ALBERT

Description: It is our hope that the "Landsat Legacy" story will appeal to a broader audience than just those who use Landsat data on a regular basis. In an era when ready access to images and data from Earth-observing satellites is routine, it is hard to believe that only a few decades ago this was not the case. As the world's first digital land-observing satellite program, Landsat missions laid the foundation for modern space-based Earth observation and blazed the trail in the new field of quantitative remote sensing.

Description: A steep decline in archiving could make large tree-ring datasets irrelevant. But increased spatiotemporal coverage, the addition of novel parameters at sub-annual resolution, and integration with other in situ and remote Earth observations will elevate tree-ring data as an essential component of global-change research.

Description: Leaf Area Index (LAI) is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs). We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), two versions of the Enhanced Vegetation Index (EVI and EVI2), and Green Chlorophyll Index (CI(sub Green)). Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS) robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 greater than 0.5), and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

Description: Pre-launch characterization and calibration of the thermal emissive spectral bands on the Joint Polar Satellite System (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS) is critical to ensure high quality data products for environmental and climate data records post-launch. A comprehensive test program was conducted at the Raytheon El Segundo facility in 2013-2014, including extensive environmental testing. This work is focused on the thermal band radiometric performance and stability, including evaluation of a number of sensor performance metrics and estimation of uncertainties. Analysis has shown that JPSS-1 VIIRS thermal bands perform very well in relation to their design specifications, and comparisons to the Suomi National Polar-orbiting Partnership (SNPP) VIIRS instrument have shown their performance to be comparable.

Description: The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing dataset that ranges from the 1980's to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance time-series and to augment the AVHRR data record with data from other sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS). In this paper, we present a summary of all the corrections applied to the AVHRR Surface Reflectance and NDVI Version 4 Product, developed in the framework of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program. These corrections result from assessment of the geo-location, improvement of the cloud masking and calibration monitoring. Additionally, we evaluate the performance of the surface reflectance over the AERONET sites by a cross-comparison with MODIS, which is an already validated product, and evaluation of a downstream Leaf Area Index (LAI) product. We demonstrate the utility of this long time-series by estimating the winter wheat yield over the USA. The methods developed by [1] and [2] are applied to both the MODIS and AVHRR data. Comparison of the results from both sensors during the MODIS-era shows the consistency of the dataset with similar errors of 10%. When applying the methods to AVHRR historical data from the 1980's, the results have errors equivalent to those derived from MODIS.

Description: The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial carbon dioxide fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem carbon dioxide exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated carbon dioxide fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8 days are reproduced (e.g., r (exp 2) =0.73 and 0.42 for 8 day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r (exp 2)=1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land carbon dioxide fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land carbon dioxide fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land carbon dioxide fluxes. These data-driven estimates can provide a new opportunity to assess carbon dioxide fluxes in Asia and evaluate and constrain terrestrial ecosystem models.

Description: On 27 August 2013, during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys field mission, NASA's ER2 research aircraft encountered a region of enhanced water vapor, extending over a depth of approximately 2 km and a minimum areal extent of 20,000 km(exp 2) in the stratosphere (375 K to 415 K potential temperature), south of the Great Lakes (42N, 90W). Water vapor mixing ratios in this plume, measured by the Harvard Water Vapor instrument, constitute the highest values recorded in situ at these potential temperatures and latitudes. An analysis of geostationary satellite imagery in combination with trajectory calculations links this water vapor enhancement to its source, a deep tropopausepenetrating convective storm system that developed over Minnesota 20 h prior to the aircraft plume encounter. High resolution, groundbased radar data reveal that this system was composed of multiple individual storms, each with convective turrets that extended to a maximum of ~4 km above the tropopause level for several hours. In situ water vapor data show that this storm system irreversibly delivered between 6.6 kt and 13.5 kt of water to the stratosphere. This constitutes a 2025% increase in water vapor abundance in a column extending from 115 hP to 70 hPa over the plume area. Both in situ and satellite climatologies show a high frequency of localized water vapor enhancements over the central U.S. in summer, suggesting that deep convection can contribute to the stratospheric water budget over this region and season.

Description: A deeper understanding of how clouds will respond to a warming climate is one of the outstanding challenges in climate science. Uncertainties in the response of clouds, and particularly shallow clouds, have been identified as the dominant source of the discrepancy in model estimates of equilibrium climate sensitivity. As the community gains a deeper understanding of the many processes involved, there is a growing appreciation of the critical role played by fluctuations in water vapor and the coupling of water vapor and atmospheric circulations. Reduction of uncertainties in cloud-climate feedbacks and convection initiation as well as improved understanding of processes governing these effects will result from profiling of water vapor in the lower troposphere with improved accuracy and vertical resolution compared to existing airborne and space-based measurements. This paper highlights new technologies and improved measurement approaches for measuring lower tropospheric water vapor and their expected added value to current observations. Those include differential absorption lidar and radar, microwave occultation between low-Earth orbiters, and hyperspectral microwave remote sensing. Each methodology is briefly explained, and measurement capabilities as well as the current technological readiness for aircraft and satellite implementation are specified. Potential synergies between the technologies are discussed, actual examples hereof are given, and future perspectives are explored. Based on technical maturity and the foreseen near-mid-term development path of the various discussed measurement approaches, we find that improved measurements of water vapor throughout the troposphere would greatly benefit from the combination of differential absorption lidar focusing on the lower troposphere with passive remote sensors constraining the upper-tropospheric humidity.

Description: In this work, we use the Clouds and the Earths Radiant Energy System (CERES) FluxByCloudTyp data product, which calculates TOA shortwave and longwave fluxes for cloud categories defined by cloud optical depth () and cloud top pressure (), to evaluate the HadGEM2-A model with a simulator. The CERES Flux-by-cloud type simulator is comprised of a cloud generator that produces subcolumns with profiles of binary cloud fraction, a cloud property simulator that determines the (,) cloud type for each subcolumn, and a radiative transfer model that calculates TOA fluxes. The identification of duplicate atmospheric profiles reduces the number of radiative transfer calculations required by approximately 97.6%. In the Southern Great Plains region in JFD (January, February, and December) 2008, the simulator shows that simulated cloud tops are higher in altitude than observed, but also have higher values of OLR than observed, leading to a compensating error that results in an average value of OLR that is close to observed. When the simulator is applied to the Southeast Pacific stratocumulus region in JJA 2008, the simulated cloud tops are primarily low in altitude; however, the clouds tend to be less numerous, and have higher optical depths than are observed. In addition to the increase in albedo that comes from having too many clouds with higher optical depth, the HadGEM2-A albedo is higher than observed for those cloud types that occur most frequently. The simulator is also applied to the entire 60 N 60 S region, and it is found that there are fewer clouds than observed for most cloud types, but there are also higher albedos for most cloud types, which represents a compensating error in terms of the shortwave radiative budget.

Description: The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure high-resolution atmospheric profiles of ozone. The accurate characterization of these lidars is necessary to determine the uniformity of the network calibration. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission and the Front Range Air Pollution and Photochemistry xperiment (FRAPP) to measure ozone variations from the boundary layer to the top of the troposphere. This study presents the analysis of the intercomparison between the TROPOZ, TOPAZ, and LMOL lidars, along with comparisons between the lidars and other in situ ozone instruments including ozonesondes and a P-3B airborne chemiluminescence sensor. The TOLNet lidars measured vertical ozone structures with an accuracy generally better than 15 % within the troposphere. Larger differences occur at some individual altitudes in both the near-field and far-field range of the lidar systems, largely as expected. In terms of column average, the TOLNet lidars measured ozone with an accuracy better than 5 % for both the intercomparison between the lidars and between the lidars and other instruments. These results indicate that these three TOLNet lidars are suitable for use in air quality, satellite validation, and ozone modeling efforts.

Description: Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality and atmospheric chemistry. The understanding and ability to model the horizontal and vertical structure of O3 mixing ratios is difficult due to the complex formation/destruction processes and transport pathways that cause large variability of O3. The Environmental Protection Agency has National Ambient Air Quality Standards for O3 set at 75 ppb with future standards proposed to be as low as 65 ppb. These lower values emphasize the need to better understand/simulate the transport processes, emission sources, and chemical processes controlling precursor species (e.g., NOx, VOCs, and CO) which influence O3 mixing ratios. The uncertainty of these controlling variables is particularly large in the southeast United States (US) which is a region impacted by multiple different emission sources of precursor species (anthropogenic and biogenic) and transport processes resulting in complex spatio-temporal O3 patterns. During this work we will evaluate O3 and precursor species in the southeast US applying models, ground-based and airborne in situ data, and lidar observations. In the summer of 2013, the UAH O3 Differential Absorption Lidar (DIAL) (part of the Tropospheric Ozone Lidar Network (TOLNet)) measured vertical O3 profiles from the surface up to approximately 12 km. During this period, the lidar observed numerous periods of dynamic temporal and vertical O3 structures. In order to determine the sources/processes impacting these O3 mixing ratios we will apply the CTM GEOS-Chem (v9-02) at a 0.25 deg x 0.3125 deg resolution. Using in situ ground-based (e.g., SEARCH Network, CASTNET), airborne (e.g., NOAA WP-3D - SENEX 2013, DC-8 - SEAC4RS), and TOLNet lidar data we will first evaluate the model to determine the capability of GEOS-Chem to simulate the spatio-temporal variability of O3 in the southeast US. Secondly, we will perform model sensitivity studies in order to quantify which emission sources (e.g., anthropogenic, biogenic, lighting, wildfire) and transport processes (e.g., stratospheric, long-range, local scale) are contributing to these TOLNet-observed dynamic O3 patterns. Results from the evaluation of the model and the study of sources/processes impacting observed O3 mixing ratios will be presented.

Description: Ecosystems worldwide are impacted by altered environment conditions resulting from climate, drought, and land use changes. Gaps in the science knowledge base regarding plant community response to these novel and rapid changes limit both science understanding and management of ecosystems. We describe how CE Technologies have enabled the rapid supply of gap-filling science, development of ecosystem simulation models, and remote sensing assessment tools to provide science-informed, adaptive management methods in the impacted aquatic ecosystem of the California Sacramento-San Joaquin River Delta. The Delta is the hub for California's water, supplying Southern California agriculture and urban communities as well as the San Francisco Bay area. The changes in environmental conditions including temperature, light, and water quality and associated expansion of invasive aquatic plants negatively impact water distribution and ecology of the San Francisco Bay/Delta complex. CE technologies define changes in resource use efficiencies, photosynthetic productivity, evapotranspiration, phenology, reproductive strategies, and spectral reflectance modifications in native and invasive species in response to altered conditions. We will discuss how the CE technologies play an enabling role in filling knowledge gaps regarding plant response to altered environments, parameterization and validation of ecosystem models, development of satellite-based, remote sensing tools, and operational management strategies.

