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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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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Differences between ERBE and CERES Tropical Mean Fluxes: ENSO, Climate Change or Calibration?

Verner E. Soumi was the father of radiation budget measurements from space. He directed the team at the University of Wisconsin that developed the first radiation budget measurements on the Iota (Explorer VII) coverage) spacecraft in 1959. The first data published was from hand calculations of night-time long-wave fluxes, with absolute accuracy estimated as better than 10 percent, and the data shown as hand drawn maps with lines of equal "long-wave radiation loss, in Langleys per minute X 10(exp -3) (isolangleys)". The first comparisons of the new radiation data with nephanalyses showed that clouds dominated the radiation patterns. Soumi immediately proposed using the radiation fields to help understand the atmospheric heat sources necessary to drive the atmospheric circulation. This early work already pointed to the relationship between the outgoing longwave radiation at the top of the atmosphere and the vertical flux divergence of infrared radiation within the atmosphere. In the next 30 years, global satellite observations of the radiation balance of the planet have advanced both in accuracy, stability, and in their ability to address cause and effect in the climate system. The purpose of the present paper is to examine early results of the new Clouds and the Earth's Radiant Energy System (CERES) data on Tropical Rainfall Measuring System (TRMM) which started data collection in January, 1998. CERES is a direct descendant of the legacy of Soumi's foresight on understanding the global energetics using satellite observations of broadband radiation.

Wielicki, Bruce A.↗
NASA NTRS1992

A three-dimensional simulation of the equatorial quasi-biennial oscillation

A simulation of the equatorial quasi-biennial oscillation (QBO) has been obtained using a three-dimensional mechanistic model of the stratosphere. The model is a simplified form of the NCAR CCM (Community Climate Model) in which the troposphere has been replaced with a specified geopotential distribution near the tropical tropopause and most of the physical parameterizations have been removed. A Kelvin wave and a Rossby-gravity wave are forced at the bottom boundary as in previous one- and two-dimensional models. The model reproduces most of the principal features of the observed QBO, as do previous models with lower dimensionality. The principal difference between the present model and previous QBO models is that the wave propagation is explicitly represented, allowing wave-wave interactions to take place. It is found that these interactions significantly affect the simulated oscillation. The interaction of the Rossby-gravity waves with the Kelvin waves results in about twice as much easterly compared to westerly forcing being required in order to obtain a QBO.

Takahashi, M.↗
NASA NTRS2012

The Response of Lower Atmospheric Ozone to ENSO in Aura Measurements and a Chemistry-Climate Simulation

The El Nino-Southern Oscillation (ENSO) is the dominant mode of tropical variability on interannual time scales. ENSO appears to extend its influence into the chemical composition of the tropical troposphere. Recent work has revealed an ENSO-induced wave-1 anomaly in observed tropical tropospheric column ozone. This results in a dipole over the western and eastern tropical Pacific, whereby differencing the two regions produces an ozone anomaly with an extremely high correlation to the Nino 3.4 Index. We have successfully reproduced this feature using the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 25 years. An examination of the modeled ozone field reveals the vertical contributions of tropospheric ozone to the column over the western and eastern Pacific region. We will show composition sensitivity in observations from NASA s Aura satellite Microwave Limb Sounder (MLS) and the Tropospheric Emissions Spectrometer (TES) and a simulation to provide insight into the vertical structure of these ENSO-induced ozone changes. The ozone changes due to the Quasi-Biennial Oscillation (QBO) in the extra-polar upper troposphere and lower stratosphere in MLS measurements will also be discussed.

Oman, L. D.↗
NASA NTRS1988

A Landsat Thematic Mapper investigation of the geobotanical relationships in the northern spruce-fir forest, Mt. Moosilauke, New Hampshire

This investigation, in the northern spruce-fir forest at Mt. Moosilauke, NH, indicates that Landsat TM data can be used to distinguish between and map major vegetation zones. Principal components analysis can be used to reduce the dimensionality of the TM data; and in this simpler spectral space, it is easier to visualize the discrimination between major vegetation zones: the northern hardwoods zone, spruce-fir zone, fir zone, and alpine tundra zone. The moisture stress index highlights areas of heavy forest damage (fir waves), but does not correlate with low levels of damage in the mixed, background forest at Mt. Moosilauke. Care must be taken to avoid confusion between high-elevation climatically-stressed vegetation (normal krummholz forest) and damaged lower elevation forests, both of which have similar TM5/TM4 ratio values.

