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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Climate-Driven Limits to Future Carbon Storage in California's Wildland Ecosystems

Enhanced ecosystem carbon storage is a key component of many climate mitigation pathways. The State of California has set an ambitious goal of carbon neutrality by 2045, relying in part on enhanced carbon sequestration in natural and working lands. We used statistical modeling, including random forest and climate analog approaches, to explore the climate-driven challenges and uncertainties associated with the goal of long-term carbon sequestration in forests and shrublands. We found that seasonal patterns of temperature and precipitation are strong controllers of the spatial distribution of aboveground live carbon. RCP8.5 projections of temperature and precipitation are estimated to drive decreases of 16.1% ± 7.5% in aboveground live carbon by the end of the century, with coastal areas of central and northern California and low/mid-elevation mountain areas being most vulnerable. With RCP4.5 projections, declines are less severe, with 8.8% ± 5.3% carbon loss. In either scenario, increases in temperature systematically cause biomass declines, and the spread of projected precipitation across 32 CMIP5 models contributes to substantial uncertainty in the magnitude of that decline. Projected changes in the environmental niche for the 20 most biomass-dominant tree species revealed widespread replacement of conifers by oak species in low elevation regions of central and northern California, with a corresponding decline in carbon storage depending on expected migration rates. The spatial patterns of vulnerability we identify may allow policymakers to assess where carbon sequestration in aboveground biomass is an appropriate part of a climate mitigation portfolio, and where future climate-driven carbon losses may be a liability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Bar Bartlett Experimental Forest

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Bar Bartlett Experimental Forest. This is the FLUXNET version of the carbon flux data for the site US-Bar Bartlett Experimental Forest produced by applying the standard ONEFlux (1F) software. Site Description - The Bartlett Experimental Forest (448170 N, 71830 W) is located within the White Mountains National Forest in north-central New Hampshire, USA. The 1050 ha forest extends across an elevational range from 200 to 900 m a.s.l. It was established in 1931 and is managed by the USDA Forest Service Northeastern Research Station in Durham, NH. The climate is humid continental with short, cool summers (mean July temperature, 19.8C) and long, cold winters (mean January temperature, 9.8C). Annual precipitation averages 130 cm and is distributed evenly throughout the year. Soils are developed from glacial till and are predominantly shallow, well-drained spodosols. At lowto mid-elevation, vegetation is dominated by northern hardwoods (American beech, Fagus grandifolia; sugar maple, Acer saccharum; yellow birch, Betula alleghaniensis; with some red maple, Acer rubrum and paper birch, Betula papyrifera). Conifers (eastern hemlock, Tsuga canadensis; eastern white pine, Pinus strobus; red spruce, Picea rubens) are occasionally found intermixed with the more abundant deciduous species but are generally confined to the highest (red spruce) and lowest (hemlock and pine) elevations. In 2003, the site was adopted as a NASA North American Carbon Program (NACP) Tier-2 field research and validation site. A 26.5 m high tower was installed in a low-elevation northern hardwood stand in November, 2003, for the purpose of making eddy covariance measurements of the forest–atmosphere exchange of CO2, H2O and radiant energy. Continuous flux and meteorological measurements began in January, 2004, and are ongoing. Average canopy height in the vicinity of the tower is approximately 20–22 m. In the tower footprint, the forest is predominantly classified into red maple, sugar maple, and American beech forest types. Leaf area index in the vicinity of the tower is 3.6 as measured by seasonal litterfall collection, and 4.5 as measured by the optically based Li-Cor LAI-2000 instrument. Further site information: http://www.fs.fed.us/ne/durham/4155/bartlett.htm

Richardson, Andrew↗
DOE OSTI2023

Monsoon Extremes: Impacts, Metrics, and Synoptic-Scale Drivers

This project was led by UC Berkeley with a subcontract to UC Davis and collaborative funding at the Lawrence Berkeley National Lab (LBNL). It produced new understanding of transient atmospheric disturbances in monsoon regions, the precipitation extremes they produce, and the sensitivity of precipitation and monsoon winds to fine-scale orography (i.e., the narrow mountain ranges that are difficult to represent in conventional Earth system models). Fundamental research undertaken as part of this project led to discovery of new mechanisms that control the generation of extreme weather events and that govern the spatial patterns of intense precipitation in monsoon climates—including the North American monsoon. These research accomplishments are summarized below and documented in a series of 23 publications, 20 of which were led by project personnel (the others were collaborative work led by staff of other projects). One of the publications produced by this project was in Nature, where it was selected for the main cover image, and another was in PNAS. The project also produced two datasets and a tracking algorithm, both of which are publicly available and listed below. The project trained three Ph.D. students and four postdoctoral scientists, the vast majority of whom have progressed to more advanced positions in their scientific careers. Although the university funding for this project ended in 2022, the LBNL component of the project proceeded for almost one year longer; this report is being provided after completion of all components of the project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evaluating probabilistic deep learning methods for uncertainty quantification of temperature downscaling

