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NASA NTRS2013

Combinations of Earth Orientation Measurements: SPACE2011, COMB2011, and POLE2011

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2011, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to July 13, 2012, at daily intervals and is available in versions with epochs given at either midnight or noon. The space-geodetic measurements used to generate SPACE2011 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2011, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to July 13, 2012, at daily intervals and which are also available in versions with epochs given at either midnight or noon; and (2) POLE2011, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to June 21, 2012, at 30.4375-day intervals.

Ratcliff, J. T.↗

NASA NTRS2013

Combinations of Earth Orientation Measurements: SPACE2012, COMB2012, and POLE2012

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2012, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to April 26, 2013, at daily intervals and is available in versions with epochs given at either midnight or noon. The space-geodetic measurements used to generate SPACE2012 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2012, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to April 26, 2013, at daily intervals and which are also available in versions with epochs given at either midnight or noon; and (2) POLE2012, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to May 22, 2013, at 30.4375-day intervals.

Ratcliff, J. T.↗

NASA NTRS2015

Combinations of Earth Orientation Measurements: SPACE2013, COMB2013, and POLE2013

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2013, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to June 30, 2014, at daily intervals and is available in versions with epochs given at either midnight or noon. The space-geodetic measurements used to generate SPACE2013 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2013, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to June 30, 2014, at daily intervals and which are also available in versions with epochs given at either midnight or noon; and (2) POLE2013, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to June 22, 2014, at 30.4375-day intervals.

Ratcliff, J. T.↗

NASA NTRS2015

Combinations of Earth Orientation Measurements: SPACE2014, COMB2014, and POLE2014

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2013, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to June 30, 2014, at daily intervals and is available in versions with epochs given at either midnight or noon. The space-geodetic measurements used to generate SPACE2013 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2013, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to June 30, 2014, at daily intervals and which are also available in versions with epochs given at either midnight or noon; and (2) POLE2013, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to June 22, 2014, at 30.4375-day intervals.

Ratcliff, J. T.↗

NASA NTRS2017

Combinations of Earth Orientation Measurements: SPACE2016, COMB2016, and POLE2016

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2016, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to June 30, 2017, at daily intervals and is available in versions with epochs given at either midnight or noon. The space-geodetic measurements used to generate SPACE2016 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2016, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to June 30, 2017, at daily intervals and which are also available in versions with epochs given at either midnight or noon; and (2) POLE2016, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to June 22, 2017, at 30.4375-day intervals.

Ratcliff, J. T.↗

NASA NTRS2016

The GPM Combined Algorithm

In this paper, the operational Global Precipitation Measurement (GPM) mission combined radar-radiometer algorithm is thoroughly described. The operational combined algorithm is designed to reduce uncertainties in GPM Core Observatory precipitation estimates by effectively integrating complementary information from the GPM Dual-Frequency Precipitation Radar (DPR) and the GPM Microwave Imager (GMI) into an optimal, physically consistent precipitation product. Although similar in many respects to previously developed combined algorithms, the GPM combined algorithm has several unique features that are specifically designed to meet the GPM objectives of deriving, based on GPM Core Observatory information, accurate and physically consistent precipitation estimates from multiple spaceborne instruments, and ancillary environmental data from reanalyses. The algorithm features an optimal estimation framework based on a statistical formulation of the Gauss-Newton method, a parameterization for the nonuniform distribution of precipitation within the radar fields of view, a methodology to detect and account for multiple scattering in Ka-band DPR observations, and a statistical deconvolution technique that allows for an efficient sequential incorporation of radiometer information into DPR precipitation retrievals.

Grecu, Mircea↗

NASA NTRS2018

Combinations of Earth Orientation Measurements: SPACE2017, COMB2017, and POLE2017

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2017, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to June 29, 2018m at daily intervals and is available in versions with epochs given at either midnight or noon. The space-geodetic measurements used to generate SPACE2017 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2017, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962 to June 29, 2018, at daily intervals and which are also available inversions with epochs given at either midnight or noon; and (2) POLE2017, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1990, to June 22, 2018, at 30.4375-day intervals.

VLBI↗

NASA NTRS2019

Combinations of Earth Orientation Measurements: SPACE2018, COMB2018, and POLE2018

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2018, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to June 28, 2019, at daily intervals and is available in versions with epochs given at either midnight or noon. The space-geodetic measurements used to generate SPACE2018 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2018, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to June 28, 2019, at daily intervals and which are also available in versions with epochs given at either midnight or noon; and (2) POLE2018, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to June 22, 2019, at 30.4375-day intervals.

