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At least 1,135 records · Page 63

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DOE OSTI2020

The Land Sparing, Water Surface Use Efficiency, and Water Surface Transformation of Floating Photovoltaic Solar Energy Installations

Floating photovoltaic solar energy installations (FPVs) represent a new type of water surface use, potentially sparing land needed for agriculture and conservation. However, standardized metrics for the land sparing and resource use efficiencies of FPVs are absent. These metrics are critical to understanding the environmental and ecological impacts that FPVs may potentially exhibit. Here, we compared techno-hydrological and spatial attributes of four FPVs spanning different climatic regimes. Next, we defined and quantified the land sparing and water surface use efficiency (WSUE) of each FPV. Lastly, we coined and calculated the water surface transformation (WST) using generation data at the world’s first FPV (Far Niente Winery, California). The four FPVs spare 59,555 m2 of land and have a mean land sparing ratio of 2.7:1 m2 compared to ground-mounted PVs. Mean direct and total capacity-based WSUE is 94.5 ± 20.1 SD Wm−2 and 35.2 ± 27.4 SD Wm−2, respectively. Direct and total generation-based WST at Far Niente is 9.3 and 13.4 m2 MWh−1 yr−1, respectively; 2.3 times less area than ground-mounted utility-scale PVs. Our results reveal diverse techno-hydrological and spatial attributes of FPVs, the capacity of FPVs to spare land, and the utility of WSUE and WST metrics.

14 SOLAR ENERGY↗

DOE OSTI2024

Beyond the visible: Accounting for ultraviolet and far‐red radiation in vegetation productivity and surface energy budgets

Photosynthetically active radiation (PAR) is typically defined as light with a wavelength within 400–700 nm. However, ultra-violet (UV) radiation within 280–400 nm and far-red (FR) radiation within 700–750 nm can also excite photosystems, though not as efficiently as PAR. Vegetation and land surface models (LSMs) typically do not explicitly account for UV's contribution to energy budgets or photosynthesis, nor FR's contribution to photosynthesis. However, whether neglecting UV and FR has significant impacts remains unknown. Here, we explored how canopy radiative transfer (RT) and photosynthesis are impacted when explicitly implementing UV in the canopy RT model and accounting for UV and FR in the photosynthesis models within a next-generation LSM that can simulate hyperspectral canopy RT. We validated our improvements using photosynthesis measurements from plants under different light sources and intensities and surface reflection from an eddy-covariance tower. Our model simulations suggested that at the whole plant level, after accounting for UV and FR explicitly, chlorophyll content, leaf area index (LAI), clumping index, and solar radiation all impact the modeling of gross primary productivity (GPP). At the global scale, mean annual GPP within a grid would increase by up to 7.3% and the increase is proportional to LAI; globally integrated GPP increases by 4.6 PgC year −1 (3.8% of the GPP without accounting for UV + FR). Further, using PAR to proxy UV could overestimate surface albedo by more than 0.1, particularly in the boreal forests. Our results highlight the importance of improving UV and FR in canopy RT and photosynthesis modeling and the necessity to implement hyperspectral or multispectral canopy RT schemes in future vegetation and LSMs.

energy budget↗

NASA NTRS1964

Surface albedo of land and sea in the arctic

Surface albedo of land and sea in arctic

ALBEDO↗

NASA NTRS2005

Simulating Descent and Landing of a Spacecraft

The Dynamics Simulator for Entry, Descent, and Surface landing (DSENDS) software performs high-fidelity simulation of the Entry, Descent, and Landing (EDL) of a spacecraft into the atmosphere and onto the surface of a planet or a smaller body. DSENDS is an extension of the DShell and DARTS programs, which afford capabilities for mathematical modeling of the dynamics of a spacecraft as a whole and of its instruments, actuators, and other subsystems. DSENDS enables the modeling (including real-time simulation) of flight-train elements and all spacecraft responses during various phases of EDL. DSENDS provides high-fidelity models of the aerodynamics of entry bodies and parachutes plus supporting models of atmospheres. Terrain and real-time responses of terrain-imaging radar and lidar instruments can also be modeled. The program includes modules for simulation of guidance, navigation, hypersonic steering, and powered descent. Automated state-machine-driven model switching is used to represent spacecraft separations and reconfigurations. Models for computing landing contact and impact forces are expected to be added. DSENDS can be used as a stand-alone program or incorporated into a larger program that simulates operations in real time.

