radiometer scenes matching scattering angles that are temporarily and spatially collocated with EPIC observations. These scenes are used to determine reflectance to count (R/C) ratios in spectrally analogous channels. Seasonal average R/C ratios were analyzed to obtain EPIC calibration gains and trends. The trends for the full dataset period are not statistically significant except in the 443 nm channel. No significant changes in calibration were found after the instrument’s exit from safe hold in March 2020. The R/C ratios were also used to determine the differences in EPIC gains resulting from separate calibrations: against MODIS Aqua or Terra, as well as against forward or aftward MISR cameras. Statistical tests indicate that the differences between the two datasets are not significant except in the 780 nm channels where Aqua-derived coefficients may be around 2% lower compared to Terra. The dependence of EPIC calibration gains on the instrument scattering angle and on DSCOVR-Earth distance were investigated. Lastly, model Low Earth Orbit (LEO) reflectances calculated to match the EPIC viewing geometry were employed to study how EPIC calibration coefficients depend on EPIC-LEO viewing geometry differences. The effect of LEO and EPIC angular mismatch on calibration was shown to be small.

deep space climate observatory/earth polychromatic↗
NASA NTRS2020

Pacific Northwest Health & Air Quality - Utilizing NASA Earth Observations to Analyze Air Quality Impacts from Wildfires in the Pacific Northwest

The Pacific Northwest region of the United States and Canada has become more vulnerable to intense wildfire regimes due to years of fire suppression and climatic changes. Smoke from fires exposes communities to hazardous aerosols and pollutants known to trigger asthma symptoms and exacerbate other respiratory and cardiovascular diseases. In partnership with The Nature Conservancy’s Washington Chapter and the Puget Sound Clean Air Agency, NASA DEVELOP investigated the impacts of wildfire smoke on air quality from 2008 to 2020 using NASA Earth observations. To explore the various dimensions of smoke and its relation to air quality, the team looked at the vertical extent of smoke plumes and the resulting changes in air quality. The team evaluated the potential relationship between plume height of wildfire smoke and fire radiative power using the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellites and Terra’s Multi-angle Imaging SpectroRadiometer (MISR) using the MISR INteractive eXplorer (MINX). The team determined that there was no regional relationship between fire radiative power and smoke plume height. To investigate changes in air quality resulting from wildfire smoke, the team utilized data from NASA’s Fire Information for Resource Management System, from the European Space Agency’s Sentinel-5P Tropospheric Monitoring Instrument (TROPOMI), and true color imagery from Landsat 8 Operational Land Imager (OLI). The team created a Google Earth Engine-based (GEE) web tool to visualize changes in atmospheric pollutants and aerosol optical depth. Results of case study fires showed varying increases in pollutant concentrations when compared to a baseline map. The end products provided the partners with tools to quantify plume height using MINX and to visualize recent air quality patterns relating to variations in wildfire extent and severity in the Pacific Northwest

Ani Matevosian↗
NASA NTRS2023

Comparison of Dust Optical Depth From Multi-Sensor Products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) Dust Reanalysis Over North Africa, the Middle East, and Europe

Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.

Michail Mytilinaios↗
NASA NTRS2019

EDOS Initiatives to Decrease Latency of NRT Data for LANCE

NASA's EOS Data and Operations System (EDOS) is the primary supplier of NRT (near real-time) data to the NASA NRT user community known as the Land, Atmosphere NRT Capability for EOS (LANCE). EDOS provides NRT data for various instruments on the EOS missions Terra, Aqua, Aura, as well as for the NOAA missions Suomi NPP and NOAA-20. This poster describes an overview of the EDOS multi-mission system with emphasis on the NRT products distributed for LANCE elements: AIRS, MISR, MLS, MODIS, MOPITT, OMPS, OMI and VIIRS. Remote EDOS high-rate data capture systems are deployed at NASA ground stations which provide data-driven capture of high-rate science for EOS missions. The remote EDOS components transfer the science data via high-rate WANs to the centralized EDOS Level-zero processing systems located at Goddard Space Flight Center. EDOS produces session-based data sets especially for LANCE NRT use from a single ground station contact; this data is sent to dual LANCE destinations as part of the standard redundancy requirement for LANCE elements. EDOS has implemented various latency improvements with the ultimate goal to have EDOS processing of NRT data keep up with the spacecraft data downlink. EDOS enhancements have included implementation of priority-based QoS, expanded network architecture to include open networks, and use of a delay-tolerant protocol. EDOS has streamlined its systems and infrastructure to minimize latency for NRT data delivery for LANCE. EDOS begins to transfer the NRT data to the LANCE elements within minutes of the end of the contact session with an average packet latency from instrument observation to Level 0 product delivery to each LANCE element of just over one hour.

