Results for “improvement” — Page 28

NASA NTRS2012

Advanced Model for Extreme Lift and Improved Aeroacoustics (AMELIA)

With the very recent advent of NASA's Environmentally Responsible Aviation Project (ERA), which is dedicated to designing aircraft that will reduce the impact of aviation on the environment, there is a need for research and development of methodologies to minimize fuel burn, emissions, and reduce community noise produced by regional airliners. ERA tackles airframe technology, propulsion technology, and vehicle systems integration to meet performance objectives in the time frame for the aircraft to be at a Technology Readiness Level (TRL) of 4-6 by the year of 2020 (deemed N+2). The proceeding project that investigated similar goals to ERA was NASA's Subsonic Fixed Wing (SFW). SFW focused on conducting research to improve prediction methods and technologies that will produce lower noise, lower emissions, and higher performing subsonic aircraft for the Next Generation Air Transportation System. The work provided in this investigation was a NASA Research Announcement (NRA) contract #NNL07AA55C funded by Subsonic Fixed Wing. The project started in 2007 with a specific goal of conducting a large-scale wind tunnel test along with the development of new and improved predictive codes for the advanced powered-lift concepts. Many of the predictive codes were incorporated to refine the wind tunnel model outer mold line design. The large scale wind tunnel test goal was to investigate powered lift technologies and provide an experimental database to validate current and future modeling techniques. Powered-lift concepts investigated were Circulation Control (CC) wing in conjunction with over-the-wing mounted engines to entrain the exhaust to further increase the lift generated by CC technologies alone. The NRA was a five-year effort; during the first year the objective was to select and refine CESTOL concepts and then to complete a preliminary design of a large-scale wind tunnel model for the large scale test. During the second, third, and fourth years the large-scale wind tunnel model design would be completed, manufactured, and calibrated. During the fifth year the large scale wind tunnel test was conducted. This technical memo will describe all phases of the Advanced Model for Extreme Lift and Improved Aeroacoustics (AMELIA) project and provide a brief summary of the background and modeling efforts involved in the NRA. The conceptual designs considered for this project and the decision process for the selected configuration adapted for a wind tunnel model will be briefly discussed. The internal configuration of AMELIA, and the internal measurements chosen in order to satisfy the requirements of obtaining a database of experimental data to be used for future computational model validations. The external experimental techniques that were employed during the test, along with the large-scale wind tunnel test facility are covered in great detail. Experimental measurements in the database include forces and moments, and surface pressure distributions, local skin friction measurements, boundary and shear layer velocity profiles, far-field acoustic data and noise signatures from turbofan propulsion simulators. Results and discussion of the circulation control performance, over-the-wing mounted engines, and the combined performance are also discussed in great detail.

Subsonic Fixed Wing↗

NASA NTRS2016

Improved ASTM G72 Test Method for Ensuring Adequate Fuel-to-Oxidizer Ratios

The ASTM G72/G72M-15 Standard Test Method for Autogenous Ignition Temperature of Liquids and Solids in a High-Pressure Oxygen-Enriched Environment is currently used to evaluate materials for the ignition susceptibility driven by exposure to external heat in an enriched oxygen environment. Testing performed on highly volatile liquids such as cleaning solvents has proven problematic due to inconsistent test results (non-ignitions). Non-ignition results can be misinterpreted as favorable oxygen compatibility, although they are more likely associated with inadequate fuel-to-oxidizer ratios. Forced evaporation during purging and inadequate sample size were identified as two potential causes for inadequate available sample material during testing. In an effort to maintain adequate fuel-to-oxidizer ratios within the reaction vessel during test, several parameters were considered, including sample size, pretest sample chilling, pretest purging, and test pressure. Tests on a variety of solvents exhibiting a range of volatilities are presented in this paper. A proposed improvement to the standard test protocol as a result of this evaluation is also presented. Execution of the final proposed improved test protocol outlines an incremental step method of determining optimal conditions using increased sample sizes while considering test system safety limits. The proposed improved test method increases confidence in results obtained by utilizing the ASTM G72 autogenous ignition temperature test method and can aid in the oxygen compatibility assessment of highly volatile liquids and other conditions that may lead to false non-ignition results.

