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At least 109 records · Page 6

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NASA NTRS2011

The CHUVA Lightning Mapping Campaign

The primary science objective for the CHUVA lightning mapping campaign is to combine measurements of total lightning activity, lightning channel mapping, and detailed information on the locations of cloud charge regions of thunderstorms with the planned observations of the CHUVA (Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement) field campaign. The lightning campaign takes place during the CHUVA intensive observation period October-December 2011 in the vicinity of S o Luiz do Paraitinga with Brazilian, US, and European government, university and industry participants. Total lightning measurements that can be provided by ground-based regional 2-D and 3-D total lightning mapping networks coincident with overpasses of the Tropical Rainfall Measuring Mission Lightning Imaging Sensor (LIS) and the SEVIRI (Spinning Enhanced Visible and Infrared Imager) on the Meteosat Second Generation satellite in geostationary earth orbit will be used to generate proxy data sets for the next generation US and European geostationary satellites. Proxy data, which play an important role in the pre-launch mission development and in user readiness preparation, are used to develop and validate algorithms so that they will be ready for operational use quickly following the planned launch of the GOES-R Geostationary Lightning Mapper (GLM) in 2015 and the Meteosat Third Generation Lightning Imager (LI) in 2017. To date there is no well-characterized total lightning data set coincident with the imagers. Therefore, to take the greatest advantage of this opportunity to collect detailed and comprehensive total lightning data sets, test and validate multi-sensor nowcasting applications for the monitoring, tracking, warning, and prediction of severe and high impact weather, and to advance our knowledge of thunderstorm physics, extensive measurements from lightning mapping networks will be collected in conjunction with electric field mills, field change sensors, high speed cameras and other lightning sensors, dual-polarimetric radars, and aircraft in-situ microphysics which will allow for excellent cross-network inter-comparisons, assessments, and physical understanding.

Goodman, Steven J.↗

NASA NTRS2011

Photogrammetric Characterization of a Brownout Cloud

Brownout is a dangerous problem for rotorcraft operating in arid and dusty environments such as the current operating theaters in Iraq and Afghanistan. Although the interest in brownout has increased in the past decade, the fundamental physics that govern the shape and size of the cloud are not yet well understood. Many computational and scaled experimental studies have been performed in an attempt to further this understanding and to simulate and predict the brownout cloud formation. However, the phenomenon significantly lacks experimental data, particularly at full-scale, which is needed to help validate the brownout simulations being performed. In an effort to increase the data set needed for this validation, tests were performed at the US Army Yuma Proving Ground using photogrammetry to obtain brownout cloud data of an EH-60L Black Hawk. Particle testing was performed on a sample of sand from the landing zone to gain more understanding on the nature of the soil. The photogrammetry technique applied to obtaining data on the formation and evolution of a brownout cloud was verified in an earlier study. The data for a landing approach was examined in greater detail and enabled velocity components of points on the cloud to be determined, as well as the dimensions of structures within the cloud.

Tanner, Philip E.↗

NASA NTRS2005

CFD Modeling Needs and What Makes a Good Supersonic Combustion Validation Experiment

If a CFD code/model developer is asked what experimental data he wants to validate his code or numerical model, his answer will be: "Everything, everywhere, at all times." Since this is not possible, practical, or even reasonable, the developer must understand what can be measured within the limits imposed by the test article, the test location, the test environment and the available diagnostic equipment. At the same time, it is important for the expermentalist/diagnostician to understand what the CFD developer needs (as opposed to wants) in order to conduct a useful CFD validation experiment. If these needs are not known, it is possible to neglect easily measured quantities at locations needed by the developer, rendering the data set useless for validation purposes. It is also important for the experimentalist/diagnostician to understand what the developer is trying to validate so that the experiment can be designed to isolate (as much as possible) the effects of a particular physical phenomena that is associated with the model to be validated. The probability of a successful validation experiment can be greatly increased if the two groups work together, each understanding the needs and limitations of the other.

Gaffney, Richard L., Jr.↗

NASA NTRS2019

Evaluation of CLARA-A2 and ISCCP-H Cloud Cover Climate Data Records over Europe with ECA&D Ground-Based Measurements