Michael, Karen↗
NASA NTRS2000

Recent Results From The Nasa Earth Science Terra Mission and Future Possibilities

The NASA Earth Sciences Enterprise has made some remarkable strides in recent times in using developing, implementing, and utilizing spaceborne observations to better understand how the Earth works as a coupled, interactive system of the land, ocean, and atmosphere. Notable examples include the Upper Atmosphere Research (UARS) Satellite, the Topology Ocean Experiment (TOPEX) mission, Landsat-7, SeaWiFS, the Tropical Rainfall Monitoring Mission (TRMM), Quickscatt, the Shuttle Radar Topography Mission (SRTM), and, quite recently, the Terra'/Earth Observing System-1 mission. The Terra mission, for example, represents a major step forward in providing sensors that offer considerable advantages and progress over heritage instruments. The Moderate Resolution Imaging Spectrometer (MODIS), the Multi-angle Imaging SpectroRadiometer (MISR), the Measurements of Pollution in the Troposphere (MOPITT), the Advanced Spaceborne Thermal Emissions and Reflections (ASTER) radiometer, and the Clouds and Earth's Radiant Energy System (CERES) radiometer are the instruments involved. Early indications in March indicate that each of these instruments are working well and will be augmenting data bases from heritage instruments as well as producing new, unprecedented observations of land, ocean, and atmosphere features. Several missions will follow the Terra mission as the Earth Observing mission systems complete development and go into operation. These missions include EOS PM-1/'Aqua', Icesat, Vegetation Canopy Lidar (VCL), Jason/TOPEX Follow-on, the Chemistry mission, etc. As the Earth Observing systems completes its first phase in about 2004 a wealth of data enabling better understanding of the Earth and the management of its resources will have been provided. Considerable thought is beginning to be placed on what advances in technology can be implemented that will enable further advances in the early part of the 21st century; e.g., in the time from of 2020. Concepts such as 'constellation' missions or 'formation flying' with 'sensorcraft', 'sensor webs', autonomous operation of satellites, more on-board processing and delivery to individual users, data synthesis and analysis in real-time, etc. are being considered. With the data now having been and soon to be received plus the very real possibilities of further advances in use and applicability of data the potential for very significant gains in knowledge for Earth studies and applications looks quite high in the next decade or two.

Salomonson, Vincent V.↗
NASA NTRS2026

Satellite Optical Remote Sensing of Clouds and Aerosols: From Particle Single-Scattering and Gaseous Absorption Through Radiative Transfer to Retrieval Products

Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.

Aerosols↗
NASA NTRS2005

Airborne Sunphotometer and Solar Spectral Flux Radiometer Measurements During INTEX/ITCT 2004

