Search NASA⌕ Search

SEARCH · Search NASA

Results for “Alternative data”

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

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

At least 1,045 records · Page 58

Gravitational Fluctuations as an Alternative to Inflation III. Numerical Results

Power spectra play an important role in the theory of inflation, and their ability to reproduce current observational data to high accuracy is often considered a triumph of inflation, largely because of a lack of credible alternatives. In previous work we introduced an alternative picture for the cosmological power spectra based on the nonperturbative features of the quantum version of Einstein’s gravity, instead of currently popular inflation models based on scalar fields. The key ingredients in this new picture are the appearance of a nontrivial gravitational vacuum condensate (directly related to the observed cosmological constant), and a calculable renormalization group running of Newton’s G on cosmological scales. More importantly, one notes the absence of any fundamental scalar fields in this approach. Results obtained previously were largely based on a semi-analytical treatment, and thus, while generally transparent in their implementation, often suffered from the limitations of various approximations and simplifying assumptions. In this work, we extend and refine our previous calculations by laying out an updated and extended analysis, which now utilizes a set of suitably modified state-of-the-art numerical programs (ISiTGR, MGCAMB and MGCLASS) developed for observational cosmology. As a result, we are able to remove some of the approximations employed in our previous studies, leading to a number of novel and detailed physical predictions. These should help in potentially distinguishing the vacuum condensate picture of quantum gravity from that of other models such as scalar field inflation. Here, besides the matter power spectrum P m (k) , we work out, in detail, predictions for what are referred to as the TT, TE, EE, BB angular spectra, as well as their closely related lensing spectra. However, the current limited precision of observational data today (especially on large angular scales) does not allow us yet to clearly prove or disprove either set of ideas. Nevertheless, by exploring in more details the relationship between gravity and cosmological matter and radiation both analytically and numerically, together with an expected future influx of increasingly accurate observational data, one can hope that the new quantum gravitational picture can be subjected to further stringent tests in the near future.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovering Hidden Geothermal Signatures using Unsupervised Machine Learning

Discovering hidden geothermal resources is a very challenging task. It requires the mining of large datasets, including various diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used Play Fairway Analysis (PFA) typically relies on subject-matter expertise to analyze site or regional data to estimate geothermal conditions and prospectivity. Here, we demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset of Southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. However, most of these systems are poorly characterized because of insufficient existing data and limited past explorative studies. This study aims to discover hidden patterns and relationships in the SWNM geothermal dataset to better understand regional hydrothermal conditions. This is achieved by applying an unsupervised machine learning algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden (latent) signatures characterizing datasets, (2) the optimal number of these signatures, (3) dominant data attributes associated with each signature, and (4) spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, geothermal attributes at 44 locations in SWNM. NMFk successfully finds data patterns and identifies the spatial associations of hydrothermal signatures with the four physiographic provinces in SWNM (Colorado Plateau, Volcanic Field, Basin and Range, and the Rio Grande rift). The algorithm identified up to 5 hydrothermal signatures in the SWNM datasets that differentiate between low- and medium-temperature hydrothermal systems in different provinces. Also, the algorithm identifies two medium-temperature hydrothermal systems in SWNM that require further exploration for geothermal resource development. Based on our analyses, 12 of the attributes are important to identify medium-temperature hydrothermal systems, and the remaining six attributes are critical to characterize low-temperature hydrothermal systems. Based on the obtained results, we identify potential physiographic provinces for further exploration to characterize them as geothermal resources. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored areas.

