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NASA NTRS1997

Inversion Schemes to Retrieve Atmospheric and Oceanic Parameters from SeaWiFS Data

The investigation focuses on two key issues in satellite ocean color remote sensing, namely the presence of whitecaps on the sea surface and the validity of the aerosol models selected for the atmospheric correction of SeaWiFS data. Experiments were designed and conducted at the Scripps Institution of Oceanography to measure the optical properties of whitecaps and to study the aerosol optical properties in a typical mid-latitude coastal environment. CIMEL Electronique sunphotometers, now integrated in the AERONET network, were also deployed permanently in Bermuda and in Lanai, calibration/validation sites for SeaWiFS and MODIS. Original results were obtained on the spectral reflectance of whitecaps and on the choice of aerosol models for atmospheric correction schemes and the type of measurements that should be made to verify those schemes. Bio-optical algorithms to remotely sense primary productivity from space were also evaluated, as well as current algorithms to estimate PAR at the earth's surface.

Deschamps, P.-Y.↗

NASA NTRS2003

Calibration of TOMS Radiances From Ground Observations

Verification of a stratospheric ozone recovery remains a high priority for environmental research and policy definition. Models predict an ozone recovery at a much lower rate than the measured depletion rate observed to date. Therefore improved precision of the satellite and ground ozone observing systems are required over the long term to verify its recovery. We show that validation of radiances from the ground can be a very effective means for correcting long term drifts of backscatter type satellite measurements and can be used to cross calibrate all BUV instruments in orbit (TOMS, SBUV/2, GOME, SCIAMACHY, OMI, GOME-2, OMPS). This method bypasses the retrieval algorithms used to derive ozone products from both satellite and ground based measurements that are normally used to validate the satellite data. Radiance comparisons employ forward models, but they are inherently more accurate than the retrieval This method employs very accurate comparisons between ground based zenith sicy radiances and satellite nadir radiances and employs two well established capabilities at the Goddard Space Flight Center, 1) the SSBUV calibration facilities and 2) the radiative transfer codes used for the TOMS and SBUV/2 algorithms and their subsequent refinements. The zenith sky observations are made by the SSBUV where its calibration is maintained to a high degree of accuracy and precision. Radiative transfer calculations show that ground based zenith sky and satellite nadir backscatter ultraviolet comparisons can be made very accurately under certain viewing conditions. Initial ground observations taken from Goddard Space Flight Center compared with radiative transfer calculations has indicated the feasibility of this method. The effect of aerosols and varying ozone amounts are considered in the model simulations and the theoretical comparisons. The radiative transfer simulations show that the ground and satellite radiance comparisons can be made with an uncertainty of less than l\% without the knowledge of the amount ozone viewed by either instrument on ground or in space. algorithms.

Bojkov, B. R.↗

NASA NTRSDate not supplied

Development of the GeoNEX Level 2G Products: Exploiting the Diurnal Variability of TOA Reflectance in Atmospheric Correction

This study develops a new atmospheric correction algorithm to generate the Level 2G products, in particular the gap-filled Surface Reflectance at 10-minute time steps, for the Geostationary-NASA Earth Exchange (GeoNEX) project. The algorithm is based on the MODIS MAIAC (Multi-Angle Implementation of Atmospheric Correction) framework but with significant modifications to exploit angular/temporal information from the diurnal variability of the GeoNEX L1G TOA (Top-of-Atmosphere) reflectance. The algorithm starts by evaluating the roughness/smoothness of the diurnal time series of the TOA reflectance. Because rapid changes in TOA reflectance are generally caused by passing clouds or shadows, rough segments of the time series are automatically filtered out while the smooth segments are further tested for brightness and temperature to identify clear-sky and snow-free observations. Next the algorithm runs the MAIAC RTM (Radiative Transfer Model) to retrieve the Ross-Thick-Li-Sparse (RTLS) BRDF model parameters and the daily-mean atmospheric optical depth (AOD) that allow the RTM to optimally simulate the observed diurnal variability of clear-sky TOA reflectance. Once the initial RTLS parameters are retrieved after the algorithm’s burn-in period, they are used as the prior information to predict the AOD level for the next days, while the subsequent clear-sky observations are used to make necessary adjustments to the RTLS parameters in an continuous fashion. This “prediction-analysis” cycle is then iterated to process the full time series of the L1G data, skipping only total-cloudy days or when surface snow is detected. We tested the algorithm over a list of selected AERONET sites. The retrieved results (the daily mean AOD and the RTLS parameters) reasonably agree with the ground-based measurements. Importantly, the results indicate that the diurnal cycles of surface reflectance are continuous functions of the illumination-view geometry. Thus we can use the retrieved RTLS model to accurately fill in data gaps on partial cloudy days. Also, our algorithm is totally independent from the traditional approaches based on the use of spectral band ratios between the shortwave infrared (e.g., 2.2µm) and the visible (e.g., 0.47µm and 0.64µm) bands. Our results thus demonstrate that the high-frequent diurnal geostationary observations contain unique information that helps us improve atmospheric correction of remote sensing data.