Deep learning (DL) has emerged as a promising tool for downscaling coarse-resolution climate data to high-resolution outputs, enabling improved regional climate predictions. A critical aspect of DL-based downscaling is the incorporation of uncertainty quantification (UQ), which enhances the interpretability and reliability of predictions—key factors for climate risk assessment and decision-making. This study develops a DL model to downscale 2 m temperature across the contiguous United States using reanalysis datasets. We systematically evaluate three epistemic UQ methods—deep ensembles (DEns), Monte Carlo dropout (MCD), and Flipout—based on their probabilistic accuracy, downscaling performance, sensitivity to geographical features, and computational efficiency. Results indicate that MCD generally outperforms Flipout and DEns in terms of calibration and downscaling accuracy. However, DEns demonstrate lower calibration errors in coastal regions, indicating its higher confidence within these areas. Flipout, in contrast, is more sensitive to elevation gradients and exhibits higher calibration errors in mountainous regions. Hence, the choice of UQ method for this task depends on the specific requirements of the application. For applications that prioritize overall calibration, downscaling accuracy, and computational efficiency, MCD is a strong candidate. These findings highlight the importance of selecting UQ methods based on application-specific requirements, such as geographical context and computational constraints. By addressing the trade-offs between UQ methods, this study provides actionable insights for improving the reliability, scalability, and utility of DL-based downscaling in climate science.

Environmental sciences↗
DOE OSTI2022

Downscaled hyper-resolution (400 m) gridded datasets of daily precipitation and temperature (2008–2019) for the East–Taylor subbasin (western United States)

Abstract. High-resolution gridded datasets of meteorological variables are needed in order to resolve fine-scale hydrological gradients in complex mountainous terrain. Across the United States, the highest available spatial resolution of gridded datasets of daily meteorological records is approximately 800 m. This work presents gridded datasets of daily precipitation and mean temperature for the East–Taylor subbasin (in the western United States) covering a 12-year period (2008–2019) at a high spatial resolution (400 m). The datasets are generated using a downscaling framework that uses data-driven models to learn relationships between climate variables and topography. We observe that downscaled datasets of precipitation and mean temperature exhibit smoother spatial gradients (while preserving the spatial variability) when compared to their coarser counterparts. Additionally, we also observe that when downscaled datasets are upscaled to the original resolution (800 m), the mean residual error is almost zero, ensuring no bias when compared with the original data. Furthermore, the downscaled datasets are observed to be linearly related to elevation, which is consistent with the methodology underlying the original 800 m product. Finally, we validate the spatial patterns exhibited by downscaled datasets via an example use case that models lidar-derived estimates of snowpack. The presented dataset constitutes a valuable resource to resolve fine-scale hydrological gradients in the mountainous terrain of the East–Taylor subbasin, which is an important study area in the context of water security for the southwestern United States and Mexico. The dataset is publicly available at https://doi.org/10.15485/1822259 (Mital et al., 2021).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A Mountain Glacier Perspective on the Bipolar Seesaw

A global record of mountain glacier terminations during the last deglaciation (∼19–11 ka) dated by a large, uncurated data set of cosmogenic-nuclide exposure ages highlights a statistically significant asynchrony in termination ages between the Northern and Southern Hemispheres. This interhemispheric offset in the timing of glacier terminations is consistent with previously correlated ice core records that show a systematic interhemispheric lag in the timing of abrupt climate events, with the Southern Hemisphere leading the Northern Hemisphere by ∼300–3,500 years. Our analysis (a) aggregates cosmogenic-nuclide exposure ages from a global data set of moraines to discern climatically driven peaks in moraine emplacement events, and (b) utilizes a Monte Carlo simulation based on a null hypothesis that moraine emplacement is interhemispherically synchronous to estimate the statistical significance of the observed offset. The observed lag of Northern Hemisphere emplacement events compared to the Southern Hemisphere is statistically significant and is consistent with the “bipolar seesaw” pattern observed in ice core records.

