Results for “ARGOS” — Page 3

NASA NTRS2001

In-Situ Detections of a Satellite Breakup by the SPADUS Experiment

For the first time, a particle detector in Earth orbit has provided evidence to directly link sub-millimeter orbital debris to a specific satellite breakup. The University of Chicago's Space Dust instrument (SPADUS), on the U.S. Air Force's Advanced Research and Global Observation Satellite (ARGOS), has been operating in a nearly polar orbit at an altitude of about 830 km since soon after its launch on 23 February 1999. The experiment was designed primarily to detect small natural and man-made particles less than 100 microns in diameter. Using a dual-plane Polyvinylidene Fluoride (PVDF)-based detection system, SPADUS can measure dust particle flux, mass distribution, velocity, and trajectory. During its first year in orbit, SPADUS recorded 195 impacts, about one impact every two days. In late March 2000 the instrument detection rate soared by approximately an order of magnitude, suggesting a potential encounter with a cloud or stream of debris. A review of the impact times and ARGOS orbital characteristics indicated that most of the detections occurred at multiples of half-revolution intervals deep in the northern and southern hemispheres, with a clear majority of impacts found in the latter. Orbital analyses linked these impact events to the orbital plane intersections of ARGOS and the debris cloud of a Chinese orbital stage (International Designator 1999-057C, US Satellite Number 25942) which had undergone a severe fragmentation on 11 March 2000 at an altitude 100 km below that of ARGOS. Approximately 40 of the SPADUS detections during the period 25 March 1 April could be associated with the postulated Chinese debris cloud. Other periods of high impact flux on SPADUS may be related to debris clouds from different sources.

Tuzzolino, A. J.↗

NASA NTRS2010

Generating a Reduced Gravity Environment on Earth

Since the 1950s several reduced gravity simulators have been designed and utilized in preparing humans for spaceflight and in reduced gravity system development. The Active Response Gravity Offload System (ARGOS) is the newest and most realistic gravity offload simulator. ARGOS provides three degrees of motion within the test area and is scalable for full building deployment. The inertia of the overhead system is eliminated by an active motor and control system. This presentation will discuss what ARGOS is, how it functions, and the unique challenges of interfacing to the human. Test data and video for human and robotic systems will be presented. A major variable in the human machine interaction is the interface of ARGOS to the human. These challenges along with design solutions will be discussed.

Dungan, Larry K.↗

NASA NTRSDate not supplied

Evaluation of Aerobic Standards for Lunar Surface Extravehicular Activities

Introduction: As NASA prepares to return to the Moon, astronauts will need to be physically primed to successfully execute Extravehicular Activities (EVA) on the Lunar surface. Compared to past Apollo missions, Artemis missions will include EVAs of increased physical demand, frequency, intensity, and duration, thus requiring adequate fitness to successfully and safely complete mission objectives. The physical demand associated with partial gravity (g) EVAs on the Moon is expected to be greater compared to microgravity EVAs based on initial workload estimation. Currently, aerobic fitness standards for partial g EVAs are not well supported by high-fidelity data and require further research for establishing standards to protect crew health and performance during Lunar surface missions. Therefore, the aim of this investigation is to characterize metabolic data from Lunar analog simulations and in-flight crew population aerobic capacity data to validate the current NASA 3001 standard for celestial partial g aerobic fitness (aerobic capacity (VO_2pk) ≥36.5ml/kg/min). Methods: In order to evaluate aerobic fitness requirements for Lunar EVAs, the following were performed: 1) preliminary analysis of long-duration (6 hr) EVA analog simulations in the Neutral Buoyancy Laboratory (NBL) and the Active Response Gravity Offload System (ARGOS) to evaluate expected metabolic rates for 1/6 g EVAs (NBL: n=1 female; ARGOS: n=1 male) and 2) assessment of the current NASA 3001 celestial surface EVA aerobic standard (aerobic capacity (VO_2pk) ≥36.5ml/kg/min) with data from an ISS astronaut population (n=30 male + 13 female) captured before and during space flight (flight day 15). Preliminary Results: Average fractional aerobic capacity during simulated EVAs were 33%±7% VO_2pk and 23.3±7% VO_2pk in the NBL and ARGOS, respectively. This was within a previously predicted 30–40% sustainable work rate. Average metabolic rates for some tasks performed in the NBL, such as traverse (40.4% VO_2pk) and ingress (47.1% VO_2pk) were higher than the predicted sustainable work range. In ARGOS, the tasks with the greatest metabolic rates were object relocation (34.2% VO_2pk) and incapacitated crew rescue (27.0% VO_2pk). Characterization of ISS crewmember aerobic capacity determined that the average preflight VO_2pk was 42.1±5.4 ml/kg/min for females and 37.5±5.4 ml/kg/min for males. At preflight, 21.5% of crewmembers were below the 36.5 ml/kg/min in-mission aerobic standard for celestial surface EVA as outlined in NASA-STD-3001. In-flight, both female and male crewmembers experienced reductions in VO_2pk (11.7% and 10.9%, respectively), such that, during the mission, 62% of crewmembers were below the standard aerobic capacity level for celestial surface EVAs. Conclusions: Our preliminary data suggest that while average metabolic rates for simulated Lunar EVA fall within the 30–40% sustainable work range, task specific metabolic rates exceed this range and may indicate that greater fitness is necessary for more strenuous tasks expected to be performed on the Lunar surface. Additionally, deconditioning due to space flight results in most crewmembers falling below the current celestial partial g EVA standard, which may increase risk to crew health and performance and completing mission objectives for surface missions. Further research is necessary in Artemis-specific analog environments to validate the current NASA-3001 aerobic standard for celestial EVAs. Additionally, work is ongoing to validate the current NASA-3001 strength standard for celestial EVAs.