58 GEOSCIENCES↗

Reactive control and reasoning assistance for scientific laboratory instruments

Scientific laboratory instruments that are involved in chemical or physical sample identification frequently require substantial human preparation, attention, and interactive control during their operation. Successful real-time analysis of incoming data that supports such interactive control requires: (1) a clear recognition of variance of the data from expected results; and (2) rapid diagnosis of possible alternative hypotheses which might explain the variance. Such analysis then aids in decisions about modifying the experiment protocol, as well as being a goal itself. This paper reports on a collaborative project at the NASA Ames Research Center between artificial intelligence researchers and planetary microbial ecologists. Our team is currently engaged in developing software that autonomously controls science laboratory instruments and that provides data analysis of the real-time data in support of dynamic refinement of the experiment control. the first two instruments to which this technology has been applied are a differential thermal analyzer (DTA) and a gas chromatograph (GC). coupled together, they form a new geochemicstry and microbial analysis tool that is capable of rapid identification of the organiz and mineralogical constituents in soils. The thermal decomposition of the minerals and organics, and the attendance release of evolved gases, provides data about the structural and molecular chemistry of the soil samples.

Thompson, David E.↗

The 250AH/90A active lithium-thionyl chloride cell for Centaur-G application

A high rate active Li/SOCl2 cell was designed for use in a 28 volt, 250 amp-hour space battery system. The lithium battery is being considered as a replacement of its heavier silver-zinc counterpart on board the Centaur-G booster rocket which is used to launch payloads from the Space Shuttle cargo bay into deep-space. Basically a feasibility study, this development effort is demonstrating the ability of the lithium cell to deliver up to 90 amps safely at power densities of approximately 25 watts per pound. Test data on 4 prototype units is showing an energy density of 85 watt-hours per pound and 9.0 watt-hours/cu in. The cells tested typically delivered 280 to 300 amp-hours under ambient temperature test conditions using alternating continuous loads of 90, 55, and 20 amperes throughout life. Data from four cells tested are presented to demonstrate the capability of Li/SOCl2 technology for a C/3 discharge rate in active and hermetic cell units.

Zolla, A. E.↗

Vicarious Calibration of GOCI for the SeaDAS Ocean Color Retrieval

A key on-orbit calibration step for satellite remote sensing of ocean color is the vicarious calibration. This establishes the final gains for each spectral band on the sensor that minimize bias in the retrieved ocean color signal. The vicarious calibration is specific to the instrument and the atmospheric correction algorithm. The vicarious calibration gains for the Geostationary Ocean Color Imager (GOCI) are presented here, which were derived to optimize the performance ofNASA's standard atmospheric correction algorithm as implemented in the l2gen code and distributed through the SeaDAS open-source software package. Following NASA's protocols, the near-infrared(NIR) bands were calibrated first, and the visible bands were then calibrated relative to this fixed NIR calibration. The gain for the 745-nm NIR band was derived using a fixed aerosol model, which waschosen based on the Angstrom Coefficients derived from MODIS onAqua (MODISA). For the vicarious gains of the visible bands, twosources for the target water-leaving radiances were tested: matchupsfrom MODISA and climatological data from SeaWiFS. A validation analysis using AERONET-OC data shows an improvement in sensor performance when compared with results using the current vicarious gains and results using no vicarious calibration. Good agreement was found in vicarious gains derived using both concurrent MODISA and climatological SeaWiFS as vicarious calibration data sources. These results support the use of a concurrent sensor for the vicarious calibration when in situ data are not available and demonstrate that using climatology from a well-calibrated sensor like SeaWiFSfor the vicarious calibration is a valid alternative when it is not possible to use a concurrent sensor or in situ data. We recommend using the gains derived from concurrent GOCI matchups with MODISA for GOCI processing in SeaDAS/l2gen.

Concha, Javier↗

Voc Degradation in TF-VLS Grown InP Solar Cells

Here we consider two hypotheses to explain the open-circuit voltage (VOC) degradation observed in thin-film vapor-liquid-solid (TF-VLS) grown p-type InP photovoltaic cells: bandgap narrowing and local shunting. First, a bandgap (Eg) narrowing effect is hypothesized, based on the surface inhomogeneity of VLS InP captured by the photoluminescence (PL) image. The PL data was used to estimate a spatially-resolved active VOC across surface of the InP sample. Combining this data with the effective Jsc allowed an assessment of the I-V characteristics of individual unit cells. Next, an H-SPICE diode compact model was utilized to reproduce the I-V characteristics of the whole sample. We find a good fit to the I-V performance of TF-VLS grown InP solar cell. Second, a local shunting effect was also considered as an alternative explanation of the VOC degradation effect. Again, PL image data was used, and small local shunt resistance was added in arbitrary elementary unit cells to represent certain dark spots seen in the PL image and dictate the VOC degradation occurred in the sample.

