SEARCH · Engineering Papers

Results for “In situ model”

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.

SourceResearch connectionFrom yearThrough year

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

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

The Land Surface in Earth System Reanalysis

Current global atmospheric reanalysis products such as ERA-5, MERRA-2, and JRA-55 provide estimates of land surface states and fluxes, including soil moisture, soil temperature, snow mass, latent and sensible heat fluxes, and runoff. These land surface estimates are based on land surface process models and, depending on the reanalysis product, on precipitation observations or the assimilation of land surface observations of soil moisture and snow conditions from satellites and in situ networks. The land models used in the current global atmospheric reanalysis systems are generally focused on water and energy balance processes, with prescribed static land cover and prescribed climatological vegetation conditions. That is, current global atmospheric reanalysis products do not reflect changes in land use or land cover, nor do they provide dynamic estimates of the land carbon cycle. These and other gaps, including the omission of anthropogenic processes such as irrigation in the land model, need to be addressed in the development of the next generation Earth system reanalysis systems. This presentation provides an overview of the state-of-the-art and future developments of land surface estimates in global reanalysis systems.

Rolf Reichle↗

NASA NTRS1991

A numerical modeling study of the interaction between the tides and the circulation forced by high-latitude plasma convection

A spectral, time-varying thermospheric general circulation model has been used to study the nonlinear interaction at high latitudes between the tides propagating into the thermosphere from below and the circulation induced by magnetospheric forcing and in situ solar heating. The model is discrete in the vertical with 27 layers spaced by half a scale height. In the horizontal, the fields are expanded in a series of spherical harmonics using a triangular truncation at wave number 31, equivalent to a homogeneous global resolution with a minimum wavelength of 1270 km. A hypothetical uniform grid point model would require a horizontal spacing of 417 km to describe the same minimum wavelength. In the high-latitude F region the tides affect the dusk vortex of the neutral flow very little, but the dawn vortex is either suppressed or amplified dependent upon the universal time and tidal phase. In the E region neutral flow, both the dusk and dawn vortices are shifted in local time by the tides, again as a function of universal time and tidal phase. At dusk a nonlinear amplification of the sunward winds occurs for certain combinations of parameters, and at dawn the winds may be completely suppressed. Below 120 km altitude the magnetospheric forcing creates a single cyclonic vortex which is also sensitive to the high-latitude tidal structure.

Mikkelsen, I. S.↗

NASA NTRS2009

Data Analysis of the Floating Potential Measurement Unit aboard the International Space Station

We present data from the Floating Potential Measurement Unit (FPMU), that is deployed on the starboard (S1) truss of the International Space Station. The FPMU is a suite of instruments capable of redundant measurements of various plasma parameters. The instrument suite consists of: a Floating Potential Probe, a Wide-sweeping spherical Langmuir probe, a Narrow-sweeping cylindrical Langmuir Probe, and a Plasma Impedance Probe. This paper gives a brief overview of the instrumentation and the received data quality, and then presents the algorithm used to reduce I-V curves to plasma parameters. Several hours of data is presented from August 5th, 2006 and March 3rd, 2007. The FPMU derived plasma density and temperatures are compared with the International Reference Ionosphere (IRI) and USU-Global Assimilation of Ionospheric Measurement (USU-GAIM) models. Our results show that the derived in-situ density matches the USU-GAIM model better than the IRI, and the derived in-situ temperatures are comparable to the average temperatures given by the IRI.

Barjatya, Aroh↗

NASA NTRSDate not supplied

Utilizing Earth Observations to Model Probable Coastal Wetland Extent, Sea-Level Rise Inundation Risk, and Assess Impacts on Historic Hawaiian Lands

Climate induced sea-level rise poses a risk to coastal areas on the Island of Hawai’i, and many of the island’s historic cultural lands are in danger of becoming overtaken by wetlands or inundation. In partnership with the County of Hawai’i, State of Hawai’i Department of Land and Natural Resources, and Arizona State University, NASA DEVELOP mapped wetland extent and short-term sea-level rise inundation risk. We utilized Earth observations over a 10-year span (2013 – 2022) that included the NASA MEaSUREs Gridded Sea Surface Height Anomalies and MEaSUREs Group for High Resolution Sea Surface Temperature datasets, United States Geological Survey (USGS) Hawaii Digital Elevation Models (DEM), and in situ tidal gauge data. Flood risk index values were acquired for 5 known Hawai’i flood events between 2019 – 2021 from the Global Flood Mapper tool on Google Earth Engine. We used a random forest model to predict short-term sea-level rise inundation risk along the entire coast of Hawai’i. Current wetland extents and probabilistic locations of new wetlands were modeled with the most recently available data from PlanetScope Surface Reflectance optical imagery (2022), USGS 3D Elevation Program (3DEP) 10m DEM (2020), temperature and precipitation data from the Hawai’i Climate Atlas, and soils data from the Hawai’i Soil Atlas (2014) using the Wetland Intrinsic Potential tool. Results indicated locations that had the highest probability of wetland creation. The end products aimed to help the partners prioritize efforts to meeting regulation requirements for wetlands protection, evaluate the inundation risk to historical features, and support decision-making for their Shoreline Setback and Climate Adaption plans.