N.C. Strock↗

NASA NTRS2012

Earth Radiation Imbalance from a Constellation of 66 Iridium Satellites: Climate Science Aspects

The "global warming hiatus" since the 1998 El Nino, highlighted by Meehl et al., and the resulting "missing energy" problem highlighted by Trenberth et al., has opened the door to a more fundamental view of climate change than mere surface air temperature. That new view is based on two variables which are strongly correlated: the rate of change of ocean heat content d(OHC)/dt; and Earth Radiation Imbalance (ERI) at the top of the atmosphere, whose guesstimated range is 0.4 to 0.9 Watts per square meters (this imbalance being mainly due to increasing CO2). The Argo float array is making better and better measurements of OHC. But existing satellite systems cannot measure ERI to even one significant digit. So, climate model predictions of ERI are used in place of real measurements of it, and the satellite data are tuned to the climate model predictions. Some oceanographers say "just depend on Argo for understanding the global warming hiatus and the missing energy", but we don't think this is a good idea because d(OHC)/dt and ERI have different time scales and are never perfectly correlated. We think the ERB community needs to step up to measuring ERI correctly, just as oceanographers have deployed Argo to measure OHC correctly. This talk will overview a proposed constellation of 66 Earth radiation budget instruments, hosted on Iridium satellites, that will actually be able to measure ERI to at least one significant digit, thus enabling a crucial test of climate models. This constellation will also be able to provide ERI at two-hourly time scales and 500-km spatial scales without extrapolations from uncalibrated narrowband geostationary instruments, using the highly successful methods of GRACE to obtain spatial resolution. This high time resolution would make ERI a synoptic variable like temperature, and allow studies of ERI's response to fast-evolving phenomena like dust storms and hurricanes and even brief excursions of Total Solar Irradiance. Time permitting, we will also discuss the emerging view of clear vs. cloudy and its implications for the traditional ERB approach.

Wiscombe, W.↗

NASA NTRS2015

Generating a Reduced Gravity Environment on Earth

The Active Response Gravity Offload System (ARGOS) is designed to simulate reduced gravity environments, such as Lunar, Martian, or microgravity using a vertical lifting hoist and horizontal motion system. Three directions of motion are provided over a 41 ft x 24 ft x 25 ft tall area. ARGOS supplies a continuous offload of a portion of a person's weight during dynamic motions such as walking, running, and jumping. The ARGOS system tracks the person's motion in the horizontal directions to maintain a vertical offload force directly above the person or payload by measuring the deflection of the cable and adjusting accordingly.