GeoNEX↗

NASA NTRS1998

Theoretical Calculation and Validation of the Water Vapor Continuum Absorption

The primary objective of this investigation is the development of an improved parameterization of the water vapor continuum absorption through the refinement and validation of our existing theoretical formalism. The chief advantage of our approach is the self-consistent, first principles, basis of the formalism which allows us to predict the frequency, temperature and pressure dependence of the continuum absorption as well as provide insights into the physical mechanisms responsible for the continuum absorption. Moreover, our approach is such that the calculated continuum absorption can be easily incorporated into satellite retrieval algorithms and climate models. Accurate determination of the water vapor continuum is essential for the next generation of retrieval algorithms which propose to use the combined constraints of multi-spectral measurements such as those under development for EOS data analysis (e.g., retrieval algorithms based on MODIS and AIRS measurements); current Pathfinder activities which seek to use the combined constraints of infrared and microwave (e.g., HIRS and MSU) measurements to improve temperature and water profile retrievals, and field campaigns which seek to reconcile spectrally-resolved and broad-band measurements such as those obtained as part of FIRE. Current widely used continuum treatments have been shown to produce spectrally dependent errors, with the magnitude of the error dependent on temperature and abundance which produces errors with a seasonal and latitude dependence. Translated into flux, current water vapor continuum parameterizations produce flux errors of order 10 W/ml, which compared to the 4 W/m' magnitude of the greenhouse gas forcing and the 1-2 W/m' estimated aerosol forcing is certainly climatologically significant and unacceptably large. While it is possible to tune the empirical formalisms, the paucity of laboratory measurements, especially at temperatures of interest for atmospheric applications, preclude tuning the empirical continuum models over the full spectral range of interest for remote sensing and climate applications. Thus, we propose to further develop and refine our existing far-wing formalism to provide an improved treatment applicable from the near-infrared through the microwave. Based on the results of this investigation, we will provide to the remote sensing/climate modeling community a practical and accurate tabulation of the continuum absorption covering the near-infrared through the microwave region of the spectrum for the range of temperatures and pressures of interest for atmospheric applications.

Ma, Qiancheng↗

NASA NTRS1992

Surface roughness considerations for atmospheric correction of ocean color sensors. I - The Rayleigh-scattering component. II - Error in the retrieved water-leaving radiance

The first step in the Coastal Zone Color Scanner (CZCS) atmospheric-correction algorithm is the computation of the Rayleigh-scattering (RS) contribution, L sub r, to the radiance leaving the top of the atmosphere over the ocean. In the present algorithm, L sub r is computed by assuming that the ocean surface is flat. Calculations of the radiance leaving an RS atmosphere overlying a rough Fresnel-reflecting ocean are presented to evaluate the radiance error caused by the flat-ocean assumption. Simulations are carried out to evaluate the error incurred when the CZCS-type algorithm is applied to a realistic ocean in which the surface is roughened by the wind. In situations where there is no direct sun glitter, it is concluded that the error induced by ignoring the Rayleigh-aerosol interaction is usually larger than that caused by ignoring the surface roughness. This suggests that, in refining algorithms for future sensors, more effort should be focused on dealing with the Rayleigh-aerosol interaction than on the roughness of the sea surface.