Clouds are of high importance for the climate system but they still remain one of its principal uncertainties. Remote sensing techniques applied to satellite observations have assisted tremendously in the creation of long-term and homogeneous data records; however, satellite data sets need to be validated and compared with other data records, especially ground measurements. In the present study, the spatiotemporal distribution and variability of Total Cloud Cover (TCC) from the Satellite Application Facility on Climate Monitoring (CM SAF) Cloud, Albedo And Surface Radiation dataset from AVHRR data—edition 2 (CLARA-A2) and the International Satellite Cloud Climatology Project H-series (ISCCP-H) is analyzed over Europe. The CLARA-A2 data record has been created using measurements of the Advanced Very High Resolution Radiometer (AVHRR) instrument onboard the polar orbiting NOAA and the EUMETSAT MetOp satellites, whereas the ISCCP-H data were produced by a combination of measurements from geostationary meteorological satellites and the AVHRR instrument on the polar orbiting satellites. An intercomparison of the two data records is performed over their common period, 1984 to 2012. In addition, a comparison of the two satellite data records is made against TCC observations at 22 meteorological stations in Europe, from the European Climate Assessment & Dataset (ECA&D). The results indicate generally larger ISCCP-H TCC with respect to the corresponding CLARA-A2 data, in particular in the Mediterranean. Compared to ECA&D data, both satellite datasets reveal a reasonable performance, with overall mean TCC biases of 2.1 and 5.2% for CLARA-A2 and ISCCP-H, respectively. This, along with the higher correlation coefficients between CLARA-A2 and ECA&D TCC, indicates the better performance of CLARA-A2 TCC data.

Tzallas, Vasileios↗

NASA NTRS1978

Stratification and sample selection for multicrop experiments

The author has identified the following significant results. A stratification was performed and sample segments were selected for an initial investigation of multicrop problems in order to support development and evaluation of procedures for using LACIE and other technologies for the classification of corn and soybeans, to identify factors likely to affect classification performance, and to evaluate problems encountered and techniques which are applicable to the crop estimation problem in foreign countries. Two types of samples, low density and high density, supporting these requirements were selected as research data set for an initial evaluation of technical issues. Looking at the geographic location of the strata, the system appears to be logical and the various segments seem to represent different conditions. This result is supportive not only of the variables and the methodology employed in the stratification, but also of the validity of the data sets employed.

Landgrebe, D. A.↗

NASA NTRS2004

Initial Validation and Results of Geoscience Laser Altimeter System Optical Properties Retrievals

Verification of Geoscience Laser Altimeter System (GLAS) optical retrievals is . problematic in that passage over ground sites is both instantaneous and sparse plus space-borne passive sensors such as MODIS are too frequently out of sync with the GLAS position. In October 2003, the GLAS Validation Experiment was executed from NASA Dryden Research Center, California to greatly increase validation possibilities. The high-altitude NASA ER-2 aircraft and onboard instrumentation of Cloud Physics Lidar (CPL), MODIS Airborne Simulator (MAS), and/or MODIS/ASTER Airborne Simulator (MASTER) under-flew seven orbit tracks of GLAS for cirrus, smoke, and urban pollution optical properties inter-comparisons. These highly calibrated suite of instruments are the best data set yet to validate GLAS atmospheric parameters. In this presentation, we will focus on the inter-comparison with GLAS and CPL and draw preliminary conclusions about the accuracies of the GLAS 532nm retrievals of optical depth, extinction, backscatter cross section, and calculated extinction-to-backscatter ratio. Comparisons to an AERONET/MPL ground-based site at Monterey, California will be attempted. Examples of GLAS operational optical data products will be shown.

Hlavka, Dennis L.↗

NASA NTRS1993

Satellite data for diagnostics and for validation of model simulations

Two issues in the treatment of tropical convection in general circulation models are examined. First, several studies have found significant gradients in clear sky longwave fluxes near large convective systems. Increased upper tropospheric moisture associated with deep convection may explain the reduction in the longwave emission. Similar local gradients are not apparent in measurements from the Earth Radiation Budget Experiment (ERBE), an important data set for model validation. Thus the average cloud forcing and greenhouse effect derived from models and observations may differ systematically over warm tropical oceans. A comparison of ERBE fluxes with radiative calculations using coincident balloon-sonde atmospheric profiles indicates negligible systematic bias in the observations. The effect of convection on the clear sky fluxes may be localized to the edges of individual cloud systems. Second, the balance between shortwave and cloud forcing and longwave forcing is a persistent feature of tropical cloud systems in ERBE data. This cancellation effect has been used to diagnose problems in GCM (General Circulation Model) cloud fields on seasonal time scales. The daily record of net cloud radiative forcing is analyzed to determine the smallest spatial and temporal scales for the balance. The results show cancellation on periods as short as three days for regions smaller than 2.5 by 2.5 deg. The analysis indicates that the balance is primarily a local phenomenon characteristic of tropical convection. This is consistent with findings that the small cloud radiative forcing is due primarily to thick tropical cirrus. These results represent a particularly stringent test of convective parameterizations in GCM's with interactive ocean surfaces.

Collins, W. D.↗

NASA NTRS1975

Assessment of NDE reliability data

Twenty sets of relevant nondestructive test (NDT) reliability data were identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations was formulated, and a model to grade the quality and validity of the data sets was developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, were formulated for each NDE method. A comprehensive computer program was written and debugged to calculate the probability of flaw detection at several confidence limits by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. An example of the calculated reliability of crack detection in bolt holes by an automatic eddy current method is presented.

