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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

DEMOS (Demographic Microsimulator Tool for Longitudinal Synthetic Population) [SWR-25-135] related to NLR SWR-26-076

The Demographic Microsimulator (DEMOS) is an agent-based simulation framework used to model the evolution of population demographic characteristics and lifecycle events, such as education attainment, marital status, and other key transitions. DEMOS modules are designed to capture the interdependencies between short-term and long-term lifecycle events, which are often influential in downstream transportation and land-use modeling. A key feature of DEMOS is its ability to track changes in an agent’s demographic status from year t to year t + 1. This structure allows the model to evolve populations over any user-defined time horizon. As a result, DEMOS is well suited for analyzing medium- and long-term transportation-related decisions, including household vehicle transactions (e.g., purchasing, selling, or replacing vehicles) and work location choices. Core features of DEMOS include the modeling of more than ten lifecycle events, behaviorally realistic patterns informed by long-running panel data, explicit representation of interdependencies among lifecycle processes, and a flexible, modular simulation architecture. A technical memorandum describing DEMOS is available here. The memorandum provides an overview of the framework’s functionality, model structure, input and output data, and its applications in transportation planning and broader policy analysis contexts. Interested readers are also encouraged to consult the paper listed below for additional details on the DEMOS methodology. Sun, Bingrong, Shivam Sharda, Venu M. Garikapati, Mohamed Amine Bouzaghrane, Juan Caicedo, Srinath Ravulaparthy, Isabel Viegas de Lima, Ling Jin, C. Anna Spurlock, and Paul Waddell. "Demographic Microsimulator for Integrated Urban Systems: Adapting Panel Survey of Income Dynamics to Capture the Continuum of Life." Transportation Research Record (2025): 03611981251333339.

Sun, Bingrong [National Laboratory of the Rockies ↗
NASA NTRS2015

Decomposition of Sources of Errors in Seasonal Streamflow Forecasting over the U.S. Sunbelt

Seasonal streamflow forecasts, contingent on climate information, can be utilized to ensure water supply for multiple uses including municipal demands, hydroelectric power generation, and for planning agricultural operations. However, uncertainties in the streamflow forecasts pose significant challenges in their utilization in real-time operations. In this study, we systematically decompose various sources of errors in developing seasonal streamflow forecasts from two Land Surface Models (LSMs) (Noah3.2 and CLM2), which are forced with downscaled and disaggregated climate forecasts. In particular, the study quantifies the relative contributions of the sources of errors from LSMs, climate forecasts, and downscaling/disaggregation techniques in developing seasonal streamflow forecast. For this purpose, three month ahead seasonal precipitation forecasts from the ECHAM4.5 general circulation model (GCM) were statistically downscaled from 2.8deg to 1/8deg spatial resolution using principal component regression (PCR) and then temporally disaggregated from monthly to daily time step using kernel-nearest neighbor (K-NN) approach. For other climatic forcings, excluding precipitation, we considered the North American Land Data Assimilation System version 2 (NLDAS-2) hourly climatology over the years 1979 to 2010. Then the selected LSMs were forced with precipitation forecasts and NLDAS-2 hourly climatology to develop retrospective seasonal streamflow forecasts over a period of 20 years (1991-2010). Finally, the performance of LSMs in forecasting streamflow under different schemes was analyzed to quantify the relative contribution of various sources of errors in developing seasonal streamflow forecast. Our results indicate that the most dominant source of errors during winter and fall seasons is the errors due to ECHAM4.5 precipitation forecasts, while temporal disaggregation scheme contributes to maximum errors during summer season.

Decomposition↗
DOE OSTI2017

Vegetation Demographics in Earth System Models: a review of progress and priorities

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Influences of North Pacific Ocean Domain Extent on the Western U.S. Winter Hydroclimatology in Variable-Resolution CESM

Variable-resolution global climate models (VRGCMs) are a dynamical downscaling method that can reach spatiotemporal scales needed for regional climate assessments. Over the years, several users of VRGCMs have assumed where the location and extent of the refinement domain should be based on knowledge of the prevailing storm tracks and resolution dependence of important regional climate processes (e.g., atmospheric rivers [ARs] and orographic uplift), but the effect of high-resolution domain size and extent on the simulation of downstream hydroclimatic phenomena has not been systematically evaluated. Here, we use variable resolution in the Community Earth System Model (VR-CESM) to perform such a test. To do this, three VR-CESM grids were generated that span the entire, two thirds, and one third of the North Pacific and evaluated for a 30-year climatology using Atmospheric Model Intercomparison Project protocols. Simulations are compared with reanalysis products offshore (fifth-generation of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis [ERA5]) and onshore (Livneh, 2015, https://doi.org/10.1038/sdata.2015.42, and Parameter-elevation Regressions on Independent Slopes Model [PRISM]) of the western United States. The westward expansion of refinement domain influenced integrated vapor transport (IVT), which was generally high biased but minimally impacted AR characteristics. Due to slight differences in landfalling AR counts in the western United States, California winter precipitation generally improved with westward expansion of the refinement domain. Western U.S. mountain snowpack and surface temperatures were insensitive to refinement domain size and were more influenced by changes in topographic resolution and/or land surface model version. Here, given minimal dependence of simulated western U.S. hydroclimate on refinement domain size over the North Pacific, we advise future VR-CESM studies to focus grid resolution on better resolving land surface heterogeneity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Mars Exploration Rover airbag landing loads testing and analsysis