Balaram, J.↗

DOE OSTI2026

Evapotranspiration partitioning estimates from 8 methods from 47 NEON sites, 2019-2021

This dataset provides daily estimates of evapotranspiration (ET) and the transpiration-to-evapotranspiration ratio (T/ET) across 47 terrestrial National Ecological Observatory Network (NEON) sites spanning diverse environmental and biome conditions in the United States across three years of data (2019-2021). Daily ET is reported in both energy units (MJ m⁻² day⁻¹) and equivalent water depth (mm day⁻¹), assuming a constant latent heat of vaporization of 2.45 MJ/kg. The primary method uses a hybrid recurrent neural network–Penman–Monteith framework (RNN-PM), which integrates physically based surface energy balance constraints with data-driven learning to partition ET into transpiration and evaporation components. Model inputs include in situ meteorological observations (air temperature, vapor pressure deficit, wind speed, and radiation) combined with satellite-derived land surface temperature, leaf area index, and soil moisture. For benchmarking and uncertainty assessment, T/ET estimates from seven additional models are included: Priestley-Taylor Jet Propulsion Laboratory (PT-JPL), Penman-Monteith (P-M), Two-Source Energy Balance (TSEB), Support Vector Regression (SVR), and Categorical Boosting (CatBoost), among others—spanning empirical, machine-learning, and process-based approaches (see methods section or linked publication for detailed descriptions). Data Package Contents: The dataset a csv files containing daily ET and T/ET estimates for each site and model, along with associated metadata files these variables. Data can be accessed using common spreadsheet software (e.g., Microsoft Excel, LibreOffice) or programming environments such as R or Python. Together, these data support cross-site comparisons of ecosystem water use, evaluation of ET partitioning methods, and development of improved land–atmosphere exchange models.

EARTH SCIENCE > ATMOSPHERE↗

DOE OSTI2022

Representation of Leaf-to-Canopy Radiative Transfer Processes Improves Simulation of Far-Red Solar-Induced Chlorophyll Fluorescence in the Community Land Model Version 5

Recent advances in satellite observations of solar-induced chlorophyll fluorescence (SIF) provide a new opportunity to evaluate and constrain the simulation of terrestrial gross primary productivity (GPP). Accurate representation of the processes driving SIF emission and the radiative transfer of SIF to remote sensing sensors is an essential prerequisite for the evaluation and data assimilation. Recently, SIF simulations have been incorporated into several land surface models, but the scaling of SIF from leaf-level to canopy level is usually not well-represented. In this work, we incorporate the simulation of far-red SIF observed at nadir into the Community Land Model version 5 (CLM5). An efficient and accurate method based on escape probability is developed to scale SIF from leaf-level to top-of-canopy while taking clumping and the radiative transfer processes into account. SIF simulated by CLM5 and a canopy-level model agreed well at sites except one in needle leaf forest (R2>0.91, root-mean-square error < 0.19W m -2 sr -1 um -1 ), and captured the day-to-day variation of tower-measured SIF at temperate forest sites (R 2 >0.68). At the global scale, simulated SIF generally captured the spatial and seasonal pat37 terns of satellite-observed SIF (R2 > 0.76 except for tropical forest). Factors including the fluorescence emission model, clumping, bidirectional effect, and canopy properties (leaf optical properties and leaf area index) had considerable impacts on SIF simulation, and the discrepancies between simulated and observed SIF varied with plant functional type. By improving the representation of radiative transfer for SIF simulation, our model allows better comparisons between simulated and observed SIF towards constraining and evaluating GPP simulations.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1993

Estimation of continental precipitation recycling

The total amount of water that precipitates on large continental regions is supplied by two mechanisms: 1) advection from the surrounding areas external to the region and 2) evaporation and transpiration from the land surface within the region. The latter supply mechanism is tantamount to the recycling of precipitation over the continental area. The degree to which regional precipitation is supplied by recycled moisture is a potentially significant climate feedback mechanism and land surface-atmosphere interaction, which may contribute to the persistence and intensification of droughts. Gridded data on observed wind and humidity in the global atmosphere are used to determine the convergence of atmospheric water vapor over continental regions. A simplified model of the atmospheric moisture over continents and simultaneous estimates of regional precipitation are employed to estimate, for several large continental regions, the fraction of precipitation that is locally derived. The results indicate that the contribution of regional evaporation to regional precipitation varies substantially with location and season. For the regions studied, the ratio of locally contributed to total monthly precipitation generally lies between 0. 10 and 0.30 but is as high as 0.40 in several cases.

