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NASA NTRS2013

SAGE Version 7.0 Algorithm: Application to SAGE II

This paper details the Stratospheric Aerosol and Gas Experiments (SAGE) version 7.0 algorithm and how it is applied to SAGE II. Changes made between the previous (v6.2) and current (v7.0) versions are described and their impacts on the data products explained for both coincident event comparisons and time-series analysis. Users of the data will notice a general improvement in all of the SAGE II data products, which are now in better agreement with more modern data sets (e.g. SAGE III) and more robust for use with trend studies.

Damadeo, R. P↗

NASA NTRS2013

A Framework to Debug Diagnostic Matrices

Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

Model-based↗

NASA NTRS2012

Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased aerosol levels was observed during the dry season, with an inverse dependence of NDVI on aerosol optical thickness (AOT). NDVI observations processed with MAIAC showed highly reproducible and stable inter-annual patterns with little or no dependence on cloud cover, and no significant dependence on AOT (p less than 0.05). In addition to a better detection of cloudy pixels, MAIAC obtained about 20-80 percent more cloud free pixels, depending on season, a considerable amount for land analysis given the very high cloud cover (75-99 percent) observed at any given time in the area. We conclude that a new generation of atmospheric correction algorithms, such as MAIAC, can help to dramatically improve vegetation estimates over tropical rain forest, ultimately leading to reduced uncertainties in satellite-derived vegetation products globally.

tropical ecosystems↗

NASA NTRS2014

Lightning Imaging Sensor (LIS) for the International Space Station (ISS): Mission Description and Science Goals

In recent years, NASA Marshall Space Flight Center, the University of Alabama in Huntsville, and their partners have developed and demonstrated space-based lightning observations as an effective remote sensing tool for Earth science research and applications. The Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) continues to provide global observations of total lightning after 17 years on-orbit. In April 2013, a space-qualified LIS built as the flight spare for TRMM, was selected for flight as a science mission on the International Space Station. The ISS LIS (or I-LIS as Hugh Christian prefers) will be flown as a hosted payload on the Department of Defense Space Test Program (STP) H5 mission, which has a January 2016 baseline launch date aboard a SpaceX launch vehicle for a 2-4 year or longer mission. The LIS measures the amount, rate, and radiant energy of global lightning. More specifically, it measures lightning during both day and night, with storm scale resolution, millisecond timing, and high, uniform detection efficiency, without any land-ocean bias. Lightning is a direct and most impressive response to intense atmospheric convection. It has been found that the characteristics of lightning that LIS measures can be quantitatively coupled to both thunderstorm and other geophysical processes. Therefore, the ISS LIS lightning observations will provide important gap-filling inputs to pressing Earth system science issues across a broad range of disciplines, including weather, climate, atmospheric chemistry, and lightning physics. A unique contribution from the ISS platform will be the availability of real-time lightning, especially valuable for operational applications over data sparse regions such as the oceans. The ISS platform will also uniquely enable LIS to provide simultaneous and complementary observations with other payloads such as the European Space Agency's Atmosphere-Space Interaction Monitor (ASIM) that will be exploring the connection between thunderstorms and lightning with terrestrial gamma-ray flashes (TGFs). Another important function of the ISS LIS will be to provide cross-sensor calibration/validation with a number of other payloads, including the TRMM LIS and the next generation geostationary lightning mappers (e.g., GOES-R Geostationary Lightning Mapper and Meteosat Third Generation Lightning Imager). This inter-calibration will improve the long term climate monitoring provided by all these systems. Finally, the ISS LIS will extend the time-series climate record of LIS lightning observations and expand the latitudinal coverage of LIS lightning to the climate significant upper middle-latitudes.

