Earth Science Research
Project Participants (BAERI): Qian Tan
Aerosols are small particles suspended in the air. They can affect the air quality and climate in many ways. The vertical distribution of aerosols and their precursors can largely affect their lifetime and magnitude of their impacts. In 2016, the team continued their study of the vertical distribution of aerosols and their precursors using both a global aerosol transport model and measurements from airborne and space-borne instruments. Multi-model comparison shows very large differences among simulated distribution of aerosols in the upper troposphere and lower stratosphere. This can lead to uncertainty in estimated source attribution and their climate impacts.
- Compared simulated sulfate aerosols and SO2 by 16 aerosol transport models from the Aerosols Modeling Inter-Comparison project (AEROCOM);
- Compared vertical distribution of aerosols from two space-borne LIDARs and tracked their transport; and
- Worked on a project to study the impact of soil moisture measured by a new satellite on the dust emission in Africa.
Tan Q., M. Chin, V. Aquila, G. Chen, M. Hoepfner, The vertical profile of SO2 seen by aircraft, satellite and models, Kaufman Symposium, June, 2016, NASA GSFC, Greenbelt, MD (poster)
Tan Q., M. Chin, V. Aquila, G. Chen, Evaluation of modeled vertical distribution of SO2 and sulfate, AeroCom Workshop, Sept 2016, Beijing, China. (poster)
Tan Q., M. Chin, V. Aquila, G. Chen, Evaluation of modeled vertical distribution of atmospheric SO2 and sulfate, AGU Fall Meeting, Dec 2016, San Francisco, CA.
Carbon Monitoring Systems (CMS)
Project Participants (BAERI): Sangram Ganguly, Subodh Kalia
The CMS program seeks to characterize, quantify, understand, and predict the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. As part of the CMS multi-phase activities, a major effort is to quantify regional-to-continental forest Aboveground Biomass (AGB) and Forest canopy height using a host of satellite-derived data, ground data and physical models. Forest canopy height and AGB are key biophysical parameters needed to understand local, regional, and global carbon cycles and serve as an important input to a variety of climate and ecosystem models.
- Developed a robust scalable machine learning algorithm (SegNet) for performing classification/segmentation of 1-m NAIP imagery and used the Allometric Scaling and Resource Limitations Model (ASRL) to model canopy heights using various geospatial predictors like elevation, long-term monthly precipitation, air temperature, solar radiation, vapor pressure and wind speed;
- Developed theoretical relationships between tree height and available, evaporative, and basal metabolic flow rates using the Allometric Scaling and Resource Limitations model and generated predictions of maximum forest height for forested areas across the continental U.S. and compared these heights to actual reference height data (FIA) by region and accounting for forest age;
- Achieved an accuracy of > 93% for the trained model; the model is scalable and can predict accurately for the areas where data is not available.
Choi. S. et al. (S. Ganguly, one of 17 co-authors). 2016. Application of metabolic scaling theory and water-energy balance equation to model large-scale patterns of maximum forest canopy height. Global Ecology and Biogeography. Wiley Online Library. 25 (12), 1428-1442, doi: 10.1111/geb.12503.
Basu, S. et al. (S. Ganguly, one of 7 co-authors). 2016. Learning sparse feature representations using Probabilistic Quadtrees and Deep Belief Nets. Neural Processing Letters. doi: 10.1007/s11063-016-9556-4
Kumar, U. et al. (S. Ganguly, one of 6 co-authors). 2016. Partially and fully constrained least squares linear spectral mixture models for subpixel land cover classification using Landsat data. International Journal of Signal Processing Systems. 4(3), 245-251. doi: 10.18178/ijsps.4.3.245-251
Earth Science Data Records
Project Participants (BAERI): Susan Kulawik
The ESDR project supports the NASA Earth Science Data Systems Program. The Program’s mission is to both manage and expand the many Earth science data records obtained from NASA satellites, airborne platforms, ground stations, and other sources. Management of these datasets includes archiving, algorithm development, calibration and validation, processing, quality control, and continued support to the user community. One component of the ESDR Program, the Earth System Data Records Uncertainty Analysis, seeks to extend and enhance Earth system data records used by NASA communities, including climate data records, through rigorous estimation of errors. Projects under the Earth System Data Records Uncertainty Analysis umbrella increase the scientific value of the measurements by identifying and validating systematic uncertainties in input data and physical models, and improving error estimations.
