Search NASA⌕ Search

SEARCH · Search NASA

Results for “Dynamic State Estimation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Human impacts on soil carbon dynamics of deep-rooted Amazonian forests

Deforestation and logging degrade more forest in eastern and southern Amazonia than in any other region of the world. This forest alteration affects regional hydrology and the global carbon cycle, but our current understanding of these effects is limited by incomplete knowledge of tropical forest ecosystems. It is widely agreed that roots are concentrated near the soil surface in moist tropical forests, but this generalization incorrectly implies that deep roots are unimportant in water and C budgets. Our results indicate that half of the closed-canopy forests of Brazilian Amazonic occur where rainfall is highly seasonal, and these forests rely on deeply penetrating roots to extract soil water. Pasture vegetation extracts less water from deep soil than the forest it replaces, thus increasing rates of drainage and decreasing rates of evapotranspiration. Deep roots are also a source of modern carbon deep in the soil. The soils of the eastern Amazon contain more carbon below 1 m depth than is present in above-ground biomass. As much as 25 percent of this deep soil C could have annual to decadal turnover times and may be lost to the atmosphere following deforestation. We compared the importance of deep roots in a mature, evergreen forest with an adjacent man-made pasture, the most common type of vegetation on deforested land in Amazonia. The study site is near the town of Paragominas, in the Brazilian state of Para, with a seasonal rainfall pattern and deeply-weathered, kaolinitic soils that are typical for large portions of Amazonia. Root distribution, soil water extraction, and soil carbon dynamics were studied using deep auger holes and shafts in each ecosystem, and the phenology and water status of the leaf canopies were measured. We estimated the geographical distribution of deeply-rooting forests using satellite imagery, rainfall data, and field measurements.

Nepstad, Daniel C.↗
NASA NTRS1994

Storage and recycling of water and carbon dioxide in the earth

The stabilities and properties of water- and carbon-bearing phases in the earth have been determined from phase equilibrium measurements, combined with new data on the equations of state of water, carbon dioxide, carbonates and hydrates. The data have then been used to predict the fate of calcite and hydrous phases in subducting oceanic lithosphere. From the compositions of MORB's one can estimate concentrations of water and carbon of around 200 ppm and 80 ppm respectively in the upper mantle. Lower mantle estimates are very uncertain, but 1900 ppm water and 2000 ppm C are plausible concentrations. Measurements of the density of supercritical water to 3 GPa demonstrate that this phase is less compressible than anticipated from the equations of state of Haar et al. or Saul and Wagner and is closer to predictions based on molecular dynamics simulations. Conversely, fugacity measurements on carbon dioxide to 7 GPa show that this fluid is more compressible than predicted from the MRK equation of state. The results imply that hydrates are relatively more stable and carbonates less stable at pressures greater than 5 GPa than would be predicted from simple extrapolation of the low pressure data. Nevertheless, carbonates remain extremely refractory phases within both the upper and lower mantle.

Wood, Bernard J.↗
NASA NTRS2004

Gravitational Effects of Flooding and Filling of Impact Basins on Mars

The presence of large impact basins and the low northern plains that might have contained ice or liquid water at an earlier stage of Mars evolution suggests that the global gravity field could have been different in the distant past than it is today. In addition, any significant change in the distribution of mass affects the moments of inertia and consequently and could conceivably change the position of the pole and the length of day. Similar effects could have been produced by large erosional processes, such as the removal of crustal material from the Arabia Terra region and subsequent re-deposition in the Chryse region of the northern plains. We have endeavored to estimate the magnitudes of material that might have been involved in these processes and their possible effect on the gravity and dynamics of Mars. We have used present-day topography and gravity field as a starting point, recognizing that both the result of the processes that we are trying to study rather than the state at the times of interest.