Blakeslee, R. J.↗

NASA NTRS2014

Lightning Imaging Sensor (LIS) for the International Space Station (ISS): Mission Description and Science Goals

Blakeslee, R. J.↗

NASA NTRS2013

Effects of Bedrock Lithology and Subglacial Till on the Motion of Ruth Glacier, Alaska, Deduced from Five Pulses from 1973-2012

A pulse is a type of unstable glacier flow intermediate between normal flow and surging. Using Landsat MSS, TM, and ETM+ imagery and feature tracking software, a time-series of mostly annual velocity maps from 1973 to 2012 was produced that reveals five pulses of Ruth Glacier, Alaska. Peaks in ice velocity were found in the 1981, 1989, 1997, 2003, and 2010; approximately every 7 years. During these peak years the ice velocity increased 300%, from approximately 40 m/yr to 160 m/yr, and occurred in an area of the glacier underlain by sedimentary bedrock. Based on the spatio-temporal behavior of Ruth Glacier during the pulse cycles, we suggest the pulses are due to enhanced basal motion via deformation of a subglacial till. The cyclical nature of the pulses is theorized to be due to a thin till, with low permeability, that causes incomplete drainage of the till between the pulses, followed by eventual recharge and dilation of the till. These findings suggest care is needed when attempting to correlate changes in regional climate with decadal-scale changes in velocity, because in some instances basal conditions may have a greater influence on ice dynamics than climate.

Glacier↗

NASA NTRS2014

Reevaluation of Stratospheric Ozone Trends From SAGE II Data Using a Simultaneous Temporal and Spatial Analysis

This paper details a new method of regression for sparsely sampled data sets for use with time-series analysis, in particular the Stratospheric Aerosol and Gas Experiment (SAGE) II ozone data set. Non-uniform spatial, temporal, and diurnal sampling present in the data set result in biased values for the long-term trend if not accounted for. This new method is performed close to the native resolution of measurements and is a simultaneous temporal and spatial analysis that accounts for potential diurnal ozone variation. Results show biases, introduced by the way data is prepared for use with traditional methods, can be as high as 10%. Derived long-term changes show declines in ozone similar to other studies but very different trends in the presumed recovery period, with differences up to 2% per decade. The regression model allows for a variable turnaround time and reveals a hemispheric asymmetry in derived trends in the middle to upper stratosphere. Similar methodology is also applied to SAGE II aerosol optical depth data to create a new volcanic proxy that covers the SAGE II mission period. Ultimately this technique may be extensible towards the inclusion of multiple data sets without the need for homogenization.

Damadeo, R. P.↗

NASA NTRS2015

Lightning Imaging Sensor (LIS) for the International Space Station (ISS): Mission Description and Science Goals

In recent years, the NASA Marshall Space Flight Center, the University of Alabama in Huntsville, and their partners have developed and demonstrated space-based lightning observations as an effective remote sensing tool for Earth science research and applications. The Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) continues to acquire global observations of total (i.e., intracloud and cloud-to-ground) lightning after 17 years on-orbit. However, TRMM is now low on fuel, so this mission will soon be completed. As a follow on to this mission, a space-qualified LIS built as the flight spare for TRMM has been selected for flight as a science mission on the International Space Station (ISS). The ISS LIS will be flown as a hosted payload on the Department of Defense Space Test Program (STP) H5 mission, which has a January 2016 baseline launch date aboard a SpaceX launch vehicle for a 2-4 year or longer mission. The LIS measures the amount, rate, and radiant energy of total lightning over the Earth. More specifically, it measures lightning during both day and night, with storm scale resolution (approx. 4 km), millisecond timing, and high, uniform detection efficiency, without any land-ocean bias. Lightning is a direct and most impressive response to intense atmospheric convection. It has been found that lightning measured by LIS can be quantitatively related to thunderstorm and other geophysical processes. Therefore, the ISS LIS lightning observations will continue to provide important gap-filling inputs to pressing Earth system science issues across a broad range of disciplines, including weather, climate, atmospheric chemistry, and lightning physics. A unique contribution from the ISS platform will be the availability of real-time lightning data, especially valuable for operational applications over data sparse regions such as the oceans. The ISS platform will also uniquely enable LIS to provide simultaneous and complementary observations with other ISS payloads such as the European Space Agency's Atmosphere-Space Interaction Monitor (ASIM) that will be exploring the connection between thunderstorms and lightning with terrestrial gamma-ray flashes (TGFs) and the Japan Aerospace Exploration Agency's Global LIghtning and Sprites MeasurementS (GLIMS) with its focus on global lightning and sprite connections. Another important function of the ISS LIS will be to provide cross-sensor calibration/validation with a number of other payloads, including the TRMM LIS and the next generation geostationary lightning mappers such as the GOES-R Geostationary Lightning Mapper (GLM) and Meteosat Third Generation Lightning Imager (MTG LI), as well as with ground-based lightning detection systems. These inter-calibrations will improve the long term climate monitoring record provided by all these systems. Finally, the ISS LIS will extend the time-series climate record of LIS lightning observations and expand the latitudinal coverage of LIS lightning to the climate significant upper middle-latitudes.