58 GEOSCIENCES↗
DOE OSTI2024

Latest Pleistocene glacial chronology and paleoclimate reconstruction for the East River watershed, Colorado, USA

Reconstructing Pleistocene glaciation timing and extent is vital for understanding paleoclimate. Whereas late Pleistocene glaciation has been studied extensively in western North American mountain ranges, the glacial history of the western Elk Range in Colorado remains understudied, particularly in the East River watershed, a site of intense scientific focus. Here we use cosmogenic nuclide exposure and depth–profile dating methods to determine the timing of glaciation in the East River watershed. We use glacier modeling to reconstruct paleoglacier extents and quantify past climate conditions. Our findings indicate that the East River glacier retreated from its maximum position approximately 17–18 ka, moving to recessional positions between 13 and 15 ka, before experiencing more substantial retreat to high-elevation cirques around 13 ka. Glacier modeling suggests that the maximum ice extents at 17–18 ka could have been sustained by temperature depressions of approximately −6.5°C compared to modern conditions, assuming consistent precipitation. Additionally, the ice position at 13–15 ka could have been supported by temperature depressions of around −4.0°C. These results offer insights into the deglaciation timeline in the East River watershed and broader western Elk Range as well as paleoclimate conditions during the late Pleistocene, which may aid future research on critical zone evolution in the East River watershed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Diurnal Trends and Meteorological Factors Influencing the Variability of Fluorescent Bioaerosol in Mt. Crested Butte, Colorado During SAIL

Abstract Despite the crucial role of bioaerosol particles (BAP) in our climate system, local ecosystems, and human health, our grasp on their atmospheric interactions is hampered by a lack of high‐resolution and long‐term data, which is essential for understanding their abundance and variability in response to meteorological conditions. To discern these relationships in a high‐altitude mountainous terrain is even less well‐studied. Therefore, we deployed a Wideband Integrated Bioaerosol Sensor (WIBS‐Neo) for three months during the first biologically active season of the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in summer 2022 on Mt. Crested Butte in Colorado (elevation 3,140 m ASL). Here, we report real‐time fluorescent BAP (FBAP) data collected from 15 June to 13 September 2022, sampled from within the ARM Aerosol Observing System (AOS). To our knowledge, these are the first high altitude (>3,000 m ASL) continuous measurements of FBAP made in North America. During this deployment, we observed on average 21% and as many as 48% (hourly maximum) of particles within the detection size range ( to ) of the WIBS as FBAP. Our analysis presents the diurnal cycles for seven distinct types of FBAP, showing unique patterns and, in some cases, correlations with temperature and solar radiation cycles. Abundance and composition of FBAP varied with relative humidity and precipitation. Precipitation events appeared to both cause emission and removal of FBAP, whereas dust and smoke events had no significant effect, highlighting the critical role of meteorology on FBAP at high altitudes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hydrological analysis in watersheds with a variable-resolution global climate model (VR-CESM)

Traditionally, watershed-scale hydrology is simulated by distributed hydrological models with offline meteorological forcing data, or by regional regional climate models that link atmospheric and land hydrology interactions. Global climate models (GCMs) are rarely used to study watershed-scale hydrology due to the relatively coarse grid resolution, computationally expensive downscaling, and simplified physical processes. Recently, however, watershed-scale hydrology analysis has become possible in GCMs due to the development of variable-resolution GCMs that dynamically couple the hydrological processes between atmosphere and land systems at fine resolutions in selected regions and coarse resolution elsewhere. In this study, we used the variable-resolution Community Earth System Model (VR-CESM) with refined-resolution (14 km) in the western U.S. and eastern China to evaluate watershed-scale hydrology. Furthermore, we compared the historical VR-CESM outputs with gauge measurements and other hydrological models (e.g., National Water Model in the U.S.) and calibrated the subsurface runoff capacities in four mountainous watersheds. An RCP8.5 projection from 2007 to 2050 is used to estimate the impact of changing precipitation and snow climatology on watershed hydrology. We also analyzed the long-term runoff variability and the possibility of extreme runoff events as simulated by the VR-CESM. Although calibration is not possible in larger-scale watersheds, VR-CESM simulates the long-term annual variability of watersheds and provides insights on climate change impacts on hydrology. We conclude that refined-resolution VR-CESM can be used for watershed-scale hydrology analysis to understand water resources and water balance, in addition to traditional watershed-scale hydrological models. It enables hydrological analysis at multiple watersheds in one simulation and can help understand the two-way dynamics between land surface hydrology and atmospheric processes, and is especially practical for projecting climate change impacts. However, it is challenging to apply VR-CESM for hydrologic analysis in regulated watersheds as human factors (e.g., pumping, irrigation, water diversion) have not been fully addressed in VR-CESM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Cosmogenic 10Be constraints on deglacial snowline rise in the Southern Alps, New Zealand