During the period 12 July - 8 August 2004, the NASA Ames 14-channel Airborne Tracking Sunphotometer (MTS-14) and Solar Spectral Flux Radiometer (SSFR) were operated aboard a Jetstream 31 (J31) aircraft and acquired measurements during nineteen science flights (approx. 53 flight hours) over the Gulf of Maine in support of the INTEX-NA (INtercontinental chemical Transport Experiment-North America) and ITCT (Intercontinental Transport and Chemical Transformation of anthropogenic pollution) field studies. In this paper, we will present results from analyses of those data sets. AATS-14 measures the direct solar beam transmission at fourteen discrete wavelengths (354-2138 nm), and provides instantaneous measurements of aerosol optical depth (AOD) spectra and water vapor column content, in addition to vertical profiles of aerosol extinction and water vapor density during suitable aircraft ascents and descents. SSFR consists of separate nadir and zenith viewing hemispheric FOV sensors that yield measurements of up- and downwelling solar irradiance at a spectral resolution of approx. 8-12 nm over the wavelength range 300-1700 nm. The objectives of the J31-based measurements during INTEX/ITCT were to provide AOD data for the evaluation of MODIS (MODerate-resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectro-Radiometer) AOD retrievals, quantify sea surface spectral albedo (which can contribute the largest uncertainty to satellite aerosol retrievals for low aerosol loading), test closure (consistency) among suborbital results, test chemical-transport models using AOD profiles, and assess regional radiative forcing by combining satellite and suborbital results. Specific J31 flight patterns were designed to achieve these objectives, and they included a mixture of vertical profiles (spiral and ramped ascents and descents) and constant altitude horizontal transects at a variety of altitudes. Additional information is included in the original extended abstract.

Russell, P. B.↗
NASA NTRSDate not supplied

The Plankton, Aerosol, Cloud, Ocean Ecosystem (Pace) Mission Overview: From Concept to Launch

Abstract for Technical Review: The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission is a strategic climate continuity mission that was defined in the 2010 document Responding to the Challenge of Climate and Environmental Change: NASA’s Plan for Climate-Centric Architecture for Earth Observations and Applications from Space (referred to as the “Climate Initiative”). Launched in February 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. PACE will extend the high quality ocean ecological, ocean biogeochemical, cloud, and aerosol particle data records begun by NASA in the 1990s, building on the exceptional heritages of the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Multi-angle Imaging SpectroRadiometer (MISR), and the Visible Infrared Imaging Radiometer Suite (VIIRS). NASA Headquarters directed the mission development and implementation to the NASA Goddard Space Flight Center (GSFC) with guidance to utilize a Design-to-Cost (DTC) process. Mission studies were conducted to define appropriate approaches within and across elements while maximizing science capabilities at a high cost confidence. Mission baseline requirements development is also embedded within the DTC process, as these requirements were not established at the onset of the mission concept development. The PACE project office at NASA’s GSFC was responsible for the satellite development, launch and commissioning. The NASA Headquarters PACE Program Science office is responsible for supporting the science data processing system and assembling competed community science teams, which includes field-based vicarious calibration and data product validation efforts to support the PACE Project Science team. The PACE observatory is comprised of three instruments, the Ocean Color Instrument (OCI) and two polarimeters, the Hyper-Angular Rainbow Polarimeter 2 (HARP2) and the Spectro-Polarimeter for Exploration (SPEXone) and the PACE spacecraft. The observatory has been commissioned and is performing on-orbit science data collection operations. Summary for Program: The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission is a strategic climate continuity mission that was defined in the 2010 document Responding to the Challenge of Climate and Environmental Change: NASA’s Plan for Climate-Centric Architecture for Earth Observations and Applications from Space (referred to as the “Climate Initiative”). Launched in February 2024 under the leadership of the NASA Goddard Space Flight Center (GSFC), the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. PACE will extend the high quality ocean ecological, ocean biogeochemical, cloud, and aerosol particle data records begun by NASA in the 1990s. The PACE observatory is comprised of the Ocean Color Instrument (OCI), the Hyper-Angular Rainbow Polarimeter 2 (HARP2) and the Spectro-Polarimeter for Exploration (SPEXone), along with the PACE spacecraft.