- Compared measurements of carbon dioxide (CO2) taken from satellites (TES, AIRS, GOSAT) and estimated from models (Carbon Tracker, and MACC) to aircraft data, starting with comparisons to the HIAPER Pole‐to‐Pole Observations (HIPPO);
- Updated comparisons between SCIAMACHY, GOSAT, MACC, and Carbon Tracker to TCCON, with a manuscript in preparation; and
- Focused on incorporating onto the analysis additional aircraft sets, sets co‐located at TCCON sites and sets of OCO‐2 data.
Kulawik, S. et al. Consistent evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON, Atmos. Meas. Tech., 9, 683-709, doi:10.5194/amt-9-683-2016, 2016.
Frankenberg, C., Kulawik, S. S., Wofsy, S. C., Chevallier, F., Daube, B., Kort, E. A., O’Dell, C., Olsen, E. T., and Osterman, G.: Using airborne HIAPER Pole-to-Pole Observations (HIPPO) to evaluate model and remote sensing estimates of atmospheric carbon dioxide, Atmos. Chem. Phys., 16, 7867-7878, doi:10.5194/acp-16-7867-2016, 2016.
Kulawik, S. et al .HIPPO versus OCO-2, OCO-2 Science Team Meeting, 21-23 March, 2016, Pasadena, CA.
Ground, Air, and Spaceborne Aerosol Typing
Project Participants (BAERI): Meloe Kacenelenbogen (PI), Qian Tan
This project, begun in March 2015, is a three-year investigation with the following goals: (1) understand the limitations of the Specified Clustering and Mahalanobis Classification (SCMC) method applied to passive spaceborne polarimetry and ground-based sun and sky photometry, (2) improve this method through the addition of mixtures of aerosol types, (3) bridge the gap between remote sensing-inferred aerosol types and their corresponding chemical speciation, (4) use the SCMC method to evaluate aerosol type predictions from the GEOS-Chem CTM, (5) study long-term trends of aerosol types at a few key locations over the globe, (6) attribute various sources to those aerosol types using the GEOS-Chem CTM and (7) provide recommendations for future passive space-borne instrumentation that could yield an improved aerosol classification from space.
- Applied the SCMC method to two different total-column datasets of aerosol optical properties: inversions from AERONET and retrievals from the space-borne POLDER (Polarization and Directionality of Earth’s Reflectances) instrument. The POLDER retrievals used differ from standard POLDER retrievals [Deuzé et al., 2001] because they make full use of multi-angle, multispectral polarimetric data [Hasekamp et al., 2011]. Their classification algorithm uses three parameters, the Extinction Angstrom Exponent (EAE491,863), the Single Scattering Albedo (SSA670), and the difference between two SSA (dSSA863-491);
- Inferred airborne SCMC aerosol types based on those optical measurements for every flight and compared those SCMC aerosol types to number fraction measurements of sulfate, organic, nitrate, biomass burning, soot, mineral and sea salt fractions from the Particle Analysis by Laser Mass Spectrometry (PALMS) instrument (present on the same aircraft during SEAC4RS); and
- Compared their airborne SCMC aerosol types to ambient mass concentration measurements of organic, sulfate, ammonium and nitrate from the High – Resolution Time – of – Flight Aerosol Mass Spectrometer (AMS) and mass concentration measurements of black carbon (BC) from the Single-Particle Soot Photometers (HD-SP2).
Kacenelenbogen et al., 2016, “Spaceborne Remote Sensing of Aerosol Type: Global Distribution, Model Evaluation and Translation into Chemical Speciation”, Oral, American Geophysical Union (AGU), 12/12-16 2016
Kacenelenbogen et al., 2016, “Spaceborne Remote Sensing of Aerosol Type: Global Distribution, Model Evaluation and Translation into Chemical Speciation”, Oral, 97th
American Meteoorlogical Society (AMS) meeting, Conference on Atmospheric Chemistry, Seattle, WA, 01/ 22–26 2017
NASA Earth Exchange (NEX)
Project Participants (BAERI): Sangram Ganguly, Subodh Kalia
The primary objective of the NEX project is to accelerate scientific discovery using data from NASA’s satellite missions and climate models, and to facilitate scientific collaboration in a way that was not previously possible. NEX maintains a large set of satellite observations and climate model data for use by NASA-supported researchers who are tackling science questions that involve data and computing intensive analyses at regional to global scales. NEX provides the Earth science research community with a virtual collaborative, where scientists can process large data sets, run model codes, and share the results and knowledge. As the data products and models available within NEX and the community utilizing NEX grow, the support needed to maintain this unique collaborative environment also grows.