We report geochronological dating of glacial landforms, such as terminal and lateral moraines, is useful for determining the extent and timing of past glaciation and for reconstructing the magnitude and rate of past climate changes. In the Southern Alps of New Zealand, well-dated glacial geomorphological records constrain the last glacial cycle across much of the Waitaki River basin (e.g. Ōhau, Pukaki, Tekapo) but its southern sector such as the Ahuriri River valley remains comparatively unconstrained. Recently, there has been debate on the scale and rapidity of mountain glacier retreat during the last glacial termination, particularly the 20–17 ka period in New Zealand. Missing from this debate is well-constrained equilibrium-line altitude (ELA) and associated temperature reconstructions, particularly over the period around 17 ka, which can help us to develop a more complete picture of how past temperature changes drove glacier retreat. Here we report the first glacial chronology dataset from the Last Glacial Maximum (LGM) and subsequent deglaciation from the Ahuriri River valley, Southern Alps, New Zealand (44°23'54"S, 169°39'48"E) based on 38 beryllium-10 ( 10 Be) surface-exposure ages from terminal moraine systems and glaciated bedrock situated at the lower and middle sections of the valley. Our results show that the former Ahuriri Glacier reached its maximum extent at 19.8 ± 0.3 ka, which coincides with the global Last Glacial Maximum. By 16.7 ± 0.3 ka, the glacier had retreat ~18 km up-valley suggesting at least ~43% glacier-length loss relative to its full LGM extent. This deglaciation was accompanied by the formation of a shallow proglacial lake. Using the accumulation area ratio (AAR) method, we estimate that the ELA was lower than present by ~880 m (~1120 m a.s.l.) at 19.8 ± 0.3 ka, and ~770 m lower (~1230 m a.s.l.) at 16.7 ± 0.3 ka. Applying an estimate for temperature lapse rate, this ELA anomaly implies that local air temperature was 5 ± 1 °C colder than present (1981–2010) at 19.8 ± 0.3 ka, while it was 4.4 ± 0.9 °C colder at 16.7 ± 0.3 ka, assuming no change in precipitation. The substantial glacier retreat in response to a relatively small accompanying increases in ELA (110 m) and temperature (0.6 °C) may have been a result of the high glacier-length sensitivity of this glacier system due to its low gradient of former ice surface. Our low warming estimate differs markedly from other deglaciation studies, specifically from Rakaia River valley, which reports a much larger temperature increase at the onset of the last deglaciation. This precisely-dated moraine record along with reconstructed ELA as proxies for atmospheric conditions, provides new insight into post LGM glacier behaviour and climate conditions in New Zealand.

58 GEOSCIENCES↗
DOE OSTI2020

AmeriFlux US-Jo2 Jornada Experimental Range Mixed Shrubland

This is the AmeriFlux version of the carbon flux data for the site US-Jo2 Jornada Experimental Range Mixed Shrubland. Site Description - The study area is in a mixed shrub-dominated portion of the San Andres Mountain piedmont, along the southeastern boundary of the Jornada Experimental Range (JER) in southern New Mexico, USA. The JER was established in 1912 as a response of scientis and landowner to the shrub enchroachment and loss of grasses due to extended grazing during the late 1800s, fire and climate change. JER has been a NSF LTER site since 1981.The study site is a small watershed (4.67 ha) in an alluvial slope or bajada, with three major areas (north-, south- and west-facing hillslopes) with low to moderate slopes (∼0–6°) with a mean slope of 2.6°, while the channel banks and propagating channel heads have higher slopes (∼15–25°). The site is charactetized by a high bare soil coverage (∼66%), ∼28% of mixed shrubs coverage and a low coverage of grass (∼4%) and weeds (∼2%).