Gordon, Howard R.↗

NASA NTRS2002

CIMEL Measurements of Zenith Radiances at the ARM Site

Starting from October 1, 2001, Cimel at the ARM Central Facility in Oklahoma has been switched to a new "cloud mode." This mode allows taking measurements of zenith radiance when the Sun in blocked by clouds. In this case, every 13 min. Cimel points straight up and takes 10 measurements with 9 sec. time interval. The new Cimel's mode has four filters at 440, 670, 870 and 1020 nm. For cloudy conditions, the spectral contrast in surface albedo dominates over Rayleigh and aerosol effects; this makes normalized zenith radiances at 440 and 670 as well as for 870 and 1020 almost indistinguishable. We compare Cimel measurements with other ARM cart site instruments: Multi-Filter Rotating Shadowband Radiometer (MFRSR), Narrow Field of View (NFOV) sensor, and MicroWave Radiometer(MWR). Based on Cimel and MFRSR 670 and 870 nm channels, we build a normalized difference cloud index (NDCI) for radiances and fluxes, respectively. Radiance NDCI from Cimel and flux NDCI from MFRSR are compared between themselves as well as with cloud Liquid Water Path (LWP) retrieved from MWR. Based on our theoretical calculations and preliminary data analysis,there is a good correlation between NDCIs and LWP for cloudy sky above green vegetation. Based on this correlation, an algorithm to retrieve cloud optical depth from NDCI is proposed.

Marshak, Alexander↗

NASA NTRS2008

Provenance in Data Interoperability for Multi-Sensor Intercomparison

As our inventory of Earth science data sets grows, the ability to compare, merge and fuse multiple datasets grows in importance. This requires a deeper data interoperability than we have now. Efforts such as Open Geospatial Consortium and OPeNDAP (Open-source Project for a Network Data Access Protocol) have broken down format barriers to interoperability; the next challenge is the semantic aspects of the data. Consider the issues when satellite data are merged, cross-calibrated, validated, inter-compared and fused. We must match up data sets that are related, yet different in significant ways: the phenomenon being measured, measurement technique, location in space-time or quality of the measurements. If subtle distinctions between similar measurements are not clear to the user, results can be meaningless or lead to an incorrect interpretation of the data. Most of these distinctions trace to how the data came to be: sensors, processing and quality assessment. For example, monthly averages of satellite-based aerosol measurements often show significant discrepancies, which might be due to differences in spatio- temporal aggregation, sampling issues, sensor biases, algorithm differences or calibration issues. Provenance information must be captured in a semantic framework that allows data inter-use tools to incorporate it and aid in the intervention of comparison or merged products. Semantic web technology allows us to encode our knowledge of measurement characteristics, phenomena measured, space-time representation, and data quality attributes in a well-structured, machine-readable ontology and rulesets. An analysis tool can use this knowledge to show users the provenance-related distrintions between two variables, advising on options for further data processing and analysis. An additional problem for workflows distributed across heterogeneous systems is retrieval and transport of provenance. Provenance may be either embedded within the data payload, or transmitted from server to client in an out-of-band mechanism. The out of band mechanism is more flexible in the richness of provenance information that can be accomodated, but it relies on a persistent framework and can be difficult for legacy clients to use. We are prototyping the embedded model, incorporating provenance within metadata objects in the data payload. Thus, it always remains with the data. The downside is a limit to the size of provenance metadata that we can include, an issue that will eventually need resolution to encompass the richness of provenance information required for daata intercomparison and merging.