- Supported the science community to derive a suite of downscaled high-resolution surface climate scenarios based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations, including the NEX-DCP30, NEX-GDDP, BCCA, and the LOCA datasets. The NEX climate datasets described above were designated as core climate datasets for the Fourth National Climate Assessment, and the NEX-DCP30 and BCCA datasets were selected as the two datasets used in the Climate Explorer, the primary data interface for climate scenarios for the U.S. Climate Resilience Toolkit. NEX team members (W Wang and F Melton) served on USGCRP working groups and provided support to USGCRP in accessing and processing these NEX datasets;
- Awarded two NASA ACCESS projects:
- (Open)NEX: Enabling Code-to-Data Migration between High-Performance Computing, Cloud and Beyond
- Object Store-Based Data Service for Earth System Science (collaboration with the HDF Group); and
- Completed the first global, 30-year, daily, 1 km dataset for maximum temperature produced through fusion of satellite and surface temperature observations. Following completion of the dataset for minimum temperature, the datasets will be released and a corresponding publication is being prepared.
Choi, S., C.P. Kempes, T. Park, S. Ganguly, W. Wang, and et al, 2016: Application of the metabolic scaling theory and water-energy balance equation to model large-scale patterns of maximum forest canopy height. Global Ecology and Biogeography, DOI: 10.1111/geb.12503.
Park, T., S. Ganguly, R. Nemani et al., 2016: Changes in growing season duration and productivity of Northern vegetation inferred from long-term remote sensing data. Environmental Research Letters. DOI: 10.1088/1748-9326/11/8/084001.
Melton, F., Xiong, J., Wang, W., Milesi, C., Li, S., Quackenbush, A., et al., 2016. Quantifying Impacts of Climate and Land Use Change on Ecosystem Processes in the Great Northern and Appalachian Landscape Conservation Cooperatives. In Climate change in wildlands: Pioneering approaches to science and management in the Rocky Mountains and Appalachians, A. Hansen, W. Monahan, and D. Theobald (eds.), Island Press.
Orbiting Carbon Observatory-2 Errors/Profiles (OCO-2 E/OCO-2 P)
Project Participants (BAERI): Susan Kulawik
The goal of this project is to develop vertically resolved GOSAT and OCO-2 products. Solving the carbon cycle to estimate locations and amounts of emitted carbon dioxide (e.g. from fires, combustion) and locations and amounts of carbon dioxide uptake (e.g. forests, oceans) is a complex problem utilizing satellite observations, ground based measurements, and transport modeling. Separation of satellite carbon dioxide measurements into lower and upper partial columns provides better constraint on model transport errors and uncertainties, and better information on whether variations in carbon dioxide result from nearby (lower partial column) versus transported (upper partial column) sources. Previous studies have shown that model transport error results in uncertainties in the carbon dioxide emissions and uptakes on continental scales and that vertically resolved observations can identify and constrain transport error.
- Produced lowermost and upper partial columns for the GOSAT v3.5 data record (the current version);
- Validated the new products versus aircraft and surface observations and published in the ACPD paper, “Lower-tropospheric CO2 from near-infrared ACOS-GOSAT observations” (in review);
- Applied the technique to OCO-2 data, resulting in good preliminary results presented at the OCO-2 Science Team Meeting in October, but the OCO-2 results have not been validated; and
- Assimilated the new products by Feng Deng of Dylan Jones’ group. The results of the assimilation were presented at the 2016 AGU Fall Meeting.
Kulawik, Susan S., O’Dell, C., Deng, F., Payne, V., Kuai, L., Worden, H.M., Jones, D.B.A., Sweeney, C., Biraud, S., Iraci, L.T., Yates, E.L., and Tanaka, T., Lower-tropospheric CO2 from near-infrared ACOS-GOSAT observations, AGU Fall Meeting, 12-16 December, 2016, San Francisco, CA
Kulawik, Susan S., O’Dell, C., Deng, F., Payne, V., Worden, H.M., Jones, D.B.A., Dlugokenck, E., Sweeney, C., Biraud, Wennberg, P., Lower troposphere CO2 from OCO-2 and GOSAT, OCO-2 Science Team Meeting, 25-27 October, 2016, NCAR Table Mesa Lab, Boulder, CO
Kulawik, Susan S., Chris O’Dell, Vivienne H. Payne, Le Kuai, Feng Deng, Colm Sweeney, Sebastien C. Biraud, Ed Dlugokencky, Laura Iraci, Emma Yates, Tomoaki Tanaka, “Lower-tropospheric CO2 from near infrared GOSAT observations”, 12th International Workshop on Greenhouse Gas Measurements from Space, Kyoto University, Kyoto, Japan
Pointing Schedules of Agile Spacecraft
Project Participants (BAERI): Sreeja Nag, Alan Li
Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now can slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard’s TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This project will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a Landsat-like sensor.