Description: Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.

Description: Aerosol types measured during the Ship-Aircraft Bio-Optical Research (SABOR) experiment are related to GEOS-Chem model chemical composition. The application for this procedure to link model chemical components to aerosol type is desirable for understanding aerosol evolution over time. The Mahalanobis distance (DM) statistic is used to cluster model groupings of five chemical components (organic carbon, black carbon, sea salt, dust and sulfate) in a way analogous to the methods used by Burton et al. [2012] and Russell et al. [2014]. First, model-to-measurement evaluation is performed by collocating vertically resolved aerosol extinction from SABOR High Spectral Resolution LiDAR (HSRL) to the GEOS-Chem nested high-resolution data. Comparisons of modeled-to-measured aerosol extinction are shown to be within 35% +/- 14%. Second, the model chemical components are calculation into five variables to calculate the DM and cluster means and covariances for each HSRL-retrieved aerosol type. The layer variables from the model are aerosol optical depth (AOD) ratios of (i) sea salt and (ii) dust to total AOD, mass ratios of (iii) total carbon (i.e. sum of organic and black carbon) to the sum of total carbon and sulfate (iv) organic carbon to black carbon, and (v) the natural log of the aerosol-to-molecular extinction ratio. Third, the layer variables and at most five out of twenty SABOR flights are used to form the pre-specified clusters for calculating DM and to assign an aerosol type. After determining the pre-specified clusters, model aerosol types are produced for the entire vertically resolved GEOS-Chem nested domain over the United States and the model chemical component distributions relating to each type are recorded. Resulting aerosol types are Dust/Dusty Mix, Maritime, Smoke, Urban and Fresh Smoke (separated into 'dark' and 'light' by a threshold of the organic to black carbon ratio). Model-calculated DM not belonging to a specific type (i.e. not meeting a threshold probability) is termed an outlier and those DM values that can belong to multiple types (i.e. showing weak probability of belonging to a specific cluster) are termed as Overlap. MODIS active fires are overlaid on the model domain to qualitatively evaluate the model-predicted Smoke aerosol types.

Description: Formaldehyde (HCHO) is one of the most abundant oxygenated volatile organic compounds (VOCs) in the atmosphere, playing a role multiple atmospheric processes. Measurements of HCHO can be used to help quantify convective transport, the abundance of VOCs, and ozone production in urban environments. The Compact Formaldehyde FluorescencE Experiment (COFFEE) instrument uses Non-Resonant Laser Induced Fluorescence (NR-LIF) to detect trace concentrations of HCHO as part of the Alpha Jet Atmospheric eXperiment (AJAX) payload. Developed at NASA GSFC, COFFEE is a small, low maintenance instrument with a sensitivity of 100 pptv and a quick response time (1 sec). The COFFEE instrument has been customized to fit in an external wing pod on the Alpha Jet aircraft based at NASA ARC. The instrument can operate over a broad range of altitudes, from boundary layer to lower stratosphere, making it well suited for the Alpha Jet, which can access altitudes from the surface up to 40,000 ft. Results of the first COFFEE science flights preformed over the California's Central Valley will be presented. Boundary layer measurements and vertical profiles in the tropospheric column will both be included. This region is of particular interest, due to its elevated levels of HCHO, revealed in satellite images, as well as its high ozone concentrations. In addition to HCHO, the AJAX payload includes measurements of atmospheric ozone, methane, and carbon dioxide. Formaldehyde is one of the few urban pollutants that can be measured from space. Plans to compare in-situ COFFEE data with satellite-based HCHO observations such as those from OMI (Aura) and OMPS (SuomiNPP) will also be presented.

Description: Reflected or emitted energy from solid surfaces in the solar system can provide insight into thermo-physical and chemical properties of the surface materials. Measurements have been obtained from instruments located on Earth-based telescopes and carried on several space missions. The characteristic spectral features commonly observed in Mid-Infrared (MIR) spectra of minerals will be reviewed, along with methods used for compositional interpretations of MIR emission spectra. The influence of surface grain size, and space weathering processes on MIR emissivity spectra will also be discussed. Methods used for estimating surface temperature, emissivity, and thermal inertias from MIR spectral observations will be reviewed.

Description: The Staring OBservations of the Atmosphere (SOBA) Mission is a concept that was developed and matured under the guidance of the NASA Ames Project EXellence (APEX) program. If funded, it will provide an unprecedented opportunity to improve ash transport forecasts and climate model simulations associated with volcanic eruptions. NASA and National science objectives require a better understanding of volcanic aerosol and trace gas emissions, transport, chemical transformation, and deposition, since they impact Earth's climate and atmospheric composition, human health, and aviation safety. Natural hazards such as the 2010 eruption of the Eyjafjallajkull volcano in Iceland demonstrated how existing remote-sensing assets were inadequate for individual volcanic event monitoring. During this eruption, available instruments were unable to provide data necessary to initialize volcanic plume transport models so that they could accurately predict the quantity and location of volcanic ash. As a result, thousands of flights around the world were grounded unnecessarily, at great expense. Volcanoes can also play a large role in regulation of the Earth's climate, so SOBA observations will also be used to evaluate and improve volcanic aerosol and trace gas simulation in chemical transport models (CTMs) and global climate models (GCMs). We propose the development of an airborne remote sensing concept and field campaign that will respond to an eruption and provide near real time observations of a volcanic plume, specifically ash injection height, transport, aerosol microphysical physical properties, and the location and concentration of sulfur dioxide (SO2) (sulfate (SO42-) aerosol precursor). This airborne system will utilize a depolarization sensitive, downward looking Light Detection And Ranging (lidar) instrument and an ultraviolet (UV) imaging spectrometer, and will provide data to be ingested by volcanic ash advisory models. Furthermore, the lessons learned in the development of this system could eventually guide regular deployment of similar systems by NASA or other government agencies.

Description: Despite the critical importance of photosynthesis for the Earth system, understanding how it is influenced by factors such as climate variability, disturbance history, and water or nutrient availability remains a challenge because of the complex interactions and the lack of GPP measurements at various temporal and spatial scales. Space observations of the sun-induced chlorophyll fluorescence (SIF) electromagnetic signal emitted by plants in the 650-850nm spectral range hold the promise of providing a new view of vegetation photosynthesis on a global basis. Global retrievals of SIF from space have recently been achieved from a number of spaceborne spectrometers originally intended for atmospheric research. Despite not having been designed for land applications, such instruments have turned out to provide the necessary spectral and radiometric sensitivity for SIF retrieval from space. The first global measurements of SIF were achieved in 2011 from spectra acquired by the Japanese GOSAT mission launched in 2009. The retrieval takes advantage of the high spectral resolution provided by GOSATs Fourier Transform Spectrometer (FTS) which allows the evaluation of the in-filling of solar Fraunhofer lines by SIF. Unfortunately, GOSAT only provides a sparse spatial sampling with individual soundings separated by several hundred kilometers. Complementary, the Global Ozone Monitoring Experiment-2 (GOME-2) instruments onboard MetOp-A and MetOp-B enable SIF retrievals since 2007 with a continuous and global spatial coverage. GOME-2 measures in the red and near-infrared (NIR) spectral regions with a spectral resolution of 0.5 nm and a pixel size of up to 40x40 km2. Most recently, another global and spatially continuous data set of SIF retrievals at 740 nm spanning the 2003-2012 time frame has been produced from ENVISATSCIAMACHY. This observational scenario has been completed by the first fluorescence data from the NASA-JPL OCO-2 mission (launched in July 2014) and the upcoming Copernicus' Sentinel 5-Precursor to be launched in early 2016. OCO-2 and TROPOMI offer the possibility of monitoring SIF globally with a 100-fold improvement in spatial and temporal resolution with respect to the current measurements from the GOSAT, GOME-2 and SCIAMACHY missions. In this contribution, we will provide an overview of existing global SIF data sets derived from space-based atmospheric spectrometers and will demonstrate the potential of such data to improve our knowledge of vegetation photosynthesis and gross primary production at the synoptic scale. We will show examples of ongoing research exploiting SIF data for an improved monitoring of photosynthetic activity in different ecosystems, including large crop belts worldwide, the Amazon rainforest and boreal evergreen forests.

Description: The California Sacramento-San Joaquin River Delta is the hub for Californias water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

Description: In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the world's coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85%. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

Description: This paper will describe the information technologies developed by NASA and NOAA for the February 2016 Sensing Hazards with Operational Unmanned Technology (SHOUT) El Nio Southern Oscillation (ENSO) Campaign. The air vehicle is a NASA Global Hawk UAS, with a primary payload of four instruments, two developed by NASA, two developed by NOAA. The aircraft is based at the NASA Armstrong Flight Research Center, Edwards Air Force Base, California. The payload components are remotely operated by scientists at various facilities, and the data collected downloaded over satellite links in real time for analysis and collaboration. NOAA: Advanced Vertical Atmospheric Profiling System (AVAPS), developed by NCAR, which deploys dozens of dropsondes at altitudes up to 65,000 ft to collect high vertical resolution measurements of the temperature, pressure, relative humidity, and wind speed and direction. NASA: High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP), a radar designed to examine the factors of storm intensity: formation, structure and intensification. NOAA: O3 Photometer (UAS-O3), designed specifically for autonomous, precise, and accurate O3 measurements in the upper troposphere and lower stratosphere (UT/LS). NASA JPL: High Altitude MMIC Sounding Radiometer (HAMSR), an atmospheric microwave temperature and humidity sounder instrument that looks at the microwave spectrum.