Dungan, L. K.↗

NASA NTRS2020

Development and Evaluation of the Active Response Gravity Offload System as a Lunar and Martian EVA Simulation Environment

In preparation for future exploration missions, NASA seeks the ability to simulate partial-gravity operations for use in ground-based research, crew training, and engineering design evaluations. The Active Response Gravity Offload System (ARGOS) at the Johnson Space Center (JSC) is designed to simulate reduced gravity environments, such as lunar, Martian, or microgravity, using a robotic system similar to an overhead bridge crane. ARGOS continuously offloads a portion of a suited human’s weight during all dynamic motions within the test facility, which can include basic functional movements such as walking, running, and jumping, as well as a wide range of planetary surface activities. This system will be used as part of a metabolic-rate task characterization study to determine the workload associated with partial-gravity extravehicular activity (EVA). Pilot testing was conducted using the MKIII prototype planetary space suit and two gimbal designs to determine the ability of the ARGOS test environment to simulate planetary EVA operations. This paper will describe the lessons learned from the feasibility testing, simulation-environment mockup design, and the results from the pilot tests and their influence into the final study design. Being able to effectively simulate partial-gravity environments and characterize the performance of crewmembers will have an impact on multiple domains including suit design, task design, thermal models, and life-support-system capacity verification plans, among others.

Omar S Bekdash↗

NASA NTRSDate not supplied

Development of an Inertial Sensor-based Methodology for Spacesuited Geology Task Assessments during Simulated Lunar Extravehicular Activities

Lunar surface exploration during Artemis missions will require the specific skill set of geology sampling. Apollo astronauts had extensive training and used specialized tools to collect lunar rocks, core samples, pebbles, sand, and dust. The inflexibility of the pressurized Apollo spacesuits forced sampling to be taken at a standstill posture. However, new exploration spacesuits are expected to incorporate advanced materials and joint bearings, allowing for greater mobility and a wider range of functional postures. Thus, science and exploration during Artemis missions will likely involve a variety of standing, squatting, and kneeling postures. In preparation for future lunar exploration missions, NASA provides geologic training to astronauts and other mission personnel. This professional training with a spacesuit in simulated lunar environments will enhance performance and reduce risk of injury to astronauts on the lunar surface. However, anecdotally, untrained or newly trained people wearing prototype planetary spacesuits have been observed to performing motions differently than a trained geologist would when conducting the same geology sampling tasks. Therefore, a tool for evaluating geology postures at extravehicular activity (EVA) training facilities becomes required. In this paper, we introduce a novel inertial measurement unit (IMU)-based method of geology task assessments in spacesuited conditions during simulated lunar EVAs. As a case study, two subjects (one geologist and one non-geologist) participated and donned the Mark III prototype planetary spacesuit during offloading with the spreader bar gimbal in NASA’s Active Response Gravity Offload System (ARGOS). For automated geology task assessments, the spacesuit was instrumented with three wireless IMUs (APDM Opal, OR, USA): one on the chest and one each on the left and right ankle bearings. Then subjects performed geology tasks using various tools (rake, trench, hammer chisel, scoop, and drive tube) for 45 minutes each. The chest IMU measured the torso tilt angle in the sagittal plane. We used an ensemble learning method with the ankle IMUs to discriminate between standing and kneeling activities. IMU data were processed using custom MATLAB (Mathworks, MA, USA) software. In our case study, the developed method was able to discriminate differences in standing and kneeling activity levels between subjects who were all highly experienced with spacesuited testing. Our preliminary data showed one subject maintained the constant and lower range of the upper body tilt angle while both standing and kneeling, while the other subject showed more variation of the upper body tilt angle and preferred bending the upper body rather than changing from standing to kneeling posture and vice versa. While geology experience may be a factor, these results need further investigation as suit sizing and ARGOS offloading configurations have been proven to have a significant influence on suited ARGOS tasks. Also, more subjects will be needed to complete these tasks for validation. IMU-based geology task assessments can provide useful information for geology training programs. Additionally, our IMU-based posture analysis can provide new insights into how to evaluate spacesuited geology task characteristics of astronauts during simulated lunar EVAs.