14 SOLAR ENERGY↗

A user's view of optical disc applications

An overall space information system is considered. It is found that data storage is required in all elements of the system with the possible exception of the wideband communication link. The data capture facility is the first ground facility to handle space-acquired data. A typical nine-day Spacelab mission is expected to generate up to 10 to the 13th bits of data. The current storage medium for this data is approximately 4000 magnetic tapes. It is pointed out that optical disk storage provides an attractive alternative to magnetic disk and tape storage. Options to install an optical disk storage system in the GSFC data capture facility in the 1986 time frame are evaluated by NASA. Attention is given to data capture and data base applications, onboard data storage applications, and numerical computation applications.

Holcomb, L. B.↗

Distributed Data-Driven Optimization for Voltage Regulation in Distribution Systems

Here, this paper proposes a distributed data-driven optimization framework for voltage regulation in distribution systems. The recursive kernel regression and alternating direction method of multipliers (ADMM) are selected to cover the system learning and distributed optimization tasks. The proposed distributed data-driven framework is capable of having a rapid response to system or load changes while considering the operation optimality. Besides, the distributed algorithm parallels the computation tasks and reduces the computational expense of a single agent. To validate the performance of the proposed method, a hypothetical 7-Bus system and the IEEE 123-Bus system are selected to show the effectiveness of the proposed data-driven framework. According to the numerical study results, the proposed method offers great flexibility for selecting customized kernel models for different regions and can effectively improve the system voltage profile in a distributed manner.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Parametric Analysis of Surveillance Quality and Level and Quality of Intent Information and Their Impact on Conflict Detection Performance

A loss-of-separation (LOS) is said to occur when two aircraft are spatially too close to one another. A LOS is the fundamental unsafe event to be avoided in air traffic management and conflict detection (CD) is the function that attempts to predict these LOS events. In general, the effectiveness of conflict detection relates to the overall safety and performance of an air traffic management concept. An abstract, parametric analysis was conducted to investigate the impact of surveillance quality, level of intent information, and quality of intent information on conflict detection performance. The data collected in this analysis can be used to estimate the conflict detection performance under alternative future scenarios or alternative allocations of the conflict detection function, based on the quality of the surveillance and intent information under those conditions.Alternatively, this data could also be used to estimate the surveillance and intent information quality required to achieve some desired CD performance as part of the design of a new separation assurance system.

Guerreiro, Nelson M.↗

Assessing global fossil fuel availability in a scenario framework

This study assesses global, long-term economic availability of coal, oil and gas within the Shared Socio-economic Pathway (SSP) scenario framework considering alternative assumptions as to highly uncertain future developments of technology, policy and the economy. Diverse sets of trajectories are formulated varying the challenges to mitigation and adaptation of climate change. The potential CO2 emissions from fossil fuels make it a crucial element subject to deep uncertainties. The analysis is based on a well-established data set of cost-quantity combinations that assumes favorable techno-economic developments, but ignores additional constraints on the extraction sector. This study significantly extends that analysis to include alternative assumptions for the fossil fuel sector consistent with the SSP scenario families and applies these filters to the original data set, thus resulting in alternative cumulative fossil fuel availability curves. In a Middle-of-the-Road scenario, low cost fossil fuels embody carbon consistent with a RCP6.0 emission profile, if all the CO2 were emitted freely during the 21st century. In scenarios with high challenges to mitigation, the assumed embodied carbon in low-cost fossil fuels can trigger a RCP8.5 scenario; low mitigation challenges scenarios are still consistent with a RCP4.5 scenario.

