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At least 865 records · Page 48

The Pattern Across the Continental United States of Evapotranspiration Variability Associated with Water Availability

The spatial pattern across the continental United States of the interannual variance of warm season water-dependent evapotranspiration, a pattern of relevance to land-atmosphere feedback, cannot be measured directly. Alternative and indirect approaches to estimating the pattern, however, do exist, and given the uncertainty of each, we use several such approaches here. We first quantify the water dependent evapotranspiration variance pattern inherent in two derived evapotranspiration datasets available from the literature. We then search for the pattern in proxy geophysical variables (air temperature, stream flow, and NDVI) known to have strong ties to evapotranspiration. The variances inherent in all of the different (and mostly independent) data sources show some differences but are generally strongly consistent they all show a large variance signal down the center of the U.S., with lower variances toward the east and (for the most part) toward the west. The robustness of the pattern across the datasets suggests that it indeed represents the pattern operating in nature. Using Budykos hydroclimatic framework, we show that the pattern can largely be explained by the relative strength of water and energy controls on evapotranspiration across the continent.

Air Temperature↗

Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations: China 2004-2013

Three decades of rapid economic development is causing severe and widespread PM2.5(particulate matter (is) less than 2.5 ) pollution in China. However, research on the health impacts of PM2.5 exposure has been hindered by limited historical PM2.5 concentration data. We estimated ambient PM2.5 concentrations from 2004 to 2013 in China at 0.1 deg resolution using the most recent satellite data and evaluated model performance with available ground observations. We developed a two-stage spatial statistical model using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) and assimilated meteorology, land use data, and PM2.5 concentrations from China's recently established ground monitoring network. An inverse variance weighting (IVW) approach was developed to combine MODIS Dark Target and Deep Blue AOD to optimize data coverage. We evaluated model predicted PM2.5 concentrations from 2004 to early 2014 using ground observations. The overall model cross-validation R(sup 2) and relative prediction error were 0.79 and 35.6%, respectively. Validation beyond the model year (2013) indicated that it accurately predicted PM(sub 2.5) concentrations with little bias at the monthly (R(sup 2) = 0.73), regression slope = 0.91) and seasonal (R(sup 2) = 0.79), regression slope = 0.92) levels. Seasonal variations revealed that winter was the most polluted season and that summer was the cleanest season. Analysis of predicted PM2.5 levels showed a mean annual increase of 1.97 micro-g/cu cm between 2004 and 2007 and a decrease of 0.46 micro-g/cu cm between 2008 and 2013. Our satellite-driven model can provide reliable historical PM2.5 estimates in China at a resolution comparable to those used in epidemiologic studies on the health effects of long-term PM2.5 exposure in North America. This data source can potentially advance research on PM2.5 health effects in China.

satellite remote sensing↗

Inviscid and Viscous CFD Analysis of Booster Separation for the Space Launch System Vehicle

This paper presents details of Computational Fluid Dynamic (CFD) simulations of the Space Launch System during solid-rocket booster separation using the Cart3D inviscid and Overflow viscous CFD codes. The discussion addresses the use of multiple data sources of computational aerodynamics, experimental aerodynamics, and trajectory simulations for this critical phase of flight. Comparisons are shown between Cart3D simulations and a wind tunnel test performed at NASA Langley Research Center's Unitary Plan Wind Tunnel, and further comparisons are shown between Cart3D and viscous Overflow solutions for the flight vehicle. The Space Launch System (SLS) is a new exploration-class launch vehicle currently in development that includes two Solid Rocket Boosters (SRBs) modified from Space Shuttle hardware. These SRBs must separate from the SLS core during a phase of flight where aerodynamic loads are nontrivial. The main challenges for creating a separation aerodynamic database are the large number of independent variables (including orientation of the core, relative position and orientation of the boosters, and rocket thrust levels) and the complex flow caused by exhaust plumes of the booster separation motors (BSMs), which are small rockets designed to push the boosters away from the core by firing partially in the direction opposite to the motion of the vehicle.