Kyoung Jae Kim↗

NASA NTRS2023

Modeling and Simulation of the Angel Upper Limb Offload Device: Branching Into New Methods

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch of the Software, Robotics, and Simulation Division. Previously we have shared preliminary modeling of that device and kinematics based on motion capture data. Here we present an alternative approach to determine device kinematics by calculating ANGEL component angles with an OpenSim plugin. We compare calculated angles to inverse kinematics (IK) derived ones with the goal of validating the model. This new method can be further informative for device design and analytically testing different configurations to achieve desired reduced gravity conditions (e.g., lunar gravity (Lg) or Martian gravity (Mg)). We have compared calculated angles with IK-derived angles in tests with a shirt-sleeve subject positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup and arm weights to emulate the weight of the suit sleeve as well as a suited subject in ARGOS with a Mark-III suit. A variety of upper body tasks were completed in the former and full-body tasks in the latter. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. There are four ANGEL components with a total of 5 degrees of freedom (DOFs), each component has a single DOF except for the cuff which is modeled as 2 DOFs. The sickle/yaw bracket and cuff rotation angles are determined statically based on the assumptions that the sickle will track the attachment point of the cuff and that the cuff will rotate such that the attachment point is at its highest point. The cuff tilt, linker and V-bracket angles are then determined by optimizing their positions to approach a mechanical equilibrium. The calculated linker angle is compared to three different methods of determining the linker line-of-force kinematically (from V-bracket to center-cuff, cuff highest point or marker-derived position). Given the joint angles of the device, the spring force and resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data. The average difference in angles is the smallest for the V-bracket and linker, around 1 to 5 degrees for most trials. The resulting offload and shoulder torque are comparable between calculated and IK-derived angles. In summary, we have developed a method to calculate the joint angles of an exoskeleton-like upper limb offloading device currently in development. We have also developed a custom plugin which will be a valuable tool to optimize device configurations for a desired gravitational environment, probe the offload achieved for motions recorded outside of our test suite, and inform future design improvements.

L B Nilsson↗

NASA NTRS2023

Modeling and Simulation of The Angel Upper Limb Offload Device: Branching into New Methods

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch of the Software, Robotics, and Simulation Division. Previously we have shared preliminary modeling of that device and kinematics based on motion capture data. Here we present an alternative approach to determine device kinematics by calculating ANGEL component angles with an OpenSim plugin. We compare calculated angles to inverse kinematics (IK) derived ones with the goal of validating the model. This new method can be further informative for device design and analytically testing different configurations to achieve desired reduced gravity conditions (e.g., lunar gravity (Lg) or Martian gravity (Mg)). We have compared calculated angles with IK-derived angles in tests with a shirt-sleeve subject positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup and arm weights to emulate the weight of the suit sleeve as well as a suited subject in ARGOS with a Mark-III suit. A variety of upper body tasks were completed in the former and full-body tasks in the latter. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. There are four ANGEL components with a total of 5 degrees of freedom (DOFs), each component has a single DOF except for the cuff which is modeled as 2 DOFs. The sickle/yaw bracket and cuff rotation angles are determined statically based on the assumptions that the sickle will track the attachment point of the cuff and that the cuff will rotate such that the attachment point is at its highest point. The cuff tilt, linker and V-bracket angles are then determined by optimizing their positions to approach a mechanical equilibrium. The calculated linker angle is compared to three different methods of determining the linker line-of-force kinematically (from V-bracket to center-cuff, cuff highest point or marker-derived position). Given the joint angles of the device, the spring force and resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data. The average difference in angles is the smallest for the V-bracket and linker, around 1 to 5 degrees for most trials. The resulting offload and shoulder torque are comparable between calculated and IK-derived angles. In summary, we have developed a method to calculate the joint angles of an exoskeleton-like upper limb offloading device currently in development. We have also developed a custom plugin which will be a valuable tool to optimize device configurations for a desired gravitational environment, probe the offload achieved for motions recorded outside of our test suite, and inform future design improvements.