Extraction Cost↗

flowVS: channel-specific variance stabilization in flow cytometry

Abstract Background Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances. Results We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett’s likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test. With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays. Conclusions The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with different levels of marker expressions. The newly developed flowVS algorithm solves the variance-stabilization problem in FC and microarrays by optimally transforming data with the help of Bartlett’s likelihood-ratio test. On two publicly available FC datasets, flowVS stabilizes within-population variances more evenly than the available transformation and normalization techniques. flowVS-based variance stabilization can help in performing comparison and alignment of phenotypically identical cell populations across different samples. flowVS and the datasets used in this paper are publicly available in Bioconductor.

60 APPLIED LIFE SCIENCES↗

Flight test validation of a frequency-based system identification method on an F-15 aircraft

A frequency-based performance identification approach was evaluated using flight data from the NASA F-15 Highly Integrated Digital Electronic Control aircraft. The approach used frequency separation to identify the effectiveness of multiple controls simultaneously as an alternative to independent control identification methods. Fourier transformations converted measured control and response data into frequency domain representations. Performance gradients were formed using multiterm frequency matching of control and response frequency domain models. An objective function was generated using these performance gradients. This function was formally optimized to produce a coordinated control trim set. This algorithm was applied to longitudinal acceleration and evaluated using two control effectors: nozzle throat area and inlet first ramp. Three criteria were investigated to validate the approach: simultaneous gradient identification, gradient frequency dependency, and repeatability. This report describes the flight test results. These data demonstrate that the approach can accurately identify performance gradients during simultaneous control excitation independent of excitation frequency.

Schkolnik, Gerard S.↗

GPS inferred geocentric reference frame for satellite positioning and navigation

Accurate geocentric three-dimensional positioning is of great importance for various geodetic and oceanographic applications. While relative positioning accuracy of a few centimeters has become a reality using Very Long Baseline Interferometry (VLBI), the uncertainty in the offset of the adopted coordinate system origin from the geocenter is still believed to be of the order of one meter. Satellite Laser Ranging (SLR) is capable of determining this offset to better than 10 cm, though, because of the limited number of satellites, this requires a long arc of data. The Global Positioning System (GPS) measurements provide a powerful alternative for an accurate determination of this origin offset in relatively short period of time. Two strategies are discussed, the first utilizes the precise relative positions predetermined by VLBI, whereas the second establishes a reference frame by holding only one of the tracking sites longitude fixed. Covariance analysis studies indicate that geocentric positioning to an accuracy of a few centimeters can be achieved with just one day of precise GPS pseudorange and carrier phase data.

Malla, Rajendra P.↗

A case study of the cusp electrodynamics by the Aureol-3 satellite - Evidence for FTE signatures?

Particle and field data from a pass of the Aureol-3 satellite through the polar cusp, several minutes after the southward turning of the IMF, are analyzed in detail. Superposed on the classical cusp, characterized by the typical ion and electron precipitations, several very narrow arcs are detected where large fluxes of electrons and ions, accelerated to 2-4 keV, precipitate simultaneously. These localized arcs correspond to the upward current sheets of a succession in latitude of narrow, alternatively upward and downward field-aligned current sheets. The data suggest that the satellite has crossed the ionospheric footprints of 2 adjacent flux transfer events separated by 100-150 km in latitude. Electric spikes and electromagnetic turbulence are typically associated with the region of downward currents.

Bosqued, Jean M.↗

Three-dimensional organization of otolith-ocular reflexes in rhesus monkeys. III. Responses To translation

