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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Changes in above- versus belowground biomass distribution in permafrost regions in response to climate warming

Permafrost regions contain approximately half of the carbon stored in land ecosystems and have warmed at least twice as much as any other biome. This warming has influenced vegetation activity, leading to changes in plant composition, physiology, and biomass storage in aboveground and belowground components, ultimately impacting ecosystem carbon balance. Yet, little is known about the causes and magnitude of long-term changes in the above- to belowground biomass ratio of plants (η). Here, in this study, we analyzed η values using 3,013 plots and 26,337 species-specific measurements across eight sites on the Tibetan Plateau from 1995 to 2021. Our analysis revealed distinct temporal trends in η for three vegetation types: a 17% increase in alpine wetlands, and a decrease of 26% and 48% in alpine meadows and alpine steppes, respectively. These trends were primarily driven by temperature-induced growth preferences rather than shifts in plant species composition. Our findings indicate that in wetter ecosystems, climate warming promotes aboveground plant growth, while in drier ecosystems, such as alpine meadows and alpine steppes, plants allocate more biomass belowground. Furthermore, we observed a threefold strengthening of the warming effect on η over the past 27 y. Soil moisture was found to modulate the sensitivity of η to soil temperature in alpine meadows and alpine steppes, but not in alpine wetlands. Our results contribute to a better understanding of the processes driving the response of biomass distribution to climate warming, which is crucial for predicting the future carbon trajectory of permafrost ecosystems and climate feedback.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

The Effect of Errors in Snow Assimilation on Land Surface Modeling

The accurate portrayal of the hydrological cycle is extremely important in land surface modeling. Central to this effort is the treatment of snow, as errors in the representation of this quantity can impact practically all other modeled quantities through alterations in the water and energy balances. Although land surface model (LSM) simulations can benefit from the assimilation of snow cover and snow depth observations, they can be negatively impacted if such observations contain errors or if a model bias exists in the simulation of surface or soil temperatures. Both cases may lead to excessive melting or growth of snow packs, and to large alterations in both the energy and water balances. Such problems in the snow assimilation process, made evident by the repeated melting and replenishing of snow pack over significant areas of the United States, exists in the Eta Data Assimilation System and is a product of the EDAS system's direct insertion assimilation of snow data. Occurring on a 24 hour cycle, the repeated melting infuses the soil column with a large quantity of water that upsets the hydrological cycle. In an effort to quantify the impacts of such errors in snow assimilation on water and energy budgets, a series of Mosaic LSM simulations were performed over the 12 month period covering October 1998 to October 1999.

Cosgrove, Brian A.↗
NASA NTRS1994

Snow hydrology in a general circulation model

A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.

Marshall, Susan↗
NASA NTRS2012

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

Reichle, Rolf H.↗
DOE OSTI2025

Mineral-Associated Organic Matter Concentration Beneath Northern Temperate Trees Varies by Mycorrhizal Type and Leaf Habit

Mycorrhizal fungi are important drivers of soil organic matter dynamics, but it can be difficult to isolate the effects of the fungi themselves from covarying traits of their host trees. For example, many trees with an evergreen leaf habit associate with ectomycorrhizal (ECM) fungi, while many deciduous tree species associate with arbuscular mycorrhizal (AM) fungi. Because leaf habit influences the quantity and quality of organic matter inputs to soil, it is often an important factor in soil carbon and nitrogen dynamics, and thus can mask the effects of mycorrhizal fungi on soil organic matter processes. We evaluated how tree mycorrhizal associations and leaf habit separately influence the amount and composition of mineral-associated organic matter (MAOM) and particulate organic matter (POM) in forest soils in New Hampshire and Vermont, USA. We measured carbon (C) and nitrogen (N) concentrations and C/N ratios of three soil density fractions beneath six tree species that vary in mycorrhizal association and leaf habit. We found lower concentrations of MAOM C and N beneath evergreen vs. deciduous trees, but only for tree species associating with AM fungi. Further, MAOM C/N was higher beneath evergreen trees and beneath trees with ECM fungi rather than AM fungi. Furthermore, these results add to the growing body of support for mycorrhizal fungi as mediators of soil organic matter dynamics, suggesting that the MAOM fraction is more sensitive to leaf habit beneath AM-associated versus ECM-associated trees. Because MAOM decomposition is thought to be less responsive than POM decomposition to changes in soil temperature and moisture, differences in the tendency of AM- and ECM-dominated forests to support MAOM formation and persistence may lead to systematic differences in the response of these forest types to ongoing climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Time-series RNA metabarcoding of the active Populus tremuloides root microbiome reveals hidden temporal dynamics and dormant core members