L B Nilsson↗

NASA NTRS1983

Satellite data relay and platform locating in oceanography. Report of the In Situ Ocean Science Working Group

The present and future use of satellites to locate offshore platforms and relay data from in situ sensors to shore was examined. A system of the ARGOS type will satisfy the increasing demand for oceanographic information through data relay and platform location. The improved ship navigation provided by the Global Positioning System (GPS) will allow direct observation of currents from underway ships. Ocean systems are described and demand estimates on satellite systems are determined. The capabilities of the ARGOS system is assessed, including anticipated demand in the next decade.

Chase, R.↗

NASA NTRS1986

A definition study of an Advanced Data Collection and Location System (ADCLS)

The technical and economic advantages of developing an Advanced Data Collection and Location System (ADCLS) to operate within the Earth Observation System (EOS) planned for Polar Platform, as a replacement and/or augmentation of the existing ARGOS data collection system were assessed. The cost/effectiveness of ADCLS with respect to ARGOS hinges on the traffic and quality of service demand of the future user constituency.

Source record↗

NASA NTRS1993

An LDEF 2 dust instrument for discrimination between orbital debris and natural particles in near-Earth space

The characteristics of a space dust instrument which would be ideally suited to carry out near-Earth dust measurements on a possible Long Duraction Exposure Facility reflight mission (LDEF 2) is discussed. As a model for the trajectory portion of the instrument proposed for LDEF 2, the characteristics of a SPAce DUSt instrument (SPADUS) currently under development for flight on the USA ARGOS mission to measure the flux, mass, velocity, and trajectory of near-Earth dust is summarized. Since natural (cosmic) dust and man-made dust particles (orbital debris) have different velocity and trajectory distributions, they are distinguished by means of the SPADUS velocity/trajectory information. The SPADUS measurements will cover the dust mass range approximately 5 x 10(exp -12) g (2 microns diameter) to approximately 1 x 10(exp -5) g (200 microns diameter), with an expected mean error in particle trajectory of approximately 7 deg (isotropic flux). Arrays of capture cell devices positioned behind the trajectory instrumentation would provide for Earth-based chemical and isotopic analysis of captured dust. The SPADUS measurement principles, characteristics, its role in the ARGOS mission, and its application to an LDEF 2 mission are summarized.

Tuzzolino, A. J.↗

NASA NTRS2009

Synthesis and Assimilation Systems - Essential Adjuncts to the Observing System

Assimilation systems synthesize diverse in-situ and satellite data streams into full four-dimensional state estimates by combining the strengths of each data set and also of the model. The resulting analysis provides an integrated view of the information in the various observations as well as derived estimates of unobserved quantities. Assimilation systems are particularly important for the ocean where subsurface observations, even today, are sparse and intermittent compared with the scales needed to represent ocean variability and where satellites only sense the surface. Increasingly, models and assimilation systems are being used to provide information about the current observing system and to help in the design plans for new observations. Whether it is as a user of observations or a contributor to evaluation of the observing system, ocean synthesis and assimilation systems are now an integral part of the global ocean observing and information system. Major advances have been made over the last decade under the auspices of WCRP's Climate Variability and Predictability Project (CLIVAR) and the Global Ocean Data Assimilation Experiment (GODAE). In addition to advances in the assimilation systems, there have been major developments in the observing system, with satellite altimetry, the tropical moored buoy arrays in the Pacific and Atlantic, and more recently Argo. These developments have led to significant advances in our understanding and prediction of ocean variations at both mesoscale and climate scales. Many challenges remain. Some of these challenges lie in the observations themselves, some in the assimilation systems that, even in the more recent era of unprecedented observations from satellite altimetry and Argo, provide different views of climate variations. Yet there are many examples of successful applications from ocean assimilation products. Use of these systems for assessing the observing system helps identify the strengths of each observation type, and indicates that none of the current observations is redundant. Indeed, the indication is that the ocean remains under-sampled and that further improvements in the observing system are needed for both climate monitoring and prediction. Future developments will be increasingly towards consistent analyses across components of the Earth system using, e.g., coupled atmosphere-ocean models.