This paper presents a summary of the testing and analysis used to quantify the expected airbag landing loads for the Mars Exploration Rovers. The airbag drop test setup, lander instrumentation, and the test data reduction method are discussed in order to provide an understanding of the empirical loads. A set of limiting cases that bound the empirical data are developed for use in finite element modeling of the lander and rover models.

modeling↗
NASA NTRS1995

Advanced Short Takeoff and Vertical Landing (ASTOVL) Concepts Tested

In this cooperative program between NASA, Lockheed Corporation, and the Advanced Research and Projects Agency (ARPA), an advanced short takeoff and vertical landing (ASTOVL) model was tested in the 9- by 15-Foot Low-Speed Wind Tunnel at the NASA Lewis Research Center. The 10-percent scaled model was tested over a range of headwind velocities from 25 to 120 kn. This inlet/forebody test was a key part of an important Department of Defense program investigation enabling technologies for future high-performance ASTOVL aircraft. The Lockheed concept is focused on a shaft-coupled lift fan system centered around Pratt & Whitney's F119 power plant. As envisioned, a conventional takeoff and landing version (CTOL) would replace the U.S. Air Force's F-16's. The ASTOVL version would eventually replace Marine and, possibly, British Harrier aircraft. The ASTOVL and CTOL versions are scheduled to begin their manufacturing development phases in 2000. The purpose of this test was to acquire data pertinent to the inlet-forebody model. The test was very successful. Both steady-state and dynamic data were obtained. This small-scale testing, which is directed at reducing risks, may greatly reduce the risks on a full-scale aircraft.

Source record↗
DOE OSTI2023

Short-term variation in leaf-level water use efficiency in a tropical forest

Here we report the representation of stomatal regulation of transpiration and CO 2 assimilation is key to forecasting terrestrial ecosystem responses to global change. Given its importance in determining the relationship between forest productivity and climate, accurate and mechanistic model representation of the relationship between stomatal conductance (g s ) and assimilation is crucial. We assess possible physiological and mechanistic controls on the estimation of the g 1 (stomatal slope, inversely proportional to water use efficiency) and g 0 (stomatal intercept) parameters, using diurnal gas exchange surveys and leaf level response curves of six tropical broadleaf evergreen tree species. g 1 estimated from ex-situ response curves averaged 50% less than g 1 estimated from survey data. While g 0 and g 1 varied between leaves of different phenological stages, the trend was not consistent among species. We identified a diurnal trend associated with g 1 and g 0 that significantly improved model projections of diurnal trends in transpiration. The accuracy of modelled g s can be improved by accounting for variation in stomatal behavior across diurnal periods, and between measurement approaches, rather than focusing on phenological variation in stomatal behavior. Additional investigation into the primary mechanisms responsible for diurnal variation in g 1 will be required to account for this phenomena in land surface models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Using NASA's Remote Sensing Datasets and Land Information System to Characterize Lightning Initiated Wildfires

Can we use modeled information of the land surface and characteristics of lightning beyond flash occurrence to increase the identification and prediction of wildfires? The goals of this study are to: combine observed cloud-to-ground (CG) flashes with real-time land surface model output; and compare data with areas where lightning did not start a wildfire to determine what land surface conditions, rainfall observations, and lightning characteristics were responsible for causing wildfires.

White, Kristopher↗
NASA NTRS2002

The Impact of Soil Moisture Initialization On Seasonal Precipitation Forecasts

Some studies suggest that the proper initialization of soil moisture in a forecasting model may contribute significantly to the accurate prediction of seasonal precipitation, especially over mid-latitude continents. In order for the initialization to have any impact at all, however, two conditions must be satisfied: (1) the initial soil moisture anomaly must be "remembered" into the forecasted season, and (2) the atmosphere must respond in a predictable way to the soil moisture anomaly. In our previous studies, we identified the key land surface and atmospheric properties needed to satisfy each condition. Here, we tie these studies together with an analysis of an ensemble of seasonal forecasts. Initial soil moisture conditions for the forecasts are established by forcing the land surface model with realistic precipitation prior to the start of the forecast period. As expected, the impacts on forecasted precipitation (relative to an ensemble of runs that do not utilize soil moisture information) tend to be localized over the small fraction of the earth with all of the required land and atmosphere properties.