Description: The NASA Ames Sun-photometer-Satellite Group, DOE, PNNL Atmospheric Sciences and Global Change Division, and NASA Goddards AERONET (AErosol RObotic NETwork) team recently collaborated on the development of a new airborne sunphotometry instrument that provides information on gases and aerosols extending far beyond what can be derived from discrete-channel direct-beam measurements, while preserving or enhancing many of the desirable AATS features (e.g., compactness, versatility, automation, reliability). The enhanced instrument combines the sun-tracking ability of the current 14-Channel NASA Ames AATS-14 with the sky-scanning ability of the ground-based AERONET Sunsky photometers, while extending both AATS-14 and AERONET capabilities by providing full spectral information from the UV (350 nm) to the SWIR (1,700 nm). Strengths of this measurement approach include many more wavelengths (isolated from gas absorption features) that may be used to characterize aerosols and detailed (oversampled) measurements of the absorption features of specific gas constituents. The Sky Scanning Sun Tracking Airborne Radiometer (3STAR) replicates the radiometer functionality of the AATS14 instrument but incorporates modern COTS technologies for all instruments subsystems. A 19-channel radiometer bundle design is borrowed from a commercial water column radiance instrument manufactured by Biospherical Instruments of San Diego California (ref, Morrow and Hooker)) and developed using NASA funds under the Small Business Innovative Research (SBIR) program. The 3STAR design also incorporates the latest in robotic motor technology embodied in Rotary actuators from Oriental motor Corp. having better than 15 arc seconds of positioning accuracy. Control system was designed, tested and simulated using a Hybrid-Dynamical modeling methodology. The design also replaces the classic quadrant detector tracking sensor with a wide dynamic range camera that provides a high precision solar position tracking signal as well as an image of the sky in the 45 field of view around the solar axis, which can be of great assistance in flagging data for cloud effects or other factors that might impact data quality.

Description: As part of the Southeast United States-based Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), and collinear with part of the Southeast Atmosphere Study, the University of Wisconsin High Spectral Resolution Lidar system was deployed to the University of Alabama from 19 June to 4 November 2013. With a collocated Aerosol Robotic Network (AERONET) sun photometer, a nearby Chemical Speciation Network (PM2.5) measurement station, and near daily ozonesonde releases for the August-September SEAC4RS campaign, the site allowed the regions first comprehensive diurnal monitoring of aerosol particle vertical structure. A 532nm lidar ratio of 55 sr provided good closure between aerosol backscatter and AERONET (aerosol optical thickness, AOT). A principle component analysis was performed to identify key modes of variability in aerosol backscatter. ''Fair weather'' days exhibited classic planetary boundary layer structure of a mixed layer accounting for approx. 50% of AOT and an entrainment zone providing another 25%. An additional 5-15% of variance is gained from the lower free troposphere from either convective detrainment or frequent intrusions of western United States biomass burning smoke. Generally, aerosol particles were contained below the 0 C level, a common level of stability in convective regimes. However, occasional strong injections of smoke to the upper troposphere were also observed, accounting for the remaining 10-15% variability in AOT. Examples of these common modes of variability in frontal and convective regimes are presented, demonstrating why AOT often has only a weak relationship to surface PM2.5 concentration.

Description: NASA Ames Research Center, located at the southern end of the San Francisco Bay (SFB) estuary has identified three primary vulnerabilities to changes in climate. The Ames Climate Adaptation Science Investigator (CASI) workgroup has studied each of these challenges to operations and the potential exposure of infrastructure and employees to an increased frequency of hazards. Sea level rise inundation scenarios for the SFB Area generally refer to projected scenarios in mean sea level rather than changes in extreme tides that could occur during future storm conditions. In the Summer of 2014, high resolution 3-D mapping of the low lying portion of Ames was performed. Those data are integrated with improved sea level inundation scenarios to identify the buildings, basements and drainage systems potentially affected. We will also identify the impacts of sea level and storm surge effects on transportation to and from the Center. This information will help Center Management develop future Master Plans. Climate change will also lead to changes in temperature, storm frequency and intensity. These changes have potential impacts on localized floods and ecosystems, as well as on electricity and water availability. Over the coming decades, these changes are going to be imposed on top of ongoing land use and land cover changes, especially those deriving from continued urbanization and increase in impervious surface areas. These coupled changes have the potential to create a series of cascading impacts on ecosystems, including changes in primary productivity and disturbance of hydrological properties and increased flood risk.The majority of the electricity used at Ames is supplied by hydroelectric dams, which will be influenced by reductions in precipitation or changes in the timing or phase of precipitation which reduces snow pack. Coupled with increased demand for summertime air conditioning and other cooling needs, NASA Ames is at risk for electricity shortfalls. To assess the anticipated energy usage as climate changes, the Ames CASI team is collecting historical energy usage data from Ames facilities, historical weather data, and projected future weather parameters from the CASI Climate subgroup. This data will be incorporated into the RETScreen model to predict how energy usage at Ames will change over the coming century.

Description: We present interpreted data analysis using MAIAC (Multiangle implementation of Atmospheric Correction) retrievals and appropriate RAPid Update Cycle (RAP) meteorology to map respirable aerosol (PM2.5) for the period January and February, 2011. The San Joaquin Valley is one of the unhealthiest regions in the USA for PM2.5 and related morbidity. The methodology evaluated can be used for the entire moderate-resolution imaging spectrometer (MODIS, VIIRS) data record. Other difficult areas of the West: Riverside, CA, Salt Lake City, UT, and Doa Ana County, NM share similar difficulties and solutions. The maps of boundary layer depth for 1116 hr local time from RAP allows us to interpret aerosol optical thickness as a concentration of particles in a nearly well-mixed box capped by clean air. That mixing is demonstrated by DISCOVER-AQ data and afternoon samples from the airborne measurements, P3B (on-board) and B200 (HSRL2 lidar). This data and the PM2.5 gathered at the deployment sites allowed us to estimate and then evaluate consistency and daily variation of the AOT to PM2.5 relationship. Mixed-effects modeling allowed a refinement of that relation from day to day; RAP mixed layers explained the success of previous mixed-effects modeling. Compositional, size-distribution, and MODIS angle-of-regard effects seem to describe the need for residual daily correction beyond ML depth.We report on an extension method to the entire San Joaquin Valley for all days with MODIS imagery using the permanent PM2.5 stations, evaluated for representativeness. Resulting map movies show distinct sources, particularly Interstate-5 (at approx. 1km x 1km resolution) and the broader Bakersfield area. Accompanying winds suggest transport effects and variable pathways of pollution cleanout. Such estimates should allow morbiditymortality studies. They should be also useful for actual model assimilations, where composition and sources are uncertain. We conclude with a description of new work to extend these insights to similar regions, e.g. interior valleys of California, the Po Valley, the Mediterranean litoral, and the Ganges Plain.This work show generalizable use of remote sensing, a major goal of DISCOVER-AQ, Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality.

Description: Remotely piloted aircraft (RPA) have the potential to revolutionize local to regional data collection for geophysicists as platform and payload size decrease while aircraft capabilities increase. In particular, data from RPAs combine high-resolution imagery available from low flight elevations with comprehensive areal coverage, unattainable from ground investigations and difficult to acquire from manned aircraft due to budgetary and logistical costs. Low flight elevations are particularly important for detecting signals that decay exponentially with distance, such as electromagnetic fields. Onboard data processing coupled with high-bandwidth telemetry open up opportunities for real-time and near real-time data processing, producing more efficient flight plans through the use of payload-directed flight, machine learning and autonomous systems. Such applications not only strive to enhance data collection, but also enable novel sensing modalities and temporal resolution. NASAs Airborne Science Program has been refining the capabilities and applications of RPA in support of satellite calibration and data product validation for several decades. In this paper, we describe current platforms, payloads, and onboard data systems available to the research community. Case studies include Fluid Lensing for littoral zone 3D mapping, structure from motion for terrestrial 3D multispectral imaging, and airborne magnetometry on medium and small RPAs.

Description: We present two new products from near-infrared GOSAT observations: lower tropospheric (LMT, from 0-2.5 km) and upper tropospheric/stratospheric (U, above 2.5 km) carbon dioxide partial columns. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial columns significantly improve over the ACOS-GOSAT initial guess/a priori, with distinct patterns in the LMT and U seasonal cycles which match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8 ppm for retrieved GOSAT LMT, U, and XCO2; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5 ppm for retrieved GOSAT LMT, U, and XCO2. In the southern hemisphere biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and CO/CO2 emission factor consistent with published values. The difference of LMT and U, useful for evaluation of model transport error, has also been validated with monthly average error of 0.8 (1.4) ppm for ocean (land). The new LMT partial column is more locally influenced than the U partial column, meaning that local fluxes can now be separated from CO2 transported from far away.

Description: A Fourier Transform Spectrometer (FTS) was deployed to the Armstrong Flight Research Center (AFRC) in Edwards, CA as a member of the Total Carbon Column Observing Network (TCCON) and has now been in operation for over 3 years. The data record from AFRC will be presented as well as airborne validation profiles obtained during the NASA SEAC4RS, SARP, KORUS-AQ, and ATom missions utilizing various NASA aircraft. One of the reasons that the AFRC location was selected is due to its proximity to a highly reflective lakebed, which has proven to be difficult for accurate satellite retrievals. As such, the data from AFRC has been used for OCO-2 calibration. In order for accurate calibration of OCO-2, the validity of the TCCON measurements must be established. To this end, integrated airborne in-situ vertical profiles will be presented and compared with the TCCON FTS measurements, where good agreement has been found.

Description: The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign is taking place in the SouthEast Atlantic during the Austral Spring for three consecutive years from 20162018. The study area encompasses one of the Earths three semipermanent subtropical Stratocumulus (Sc) cloud decks,and experiences very large aerosol optical depths, mainly biomass burning, originating from Africa. Over time, cloud optical depth (COD), lifetime and cloud microphysics (number concentration, effective radii Reff and precipitation) are expected to be influenced by indirect aerosol effects. These changes play a key role in the energetic balance of the region, and are part of the core investigation objectives of the ORACLES campaign, which acquires measurements of clean and polluted scenes of above cloud aerosols (ACA). Simultaneous retrievals of aerosol and cloud optical properties are being developed (e.g. MODIS, OMI), butstill challenging, especially for passive, single viewing angle instruments. By comparison, multiangle polarimetric instruments like RSP (Research Scanning Polarimeter) show promise for detection and quantification of ACA, however, there are no operational retrieval algorithms available yet. Here we describe anew algorithm to retrieve cloud and aerosol optical properties from observations by RSP flown on the ER2and P3 during the 2016 ORACLES campaign. The algorithm is based on training a NN, and is intended to retrieve aerosol and cloud properties simultaneously. However, the first step was to establish the retrievalscheme for low level Sc cloud optical properties. The NN training was based on simulated RSP total and polarized radiances for a range of COD, Reff, and effective variances, spanning 7 wavelength bands and 152 viewing zenith angles. Random and correlated noise were added to the simulations to achieve a morerealistic representation of the signals. Before introducing the input variables to the network, the signals are projected on a principle component plane that retains the maximal signal information but minimizes the noise contribution. We will discuss parameter choices for the network and present preliminary results of cloudretrievals from ORACLES, compared with standard RSP low-levelcloud retrieval method that has been validated against in situ observations.