Lisa Tanh↗

NASA NTRS2003

Studies of MGS TES and MPF MET Data

The work supported by this grant was divided into two broad areas: (1) mesoscale modeling of atmospheric circulations and analyses of Pathfinder, Viking, and other Mars data, and (2) analyses of MGS TES temperature data. The mesoscale modeling began with the development of a suitable Mars mesoscale model based upon the terrestrial MM5 model, which was then applied to the simulation of the meteorological observations at the Pathfinder and Viking Lander 1 sites during northern summer. This extended study served a dual purpose: to validate the new mesoscale model with the best of the available in-situ data, and to use the model to aid in the interpretation of the surface meteorological data.

Barnes, Jeff R.↗

NASA NTRS1989

Evaluating atmospheric correction models for retrieving surface temperatures from the AVHRR over a tallgrass prairie

The effects of atmospheric attenuation on surface radiative temperatures obtained by the AVHRR over a tallgrass prairie area in the Flint Hills of Kansas are examined. Six atmospheric correction models developed primarily for sea-surface temperature studies are used to test their utility for retrieval of radiative temperatures over the land surface. An uncertainty of + or - 3.0 C was found for the AVHRR data, and used to evaluate the performance of a given model. When the difference between in situ and AVHRR surface temperatures was smaller than the uncertainty, the model was judged to be adequate. Among the six models evaluated, only the NOAA split-window model consistently adjusted the AVHRR surface temperatures within + or - 3.0 C of the in situ measurements.

Cooper, D. I.↗

NASA NTRS2018

Chemical Modeling of the Reactivity of Short-Lived Greenhouse Gases: A Model Inter-Comparison Prescribing a Well-Measured, Remote Troposphere

We develop a new protocol for merging in situ measurements with 3-D model simulations of atmospheric chemistry with the goal of integrating over the data to identify the most reactive air parcels in terms of tropospheric production and loss of the greenhouse gases ozone and methane. Presupposing that we can accurately measure atmospheric composition, we examine whether models constrained by such measurements agree on the chemical budgets for ozone and methane. In applying our technique to a synthetic data stream of 14,880 parcels along 180W, we are able to isolate the performance of the photochemical modules operating within their global chemistry-climate and chemistry-transport models, removing the effects of modules controlling tracer transport, emissions, and scavenging. Differences in reactivity across models are driven only by the chemical mechanism and the diurnal cycle of photolysis rates, which are driven in turn by temperature, water vapor, solar zenith angle, clouds, and possibly aerosols and overhead ozone, which are calculated in each model. We evaluate six global models and identify their differences and similarities in simulating the chemistry through a range of innovative diagnostics. All models agree that the more highly reactive parcels dominate the chemistry (e.g., the hottest 10% of parcels control 25-30% of the total reactivities), but do not fully agree on which parcels comprise the top 10%. Distinct differences in specific features occur, including the regions of maximum ozone production and methane loss, as well as in the relationship between photolysis and these reactivities. Unique, possibly aberrant, features are identified for each model, providing a benchmark for photochemical module development. Among the 6 models tested here, 3 are almost indistinguishable based on the inherent variability caused by clouds, and thus we identify 4, effectively distinct, chemical models. Based on this work, we suggest that water vapor differences in model simulations of past and future atmospheres may be a cause of the different evolution of tropospheric O3 and CH4, and lead to different chemistry-climate feedbacks across the models.

greenhouse gases↗

NASA NTRS2019

Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land-Atmosphere Coupling

The role of soil moisture in NWP has gained more attention in recent years, as studies have demonstrated impacts of land surface states on ambient weather from diurnal to seasonal scales. However, soil moisture initialization approaches in coupled models remain quite diverse in terms of their complexity and observational roots, while assessment using bulk forecast statistics can be simplistic and misleading. In this study, a suite of soil moisture initialization approaches is used to generate short-term coupled forecasts over the U.S. Southern Great Plains using NASA’s Land Information System (LIS) and NASA Unified WRF (NU-WRF) modeling systems. This includes a wide range of currently used initialization approaches, including soil moisture derived from ‘off-the-shelf’ products such as atmospheric models and land data assimilation systems, high-resolution land surface model spinups, and satellite-based soil moisture products from SMAP. Results indicate that the spread across initialization approaches can be quite large in terms of soil moisture conditions and spatial resolution, and that SMAP performs well in terms of heterogeneity and temporal dynamics when compared against high resolution land surface model and in-situ soil moisture estimates. Case studies are analyzed using the local land-atmosphere coupling (LoCo) framework that relies on integrated assessment of soil moisture, surface flux, boundary layer, and ambient weather, with results highlighting the critical role of inherent model background biases. In addition, simultaneous assessment of land vs. atmospheric initial conditions in an integrated, process-level fashion can help address the question of whether improvements in traditional NWP verification statistics are achieved for the right reasons.