The rhizosphere is a critical interface between plant roots and soil, harboring diverse microbial communities that are essential to plant and ecosystem health. Although these communities exhibit stark temporal dynamics, their dormancy/activity transitions remain poorly understood. Such transitions may enable microbes to rapidly adjust functional contributions faster than community turnover alone would allow. Here, we used RNA metabarcoding to characterize the active fraction of microbial communities on the roots of quaking aspen (Populus tremuloides) in a time-series study across a natural environmental gradient. We explore cryptic temporal microbial community dynamics of rhizosphere communities at the ecosystem scale. The active rhizosphere bacterial and fungal communities were more temporally dynamic than total communities, while total communities exhibited a stronger response to site-specific conditions. Notably, some core microbiome members were often inactive, yielding a smaller “active core” subset. The fungal endophyte Hyaloscypha finlandica was the only microbe that was both present and active in all plots across all timepoints. Soil temperature strongly influenced both total and active community composition, with the fungal class Eurotiomycetes showing a temperature-dependent seasonal decline in abundance. Together, these results reveal that modulation of microbial activity levels is a key mechanism by which the plant root holobiont responds to environmental variation, and that even dominant symbionts may frequently persist in dormancy within the rhizosphere.

Community Structure and Diversity↗
NASA NTRS2015

Evaluation of Spaceborne L-band Radiometer Measurements for Terrestrial Freeze/Thaw Retrievals in Canada

The landscape freeze/thaw (FT) state has an important impact on the surface energy balance, carbon fluxes, and hydrologic processes; the timing of spring melt is linked to active layer dynamics in permafrost areas. L-band (1.4 GHz) microwave emission could allow the monitoring of surface state dynamics due to its sensitivity to the pronounced permittivity difference between frozen and thawed soil. The aim of this paper is to evaluate the performance of both Aquarius and Soil Moisture and Ocean Salinity (SMOS) L-band passive microwave measurements using a polarization ratio-based algorithm for landscape FT monitoring. Weekly L-band satellite observations are compared with a large set of reference data at 48 sites across Canada spanning three environments: tundra, boreal forest, and prairies. The reference data include in situ measurements of soil temperature (Tsoil) and air temperature (Tair), and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and snow cover area (SCA) products. Results show generally good agreement between Lband FT detection and the surface state estimated from four reference datasets. The best apparent accuracies for all seasons are obtained using Tair as the reference. Aquarius radiometer 2 (incidence angle of 39.6) data gives the best accuracies (90.8), while for SMOS the best results (87.8 of accuracy) are obtained at higher incidence angles (55- 60). The FT algorithm identifies both freeze onset and end with a delay of about one week in tundra and two weeks in forest and prairies, when compared to Tair. The analysis shows a stronger FT signal at tundra sites due to the typically clean transitions between consistently frozen and thawed conditions (and vice versa) and the absence of surface vegetation. Results in the prairies were poorer because of the influence of vegetation growth in summer (which decreases the polarization ratio) and the high frequency of ephemeral thaw events during winter. Freeze onset and end maps created from the same algorithm applied to SMOS and Aquarius measurements characterize similar FT patterns over Canada. This study shows the potential of using L-band spaceborne observations for FT monitoring, but underlines some limitations due to ice crusts in the snowpack, liquid water content in snow cover during the spring freeze to thaw transition, and vegetation growth.

soil freeze/thaw↗
DOE OSTI2024

Phenology of Photosynthesis in Winter‐Dormant Temperate and Boreal Forests: Long‐Term Observations From Flux Towers and Quantitative Evaluation of Phenology Models

Abstract We examined the seasonality of photosynthesis in 46 evergreen needleleaf (evergreen needleleaf forests (ENF)) and deciduous broadleaf (deciduous broadleaf forests (DBF)) forests across North America and Eurasia. We quantified the onset and end (Start GPP and End GPP ) of photosynthesis in spring and autumn based on the response of net ecosystem exchange of CO 2 to sunlight. To test the hypothesis that snowmelt is required for photosynthesis to begin, these were compared with end of snowmelt derived from soil temperature. ENF forests achieved 10% of summer photosynthetic capacity ∼3 weeks before end of snowmelt, while DBF forests achieved that capacity ∼4 weeks afterward. DBF forests increased photosynthetic capacity in spring faster (1.95% d −1 ) than ENF (1.10% d −1 ), and their active season length (End GPP –Start GPP ) was ∼50 days shorter. We hypothesized that warming has influenced timing of the photosynthesis season. We found minimal evidence for long‐term change in Start GPP , End GPP , or air temperature, but their interannual anomalies were significantly correlated. Warmer weather was associated with earlier Start GPP (1.3–2.5 days °C −1 ) or later End GPP (1.5–1.8 days °C −1 , depending on forest type and month). Finally, we tested whether existing phenological models could predict Start GPP and End GPP . For ENF forests, air temperature‐ and daylength‐based models provided best predictions for Start GPP , while a chilling‐degree‐day model was best for End GPP . The root mean square errors (RMSE) between predicted and observed Start GPP and End GPP were 11.7 and 11.3 days, respectively. For DBF forests, temperature‐ and daylength‐based models yielded the best results (RMSE 6.3 and 10.5 days).