Description: Hydrogen cyanide (HCN) has successfully been used as a tracer of biomassburning in the context of aircraft campaigns. We show HCN observations fromAura-TES for a major fire in Indonesia in 2006, and globally over differentseasons. We develop a fire-influence flag for TES observations and show howthis relates to enhancements of other TES products, such as PAN, carbonmonoxide, and ozone.

Description: In October 2015, the Environmental Protection Agency lowered the National Ambient Air Quality Standard for ozone (O3) from 75 ppbv to 70 ppbv. However, meeting the stricter air standards is a challenge for certain areas of California, like the San Joaquin Valley (SJV), where O3 levels are typically high due to topography, meteorology, and local emissions. Another factor potentially contributing to increased surface O3 is the trans-Pacific transport of O3 from Asia. The extent of which O3stems from local emissions or is transported across the Pacific, however, is unclear. The California Ozone Transport Study (CABOTS), a joint effort between the California Air Resource Board, the National Oceanic and Atmospheric Administration, and San Jose State University, was conducted during the spring and summer of 2016 in an attempt to answer this question.Nearly 10 science flights were carried out by the Alpha Jet Atmospheric eXperiment (AJAX) between June and August 2016, based out of the NASA Ames Research Center. A summary of airborne O3, CO2, CH4, H2O, formaldehyde (HCHO), and 3D wind measurements will be presented. AJAX flights connect the fixed-location measurements at Visalia (TOPAZ ozone lidar) and Bodega Bay (ozonesondes), while exploring the spatial heterogeneity of O3 concentrations across California and at various offshore locations. Preliminary analyses of these flights will investigate connections between offshore O3 and Central Valley O3. Vertical profiles, time series, and tracer-tracer correlations will be employed to identify the sources of O3 during these flights.

Description: Satellite mapping of evapotranspiration (ET) from irrigated agricultural lands can provide agricultural producers and water managers with information that can be used to optimize agricultural water use, especially in regions with limited water supplies. The timely delivery of information on agricultural crop water requirements has the potential to make irrigation scheduling more practical, convenient, and accurate. We present a system for irrigation scheduling and management support in California and describe lessons learned from the development and implementation of the system. The Satellite Irrigation Management Support (SIMS) framework integrates satellite data with information from agricultural weather networks to map crop canopy development, basal crop coefficients (Kcb), and basal crop evapotranspiration (ETcb) at the scale of individual fields. Information is distributed to agricultural producers and water managers via a web-based irrigation management decision support system and web data services. SIMS also provides an application programming interface (API) that facilitates integration with other irrigation decision support tools, estimation of total crop evapotranspiration (ETc) and calculation of on-farm water use efficiency metrics. Accuracy assessments conducted in commercial fields for more than a dozen crop types to date have shown that SIMS seasonal ETcb estimates are within 10 mean absolute error (MAE) for well-watered crops and within 15 across all crop types studied, and closely track daily ETc and running totals of ETc measured in each field. Use of a soil water balance model to correct for soil evaporation and crop water stress reduces this error to less than 8 MAE across all crop types studied to date relative to field measurements of ETc. Results from irrigation trials conducted by the project for four vegetable crops have also demonstrated the potential for use of ET-based irrigation management strategies to reduce total applied water by 20-40 relative to grower standard practices while maintaining crop yields and quality.

Description: The Advanced Topographic Laser Altimeter System (ATLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat-2) mission is a six beam, low energy, high repetition rate, 532 nm laser transmitter with photon counting detectors. Although designed primarily for detecting height changes in icecaps, sea ice and vegetation, the polar-orbital satellite will observe global surface water during its designed three year life span, including inland water bodies, coasts, and open oceans. In preparation for the mission, an ICESat-2 prototype or the Multiple Altimeter Beam Experimental Lidar (MABEL), was built and flown on high altitude aircraft experiments over a range of inland and near-shore targets. The purpose was to test the ATLAS concept and to provide a database for developing an algorithm that detects along track surface water height and light penetration under a range of atmospheric and water conditions. The current analysis examines the datasets of three MABEL transects observed from 20 km above ground of coastal and inland waters conducted in 2012 and 2013. Transects ranged from about 2 to 12 km in length and included the middle Chesapeake Bay, the near shore Atlantic coast at Virginia Beach, and Lake Mead. Results indicate MABEL's high capability for retrieving surface water height statistics with a mean height precision of approximately 5-7 cm per 100m segment length. Profiles of attenuated subsurface backscatter, characterized using a Signal to Background Ratio written in Log10 base, or LSBR0, were observed over a range of 1.3 to 9.3 meters depending on water clarity and atmospheric background. Results indicate that observable penetration depth, although primarily dependent on water properties, was greatest when solar background rate was low. Near shore bottom reflectance was detected only at the Lake Mead site down to maximum of 10 m under a clear night sky and low turbidity of approximately 1.6 Nephelometric Turbidity Units (NTU). The overall results suggest that the feasibility of retrieving operational surface water height statistics from space-based photon counting systems such as ATLAS is very high for resolutions down to about 100m, even in partly cloudy conditions. The capability to observe subsurface backscatter profiles is achievable but requires much longer transects of several hundreds of meters.

Description: Various land use changes driven by urbanization, conversion of grasslands and woodlands into farmlands, intensification of agricultural practices, deforestation, land fragmentation and degradation are taking place in Africa. In Kenya, agriculture is the main driver of land use conversions. The impacts of these land use changes are observable in land cover maps, and eventually in the hydrological systems. Reduction or change of natural vegetation cover types increases the speed of surface runoff and reduces water and nutrient retention capacities. This can lead to high nutrient inputs into lakes, resulting in eutrophication, siltation and infestation of floating aquatic vegetation. To assess if changes in land use could be contributing to increased phytoplankton blooms and sediment loads into Lake Victoria, we analyzed land use land cover data from Landsat, as well as surface chlorophyll-a and total suspended matter from MODIS-Aqua sensor.

Description: No abstract available

Description: In the United States, the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) is charged with performing damage assessments when storm or tornado damage is suspected after a severe weather event. This has led to the development of the Damage Assessment Toolkit (DAT), an application for smartphones, tablets and web browsers that allows for the collection, geolocation, and aggregation of various damage indicators collected during storm surveys.

Description: As expanding service offerings and decreasing prices make the cloud increasingly attractive to Earth Science applications, there are nontrivial practical considerations which can hinder its meaningful use. In this talk, we will discuss architectural recommendations and lessons learned while working on EOSDIS' cloud efforts, particularly the NASA-compliant General Application Platform (NGAP) and its associated applications. Prominent in our findings is the importance of 12-factor design patterns and the powerful "wins" they enable in the cloud. We will share our strategies for "fast-tracking" applications to the cloud --whether they be legacy, planned for the future, or somewhere in between.

Description: No abstract available

Description: No abstract available

Description: Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, and sea level has risen.

Description: The main goal of this research is to design, fabricate, and test deployable VHF antennas for 6U Cubesat platforms to enable validation of root zone soil moisture (RZSM) estimation algorithms for signal of opportunity (SoOp) remote sensing over the 240-270 MHz frequency band. The proposed work provides a strong foundation for establishing a technology development path for maturing a truly global direct surface soil moisture (SM) and RZSM measurement system (Figure 1) over a variety of land covers with limited density restrictions. In SoOp methodology, signals transmitted by already existing transmitters (known as transmitters of opportunity, in this case the Military Satellite Communication (MilSatCom) System's UHF Follow-On program) are utilized to measure properties of reflecting targets by recording reflected signals using a simple passive microwave receiver.

Description: As atmospheric reflectance dominates top-of-the-atmosphere radiance over ocean, atmospheric correction is a critical component of ocean color retrievals. This paper explores the operational Sea-viewing Wide Field-of-View Sensor (SeaWiFS) algorithm atmospheric correction with approximately 13 000 coincident surface-based aerosol measurements. Aerosol optical depth at 440 nm (AOD(sub 440)) is overestimated for AOD below approximately 0.1-0.15 and is increasingly underestimated at higher AOD; also, single-scattering albedo (SSA) appears overestimated when the actual value less than approximately 0.96.AOD(sub 440) and its spectral slope tend to be overestimated preferentially for coarse-mode particles. Sensitivity analysis shows that changes in these factors lead to systematic differences in derived ocean water-leaving reflectance (Rrs) at 440 nm. The standard SeaWiFS algorithm compensates for AOD anomalies in the presence of nonabsorbing, medium-size-dominated aerosols. However, at low AOD and with absorbing aerosols, in situ observations and previous case studies demonstrate that retrieved Rrs is sensitive to spectral AOD and possibly also SSA anomalies. Stratifying the dataset by aerosol-type proxies shows the dependence of the AOD anomaly and resulting Rrs patterns on aerosol type, though the correlation with the SSA anomaly is too subtle to be quantified with these data. Retrieved chlorophyll-a concentrations (Chl) are affected in a complex way by Rrs differences, and these effects occur preferentially at high and low Chl values. Absorbing aerosol effects are likely to be most important over biologically productive waters near coasts and along major aerosol transport pathways. These results suggest that future ocean color spacecraft missions aiming to cover the range of naturally occurring and anthropogenic aerosols, especially at wavelengths shorter than 440 nm, will require better aerosol amount and type constraints.