- Developed capability to scheduling pointing operations for NFoV sensors, for imaging, calibration and downlink, on Single spacecraft in known orbits and Satellite constellations and demonstrated value through a case study – Single and multiple satellites in the Landsat orbits with the existing FOVs;
- Set up computer simulations to mimic and predict interactions of UAS communications so as to stay in touch UAS operators and potentially serve as vehicles to make responsive and valuable measurements for Earth Science;
- Reviewed the commercially available transponders for UAS communication and compare them quantitatively; and
- Completed software development of Executive Driver and Data Computation modules of TAT-C. This included completing its system architecture design and the development of the system Interface Control Document.
Nag,S., C.K. Gatebe, D.W. Miller, O.L. de Weck, “Effect of Satellite Formation Architectures and Imaging Modes on Global Albedo Estimation”, Acta Astronautica 126 (2016), 77-97, DOI:10.1016/j.actaastro.2016.04.004
Nag, S., A.S. Li, “Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging”, American Geophysical Union Fall Meeting, California USA, December 201
Tropospheric Emission Spectrometer (TES)
Project Participants (BAERI): Susan Kulawik
The Tropospheric Emission Spectrometer (TES) is an infrared spectrometer flying aboard the Aura satellite, currently in Earth orbit. Its high spectral resolution enables it to measure concentrations of many chemical constituents in our atmosphere including: O3, CO, H2O (g), PAN, CH2O2, CH3OH, CH4 and other gases. Measurements made by TES advance our understanding of the atmosphere’s chemistry, a knowledge that is prerequisite to addressing air pollution and climate change. TES focuses on the troposphere, the layer of atmosphere that stretches from the ground to approximately 32,000 ft. TES can distinguish concentrations of gases at different altitudes, a key factor in understanding their behavior and impact. It is the first orbiting instrument able to measure O3 profiles, a very important chemical with regard to both global warming and air pollution.
ARC‐CREST researchers and their partners at NASA‐JPL are analyzing and interpreting TES data, making high quality TES data products available to the scientific community. Their work requires close coordination with the NASA Distributed Active Archive Center where these large datasets are hosted. Further, they work closely with the TES science team to expand the retrieval algorithms to capture additional atmospheric gas concentrations, to improve existing algorithms by reducing or better quantifying errors, and to conduct comparisons with other satellite or ground‐based retrievals.
- Worked with the software team to transition the multi-satellite retrieval code to an operational code being run by the software team on OMI and AIRS data to continue the A-Train ozone record begun by TES;
- Developed TES ozone time series products for the Total Ozone Assessment Report (TOAR); and
- Continued to support TES “Lite” products which are easier for first time users, and continued development of the TES-heritage multi-satellite retrieval code.
Kulawik, S., Vivienne Payne, Emily Fischer, Dejian Fu, “Acetone and Hydrogen Cyanide from Aura-TES”, August 30-Sept 1, 2016, Rotterdam, The Netherlands.
Kulawik, S., Vivienne Payne, Emily Fischer, Dejian Fu, “Using TES retrievals of HCN to determine fire influence of Aura-TES footprints”, AGU Fall Meeting, 12-16 December, 2016, San Francisco, CA
GEOstationary Coastal and Air Pollution Events Mission (GEO-CAPE)
Project Participants (BAERI): Susan Kulawik
The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) mission was recommended by the National Research Council’s Earth Science Decadal Survey to measure tropospheric trace gases and aerosols as well as coastal ocean phytoplankton, water quality, and biogeochemistry from geostationary orbit. Multiple observations per day are required to determine tropospheric composition and air quality over spatial scales ranging from urban to continental, and over temporal scales ranging from diurnal to seasonal. High frequency satellite observations are also critical to studying and quantifying biological, chemical, and physical processes within the coastal ocean and beyond. Dr. Kulawik is involved in mission planning and the development of instrument concepts for this upcoming satellite mission. GEO-CAPE is planned to be in orbit in the 2020 timeframe. At this preliminary stage, several instrument concepts are being studied to ensure that a range of potential instruments can meet GEO-CAPE requirements.