Smith, David E.↗
NASA NTRS2019

Uncertainty in Soil Moisture Retrievals: an Ensemble Approach Using SMOS L-Band Microwave Data

The uncertainty of soil moisture (SM) retrievals from satellite brightness temperature (TB) observations depends primarily on the choice of radiative transfer model (RTM) parameters, prior SM information and TB inputs. This paper studies the sensitivity of several (quasi-)operational and experimental SM retrieval products from the Soil Moisture Ocean Salinity (SMOS) mission to these choices at 11 reference sites, located in 7 watersheds across the United States (US). Different literature-based RTM parameter sets cause large biases between retrievals. Whereas typical RTM parameter sets are calibrated for SM retrievals, it is shown that a parameter set carefully optimized for TB forward modeling can also be used for retrieving SM. It is also shown that the inclusion of dynamic prior SM estimates in a Bayesian retrieval scheme can strongly improve SM retrievals, regardless of the choice of RTM parameters, and that the use of multi-angular and multi-polarization TB does not necessarily lead to superior retrievals compared to retrievals based on TB data at a single incidence angle and polarization. The second part of this paper evaluates ensemble uncertainty metrics for SM retrievals obtained by propagating a wide range of RTM parameters through the RTM. As expected for bounded variables, the spread in the ensemble SM retrievals is smallest for wet and dry SM values and highest for intermediate SM values. After removal of the strong long-term mean bias associated with the RTM parameter values for individual ensemble members, the remaining anomaly ensemble SM spread of 0.037 cu m/cu m approximates the actual time series unbiased root-mean-square-difference of 0.042 cu m/cu m between ensemble mean retrievals and in situ reference data across the reference sites. However, the temporal variability in the anomaly ensemble spread reveals higher-order biases in the retrieval error, which should be accounted for when characterizing retrieval error.

Jan Quets↗
NASA NTRS2019

Real-Time UAV Trajectory Prediction for Safety Monitoring in Low-Altitude Airspace

The rising number of small unmanned aerial vehicles (UAVs) expected in the next decade will enable a new series of commercial, service, and military operations in low altitude airspace as well as above densely populated areas. These operations may include on-demand delivery, medical transportation services, law enforcement operations, traffic surveillance and many more. Such unprecedented scenarios create the need for robust, efficient ways to monitor the UAV state in time to guarantee safety and mitigate contingencies throughout the operations. This work proposes a generalized monitoring and prediction methodology that utilizes realtime measurements of an autonomous UAV following a series of way-points. Two different methods, based on sinusoidal acceleration profiles and high-order splines, are utilized to generate the predicted path. The monitoring approach includes dynamic trajectory re-planning in the event of unexpected detour or hovering of the UAV during flight. It can be further extended to different vehicle types, to quantify uncertainty affecting the state variables, e.g., aerodynamic and other environmental effects, and can also be implemented to prognosticate safety-critical metrics which depend on the estimated flight path and required thrust. The proposed framework is implemented on a simplified, scalable UAV modeling and control system traversing 3D trajectories. Results presented include examples of real-time predictions of the UAV trajectories during flight and a critical analysis of the proposed scenarios under uncertainty constraints.

UAV trajectory prognosis↗
NASA NTRSDate not supplied

Aeroelastic Simulation of Transonic Truss-Braced Wing Aircraft for Flight Dynamic Stability Analysis

This paper presents aeroelastic simulation of the Mach 0.8 Transonic Truss-Braced Wing (TTBW) aeroelastic model using CFD solver FUN3D for the flight dynamic and control stability analysis. A jig twist optimization is performed to obtain a flight optimized jig twist for the flexible Mach 0.8 TTBW model. The developed aeroelastic model steady-state stability derivatives with respect to the angle of attack, angle of sideslip, and airspeed are calculated with perturbations in the angle of attack, angle of sideslip, and Mach number, respectively. A series of unsteady simulations is conducted for the developed aeroelastic model in pitch oscillation at various reduced frequencies. The dynamic stability derivatives are estimated using a frequency domain estimation method. The control derivatives of the elevator, rudder, and ailerons of the developed aeroelastic model are estimated for control stability analysis.