Southern Great Plains↗

NASA NTRS1994

Infrared algorithm development for ocean observations with EOS/MODIS

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling and evaluation of atmospheric path radiance efforts on SST estimation, exploration of involvement in ongoing field studies, evaluation of new computer networking strategies, and objective analysis approaches.

Brown, Otis B.↗

NASA NTRS1995

Infrared algorithm development for ocean observations

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, involvement in field studies, production and evaluation of new computer networking strategies, and objective analysis approaches.

Brown, Otis B.↗

NASA NTRS1997

Infrared Algorithm Development for Ocean Observations with EOS/MODIS

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared measurements. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, development of experimental instrumentation, and participation in MODIS (project) related activities. Activities in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, undertake field campaigns, analysis of field data, and participation in MODIS meetings.

Brown, Otis B.↗

NASA NTRS2004

Methods for Validation and Intercomparison of Remote Sensing and In situ Ice Water Measurements: Case Studies from CRYSTAL-FACE and Model Results

Remote sensing observations, such as those from AURA, are necessary to understand the role of cirrus in determining the radiative and humidity budgets of the upper troposphere. Using these measurements quantitatively requires comparisons with in situ measurements that have previously been validated. However, a direct comparison of remote and in situ measurements is difficult due to the requirement that the spatial and temporal overlap be sufficient in order to guarantee that both instruments are measuring the same air parcel. A difficult as this might be for gas phase intercomparisons, cloud inhomogeneities significantly exacerbate the problem for cloud ice water content measurements. The CRYSTAL-FACE mission provided an opportunity to assess how well such intercomparisons can be performed and to establish flight plans that will be necessary for validation of future satellite instruments. During CRYSTAL-FACE, remote and in situ instruments were placed on different aircraft (NASA's ER-2 and WB-59, and the two planes flew in tandem so that the in situ payload flew in the field of view of the remote instruments. We show here that, even with this type of careful flight planning, it is not always possible to guarantee that remote and in situ instruments are viewing the same air parcel. We use ice water data derived from the in situ Harvard Total Water (HV-TW) instrument, and the remote Goddard Cloud Radar System (CRS) and show that agreement between HV-TW and CRS is a strong function of the horizontal separation and the time delay between the aircraft transects. We also use a cloud model to simulate possible trajectories through a cloud and evaluate the use of statistical analysis in determining the agreement between the two instruments. This type of analysis should guide flight planning for future intercomparison efforts, whether for aircraft or satellite-borne instrumentation.

Sayres, D.S.↗

NASA NTRS1993

Emission characteristics of a model gas turbine combustor at practical conditions

This paper reports on in situ and exit plane emissions measurements from a model gas turbine combustor at practical air preheat temperatures and pressures for a range of operating conditions. The model combustor chosen for the study features two rows of jets (primary and dilution) with four jets per row, and utilizes effusive air cooling holes on the liner wall. The combustor dome is equipped with a flat-vaned swirler with a vane angle of 60 deg. Data are obtained at combustor pressures ranging from 2 to 10 atmospheres, air preheat temperatures from 204 C to 427 C, and combustor reference velocities from 10.0 to 20.0 m/s. An overall equivalence ratio of 0.3 was constant for all conditions. Exit plane and in situ measurements are presented for HC, O2, CO2, CO, and NO(x). The results from exit plane NO(x) measurements illustrate that the model combustor is representative of current gas turbine combustors. The in situ data reveal effects of fuel/air and wall jet mixing on emission performance.

Drennan, S. A.↗

NASA NTRS2022

Validation and Interpretation of a Three-dimensional Configuration of a Magnetic Cloud Flux Rope

One strong magnetic cloud (MC)with a magnetic field magnitude reaching∼40 nT at 1 au during 2012 June16–17 is examined in association with a preexisting magnetic flux rope (MFR)identified on the Sun. The MC is characterized by a quasi-three-dimensional(3D) flux rope model based on in situ measurements from the Wind spacecraft. The contents of the magnetic flux and other parameters are quantified. In addition, a correlative study with the corresponding measurements of the same structure crossed by the Venus Express (VEX)spacecraft at a heliocentric distance of 0.7 au and with an angular separation of∼6°in longitude is performed to validate the MC modeling results. The spatial variation between the Wind and VEX magnetic field measurements is attributed to the3D configuration of the structure appearing as a knotted bundle of flux. A comparison of the magnetic flux contents between the MC and the preexisting MFR on the Sun indicates that the 3D reconnection process accompanying anM1.9flare may correspond to the magnetic reconnection between the field lines of the preexisting MFR rooted in the opposite polarity foot points. Such a process reduces the amount of the axial magnetic flux in the erupted flux rope, by approximately 50%, in this case.