Juarez, Alfredo↗

NASA NTRS2016

The Business Change Initiative: A Novel Approach to Improved Cost and Schedule Management

Goddard Space Flight Center's Flight Projects Directorate employed a Business Change Initiative (BCI) to infuse a series of activities coordinated to drive improved cost and schedule performance across Goddard's missions. This sustaining change framework provides a platform to manage and implement cost and schedule control techniques throughout the project portfolio. The BCI concluded in December 2014, deploying over 100 cost and schedule management changes including best practices, tools, methods, training, and knowledge sharing. The new business approach has driven the portfolio to improved programmatic performance. The last eight launched GSFC missions have optimized cost, schedule, and technical performance on a sustained basis to deliver on time and within budget, returning funds in many cases. While not every future mission will boast such strong performance, improved cost and schedule tools, management practices, and ongoing comprehensive evaluations of program planning and control methods to refine and implement best practices will continue to provide a framework for sustained performance. This paper will describe the tools, techniques, and processes developed during the BCI and the utilization of collaborative content management tools to disseminate project planning and control techniques to ensure continuous collaboration and optimization of cost and schedule management in the future.

Schedule↗

NASA NTRS2016

Improved ASTM G72 Test Method for Ensuring Adequate Fuel-to-Oxidizer Ratios

The ASTM G72/G72M-15 Standard Test Method for Autogenous Ignition Temperature of Liquids and Solids in a High-Pressure Oxygen-Enriched Environment is currently used to evaluate materials for the ignition susceptibility driven by exposure to external heat in an enriched oxygen environment. Testing performed on highly volatile liquids such as cleaning solvents has proven problematic due to inconsistent test results (non-ignitions). Non-ignition results can be misinterpreted as favorable oxygen compatibility, although they are more likely associated with inadequate fuel-to-oxidizer ratios. Forced evaporation during purging and inadequate sample size were identified as two potential causes for inadequate available sample material during testing. In an effort to maintain adequate fuel-to-oxidizer ratios within the reaction vessel during test, several parameters were considered, including sample size, pretest sample chilling, pretest purging, and test pressure. Tests on a variety of solvents exhibiting a range of volatilities are presented in this paper. A proposed improvement to the standard test protocol as a result of this evaluation is also presented. Execution of the final proposed improved test protocol outlines an incremental step method of determining optimal conditions using increased sample sizes while considering test system safety limits. The proposed improved test method increases confidence in results obtained by utilizing the ASTM G72 autogenous ignition temperature test method and can aid in the oxygen compatibility assessment of highly volatile liquids and other conditions that may lead to false non-ignition results.

Juarez, Alfredo↗

NASA NTRS2015

Improvements to the Tendon-Actuated Lightweight In-Space MANipulator (TALISMAN)