TTBW↗
NASA NTRS2012

Carbon Consequences of Forest Disturbance and Recovery Across the Conterminous United States

Forests of North America are thought to constitute a significant long term sink for atmospheric carbon. The United States Forest Service Forest Inventory and Analysis (FIA) program has developed a large data base of stock changes derived from consecutive estimates of growing stock volume in the US. These data reveal a large and relatively stable increase in forest carbon stocks over the last two decades or more. The mechanisms underlying this national increase in forest stocks may include recovery of forests from past disturbances, net increases in forest area, and growth enhancement driven by climate or fertilization by CO2 and Nitrogen. Here we estimate the forest recovery component of the observed stock changes using FIA data on the age structure of US forests and carbon stocks as a function of age. The latter are used to parameterize forest disturbance and recovery processes in a carbon cycle model. We then apply resulting disturbance/recovery dynamics to landscapes and regions based on the forest age distributions. The analysis centers on 28 representative climate settings spread about forested regions of the conterminous US. We estimate carbon fluxes for each region and propagate uncertainties in calibration data through to the predicted fluxes. The largest recovery-driven carbon sinks are found in the South central, Pacific Northwest, and Pacific Southwest regions, with spatially averaged net ecosystem productivity (NEP) of about 100 g C / square m / a driven by forest age structure. Carbon sinks from recovery in the Northeast and Northern Lake States remain moderate to large owing to the legacy of historical clearing and relatively low modern disturbance rates from harvest and fire. At the continental scale, we find a conterminous U.S. forest NEP of only 0.16 Pg C/a from age structure in 2005, or only 0.047 Pg C/a of forest stock change after accounting for fire emissions and harvest transfers. Recent estimates of NEP derived from inventory stock change, harvest, and fire data show twice the NEP sink we derive from forest age distributions. We discuss possible reasons for the discrepancies including modeling errors and the possibility of climate and/or fertilization (CO2 or N) growth enhancements.

Williams, Christopher A.↗
NASA NTRS1998

The High Stability Engine Control (HISTEC) Program: Flight Demonstration Phase

Future aircraft turbine engines, both commercial and military, must be able to accommodate expected increased levels of steady-state and dynamic engine-face distortion. The current approach of incorporating sufficient design stall margin to tolerate these increased levels of distortion would significantly reduce performance. The objective of the High Stability Engine Control (HISTEC) program is to design, develop, and flight-demonstrate an advanced, integrated engine control system that uses measurement-based estimates of distortion to enhance engine stability. The resulting distortion tolerant control reduces the required design stall margin, with a corresponding increase in performance and decrease in fuel burn. The HISTEC concept has been developed and was successfully flight demonstrated on the F-15 ACTIVE aircraft during the summer of 1997. The flight demonstration was planned and carried out in two phases, the first to show distortion estimation, and the second to show distortion accommodation. Post-flight analysis shows that the HISTEC technologies are able to successfully estimate and accommodate distortion, transiently setting the stall margin requirement on-line and in real-time. This allows the design stall margin requirement to be reduced, which in turn can be traded for significantly increased performance and/or decreased weight. Flight demonstration of the HISTEC technologies has significantly reduced the risk of transitioning the technology to tactical and commercial engines.

DeLaat, John C.↗
NASA NTRS1977

Lunar gravity - A long-term Keplerian rate method

Nearside tracking data from Apollo subsatellites and Lunar Orbiter 5 are used to construct a model of the farside lunar gravity field. An indirect method of calculating the average effect of all the gravity anomalies which affect spacecraft orbits is reduced to a linear estimation problem by eliminating the integration of spacecraft dynamics. Doppler frequency shifts between the lunar satellite and earth-based tracking station are used to measure the line of sight velocity component between the orbiter and the tracker; gravity determination is then performed in a weighted least squares estimator which employs the orbital rates as data and formulates the normal equations using the associated Keplerian state. Simulations performed demonstrate that farside gravity features can be economically determined by use of gravity estimates obtained from long-period models of nearside orbiting tracks.

