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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2002

STS 110 Mission Highlights Resource Tape

A continuation of 'STS 110 Mission Highlights Resource Tape'. This video, Part 4 of 4, shows footage from flight days 10 through 12 of STS-110. The spacecrew includes Michael J. Bloomfield, Commander; Stephen N. Frick, Pilot; Jerry L. Ross, Mission Specialist; Steven L. Smith, Mission Specialist; Ellen Ochoa, Mission Specialist; Lee M.E. Morin, Mission Specialist; Rex J. Walheim, Mission Specialist. Flight day 10 includes an exchange of farewells with the Expedition 4 crew (Yury I. Onufrienko, Commander; Daniel W. Bursch, Flight Engineer; Carl E. Walz, Flight Engineer) of the International Space Station (ISS), and undocking. The video includes many views of the ISS as Atlantis departs, including cloud cover and the Earth's limb as backgrounds. There is also a view of Atlantis with its payload bay open. On flight day 11, in preparation for landing, the crew conducts a checkout of flight controls and a test firing. A spaceborne wheat plant experiment onboard the ISS is briefly shown. Flight day 12 includes closing the payload bay, suit-up, and landing. Kennedy Space Center is seen from the air, and the video shows landing replays, as well as a heads-up display view of the landing. Earth views include clear views of Western Sahara, Morocco, Mauritania, and Algeria, with the Atlantic Ocean, a cloud obstructed view of Newfoundland and the Atlantic, Pacific Ocean sun glint, and an excellent view of the Chicago area and Lake Michigan at night. The activities from other flights days can be seen on "STS 110 Mission Highlights Resource Tape" Part 1 of 4 (internal ID 2002137575), "STS 110 Mission Highlights Resource Tape" Part 2 of 4 (internal ID 2002137573), and "STS 110 Mission Highlights Resource Tape" Part 3 of 4 (internal ID 2002137574).

Source record↗
NASA NTRS2003

New Total Ozone Algorithm for Application to the Total Ozone Mapping Spectrometer

The Total Ozone Mapping Spectrometer (TOMS) series comprises four instruments providing a total of 25 years of daily global stratospheric ozone data over the sunlit portion of the Earth. A new retrieval algorithm has been developed for TOMS, designated Version 8. The algorithm is based on differential absorption across a pair of wavelength channels chosen close together to minimize the impact of wavelength dependent forward modeling errors. Version 8 enhancements include correction for the presence of tropospheric aerosols and sun glint from water surfaces, a better treatment of variability due to tropospheric ozone and temperature dependence, and an improved forward model, particularly in regions of persistent snow and ice. Among other things, the Version 8 enhancements have reduced latitudinal dependence seen previously in TOMS - Dobson comparisons, predominantly in the Southern Hemisphere's summer, when the tropospheric ozone, temperature, and snow/ice corrections are additive. The basic components of the algorithm and its impact on derived total ozone will be discussed.

Wellemeyer, C.↗
NASA NTRS2003

Satellite Ocean-Color Validation Using Ships of Opportunity

The investigation s main objective is to collect from platforms of opportunity (merchant ships, research vessels) concomitant normalized water-leaving radiance and aerosol optical thickness data over the world s oceans. A global, long-term data set of these variables is needed to verify whether satellite retrievals of normalized water-leaving radiance are within acceptable error limits and, eventually, to adjust atmospheric correction schemes. To achieve this objective, volunteer officers, technicians, and scientists onboard the selected ships collect data from portable SIMBAD and Advanced SIMBAD (SIMBADA) radiometers. These instruments are specifically designed for evaluation of satellite-derived ocean color. They measure radiance in spectral bands typical of ocean-color sensors. The SIMBAD version measures in 5 spectral bands centered at 443, 490, 560, 670, and 870 nm, and the Advanced SIMBAD version in 11 spectral bands centered at 350, 380, 412, 443, 490, 510, 565, 620, 670, 750, and 870 nm. Aerosol optical thickness is obtained by viewing the sun disk like a classic sun photometer. Normalized water-leaving radiance, or marine reflectance, is obtained by viewing the ocean surface through a vertical polarizer in a specific geometry (nadir angle of 45o and relative azimuth angle of 135deg) to minimize direct sun glint and reflected sky radiation. The SIMBAD and SIMBADA data, after proper quality control and processing, are delivered to the SIMBIOS project office for inclusion in the SeaBASS archive. They complement data collected in a similar way by the Laboratoire d'Optique Atmospherique of the University of Lille, France. The SIMBAD and SIMBADA data are used to check the radiometric calibration of satellite ocean-color sensors after launch and to evaluate derived ocean-color variables (i.e., normalized water-leaving radiance, aerosol optical thickness, and aerosol type). Analysis of the SIMBAD and SIMBADA data provides information on the accuracy of satellite retrievals of normalized water-leaving radiance, an understanding of the discrepancies between satellite and in situ data, and algorithms that reduce the discrepancies, contributing to more accurate and consistent global ocean color data sets.