Viscous↗

Basin-Scale Assessment of the Land Surface Energy Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

This paper compares the annual and monthly components of the simulated energy budget from the North American Land Data Assimilation System phase 2 (NLDAS-2) with reference products over the domains of the 12 River Forecast Centers (RFCs) of the continental United States (CONUS). The simulations are calculated from both operational and research versions of NLDAS-2. The reference radiation components are obtained from the National Aeronautics and Space Administration Surface Radiation Budget product. The reference sensible and latent heat fluxes are obtained from a multitree ensemble method applied to gridded FLUXNET data from the Max Planck Institute, Germany. As these references are obtained from different data sources, they cannot fully close the energy budget, although the range of closure error is less than 15%formean annual results. The analysis here demonstrates the usefulness of basin-scale surface energy budget analysis for evaluating model skill and deficiencies. The operational (i.e., Noah, Mosaic, and VIC) and research (i.e., Noah-I and VIC4.0.5) NLDAS-2 land surface models exhibit similarities and differences in depicting basin-averaged energy components. For example, the energy components of the five models have similar seasonal cycles, but with different magnitudes. Generally, Noah and VIC overestimate (underestimate) sensible (latent) heat flux over several RFCs of the eastern CONUS. In contrast, Mosaic underestimates (overestimates) sensible (latent) heat flux over almost all 12 RFCs. The research Noah-I and VIC4.0.5 versions show moderate-to-large improvements (basin and model dependent) relative to their operational versions, which indicates likely pathways for future improvements in the operational NLDAS-2 system.

Energy↗

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

aerosols above clouds↗

Low Ozone over Europe Doesn't Mean the Sky Is Falling, Its Actually Rising

Data Sources: NASA Aura Microwave Limb Sounder (MLS) (O3 profiles and columns), NASA Global Modeling Initiative (GMI) Chemistry and Transport Model (calculated O3depletion), and MERRA Tropopause Heights. Technical Description of Figures: The left graphics show MLS northern hemisphere stratospheric column ozone on Feb. 1, 2016. Very low columns are seen over the UK and Europe (<225 DU, inside dashed circle). The lower graphic shows the GMI-calculated O3 depletion. It's very small, suggesting the low O3 does not indicate significant depletion. The right graphics show how the high tropopause height in this region explains the observed low ozone. The lower panel shows that the high tropopause on Feb. 1 lifts the O3 profile compared to a typical profile found earlier in winter. This motion lifts the profile to lower pressures thus reducing the total column. The GMI Model shows only 4 Dobson Units (DU) of O3 depletion even though the column is more than 100 DU lower than one month earlier. Scientific significant and societal relevance: To quantitatively understand anthropogenic impacts to the stratospheric ozone layer, we must be able to distinguish between low ozone caused by ozone depleting substances and that caused by natural dynamical variability in the atmosphere. Observations and realistic simulations of atmospheric composition are both required in order to separate natural and anthropogenic ozone variability.

Stratospheric↗

Comparison of Factorization-Based Filtering for Landing Navigation

This paper develops and analyzes methods for fusing inertial navigation data with external data, such as data obtained from an altimeter and a star camera. The particular filtering techniques are based upon factorized forms of the Kalman filter, specifically the UDU and Cholesky factorizations. The factorized Kalman filters are utilized to ensure numerical stability of the navigation solution. Simulations are carried out to compare the performance of the different approaches along a lunar descent trajectory using inertial and external data sources. It is found that the factorized forms improve upon conventional filtering techniques in terms of ensuring numerical stability for the investigated landing navigation scenario.

McCabe, James S.↗

Satellite Estimation of Fractional Cover in Several California Specialty Crops

Past research in California and elsewhere has revealed strong relationships between satellite NDVI, photosynthetically active vegetation fraction (Fc), and crop evapotranspiration (ETc). Estimation of ETc can support efficiency of irrigation practice, which enhances water security and may mitigate nitrate leaching. The U.C. Cooperative Extension previously developed the CropManage (CM) web application for evaluation of crop water requirement and irrigation scheduling for several high-value specialty crops. CM currently uses empirical equations to predict daily Fc as a function of crop type, planting date and expected harvest date. The Fc prediction is transformed to fraction of reference ET and combined with reference data from the California Irrigation Management Information System to estimate daily ETc. In the current study, atmospherically-corrected Landsat NDVI data were compared with in-situ Fc estimates on several crops in the Salinas Valley during 2011-2014. The satellite data were observed on day of ground collection or were linearly interpolated across no more than an 8-day revisit period. Results will be presented for lettuce, spinach, celery, broccoli, cauliflower, cabbage, peppers, and strawberry. An application programming interface (API) allows CM and other clients to automatically retrieve NDVI and associated data from NASA's Satellite Irrigation Management Support (SIMS) web service. The SIMS API allows for queries both by individual points or user-defined polygons, and provides data for individual days or annual timeseries. Updates to the CM web app will convert these NDVI data to Fc on a crop-specific basis. The satellite observations are expected to play a support role in Salinas Valley, and may eventually serve as a primary data source as CM is extended to crop systems or regions where Fc is less predictable.