Vivoni, Enrique R.↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-Jo2 Jornada Experimental Range Mixed Shrubland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Jo2 Jornada Experimental Range Mixed Shrubland. This is the FLUXNET version of the carbon flux data for the site US-Jo2 Jornada Experimental Range Mixed Shrubland produced by applying the standard ONEFlux (1F) software. Site Description - The study area is in a mixed shrub-dominated portion of the San Andres Mountain piedmont, along the southeastern boundary of the Jornada Experimental Range (JER) in southern New Mexico, USA. The JER was established in 1912 as a response of scientis and landowner to the shrub enchroachment and loss of grasses due to extended grazing during the late 1800s, fire and climate change. JER has been a NSF LTER site since 1981.The study site is a small watershed (4.67 ha) in an alluvial slope or bajada, with three major areas (north-, south- and west-facing hillslopes) with low to moderate slopes (∼0–6°) with a mean slope of 2.6°, while the channel banks and propagating channel heads have higher slopes (∼15–25°). The site is charactetized by a high bare soil coverage (∼66%), ∼28% of mixed shrubs coverage and a low coverage of grass (∼4%) and weeds (∼2%).

Vivoni, Enrique R.↗
DOE OSTI2023

The detection and attribution of extreme reductions in vegetation growth across the global land surface

Abstract Negative extreme anomalies in vegetation growth (NEGs) usually indicate severely impaired ecosystem services. These NEGs can result from diverse natural and anthropogenic causes, especially climate extremes (CEs). However, the relationship between NEGs and many types of CEs remains largely unknown at regional and global scales. Here, with satellite‐derived vegetation index data and supporting tree‐ring chronologies, we identify periods of NEGs from 1981 to 2015 across the global land surface. We find 70% of these NEGs are attributable to five types of CEs and their combinations, with compound CEs generally more detrimental than individual ones. More importantly, we find that dominant CEs for NEGs vary by biome and region. Specifically, cold and/or wet extremes dominate NEGs in temperate mountains and high latitudes, whereas soil drought and related compound extremes are primarily responsible for NEGs in wet tropical, arid and semi‐arid regions. Key characteristics (e.g., the frequency, intensity and duration of CEs, and the vulnerability of vegetation) that determine the dominance of CEs are also region‐ and biome‐dependent. For example, in the wet tropics, dominant individual CEs have both higher intensity and longer duration than non‐dominant ones. However, in the dry tropics and some temperate regions, a longer CE duration is more important than higher intensity. Our work provides the first global accounting of the attribution of NEGs to diverse climatic extremes. Our analysis has important implications for developing climate‐specific disaster prevention and mitigation plans among different regions of the globe in a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Land management explains major trends in forest structure and composition over the last millennium in California’s Klamath Mountains

Significance We provide the first assessment of aboveground live tree biomass in a mixed conifer forest over the late Holocene. The biomass record, coupled with local Native oral history and fire scar records, shows that Native burning practices, along with a natural lightning-based fire regime, promoted long-term stability of the forest structure and composition for at least 1 millennium in a California forest. This record demonstrates that climate alone cannot account for observed forest conditions. Instead, forests were also shaped by a regime of frequent fire, including intentional ignitions by Native people. This work suggests a large-scale intervention could be required to achieve the historical conditions that supported forest resiliency and reflected Indigenous influence.

Knight, Clarke A.↗
DOE OSTI2022

A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA

We present meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains (USA) over three consecutive water years with different amounts of snow water equivalent (SWE) accumulation: A year with above average SWE (2019), a year with average SWE (2020), and a year with below average SWE (2021). This data set is distinguished by its emphasis on paired open-forest sites in a continental snow climate. Approximately once a month during February–May, we collected data from 15 to 20 snow pits and took 8 to 19 snow depth transects. Our sampling sites were in open and adjacent forested areas at 3,100 m and in a lower elevation aspen (3,035 m) and higher elevation conifer stand (3,395 m). In total, we recorded 270 individual snow pit density and temperature profiles and over 4,000 snow depth measurements. These data are complimented by continuous meteorological measurements from two weather stations: One in the open and one in the adjacent forest. Meteorology data—including incoming shortwave and longwave radiation, outgoing shortwave radiation, relative humidity, wind speed, snow depth, and air and infrared surface temperature—were quality controlled and the forcing data were gap-filled. These data are available to download from Bonner, Smyth, et al. at three levels of processing, including a level with downscaled, adjusted precipitation based on data assimilation using observed snow depth and a process-based snow model. We demonstrate the utility of these data with a modeling experiment that explores open-forest differences and identifies opportunities for improvements in model representation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The Q 10 of in situ microbial soil respiration varies with mean annual temperature, precipitation, pH, and plant cover: a meta-analysis and spatial prediction of Q 10