Torcoletti, Paul J.↗
NASA NTRS2007

Multiyear On-orbit Calibration and Performance of Terra MODIS Thermal Emissive Bands

Since launch in December 1999, Terra MODIS has been making continuous Earth observations for more than seven years. It has produced a broad range of land, ocean, and atmospheric science data products for improvements in studies of global climate and environmental change. Among its 36 spectral bands, there are 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). MODIS thermal emissive bands cover the mid-wave infrared (MWIR) and long-wave infrared (LWIR) spectral regions with wavelengths from 3.7 to 14.4pm. They are calibrated on-orbit using an on-board blackbody (BB) with its temperature measured by a set of thermistors on a scan-by-scan basis. This paper will provide a brief overview of MODIS TEB calibration and characterization methodologies and illustrate on-board BB functions and TEB performance over more than seven years of on-orbit operation and calibration. Discussions will be focused on TEB detector short-term stability and noise characterization, and changes in long-term response (or system gain). Results show that Terra MODIS BB operation has been extremely stable since launch. When operated at its nominal controlled temperature of 290K, the BB temperature variation is typically less than +0.30mK on a scan-by-scan basis and there has been no time-dependent temperature drift. In addition to excellent short-term stability, most TEB detectors continue to meet or exceed their specified noise characterization requirements, thus enabling calibration accuracy and science data product quality to be maintained. Excluding the noisy detectors identified pre-launch and those that occurred post-launch, the changes in TEB responses have been less than 0.7% on an annual basis. The optical leak corrections applied to bands 32-36 have been effective and stable over the entire mission

Xiong, Xiaoxiong↗
NASA NTRS2011

Sensitivity of the Mid-Winter Arctic Stratosphere to QBO Width in a Simplified Chemistry-Climate Model

In the stratosphere, equatorial winds continually alternate between easterly (westward) and westerly (eastward). This phenomenon is called the quasi-biennial oscillation (QBO). The average QBO cycle (Le. easterly to westerly to easterly) lasts approximately 27 months. Large-scale 'planetary' waves can only travel upward through the atmosphere when equatorial winds are westerly, and below a critical threshold. Thus, the amount of wave energy that reaches the middle atmosphere depends on the wind direction. When equatorial winds are easterly, wave energy is concentrated at higher latitudes, weakening the high-latitude eastward wind feature known as the 'polar jet' during the Northern Hemisphere winter season. Holton and Tan (1980) used atmospheric observations to show the dependence of the strength of the northern polar jet on the phase (easterly vs. westerly) of the QBO. This modeling study finds that the width of the quasi-biennial oscillation (QBO) varies from one cycle to the next, and that variation in QBO width may exert equal influence on the Arctic stratosphere as does the QBO wind direction. High latitude winds are weaker and ozone values are higher in a wide-QBO model simulation, as compared with a realistic simulation. This result implies that a relatively wider QBO acts like a preferential shift toward the easterly phase of the QBO.

Hurwitz, M. M.↗
NASA NTRS2004

A Mechanism For Solar Forcing of Climate: Did the Maunder Minimum Cause the Little Ice Age?

The mechanism we wish to demonstrate exploits chemical, radiative, and dynamical sensitivities in the stratosphere to affect the climate of the troposphere. The sun, while its variability in total radiative output over the course of the solar cycle is on the order of 0.1%, exhibits variability in the UV output on the order of 5%. We expect to show that a substantially decreased solar UV output lessened the heating of the Earth's stratosphere during the Maunder Minimum, through decreased radiative absorption by ozone and oxygen. These changes in stratospheric heating would lead to major changes in the stratospheric zonal wind pattern which would in turn affect the propagation characteristics of planetary-scale waves launched in the winter hemisphere. Until recently, there was no quantitative data to relate the changes in the stratosphere to those at the surface. There is now empirical evidence from the NCEP Reanalysis data that a definitive effect of the solar cycle on climate in the troposphere exists. Our recent work is summarized as follows (see complete list of publications in later part of this report).