Blakeslee, R. J.↗

NASA NTRS2015

Representative Agricultural Pathways and Scenarios for Regional Integrated Assessment of Climate Change Impacts, Vulnerability, and Adaptation: Chapter - 5

The global change research community has recognized that new pathway and scenario concepts are needed to implement impact and vulnerability assessment where precise prediction is not possible, and also that these scenarios need to be logically consistent across local, regional, and global scales. For global climate models, representative concentration pathways (RCPs) have been developed that provide a range of time-series of atmospheric greenhouse-gas concentrations into the future. For impact and vulnerability assessment, new socio-economic pathway and scenario concepts have also been developed, with leadership from the Integrated Assessment Modeling Consortium (IAMC).This chapter presents concepts and methods for development of regional representative agricultural pathways (RAOs) and scenarios that can be used for agricultural model intercomparison, improvement, and impact assessment in a manner consistent with the new global pathways and scenarios. The development of agriculture-specific pathways and scenarios is motivated by the need for a protocol-based approach to climate impact, vulnerability, and adaptation assessment. Until now, the various global and regional models used for agricultural-impact assessment have been implemented with individualized scenarios using various data and model structures, often without transparent documentation, public availability, and consistency across disciplines. These practices have reduced the credibility of assessments, and also hampered the advancement of the science through model intercomparison, improvement, and synthesis of model results across studies. The recognition of the need for better coordination among the agricultural modeling community, including the development of standard reference scenarios with adequate agriculture-specific detail led to the creation of the Agricultural Model Intercomparison and Improvement Project (AgMIP) in 2010. The development of RAPs is one of the cross-cutting themes in AgMIP's work plan, and has been the subject of ongoing work by AgMIP since its creation.

agriculture↗

NASA NTRS2015

Integrated Assessments of the Impact of Climate Change on Agriculture: An Overview of AgMIP Regional Research in South Asia

South Asia encompasses a wide and highly varied geographic region, and includes climate zones ranging from the mountainous Himalayan territory to the tropical lowland and coastal zones along alluvial floodplains. The region's climate is dominated by a monsoonal circulation that heralds the arrival of seasonal rainfall, upon which much of the regional agriculture relies. The spatial and temporal distribution of this rainfall is, however, not uniform over the region. Northern South Asia, central India, and the west coast receive much of their rainfall during the southwest monsoon season, between June and September. These rains partly result from the moisture transport accompanying the monsoonal winds, which move in the southwesterly direction from the equatorial Indian Ocean. Regions further south, such as south/southeast India and Sri Lanka, may receive rains from both the southwest monsoon, and also during the northeast monsoon season between October and December (with northeasterly monsoon wind flow and moisture flux), which results in a bi- or multi-modal rainfall distribution. In addition, rainfall across South Asia displays a large amount of intraseasonal and interannual variability. Interannual variability is influenced by many drivers, both natural (e.g., El Ni-Southern Oscillation; ENSO) and man-made (e.g., rising temperatures due to increasing greenhouse gas concentrations), and it is challenging to obtaining accurate time-series of annual rainfall, even amongst various observed data products, which display inconsistencies amongst themselves. These climatic and rainfall variations can further complicate South Asia's agricultural and water management. Agriculture employs at least 65 of the workforce in most South Asian countries, and nearly 80 of South Asia's poor inhabit rural areas. Understanding the response of current agricultural production to climate variability and future climate change is of utmost importance in securing food and livelihoods for South Asia's growing population. In order to assess the future of food and livelihood security across South Asia, the Agricultural Model Intercomparison and Improvement Project (AgMIP) has undertaken integrated climate-crop-economic assessments of the impact of climate change on food security and poverty in South Asia, encompassing Bangladesh, India, Nepal, Pakistan, and Sri Lanka. AgMIP has funded, on a competitive basis, four South Asian regional research teams (RRTs) and one South Asian coordination team (CT) to undertake climate-crop-economic integrated assessments of food security for many districts in each of these countries, with the goal of characterizing the state of food security and poverty across the region, and projecting how these are subject to change under future climate change conditions.