VLBI↗

NASA NTRSDate not supplied

Novel insights enabled by combining mouse muscle datasets from the Rodent Research-1 mission

Biological space experiments are often expensive and difficult to conduct. As such, it is critical to maximize the value of the data that is collected during these experiments. One way to do this is to combine multiple–previously separate–datasets. This can increase the number of replicates for the conditions of interest (and hence statistical power), allow new multi-factor questions to be asked, and potentially highlight new patterns that otherwise would not have been identified from single-dataset studies. However, the process of combining datasets introduces noise due to inherent technical variations between experiments. To better understand the insights that can be gained from multi-dataset analyses and the problems that may arise from joining multiple datasets, several mouse muscle RNA-Seq datasets from the Rodent Research-1 mission were first selected. Then, using the R package DESeq2, principal component analysis (PCA) plots and differentially expressed gene (DEG) lists between ground and flight muscle samples were generated for individual datasets and for different pairwise combinations of datasets. Several new DEGs were identified in the combined datasets, and patterns in the PCA plots were affected depending on which datasets were joined. Understanding the results of this work will be critical for future studies that seek to perform multi-dataset analyses.

spaceflight↗

NASA NTRSDate not supplied

An Optimal Estimation Aerosol Retrieval Algorithm for Lidar-only and Combined Lidar Polarimeter Remote Sensors

Global measurements of aerosol vertical profile, composition, concentration, and size distribution are very important due to aerosol impacts on air quality, climate, clouds, and ocean ecosystems. We have developed a lidar-only and combined lidar and polarimeter algorithm to retrieve vertically-resolved profiles of aerosol microphysical properties. The new retrieval system is modular in design. It consists of three modules, a vertically-resolved aerosol profile retrieval module for lidar data, an aerosol and cloud/ocean retrieval module for polarimeter data, and a combined retrieval module for both lidar and polarimeter measurements. In addition to performing optimal estimation retrievals on various data sources, we have designed the system so that it can be used to carry out aerosol retrieval performance trade studies for various lidar and polarimeter configurations. For example, the retrieval system can take inputs from attenuated backscatter lidar at two wavelengths (e.g. CALIPSO like instrument), aerosol backscattering measured at two wavelengths and and aerosol extinction measured at one wavelength (HSRL-1), or aerosol backscattering measured at three wavelengths and aerosol extinction measured at two wavelengths (HSRL-1) (HSRL-2). We have applied the lidar-only algorithm to both simulated data and various field campaign data (DISCOVER-AQ, CHARMS, TCAP, and ORACLES). For polarimeter-only modules, we have done the same for SABOR, TCAP, NAAMES, and ORACLES data. We have applied the combined retrieval algorithm to ORACLES data. The simulated retrieval studies show that the combined lidar+polarimeter retrieval provides much higher information content relative to their individual counterparts for retrieving effective radius, particle concentrations, and absorption properties.

Xu Liu↗

NASA NTRS2004

Combinations of Earth orientation measurements : SPACE2003, COMB2003, and POLE2003

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the global positioning system have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2003, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28.0, 1976 to January 31.0, 2004 at daily intervals and is available in versions whose epochs are given at either midnight or noon. The space-geodetic measurements used to generate SPACE2003 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2003, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20.0, 1962 to January 31.0, 2004 at daily intervals and which is also available in versions whose epochs are given at either midnight or noon, and (2) POLE2003, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900 to January 21, 2004 at 30.4375-day intervals.

Gross, Richard↗

NASA NTRS2009

Combinations of Earth orientation measurements : SPACE2007, COMB2007, and POLE2007.

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2007, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to March 29, 2008, at daily intervals and is available in versions whose epochs are given at either midnight or noon. The space-geodetic measurements used to generate SPACE2007 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2007, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to March 29, 2008, at daily intervals and which is also available in versions whose epochs are given at either midnight or noon; and (2) POLE2007, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to March 22, 2008, at 30.4375-day intervals.

Gross, R. S.↗

NASA NTRS2010

Combinations of Earth orientation measurements : SPACE2008, COMB2008, and POLE2008

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2008, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to July 2, 2009, at daily intervals and is available in versions whose with epochs are given at either midnight or noon. The space-geodetic measurements used to generate SPACE2008 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2008, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to July 2, 2009, at daily intervals and which areis also available in versions whose with epochs are given at either midnight or noon; and (2) POLE2008, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to June 22, 2009, at 30.4375-day intervals..

Gross, R. S.↗

NASA NTRS2011

Combinations of Earth Orientation Measurements : SPACE2010, COMB2010, and POLE2010

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2010, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to July 15, 2011, at daily intervals and is available in versions with epochs given at either midnight or noon. The space-geodetic measurements used to generate SPACE2010 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2010, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to July 15, 2011, at daily intervals and which are also available in versions with epochs given at either midnight or noon; and (2) POLE2010, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to June 22, 2011, at 30.4375-day intervals.