Yung, Yuk L.↗
NASA NTRSDate not supplied

Variability in Modelled Airborne Dust Mineralogy Derived from Global Soil Composition Uncertainties

Dust aerosols consist on a variety of minerals with different physic and chemical properties. As such, they interact with short and long wave radiation, potentially form clouds, act as nutrients modulating biogeochemical cycles, or influence atmospheric chemistry, differently. Most current state-of-the-art Earth System Models (ESMs) neglect the complexity in dust composition, mainly due to computational constraints, but also to the existing uncertainties in the size resolved composition of parent soils, the resulting distribution of minerals in airborne dust, and the scarcity of observations to constrain them. Within this work, we assess the variability of global dust composition due to uncertainties in the characterization of the parent soil mineralogy. To that end, we consider two available global soil mineralogy atlases, developed by Claquin et al. (1999) –C1999- and Journet et al. (2014) –J2014-, which represent respectively 8 and 12 relevant minerals for climate (namely: illite, smectite/montmorillonite, kaolinite, calcite, gypsum, hematite, quartz, and feldspars in C1999, and those plus chlorite, vermiculite, goethite, and mica in J2014). Thanks to a recently developed feature of the MONARCH atmospheric-chemistry model, we are able to explicitly resolve the minerals’ atmospheric cycle. Therefore, we define two global experiments to assess changes on airborne dust composition attributed to the soil mineralogy assumptions and provide a measure of their variability. We also perform a preliminary evaluation of the global mineralogy results against available observations of mineral fractions in surface dust concentration. Our results will inform the climate modelling community about the potential variability in dust composition, an aspect that will gain relevance as ESMs continue growing in complexity and new processes to better characterize aerosols’ forcing or biogeochemical cycles are added. Further observational constraints, such as those that will derive from the EMIT NASA mission on soil composition or the FRAGMENT experimental campaigns on airborne dust characterization, will be key in the near future to improve our understanding of the impact of dust mineralogy on fundamental climate features.

Dust aerosols↗
NASA NTRSDate not supplied

Applied Uses of MERRA Reanalyses: Current and Future Prospects

During the initial planning of the Modern Era Retrospective-analysis for Research and Applications (MERRA), the project was envisioned to become a tool for applied sciences and decision makers, as well as weather and climate research. MERRA was the first reanalysis to provide data at 1 hourly frequencies. After discussions with wind energy users, 50m above the surface winds were included in the data collection to begin to represent the environment at the turbine height. MERRA-2 was the first reanalysis to include interactive and assimilated aerosols. From these, PM 1, 2.5 and 10 records have been computed and contribute to the climate and health sector. The US Center for Disease Control is accessing MERRA-2 data for comparison along with their health data. MERRA-2 Extreme Indices have been computed from the high frequency data (e.g. precipitation maxima, heat waves and fire weather). These have been used to characterize the changing extremes in the United States and around the globe as well as the weather associated with the extremes. The next-generation, MERRA-21C, includes increased resolution (25km) and continues to provide innovative Earth system data. For example, a boundary layer collection will provide constant height level data starting at 100m, continuing up to 4000m. This will provide detailed information about the boundary layer processes that greatly affect the biosphere. Chemical tracers for constituents are included in the system. The ensemble data assimilation is run with 32 members, and the variance for critical variables are stored. We will explore the use of this variance as one measure of uncertainty relevant for applied uses, which has not been included in any MERRA reanalysis. We will discuss use case scenarios developed to engage with the energy and financial sectors, to better understand their needs for climate data. Prospects for further downscaling of reanalyses will also be explored.

Michael Bosilovich↗
NASA NTRS1986

An introduction to three-dimensional climate modeling

The development and use of three-dimensional computer models of the earth's climate are discussed. The processes and interactions of the atmosphere, oceans, and sea ice are examined. The basic theory of climate simulation which includes the fundamental equations, models, and numerical techniques for simulating the atmosphere, oceans, and sea ice is described. Simulated wind, temperature, precipitation, ocean current, and sea ice distribution data are presented and compared to observational data. The responses of the climate to various environmental changes, such as variations in solar output or increases in atmospheric carbon dioxide, are modeled. Future developments in climate modeling are considered. Information is also provided on the derivation of the energy equation, the finite difference barotropic forecast model, the spectral transform technique, and the finite difference shallow water waved equation model.