- Focused on real-time simulated retrievals; and
- Performed the first simulated NO2 retrievals in November.
Natraj, V., Brad Pierce, Allen Lenzen, Susan Kulawik, Helen Worden, Xiong Liu, Mike Newchurch, Konstantin Vinnikov, “Ozone and NO2 OSSEs on a Regional/Urban Scale for GEO-CAPE”, GEMS Science Team Meeting, October 11, 2016, Yonsei University, Seoul, Korea.
Natraj, V., B. Pierce, A. Lenzen, S. S. Kulawik, “NO2 OSSEs on a Regional/Urban Scale for the GEO-CAPE Mission”, AGU Fall Meeting, 12-16 December, 2016, San Francisco, CA
Alpha Jet Atmospheric Experiment (AJAX)
Project Participants (BAERI): Emma Yates, Ju-Mee Ryoo
AJAX is a public-private partnership between the aircraft owner (H211, LLC) and NASA Ames Research Center. The project uses a tactical strike to carry scientific instruments housed in externally mounted wing pods. Current scientific payload consists of an ozone monitor, a greenhouse gas (carbon dioxide and methane) sensor, and a meteorological measurement system (MMS). Plans are underway to install a formaldehyde instrument. In the past six years, AJAX has flown 203 science flights and participated in numerous field campaigns. The AJAX team researches many topics including 1) Satellite and remote sensing validation (OCO-2, GOSAT, TCCON), 2) investigating the transport of ozone from the free troposphere to the surface, impacting air quality, 3) identifying inaccuracies (under-estimations) in methane emission inventories for the State of California and 4) studying emissions from recent California wildfires.
- Dedicated 8 flights to sampling ozone inflow and variations in California’s boundary layer as part of California Baseline Ozone Transport Study (CABOTS);
- Dedicated 5 flights to sampling emissions from Californian wildfires, particularly the Soberanes megafire;
- Dedicated 5 flights to sampling emissions from urban centers and/or oil and gas structures; and
- Participated in CalWater, CABOTS, SF Bay Area campaign & GOSAT-COMEX campaigns.
Yates, E. L., et al. An assessment of ground-level and free-tropospheric ozone over California and Nevada. (In review, Dec 2016).
Ryoo, J. M., M. S. Johnson, L. T. Iraci, E. L. Yates, R. Bradley Pierce, W. Gore. Investigating sources of ozone in California using AJAX airborne measurements and models: Implications for stratospheric intrusion and long-range transport (In review, Dec 2016).
Kulawik, S., et al. 2016. Lower-tropospheric CO2 from near infrared ACOS-GOSAT observations. Atmospheric Chemistry & Physics Discussions, doi: 10.5194/acp-2016-720.
Yates, E. L., et al. 2016. Airborne measurements and emission estimates of greenhouse gases and other trace constituents from the 2013 California Yosemite Rim wildfire. Atmospheric Environment, 127, 293-302, 2016, doi:10.1016/j.atmosenv.2015.12.038.
Yates, E. L., et al. Western US tropospheric ozone: An assessment of vertical and seasonal variations over California and Nevada. AGU Fall Meeting, San Francisco, CA, December 2016.
Coastal Ocean Biology
Project Participants (BAERI): Juan L. Torres-Pérez, Sherry L. Palacios
This project aims to understand the effects of humans on the health and resilience of reefs, particularly those in the Caribbean. One of the current projects, Human Impacts to Coastal Ecosystems in Puerto Rico (HICE-PR) aims at studying how anthropogenic impacts to watersheds in Puerto Rico eventually cause detrimental effects on the shallow coastal reefs of the Island. The High-Quality Optical Observations (H-Q2O) project is designed to improve Atmospheric Correction and Remote Sensing of Water Quality in the Coastal Zone. Finally, the Hyperspectral Infrared Imager (HyspIRI) is being used to understand ocean biodiversity through the development of remote sensing algorithms that enable a synoptic view of phytoplankton community structure using airborne and satellite ocean color observations.