Gross, R. S.↗

NASA NTRS2013

Combinations of Earth Orientation Measurements: SPACE2011, COMB2011, and POLE2011

Gross, R. S.↗

NASA NTRS2015

Combinations of Earth orientation measurements: SPACE2014, COMB2014, and POLE2014

Independent Earth orientation measurements taken by the space-geodetic techniques of lunar and satellite laser ranging, very long baseline interferometry, and the Global Positioning System have been combined using a Kalman filter. The resulting combined Earth orientation series, SPACE2014, consists of values and uncertainties for Universal Time, polar motion, and their rates that span from September 28, 1976, to April 14, 2015, at daily intervals and is available in versions with epochs given at either midnight or noon. The space-geodetic measurements used to generate SPACE2014 have then been combined with optical astrometric measurements to form two additional combined Earth orientation series: (1) COMB2014, consisting of values and uncertainties for Universal Time, polar motion, and their rates that span from January 20, 1962, to April 14, 2015, at daily intervals and which are also available in versions with epochs given at either midnight or noon; and (2) POLE2014, consisting of values and uncertainties for polar motion and its rate that span from January 20, 1900, to March 23, 2015, at 30.4375-day intervals.

Gross, R.S.↗

NASA NTRS2019

Early Lessons on Combining Lidar and Multi‑baseline SAR Measurements for Forest Structure Characterization

The estimation and monitoring of 3D forest structure at large scales strongly rely on the use of remote sensing techniques. Today, two of them are able to provide 3D forest structure estimates: lidar and synthetic aperture radar (SAR) configurations. The differences in wavelength, imaging geometry, and technical implementation make the measurements pro-vided by the two configurations different and, when it comes to the sensitivity to individual 3D forest structure components, complementary. Accordingly, the potential of combining lidar and SAR measurements toward an improved 3D forest structure estimation has been recognised from the very beginning. However, until today there is no established frame-work for this combination. This paper attempts to review differences, commonalities, and complementarities of lidar and SAR measurements. First, vertical lidar reflectance and SAR reflectivity profiles at different wavelengths are compared in different forest types. Then, current perspectives on their combination for the generation of enhanced structure products are discussed. Two promising frameworks for combining lidar and SAR measurements are reviewed. The first one is a model-based framework where lidar-derived parameters are used to initialize SAR scattering models, and relies on both the validity of the models and on the physical equivalence of the used lidar and SAR parameters. The second one is a structure-based framework based on the ability of lidar and SAR measurements to express physical forest structure by means of appropriate indices. These indices can then be used to establish a link between the two kind of measurements. The review is supported by experimental results achieved using space- and airborne data acquired in recent relevant mission and campaigns.

Matteo Pardini↗

NASA NTRSDate not supplied

Sensorimotor Application of Proposed Methods to Combine the Effects of Multiple Countermeasures for PRisM

Risk associated with human systems is challenging to quantify but is critical for the mission planning and decision making required to enable future Lunar and Martian missions. To address this gap, the Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) project is developing an integrated computational model for CHP mission risk. Much like how MEDPRAT is designed to allow medical resource trades informed by medical risk, CHP-PRA will enable analogous trades in human system risks across multiple CHP functions and capabilities. Human performance is one component of the risk intended to be captured by CHP-PRA through the Performance Risk Model (PRisM). The sensorimotor risk area provides a good frame of reference for investigating the structure of a performance model because most tasks that astronauts are expected to perform require input from the sensory system and/or movement/motor control. Additionally, sensorimotor countermeasures are an area of particular concern for NASA’s Human Research Program because of the increased sensorimotor risk associated with surface operations in Lunar and Martian missions. Thus, a tool that can quickly compare risk reductions of potential countermeasures would be beneficial in guiding research and development of effective countermeasures. In this proof of concept, we present a systematic way to combine multiple performance data sets for humans subjected to different countermeasures such that we can predict the countermeasure(s) that optimize astronaut performance on relevant tasks. PRisM assumes that both the tests that are used to measure countermeasure effectiveness (input data) and the tasks we use to represent astronaut performance, can be broken down and represented as a function/vector of the human systems required to perform that test/task. Through mathematical combination, test data are used to predict performance on astronaut tasks that use similar systems. We propose that when combining countermeasures evaluated using the same test, that only one value should be used to represent their combined effectiveness. We start our analysis with the assumption that two countermeasures together will perform better than each countermeasure individually. Our initial implementation of this framework compares various space motion sickness countermeasures and the most up to date analysis will be demonstrated at the IWS.

Caroline R Austin↗