Brubaker, Kaye L.↗

NASA NTRS1967

Dynamic model investigation of touchdown stability of lunar-landing vehicles

Dynamic scale model of lunar module type spacecraft - overturn stability for nonlevel surface landings

SURFACE STABILITY↗

NASA NTRS2021

Drought Variability over the Conterminous United States for the past century

We examine the drought variability over the Conterminous United States (CONUS) for 1915-2018 using the Noah-MP land-surface model. We examine different model options on drought reconstruction including optional representation of groundwater and dynamic vegetation phenology. Over our 104-year reconstruction period, we identify 12 great droughts that each covered at least 36% of CONUS and lasted for at least 5 months. The great droughts tend to have smaller areas when groundwater and/or dynamic vegetation are included in the model configuration. We detect a small decreasing trend in dry area coverage over CONUS in all configurations. We identify 45 major droughts in the baseline (with a dry area coverage greater than 23.6% of CONUS) that are, on average, somewhat less severe than great droughts. We find that representation of groundwater tends to increase drought duration for both great and major droughts, primarily by leading to earlier drought onset (some due to short-lived recovery from a previous drought) or later demise (groundwater anomalies lag precipitation anomalies). In contrast, representation of dynamic vegetation tends to shorten major droughts duration, primarily due to earlier drought demise ( closed stoma or dead vegetation reduces ET loss during droughts). On a regional basis, the U.S. Southwest (Southeast) has the longest (shortest) major drought durations. Consistent with earlier work, dry area coverage in all subregions except the Southwest has decreased. The effects of groundwater and dynamic vegetation vary regionally due to differences in groundwater depths (hence connectivity with the surface) and vegetation types.

drought↗

NASA NTRS2001

Comparing the Degree of Land-Atmosphere Interaction in Four Atmospheric General Circulation Models

Land-atmosphere feedback, by which (for example) precipitation-induced moisture anomalies at the land surface affect the overlying atmosphere and thereby the subsequent generation of precipitation, has been examined and quantified with many atmospheric general circulation models (AGCMs). Generally missing from such studies, however, is an indication of the extent to which the simulated feedback strength is model dependent. Four modeling groups have recently performed a highly controlled numerical experiment that allows an objective inter-model comparison of land-atmosphere feedback strength. The experiment essentially consists of an ensemble of simulations in which each member simulation artificially maintains the same time series of surface prognostic variables. Differences in atmospheric behavior between the ensemble members then indicates the degree to which the state of the land surface controls atmospheric processes in that model. A comparison of the four sets of experimental results shows that feedback strength does indeed vary significantly between the AGCMs.

Koster, Randal D.↗

NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Robertson, F. R.↗

NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Robertson, F. R.↗

NASA NTRSDate not supplied

Improving the Use of Surface-Sensitive Radiances in the GMAO Hybrid-4DEnVar System

The planetary boundary layer (PBL) was designated as an incubation-class targeted observable (TO) in the 2018 Decadal Survey. As no single instrument source will provide enough information to constrain the global PBL, the assimilation of a wide range of observations in data assimilation (DA) systems will play a critical role, and GMAO has put in efforts to enhance surface-sensitive radiance assimilation. Although a vast number of microwave radiance observations are used in the GEOS global DA system, very few surface-sensitive radiances are currently used over land due to large uncertainty of land surface emissivity in the CRTM as well as cloud detection issue. Dynamically varying emissivity is retrieved from observations of window channels in the GEOS system for non-scattering FOVs and applied to sounding channel assimilation. Moreover, the original radiance bias correction is found not to work well over land, and shows drifting bias when the original emissivity sensitivity bias predictor with a dynamically varying emissivity retrieval is used. Hence, the radiance bias correction has been modified, and the quality control procedure has been adapted accordingly. Cycled experiment results show improvement in the temperature forecast at lower model levels; further refinement of this system continues.

Yanqiu Zhu↗

DOE OSTI2022

Surface temperatures reveal the patterns of vegetation water stress and their environmental drivers across the tropical Americas

Vegetation is a key component in the global carbon cycle as it stores ~450 GtC as biomass, and removes about a third of anthropogenic CO2 emissions. However, in some regions, the rate of plant carbon uptake is beginning to slow, largely because of water stress. Here, we develop a new observation-based methodology to diagnose vegetation water stress and link it to environmental drivers. We used the ratio of remotely sensed land surface to near surface atmospheric temperatures (LST/Tair) to represent vegetation water stress, and built regression tree models (random forests) to assess the relationship between LST/Tair and the main environmental drivers of surface energy fluxes in the tropical Americas. We further determined ecosystem traits associated with water stress and surface energy partitioning, pinpointed critical thresholds for water stress, and quantified changes in ecosystem carbon uptake associated with crossing these critical thresholds. Additionally, we found that the top drivers of LST/Tair, explaining over a quarter of its local variability in the study region, are (1) radiation, in 58% of the study region; (2) water supply from precipitation, in 30% of the study region; and (3) atmospheric water demand from vapor pressure deficits (VPD), in 22% of the study region. Regions in which LST/Tair variation is driven by radiation are located in regions of high aboveground biomass or at high elevations, while regions in which LST/Tair is driven by water supply from precipitation or atmospheric demand tend to have low species richness. Carbon uptake by photosynthesis can be reduced by up to 80% in water-limited regions when critical thresholds for precipitation and air dryness are exceeded simultaneously, that is, as compound events. Our results demonstrate that vegetation structure and diversity can be important for regulating surface energy and carbon fluxes over tropical regions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Upstream surface roughness and terrain are strong drivers of contrast in tornado potential between North and South America