- Continued the collection of additional benthic data from the reefs located in the southwest coast which are associated with the Río Loco watershed. The benthic data collected so far during the past 3 years in both watersheds sums to more than 10,000 photo grids;
- Participated in a training exercise on the use of wave gliders to collect bio-optical data in Hawaii. The idea is to eventually use these gliders to collect additional water quality bio-optical data on the study sites;
- Participated in field campaigns in Monterey Bay related to the HyspIRI Preparatory Mission and the C-HORSE project, collecting field spectral information at Pinto Lake in Watsonville and the Santa Cruz Wharf with different radiometers; and
- Applied PHYDOTax to San Francisco Bay remote sensing imagery to evaluate phytoplankton community structure, or “food quality” for higher trophic levels in the bay. Phytoplankton community structure strongly influences pelagic fish populations in the bay, including several endangered species.
Torres-Pérez, J.L. 2016. Advancing the knowledge of coral reef spectroscopy and human impacts in coastal and marine ecosystems in the Caribbean. Invited speaker. UC Santa Cruz. February 2016.
Torres-Pérez, J.L., L.S. Guild, and R.A. Armstrong. Advancing the knowledge of coral reef spectroscopy and human impacts in coastal and marine ecosystems in the Caribbean. Invited plenary speaker. Percepción Remota y Sistemas de Información Geográfica en Puerto Rico, 2016 Meeting. University of Puerto Rico at Mayaguez. October, 2016.
Palacios, SL, DR Thompson, RM Kudela, KK Hayashi, LS Guild, B-C Gao, RO Green, JL Torres-Perez. Seasonal and Inter-Annual Patterns of Chlorophyll and Phytoplankton Community Structure in Monterey Bay, CA Derived from AVIRIS Data During the 2013-2015 HyspIRI Airborne Campaign. 2016 Ocean Sciences Meeting, New Orleans LA
4STAR and Satellite Data Analysis
Project Participants (BAERI): Cecilia Chang, Meloe Kacenelenbogen, Samuel LeBlanc, Yohei Shinozuka, Michal Segal-Rozenhaimer, Qin Zhang
The Ames 4STAR (Sky-scanning, Sun-tracking Atmospheric Research) Project uses ground and airborne sun‐photometer instruments to study aerosol radiative properties and measure atmospheric trace gases. Instruments currently in use include: the 4STAR ground and air instruments and the Ames Airborne Tracking Sun‐photometer (AATS‐14). Scientists analyze measurements from these instruments to yield atmospheric aerosol optical depth and extinction spectra, aerosol size distributions, water vapor columns and profiles, and ozone columns. They also have used the sun‐photometer instruments to validate measurements from 12 satellite instruments, two airborne simulators of satellite instruments, and several airborne and ground‐based LIDARS. The 4STAR ground and air instruments broaden the types of usable aircraft and add the additional measurement capabilities of sky‐scanning and improved wavelength resolution.
- Developed an alternate retrieval of aerosol above opaque water cloud using the CALIOP/ CALIPSO Depolarization Ratio Technique over the globe; and
- Continued working on improving instrument reliability and accuracy through the AITT project. Specifically, we worked on instrument calibration stability via comparisons with newly developed ground based standard, and developing an active imager based sun-tracking system.
- Generated, during ORACLES 2016 (phase I of III) total AOD, columnar water vapor, O3 and NO2 as well as sky scans for all ORACLES flights. These will be inverted to get optical properties of the BB aerosols and other aerosols encountered during the campaign. 4STAR has measured Zenith cloud radiance as well, and data was processed to retrieve cloud optical depth and cloud droplet effective radii, which is scheduled to be archived soon.
Jethva, H., Torres, O., Remer, L., Redemann, J., Livingston, J., Dunagan, S., Shinozuka, Y., Kacenelenbogen, M., Segal Rosenheimer, M. Spurr, R. (2016). Validating MODIS Above-cloud Aerosol Optical Depth Retrieved from “Color Ratio ” Algorithm using Direct Measurements made by NASA ’ s Airborne AATS and 4STAR Sensors. AMT, (June), 1–16. http://doi.org/10.5194/amt-2016-178.
Kacenelenbogen et al., CALIOP/ CALIPSO global seasonal nighttime aerosol extinction-to-backscatter (lidar) ratios and optical depths above low opaque water clouds, JGR, in preparation
Making Earth System Data Records for Use in Research Environments (MEaSUREs)
Project Participants (BAERI): Pardha Teluguntla, Jun Xiong
The MEaSUREs project is part of NASA’s Earth Science Data Systems Program, the mission of which is to both manage and expand the many Earth science data records obtained from NASA satellites, airborne platforms, ground stations, and other sources. The MEaSUREs project monitors global croplands to ensure sustainable water and food security. Development and maintenance of this data is important to climate scientists, agricultural scientists, farmers, natural resource managers, and national leaders.