Washington, W. M.↗
NASA NTRS2015

Introduction The Role of the Agricultural Model Intercomparison and Improvement Project

Climate impacts on agriculture are of increasing concern in both the scientific and policy communities because of the need to ensure food security for a growing population. A special challenge is posed by the changes in the frequency and intensity of heat-waves, droughts, and episodic rainstorms already underway in many parts of the world. Changes in production are directly linked to such variations in temperature and precipitation during the growing season, and often to offseason changes in weather affecting soil-water storage and availability to crops. This is not an isolated problem but one of both global and regional importance, because of impacts on the livelihoods of smallholder farmers as well as consequences for the world food trade system. This two-part set the Agricultural Model Intercomparison and Improvement Project (AgMIP): Integrated Crop and Economic Assessments is the first to be entirely devoted to AgMIP (www.agmip.org). AgMIP is a major international research program focused on climate change and agriculture. The goal of the two parts is to advance the field by providing detailed information on new simulation techniques and assessments being conducted by this program. It presents information about new methods of global and regional integrated assessment, results from agricultural regions, and adaptation strategies for maintaining food security under changing climate conditions.

security↗
NASA NTRS2013

Impacts of Atmosphere-Ocean Coupling on Southern Hemisphere Climate Change

Climate in the Southern Hemisphere (SH) has undergone significant changes in recent decades. These changes are closely linked to the shift of the Southern Annular Mode (SAM) towards its positive polarity, which is driven primarily by Antarctic ozone depletion. There is growing evidence that Antarctic ozone depletion has significant impacts on Southern Ocean circulation change. However, it is poorly understood whether and how ocean feedback might impact the SAM and climate change in the SH atmosphere. This outstanding science question is investigated using the Goddard Earth Observing System Coupled Atmosphere-Ocean-Chemistry Climate Model(GEOS-AOCCM).We perform ensemble simulations of the recent past (1960-2010) with and without the interactive ocean. For simulations without the interactive ocean, we use sea surface temperatures and sea ice concentrations produced by the interactive ocean simulations. The differences between these two ensemble simulations quantify the effects of atmosphere-ocean coupling. We will investigate the impacts of atmosphere-ocean coupling on stratospheric processes such as Antarctic ozone depletion and Antarctic polar vortex breakup. We will address whether ocean feedback affects Rossby wave generation in the troposphere and wave propagation into the stratosphere. Another focuson this study is to assess how ocean feedback might affect the tropospheric SAM response to Antarctic ozone depletion

Chemistry-Climate Modeling↗
NASA NTRS1999

A Simple Stratosphere-Mesosphere Extension of the Held-Suarez Forcing for Dynamical Cores

A simple extension of the Held-Suarez (H-S) forcing that is capable of producing a realistic general circulation not only in the troposphere but also the stratosphere and the mesosphere will be presented. Similar to the original H-S forcing, an annual-mean like radiative equilibrium temperature is used. This extension is an ideal test bed for gravity wave drag parameterizations. It is also an inexpensive test bed for studying the mechanism of the Quasi-Biannual oscillations (QBO) and the "age spectrum" of the dynamical core formulation. The "mean climate" as well as the natural variability of the middle atmosphere as simulated by the NASA Data Assimilation Office finite-volume dynamical core under this forcing will be shown.