Environmental Sciences & Ecology↗
DOE OSTI2025

GNSS-based Vegetation Optical Depth, Tree Sway, and Evapotranspiration data from the Niwot Ridge Subalpine Forest (US-NR1) AmeriFlux site

This data package contains data and information about Global Navigation Satellite System (GNSS)-based Vegetation Optical Depth (VOD), tree sway motion, and eddy-covariance evapotranspiration (ET) data collected at the Niwot Ridge Subalpine Forest AmeriFlux site (US-NR1). The raw GNSS data were collected between May 2022 and August 2023. Other processed datasets such as tree sway motion and ET data are also included. The goal was to study the water content within a subalpine forest and, more specifically, examine the canopy evaporation process. This data archive includes all data that were used within the following Biogeosciences discussion paper that further summarizes the research objectives and conclusions:Burns, S.P., V. Humphrey, E.D. Gutmann, M.S. Raleigh, D.R. Bowling, and P.D. Blanken, 2025: Using GNSS-based vegetation optical depth, tree sway motion, and eddy-covariance to examine evaporation of canopy-intercepted rainfall in a subalpine forest. EGUsphere [preprint],https://doi.org/10.5194/egusphere-2025-1755This data archive also supplements the 30-min Lawrence Berkeley National Laboratory (LBNL) AmeriFlux dataset for US-NR1 (i.e., https://doi.org/10.17190/AMF/1246088) and updates what was in the 2020 ESS-DIVE US-NR1 archive (https://doi.org/10.15485/1671825) to include data from the years 2020-2025. More specifically, the following updates are provided: (i) five-minute statistics (means, variances, covariances) of all data measured by the US-NR1 data system between Sep 2020 and Jun 2025 in netCDF format, (ii) the electronic logbook of US-NR1 site visits, (iii) a web calendar (in HTML format) documenting activity at the site (a replica of https://urquell.colorado.edu/calendar/), (iv) photos taken at the site between years 2020 and present day (Aug 2025), and (v) several auxiliary datasets, primary related to trees near the site, soil properties, soil moisture and soil temperature, and subcanopy radiation data. The data package is setup so that the web calendar, photos, and electronic logbook can be easily accessed on a local computer using a web browser. The provided data files are in either BINEX or SBF format (for the raw GNSS data), netCDF, CSV, ASCII, or MATLAB format. To obtain a better understanding about the archive, please start by reading the following PDF which is included within the data archive:README_ESS_DIVE_USNR1_2025_readme_first.pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Pilot-Scale Validation of Distributed Optical Fiber Sensors for Underground Pipeline Monitoring

Monitoring parameters such as hoop strain, pressure, and acoustic vibrations is key to detecting potential leaks, intrusions, or structural issues. Distributed optical fiber sensor (DOFS) systems provide a compelling solution for continuous, real-time monitoring over long distances. This paper details the development and pilot-scale implementation of DOFS systems for underground pipeline monitoring, evolving from a proof-of-concept stage. Multiple custom-designed DOFS interrogator units—such as optical frequency-domain reflectometry (OFDR), Brillouin optical time-domain analysis (BOTDA), and multimodal interferometer-based fiber acoustic sensor systems were tested to measure the key parameters, such as hoop strain, pipe pressure, surrounding soil temperature, and acoustic vibrations. The underground product pipeline’s outer diameter is 30 inches, the wall thickness is 1.28 inches, and 3 feet deep from the surface. The fiber deployment strategies and sensing data acquisition methods for these systems are discussed. The results demonstrate the effectiveness of DOFS in detecting hoop strain, temperature changes, and acoustic vibrations, showcasing their potential for real-time monitoring and enhancing pipeline safety. These findings from pilot-scale testing offer valuable insights into advancing pipeline monitoring technologies and improving the reliability of underground pipeline systems.

fiber optic sensors↗
DOE OSTI2025

Experimental Study of a Novel Semi-Transparent Bi-Facial Agri-Voltaic System: Initial Results