- Produced Production of Global Cropland Extent Version 2. 0 (GCE V2.0) at 250 m resolution for the nominal 2014 using MODIS time-series data, ground knowledge and Spectral Matching Techniques(SMT) for Australia/Africa. Products & Documentation were submitted to LP DAAC, under review;
- Produced 30m Cropland extent version 1.0 (GFSAD30CE) cropland products for Australia/Africa. Finalized the methodology/products, released web-access through www.croplands.org; and
- Developed Crop Intensity layer using MODIS Vegetation indices 16-day composite (MODIS/MOD13Q1). The proposed algorithm was deployed in Google Earth Engine to scale to large area. The global 250m crop intensity map was generated for further evaluation.
Telugunlta et al. “Spectral Matching Techniques (SMTs) and Automated Cropland Classification Algorithms (ACCA’s) for Production of Multi-Year Cropland Products to Address Food Security Issues using MODIS 250m Time-series Data for Australia”, submitted to International Journal of Digital Earth (IJDE), under review.
Cropland Products of Australia @ MODIS 250 m (GCE V2.0) and Landsat 30m (GCE V3.0) : Current status (Pardhasaradhi Teluguntla et al.). Presented during GFSAD30m January 2016 workshop conducted at W.G.S.C, U.S. Geological Survey, MenloPark, CA
Global Croplands Mapping, Pardhasaradhi Teluguntla, Jun Xiong and Adam Oliphant. Museum of Northern Arizona. Sept 29. 2016, Flagstaff, Arizona
ORACLES Radiative Transfer Algorithm Development
Project Participants (BAERI): Michal Segal-Rozenhaimer
The primary goal of this research is to develop new algorithms to retrieve atmospheric aerosol and cloud optical properties from observations by polarimetrically sensitive instruments. These algorithms are intended for the analysis of aerosols lofted above clouds, the main target of ORACLES (ObseRvations of Aerosols Above CLouds and their IntEractionS). The ORACLES experiment will consist of three deployments offshore from Namibia involving two airplanes with numerous ground-based and airborne remote sensing and In-situ instruments. The first deployment was in 2016, and deployments will follow in 2017 and 2018. ORACLES provides multi-year airborne observations over the complete vertical column of the key parameters that drive aerosol-cloud interactions in the South-East Atlantic, an area with some of the largest inter-model differences in aerosol forcing assessments on the planet. Algorithms will be applied to observations by the Research Scanning Polarimeter (RSP) and the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI).
- Worked on developing low level liquid cloud NN retrieval algorithm using RSP polarized simulated data; this enticed generating simulated data that can be used as a training set for the ORACLES campaign, coding up NN scheme framework, performing sensitivity studies on various input combinations and performing network parameter selection and optimization through cross-validation and training/test runs;
- Retrieved cloud properties from ORACLES 2016, comparing with other RSP algorithms to assess their method; and
- Summarized all the algorithm development, sensitivity studies, and retrieval ability and results in a manuscript.
Segal-Rozenhaimer, M., Kirk Knobelspiesse, Jens Redemann, Brian Cairns, Retrievals of liquid cloud properties from polarimetric measurements using Neural Network, in prep. for Remote Sensing of Environment
Segal-Rozenhaimer, M., Kirk Knobelspiesse, Jens Redemann, Brian Cairns, Neural Network (NN) retrievals of Stratocumulus cloud properties using multi-angle polarimetric observations during ORACLES, Oral presentation at AGU fall meeting A33L-06
Project Participants (BAERI): Dave Wilson, Greg Schlick
ARC-CREST researchers on the Plant Physiology team are studying the ecophysiology of biological systems in both synthetic and natural environments. In natural environments, the team is investigating how plants respond to environmental toxicity, bioremediation, and adaptation to climate change, as well as how invasive plant species impact ecosystem functions. This investigation is especially important because the range of many plant species is expected to shift with changing climate and associated changes in resource availability. As the climate changes, different types of plants may be co-located that were not historically within the same ecosystem. This project is currently focused on the Yellowstar Thistle and Cheatgrass, invasive species to California.