satellite↗

Analysis of Rawinsonde Spatial Separation for Space Launch Vehicle Applications at the Eastern Range

Spatial separation of HR rawinsonde data is directly correlated with climatological tropospheric wind environment over ER. Stronger winds in the winter result in further downrange drift. Lighter winds in the summer result in the less horizontal drift during ascent. Maximum downrange distance can exceed 200 km during winter months. Data could misrepresent the environment the vehicle will experience during ascent. PRESTO uses all available data sources to produce the best representative, vertically complete atmosphere for launch vehicle DOL operations. Capability planned for use by NASA Space Launch System vehicle's first flight scheduled for Fall 2018.

Decker, Ryan K.↗

Assessment of the SMAP Passive Soil Moisture Product

The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational Level 2 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 kilometer Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 cubic meter per cubic meter unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 cubic meter per cubic meter.

passive↗

Improvement in the Characterization of MODIS Subframe Difference

MODIS is a key instrument of NASA's Earth Observing System. It has successfully operated for 16+ years on the Terra satellite and 14+ years on the Aqua satellite, respectively. MODIS has 36 spectral bands at three different nadir spatial resolutions, 250m (bands 1-2), 500m (bands 3-7), and 1km (bands 8-36). MODIS subframe measurement is designed for bands 1-7 to match their spatial resolution in the scan direction to that of the track direction. Within each 1 km frame, the MODIS 250 m resolution bands sample four subframes and the 500 m resolution bands sample two subframes. The detector gains are calibrated at a subframe level. Due to calibration differences between subframes, noticeable subframe striping is observed in the Level 1B (L1B) products, which exhibit a predominant radiance-level dependence. This paper presents results of subframe differences from various onboard and earth-view data sources (e.g. solar diffuser, electronic calibration, spectro-radiometric calibration assembly, Earth view, etc.). A subframe bias correction algorithm is proposed to minimize the subframe striping in MODIS L1B image. The algorithm has been tested using sample L1B images and the vertical striping at lower radiance value is mitigated after applying the corrections. The subframe bias correction approach will be considered for implementation in future versions of the calibration algorithm.

Li, Yonghong↗

The Integrated Medical Model: Outcomes from Independent Review

In 2016, the Integrated Medical Model (IMM) v4.0 underwent an extensive external review in preparation for transition to an operational status. In order to insure impartiality of the review process, the Exploration Medical Capabilities Element of NASA's Human Research Program convened the review through the Systems Review Office at NASA Goddard Space Flight Center (GSFC). The review board convened by GSFC consisted of persons from both NASA and academia with expertise in the fields of statistics, epidemiology, modeling, software development, aerospace medicine, and project management (see Figure 1). The board reviewed software and code standards, as well as evidence pedigree associated with both the input and outcomes information. The board also assesses the models verification, validation, sensitivity to parameters and ability to answer operational questions. This talk will discuss the processes for designing the review, how the review progressed and the findings from the board, as well as summarize the IMM project responses to those findings. Overall, the board found that the IMM is scientifically sound, represents a necessary, comprehensive approach to identifying medical and environmental risks facing astronauts in long duration missions and is an excellent tool for communication between engineers and physicians. The board also found IMM and its customer(s) should convene an additional review of the IMM data sources and to develop a sustainable approach to augment, peer review, and maintain the information utilized in the IMM. The board found this is critically important because medical knowledge continues to evolve. Delivery of IMM v4.0 to the Crew Health and Safety (CHS) Program will occur in the 2017. Once delivered for operational decision support, IMM v4.0 will provide CHS with additional quantitative capability in to assess astronaut medical risks and required medical capabilities to help drive down overall mission risks.

medical equipment↗

Parameter Validation for Evaluation of Spaceflight Hardware Reusability

Within recent years, there has been an influx of companies around the world pursuing reusable systems for space flight. Much like NASA, many of these new entrants are learning that reusable systems are complex and difficult to acheive. For instance, in its first attempts to retrieve spaceflight hardware for future reuse, SpaceX unsuccessfully tried to land on a barge at sea, resulting in a crash-landing. As this new generation of launch developers continues to develop concepts for reusable systems, having a systematic approach for determining the most effective systems for reuse is paramount. Three factors that influence the effective implementation of reusability are cost, operability and reliability. Therefore, a method that integrates these factors into the decision-making process must be utilized to adequately determine whether hardware used in space flight should be reused or discarded. Previous research has identified seven features that contribute to the successful implementation of reusability for space flight applications, defined reusability for space flight applications, highlighted the importance of reusability, and presented areas that hinder successful implementation of reusability. The next step is to ensure that the list of reusability parameters previously identified is comprehensive, and any duplication is either removed or consolidated. The characteristics to judge the seven features as good indicators for successful reuse are identified and then assessed using multiattribute decision making. Next, discriminators in the form of metrics or descriptors are assigned to each parameter. This paper explains the approach used to evaluate these parameters, define the Measures of Effectiveness (MOE) for reusability, and quantify these parameters. Using the MOEs, each parameter is assessed for its contribution to the reusability of the hardware. Potential data sources needed to validate the approach will be identified.