Description: Natural dust is often associated with hot, subtropical deserts, but significant dust events have been reported from cold, high latitudes. This review synthesizes current understanding of high-latitude (〉 or = 50degN and 〉 or = 40degS) dust source geography and dynamics and provides a prospectus for future research on the topic. Although the fundamental processes controlling aeolian dust emissions in high latitudes are essentially the same as in temperate regions, there are additional processes specific to or enhanced in cold regions. These include low temperatures, humidity, strong winds, permafrost and niveo-aeolian processes all of which can affect the efficiency of dust emission and distribution of sediments. Dust deposition at high latitudes can provide nutrients to the marine system, specifically by contributing iron to high-nutrient, low-chlorophyll oceans; it also affects ice albedo and melt rates. There have been no attempts to quantify systematically the expanse, characteristics, or dynamics of high-latitude dust sources. To address this, we identify and compare the main sources and drivers of dust emissions in the Northern (Alaska, Canada, Greenland, and Iceland) and Southern (Antarctica, New Zealand, and Patagonia) Hemispheres. The scarcity of year-round observations and limitations of satellite remote sensing data at high latitudes are discussed. It is estimated that under contemporary conditions high-latitude sources cover 〉500,000 sq km and contribute at least 80-100 Tg/yr1 of dust to the Earth system (approx. 5% of the global dust budget); both are projected to increase under future climate change scenarios.

Description: We discuss the development of the Ukrainian space project Aerosol-UA which has the following three main objectives: (1) to monitor the spatial distribution of key characteristics of terrestrial tropospheric and stratospheric aerosols; (2) to provide a comprehensive observational database enabling accurate quantitative estimates of the aerosol contribution to the energy budget of the climate system; and (3) quantify the contribution of anthropogenic aerosols to climate and ecological processes. The remote sensing concept of the project is based on precise orbital measurements of the intensity and polarization of sunlight scattered by the atmosphere and the surface with a scanning polarimeter accompanied by a wide-angle multispectral imager-polarimeter. Preparations have already been made for the development of the instrument suite for the Aerosol-UA project, in particular, of the multi-channel scanning polarimeter (ScanPol) designed for remote sensing studies of the global distribution of aerosol and cloud properties (such as particle size, morphology, and composition) in the terrestrial atmosphere by polarimetric and spectrophotometric measurements of the scattered sunlight in a wide range of wavelengths and viewing directions from which a scene location is observed. ScanPol is accompanied by multispectral wide-angle imager-polarimeter (MSIP) that serves to collect information on cloud conditions and Earths surface image. Various components of the polarimeter ScanPol have been prototyped, including the opto-mechanical and electronic assemblies and the scanning mirror controller. Preliminary synthetic data simulations for the retrieval of aerosol parameters over land surfaces have been performed using the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm. Methods for the validation of satellite data using ground-based observations of aerosol properties are also discussed. We assume that designing, building, and launching into orbit a multi-functional high-precision scanning polarimeter and an imager-polarimeter should make a significant contribution to the study of natural and anthropogenic aerosols and their climatic and ecological effects.

Description: The Northwest India Aquifer (NWIA) has been shown to have the highest groundwater depletion (GWD) rate globally, threatening crop production and sustainability of groundwater resources. Gravity Recovery and Climate Experiment (GRACE) satellites have been emerging as a powerful tool to evaluate GWD with ancillary data. Accurate GWD estimation is, however, challenging because of uncertainties in GRACE data processing. We evaluated GWD rates over the NWIA using a variety of approaches, including newly developed constrained forward modeling resulting in a GWD rate of 3.1 plus or minus 0.1 centimeters per acre (or 14 plus or minus 0.4 cubic kilometers per acre) for Jan 2005-Dec 2010, consistent with the GWD rate (2.8 centimeters per acre or 12.3 cubic kilometers per acre) from groundwater-level monitoring data. Published studies (e.g., 4 plus or minus 1 centimeter per acre or 18 plus or minus 4.4 cubic kilometers per acre) may overestimate GWD over this region. This study highlights uncertainties in GWD estimates and the importance of incorporating a priori information to refine spatial patterns of GRACE signals that could be more useful in groundwater resource management and need to be paid more attention in future studies.

Description: No abstract available

Description: The AIRS Science Team Version-6 retrieval algorithm is currently producing level-3 Climate Data Records (CDRs) from AIRS that have been proven useful to scientists in understanding climate processes. CDRs are gridded level-3 products which include all cases passing AIRS Climate QC. SRT has made significant further improvements to AIRS Version-6. At the last Science Team Meeting, we described results using SRT AIRS Version-6.22. SRT Version-6.22 is now an official build at JPL called 6.2.4. Version-6.22 results are significantly improved compared to Version-6, especially with regard to water vapor and ozone profiles. We have adapted AIRS Version-6.22 to run with CrIS/ATMS, at the Sounder SIPS which processed CrIS/ATMS data for August 2014. JPL AIRS Version-6.22 uses the Version-6 AIRS tuning coefficients. AIRS Version-6.22 has at least two limitations which must be improved before finalization of Version-7: Version-6.22 total O3 has spurious high values in the presence of Saharan dust over the ocean; and Version-6.22 retrieved upper stratospheric temperatures are very poor in polar winter. SRT Version-6.28 addresses the first concern. John Blaisdell ran the analog of AIRS Version-6.28 in his own sandbox at JPL for the 14th and 15th of every month in 2014 and all of July and October for 2014. AIRS Version-6.28a is hot off the presses and addresses the second concern.

Description: This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP), which takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.

Description: No abstract available

Description: Three decades of rapid economic development is causing severe and widespread PM2.5(particulate matter (is) less than 2.5 ) pollution in China. However, research on the health impacts of PM2.5 exposure has been hindered by limited historical PM2.5 concentration data. We estimated ambient PM2.5 concentrations from 2004 to 2013 in China at 0.1 deg resolution using the most recent satellite data and evaluated model performance with available ground observations. We developed a two-stage spatial statistical model using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) and assimilated meteorology, land use data, and PM2.5 concentrations from China's recently established ground monitoring network. An inverse variance weighting (IVW) approach was developed to combine MODIS Dark Target and Deep Blue AOD to optimize data coverage. We evaluated model predicted PM2.5 concentrations from 2004 to early 2014 using ground observations. The overall model cross-validation R(sup 2) and relative prediction error were 0.79 and 35.6%, respectively. Validation beyond the model year (2013) indicated that it accurately predicted PM(sub 2.5) concentrations with little bias at the monthly (R(sup 2) = 0.73), regression slope = 0.91) and seasonal (R(sup 2) = 0.79), regression slope = 0.92) levels. Seasonal variations revealed that winter was the most polluted season and that summer was the cleanest season. Analysis of predicted PM2.5 levels showed a mean annual increase of 1.97 micro-g/cu cm between 2004 and 2007 and a decrease of 0.46 micro-g/cu cm between 2008 and 2013. Our satellite-driven model can provide reliable historical PM2.5 estimates in China at a resolution comparable to those used in epidemiologic studies on the health effects of long-term PM2.5 exposure in North America. This data source can potentially advance research on PM2.5 health effects in China.

Description: To sustain growing food demand and increasing standard of living, global water use increased by nearly 6 times during the last 100 years, and continues to grow. As water demands get closer and closer to the water availability in many regions, each drop of water becomes increasingly valuable and water must be managed more efficiently and intensively. However, soaring water use worsens water scarcity conditions already prevalent in semi-arid and arid regions, increasing uncertainty for sustainable food production and economic development. Planning for future development and investments requires that we prepare water projections for the future. However, estimations are complicated because the future of the world's waters will be influenced by a combination of environmental, social, economic, and political factors, and there is only limited knowledge and data available about freshwater resources and how they are being used. The Water Futures and Solutions (WFaS) initiative coordinates its work with other ongoing scenario efforts for the sake of establishing a consistent set of new global water scenarios based on the shared socio-economic pathways (SSPs) and the representative concentration pathways (RCPs). The WFaS "fast track" assessment uses three global water models, namely H08, PCR-GLOBWB, and WaterGAP. This study assesses the state of the art for estimating and projecting water use regionally and globally in a consistent manner. It provides an overview of different approaches, the uncertainty, strengths and weaknesses of the various estimation methods, types of management and policy decisions for which the current estimation methods are useful. We also discuss additional information most needed to be able to improve water use estimates and be able to assess a greater range of management options across the water-energy-climate nexus.

Description: Spaceborne spectrometers require spectral-temporal stability characterization to aid validation of derived data products. EO-1 began orbital precession in 2011 after exhausting onboard fuel resources. In the Libya-4 Pseudo Invariant Calibration Site (PICS) this resulted in a progressive shift from a mean local equatorial crossing time of approx. 10:00 AM in 2011 to approx. 8:30 AM in late 2015. Here, we studied precession impacts to Hyperion surface reflectance products using three atmospheric correction approaches from 2004 to 2015. Combined difference estimates of surface reflectance were 〈 5% in the visible near infrared (VNIR) and 〈 10% for most of the shortwave infrared (SWIR). Combined coefficient of variation (CV) estimates in the VNIR ranged from 0.025 0.095, and in the SWIR ranged from 0.025 0.06, excluding bands near atmospheric absorption features. Reflectances produced with different atmospheric models were correlated (R2) in VNIR from 0.25 0.94 and SWIR from 0.12 0.88 (p 〈 0.01). The uncertainties in all models increased with terrain slope up to 15deg and selecting dune flats could reduce errors. We conclude that these data remain a useful resource over this period.

Description: No abstract available

Description: Faraday rotation is a change in the polarization as signal propagates through the ionosphere. At L-band it is necessary to correct for this change and measurements are made on the spacecraft of the rotation angle. These figures show that there is good agreement between the SMAP measurements (blue) and predictions based on models (red).

Description: The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude. Since April, 2015, the radiometer is under calibration and validation to assess the quality of the radiometer L1B data product. Calibration methods including the SMAP L1B TA2TB (from Antenna Temperature (TA) to the Earth's surface Brightness Temperature (TB)) algorithm and TA forward models are outlined, and validation approaches to calibration stability/quality are described in this paper including future work. Results show that the current radiometer L1B data satisfies its requirements.

Description: Fowler Sneaker Index (FSI), developed by a NASA summer intern, is a new Ocean Color application that facilitates continuous monitoring of environmental conditions in the Chesapeake Bay. It builds on three decades of citizen science data collected by former Maryland State Senator Bernie Fowler, during his yearly "Wade-ins in the Patuxent River". FSI demonstrates how NASA's Earth-observing tools, in combination with a concerned and engaged public, can take science from the tips of our toes-to-top-of the atmosphere and back.