- Developed a new methodology for generating bi-weekly WH percent cover maps from (30 meter) Landsat satellite imagery for the SF Bay and Delta;
- Acquired and processed AVIRIS (15 meter) airborne hyperspectral imagery and tested classification methods for Egaria densa; and
- Set-up successfully the USDA Soil and Water Assessment Tool (SWAT) for the Legal Delta area and tested agricultural drainage water quality simulations
Project Participants (BAERI): Sangram Ganguly, Shuang Li
Sentinel-2 (S2) is a land monitoring constellation of two satellites that provides high resolution optical imagery by European Space Agency (ESA). Sentinel-2A is the first of two satellites was successfully launched in June 2015. Its MultiSpectral Instrument (MSI) capitalizes on the technology and the vast experience acquired with SPOT and Landsat over the past three decades. The S2 MSI samples 13 spectral bands: four bands at 10 meters, six bands at 20 meters and three bands at 60-meters spatial resolution.
NASA Earth Exchange (NEX) team has been working on radiometric cross-calibration of the S2 MSI and Landsat-8 OLI sensors based on the latest released sample S2 images from ESA. An S2 processing pipeline has also been developed to provide research ready S2 imagery to the remote sensing community. The algorithm used for S2 atmospheric correction is consistent with standard Landsat OLI product, which provides potential data harmonization between Landsat 8 and S2. NEX supercomputing facility will be used to process daily-acquired S2 images.
- Deployed S2 atmospheric correction tool (ESA) on NASA NEX;
- Processed all the released sample S2 data and compared with Landsat 8 images; and
- Determined that the atmospheric correction tool (developed by ESA) is not reliable in its current status. Abnormal pixel values from derived S2 L2A products (surface reflectance) occur in all land cover types
Huang, S., H. Liu, D. Dahal, S. Jin, S. Li, and S. Liu (2016). Spatial variations in immediate greenhouse gases and aerosol emissions and resulting radiative forcing from wildfires in interior Alaska. Theoretical and Applied Climatology. 123(3): 581-592. doi:10.1007/s00704-015-1379-0
Li, S., S. Ganguly, J. Dungan, W. Wang, R.R. Nemani (2016). Sentinel-2 MSI Radiometric Characterization and Cross-Calibration with Landsat-8 OLI. Ready to submit for review
Project Participants (BAERI): Cindy Schmidt. NASA: Jim Brass
The Ecological Forecasting program is a sub-program within NASA’s Applied Science Program whose larger goal is to advance innovative and practical uses of Earth observations and modelling in order to enhance stewardship of natural resources and decision making of public and private organizations. ARC-CREST staff are part of the Program management team. In this capacity, they track the projects in the Ecological Forecasting portfolio, support strategic planning activities, help coordinate annual program review meetings and participate in interagency activities and meetings as required by the Program Manager for Ecological Forecasting.
- Attended Arctic Boreal Vulnerability Experiment meeting to represent NASA Applied Sciences program, Anchorage, AK ;
- Helped organize and attended NASA Ecological Forecasting PI meeting, Washington DC
- Conducted site visit to University of Wisconsin, Madison to meet with the “Snapshot Wisconsin” team
“Using NASA data for Earth Science Applications”, Key Note Presentation, Florida GIS Conference, Daytona Beach, Florida
Project Participants (BAERI): Vickie Ly, Cindy Schmidt, Sherry Palacios
The NASA Applied Science Capacity Building program seeks to better understand the needs and data gaps in the use of geospatial data, particularly NASA Earth science data and products, within Indigenous communities in North America. Tribal members and other long-term residents of particular areas have developed extensive knowledge bases that include deep understanding of local environments and adaptive processes passed down through generations. That knowledge, referred to as “indigenous knowledge” or “traditional ecological knowledge (TEK)” is typically orally passed down through generations, and holistic in having cultural and spiritual components. TEK encompasses the relation of living beings with each other and the surrounding environment. In addition to better understanding the needs and data gaps of Indigenous groups, this effort also seeks to understand how TEK can inform NASA Earth Science activities.
- Attended Conferences: National Indian Timber Symposium, San Carlos Apache Reservation (April), Intertribal Environmental Summit, Dallas, TX (April), Tribal GIS Conference, Albuquerque, NM (November)
- Visited Sault tribe of Chippewa Indians, Sault Ste Marie, MI (August);
- Conducted 1-day, hands-on Introduction to Remote Sensing workshop, Tribal GIS Conference, Albuquerque, NM (November)
“Using NASA Data for Earth Science Applications”, National Indian Timber Symposium, San Carlos Apache Reservation, Arizona (April)
“Using NASA Data for Earth Science Applications”, Intertribal Environmental Summit, Dallas, TX (April)
“Using NASA Data for Earth Science Applications”, Tribal GIS conference, Albuquerque, NM (November)