Koster, R. D.↗
NASA NTRS1999

Simulation of 1986 South China Sea Monsoon with a Regional Climate Model

A Regional Land-Atmosphere Climate Simulation System (RELACS) project is being developed at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes and in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water/energy cycles in the IndoChina/South China Sea (SCS) region. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. The original MM5 model (without PLACE) includes the option for either a simple slab soil model or a five-layer soil model (MRF) in which the soil moisture availability evolves over time. However, the MM5 soil models do not include the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are precluded. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. In addition, the Penn State/NCAR MM5 atmospheric modeling system has been: (1) coupled to the Goddard Ice Microphysical scheme; (2) coupled to a turbulent kinetic energy (TKE) scheme; (3) modified to ensure cloud budget balance; and (4) incorporated initialization with the Goddard EOS data sets at NASA/Goddard Laboratory for Atmospheres. The improved MM5 with two nested domains (60 and 20 km horizontal resolution) was used to simulate convective activity over IndoChina and the South China Sea, during the monsoon season, from May 6 to May 20, 1986. The model results captured several dominant observed features, such as twin cyclones, a depression system over the Bay of Bengal, strong south-westerly winds over IndoChina before and during the on-set of convection over the SCS, and a vortex over the SCS. Two additional MM5 runs with different land process models, Blackadar and MRF, were performed, and their results are compared to the run with PLACE. The preliminary results indicate that the MM5 results using PLACE and Blackadar are in very good agreement, but the results using MRF do not contain the south-westerly wind over IndoChina prior to the on-set of convection over the SCS.

Tao, W. -K.↗
DOE OSTI2016

Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009

A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO 2 and CH 4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3 m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8 × 10 3 km 2 yr –1 ). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954 Tg C yr –1 between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO 2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982–2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. Furthermore, to improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.

58 GEOSCIENCES↗
NASA NTRS1983

Simulation of terrain effects using a mesoscale mixed-layer model

The model discussed here is described in the study by Han et al. (1982) and is based on the shallow-water equations. It is noted that the mixed layer is another name for the earth's turbulent boundary layer when the latter is well stirred vertically, as under typical daytime conditions over land. The model abbreviates the vertical resolution by using only one and one-half layers; in this way, the computer power can be concentrated on the horizontal resolution of topographic effects. It is found that a steady flow pattern evolves over terrain when steady forcing occurs in the absence of surface heating or mixed-layer entrainment and that this simplification is removed when surface heating and entrainment do occur. While these findings are regarded as interesting, it is believed that they may be model dependent. The pressure adjustments upon the mixed layer caused by air movements above the mixed layer may be sufficient to preclude the evolution of a steady state on the mesoscale, even under the most ideal conditions.

Deardorff, J. W.↗
NASA NTRS2004

Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. The availability of global albedo data over a large range of spectral channels and at high spatial resolution has dramatically improved with the launch of the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard NASA s Earth Observing System (EOS) Terra spacecraft in December 1999. However, lack of spatial and temporal coverage due to cloud and snow effects can preclude utilization of official products in production and research studies. We report on a technique used to fill incomplete MOD43 albedo data sets with the intention of providing complete value-added maps. The technique is influenced by the phenological concept that within a certain area, a pixel s ecosystem class should exhibit similar growth cycle events over the same time period. The shape of an area s phenological temporal curve can be imposed upon existing pixel-level data to fill missing temporal points. The methodology will be reviewed by showcasing 2001 global and regional results of complete albedo and NDVl data sets.

Moody, E. G.↗
NASA NTRS2004

Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent observations of diffuse bihemispherical (white-sky) and direct beam directional hemispherical (black-sky ) land surface albedo included in the MOD43B3 product from MODIS instruments aboard NASA's Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal characteristics. Cloud and seasonal snow cover, however, curtail retrievals to approximately half the global land surfaces on an annual equal-angle basis, precluding MOD43B3 albedo products from direct inclusion in some research projects and production environments.