Description: Global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. This research enables the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

Description: Mangroves act as a transition zone between fresh and salt water habitats by filtering and indicating salinity levels along the coast of the Florida Everglades. However, dredging and canals built in the early 1900s depleted the Everglades of much of its freshwater resources. In an attempt to assist in maintaining the health of threatened habitats, efforts have been made within Everglades National Park to rebalance the ecosystem and adhere to sustainably managing mangrove forests. The Everglades Ecological Forecasting II team utilized Google Earth Engine API and satellite imagery from Landsat 5, 7, and 8 to continuously create land-change maps over a 25 year period, and to allow park officials to continue producing maps in the future. In order to make the process replicable for project partners at Everglades National Park, the team was able to conduct a supervised classification approach to display mangrove regions in 1995, 2000, 2005, 2010 and 2015. As freshwater was depleted, mangroves encroached further inland and freshwater marshes declined. The current extent map, along with transition maps helped create forecasting models that show mangrove encroachment further inland in the year 2030 as well. This project highlights the changes to the Everglade habitats in relation to a changing climate and hydrological changes throughout the park.

Description: New visualizations dramatically display the decreases in Arctic sea ice coverage over the years 1979-2015, apparent in each month of the year, with not a single record high in ice extents occurring in any month since 1986, a time period with 75 monthly record lows. Results are less dramatic in the Antarctic, but intriguingly in the opposite direction, with only 6 record lows since 1986 and 45 record highs.

Description: The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude. Since April, 2015, the radiometer is under calibration and validation to assess the quality of the radiometer L1B data product. Calibration methods including the SMAP L1B TA2TB (from Antenna Temperature (TA) to the Earths surface Brightness Temperature (TB)) algorithm and TA forward models are outlined, and validation approaches to calibration stability/quality are described in this paper including future work. Results show that the current radiometer L1B data satisfies its requirements.

Description: No abstract available

Description: Restoring Terra MODIS LWIR spectral band calibration and data quality using improved crosstalk correction algorithm and coefficients derived from on-orbit lunar observations.

Description: No abstract available

Description: No abstract available

Description: No abstract available

Description: In July and August 2014, NASA conducted an airborne lidar campaign based out of Fort Wainwright,Fairbanks, Alaska, in support of Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) algorithm development. The survey targeted Alaskan glaciers and icefields and sea ice in the Arctic Ocean during the summer melt season. Ultimately, the mission, MABEL Alaska 2014, including checkout and transit flights, conducted 11 science flights, for a total of over 50 flight hours over glaciers, icefields, and sea ice.

Description: Yellow Starthistle (Centaurea solstitialis) is a native annual weed of Eurasia and since introduction into the US has become an invasive and noxious weed. It grows in a rosette habit during the vegetative state and usually bolts in summer to produce a large and branched flowering stem. Time to flowering in Yellow Starthistle has been attributed to photoperiod, nitrogen nutrition, temperature, and water stress. We executed a series of studies to investigate the role of light, both photoperiod and photosynthetic photon flux, on flowering and development in Yellow Starthistle. Treatments were presented in 4 ways: (1) Varying day length with constant photosynthetic photon flus (PPF) - providing increasing daily integrated Photosynthetic Photon (PP) exposure with longer day lengths, (2) Varying day length while adjusting PPF to maintain daily PP exposure for all treatments, (3) Extending photoperiod treatments beyond common 12-h photosynthetic period with low light levels to maintain both PPF and daily PP across all treatments; and (4) Reciprocal exchange of plant among photoperiod treatments. Yellow Starthistle appears to be a long-day plant with a critical day length requirement between 14-h and 16-h to induce transition from vegetative to floral stages in development. PPF and daily absorbed photons did not affect time to vegetative / floral stage transition, but did affect factors such as biomass accumulation and canopy parameters such as specific leaf mass. Reciprocal exchange of plants between floral inducing and inhibiting photoperiod treatments, starting at 2-weeks post germination, had no effect on to flower. Flowering was determined by photoperiod experienced during the first 2-weeks (or less) post germination. Yellow Starthistle net photosynthetic response to elevated atmospheric CO2 concentrations over a range of photosynthetically active radiation flux rates and temperatures will also be presented and discussed.

Description: On the afternoon of May 17th, 2016, a major landslide event caused at least 92 deaths, with 109 still missing*. The site was rated highly susceptible to landslides in a new global landslide susceptibility map. GPM precipitation data suggest that both antecedent and current rainfall as well as complex topography played a role in the slope failures.

Description: Photosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe.

Description: There has been no spatial surface wind map even over the conterminous USA due to the difficulty of spatial interpolation of wind field. As a result, the reanalysis data were often used to analyze the statistics of spatial pattern in surface wind speed. Unfortunately, no consistent trend in wind field was found among the available reanalysis data, and that obstructed the further analysis or projection of spatial pattern of wind speed. In this study, we developed the methodology to interpolate the observed wind speed data at weather stations using random forest algorithm. We produced the 1-km daily climate variables over the conterminous USA from 1979 to 2015. The validation using Ameriflux daily data showed that R2 is 0.59. Existing studies have found the negative trend over the Eastern US, and our study also showed same results. However, our new datasets also revealed the significant increasing trend over the southwest US especially from April to June. The trend in the southwestern US represented change or seasonal shift in North American Monsoon. Global analysis of CMIP5 data projected the decrease trend in mid-latitude, while increase trend in tropical region over the land. Most likely because of the low resolution in GCM, CMIP5 data failed to simulate the increase trend in the southwest US, even though it was qualitatively predicted that pole ward shift of anticyclone help the North American Monsoon.

Description: This work is using the newly available NASA SMAP soil moisture measurement data to evaluate its impact on the atmospheric dust emissions. Dust is an important component of atmospheric aerosols, which affects both climate and air quality. In this work, we focused on semi-desert regions, where dust emissions show seasonal variations due to soil moisture changes, i.e. in Sahel of Africa. We first identified three Aerosol Robotic Network (AERONET) sites in the Sahel (IER_Cinzana, Banizoumbou, and Zinder_Airport). We then utilized measurements of aerosol optical depth (AOD), fine mode fraction, size distribution, and single-scattering albedo and its wave-length dependence to select dust plumes from the available measurements We matched the latitude and longitude of the AERONET station to the corresponding SMAP data cell in the years 2015 and 2016, and calculated their correlation coefficient. Additionally, we looked at the correlation coefficient with a three-day and a five-day shift to check the impact of soil moisture on dust plumes with some time delay. Due to the arid nature of Banizoumbou and Zinder_Airport, no correlation was found to exist between local soil moisture and dust aerosol load. While IER_Cinzana had soil moisture levels above the satellite threshold of 0.02cm3/cm3, R-value approaching zero indicated no presence of a correlation. On the other hand, Ilorin demonstrated a significant negative correlation between aerosol optical depth and soil moisture. When isolating the analysis to Ilorin's dry season, a negative correlation of -0.593 was the largest dust-isolated R-value recorded, suggesting that soil moisture is driven the dust emission in this semi-desert region during transitional season.

Description: Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed a 80% overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

Description: Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

Description: Remotely sensing the water status of plants and the water content of canopies remain long-term goals of remote sensing research. For monitoring canopy water status, existing approaches such as the Crop Water Stress Index and the Equivalent Water Thickness have limitations. The CWSI does not work well in humid regions, requires estimates of the vapor pressure deficit near the canopy during the remote sensing over-flight and, once stomata close, provides little information regarding the canopy water status. The EWI is based upon the physics of water-light interaction, not plant physiology. In this research, we applied optical polarization techniques to monitor the VISNIR light reflected from the leaf interior, R, as well as the leaf transmittance, T, as the relative water content (RWC) of corn (Zea mays) leaves decreased. Our results show that R and T both changed nonlinearly as each leaf dried, R increasing and T decreasing. Our results tie changes in the VISNIR R and T to leaf physiological changes linking the light scattered out of the drying leaf interior to its relative water content and to changes in leaf cellular structure and pigments. Our results suggest remotely sensing the physiological water status of a single leaf and perhaps of a plant canopy might be possible in the future. However, using our approach to estimate the water status of a leaf does not appear possible at present, because our results display too much variability that we do not yet understand.

Description: Small, modular aircraft are an emerging technology with a goal to maximize flexibility and enable multi-mission support. This reports the progress of an unmanned aerial system (UAS) project conducted at the NASA Ames Research Center (ARC) in 2016. This interdisciplinary effort builds upon the success of the 2014 FrankenEye project to apply rapid prototyping techniques to UAS, to develop a variety of platforms to host remote sensing instruments. In 2016, ARC received AeroVironment RQ-11A and RQ-11B Raven UAS from the US Department of the Interior, Office of Aviation Services. These aircraft have electric propulsion, a wingspan of roughly 1.3m, and have demonstrated reliability in challenging environments. The Raven airframe is an ideal foundation to construct more complex aircraft, and student interns using 3D printing were able to graft multiple Raven wings and fuselages into FrankenRaven aircraft. Aeronautical analysis shows that the new configuration has enhanced flight time, payload capacity, and distance compared to the original Raven. The FrankenRaven avionics architecture replaces the mil-spec avionics with COTS technology based upon the 3DR Pixhawk PX4 autopilot with a safety multiplexer for failsafe handoff to 2.4 GHz RC control and 915 MHz telemetry. This project demonstrates how design reuse, rapid prototyping, and modular subcomponents can be leveraged into flexible airborne platforms that can host a variety of remote sensing payloads and even multiple payloads. Modularity advances a new paradigm: mass-customization of aircraft around given payload(s). Multi-fuselage designs are currently under development to host a wide variety of payloads including a zenith-pointing spectrometer, a magnetometer, a multi-spectral camera, and a RGB camera. After airworthiness certification, flight readiness review, and test flights are performed at Crows Landing airfield in central California, field data will be taken at Kilauea volcano in Hawaii and other locations.