mountains↗

NASA NTRS2015

ACCEPT: Introduction of the Adverse Condition and Critical Event Prediction Toolbox

The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we introduce a generic framework developed in MATLAB (sup registered mark) called ACCEPT (Adverse Condition and Critical Event Prediction Toolbox). ACCEPT is an architectural framework designed to compare and contrast the performance of a variety of machine learning and early warning algorithms, and tests the capability of these algorithms to robustly predict the onset of adverse events in any time-series data generating systems or processes.

machine learning↗

NASA NTRS2016

Transiting Exoplanet Studies and Community Targets for JWST's Early Release Science Program

The James Webb Space Telescope (JWST) will likely revolutionize transiting exoplanet atmospheric science, due to a combination of its capability for continuous, long duration observations and its larger collecting area, spectral coverage, and spectral resolution compared to existing space-based facilities. However, it is unclear precisely how well JWST will perform and which of its myriad instruments and observing modes will be best suited for transiting exoplanet studies. In this article, we describe a prefatory JWST Early Release Science (ERS) Cycle 1 program that focuses on testing specific observing modes to quickly give the community the data and experience it needs to plan more efficient and successful transiting exoplanet characterization programs in later cycles. We propose a multi-pronged approach wherein one aspect of the program focuses on observing transits of a single target with all of the recommended observing modes to identify and understand potential systematics, compare transmission spectra at overlapping and neighboring wavelength regions, confirm throughputs, and determine overall performances. In our search for transiting exoplanets that are well suited to achieving these goals, we identify 12 objects (dubbed community targets'') that meet our defined criteria. Currently, the most favorable target is WASP-62b because of its large predicted signal size, relatively bright host star, and location in JWST's continuous viewing zone. Since most of the community targets do not have well-characterized atmospheres, we recommend initiating preparatory observing programs to determine the presence of obscuring clouds/hazes within their atmospheres. Measurable spectroscopic features are needed to establish the optimal resolution and wavelength regions for exoplanet characterization. Other initiatives from our proposed ERS program include testing the instrument brightness limits and performing phase-curve observations. The latter are a unique challenge compared to transit observations because of their significantly longer durations. Using only a single mode, we propose to observe a full-orbit phase curve of one of the previously characterized, short-orbital-period planets to evaluate the facility-level aspects of long, uninterrupted time-series observations.

JWST Early Release Science (ERS)↗

NASA NTRS2016

Chaos in Kepler's Multiple Planet Systems and K2s Observations of the Atmospheres of Uranus Neptune

More than one-third of the 4700 planet candidates found by NASA's Kepler spacecraft during its prime mission are associated with target stars that have more than one planet candidate, and such "multis" account for the vast majority of candidates that have been verified as true planets. The large number of multis tells us that flat multiplanet systems like our Solar System are common. Virtually all of the candidate planetary systems are stable, as tested by numerical integrations that assume a physically motivated mass-radius relationship, but some of the systems lie in chaotic regions close to instability. The characteristics of some of the most interesting confirmed Kepler multi-planet systems will be discussed. The Kepler spacecraft's 'second life' in theK2 mission has allowed it to obtain long time-series observations of Solar System targets, including the giant planets Uranus & Neptune. These observations show variability caused by the chaotic weather patterns on Uranus & Neptune.

planet candidates↗

NASA NTRS2016

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to time-series data from Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus), OLI (Operational Land Imager), and MODIS (Moderate Resolution Imaging Spectroradiometer). Our effort has been focused on development of indicators of drought impacts in the March-August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March-September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Valleys↗