Central North America is the global hotspot for tornadoes, fueled by elevated terrain of the Rockies to the west and a source of warm, moist air from equatorward oceans. This conventional wisdom argues that central South America, with the Andes to the west and Amazon basin to the north, should have a “tornado alley” at least as active as central North America. Central South America has frequent severe thunderstorms yet relatively few tornadoes. Here, we show that conventional wisdom is missing an important ingredient specific to tornadoes: a smooth, flat ocean-like upstream surface. Using global climate model experiments, we show that central South American tornado potential substantially increases if its equatorward land surface is smoothed and flattened to be ocean-like. Similarly, we show that central North American tornado potential substantially decreases if its equatorward ocean surface is roughened to values comparable to forested land. A rough upstream surface suppresses the formation of tornadic environments principally by weakening the poleward low-level winds, characterized by a weakened low-level jet east of the mountain range. Results are shown to be robust for any midlatitude landmass using idealized experiments with a simplified continent and mountain range. Our findings indicate that large-scale upstream surface roughness is likely a first-order driver of the strong contrast in tornado potential between North and South America.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Remote Sensing of Lineage Functional Types for Modeling and Monitoring Biodiversity

Hyperspectral remote sensing has the potential to continuously scale plant function and plant diversity information from landscape to global extents. Numerous studies have indicated that VSWIR (400-2500 nm) reflectance properties of vegetation capture evolutionarily conserved biochemical, structural, and other functional attributes of plant species. Spectral properties conserved in plants provide the opportunity to both 1) aggregate species into lineages with improved classification accuracy and 2) link those lineages directly to plant traits. Full realization of this goal will enable parameterization of Land Surface Models (LSMs) with remotely sensed information, e.g., canopy nitrogen, and better representations of biodiversity and functional diversity in biogeographic studies. In this study, we use hyperspectral AVIRIS data from the 2013 HyspIRI campaign over the Southern Sierra Nevada, California flight box to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from roughly 1372 surveys and a phylogeny representing 1361 species. We aggregate species into lineages ranging from species level groups down to similar number of Plant Functional Types as often used in LSMs. We assessed the ability of Random Forest and Partial Least Squares Discriminant Analysis to discriminate across these different phylogenetic scales and determine the optimal number of lineages to classify. Although there are some temporal and spatial differences in our training data, our best approaches achieved moderate classification accuracy (Kappa > 0.65). Given an optimal number of lineages, we explored approaches to improve classifications including machine learning and unmixing approaches. This work suggests that lineage-based methods may be a promising way to leverage the huge amounts of data that will come from high resolution and high return interval hyperspectral data planned for the Surface Biology and Geology mission with sparsely sampled existing ground-based ecological data.

Hyperspectral↗

NASA NTRS2013

The Response of the South Asian Summer Monsoon Circulation to Intensified Irrigation in Global Climate Model Simulations

Agricultural intensification in South Asia has resulted in the expansion and intensification of surface irrigation over the twentieth century. The resulting changes to the surface energy balance could affect the temperature contrasts between the South Asian land surface and the equatorial Indian Ocean, potentially altering the South Asian Summer Monsoon (SASM) circulation. Prior studies have noted apparent declines in the monsoon intensity over the twentieth century and have focused on how altered surface energy balances impact the SASM rainfall distribution. Here, we use the coupled Goddard Institute for Space Studies ModelE-R general circulation model to investigate the impact of intensifying irrigation on the large-scale SASM circulation over the twentieth century, including how the effect of irrigation compares to the impact of increasing greenhouse gas (GHG) forcing. We force our simulations with time-varying, historical estimates of irrigation, both alone and with twentieth century GHGs and other forcings. In the irrigation only experiment, irrigation rates correlate strongly with lower and upper level temperature contrasts between the Indian sub-continent and the Indian Ocean (Pearson's r = -0.66 and r = -0.46, respectively), important quantities that control the strength of the SASM circulation. When GHG forcing is included, these correlations strengthen: r = -0.72 and r = -0.47 for lower and upper level temperature contrasts, respectively. Under irrigated conditions, the mean SASM intensity in the model decreases only slightly and insignificantly. However, in the simulation with irrigation and GHG forcing, inter-annual variability of the SASM circulation decreases by *40 %, consistent with trends in the reanalysis products. This suggests that the inclusion of irrigation may be necessary to accurately simulate the historical trends and variability of the SASM system over the last 50 years. These findings suggest that intensifying irrigation, in concert with increased GHG forcing, is capable of reducing the variability of the simulated SASM circulation and altering the regional moisture transport by limiting the surface warming and reducing land-sea temperature gradients.

amplification↗

NASA NTRS2013

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.

Deep Blue↗