The three-dimensional (3-D) properties of the translational vestibulo-ocular reflexes (translational VORs) during lateral and fore-aft oscillations in complete darkness were studied in rhesus monkeys at frequencies between 0.16 and 25 Hz. In addition, constant velocity off-vertical axis rotations extended the frequency range to 0.02 Hz. During lateral motion, horizontal responses were in phase with linear velocity in the frequency range of 2-10 Hz. At both lower and higher frequencies, phase lags were introduced. Torsional response phase changed more than 180 degrees in the tested frequency range such that torsional eye movements, which could be regarded as compensatory to "an apparent roll tilt" at the lowest frequencies, became anticompensatory at all frequencies above approximately 1 Hz. These results suggest two functionally different frequency bandwidths for the translational VORs. In the low-frequency spectrum (<<0.5 Hz), horizontal responses compensatory to translation are small and high-pass-filtered whereas torsional response sensitivity is relatively frequency independent. At higher frequencies however, both horizontal and torsional response sensitivity and phase exhibit a similar frequency dependence, suggesting a common role during head translation. During up-down motion, vertical responses were in phase with translational velocity at 3-5 Hz but phase leads progressively increased for lower frequencies (>90 degrees at frequencies <0.2 Hz). No consistent dependence on static head orientation was observed for the vertical response components during up-down motion and the horizontal and torsional response components during lateral translation. The frequency response characteristics of the translational VORs were fitted by "periphery/brain stem" functions that related the linear acceleration input, transduced by primary otolith afferents, to the velocity signals providing the input to the velocity-to-position neural integrator and the oculomotor plant. The lowest-order, best-fit periphery/brain stem model that approximated the frequency dependence of the data consisted of a second order transfer function with two alternating poles (at 0.4 and 7.2 Hz) and zeros (at 0.035 and 3.4 Hz). In addition to clearly differentiator dynamics at low frequencies (less than approximately 0.5 Hz), there was no frequency bandwidth where the periphery/brain stem function could be approximated by an integrator, as previously suggested. In this scheme, the oculomotor plant dynamics are assumed to perform the necessary high-frequency integration as required by the reflex. The detailed frequency dependence of the data could only be precisely described by higher order functions with nonminimum phase characteristics that preclude simple filtering of afferent inputs and might be suggestive of distributed spatiotemporal processing of otolith signals in the translational VORs.

Non-NASA Center↗

Paths Forward for Nuclear Energy: Using a Nationwide Post-Stratified Hierarchical Model to Facilitate Matching of New Nuclear Technologies to Receptive Host Communities

This project was a collaboration between the University of Oklahoma (OU) and the University of Michigan (UMich). The overall objective of the project was to address a critical problem facing the siting of nuclear facilities, where there is no mechanism for incorporating public attitudes at a state and local level into decision-making. Utilizing recent advances in data modeling over local spatial scales, the research team created a state and county level map of public attitudes towards nuclear energy. Current estimates for public acceptance of nuclear technologies primarily exists on a national level, and sub-national estimates of public opinion about reactor siting, research facilities, transport routes, or storage and disposal facilities are very scarce. Model results from this project provide a systematic basis for technology developers to evaluate public acceptance across alternative siting options as a critical component for weighing potential benefit-cost tradeoffs for alternative paths to deploy new nuclear facilities. The project utilized data from the largest database of nuclear attitudes in the US, coupled with Census and elections-related data as well as data on social vulnerability and proximity to current nuclear facilities. In addition to modeling public support, the team also developed an interactive map to showcase results, using an online tool called Public and Local Attitudes about Nuclear Energy Technologies (PLANET). The tool allows technology developers and stakeholders to interact with the model results and better understand variation in support for nuclear facility siting on a state and county level. The interactive nature of the tool also allows users to analyze results in a targeted way, by comparing levels of support across different states and/or counties as desired.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Lead exposure in young children over a 5-year period from urban environments using alternative exposure measures with the US EPA IEUBK model – A trial