NASA NTRS2016

Impact of Scattering Model on Disdrometer Derived Attenuation Scaling

NASA Glenn Research Center (GRC), the Air Force Research Laboratory (AFRL), and the Politecnico di Milano (POLIMI) are currently entering the third year of a joint propagation study in Milan, Italy utilizing the 20 and 40 GHz beacons of the Alphasat TDP#5 Aldo Paraboni scientific payload. The Ka- and Q-band beacon receivers were installed at the POLIMI campus in June of 2014 and provide direct measurements of signal attenuation at each frequency. Collocated weather instrumentation provides concurrent measurement of atmospheric conditions at the receiver; included among these weather instruments is a Thies Clima Laser Precipitation Monitor (optical disdrometer) which records droplet size distributions (DSD) and droplet velocity distributions (DVD) during precipitation events. This information can be used to derive the specific attenuation at frequencies of interest and thereby scale measured attenuation data from one frequency to another. Given the ability to both predict the 40 gigahertz attenuation from the disdrometer and the 20 gigahertz time-series as well as to directly measure the 40 gigahertz attenuation with the beacon receiver, the Milan terminal is uniquely able to assess these scaling techniques and refine the methods used to infer attenuation from disdrometer data. In order to derive specific attenuation from the DSD, the forward scattering coefficient must be computed. In previous work, this has been done using the Mie scattering model, however, this assumes a spherical droplet shape. The primary goal of this analysis is to assess the impact of the scattering model and droplet shape on disdrometer-derived attenuation predictions by comparing the use of the Mie scattering model to the use of the T-matrix method, which does not assume a spherical droplet. In particular, this paper will investigate the impact of these two scattering approaches on the error of the resulting predictions as well as on the relationship between prediction error and rain rate.

Radio Transmission↗

NASA NTRS2016

Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function Over Northern High Latitude Forests

This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.

Australia↗

NASA NTRS2016

Transiting Exoplanet Studies and Community Targets for JWST's Early Release Science Program

The James Webb Space Telescope (JWST) will likely revolutionize transiting exoplanet atmospheric science, due to a combination of its capability for continuous, long duration observations and its larger collecting area, spectral coverage, and spectral resolution compared to existing space-based facilities. However, it is unclear precisely how well JWST will perform and which of its myriad instruments and observing modes will be best suited for transiting exoplanet studies. In this article, we describe a prefatory JWST Early Release Science (ERS) Cycle1 program that focuses on testing specific observing modes to quickly give the community the data and experience it needs to plan more efficient and successful transiting exoplanet characterization programs in later cycles. We propose a multi-pronged approach wherein one aspect of the program focuses on observing transits of a single target with all of the recommended observing modes to identify and understand potential systematics, compare transmission spectra at overlapping and neighboring wavelength regions, confirm throughputs, and determine overall performances. In our search for transiting exoplanets that are well suited to achieving these goals, we identify 12 objects (dubbed community targets) that meet our defined criteria. Currently, the most favorable target is WASP-62b because of its large predicted signal size, relatively bright host star, and location in JWSTs continuous viewing zone. Since most of the community targets do not have well-characterized atmospheres, we recommend initiating preparatory observing programs to determine the presence of obscuring cloudshazes within their atmospheres. Measurable spectroscopic features are needed to establish the optimal resolution and wavelength regions for exoplanet characterization. Other initiatives from our proposed ERS program include testing the instrument brightness limits and performing phase-curve observations. The latter are a unique challenge compared to transit observations because of their significantly longer durations. Using only a single mode, we propose to observe a full-orbit phase curve of one of the previously characterized, short-orbital-period planets to evaluate the facility-level aspects of long, uninterrupted time-series observations.

Stevenson, Kevin B.↗

NASA NTRS2016

A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description, Validation, and Case Study

In- land surface models, which are used to evaluate the role of vegetation in the context ofglobal climate change and variability, LAI and FAPAR play a key role, specifically with respect to thecarbon and water cycles. The AVHRR-based LAIFAPAR dataset offers daily temporal resolution,an improvement over previous products. This climate data record is based on a carefully calibratedand corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitablefor climate studies. It spans from mid-1981 to the present. Further, this operational dataset is availablein near real-time allowing use for monitoring purposes. The algorithm relies on artificial neuralnetworks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparisonwith MODIS products and in situ data show the dataset is consistent and reliable with overalluncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect isobserved in the broadleaf forest biomes with high LAI (greater than 4.5) and FAPAR (greater than 0.8) values.

MODIS↗