Lynnes, Chris↗

NASA NTRS2020

The Evolution of Icelandic Volcano Emissions, as Observed From Space in the Era of NASA's Earth Observing System (EOS)

Volcanoes are natural phenomena that have global environmental impacts. Satellite remote sensing can help classify volcanic eruptions and track the dispersion of emissions. We assess multiple volcanic eruptions in Iceland (Eyjafjallajökull 2010, Grímsvötn 2011 and Holuhraun 2014-2015), using space-borne observations to infer information about the geological dynamics of each volcano and the properties and evolution of plume particles. We derive qualitative constraints on plume particle size, shape and light-absorption characteristics from Multi-angle Imaging SpectroRadiometer (MISR) space-borne imagery. With the MISR Research Algorithm (RA), we distinguish sulfate/water-dominated volcanic plumes from Holuhraun and ash-dominated plumes from Eyjafjallajökull and Grímsvötn, and even identify subtler changes in ash particle size and light-absorption within plumes. Additionally, plume heights are retrieved geometrically from MISR. These are combined with surface thermal anomalies from the MODerate resolution Imaging Spectroradiometer (MODIS) and SO2 concentrations derived from the Ozone Monitoring Instrument (OMI) to synthesize eruption remote-sensing chronologies. Signals related to differences in particle properties are identified and linked to evolving magma composition at Eyjafjallajökull. The results illustrate the potential to distinguish qualitative differences in eruptive magma composition based on particle light absorption and plume profile from remote-sensing. For the sulfate-rich Holuhraun plumes, the influence of aerosol hygroscopic growth during transport is inferred from such data. Three processes appear to dominate plume evolution in Iceland: downwind aerosol formation; particle hydration; and particle deposition. This work demonstrates enhanced MISR capabilities, and more generally, remote-sensing analysis that can be applied globally, especially where suborbital volcano observations are limited or entirely absent.

remote sensting↗

NASA NTRS2021

Quantifying Uncertainties in Nighttime Light Retrievals From Suomi-NPP and NOAA-20 VIIRS Day/Night Band Data

Satellite observations of nighttime lights (NTL) from Suomi-NPP and NOAA-20 VIIRS Day/Night Band data have been widely used to estimate human activities. Long-term changes such as urban development and abrupt short-term changes such as power outages have been monitored from temporal NTL acquired by satellites. While high temporal NTL variation has been found across NTL data of varying temporal scale (e.g., daily, monthly, and annual composites), the sources of measurement error and uncertainty are poorly understood. This paper quantifies the sources of VIIRS-derived NTL uncertainty due to view-illumination geometry, surface Bidirectional Reflectance Distribution Function (BRDF)/albedo, and the effects of snow cover, lunar irradiance, aerosol loading, cloud mask, vegetation, geometry, and ephemeral artifacts (e.g., the Aurora Borealis). Based on this current assessment of NASA Black Marble retrievals (VNP46, Collection V001), we found that angular and atmospheric effects dominate retrieval uncertainty. Errors introduced by upstream data inputs (e.g., a coarser nighttime snow cover flag and misclassification errors in the existing VIIRS nighttime cloud mask) were also found to impact retrieval quality. Despite these challenges, a consistent daily NTL time series record can be routinely generated from top-of-atmosphere VNP46 radiances. Key recommendations include: (1) the use of lunar-BRDF adjusted and atmospherically corrected NTL (i.e., as identified as high-quality retrievals in the VNP46 QA fields), (2) development and improvement to the VIIRS snow cover and cloud masks algorithms to accurately reflect NTL retrieval conditions, (3) characterizing seasonal variations in NTL due to vegetation and snow, (4) reducing geometric effects due to the spatial mismatch of gridded pixel and observation footprint, (5) employing angularly-consistent NTL observations from multiple VIIRS instruments (i.e., Suomi-NPP and NOAA-20) to reduce pixel-based uncertainties and address persistent data gaps, and (6) being mindful of surface-reflected radiance from aurora events at mid-to-high latitudes.