Frouin, Robert↗
NASA NTRS2004

Application of Bayesian Classification to Content-Based Data Management

The high volume of Earth Observing System data has proven to be challenging to manage for data centers and users alike. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), about 1 TB of new data are archived each day. Distribution to users is also about 1 TB/day. A substantial portion of this distribution is MODIS calibrated radiance data, which has a wide variety of uses. However, much of the data is not useful for a particular user's needs: for example, ocean color users typically need oceanic pixels that are free of cloud and sun-glint. The GES DAAC is using a simple Bayesian classification scheme to rapidly classify each pixel in the scene in order to support several experimental content-based data services for near-real-time MODIS calibrated radiance products (from Direct Readout stations). Content-based subsetting would allow distribution of, say, only clear pixels to the user if desired. Content-based subscriptions would distribute data to users only when they fit the user's usability criteria in their area of interest within the scene. Content-based cache management would retain more useful data on disk for easy online access. The classification may even be exploited in an automated quality assessment of the geolocation product. Though initially to be demonstrated at the GES DAAC, these techniques have applicability in other resource-limited environments, such as spaceborne data systems.

Lynnes, Christopher↗
NASA NTRS2004

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

The purpose of this joint University of Wisconsin (UW) and Louisiana State University (LSU) project has been to relate short term climate variation to response in the coastal zone of Louisiana in an attempt to better understand how the coastal zone is shaped by climate variation. Climate variation in this case largely refers to variation in surface wind conditions that affect wave action and water currents in the coastal zone. The primary region of focus was the Atchafalaya Bay and surrounding bays in the central coastal region of Louisiana. Suspended solids in the water column show response to wind systems both in quantity (through resuspension) and in the pattern of dispersement or transport. Wind systems associated with cold fronts are influenced by short term climate variation. Wind energy was used as the primary signature of climate variation in this study because winds are a significant influence on sediment transport in the micro-tidal Gilf of Mexico coastal zone. Using case studies, the project has been able to investigate the influence of short term climate variation on sediment transport. Wind energy data, collected daily for National Weather Service (NWS) stations at Lake Charles and New Orleans, LA, were used as an indicator of short term climate variation influence on seasonal time scales. A goal was to relate wind energy to coastal impact through sediment transport. This goal was partially accomplished by combining remote sensing and wind energy data. Daily high resolution remote sensing observations are needed to monitor the complex coastal zone environment, where winds, tides, and water level all interact to influence sediment transport. The NASA Earth Observing System (EOS) era brings hope for documenting and revealing response of the complex coastal transport mosaic through regular high spatial resolution observations from the Moderate resolution Imaging Spectrometer (MODIS) instrument. MODIS observations were sampled in this project for information content and should continue to be viewed as a resource for coastal zone monitoring. The project initialized the effort to transfer a suspended sediment concentration (SSC) algorithm to the MODIS platform for case 2 waters. MODIS enables monitoring of turbid coastal zones around the globe. The MODIS SSC algorithm requires refinements in the atmospheric aerosol contribution, sun glint influence, and designation of the sediment inherent optical properties (IOPs); the framework for continued development is in place with a plan to release the algorithm to the MODIS direct broadcast community.