Robert H Estep, Jr↗
NASA NTRSDate not supplied

Mission Overview and Status from Concept to Launch

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission is a strategic climate continuity mission that was defined in the 2010 document Responding to the Challenge of Climate and Environmental Change: NASA’s Plan for Climate-Centric Architecture for Earth Observations and Applications from Space (referred to as the “Climate Initiative”). Launched in February 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. PACE will extend the high quality ocean ecological, ocean biogeochemical, cloud, and aerosol particle data records begun by NASA in the 1990s, building on the exceptional heritages of the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Multi-angle Imaging SpectroRadiometer (MISR), and the Visible Infrared Imaging Radiometer Suite (VIIRS). NASA Headquarters directed the mission development and implementation to the NASA Goddard Space Flight Center (GSFC) with guidance to utilize a Design-to-Cost (DTC) process. Mission studies were conducted to define appropriate approaches within and across elements while maximizing science capabilities at a high cost confidence. Mission baseline requirements development is also embedded within the DTC process, as these requirements were not established at the onset of the mission concept development. The PACE project office at NASA’s GSFC was responsible for the satellite development, launch and commissioning. The NASA Headquarters PACE Program Science office is responsible for supporting the science data processing system and assembling competed community science teams, which includes field-based vicarious calibration and data product validation efforts to support the PACE Project Science team. The PACE observatory is comprised of three instruments, the Ocean Color Instrument (OCI) and two polarimeters, the Hyper-Angular Rainbow Polarimeter 2 (HARP2) and the Spectro-Polarimeter for Exploration (SPEXone) and the PACE spacecraft. The observatory has been commissioned and is performing on-orbit science data collection operations. Summary for Program: The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission is a strategic climate continuity mission that was defined in the 2010 document Responding to the Challenge of Climate and Environmental Change: NASA’s Plan for Climate-Centric Architecture for Earth Observations and Applications from Space (referred to as the “Climate Initiative”). Launched in February 2024 under the leadership of the NASA Goddard Space Flight Center (GSFC), the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. PACE will extend the high quality ocean ecological, ocean biogeochemical, cloud, and aerosol particle data records begun by NASA in the 1990s. The PACE observatory is comprised of the Ocean Color Instrument (OCI), the Hyper-Angular Rainbow Polarimeter 2 (HARP2) and the Spectro-Polarimeter for Exploration (SPEXone), along with the PACE spacecraft.

Robby Estep↗
NASA NTRS2019

Validation, Comparison, and Integration of GOCI, AHI, MODIS, MISR, and VIIRS Aerosol Optical Depth Over East Asia During the 2016 KORUS-AQ Campaign

Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5∘×0.5∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

Myungje Choi↗
NASA NTRS2001

ACE-Asia Aerosol Optical Depth and Water Vapor Measured by Airborne Sunphotometers and Related to Other Measurements and Calculations

In the Spring 2001 phase of the Asian Pacific Regional Aerosol Characterization Experiment (ACE-Asia), the 6-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) operated on 15 of the 19 research flights of the NCAR C-130, while its 14-channel counterpart (AATS- 14) flew successfully on all 18 research flights of the CIRPAS Twin Otter. ACE-Asia studied aerosol outflow from the Asian continent to the Pacific basin. It was designed to integrate suborbital and satellite measurements and models so as to reduce the uncertainty in calculations of the climate forcing due to aerosols. AATS-6 and AATS-14 measured solar beam transmission at 6 and 14 wavelengths (380-1021 and 354-1558 nm, respectively), yielding aerosol optical depth (AOD) spectra and column water vapor (CWV). Vertical differentiation in profiles yielded aerosol extinction spectra and water vapor concentration. The wavelength dependence of these AOD and extinction spectra indicates that supermicron dust was often a major component of the ACE-Asia aerosol. Frequently this dust-containing aerosol extended to high altitudes. For example, in AATS- 14 profiles analyzed to date, 36% of full-column AOD at 525 nm was above 3 km. In contrast, only 10% of CWV was above 3 km. Analyses and applications of AATS-6 and AATS-14 data to date include comparisons to (i) extinction products derived using in situ measurements, (ii) extinction profiles derived from lidar measurements, and (iii) AOD retrievals from the Multi-angle Imaging Spectro-Radiometer (MISR) aboard the TERRA satellite. Other planned collaborative studies include comparisons to results from size spectrometers, chemical measurements, other satellite sensors, flux radiometers, and chemical transport models. Early results of these studies will be presented.