Qiang Hu↗

NASA NTRS2017

Land surface Verification Toolkit (LVT)

LVT is a framework developed to provide an automated, consolidated environment for systematic land surface model evaluation Includes support for a range of in-situ, remote-sensing and other model and reanalysis products. Supports the analysis of outputs from various LIS subsystems, including LIS-DA, LIS-OPT, LIS-UE. Note: The Land Information System Verification Toolkit (LVT) is a NASA software tool designed to enable the evaluation, analysis and comparison of outputs generated by the Land Information System (LIS). The LVT software is released under the terms and conditions of the NASA Open Source Agreement (NOSA) Version 1.1 or later. Land Information System Verification Toolkit (LVT) NOSA.

surface model↗

NASA NTRS2023

A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R 2 ) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value −235 mm w.e. yr -1 (original) to −57 mm w.e. yr -1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature.

Greenland Ice Sheet↗

NASA NTRS2024

Evaluation of Vertical Patterns in Chlorophyll-A Derived From A Data Assimilating Model of Satellite-Based Ocean Color

Satellite-based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC-Argo floats are now filling the information gap at depth. Here we use BGC-Argo data to assess depth-resolved information on chlorophyll-a derived from an ocean biogeochemical model constrained by the assimilation of surface ocean color remote sensing. The data-assimilating model replicates well the general seasonality and meridional gradients in surface and depth-resolved chlorophyll-a inferred from the float array in the Southern Ocean. On average, the model tends to overestimate float-based chlorophyll, particularly at times and locations of high productivity such as the beginning of the spring bloom, subtropical deep chlorophyll maxima, and non-iron limited regions of the Southern Ocean. The highest model RMSE in the upper 50 m with respect to the float array is of 0.6 mg Chl m −3 , which should allow the detection of seasonal changes in float-based biomass (varying between 0.01 and >1 mg Chl m −3 ) but might hinder the identification of subtle changes in chlorophyll at narrow local scales. Both model and float profiling data show good agreement with in situ data from station ALOHA, with model estimates showing a slight accuracy edge in inferring depth-resolved observations. Uncertainties in float bio-optical estimates impede their use as a reliable benchmark for validation, but the general qualitative agreement between model and float data provides confidence in the ability of model to replicate biogeochemical features below the surface, where data is not directly constrained by the assimilation of satellite ocean color.

Lionel A Quintero↗

NASA NTRS2010

Utilizing In Situ Directional Hyperspectral Measurements to Validate Bio-Indicator Simulations for a Corn Crop Canopy

Two radiative transfer canopy models, SAIL and the two-layer Markov-Chain Canopy Reflectance Model (MCRM), were coupled with in situ leaf optical properties to simulate canopy-level spectral band ratio vegetation indices with the focus on the photochemical reflectance index in a cornfield. In situ hyperspectral measurements were made at both leaf and canopy levels. Leaf optical properties were obtained from both sunlit and shaded leaves. Canopy reflectance was acquired for eight different relative azimuth angles (psi) at three different view zenith angles (Theta (sub v)), and later used to validate model outputs. Field observations of photochemical reflectance index (PRI) for sunlit leaves exhibited lower values than shaded leaves, indicating higher light stress. Canopy PRI expressed obvious sensitivity to viewing geometry, as a function of both Theta (sub v) and psi . Overall, simulations from MCRM exhibited better agreements with in situ values than SAIL. When using only sunlit leaves as input, the MCRM-simulated PRI values showed satisfactory correlation and RMSE, as compared to in situ values. However, the performance of the MCRM model was significantly improved after defining a lower canopy layer comprised of shaded leaves beneath the upper sunlit leaf layer. Four other widely used band ratio vegetation indices were also studied and compared with the PRI results. MCRM simulations were able to generate satisfactory simulations for these other four indices when using only sunlit leaves as input; but unlike PRI, adding shaded leaves did not improve the performance of MCRM. These results support the hypothesis that the PRI is sensitive to physiological dynamics while the others detect static factors related to canopy structure. Sensitivity analysis was performed on MCRM in order to better understand the effects of structure related parameters on the PRI simulations. Leaf area index (LAI) showed the most significant impact on MCRM-simulated PRI among the parameters studied. This research shows the importance of hyperspectral and narrow band sensor studies, and especially the necessity of including the green wavelengths (e.g., 531 nm) on satellites proposing to monitor carbon dynamics of terrestrial ecosystems.

Cheng, Yen-Ben↗