Level 2 Aerosol Retrieval Algorithm Theoretical Basis
This Algorithm Basis (ATB) document describes the algorithms used to retrieve the aerosol parameters of the MISR Level 2 Aerosol/Surface Product.
Level 2 retrieval algorithm theoretical basis↗
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Draft Genome Sequences of Biosafety Level 2 Opportunistic Pathogens Isolated From the Environmental Surfaces of the International Space Station
The draft genome sequences of 20 biosafety level 2 (BSL-2) opportunistic pathogens isolated from the environmental surfaces of the International Space Station (ISS) were presented. These genomic sequences will help in understanding the influence of microgravity on the pathogenicity and virulence of these strains when compared with Earth strains.
Aleksandra Checinska Sielaff↗
Challenges in Obtaining and Visualizing Satellite Level 2 Data in GIS
Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. One way to help users better understand the satellite data is to provide data along with Images, including accurate pixel coverage area delineation, and science team recommended quality screening for individual geophysical parameters. However, there are challenges of visualizing remote sensed non-gridded products: (1) different geodetics of space-borne instruments (2) data often arranged in a long-track and a cross-track axes (3) spatially and temporally continuous data chunked into granule files: data for a portion (or all) of a satellite orbit (4) no general rule of resampling or interpolations to a grid (5) geophysical retrieval only based on pixel center location without shape information. In this presentation, we will unravel a new Goddard Earth Sciences Data and Information Services Center (GES DISC) Level 2 (L2) visualization on-demand service. The service's front end provides various visualization and data accessing capabilities, such as overlay and swipe of multiply variables and subset and download of data in different formats. The backend of the service consists of Open Geospatial Consortium (OGC) standard-compliant Web Mapping Service (WMS) and Web Coverage Service. The infrastructure allows inclusion of outside data sources served in OGC compliant protocols and allows other interoperable clients, such as ArcGIS clients, to connect to our L2 WCS/WMS.
GI↗
Maintenance of quasi-stationary waves in a 2-level quasi-geostrophic spectral model with topography
The maintenance of the quasi-stationary waves obtained through numerically integrating a 2-level quasi-geostrophic spectral model on a beta-plane is investigated. An idealized topography which has only wavenumber n in the zonal direction and the first mode in the meridional direction is used to force the quasi-stationary waves. It is shown that the topographical forcing is not necessarily the mechanism for maintaining the quasi-stationary waves.
Yao, M. S.↗
Level 2 Surface Retrieval Algorithm Theoertical Basis
This Algorithm Theoretical Basis (ATB) document describes the algorithms used to retrieve the surface parameters of the MISR Level 2 Aerosol/Surface Product.
surface algorithm theoretical retrieval↗
Laser Remote Sensing from ISS: CATS Cloud and Aerosol Level 2 Data Products (Heritage Edition)
With the recent launch of the Cloud-Aerosol Transport System (CATS) we have the opportunity to acquire a continuous record of space based lidar measurements spanning from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) era to the start of the EarthCARE mission. Utilizing existing well-validated science algorithms from the CALIPSO mission, we will ingest the CATS data stream and deliver high-quality lidar data sets to the user community at the earliest possible opportunity. In this paper we present an overview of procedures necessary to generate CALIPSO-like lidar level 2 data products from the CATS level 1 data products.
cloud-aerosol lidar↗
Development of Level 2 Calibration and Validation Plans for GOES-R; What is a RIMP?
Calibration and Validation (CalVal) plans for Geostationary Operational Environmental Satellite version R (GOES-R) Level 2 (L2) products were documented via Resource, Implementation, and Management Plans (RIMPs) for all of the official L2 products required from the GOES-R Advanced Baseline Imager (ABI). In 2015 the GOES-R program decided to replace the typical CalVal plans with RIMPs that covered, for a given L2 product, what was required from that product, how it would be validated, and what tools would be used to do so. Similar to Level 1b products, the intent was to cover the full spectrum of planning required for the CalVal of L2 ABI products. Instead of focusing on step-by-step procedures, the RIMPs concentrated on the criteria for each stage of the validation process (Beta, Provisional, and Full Validation) and the many elements required to prove when each stage was reached.
Validation↗
Development of Level 2 Calibration and Validation Plans for GOES-R; What is a RIMP?