Menzel, W. Paul↗
NASA NTRS2009

Metrology System for a Large, Somewhat Flexible Telescope

A proposed metrology system would be incorporated into a proposed telescope that would include focusing optics on a rigid bench connected via a deployable mast to another rigid bench holding a focal-plane array of photon counting photodetectors. Deformations of the deployable mast would give rise to optical misalignments that would alter the directions (and, hence, locations) of incidence of photons on the focal plane. The metrology system would measure the relative displacement of the focusing- optics bench and the focal-plane array bench. The measurement data would be used in post-processing of the digitized photodetector outputs to compensate for the mast-deformation-induced changes in the locations of incidence of photons on the focal plane, thereby making it possible to determine the original directions of incidence of photons with greater accuracy. The proposed metrology system is designed specifically for the Nuclear Spectroscopic Telescope Array (NuSTAR) a proposed spaceborne x-ray telescope. The basic principles of design and operation are also applicable to other large, somewhat flexible telescopes, both terrestrial and spaceborne. In the NuSTAR, the structural member connecting the optical bench and the photodetector array would be a 10-m-long deployable mast, and there is a requirement to keep errors in measured directions of incidence of photons below 10 arc seconds (3 sigma). The proposed system would include three diode lasers that would be mounted on the focusing-optics bench. For clarity, only one laser is shown in the figure, which is a greatly simplified schematic diagram of the system. Each laser would be aimed at a position-sensitive photodiode that would be mounted on the detector bench alongside the aforementioned telescope photodetector array. The diode lasers would operate at a wavelength of 830 nm, each at a power of 200 mW. Each laser beam would be focused to a spot of .1-mm diameter on the corresponding position-sensitive photodiode. To reduce the effect of sunlight on the measurements, a one-stage light baffle and an 830-nm transmission filter of 10-nm bandwidth would be placed in front of the position- sensitive photodiode. For each metrology reading, the output of the position-sensitive detector would be sampled and digitized twice: once with the lasers turned on, then once with the lasers turned off. The data from these two sets of samples would be subtracted from each other to further reduce the effects of sun glints or other background light sources.

Liebe, Carl Christian↗
NASA NTRS2008

Issues in Data Fusion for Satellite Aerosol Measurements for Applications with GIOVANNI System at NASA GES DISC

We look at issues, barriers and approaches for Data Fusion of satellite aerosol data as available from the GES DISC GIOVANNI Web Service. Daily Global Maps of AOT from a single satellite sensor alone contain gaps that arise due to various sources (sun glint regions, clouds, orbital swath gaps at low latitudes, bright underlying surfaces etc.). The goal is to develop a fast, accurate and efficient method to improve the spatial coverage of the Daily AOT data to facilitate comparisons with Global Models. Data Fusion may be supplemented by Optimal Interpolation (OI) as needed.

Gopalan, Arun↗
NASA NTRS2010

Detection of Natural Oil Seeps in the Atlantic Ocean Using MODIS

Natural oil seepage is the release of crude oil into the ocean from fissures in the seabed. Oil seepage is a major contributor to the total amount of oil entering the world s oceans. According to a 2003 study by the National Academy of Sciences (NAS), 47 percent of oil entering the world s oceans is from natural seeps, and 53 percent is from human sources (extraction, transportation, and consumption). Oil seeps cause smooth oil slicks to form on the water s surface. Oil seeps can indicate the location of stores of fossil fuel beneath the ocean floor. Knowledge of the effect of oil seepage on marine life and marine ecosystems remains limited. In the past, remote sensing has been used to detect oil seeps in the Gulf of Mexico and off of the coast of southern California. This project utilized sun glint MODIS imagery to locate oil slicks off of the Atlantic coast, an area that had not previously been surveyed for natural oil seeps using remote sensing. Since 1982, the Atlantic Ocean has been closed to any oil and gas drilling. Recently, however, the U.S. Minerals Management Services (MMS) has proposed a lease for oil and gas drilling off the coasts of Virginia and North Carolina. Determining the location of seepage sites in the Atlantic Ocean will help MMS locate potential deposits of oil and natural gas, thereby reducing the risk of leasing areas for petroleum extraction that do not contain these natural resources.

Reahard, Ross↗
NASA NTRS2011

Sensitivity of Depth-Integrated Satellite Lidar to Subaqueous Scattering

A method is presented for estimating subaqueous integrated backscatter from the CALIOP lidar. The algorithm takes into account specular reflection of laser light, laser scattering by wind-generated foam as well as sun glint and solar scattering from the foam Analyses show that the estimated subaqueous integrated backscatter is most sensitive to the estimate of transmittance used in the atmospheric correction, and is very insensitive to the estimate of wind speed used. As a case study, CALIOP data over Tampa Bay were compared to MODIS 645 nm remote sensing reflectance, which previously has been shown to be nearly linearly related to turbidity. The results indicate good correlation on nearly all CALIOP clear-free dates during the period 2006 through 2007, particularly those with relatively high atmospheric transmittance. When data are composited over the entire period the correlation is reduced but still statistically significant, an indication of variability in the biogeochemical composition in the water. Overall, the favorable results show promise for the application of satellite lidar integrated backscatter in providing information about subsurface backscatter properties, which can be extracted using appropriate models