Highlights: • IEUBK simulations of soil with petri dish dust (PDD), soil with handwipes, sweepings with PDD, sweepings with wipes. • Predicted blood lead levels (PbB) generally give good agreement with observed PbB in spite of differences in intake units for PDD and handwipes. • Analyses with dust loadings converted to concentration give higher predicted PbB. • Simulations on aggregated data for each child give similar results to age-stratified data. • Estimating house dust Pb from measured soil Pb concentrations (in the absence of measured house dust concentrations) results in over-prediction of PbB. The US Environmental Protection Agency (EPA) Integrated Exposure Uptake Biokinetic (IEUBK) model has been widely used to predict blood lead (PbB) levels in children especially around industrial sites. Exposure variables have strongly focussed on the major contribution of lead (Pb) in soil and interior dust to total intake and, in many studies, site-specific data for air, water, diet and measured PbB were not available. We have applied the IEUBK model to a comprehensive data set, including measured PbB, for 108 children monitored over a 5-year period in Sydney, New South Wales, Australia. To use this data set, we have substituted available data (with or without modification) for standard inputs as needed. For example, as an alternative measure for soil Pb concentration (μg/g), we have substituted exterior dust sweepings Pb concentration (μg/g). As alternative measures for interior dust Pb concentration (μg/g) we have used 1) 30-day cumulative petri dish deposition data (PDD) (as µg Pb/m{sup 2}/30days), or 2) hand wipe data (as μg Pb/hand). For comparison, simulations were also undertaken with estimates of dust Pb concentration derived from a prior regression of dust Pb concentration (μg/g) on dust Pb loading (μg/ft{sup 2}) as concentration is the unit specified for the Model. Simulations for each subject using observed data aggregated over the 5-year interval of the study, the most usual application of the IEUBK model, showed using Wilcoxon tests that there was a significant difference between the observed values and the values predicted by the Model containing soil with hand wipes (p < 0.001), and soil and PDD (p = 0.026) but not those for the other two sets of predictors, based on sweepings and PDD or sweepings and wipes. Overall, simulations of the Model using alternative exposure measures of petri dish dust (and possibly hand wipes) instead of vacuum cleaner dust and dust sweepings instead of soil provide predicted PbB which are generally consistent with each other and observed values. The predicted geometric mean PbBs were 2.17 ( ± 1.24) μg/dL for soil with PDD, 1.95 ( ± 1.17) μg/dL for soil with hand wipes, 2.36 ( ± 1.75) μg/dL for sweepings with PDD, and 2.15 ( ± 1.69) for sweepings with hand wipes. These results are in good agreement with the observed geometric mean PbB of 2.46 ( ± 0.99) μg/dL. In contrast to all other IEUBK model studies to our knowledge, we have stratified the data over the age ranges from 1 to 5 years. The median of the predicted values was lower than that for the observed values for every combination of age and set of measures; in some cases, the difference was statistically significant. The differences between observed and predicted PbB tended to be greatest for the soil plus wipes measure and for the oldest age group. Use of ‘default dust’ values calculated from the site-specific soil values, a common application of the IEUBK model, results in predicted PbB about 22% (range 0 to 52%) higher than those from soil with PDD data sets. Geometric mean contributions estimated from the Model to total Pb intake for a child aged 1–2 years was 0.09% for air, 42% for diet, 5.3% for water and 42% for soil and dust. Our results indicate that it is feasible to use alternative measures of soil and dust exposure to provide reliable predictions of PbB in urban environments.

54 ENVIRONMENTAL SCIENCES↗

NASA GLDAS Evapotranspiration Data and Climatology

Evapotranspiration (ET) is the water lost to the atmosphere by evaporation and transpiration. ET is a shared component in the energy and water budget, therefore, a critical variable for global energy and water cycle and climate change studies. However, direct ET measurements and data acquisition are difficult and expensive, especially at the global level. Therefore, modeling is one common alternative for estimating ET. With the goal to generate optimal fields of land surface states and fluxes, the Global Land Data Assimilation System (GLDAS) has been generating quality-controlled, spatially and temporally consistent, terrestrial hydrologic data, including ET and other variables that affect evaporation and transpiration, such as temperature, precipitation, humidity, wind, soil moisture, heat flux, and solar radiation. This poster presents the long-term ET climatology (mean and monthly), derived from the 61-year GLDAS-2 monthly 1.0 deg x 1.0 deg. NOAH model Experiment-1 data, and describes the basic characteristics of spatial and seasonal variations of the climatology. The time series of GLDAS-2 precipitation and radiation, and ET are also discussed to show the improvement of GLDAS-2 forcing data and model output over those from GLDAS-1.

Rui, Hualan↗