Devices for manipulating and precisely placing payloads are critical for efficient space operations including berthing of spacecraft, in-space assembly, construction and repair. Key to the success of many NASA space activities has been the availability of long-reach crane-like devices such as the Shuttle Remote Manipulation System (SRMS) and the Space Station Remote Manipulation System (SSRMS). These devices have been used for many operations including berthing visiting spacecraft to the International Space Station, deployment of spacecraft, space station assembly, astronaut positioning, payload transfer, and spacecraft inspection prior to atmospheric re-entry. Retiring the Space Transportation System has led to the removal of the SRMS from consideration for in-space missions, thus creating a capability gap. Recognizing this gap, work was initiated at NASA on a new architecture for long-reach space manipulators. Most current devices are constructed by joining revolute joints with carbon composite tubes, with the joints accounting for the majority of the device mass. For example in the case of the SRMS, the entire device mass is 410 kg (904 lbm); the joint structure, motors, gear train, cabling, etc., accounts for the majority of the system mass because the carbon composite tubes mass is 46 kg (101 lbm). An alternate space manipulator concept, the Tendon-Actuated Lightweight In-Space MANipulator (TALISMAN) was created to address deficiencies in the current state-of-the-art in long-reach manipulators. The antagonistic tendon actuated joint architecture allows the motors actuating the joint to be removed from the joint axis, which simplifies the joint design while simultaneously providing mechanical advantage for the motors. The improved mechanical advantage, in turn, reduces the size and power requirements for the motor and gear train. This paper will describe recent architectural improvements to the TALISMAN design that: 1) improve the operational robustness of the system by enabling maneuvers not originally possible by varying the TALISMAN geometry; 2) enable efficient active antagonistic control of a joint while sharing cable between antagonistic tension networks; and 3) uses a unique arrangement of differential capstans to reduce motor torque requirements by an order of magnitude. The paper will also summarize recent efforts to enable autonomous deployment of a TALISMAN including the deployment concept of operations and associated hardware system design. The deployment forces are provided by the same motor systems that are used for articulation, thus reducing the mass associated with the deployment system. The deployment approach is being tested on a TALISMAN prototype which is designed to provide the same operational performance as a shuttle-class manipulator. The prototype has been fabricated and is operational in a new facility at NASA Langley Research Center that has a large area (15.2 m by 21.3 m [50 ft by 70 ft]) air-bearing floor.

Doggett, William R.↗

NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗

NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗

NASA NTRS2015

Mach Stability Improvements Using an Existing Second Throat Capability at the National Transonic Facility

Recent data quality improvements at the National Transonic Facility (NTF) have an intended goal of reducing the Mach number variation in a data point to within unit vector A plus or minus 0.0005, with the ultimate goal of reducing the data repeatability of the drag coefficient for full-span subsonic transport models at transonic speeds to within half of a drag count. This paper will discuss the Mach stability improvements achieved through the use of an existing second throat capability at the NTF to create a minimum area at the end of the test section. These improvements were demonstrated using both the NASA Common Research Model and the NTF Pathfinder-I model in recent experiments. Sonic conditions at the throat were verified using sidewall static pressure data. The Mach variation levels from both experiments in the baseline tunnel configuration and the choked tunnel configuration will be presented. Finally, a brief discussion is given on the consequences of using the second throat in its location at the end of the test section.

Chan, David T.↗

NASA NTRS2016

Improving 7-Day Forecast Skill by Assimilation of Retrieved AIRS Temperature Profiles

We conducted a new set of Data Assimilation Experiments covering the period January 1 to February 29, 2016 using the GEOS-5 DAS. Our experiments assimilate all data used operationally by GMAO (Control) with some modifications. Significant improvement in Global and Southern Hemisphere Extra-tropical 7-day forecast skill was obtained when: We assimilated AIRS Quality Controlled temperature profiles in place of observed AIRS radiances, and also did not assimilate CrISATMS radiances, nor did we assimilate radiosonde temperature profiles or aircraft temperatures. This new methodology did not improve or degrade 7-day Northern Hemispheric Extra-tropical forecast skill. We are conducting experiments aimed at further improving of Northern Hemisphere Extra-tropical forecast skill.

AIRS Temperature Profiles↗

NASA NTRS2016

A Method for Improving Hotspot Directional Signatures in BRDF Models Used for MODIS

The semi-empirical, kernel-driven, linear RossThick-LiSparseReciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model is used to generate the routine MODIS BRDFAlbedo product due to its global applicability and the underlying physics. A challenge of this model in regard to surface reflectance anisotropy effects comes from its underestimation of the directional reflectance signatures near the Sun illumination direction; also known as the hotspot effect. In this study, a method has been developed for improving the ability of the RTLSR model to simulate the magnitude and width of the hotspot effect. The method corrects the volumetric scattering component of the RTLSR model using an exponential approximation of a physical hotspot kernel, which recreates the hotspot magnitude and width using two free parameters (C(sub 1) and C(sub 2), respectively). The approach allows one to reconstruct, with reasonable accuracy, the hotspot effect by adjusting or using the prior values of these two hotspot variables. Our results demonstrate that: (1) significant improvements in capturing hotspot effect can be made to this method by using the inverted hotspot parameters; (2) the reciprocal nature allow this method to be more adaptive for simulating the hotspot height and width with high accuracy, especially in cases where hotspot signatures are available; and (3) while the new approach is consistent with the heritage RTLSR model inversion used to estimate intrinsic narrowband and broadband albedos, it presents some differences for vegetation clumping index (CI) retrievals. With the hotspot-related model parameters determined a priori, this method offers improved performance for various ecological remote sensing applications; including the estimation of canopy structure parameters.