Calibration and Validation (CalVal) plans for Geostationary Operational Environmental Satellite version R (GOES-R) Level 2 (L2) products were documented via Resource, Implementation, and Management Plans (RIMPs) for all of the official L2 products required from the GOES-R Advanced Baseline Imager (ABI). In 2015 the GOES-R program decided to replace the typical CalVal plans with RIMPs that covered, for a given L2 product, what was required from that product, how it would be validated, and what tools would be used to do so. Similar to Level 1b products, the intent was to cover the full spectrum of planning required for the CalVal of L2 ABI products. Instead of focusing on step-by-step procedures, the RIMPs concentrated on the criteria for each stage of the validation process (Beta, Provisional, and Full Validation) and the many elements required to prove when each stage was reached.
Validation↗
Level 2 Cloud Detection and Classification Algorithm Theoretical Basis
This Algorithm Theoretical Basis (ATB) document describes the algorithms used to retrieve the cloud classification parameters of the MISR Level 2 Top-of-Atmosphere (TOA)/Cloud Product.
detection cloud classification algorithm↗
Level 2 Ancillary Products and Datasets Algorithm Theoretical Basis
This Algorithm Theoretical Basis (ATB) document describes the algorithms used to generate the parameters of certain ancillary products and datasets used during Level 2 processing of Multi-angle Imaging SpectroRadiometer (MIST) data.
ancillary algorithm theoretical↗
SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation
Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.
Bindlish, Rajat↗
Aerosol Optical Depth Changes in Version 4 CALIPSO Level 2 Product
The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 4.10 (V4) products were released in November 2016 with substantial enhancements. There have been improvements in the V4 CALIOP level 2 aerosol optical depth (AOD) compared to V3 (version 3) due to various factors. AOD change from V3 to V4 is investigated by separating factors. CALIOP AOD was compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) for both V3 and V4.
Kim, Man-Hae↗
Level 2 Top-of-Atmosphere Albedo Algorithm Theorectical Basis
This Algorithm Theoretical Basis (ATB) document describes the algorithms used to retrieve the albedo parameters of the Multi-angle Imaging SpectroRadiometer (MISR) Level 2 Top-of-Atmosphere (TOA)/Cloud Product.
Top-of-Atmosphere albedo algorithm↗
ResStock Measure Documentation: Electric Vehicle Adoption With Level 2 Charging
This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 2 Charging" measure upgrade methodology and briefly discusses key results.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
ResStock Measure Documentation: Efficient Electric Vehicle Adoption With Level 2 Charging
This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Efficient Electric Vehicle Adoption With Level 2 Charging" measure upgrade methodology and briefly discusses key results.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
ResStock Measure Documentation: Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility
This report is part of a series describing different ResStock measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility" measure upgrade methodology and briefly discusses key results.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
ResStock Measure Documentation: Efficient Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility
This report is part of a series describing different ResStock measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Efficient Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility" measure upgrade methodology and briefly discusses key results.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Technical Capability Level 2 Unmanned Aircraft System Traffic Management (UTM) Flight Demonstration: Description and Analysis
NASA's UAS Traffic Management (UTM) project concluded its second flight demonstration activity in late October 2016. This activity demonstrated the capabilities and functionality incorporated into its Technical Capability Level 2 (TCL2) concept, which envisions future operations that are low density, capable of being performed over sparsely populated areas, and allow for a concurrent mix of longer duration, beyond visual-line-of-sight flights and shorter flights within visual-line-of-sight (VLOS). To incorporate these features into a flight demonstration, a scenario-based approach was taken to address different aspects of the TCL2 environment and to meet defined objectives. This paper will describe elements of how the flight activity was conducted and present analyses regarding UTM operations, system messages, and alerting as they pertained to meeting the demonstration objectives and shedding light on research questions and lessons learned.NASA was able to successfully demonstrate complex UTMoperations in a TCL 2 environment in collaboration withindustry partners and the Reno-Stead Airport UAS test range.A scenario-based approach to the demonstration provided arelevant means through which the key elements and objectivesof the test could be captured. Although issues were identifiedthrough the testing and feedback of test participants, theoverall results were in line with the overall UTM objective ofsafely enabling large-scale UAS operations in low altitudeairspace.
Homola, Jeffrey↗