Rienecker, Michele M.↗

NASA NTRS2010

The Impact of Ocean Observations in Seasonal Climate Prediction

The ocean provides the most significant memory for the climate system. Hence, a critical element in climate forecasting with coupled models is the initialization of the ocean with states from an ocean data assimilation system. Remotely-sensed ocean surface fields (e.g., sea surface topography, SST, winds) are now available for extensive periods and have been used to constrain ocean models to provide a record of climate variations. Since the ocean is virtually opaque to electromagnetic radiation, the assimilation of these satellite data is essential to extracting the maximum information content. More recently, the Argo drifters have provided unprecedented sampling of the subsurface temperature and salinity. Although the duration of this observation set has been too short to provide solid statistical evidence of its impact, there are indications that Argo improves the forecast skill of coupled systems. This presentation will address the impact these different observations have had on seasonal climate predictions with the GMAO's coupled model.

Rienecker, Michele↗

NASA NTRS2010

2009 Goose Bay Experiment Ocean Measurements: Data - Part 1

During late February and early March 2009, a field experiment was performed using the NASA P3 over the Labrador Sea. During this experiment, expendable probes deployed from the aircraft acquired ocean mixed layer temperature, salinity and currents Probes were deployed during three flights of the four. Overall 7 AXBTs, 15 AXCTDs and 7 AXCPs were deployed with a success rate of nearly 70%. This is much lower than expected based on prior experience deploying from other aircraft. But given the difficulties associated with the Pneumatic Sonobuoy Launch Tube mechanism on the NASA P3, this rate likely can be improved significantly by using a different deployment mechanism. Additionally, two sets of collocated measurements of AXBTs, AXCPs and AXCTDs were made to verify the drop rates and measurements of the old AXBTs. While there were differences in the measurements, the old AXCTDs are performing well. The expendable data from the experiment are compared to the Argo profiles in the region to check for consistency. Comparisons indicate all the expendable probes acquired useful data and are well within the range of values measured by Argo floats.

Jacob, S. Daniel↗

NASA NTRS2012

The GEOS-iODAS: Description and Evaluation

This report documents the GMAO's Goddard Earth Observing System sea ice and ocean data assimilation systems (GEOS iODAS) and their evolution from the first reanalysis test, through the implementation that was used to initialize the GMAO decadal forecasts, and to the current system that is used to initialize the GMAO seasonal forecasts. The iODAS assimilates a wide range of observations into the ocean and sea ice components: in-situ temperature and salinity profiles, sea level anomalies from satellite altimetry, analyzed SST, and sea-ice concentration. The climatological sea surface salinity is used to constrain the surface salinity prior to the Argo years. Climatological temperature and salinity gridded data sets from the 2009 version of the World Ocean Atlas (WOA09) are used to help constrain the analysis in data sparse areas. The latest analysis, GEOS ODAS5.2, is diagnosed through detailed studies of the statistics of the innovations and analysis departures, comparisons with independent data, and integrated values such as volume transport. Finally, the climatologies of temperature and salinity fields from the Argo era, 2002-2011, are presented and compared with the WOA09.

Climate↗

NASA NTRS2014

Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data Assimilation

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Error Covariance↗

NASA NTRS2014

The Impact of the Assimilation of Aquarius Sea Surface Salinity Data in the GEOS Ocean Data Assimilation System

Ocean salinity and temperature differences drive thermohaline circulations. These properties also play a key role in the ocean-atmosphere coupling. With the availability of L-band space-borne observations, it becomes possible to provide global scale sea surface salinity (SSS) distribution. This study analyzes globally the along-track (Level 2) Aquarius SSS retrievals obtained using both passive and active L-band observations. Aquarius alongtrack retrieved SSS are assimilated into the ocean data assimilation component of Version 5 of the Goddard Earth Observing System (GEOS-5) assimilation and forecast model. We present a methodology to correct the large biases and errors apparent in Version 2.0 of the Aquarius SSS retrieval algorithm and map the observed Aquarius SSS retrieval into the ocean models bulk salinity in the topmost layer. The impact of the assimilation of the corrected SSS on the salinity analysis is evaluated by comparisons with insitu salinity observations from Argo. The results show a significant reduction of the global biases and RMS of observations-minus-forecast differences at in-situ locations. The most striking results are found in the tropics and southern latitudes. Our results highlight the complementary role and problems that arise during the assimilation of salinity information from in-situ (Argo) and space-borne surface (SSS) observations

Salinty↗