Moody, Eric G.↗
NASA NTRS2022

L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation and Soil Salinity

The Dry Chaco in South America is a semi-arid ecoregion prone to dryland salinization. In this region, we investigated coarse-scale surface soil moisture (SM), soil temperature, soil salinity and vegetation, using L-band microwave brightness temperature (TB) observations and retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite missions, Catchment Land Surface Model (CLSM) simulations, and in situ measurements within 26 sampled satellite pixels. Across these 26 sampled pixels, the satellite-based SM outperformed CLSM SM compared to field data, and forward L-band TB simulations derived from in situ SM and temperature performed better than those derived from CLSM estimates relative to SMOS TB observations. The surface salinity for the sampled pixels was on average only 4 mg/g and only locally influenced the TB simulations, when including salinity in the dielectric mixing model of the forward radiative transfer model (RTM) simulations. To explore the potential of retrieving salinity together with other RTM parameters to optimize TB simulations over the entire Dry Chaco, the RTM was inverted using 10 years of multi-angular SMOS TB data and constraints of CLSM SM and temperature. However, the latter modeled SM was not sufficiently accurate and factors such as open surface water were missing in the background constraints, so that the salinity retrievals effectively represented a bulk correction of the dielectric constant, rather than salinity per se. However, the retrieval of vegetation, scattering albedo and surface roughness resulted in realistic values.

L-Band↗
DOE OSTI2017

Developing a molecular picture of soil organic matter–mineral interactions by quantifying organo–mineral binding

Long residence times of soil organic matter have been attributed to reactive mineral surface sites that sorb organic species and cause inaccessibility due to isolation and chemical stabilization at the organic-mineral interface. Instrumentation for probing this interface is limited. As a result, much of the micron- and molecular-scale knowledge about organic-mineral interactions remains largely qualitative. We report the use of force spectroscopy to directly measure the binding between organic ligands with known chemical functionalities to soil minerals in aqueous environments. By systematically studying the role of organic functional group chemistry with model minerals, we demonstrate that the chemistry of both the organic ligand and mineral contribute to values of binding free energy and that changes in pH and ionic strength produce significant differences in binding energies. These direct measurements of molecular binding provide mechanistic insights into organo-mineral interactions, which could potentially inform land-carbon models that explicitly include mineral-bound C pools.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2021

Contribution of Meteorological Downscaling to Skill and Precision of Seasonal Drought Forecasts

Research in meteorological prediction on sub-seasonal to seasonal (S2S) timescales has seen growth in recent years. Concurrent with this, demand for seasonal drought forecasting has risen. While there is obvious synergy between these fields, S2S meteorological forecasting has typically focused on low resolution global models, while the development of drought can be sensitive to the local expression of weather anomalies and their interaction with local surface properties and processes. This suggests that downscaling might play an important role in the application of meteorological S2S forecasts to skillful forecasting of drought. Here, we apply the Generalized Analog Regression Downscaling (GARD) algorithm to downscale meteorological hindcasts from the NASA Goddard Earth Observing System (GEOS) global S2S forecast system. Downscaled meteorological fields are then applied to drive offline simulations with the Catchment Land Surface Model (CLSM) to forecast United States Drought Monitor (USDM) style drought indicators derived from simulated surface hydrology variables. We compare the representation of drought in these downscaled hindcasts to hindcasts that are not downscaled, using the North American Land Data Assimilation System Phase 2 (NLDAS-2) dataset as an observational reference. We find that downscaling using GARD improves hindcasts of temperature and temperature anomalies, but the results for precipitation are mixed and generally small. Overall, GARD downscaling led to improved hindcast skill for total drought across the Contiguous United States (CONUS), and improvements were greatest for extreme (D3) and exceptional (D4) drought categories.

Ryan A Zamora↗
NASA NTRS2012

Integrated Modeling of Aerosol, Cloud, Precipitation and Land Processes at Satellite-Resolved Scales

In this talk, I will present recent results from a project led at NASA/GSFC, in collaboration with NASA/MSFC and JHU, focused on the development and application of an observation-driven integrated modeling system that represents aerosol, cloud, precipitation and land processes at satellite-resolved scales. The project, known as the NASA Unified WRF (NU-WRF), is funded by NASA's Modeling and Analysis Program, and leverages prior investments from the Air Force Weather Agency and NASA's Earth Science Technology Office (ESTO). We define "satellite-resolved" scales as being within a typical mesoscale atmospheric modeling grid (roughly 1-25 km), although this work is designed to bridge the continuum between local (microscale), regional (mesoscale) and global (synoptic) processes. NU-WRF is a superset of the standard NCAR Advanced Research WRF model, achieved by fully integrating the GSFC Land Information System (LIS, already coupled to WRF), the WRF/Chem enabled version of the Goddard Chemistry Aerosols Radiation Transport (GOCART) model, the Goddard Satellite Data Simulation Unit (SDSU), and boundary/initial condition preprocessors for MERRA and GEOS-5 into a single software release (with source code available by agreement with NASA/GSFC). I will show examples where the full coupling between aerosol, cloud, precipitation and land processes is critical for predicting local, regional, and global water and energy cycles, including some high-impact phenomena such as floods, hurricanes, mesoscale convective systems, droughts, and monsoons.

Peters-Lidard, Christa↗