Livingston, John M.↗
NASA NTRS2001

Airborne Sunphotometry of Aerosol Optical Depth and Columnar Water Vapor During ACE-Asia

During the Intensive Field Campaign (IFC) of the Aerosol Characterization Experiment - Asia (ACE-Asia), March-May 2001, the 6-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) operated during 15 of the 19 research flights aboard the NCAR C- 130, while its 14-channel counterpart (AATS- 14) was flown successfully on all 18 research flights of a Twin Otter aircraft operated by the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS), Monterey, CA. ACE-Asia was the fourth in a series of aerosol characterization experiments and focused on aerosol outflow from the Asian continent to the Pacific basin. Each ACE was designed to integrate suborbital and satellite measurements and models so as to reduce the uncertainty in calculations of the climate forcing due to aerosols. The Ames Airborne Tracking Sunphotometers measured solar beam transmission at 6 (380-1021 nm, AATS-6) and 14 wavelengths (353-1558 nm, AATS-14) respectively, yielding aerosol optical depth (AOD) spectra and column water vapor (CWV). Vertical differentiation in profiles yielded aerosol extinction and water vapor concentration. The wavelength dependence of AOD and extinction indicates that supermicron dust was often a major component of the aerosol. Frequently this dust-containing aerosol extended to high altitudes. For example, in data flights analyzed to date 34 +/- 13% of full-column AOD(525 nm) was above 3 km. In contrast, only 10 +/- 4% of CWV was above 3 km. In this paper, we will show first sunphotometer-derived results regarding the spatial variation of AOD and CWV, as well as the vertical distribution of aerosol extinction and water vapor concentration. Preliminary comparison studies between our AOD/aerosol extinction data and results from: (1) extinction products derived using in situ measurements and (2) AOD retrievals using the Multi-angle Imaging Spectro-Radiometer (MISR) aboard the TERRA satellite will also be presented.

Redemann, Jens↗
NASA NTRS2000

Airborne Sunphotometry of African Dust and Marine Boundary Layer Aerosols in PRIDE

The Puerto Rico Dust Experiment (PRIDE) was conducted during summer 2000 to study the radiative, microphysical and transport properties of Saharan dust in the Caribbean region. During PRIDE, NASA Ames Research Center's six-channel airborne autotracking sunphotometer (AATS-6) was operated aboard a Piper Navajo airplane based at Roosevelt Roads Naval Station on the northeast coast of Puerto Rico. AATS-6 measurements were taken during 21 science flights off the coast of Puerto Rico in the western Caribbean. Data were acquired within and above the Marine Boundary Layer (MBL) and the Saharan Aerosol Layer (SAL) up to 5.5 km altitude tinder a wide range of dust loadings. Aerosol optical depth (AOD) spectra and columnar water vapor (CWV) values have been calculated from the AATS-6 measurements by using sunphotometer calibration data obtained at Mauna Loa Observatory (3A kin ASL) before (May) and after (October) PRIDE. Mid-visible AOD values measured near the surface during PRIDE ranged from 0.07 on the cleanest day to 0.55 on the most turbid day. Values measured above the MBL were as high as 0.35; values above the SAL were as low as 0.01. The fraction of total column AOD due to Saharan dust cannot be determined precisely from AATS-6 AOD data alone due to the uncertainty in the extent of vertical mixing of the dust down through the MBL. However, analyses of ground-based and airborne in-situ aerosol sampling measurements and ground-based aerosol lidar backscatter data should yield accurate characterization of the vertical mixing that will enable calculation of the Saharan dust AOD component from the sunphotometer data. Examples will be presented showing measured AATS-6 AOD spectra, calculated aerosol extinction and water vapor density vertical profiles, and aerosol size distributions retrieved by inversion of the AOD spectra. Near sea-surface AOD spectra acquired by AATS-6 during horizontal flight legs at 30 m ASL are available for validation of AOD derived from coincident satellite sensor (TOMS, MODIS, MISR) measurements. AATS-6 AOD data acquired during numerous aircraft ascents and descents through the MBL and the SAL should permit atmospheric column closure analyses with respect to aerosol optical depth, extinction, and size distribution by comparison with coincident aircraft-based in-situ particle size distribution measurements and ground-based (Cabras Island, Puerto Rico) micropulse lidar aerosol backscatter measurements. The aerosol information derived from the column closure analyses can be used subsequently to calculate radiative flux changes, which can then be compared with coincident spectral flux measurements taken from aboard the aircraft with a solar spectral flux radiometer.