Yee, B. G. W.↗

NASA NTRS2001

Satellite Remote Sensing of Ozone Change, Air Quality and Climate

To date satellite remote sensing of ozone depletion has been very successful. Data sets have been validated and measured trends are in agreement with model calculations. Technology developed for sensing the stratosphere is now being employed to study air quality and climate with promising results. These new data show that air quality is a transcontinental issue, but that better instrumentation is needed. Recent data show a connection between the stratosphere, troposphere and climate, which will require new technology to quantify these relationships. NASA and NOAA (National Oceanic and Atmospheric Administration) are planning and developing new missions. Recent results from TOMS (Total Ozone Mapping Spectrometer), SeaWiffs, and Terra will be discussed and upcoming missions to study atmospheric chemistry will be discussed.

Hilsenrath, Ernest↗

NASA NTRS1976

Assessment of NDE Reliability Data

Twenty sets of relevant Nondestructive Evaluation (NDE) reliability data have been identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations has been formulated. A model to grade the quality and validity of the data sets has been developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, have been formulated for each NDE method. A comprehensive computer program has been written to calculate the probability of flaw detection at several confidence levels by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. Probability of detection curves at 95 and 50 percent confidence levels have been plotted for individual sets of relevant data as well as for several sets of merged data with common sets of NDE parameters.

Yee, B. G. W.↗

NASA NTRS2003

Validation of Spacecraft Active Cavity Radiometer Total Solar Irradiance (TSI) Long Term Measurement Trends Using Proxy TSI Least Squares Analyses

Long-term, incoming total solar irradiance (TSI) measurement trends were validated using proxy TSI values, derived from indices of solar magnetic activity. Spacecraft active cavity radiometers (ACR) are being used to measure longterm TSI variability, which may trigger global climate changes. The TSI, typically referred to as the solar constant, was normalized to the mean earth-sun distance. Studies of spacecraft TSI data sets confirmed the existence of a 0.1 %, long-term TSI variability component within a 10-year period. The 0.1% TSI variability component is clearly present in the spacecraft data sets from the 1984-2004 time frame. Typically, three overlapping spacecraft data sets were used to validate long-term TSI variability trends. However, during the years of 1978-1984, 1989-1991, and 1993-1996, three overlapping spacecraft data sets were not available in order to validate TSI trends. The TSI was found to vary with indices of solar magnetic activity associated with recent 10-year sunspot cycles. Proxy TSI values were derived from least squares analyses of the measured TSI variability with the solar indices of 10.7-cm solar fluxes, and with limb-darked sunspot fluxes. The resulting proxy TSI values were compared to the spacecraft ACR measurements of TSI variability to detect ACR instrument degradation, which may be interpreted as TSI variability. Analyses of ACR measurements and TSI proxies are presented primarily for the 1984-2004, Earth Radiation Budget Experiment (ERBE) ACR solar monitor data set. Differences in proxy and spacecraft measurement data sets suggest the existence of another TSI variability component with an amplitude greater than or equal to 0.5 Wm-2 (0.04%), and with a cycle of 20 years or more.

Lee, Robert Benjamin, III↗

NASA NTRS2020

How Long Is Too Long? Variogram Analysis of AERONET Data to Aid Aerosol Validation and Intercomparison Studies

Geophysical data sets derived from satellite sensors, ground/airborne instrumentation, and computational models are often compared against each other. A common example is the validation of satellite aerosol optical depth (AOD) retrievals against measurements from Aerosol Robotic Network (AERONET) Sun photometers. Spatiotemporal mismatch between data set sampling means that uncaptured variation in the underlying geophysical field introduces apparent disagreement into such comparisons, known as representation or collocation matchup uncertainty. This study uses variogram analysis of AERONET data to estimate temporal mismatch uncertainties and decorrelation time scales for the global AERONET record. As well as total AOD, the fine‐ and coarse‐mode AODs, Ångström Exponent (AE), and fine‐mode fraction (FMF) of AOD are analyzed. Globally, a time difference of 30 min typically induces from 0.011–0.035 variation in AOD. For total, fine, and coarse AODs the typical time to decorrelation is around 2–10 days. For AE and FMF it is 3–33 days; that is, aerosol systems often persist significantly longer than individual events in them. Biomass burning regions tend to show the largest and fastest subdaily AOD variability and also longest times to decorrelation. Some sites show significant season‐to‐season variations in behavior. These results can be used to inform site‐specific time collocation thresholds for aerosol validation analyses and account for temporal variation when estimating data set uncertainty. They also have implications for comparisons between different satellite products or models, data aggregation, and time series analyses. Results are provided on a site‐by‐site basis to facilitate use by other researchers.