airborne measurements↗

NASA NTRS2016

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

Li, Yonghong↗

NASA NTRS2016

A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E's day- and night-time observations.

soil moisture↗

NASA NTRS2015

Improving AIRS Radiance Spectra in High Contrast Scenes Using MODIS

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in 2378 channels ranging in wavelength from 3.7-15.4 microns with spectral resolution of better than 1200, and spatial resolution of 13.5 km with global daily coverage. The AIRS is designed to measure temperature and water vapor profiles for improvement in weather forecast accuracy and improved understanding of climate processes. As with most instruments, the AIRS Point Spread Functions (PSFs) are not the same for all detectors. When viewing a non-uniform scene, this causes a significant radiometric error in some channels that is scene dependent and cannot be removed without knowledge of the underlying scene. The magnitude of the error depends on the combination of non-uniformity of the AIRS spatial response for a given channel and the non-uniformity of the scene, but is typically only noticeable in about 1% of the scenes and about 10% of the channels. The current solution is to avoid those channels when performing geophysical retrievals. In this effort we use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument to provide information on the scene uniformity that is used to correct the AIRS data. For the vast majority of channels and footprints the technique works extremely well when compared to a Principal Component (PC) reconstruction of the AIRS channels. In some cases where the scene has high inhomogeneity in an irregular pattern, and in some channels, the method can actually degrade the spectrum. Most of the degraded channels appear to be slightly affected by random noise introduced in the process, but those with larger degradation may be affected by alignment errors in the AIRS relative to MODIS or uncertainties in the PSF. Despite these errors, the methodology shows the ability to correct AIRS radiances in non-uniform scenes under some of the worst case conditions and improves the ability to match AIRS and MODIS radiances in non-uniform scenes.

spatial↗

NASA NTRS2017

Improving X-Ray Optics via Differential Deposition

Differential deposition, a post-fabrication figure correction technique, has the potential to significantly improve the imaging quality of grazing-incidence X-ray optics. DC magnetron sputtering is used to selectively coat the mirror in order to minimize the figure deviations. Custom vacuum chambers have been developed at NASA MSFC that will enable the implementation of the deposition on X-ray optics. A factor of two improvement has been achieved in the angular resolution of the full-shell X-ray optics with first stage correction of differential deposition. Current efforts are focused on achieving higher improvements through efficient implementation of differential deposition.

differential deposition grazing↗

NASA NTRS2017

Improvement of Reynolds-Stress and Triple-Product Lag Models

The Reynolds-stress and triple product Lag models were created with a normal stress distribution which was defined by the accepted 4:3:2 distribution of streamwise, spanwise and wall normal stresses, and a ratio of τ(sub w) = 0.3k in the log layer region of high Reynolds number flat plate flow, which implies R11(+) = 4/(9/2)∗.3 ≈ 2.96. More recent measurements show a more complex picture of the log layer region at high Reynolds numbers. The first cut at improving these models along with the direction for future refinements is described. Comparison with recent high Reynolds number data shows areas where further work is needed, but also shows inclusion of the modeled turbulent transport terms improve the prediction where they influence the solution. Additional work is needed to develop a model that better matches experiments, but there is significant improvement in many of the details of the log layer behavior.