Lin, S.-J.↗
NASA NTRS2009

Comparison of Anomalies and Trends of OLR as Observed by CERES and Computed from Geophysical Parameters Derived from Analysis of AIRS/AMSU Data

Anomalies and trends of outgoing longwave radiation (OLR) serve as important indicators of climate change. Several satellite based instruments currently provide information related to OLR. CERES, on board the EOS Aqua and Terra satellites, contains broad band radiometers that measure total flux and short-wave flux, from which OLR is determined. AIRS is a high spectral resolution IR sounder on EOS Aqua that measures IR radiances covering most of the spectral interval 650 cm-1 to 2670 cm-1. These observations enable the determination of detailed information about atmospheric temperature, moisture, and ozone profiles, as well as surface skin temperatures and cloud parameters. The AIRS OLR product is the total flux over the spectral interval 2 cm-1 to2750 cm-1 computed for the surface and atmospheric state determined from AIRS observations. We compared spatial anomalies and trends of OLR, over the seven year period September 2002 through August 2009, as observed by CERES and computed using Version 5 AIRS products. These two sets of OLR anomalies and trends, obtained in very different ways, agree with each other almost perfectly in essentially every detail. This important finding shows that a very stable high spectral infra-red sounder such as AIRS corroborates the anomalies and trends of OLR obtained from CERES. More significantly, anomalies and trends of the individual geophysical parameters derived from AIRS explain the detailed causes of the anomalies and trends of CERES OLR. Both sets of results show that global mean OLR has been decreasing at a rate of 0.12 W/m2/yr over the seven year time period under study. Both also confirm that the primary cause of this is due to changes in the tropics, in which OLR has been decreasing at a rate of 0.27 W/m2/yr. AIRS products show that the decrease of tropical OLR is a result of increasing tropical atmospheric water vapor and cloud cover over the time period studied, which in turn is responding to a very strong E1 Nino/ La Nina cycle. Equatorial ocean temperatures between 160E and 120W cooled considerably during this time period, with corresponding local decreases in mid-tropospheric humidity and cloud cover, resulting in increases in local OLR. This was more than compensated by substantial increases in water vapor and cloud cover elsewhere in the tropics, resulting in a net decrease in tropical OLR.

Susskind, Joel↗
NASA NTRS2010

AIRS Products Confirm and Explain Recent Negative Trends of OLR as Observed by CERES

Anomalies and trends of OLR serve as important indicators of climate change. Several satellite based instruments currently provide information related to OLR. CERES, on board the EOS Aqua and Terra satellites, contains broad band radiometers that measure total flux and short-wave flux, from which OLR is determined. AIRS is a high spectral resolution IR sounder on EOS Aqua that measures IR radiances covering most of the spectral interval 650/cm to 2670/cm. These observations enable the determination of detailed information about atmospheric temperature, moisture, and ozone profiles, as well as surface skin temperatures and cloud parameters. The AIRS OLR product is the total flux over the spectral interval 2/cm to 2750/cm computed for the surface and atmospheric state determined from AIRS observations. We compared spatial anomalies and trends of OLR, over the seven year period September 2002 through August 2009, as observed by CERES and computed using Version-5 AIRS products. These two sets of OLR anomalies and trends, obtained in very different ways, agree with each other almost perfectly in essentially every detail. This important finding shows that a very stable high spectral infra-red sounder such as AIRS corroborates the anomalies and trends of OLR obtained from CERES. More significantly, anomalies and trends of the individual geophysical parameters derived from AIRS explain the detailed causes of the anomalies and trends of CERES OLR. Both sets of results show that global mean OLR has been decreasing at a rate of 0.12 W/sq m/yr over the seven year time period under study. Both also confirm that the primary cause of this is due to changes in the tropics, in which OLR has been decreasing at a rate of 0.27 W/sq m/yr. AIRS products show that the decrease of tropical OLR is a result of increasing tropical atmospheric water vapor and cloud cover over that time period studied, which in turn is responding to a very strong La Nina; a event starting in late 2007. Equatorial ocean temperatures between 160 E and 120 W cooled considerably during this time period, with corresponding local decreases in mid-tropospheric humidity and cloud cover, resulting in increases in local OLR. This was more than compensated by substantial increases in water vapor and cloud cover elsewhere in the tropics, resulting in a net decrease in tropical OLR. The AIRS Version-5 products currently extend through December 2009. An El Nino event began in late 2009. AIRS products show that tropical OLR began to increase at that time, and there was a corresponding reversal of sign of tropical cloud and water vapor anomalies.

Susskind, Joel↗
NASA NTRS2017

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗
NASA NTRS2017

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗
NASA NTRS2018

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Neural↗