satellite↗

NASA NTRS1981

The validation of LIMS ozone profiles using correlative rocket, ECC, and Dobson data sets

The Limb Infrared Monitor of the Stratosphere (LIMS) experiment is a limb scanning infrared sounder designed to measure vertical temperature profiles and the concentrations of key chemical compounds which are important in the stratospheric ozone-nitrogen photochemistry. Preliminary ozone profiles are being intercompared with correlative rocket and balloonsonde ozone data sets as part of the Nimbus 7 LIMS data validation activity. The LIMS ozone retrievals extend from the lower mesosphere to the tropopause (or cloud-top altitudes). In this paper, preliminary statistics of comparisons of ECC (electrochemical concentration cell) ozonesonde and rocket ozone profiles with LIMS ozone profiles are presented. ECC ozonesonde data taken at times of LIMS overpasses are also used to extend the LIMS retrieval down to ground level. Each combined profile is then integrated to obtain total column ozone. These integrated results are compared to Dobson data obtained at approximately the same time and location.

Remsberg, E. E.↗

NASA NTRS1993

Comparison Between Predicted and Experimentally Measured Flow Fields at the Exit of the SSME HPFTP Impeller

Validation of CFD codes is a critical first step in the process of developing CFD design capability. The MSFC Pump Technology Team has recognized the importance of validation and has thus funded several experimental programs designed to obtain CFD quality validation data. The first data set to become available is for the SSME High Pressure Fuel Turbopump Impeller. LDV Data was taken at the impeller inlet (to obtain a reliable inlet boundary condition) and three radial positions at the impeller discharge. Our CFD code, TASCflow, is used within the Propulsion and Commercial Pump industry as a tool for pump design. The objective of this work, therefore, is to further validate TASCflow for application in pump design. TASCflow was used to predict flow at the impeller discharge for flowrates of 80, 100 and 115 percent of design flow. Comparison to data has been made with encouraging results.

Bache, George↗

DOE OSTI2026

Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

AI/ML↗

NASA NTRSDate not supplied

Aeroheating Testing of the Mars Sample Return Earth Entry System with Surface Roughness

The Mars Sample Return Earth Entry System is a mission concept which would be the first NASA entry vehicle to utilize a woven thermal protection system as well as a 52.5 degree sphere-cone forebody geometry. Due to its novel design, historic experimental data sets were insufficient to validate the models used to characterize the expected aerothermal environment. A wind tunnel test campaign was funded by the Mars Sample Return Earth Entry System project in the NASA Langley 20-Inch Mach 6 Air Tunnel in order to obtain validation data. The December 2023 test entry of this campaign sought to obtain thermographic data to capture the impact of supersonic flow near woven surface roughness elements on convective heating augmentation, which was the largest remaining uncertainty in aerothermal design of the Earth Entry System. Data obtained were in family with prior results obtained on identical woven patterns without supersonic flow present at roughness elements, and it was found that this presence of supersonic flow did not have a noticeable effect on surface convective heating augmentation. Data were directly leveraged to support the NASA Mars Sample Return flight program and this data set is valuable for validating computational solutions on roughness-resolved grids.

Mars Sample Return↗

NASA NTRSDate not supplied

Aeroheating Testing of the Mars Sample Return Earth Entry System with Surface Roughness

Mars Sample Return↗

DOE OSTI2024

A Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site‐Level Validation, and Global Applicability

Abstract Lakes are important sentinels of climate change and may contribute over 30% of natural methane (CH 4 ) emissions; however, no earth system model (ESM) has represented lake CH 4 dynamics. To fill this gap, we refined a process‐based lake biogeochemical model to simulate global lake CH 4 emissions, including representation of lake bathymetry, oxic methane production (OMP), the effect of water level on ebullition, new non‐linear CH 4 oxidation kinetics, and the coupling of sediment carbon pools with in‐lake primary production and terrigenous carbon loadings. We compiled a lake CH 4 data set for model validation. The model shows promising performance in capturing the seasonal and inter‐annual variabilities of CH 4 emissions at 10 representative lakes for different lake types and the variations in mean annual CH 4 emissions among 106 lakes across the globe. The model reproduces the variations of the observed surface CH 4 diffusion and ebullition along the gradients of lake latitude, depth, and surface area. The results suggest that OMP could play an important role in surface CH 4 diffusion, and its relative importance is higher in less productive and/or deeper lakes. The model performance is improved for capturing CH 4 outgassing events in non‐floodplain lakes and the seasonal variability of CH 4 ebullition in floodplain lakes by representing the effect of water level on ebullition. The model can be integrated into ESMs to constrain global lake CH 4 emissions and climate‐CH 4 feedback.

54 ENVIRONMENTAL SCIENCES↗