Fluid dynamics↗

NASA NTRS2017

Exposing the Strategies that Can Reduce the Obstacles: Improving the Science User Experience

It is now well established that pursuing generic solutions to what seem are common problems in Earth science data access and use can often lead to disappointing results for both system developers and the intended users. This presentation focuses on real-world experience of managing a large and complex data system, NASAs Earth Science Data and Information Science System (EOSDIS), whose mission is to serve both broad user communities and those in smaller niche applications of Earth science data and services. In the talk, we focus on our experiences with known data user obstacles characterizing EOSDIS approaches, including various technological techniques, for engaging and bolstering, where possible, user experiences with EOSDIS. For improving how existing and prospective users discover and access NASA data from EOSDIS we introduce our cross-archive tool: Earthdata Search. This new search and order tool further empowers users to quickly access data sets using clever and intuitive features. The Worldview data visualization tool is also discussed highlighting how many users are now performing extensive data exploration without necessarily downloading data. Also, we explore our EOSDIS data discovery and access webinars, data recipes and short tutorials, targeted technical and data publications, user profiles and social media as additional tools and methods used for improving our outreach and communications to a diverse user community. These efforts have paid substantial dividends for our user communities by allowing us to target discipline specific community needs. The desired take-away from this presentation will be an improved understanding of how EOSDIS has approached, and in several instances achieved, removing or lowering the barriers to data access and use. As we look ahead to more complex Earth science missions, EOSDIS will continue to focus on our user communities, both broad and specialized, so that our overall data system can continue to serve the needs of science and applications users.

communications↗

NASA NTRS2018

Orion Heat Shield Manufacturing Producibility Improvements for the EM-1 Flight Test Program

This paper describes how the ORION program is incorporating improvements in the heat shield design and manufacturing processes reducing programmatic risk and ensuring crew safety in support of NASA's Exploration missions. The approach for the EFT-1 heat shield utilized a low risk Apollo heritage design and manufacturing process using an Avcoat TPS ablator with a honeycomb substrate to provide a one piece heat shield to meet the mission re-entry heating environments. The EM-1 mission will have additional flight systems installed to fly to the moon and return to Earth. Heat shield design and producibility improvements have been incorporated in the EM-1 vehicle to meet deep space mission requirements. The design continues to use the Avcoat material, but in a block configuration to enable improvements in consistant and repeatable application processes using tile bonding experience developed on the Space Shuttle Transportation System Program.

Producibility↗

NASA NTRS2018

The SMAP Level-4 ECO Project: Improving Terrestrial Flux Estimates Through Coupled Hydrology-Vegetation Data Assimilation

Simulations of hydrologic and vegetation states as well as water, energy and carbon fluxes from the land surface to the atmosphere are crucial for a wide range of applications, including agricultural advisories, forecasts of (short-term) atmospheric behavior and seasonal weather predictions including forecasts of extreme events, such as heatwaves or droughts. The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Eco-Hydrology (L4-ECO) project aims to improve modeled estimates of the terrestrial water, energy and carbon fluxes and states by developing a fully-coupled hydrology-vegetation data assimilation system. This system is developed around the NASA Goddard Earth Observing System (GEOS) Catchment-CN land surface model, which combines land hydrology and energy balance components of the GEOS Catchment model with dynamic vegetation components of the Community Land Model version 4. Catchment-CN fully couples the terrestrial water, energy and carbon cycles, allowing feedbacks from the land hydrology to the biosphere and vice versa.Here, we implement a calibration of the Catchment-CN vegetation parameterization against observations of the fraction of absorbed photosynthetically active radiation (FPAR) from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve the model's standalone skill. Later, the DA algorithm used to produce the SMAP L4 soil moisture product will be adapted to Catchment-CN to assimilate SMAP brightness temperatures and inform the model's land hydrology component. Finally, the DA system will be further extended to assimilate MODIS FPAR observations in order to constrain the model's dynamic vegetation component.In this presentation, we demonstrate that the Catchment-CN parameter calibration leads to more realistic vegetation simulations and reduces the root mean squared error between modeled and observed vegetation states across the model's various plant functional types. We also show that the assimilation of SMAP observations is able to improve the average correlation, bias and unbiased RMSE between the modeled surface and root zone soil moisture estimates, and ground observations from the SMAP core validation sites.

Kolassa, Jana↗