Ferrari, A. J.↗
NASA NTRS1994

State-space self-tuner for on-line adaptive control

Dynamic systems, such as flight vehicles, satellites and space stations, operating in real environments, constantly face parameter and/or structural variations owing to nonlinear behavior of actuators, failure of sensors, changes in operating conditions, disturbances acting on the system, etc. In the past three decades, adaptive control has been shown to be effective in dealing with dynamic systems in the presence of parameter uncertainties, structural perturbations, random disturbances and environmental variations. Among the existing adaptive control methodologies, the state-space self-tuning control methods, initially proposed by us, are shown to be effective in designing advanced adaptive controllers for multivariable systems. In our approaches, we have embedded the standard Kalman state-estimation algorithm into an online parameter estimation algorithm. Thus, the advanced state-feedback controllers can be easily established for digital adaptive control of continuous-time stochastic multivariable systems. A state-space self-tuner for a general multivariable stochastic system has been developed and successfully applied to the space station for on-line adaptive control. Also, a technique for multistage design of an optimal momentum management controller for the space station has been developed and reported in. Moreover, we have successfully developed various digital redesign techniques which can convert a continuous-time controller to an equivalent digital controller. As a result, the expensive and unreliable continuous-time controller can be implemented using low-cost and high performance microprocessors. Recently, we have developed a new hybrid state-space self tuner using a new dual-rate sampling scheme for on-line adaptive control of continuous-time uncertain systems.

Shieh, L. S.↗
NASA NTRSDate not supplied

Ensemble Forecasting/Assimilation/Emissions Estimation with WRF-Chem/DART: Accomplishments, Lessons Learned, and Future Plans

Over the past ten years, we have been conducting research on regional ensemble atmospheric composition forecasting/data assimilation/emissions estimation with WRF-Chem/DART. WRF- Chem/DART integrates the Weather Research and Forecasting model (WRF) with online chemistry (WRF-Chem) into the Data Assimilation Research Testbed (DART). DART is an ensemble data assimilation system based on the ensemble adjustment Kalman filter (EAKF) with adaptive inflation, localization (physical and state space), and an optional non-Gaussian formulation of the EAKF. DART includes assimilation of meteorological and limited chemical observations. WRF-Chem/DART extends DART to include assimilation of: MOPITT CO; IASI CO and O3; MODIS AOD; OMI O3, NO2, and SO2; TROPOMI CO, O3, NO2, and SO2, TES CO, CO2 (research mode), O3, NH3, and CH4 (research mode); CrIS CO, O3, NH3, CH4 (research mode), and PAN; SCIAMACHY NO2; GOME2a NO2; MLS O3 and HNO3; and proxy TEMPO O3, and NO2 satellite retrievals as raw retrievals or as ‘compact phase space retrievals’ (CPSRs) for profile retrievals. WRF-Chem/DART also assimilates in situ atmospheric composition measurements and uses the ‘state augmentation method’ for emissions estimation. In our presentation, we will provide an overview of WRF-Chem/DART: • applications and results; • lessons learned from: (i) independent versus joint assimilation; (ii) total/partial column versus profile retrieval assimilation; (iii) joint in situ and retrieval assimilation; (iv) assimilation at grid resolutions ranging from 100 km to 4 km; (v) dynamic emissions estimation; and • future work related to wildfire emissions estimation and intercomparison of CMAQ (online)/JEDI and CMAQ (online and offline)/DART.