Description: Vegetation growing season and maximum photosynthetic state determine spatiotemporal variability of seasonal total gross primary productivity of vegetation. Recent warming induced impacts accelerate shifts on growing season and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we first investigate how vegetation growing season and maximum photosynthesis state are evolved and how such components contribute on inter-annual variation of seasonal total gross primary productivity. Furthermore, seasonally different response of northern vegetation to changing temperature and water availability is also investigated. We utilized both long-term remotely sensed data to extract larger scale growing season metrics (growing season start, end and duration) and productivity (i.e., growing season summed vegetation index, GSSVI) for answering these questions. We find that regionally diverged growing season shift and maximum photosynthetic state contribute differently characterized productivity inter-annual variability and trend. Also seasonally different response of vegetation gives different view of spatially varying interaction between vegetation and climate. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation to changing climate.

Description: The Soberanes Fire started on July 22, 2016 in Monterey County on the California Central Coast from an illegal campfire. This fire burned for 10 weeks at a record cost of more than $208 million for protection and control. A progressive analysis of the normalized burn ratio from the Landsat satellite showed that the final high burn severity (HBS) area for the Soberanes Fire comprised 22 percent of the total area burned, whereas final moderate burn severity (MBS) area comprised about 10 percent of the total area burned of approximately 53,470 ha (132,130 acres). The resulting landscape pattern of burn severity classes from the 2016 Soberanes Fire revealed that the majority of HBS area was located in the elevation zone between 500 and 1000 m, in the slope zone between 15 percent and 30 percent, or on south-facing aspects.

Description: Inflow projections provide scenarios for future water availability and are integral to operational reservoir management. They can aid water practitioners in decision-making for conservation efforts, multiyear storage retention, managing flood risk, downstream water releases, and regional growth planning. However, conventional methods are often limited in terms of their ability to incorporate non-stationarity, long run persistence, and the cross-correlation of multiple series in a region. This research aims to address these issues with a hybrid approach that integrates Empirical Mode Decomposition (EMD) with the Matalas multisite generation method. Multiple long-run inflows were examined for the Shasta/Trinity Reservoirs and Oroville Reservoir of California. EMD is used to decompose each inflow series into a set of independent intrinsic mode functions (IMFs) that have different timescales and frequencies. These IMFs were grouped into intradecadal (less-than- 10-year average periodicity) and interdecadal (greater-than-10-year average periodicity) series for each site. The IMF projections at each site were then combined to produce replicates of the historical data. This preserves the correlation structure of the intra- and interdecadal components of the series. The hybrid EMD-Matalas method was compared to a traditional autoregressive lag-one model. Both methods were found to retain the statistical characteristics of the historical data. However, the EMD-Matalas method retained the multiyear wet and dry periods to a greater degree. This was examined by comparing the 5-year and 10-year sums from the traditional model with the hybrid EMD-Matalas model. An advantage of the EMD-Matalas method is the ability to explicitly incorporate modes of non-stationary long-run persistence often associated with large-scale climate drivers such as the El Nino Southern Oscillation (ENSO) or the Pacific Decadal Oscillation (PDO). This contributes to scenario planning that may be particularly important for managing multiyear low flow periods.

Description: The North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) is a five-year Earth-Venture Suborbital-2 Mission to characterize the plankton ecosystems and their influences on remote marine aerosols, boundary layer clouds, and their implications for climate in the North Atlantic. While marine-sourced aerosols have been shown to make important contributions to surface aerosol loading, cloud condensation nuclei and ice nuclei concentrations over remote marine and coastal regions, it is still a challenge to differentiate the marine biogenic aerosol signal from the strong influence of continental pollution outflow. We examine here the spatiotemporal variability and quantify the sources of tropospheric aerosols over the North Atlantic during the first two phases (November 2015 and May-June 2016) of NAAMES using a state-of-the-art chemical transport model (GEOS-Chem). The model is driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) from the NASA Global Modeling and Assimilation Office (GMAO). It includes sulfate-nitrate-ammonium aerosol thermodynamics coupled to ozone-NOx-hydrocarbon-aerosol chemistry, mineral dust, sea salt, elemental and organic carbon aerosols, and especially a recently implemented parameterization for the marine primary organic aerosol emission. The simulated aerosols over the North Atlantic are evaluated with available satellite (e.g., MODIS) observations of aerosol optical depths (AOD), and aircraft and ship aerosol measurements. We diagnose transport pathways for continental pollution outflow over the North Atlantic using carbon monoxide, an excellent tracer for anthropogenic pollution transport. We also conduct model perturbation experiments to quantify the relative contributions of terrestrial and oceanic sources to the aerosol loading, AOD, and their variability over the North Atlantic.

Description: We identify eleven megafans (partial cones of fluvial sediment, 〉80 km radius) in the northern Kalahari Basin, using several criteria based on VIS and IR remotely sensed data and SRTM-based surface morphology reconstructions. Two other features meet fewer criteria of the form which we class as possible megafans. The northern Kalahari megafans are located in a 1700 km arc around the southern and eastern flanks of the Angola's Bi Plateau, from northern Namibia through northwest Botswana to western Zambia. Three lie in the Owambo subbasin centered on the Etosha Pan, three in the relatively small Okavango rift depression, and five in the Upper Zambezi basin. The population includes the well-known Okavango megafan (150 km), Namibia's Cubango megafan, the largest megafan in the region (350 km long), and the largest nested group (the five major contiguous megafans on the west slopes of the upper Zambezi Valley). We use new, SRTM-based topographic roughness data to discriminate various depositional surfaces within the flat N. Kalahari landscapes. We introduce the concepts of divide megafans, derived megafans, and fan-margin rivers. Conclusions. (i) Eleven megafan cones total an area of ~190,000 sq km. (ii) Different controls on megafan size operate in the three component basins: in the Okavango rift structural controls become the prime constraint on megafan length by controlling basin dimensions. Megafans in the other les constricted basins appear to conform to classic relationships fan area, slope, and feeder-basin area. (iii) Active fans occupy the Okavango rift depression with one in the Owambo basin. The rest of the population are relict but recently active fans (surfaces are relict with respect to activity by the feeder river). (iv) Avulsive behavior of the formative river-axiomatic for the evolution of megafans-has resulted in repeated rearrangements of regional drainage, with likely effects in the study area well back into the Neogene. Divide megafans comprise the majority of the identified features, some of which have delivered water and sediment alternately to neighboring basins in the course of normal avulsion activity, likely resulting in significant changes in the hydrologies of two of the study-area subbasins. (v) Paleoclimatic inferences extracted from fluvial and lacustrine sediments therefore need to take account of avulsion-driven drainage configurations, especially where these are autogenically controlled.

Description: The California Sacramento-San Joaquin River Delta is the hub for California's water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

Description: Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed an 80 percent overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

Description: The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument on-board the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft. The S-NPP launched in October 2011 and it has been collecting valuable Earth science data with VIIRS and four other instruments for more than five years. The VIIRS Characterization Support Team (VCST) of the National Aeronautics and Space Administration (NASA) Science Investigator-led Processing Systems (SIPS) is designed to support the VIIRS sensor pre-launch geometric and radiometric characterization and to access on-orbit long-term Level-1B (L1B) calibration and performance. This paper reviews the VIIRS thermal emissive bands (TEB), covering wavelengths from 3.7 to 12.0 m, L1B radiometric calibration algorithms and presents the calibration uncertainty methodology which will be implanted in the L1B processing software. Discussions will be focused on the key uncertainty parameters and the application in L1B.

Description: It is essential to evaluate and refine aerosol classification methods applied to passive satellite remote sensing. We have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol type to multi-parameter retrievals by spaceborne, airborne or ground-based passive remote sensing instruments [1]. The aerosol types identified by our scheme are pure dust, polluted dust, urban-industrialdeveloped economy, urban-industrialdeveloping economy, dark biomass smoke, light biomass smoke and pure marine. We apply the SCMC method to inversions from the ground-based AErosol RObotic NETwork (AERONET [2]) and retrievals from the space-borne Polarization and Directionality of Earths Reflectances instrument (POLDER, [3]). The POLDER retrievals that we use differ from the standard POLDER retrievals [4] as they make full use of multi-angle, multispectral polarimetric data [5]. We analyze agreement in the aerosol types inferred from both AERONET and POLDER and evaluate GEOS-Chem [6] simulations over the globe. Finally, we use in-situ observations from the SEAC4RS airborne field experiment to bridge the gap between remote sensing-inferred qualitative SCMC aerosol types and their corresponding quantitative chemical speciation. We apply the SCMC method to airborne in-situ observations from the NASA Langley Aerosol Research Group Experiment (LARGE, [7]) and the Differential Aerosol Sizing and Hygroscopicity Spectrometer Probe (DASH-SP, [8]) instruments; we then relate each coarsely defined SCMC type to a sum of percentage of individual aerosol species, using in-situ observations from the Particle Analysis by Laser Mass Spectrometry (PALMS, [9]), the Soluble Acidic Gases and Aerosol (SAGA, [10]), and the High - Resolution Time - of - Flight Aerosol Mass Spectrometer (HR ToF AMS, [11]).

Description: The successful launch of the European Space Agency (ESA) Sentinel-2A (S2-A) on 23 June 2015 with its MultiSpectral Instrument (MSI) provides an important means to augment Earth-observation capabilities following the legacy of Landsat. After the three-month satellite commissioning campaign, the MSI onboard S-2A is performing very well (ESA, 2015). By 3 December 2015, the sensor data records have achieved provisional maturity status and have been accessed in level-1C Top-Of-Atmosphere (TOA) reflectance by the remote sensing community worldwide. Near-nadir observations by the MSI onboard S-2A and the Operational Land Imager (OLI) onboard Landsat 8 were collected during Simultaneous Nadir Overpasses as well as nearly coincident overpasses. This paper presents a processing chain using harmonized S-2A MSI and Landsat 8 OLI sensors to obtain increased temporal resolution in Leaf Area Index (LAI) estimates using the red-edge band B8A of MSI to replace the NIR band B08. Results demonstrate that LAI estimates from the MSI and OLI are comparable, and, given sufficient preprocessing for atmospheric correction and geometric rectification, can be used interchangeably to improve the frequency with which low LAI canopies can be monitored.

Description: Talks presented by Dr. Ralph Kahn at the 16th AeroCom and 5th AeroSat Workshops, held October 9-13, 2017 in Helsinki, Finland.