Barton, Jonathan S.↗
NASA NTRS2011

Chlorophyll-a Algorithms for Oligotrophic Oceans: A Novel Approach Based on Three-Band Reflectance Difference

A new empirical algorithm is proposed to estimate surface chlorophyll-a concentrations (Chl) in the global ocean for Chl less than or equal to 0.25 milligrams per cubic meters (approximately 77% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote sensing reflectance (R(sub rs), sr(sup -1) in the green and a reference formed linearly between R(sub rs) in the blue and red. For low Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band-ratios and Chl, which was further validated using global data collected concurrently by ship-borne and SeaWiFS satellite instruments. Model simulations showed that for low Chl waters, compared with the band-ratio algorithm, the CI-based algorithm (CIA) was more tolerant to changes in chlorophyll-specific backscattering coefficient, and performed similarly for different relative contributions of non-phytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band-ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time-series analyses of SeaWiFS and MODIS/Aqua data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over MERIS and CZCS data indicate that the new approach should be generally applicable to all existing and future ocean color instruments.

Hu, Chuanmin↗
NASA NTRS2014

Model-Based Estimation of Sampling-Caused Uncertainty in Aerosol Remote Sensing for Climate Research Applications

To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiationtransport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125 deg × 1.125 deg and 2 deg × 3◦: the analysis is restricted to 60 deg S-60 deg N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long-term mean absolute monthly difference between all and dark target (DT) pixels was 0.01-0.02 over the ocean and 0.03-0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07-0.12 (30-45% of the global long-term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01-0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun-glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel-wide along-track instruments such as the Aerosol Polarimetry Sensor and the Cloud-Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along-track sensor to be 0.0005-0.0015 (ocean) and 0.0029-0.01 (land) or 0.5-1.2% and 1.1-4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale.

long-term variability↗
NASA NTRS2016

Coastal High-resolution Observations and Remote Sensing of Ecosystems (C-HORSE)

Coastal benthic marine ecosystems, such as coral reefs, seagrass beds, and kelp forests are highly productive as well as ecologically and commercially important resources. These systems are vulnerable to degraded water quality due to coastal development, terrestrial run-off, and harmful algal blooms. Measurements of these features are important for understanding linkages with land-based sources of pollution and impacts to coastal ecosystems. Challenges for accurate remote sensing of coastal benthic (shallow water) ecosystems and water quality are complicated by atmospheric scattering/absorption (approximately 80+% of the signal), sun glint from the sea surface, and water column scattering (e.g., turbidity). Further, sensor challenges related to signal to noise (SNR) over optically dark targets as well as insufficient radiometric calibration thwart the value of coastal remotely-sensed data. Atmospheric correction of satellite and airborne remotely-sensed radiance data is crucial for deriving accurate water-leaving radiance in coastal waters. C-HORSE seeks to optimize coastal remote sensing measurements by using a novel airborne instrument suite that will bridge calibration, validation, and research capabilities of bio-optical measurements from the sea to the high altitude remote sensing platform. The primary goal of C-HORSE is to facilitate enhanced optical observations of coastal ecosystems using state of the art portable microradiometers with 19 targeted spectral channels and flight planning to optimize measurements further supporting current and future remote sensing missions.

Coasts↗
NASA NTRS2018

Remote Sensing of the Ocean Surface Refractive Index via Short-Wave Infrared Polarimetry