Zhuosen Wang↗

NASA NTRS1998

Theoretical Calculation and Validation of the Water Vapor Continuum Absorption

The primary objective of this investigation is the development of an improved parameterization of the water vapor continuum absorption through the refinement and validation of our existing theoretical formalism. The chief advantage of our approach is the self-consistent, first principles, basis of the formalism which allows us to predict the frequency, temperature and pressure dependence of the continuum absorption as well as provide insights into the physical mechanisms responsible for the continuum absorption. Moreover, our approach is such that the calculated continuum absorption can be easily incorporated into satellite retrieval algorithms and climate models. Accurate determination of the water vapor continuum is essential for the next generation of retrieval algorithms which propose to use the combined constraints of multispectral measurements such as those under development for EOS data analysis (e.g., retrieval algorithms based on MODIS and AIRS measurements); current Pathfinder activities which seek to use the combined constraints of infrared and microwave (e.g., HIRS and MSU) measurements to improve temperature and water profile retrievals, and field campaigns which seek to reconcile spectrally-resolved and broad-band measurements such as those obtained as part of FIRE. Current widely used continuum treatments have been shown to produce spectrally dependent errors, with the magnitude of the error dependent on temperature and abundance which produces errors with a seasonal and latitude dependence. Translated into flux, current water vapor continuum parameterizations produce flux errors of order 10 W/sq m, which compared to the 4 W/sq m magnitude of the greenhouse gas forcing and the 1-2 W/sq m estimated aerosol forcing is certainly climatologically significant and unacceptably large. While it is possible to tune the empirical formalisms, the paucity of laboratory measurements, especially at temperatures of interest for atmospheric applications, preclude tuning, the empirical continuum models over the full spectral range of interest for remote sensing and climate applications. Thus, we propose to further develop and refine our existing, far-wing formalism to provide an improved treatment applicable from the near-infrared through the microwave. Based on the results of this investigation, we will provide to the remote sensing/climate modeling community a practical and accurate tabulation of the continuum absorption covering the near-infrared through the microwave region of the spectrum for the range of temperatures and pressures of interest for atmospheric applications.

Ma, Qiancheng↗

NASA NTRS2009

A Critical Look at Deriving Monthly Aerosol Optical Depth from Satellite Data

Satellite-derived aerosol data sets, such as those provided by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, are greatly improving our understanding of global aerosol optical depth (AOD). Yet, there are sampling issues. MODIS specific orbital geometry, convolved with the need to avoid bright surfaces (glint, desert, clouds, etc.), means that AOD can be under- or over-sampled in places. When deriving downstream products, such as daily or monthly gridded AOD, one must consider the spatial and temporal density of the measurements relative to the gradients of the true AOD. Additionally, retrieval confidence criteria should be considered. Averaged products are highly dependent on choices made for data aggregation and weighting, and sampling errors can be further propagated when deriving regional or global mean AOD. Different choices for aggregation and weighting result in estimates of regional and global means varying by 30% or more. The impacts of a particular averaging algorithm vary by region and surface type and can be shown to represent different tolerance for clouds and retrieval confidence.

Levy, R. C.↗

NASA NTRSDate not supplied

Modeling Atmospheric Science Knowledge from Research Publications

NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven dataset discovery, where users seek publications on projects similar to their intended study. For this approach to be effective, users need a clear connection between the underlying data in the publications and the study objectives; this is not often apparent to non-expert users. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. As an illustration of these challenges, in this work we focus on the atmospheric chemistry processes related to Earth environmental impacts such as ozone depletion, aerosols, smog formation, acid rain, and radiative forcing. We further limit our study to publications that use data from the Microwave Limb Sounder (MLS) instrument flown on the Aura Earth Observing System. To create knowledge representations of science carried out in these publications, we use existing ontologies such as the Global Change Master Directory (GCMD) and Semantic Web for Earth and Environmental Terminology (SWEET). These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, action words, among many others. Based on these terms acknowledge graph database was populated with the terms retrieved from scientific publications that study atmospheric chemistry. These databases can be used to further enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. These tools and methods can also be extended to apply to content from other related Earth science domains.

Irina Gerasimov↗

NASA NTRS1997

An Overview of the Tropospheric Aerosol Radiative Forcing Observational Experiment