WRF-Chem/DART↗
NASA NTRSDate not supplied

Strategy for Risk Quantification of Spaceflight Crew Health and Performance Using Dynamic Probabilistic Risk Assessment

At NASA, the Crew Health and Performance (CHP) system represents the span of countermeasures, capabilities, interventions, and tested processes and procedures that in combination work to mitigate the human component of spaceflight mission risk. Across the varying NASA mental models of the CHP system, the different functionalities needed to meet human flight systems standards can be broken down into specific categories (i.e. medical capability, environmental health, behavioral health). These categories can be further broken down into specific subgroups generally associated with the CHP functionalities meant to mitigate or buy down individual human system risks. Taking a similar development approach we seek to leverage dynamic probabilistic risk assessment as a means to quantify and relatively assess the human risk state within the crew health and performance domain. By utilizing existing tools as integrators, we propose a rapid development strategy for incorporating research and operational data that represent the influence of the CHP system functionalities, in order to provide order of magnitudes estimates of the influence on most human system risks outcomes. The model system utilizes a modest cumulative risk approach and that limits the scope to primary paths of influence between the CHP functionalities and human system risks, thus enabling quick prototypes of the integrative effects of CHP functional combinations to solicit valuable feedback from stakeholders and customers on the data, relationship, and structure of the integration.

Drayton Munster↗
NASA NTRS1995

Use of nonlinear identification in robust attitude and attitude rate estimation for SAMPEX

A method is described for obtaining optimal attitude estimation/identification algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. The absence of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. In addition, attitude data is occasionally unavailable (for example, during sun occultation). As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is an increased need for accurate models of the rotational dynamics. The Minimum Model Error(MME)/Least Square Correlation(LSC) algorithm accurately identifies an improved model for SAMPEX to be used during periods of complete data loss or extreme noise. The model correction is determined by estimating only one orbit(the identification pass) just prior to the assumed data loss(the prediction pass). The MME estimator correctly predicted the states during the identification phase, but more importantly determines the necessary model correction trajectory, d(t). The LSC algorithm is then used to find this trajectory's functional form, H(x(t)). The results show significant improvement of the new corrected model's attitude estimates as compared to the original uncorrected model's estimates. The possible functional form of the correction term is limited at this point in the study to functions strictly of the estimated states. The results, however, strongly suggest that functions based on the relative position of the satellite may also be possible candidates for future consideration.

Mook, D. Joseph↗
NASA NTRS1998

Use of microgravity sensors for quantification of space shuttle orbiter vernier reaction control system induced environments

In the modeling of spacecraft dynamics it is important to accurately characterize the environment in which the vehicle operates, including the environments induced by the vehicle itself. On the Space Shuttle these induced environmental factors include reaction control system plume. Knowledge of these environments is necessary for performance of control systems and loads analyses, estimation of disturbances due to thruster firings, and accurate state vector propagation. During the STS-71 mission, while the Orbiter was performing attitude control for the mated Orbiter/Mir stack, it was noted that the autopilot was limit cycling at a rate higher than expected from pre-flight simulations. Investigations during the mission resulted in the conjecture that an unmodelled plume impingement force was acting upon the orbiter elevons. The in-flight investigations were not successful in determining the actual magnitude of the impingement, resulting in several sequential post-flight investigations. Efforts performed to better quantify the vernier reaction control system induced plume impingement environment of the Space Shuttle orbiter are described in this paper, and background detailing circumstances which required the more detailed knowledge of the RCS self impingement forces, as well as a description of the resulting investigations and their results is presented. The investigations described in this paper applied microgravity acceleration data from two shuttle borne microgravity experiments, SAMS and OARE, to the solution of this particular problem. This solution, now used by shuttle analysts and mission planners, results in more accurate propellant consumption and attitude limit cycle estimates in preflight analyses, which are critical for pending International Space Station missions.