Description: We present NASA ESTO FluidCam 1 & 2, Visible and NIR Fluid-Lensing-enabled imaging payloads for Unmanned Aerial Vehicles (UAVs). Developed as part of a focused 2014 earth science technology grant, FluidCam 1&2 are Fluid-Lensing-based computational optical imagers designed for automated 3D mapping and remote sensing of underwater coastal targets from airborne platforms. Fluid Lensing has been used to map underwater reefs in 3D in American Samoa and Hamelin Pool, Australia from UAV platforms at sub-cm scale, which has proven a valuable tool in modern marine research for marine biosphere assessment and conservation. We share FluidCam 1&2 instrument validation and testing results as well as preliminary processed data from field campaigns. Petabyte-scale aerial survey efforts using Fluid Lensing to image at-risk reefs demonstrate broad applicability to large-scale automated species identification, morphology studies and reef ecosystem characterization for shallow marine environments and terrestrial biospheres, of crucial importance to improving bathymetry data for physical oceanographic models and understanding climate changes impact on coastal zones, global oxygen production, carbon sequestration.

Description: No abstract available

Description: No abstract available

Description: The Gravity Recovery and Climate Experiment - Follow-On (GRACE-FO) Mission is a NASA directed mission to continue the goals of the original GRACE mission and provide continuity for the GRACE data set. The GRACE-FO mission is the result of an international cooperation to develop a concept and approach that minimizes cost and risk and maximizes the probability of success through limited changes to the original GRACE system design. The result is a system architecture in which maintenance of heritage is paramount, including heritage derived through the partnership with the German Research Centre for Geosciences (GFZ) in Germany. As a secondary goal, GRACE-FO will carry a Laser Ranging Interferometer (LRI) as a technology demonstration, which will provide laser interferometry measurements of inter-satellite range, complementary to the K/Ka-Band microwave link to demonstrate laser-ranging technology in support of future GRACE-like missions. Another secondary objective is the continuation of GRACE radio occultation measurements.

Description: The ObseRvations of Aerosols above Clouds and their interactions (ORACLES) project is making a series of field deployments to the southeastern Atlantic with NASA ER-2 and P3 aircraft to acquire both detailed remote sensing observations and in situ measurements of the aerosols and clouds in that region. This area is home to one of the largest low-level cloud decks on Earth that is seasonally affected by vast plumes of smoke from biomass burning, which in effect provides a natural experiment testing the radiative and microphysical interactions between the smoke and the clouds. The downward solar radiation at the surface, or cloud top, is always reduced by the presence of smoke. However, whether the amount of sunlight reflected back out to space is increased, or decreased by the presence of smoke is sensitively dependent on the brightness of the clouds and the fraction of light that the smoke absorbs each time light hits a smoke particle. In this study we use data from the Research Scanning Polarimeter, an along track scanning instrument, that provides measurements of the Stokes parameters I, Q and U at 410, 470, 555, 670, 865, 960, 1590, 1880 and 2260 nm at 150 viewing angles over a range of +/- 60 from nadir for each contiguous sub-aircraft pixel (~ 300 m in size). A retrieval algorithm is applied to the data acquired with a table look up technique, similar to that of the operational POLDER algorithm, to provide a first guess of the complex refractive index, optical depth and size distribution of the smoke particles together with cloud droplet size and optical depth. A subsequent iterative fitting procedure, where the fact that the doubling/adding method allows the construction of the Green's function for the radiative transfer equation, is used to obtain an efficient and statistically optimal estimate of the aerosol and cloud retrieval parameters. These retrieval parameters are evaluated against in situ observations, when available, and the optical depth and intensive lidar variables that are measured by the High Spectral Resolution Lidar 2. Finally, the aerosol and cloud retrievals are used to evaluate the variations in top of the atmosphere, surface/cloud top shortwave radiative forcing and atmospheric absorption that are caused by variations in the smoke and clouds.

Description: This paper describes the current ground-based calibration results of Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Suomi National Polar orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS), and Sentinel-2A Multispectral Instrument (MSI), using an automated suite of instruments located at Railroad Valley, Nevada, USA. The period of this study is 2012 to 2016 for MODIS, VIIRS, and ETM+, 2013 to 2016 for OLI, and 2015 to 2016 for MSI. The current results show that all sensors agree with the Radiometric Calibration Test Site (RadCaTS) to within +/-5% in the solar-reflective regime, except for one band on VIIRS that is within +/-6%. In the case of ETM+ and OLI, the agreement is within +/-3%, and, in the case of MODIS, the agreement is within +/-3.5%. MSI agrees with RadCaTS to within +/-4.5% in all applicable bands.

Description: We derive water vapor column abundances and aerosol properties from Mars Science Laboratory (MSL) ChemCam passive mode observations of scattered sky light. This paper covers the methodology and initial results for water vapor and also provides preliminary results for aerosols. The data set presented here includes the results of 113 observations spanning from Mars Year 31 L(s) = 291 deg (March 30, 2013) to Mars Year 33 L(s) = 127 deg (March 24, 2016). Each ChemCam passive sky observation acquires spectra at two different elevation angles. We fit these spectra with a discrete-ordinates multiple scattering radiative transfer model, using the correlated-k approximation for gas absorption bands. The retrieval proceeds by first fitting the continuum of the ratio of the two elevation angles to solve for aerosol properties, and then fitting the continuum-removed ratio to solve for gas abundances. The final step of the retrieval makes use of the observed CO 2 absorptions and the known CO 2 abundance to correct the retrieved water vapor abundance for the effects of the vertical distribution of scattering aerosols and to derive an aerosol scale height parameter. Our water vapor results give water vapor column abundance with a precision of +/-0.6 precipitable microns and systematic errors no larger than +/-0.3 precipitable microns, assuming uniform vertical mixing. The ChemCam-retrieved water abundances show, with only a few exceptions, the same seasonal behavior and the same timing of seasonal minima and maxima as the TES, CRISM, and REMS-H data sets that we compare them to. However ChemCam-retrieved water abundances are generally lower than zonal and regional scale from-orbit water vapor data, while at the same time being significantly larger than pre-dawn REMS-H abundances. Pending further analysis of REMS-H volume mixing ratio uncertainties, the differences between ChemCam and REMS-H pre-dawn mixing ratios appear to be much too large to be explained by large scale circulations and thus they tend to support the hypothesis of substantial diurnal interactions of water vapor with the surface. Our preliminary aerosol results, meanwhile, show the expected seasonal pattern in dust particle size but also indicate a surprising interannual increase in water-ice cloud opacities.

Description: Since the 1960s, satellites have been looking down at the Earth to monitor weather patterns and track severe storms, observe how our land surface is changing and responding to hydrometerological extremes, and even to sense how the Earth's crust is deforming from earthquakes and volcanoes. Space and airborne platforms can provide unique views of the disaster lifecycle, informing pre-event mitigation and preparedness, emergency response following an event, and monitoring longer-term recovery. These remotely-sensed data, products and models can provide a global perspective to see beyond administrative boundaries, reach remote places where in situ observations are di cult or non-existent, and provide the necessary context and situational awareness to aid in disaster response. So how do these platforms work? Instruments aboard satellites use different portions of the electromagnetic spectrum to passively or actively observe energy across a range of wavelengths, which can be turned into meaningful data on geophysical, atmospheric, and hydrological variables. e US has had a broad range of Earth observation (EO) platforms delivering open data for scientific research and societal benefits for decades. e Landsat programme, a joint initiative between the US Geological Survey (USGS) and NASA, has the world's longest continuous collection of space-based satellite imagery of the Earth, extending from 1972 to present. e Landsat satellites provide visible, near infrared, and thermal data that are used to support emergency response and disaster relief by mapping changes in water during floods, and dramatic land surface changes, including those resulting from landslides, wild res, severe weather, volcanic plumes, and dust storms.

Description: No abstract available

Description: No abstract available

Description: This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural network (NN) and physically-based SMAP soil moisture retrievals were assimilated into the National Aeronautics and Space Administration (NASA) Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture. Assimilating the NN retrievals without further bias correction improved the surface and root zone correlations against in situ measurements from 14 SMAP core validation sites (CVS) by 0.12 and 0.16, respectively, over the model-only skill, and reduced the surface and root zone unbiased root-mean-square error (ubRMSE) by 0.005 m(exp 3) m(exp 3) and 0.001 m(exp 3) m(exp 3), respectively. The assimilation reduced the average absolute surface bias against the CVS measurements by 0.009 m(exp 3) m(exp 3), but increased the root zone bias by 0.014 m(exp 3) m(exp 3). Assimilating the NN retrievals after a localized bias correction yielded slightly lower surface correlation and ubRMSE improvements, but generally the skill differences were small. The assimilation of the physically-based SMAP Level-2 passive soil moisture retrievals using a global bias correction yielded similar skill improvements, as did the direct assimilation of locally bias-corrected SMAP brightness temperatures within the SMAP Level-4 soil moisture algorithm. The results show that global bias correction methods may be able to extract more independent information from SMAP observations compared to local bias correction methods, but without accurate quality control and observation error characterization they are also more vulnerable to adverse effects from retrieval errors related to uncertainties in the retrieval inputs and algorithm. Furthermore, the results show that using global bias correction approaches without a simultaneous re-calibration of the land model processes can lead to skill degradation in other land surface variables.

Description: Disturbances, both natural and anthropogenic, are critical determinants of forest structure, function, and distribution. The vulnerability of forests to potential changes in disturbance rates remains largely unknown. Here, we developed a framework for quantifying and mapping the vulnerability of forests to changes in disturbance rates. By comparing recent estimates of observed forest disturbance rates over a sample of contiguous US forests to modeled rates of disturbance resulting in forest loss, a novel index of vulnerability, Disturbance Distance, was produced. Sample results indicate that 20% of current US forestland could be lost if disturbance rates were to double, with southwestern forests showing highest vulnerability. Under a future climate scenario, the majority of US forests showed capabilities of withstanding higher rates of disturbance then under the current climate scenario, which may buffer some impacts of intensified forest disturbance.

Description: The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite uses its 14 reflective solar bands to passively collect solar radiant energy reflected off the Earth. The Level 1 product is the geolocated and radiometrically calibrated top-of- the-atmosphere solar reflectance. The absolute radiometric uncertainty associated with this product includes contributions from the noise associated with measured detector digital counts and the radiometric calibration bias. Here, we provide a detailed algorithm for calculating the estimated standard deviation of the retrieved top-of-the-atmosphere spectral solar radiation reflectance.