Aerosol effects on atmospheric radiation are a leading source of uncertainty in predicting future climate. As a result, the International Global Atmospheric Chemistry Program has established a Focus on Atmospheric Aerosols (IGAC/FAA) and endorsed a series of aerosol field campaigns. TARFOX, the second in the IGAC/FAA series, was designed to reduce this uncertainty by measuring aerosol properties and effects in the US eastern seaboard, where one of the world's major plumes of industrial haze moves from the continent over the Atlantic Ocean. TARFOX's objectives are to: 1. Make simultaneous measurements of: (a) aerosol effects on radiation fields, and (b) the chemical, physical, and optical properties of the aerosols causing those effects. 2. Perform a variety of closure studies by using overdetermined data sets to test the mutual consistency of measurements and calculations of a wide range of aerosol properties and effects. 3. Use the results of the closure studies to assess and reduce uncertainties in estimates of aerosol radiative forcing, as well as to guide future field programs. An important subset of the closure studies is tests and improvements of algorithms used to derive aerosol properties and radiative effects from satellite measurements. The TARFOX Intensive Field Period (IFP) was conducted July 10-31, 1996. It included coordinated measurements from four satellites (GOES-8, NOAA-14, ERS-2, LANDSAT), four aircraft (ER-2, C-130, C-131, and a modified Cessna), land sites, and ships. A variety of aerosol conditions was sampled, ranging from relatively clean behind frontal passages to moderately polluted with aerosol optical depths exceeding 0.5 at mid-visible wavelengths. The latter conditions included separate incidents of enhancements caused primarily by anthropogenic sources and another incident of enhancement apparently influenced by recent fog processing. Spatial gradients of aerosol optical thickness were sampled to aid in isolating aerosol effects from other radiative effects and to more tightly constrain closure tests, including those of satellite retrievals. This talk gives an overview of TARFOX goals, rationale, methods, and initial key findings.

Russell, P. B.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-29194-DND

The Stratospheric Aerosol and Gas Experiment (SAGE) III instrument was deployed on the International Space Station (ISS) in early March 2017. SAGE III/ISS is the latest in the NASA lineage of solar occultation satellite instruments designed to monitor the vertical distribution of aerosol, ozone and other trace gases in the upper atmosphere. Originally built in the early 2000s, the SAGE III/ISS instrument required extensive testing and refurbishment prior to deliver to ISS, including the replacement of the neutral density filter that has been associated with some instrument response issues during the METEOR/3M mission. In particular, METEOR/3M measurements of the oxygen A-band absorption feature near 762 nm that were to be utilized to retrieve profiles of temperature and pressure were adversely affected by this instrument issue. Preliminary examination of the SAGE III/ISS oxygen A-band spectra indicate that the measurements are of higher fidelity than from the METEOR/3M instrument, which may permit successful retrieval of science quality temperature and pressure products. In this paper, we will provide an overview of the temperature and pressure retrieval algorithm, present preliminary analyses of the SAGE III/ISS oxygen A-band measurements, and an initial assessment of the quality of the temperature and pressure retrievals.

Michael Pitts↗

NASA NTRS2000

Autonomous, Full-Time Cloud Profiling at Arm Sites with Micro Pulse Lidar

Since the early 1990's technology advances permit ground based lidar to operate full time and profile all significant aerosol and cloud structure of the atmosphere up to the limit of signal attenuation. These systems are known as Micro Pulse Lidars (MPL), as referenced by Spinhirne (1993), and were first in operation at DOE Atmospheric Radiation Measurement (ARM) sites. The objective of the ARM program is to improve the predictability of climate change, particularly as it relates to cloud-climate feedback. The fundamental application of the MPL systems is towards the detection of all significant hydrometeor layers, to the limit of signal attenuation. The heating and cooling of the atmosphere are effected by the distribution and characteristics of clouds and aerosol concentration. Aerosol and cloud retrievals in several important areas can only be adequately obtained with active remote sensing by lidar. For cloud cover, the height and related emissivity of thin clouds and the distribution of base height for all clouds are basic parameters for the surface radiation budget, and lidar is essetial for accurate measurements. The ARM MPL observing network represents the first long-term, global lidar study known within the community. MPL systems are now operational at four ARM sites. A six year data set has been obtained at the original Oklahoma site, and there are several years of observations at tropical and artic sites. Observational results include cloud base height distributions and aerosol profiles. These expanding data sets offer a significant new resource for cloud, aerosol and atmospheric radiation analysis. The nature of the data sets, data processing algorithms, derived parameters and application results are presented.