Solar (photovoltaic)-agriculture practices have experienced notable progress across several countries over the past few decades, creating a field widely known as agrivoltaics. This co-location practice has proved effective for certain crops that prefer partial shade like tomatoes, lettuce, and peppers, although it is less effective for crops needing more sun. Availability of natural sunlight with a specific spectral signature is necessary for agricultural practices as many plant species require an optimum-level and quality of sunlight for photosynthesis. The goal of this work is to model and validate ground-level irradiance for a semi-transparent bifacial solar collector equipped with a custom spectral reflector. By introducing intentional gaps between opaque solar cells, we hope to allow 50% of visible light to pass through the module. Additionally, this technology could reduce the soil temperature by 2° C, improve moisture retention, and enhance yield by providing partial solar radiation. In our model, we can calculate the total solar irradiance for the plants as a function of the cell distribution, material absorption, height of the panel and time of year with a spatial resolution of 0.0625 m2. When comparing theoretical estimates to experimental measurements of photosynthetically active radiation (PAR), we find a discrepancy of 32-48%, and a discrepancy of 19-38% after correction with TMY data.

McGraw, Duncan (ORCID:0000000256388118)↗
NASA NTRS1975

Remote estimation of soil moisture

Two methods under consideration for making remote estimates of soil moisture involve measurements made in electromagnetic spectral region of 0.4 to 14.0 micrometers: (1) spectral reflectance, (2) soil temperature.

Blanchard, M. B.↗
NASA NTRS1975

Meteorological applications of remote sensing from satellites

Current and promising future contributions to meteorology from satellite-borne sensors are discussed, with emphasis on performance and the limitations thereto. The discussion covers (1) synoptic meteorology, where satellite observations of clouds provide measures of winds, cyclogenesis, and rainfall estimation; (2) atmospheric profiling, wherein vertical profiles of temperature, humidity, and certain gaseous constituents are provided; (3) radiation budget or the energy exchange between the earth and the space-sun environment; and (4) surface features of importance to meteorology-temperature, soil moisture, and sea ice coverage.

Yates, H. W.↗
NASA NTRS1976

Snow backscatter in the 1-8 GHz region

The 1-8 GHz microwave active spectrometer system was used to measure the backscatter response of snow covered ground. The scattering coefficient was measured for all linear polarization combinations at angles of incidence between nadir and 70 deg. Ground truth data consisted of soil moisture, soil temperature profile, snow depth, snow temperature profile, and snow water equivalent. The radar sensitivity to snow water equivalent increased in magnitude with increasing frequency and was almost angle independent for angles of incidence higher than 30 deg, particularly at the higher frequencies. In the 50 deg to 70 deg angular range and in the 6 to 8 GHz frequency range, the sensitivity was typically between -0.4 dB/.1 g/sq cm and -0.5 dB/,1 g/sq cm, and the associated linear correlation coefficient had a magnitude of about 0.8.

Ulaby, F. T.↗
NASA NTRS1981

Evaluation of the Doraiswamy-Thompson winter wheat crop calendar model incorporating a modified spring restart sequence

The Robertson phenology was used to provide growth stage information to a wheat stress indicator mode. A stress indicator model demands two acurate predictions from a crop calendar: date of spring growth initiation; and crop calendar stage at growth initiation. Several approaches for restarting the Robertson phenology model at spring growth initiation were studied. Although best results were obtained with a solar thermal unit method, an alternate approach which indicates soil temperature as the controlling parameter for spring growth initiation was selected and tested. The modified model (Doraiswamy-Thompson) is compared to LACIE-Robertson model predictions.

Taylor, T. W.↗
NASA NTRS1980

Data documentation for the bare soil experiment at the University of Arkansas

The reflectivities of several controlled moisture test plots were investigated. These test plots were of a similar soil texture which was clay loam and were prepared to give a desired initial soil moisture and density profile. Measurements were conducted on the plots as the soil water redistributed for both long term and diurnal cycles. These measurements included reflectivity, gravimetric and volumetric soil moisture, soil moisture potential, and soil temperature.

Waite, W. P.↗
NASA NTRS1985

Measurements of the surface energy budget in the southern Gobi Desert of China, and in the Rocky Mountains of Colorado

Observations of the land surface energy balance were made in the Gobi desert and at two mountain sites in northern Colorado. The Gobi study included 12 days of observations in spring (April 8 to 20, 1984) and 31 days in summer at the same site (June 17 to July 18, 1984). The Colorado study included 126 days (March 13 to July 17, 1984) at a valley site and 34 days (July 31 to September 3, 1984) at a mountain top location. The data for each study included continuous observations of upward and downward radiative fluxes in three wave bands, soil temperature and moisture at four levels, air temperature and humidity at four levels and UVW wind components at three levels. Analyses of the Gobi data include definition of the impact of variable atmospheric moisture on the surface energy balance between spring and summer. In addition, diurnal wind circulations forced by heating of the northern edge of the Tibetan Plateau were observed during both periods.

Reiter, E. R.↗