Livingston, John M.↗
NASA NTRS2006

Use of Photoelastic Modulators for High-accuracy Spectropolarimetric Imaging of Aerosols

Passive multiangular, multispectral, and polarimetric sensing approaches each have unique strengths for the measurement of tropospheric aerosol column abundances and microphysical properties. Current spaceborne multispectral and multiangular aerosols sensors operate at approximately 1 km resolution. Under NASA's Instrument Incubator Program, we are developing an electro-optic imaging approach that will enable adding high-accuracy polarimetry to such observations. To achieve a degree of linear polarization (DOLP) uncertainty of 0.5%, our approach temporally modulates the linear-polarization component of incoming light at a rapid rate, enabling each detector within a focal-plane array, combined with polarization analyzers, to measure the relative proportions of the linear Stokes components Q or U to the total intensity. Our system uses tandem photoelastic modulators (PEMs) within a high-reflectance, low diattenuation camera design. The two PEMs vibrate at slightly different resonant frequencies, leading to modulation of the polarized light at a heterodyne frequency of ~25 Hz. High-speed (1 kHz) readout of the detector arrays samples the output waveforms from which Q/I and U/I are derived. We report on experimental and theoretical analyses of PEM and optical system performance, along with plans for developing ruggedized PEMs capable of withstanding launch and on-orbit stresses.

photoelastics↗
NASA NTRS2002

Airborne Sunphotometer Measurements of Aerosol Optical Depth and Water Vapor in ACE-Asia and Their Comparisons to Correlative Measurements

In the Spring 2001 phase of the Asian Pacific Regional Aerosol Characterization Experiment (ACE-Asia), the 6-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) operated on 15 of the 19 research flights of the NCAR C-130, while its 14-channel counterpart (AATS-14) flew successfully on all 19 research flights of the CIRPAS Twin Otter. ACE-Asia studied aerosol outflow from the Asian continent to the Pacific basin. It was designed to integrate suborbital and satellite measurements and models to reduce the uncertainty in calculations of the climate forcing due to aerosols. AATS-6 and AATS-14 measured solar beam transmission at six and 14 wavelengths (380-1021 and 354-1558 nm, respectively), yielding aerosol optical depth (AOD) spectra and columnar water vapor (CWV). Vertical differentiation in profiles yielded aerosol extinction spectra and water vapor concentration. In this paper, we plan to present examples of the following, preliminary findings that are based in part on our airborne sunphotometer measurements: (1) The wavelength dependence of sunphotometer-derived AOD and extinction indicates that supermicron dust was often a major component of the aerosol, frequently extending to high altitudes. The percentage of full-column AOD (525 nm) that Jay above 3 km was typically 34+/-13%. In contrast, the analogous percentage of columnar water vapor was only 10+/-4%; (2) Initial comparison studies between AOD data obtained by AATS-6 and AATS-14 during coordinated low-level flight legs show agreement well within the instruments' error bars; (3) Aerosol extinction has been derived from airborne in situ measurements of scattering (nephelometers) and absorption (particle soot/ absorption photometer, PSAP) or calculated from particle size distribution measurements (mobility analyzers and aerodynamic particle sizers). Comparison with corresponding extinction values derived from the Ames airborne sunphotometer measurements shows good agreement for the vertical distribution of aerosol layers. However, the level of agreement in absolute magnitude of the derived aerosol extinction/optical depth varied among the aerosol layers sampled; (4) Initial comparisons of sunphotometer and satellite-derived AOD using SeaWiFS, MISR and AVHRR show promising results. We also plan to include comparisons with MODIS and TOMS: (5) Initial comparisons of sunphotometer-derived AOD and aerosol extinction profiles with lidars in Tokyo and on a ship show reasonable agreement.

Schmid, B.↗