The linear polarization of sunlight reflected by ocean surfaces in the shortwave infrared (SWIR), at geometries where specular reflection dominates the signal, is a direct function of the refractive index of the surface microlayer(SML). This simple physical concept is at the base of a novel technique presented in this study. We invert observations obtained by the airborne Research Scanning Polarimeter (RSP) in the sun glint region, where each pixel's radiance is dominated by the signal originating from the wave slopes oriented precisely to cause specular reflection. The SWIR wavelength ensures minimization of aerosol interference when radiance travels through the atmosphere; strong absorption by the water body then limits the penetration depth to the first micrometer or so, effectively probing the SML. The resulting Degree of Linear Polarization (DoLP) is then governed by the refractive index via the Fresnel law for the specfic pixel geometry, independently of the wind speed. The selected dataset concerns several field deployments from both low- and high-altitude aircraft, including total reflectance measurements with the sole purpose of accounting for the residual aerosol effect.Stable retrievals from transects above pure seawater yielded values of refractive index that match the values published in the literature within an accuracy of 5 x 10 [superscript 4]. Flying over the oil spill caused by the explosion of the Deepwater Horizon platform, detected variations were found compatible with the presence of an oil slick. The robustness of the results, guaranteedby the high RSP polarimetric accuracy (less than or equal to 0:2%), opens the possibility for remote-sensing detection of other entities that similarly affect the refractive index including whitecaps, microplastics, biological gels, seaweed and grass mats.

Surface Microlayer↗
NASA NTRS2019

Cloud Remote Sensing with EPIC/DSCOVR Observations: A Sensitivity Study with Radiative Transfer Simulations

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) views nearly the whole sunlit face of the Earth with 10 spectral bands ranging from the UV to the near-infrared, including two oxygen absorbing bands centered at 764 nm (A-band) and 687.75 nm (B-band). Clouds are among the primary remote sensing targets using EPIC images because of their important impacts on the Earth’s radiation budget. In order to facilitate the EPIC cloud data product development, we have built a radiative transfer simulator featuring flexible cloud microphysical parameters, gas absorptions, and the instrument line shape functions for each EPIC band. The radiative transfer simulator is used to explore the sensitivity of EPIC observations on liquid-phase cloud microphysical parameters, including optical depth, geometric thickness, and cloud top height. We found that the ratios of the reflectances in the oxygen A and B bands to their respective continuum measurements can be used to increase the confidence level of cloud masking over scenes with sun-glint. In addition, the 388 nm band can be used to differentiate low and high clouds with the uncertainty of roughly 2–3 km. Combining this information with the oxygen absorption bands, the cloud geometric thickness can be obtained with the rough uncertainty of 3–4 km.

atmospheric and ocean optics↗
NASA NTRS2016

Scientific and Technical Assistance for the Deployment of a Flexible Airborne Spectrometer System During C-MAPExp and COMEX: COMEX Version - 1.9T

The COMEX (CO2 and MEthane eXperiment) campaign supports the mission definition of CarbonSat and HyspIRI (Hyperspectral Infrared Imager) by providing representative airborne remote sensing data ‐ MAMAP (Methane Airborne MAPper) for CarbonSat; the Airborne Visual InfraRed Imaging Spectrometer (Classic & Next Generation) AVIRIS‐C/AVIRIS‐NG for HyspIRI ‐ as well as ground-based and airborne in‐situ data. The objectives of the COMEX campaign activities are (see Campaign Implementation Plan (RD‐4)): 1. Investigate spatial/spectral resolution trade‐offs for CH4 anomaly detection and flux inversion by comparison of MAMAP‐derived emission estimates with AVIRIS/AVIRIS‐NG derived data. 2. Evaluate sun‐glint observation geometry on CH4 retrievals for marine sources. 3. Characterize the effect of Surface Spectral Reflectance (SSR) heterogeneity on trace gas retrievals of CO2 and CH4 for medium and low‐resolution spectrometry. 4. Identify benefits from joint SWIR/TIR (ShortWave InfraRed/Thermal InfraRed ) data for trace gas detection and retrieval by comparison of MAMAP and AVIRIS/AVIRIS‐NG NIR/SWIR data with MAKO (Aerospace Corp.)TIR data. The ability to derive emission source strength for a range of strong emitting targets by remote sensing will be evaluated from combined AVIRIS‐NG and MAMAP data, adding significant value to the HyspIRI campaign AVIRIS‐NG dataset. The data will be used to quantify anomalies in atmospheric CO2 and CH4 from strong local greenhouse gas sources e.g. localized industrial complexes, landfills, etc. and to derive CO2 and CH4 emissions estimates from atmospheric gradient measurements. The original campaign concept was developed by University of Bremen and BRI. The COMEX campaign is funded bilaterally by NASA and ESA (European Space Agency). Whereas NASA funds the US part of the project via a contract with Dr. Ira Leifer, BRI (Bubbleology Research International), the contribution of MAMAP to the COMEX campaign is funded by ESA within the COMEX‐E project and NASA with respect to a 50 percent contribution to the flight-related costs of flying MAMAP on a US aircraft. The Data Acquisition Report (RD‐9) describes the instrumentation used, the measurements made by the team during the COMEX campaign in May/June 2014 and August/September 2014 in California, and an initial assessment of the data quality.