Spinhirne, James D.↗

NASA NTRS2003

Assessment, Validation, and Refinement of the Atmospheric Correction Algorithm for the Ocean Color Sensors

The primary focus of this proposed research is for the atmospheric correction algorithm evaluation and development and satellite sensor calibration and characterization. It is well known that the atmospheric correction, which removes more than 90% of sensor-measured signals contributed from atmosphere in the visible, is the key procedure in the ocean color remote sensing (Gordon and Wang, 1994). The accuracy and effectiveness of the atmospheric correction directly affect the remotely retrieved ocean bio-optical products. On the other hand, for ocean color remote sensing, in order to obtain the required accuracy in the derived water-leaving signals from satellite measurements, an on-orbit vicarious calibration of the whole system, i.e., sensor and algorithms, is necessary. In addition, it is important to address issues of (i) cross-calibration of two or more sensors and (ii) in-orbit vicarious calibration of the sensor-atmosphere system. The goal of these researches is to develop methods for meaningful comparison and possible merging of data products from multiple ocean color missions. In the past year, much efforts have been on (a) understanding and correcting the artifacts appeared in the SeaWiFS-derived ocean and atmospheric produces; (b) developing an efficient method in generating the SeaWiFS aerosol lookup tables, (c) evaluating the effects of calibration error in the near-infrared (NIR) band to the atmospheric correction of the ocean color remote sensors, (d) comparing the aerosol correction algorithm using the singlescattering epsilon (the current SeaWiFS algorithm) vs. the multiple-scattering epsilon method, and (e) continuing on activities for the International Ocean-Color Coordinating Group (IOCCG) atmospheric correction working group. In this report, I will briefly present and discuss these and some other research activities.

Wang, Menghua↗

NASA NTRS2007

Ground-Based Correction of Remote-Sensing Spectral Imagery

Software has been developed for an improved method of correcting for the atmospheric optical effects (primarily, effects of aerosols and water vapor) in spectral images of the surface of the Earth acquired by airborne and spaceborne remote-sensing instruments. In this method, the variables needed for the corrections are extracted from the readings of a radiometer located on the ground in the vicinity of the scene of interest. The software includes algorithms that analyze measurement data acquired from a shadow-band radiometer. These algorithms are based on a prior radiation transport software model, called MODTRAN, that has been developed through several versions up to what are now known as MODTRAN4 and MODTRAN5 . These components have been integrated with a user-friendly Interactive Data Language (IDL) front end and an advanced version of MODTRAN4. Software tools for handling general data formats, performing a Langley-type calibration, and generating an output file of retrieved atmospheric parameters for use in another atmospheric-correction computer program known as FLAASH have also been incorporated into the present soft-ware. Concomitantly with the soft-ware described thus far, there has been developed a version of FLAASH that utilizes the retrieved atmospheric parameters to process spectral image data.

Alder-Golden, Steven M.↗

NASA NTRS2001

Aerosol Measurements by the Globally Distributed Micro Pulse Lidar Network

Full time measurements of the vertical distribution of aerosol are now being acquired at a number of globally distributed MP (micro pulse) lidar sites. The MP lidar systems provide full time profiling of all significant cloud and aerosol to the limit of signal attenuation from compact, eye safe instruments. There are currently eight sites in operation and over a dozen planned. At all sited there are also passive aerosol and radiation measurements supporting the lidar data. Four of the installations are at Atmospheric Radiation Measurement program sites. The network operation includes instrument operation and calibration and the processing of aerosol measurements with standard retrievals and data products from the network sites. Data products include optical thickness and extinction cross section profiles. Application of data is to supplement satellite aerosol measurements and to provide a climatology of the height distribution of aerosol. The height distribution of aerosol is important for aerosol transport and the direct scattering and absorption of shortwave radiation in the atmosphere. Current satellite and other data already provide a great amount of information on aerosol distribution, but no passive technique can adequately resolve the height profile of aerosol. The Geoscience Laser Altimeter System (GLAS) is an orbital lidar to be launched in early 2002. GLAS will provide global measurements of the height distribution of aerosol. The MP lidar network will provide ground truth and analysis support for GLAS and other NASA Earth Observing System data. The instruments, sites, calibration procedures and standard data product algorithms for the MPL network will be described.

Spinhirne, James↗