Friend, Robert B.↗
NASA NTRS2017

Resolution of Orbit Determination Prediction Instabilities at Titan During Cassini's Solstice Mission

The Cassini spacecraft has been in orbit about Saturn since 2004. Exploration of the Saturn system is driven by gravitational flybys of the moon Titan which alter the spacecraft trajectory. The Cassini Navigation Team receives regular updates to the Saturn satellites ephemeris from JPL's Solar System Dynamics group. The difference between subsequent ephemeris deliveries can be hundreds of meters in the position of Titan at the time of a flyby. Errors in Titan's position propagate downstream to the next flyby through the estimated spacecraft trajectory. Prior to 2013, the Cassini Orbit Determination Team estimated the Saturn satellite ephemeris parameters and used the a posteriori states and covariance of an operations arc as a priori inputs to subsequent estimation arcs. Since 2013, the OD Team has only been considering errors in the ephemeris and not estimating a correction to the satellite positions. The T119 Titan flyby exhibited a 3D miss distance of 2.44 km and the following T120 flyby yielded a smaller miss of 1.06 km at the 2.9s error level. These discrepancies between pre-flyby prediction and post-flyby trajectory reconstruction were due to errors in the Titan ephemeris. In order to improve the targeting of Titan in future flybys, the team restarted the satellite ephemeris estimation process for orbit determination solutions. Subsequent flybys had target misses of less than 1 km at the sub-3 error level. This paper describes the method of scaling the a priori satellite ephemeris covariance in the orbit determination process to allow larger corrections to the satellite system and improve the prediction of the spacecraft’s Titan-relative position at the time of encounters.

Boone, Dylan↗
NASA NTRS2003

Assessing Impacts of Global Warming on Tropical Cyclone Tracks

A new approach is proposed to assess the possible impacts of the global climate change on tropical cyclone (TC) tracks in the western North Pacific (WNP) basin. The idea is based on the premise that the future change of TC track characteristics is primarily determined by changes in large-scale environmental steering flows. It is demonstrated that the main characteristics of the current climatology of TC tracks can be derived from the climatological mean velocity field of TC motion by using a trajectory model. The climatological mean velocity of TC motion, which is composed of the large-scale steering and beta drift, is determined on each grid of the basin. The mean beta drift is estimated from the best track data, and the mean large-scale steering flow is computed from the NCEP/NCAR reanalysis for the current climate state. The derived mean beta drift agrees well with the results of previous observational and numerical studies in terms of its direction and magnitude. The outputs of experiments A2 and B2 of the Geophysical Fluid Dynamics Laboratory (GFDL) R30 climate model suggest that the subtropical high will be persistently weak over the western part of the WNP or shift eastward during July-September in response to the future climate change. By assuming that the mean beta drift in the future climate state is unchanged, the change in the general circulation by 2059 will decrease the TC activities in the WNP, but favor a northward shift of typical TC tracks. As a result, the storm activities in the South China Sea will decrease by about 12%, while the Japan region will experience an increase of TCs by 12-15%. During the period of 2000-2029, the tropical storms that affect the China region will increase by 5-6%, but return to the current level during 2030-2059. It is also suggested that, during the period of 2030-2059 tropical storms will more frequently affect Japan and the middle latitude region of China given that the formation locations remain the same as in the current climate state.

Wu, Li-Guang↗
NASA NTRS2009

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

Peters-Lidard, Christa D.↗
NASA NTRS2014

Use of an OSSE to Evaluate Background Error Covariances Estimated by the 'NMC Method'

The NMC method has proven utility for prescribing approximate background-error covariances required by variational data assimilation systems. Here, untunedNMCmethod estimates are compared with explicitly determined error covariances produced within an OSSE context by exploiting availability of the true simulated states. Such a comparison provides insights into what kind of rescaling is required to render the NMC method estimates usable. It is shown that rescaling of variances and directional correlation lengths depends greatly on both pressure and latitude. In particular, some scaling coefficients appropriate in the Tropics are the reciprocal of those in the Extratropics. Also, the degree of dynamic balance is grossly overestimated by the NMC method. These results agree with previous examinations of the NMC method which used ensembles as an alternative for estimating background-error statistics.

Data Assimilation↗