Point Sources↗
NASA NTRS2019

First Steps in the Creation of a Joint MISR/MODIS Ocean Color Atmospheric Correction Algorithm

We are creating a new algorithm that combines observations from MISR and MODIS (both on the NASA Terra spacecraft) to improve atmospheric correction and coverage for ocean color data products. The algorithm utilizes information rich, multi-angle MISR observations for atmospheric correction, applied to MODIS. Our goal is to produce atmospherically corrected Remote Sensing Reflectance from MODIS with enhanced coverage and accuracy, for input to downstream bio-optical ocean parameter retrieval algorithms.An important aspect of this work is the utilization of multi-angle views of the reflected ocean surface sun glint. Usually, such observations are avoided, since the intensity of the glint overwhelms any contribution from the ocean body. However, MISR's multi-angle observations see varying degrees of glint, which means they can be used to better determine aerosol optical properties (Kaufman et al., 2002, Ottaviani et al., 2013), and to identify surface wind speeds that govern the glint pattern. The latter could be utilized to replace the wind speeds taken from ancillary sources that are currently used to conservatively mask potential glint contamination in MODIS observations.To assess this capability, and to identify the appropriate parameterization, we present an analysis using the Generalized Nonlinear Retrieval Analysis (GENRA, Vukicevic et al., 2009) information content assessment. This technique is also easily modified to act as a Bayesian retrieval algorithm, for which initial results are discussed. Finally, we describe the status of integrating MISR data into the processing capabilities of the Ocean Biology Processing Group (OBPG) at NASA, and show the first ocean color vicarious calibration (Franz et al., 2007) of the MISR instrument.

Knobelspiesse, Kirk↗
NASA NTRS2014

TPSAS-NF1676L-19259-DND

In climate and Earth energy budget studies, understanding the presence and distribution of clouds is an essential first step. AVHRR measurements comprise the longest record of imager data from a common instrument for remote sensing of cloud and radiation properties. The NASA LaRC AVHRR cloud mask is a global cloud detection algorithm used as part of the Climate Data Record (CDR) project initiated by NOAA's National Climatic Data Center (NCDC). The objective of CDR program is to provide climate information derived from weather satellite data for more than 30 years. Recent improvements in the LaRC AVHRR cloud mask include detecting more daytime small cumulus and thin Cirrus in tropical oceans, especially over Sun Glint regions, better discrimination between polar clouds and snow ice surfaces including nighttime over Antarctica where 3.7 μm signals are noisy, and enhancement of nighttime ocean thin Cirrus and low clouds detection. Monthly averaged global and zonal cloud fractions from improved NOAA 18 AVHRR cloud mask compare well with CERES-MODIS Edition 4 (CM Ed4), MODIS team, and CALIPSO cloud mask. Spatially and temporally matched cloud detection statistics between NOAA 18 AVHRR and CALIPSO cloud mask will also be presented.

Qing Z Trepte↗
NASA NTRS2010

TPSAS-NF1676L-10863-DND

One important aspect of successful climate monitoring is satellite calibration. There is at least a 25-year of operational geostationary (GEO) record available for climate studies, if properly calibrated. The Global Space-based Inter-Calibration System (GSICS) project is another effort to provide the climate community consistent calibration across multiple platforms. Also, the Clouds and the Earth's Radiant Energy System (CERES) project, provides consistent GEO retrieved cloud properties and derived broadband fluxes across multiple platforms. This year GSICS is focusing on geostationary visible channel calibration. The GSICS strategy is to use multiple approaches, such as cross-calibrating the GEO radiances against MODIS as a reference, deep convective clouds as bright stable targets, deserts, sun-glint, stars, moon and other model based calibration methods. Each of these methods is independent of each other and can assess the stability of the GEO visible instrument with differing uncertainties. This study focuses on the inter-calibration of the GEO radiances against MODIS as a reference by using collocated, and coincident ray-matched radiances. The advantage of the ray-matching technique is that it provides a full dynamic range of radiances to check the linearity of the GEO visible instrument. This presentation will focus on the technique, some error analysis, comparisons with other methods, and an approach to inter-calibrate historical GEOs before MODIS.

D R Doelling↗