Childress-Thompson, Rhonda↗

Introduction to Remote Sensing Image Registration

For many applications, accurate and fast image registration of large amounts of multi-source data is the first necessary step before subsequent processing and integration. Image registration is defined by several steps and each step can be approached by various methods which all present diverse advantages and drawbacks depending on the type of data, the type of applications, the a prior information known about the data and the type of accuracy that is required. This paper will first present a general overview of remote sensing image registration and then will go over a few specific methods and their applications

Pattern Recognition↗

Parameter Validation for Evaluation of Spaceflight Hardware Reusability

Within recent years, there has been an influx of companies around the world pursuing reusable systems for space flight. Much like NASA, many of these new entrants are learning that reusable systems are complex and difficult to acheive. For instance, in its first attempts to retrieve spaceflight hardware for future reuse, SpaceX unsuccessfully tried to land on a barge at sea, resulting in a crash-landing. As this new generation of launch developers continues to develop concepts for reusable systems, having a systematic approach for determining the most effective systems for reuse is paramount. Three factors that influence the effective implementation of reusability are cost, operability and reliability. Therefore, a method that integrates these factors into the decision-making process must be utilized to adequately determine whether hardware used in space flight should be reused or discarded. Previous research has identified seven features that contribute to the successful implementation of reusability for space flight applications, defined reusability for space flight applications, highlighted the importance of reusability, and presented areas that hinder successful implementation of reusability. The next step is to ensure that the list of reusability parameters previously identified is comprehensive, and any duplication is either removed or consolidated. The characteristics to judge the seven features as good indicators for successful reuse are identified and then assessed using multiattribute decision making. Next, discriminators in the form of metrics or descriptors are assigned to each parameter. This paper explains the approach used to evaluate these parameters, define the Measures of Effectiveness (MOE) for reusability, and quantify these parameters. Using the MOEs, each parameter is assessed for its contribution to the reusability of the hardware. Potential data sources needed to validate the approach will be identified.

Childress-Thompson, Rhonda↗

The Opportunity in Commercial Approaches for Future NASA Deep Space Exploration Elements

In 2011, NASA released a report assessing the market for commercial crew and cargo services to low Earth orbit (LEO). The report stated that NASA had spent a few hundred million dollars in the Commercial Orbital Transportation Services (COTS) program on the portion related to the development of the Falcon 9 launch vehicle. Yet a NASA cost model predicted the cost would have been significantly more with a non-commercial cost-plus contracting approach. By 2016 a NASA request for information stated it must "maximize the efficiency and sustainability of the Exploration Systems development programs", as "critical to free resources for reinvestment...such as other required deep space exploration capabilities." This work joins the previous two events, showing the potential for commercial, public private partnerships, modeled on programs like COTS, to reduce the cost to NASA significantly for "...other required deep space exploration capabilities." These other capabilities include landers, stages and more. We mature the concept of "costed baseball cards", adding cost estimates to NASA's space systems "baseball cards." We show some potential costs, including analysis, the basis of estimates, data sources and caveats to address a critical question - based on initial assessment, are significant agency resources justified for more detailed analysis and due diligence to understand and invest in public private partnerships for human deep space exploration systems? The cost analysis spans commercial to cost-plus contracting approaches, for smaller elements vs. larger, with some variation for lunar or Mars. By extension, we delve briefly into the potentially much broader significance of the individual cost estimates if taken together as a NASA investment portfolio where public private partnership are stitched together for deep space exploration. How might multiple improvements in individual systems add up to NASA human deep space exploration achievements, realistically, affordably, sustainably, in a relevant timeframe?

cost modeling estimation↗

WG 3: EWV and Observations

Establish a minimum set of EWV and assess the status for each EWV. Assess opportunities in applying citizen science and private source data to provide EWV data. Promote continuity in observational systems and open access to data.

Huffman, George J.↗