The temperature sensitivity of soil microbial respiration, commonly quantified using the Q 10 coefficient, is a key parameter in carbon cycle models. Uncovering how environmental factors affect in situ Q 10 values can therefore provide critical insight into potential shifts in global carbon stocks under climate change. We collected data from previously published field experiments that measured soil microbial respiration across a range of temperatures. We hypothesized that the Q 10 coefficient of in situ soil microbial respiration would vary based on environmental factors including mean annual temperature (MAT), mean annual precipitation (MAP), plant cover type, pH, soil C:N, and latitude. Linear regression revealed that Q 10 correlates negatively with MAT and MAP and positively with pH and absolute latitude. Additionally, average Q 10 varied significantly across different plant cover types; it was highest in mountain grasslands and lowest in tropical moist forests. Variation in microbial Q 10 across environmental factors may arise from underlying mechanisms such as enzyme kinetics, substrate availability and complexity, and microbial adaptation. To capture patterns in Q 10 more comprehensively, we developed a multiple linear regression model of Q 10 based on the most individually significant environmental drivers and applied it to public datasets to generate a global map of predicted Q 10 . Q 10 was higher in high-latitude and high-altitude regions, where large permafrost carbon stores are vulnerable to thawing and decomposition. We also compared fits between the Q 10 equation and a model produced from macromolecular rate theory (MMRT). We found that the MMRT model had the superior fit and may be better suited to model temperature sensitivity of complex biological reactions. Overall, our results emphasize that relationships between microbial Q 10 and environmental variables should be accounted for in climate models. Incorporating these variations in the Q 10 parameter, rather than using a fixed value, will help predict whether CO 2 emissions will be buffered or exacerbated by soil microbial respiration under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A spatiotemporally explicit and scalable indicator of intact lands across the conterminous United States, 1986–2023

Globally, ecologically intact areas are increasingly scarce. Agricultural expansion into previously uncultivated areas drives the loss of intact lands that might otherwise exhibit high levels of ecological integrity. Thus, the absence of cultivation can be an indicator of intact lands as measured from remote sensing data and thematic maps. Our objective for this study was to develop and compare tractable approaches based on remotely sensed satellite data to map spatial patterns of potentially intact lands across the conterminous U.S. (CONUS). Using annual cultivation probabilities derived from satellite observations, we classified and mapped potentially intact lands across CONUS from 1986 to 2023 at 30 m resolution. We created three maps, first by applying a constant cultivation probability threshold across CONUS, second by varying the threshold state-by-state to maximize state-level overall accuracies, and third by equalizing the state-level user's and producer's accuracies to minimize classification bias. Validation against 800,000+ independent ground samples resulted in CONUS-level overall accuracies ≥85% for the roughly 660 million ha of potentially intact land. Map accuracy varied with the proportion of potentially intact lands across regions, with the Pacific-Mountain and Great Plains regions exhibiting the highest accuracies, while Eastern CONUS exhibited a greater mix of potentially intact and non-intact lands and more moderate map accuracies. These novel maps and approaches can be adapted to different spatiotemporal extents to support conservation and production decisions ranging from species and ecosystems protection to reducing land conversion and climate mitigation.

agriculture↗
DOE OSTI2020

Infrasound and Gravity Waves Over the Andes Observed by a Pressure Sensor on Board a Stratospheric Balloon

The study of infrasound (acoustic) and gravity waves sources and propagation in the atmosphere of a planet gives us precious insight on atmosphere dynamics, climate, and even internal structure. The implementation of modern pressure sensors with high rate sampling on stratospheric balloons is improving their study. In our work we analyzed the data from the National Aeronautics and Space Administration Ultra Long Duration Balloon mission (16 May to 30 June 2016). Here, we focus on the balloon's transit of the Andes Mountains. We detected gravity waves that are associated to troposphere convective activity and mountain waves. An increase of the horizontal wavelengths from 50 to 70 km with increasing distance to the mountains is favoring the presence of mountain waves. We also report on the detection of infrasounds generated by the mountains in the 0.01–0.1 Hz range with a pressure amplitude increase by a factor 2 relative background signal. Besides, we characterized the decrease of microbaroms power when the balloon was flying away from the ocean coast. These observations suggest, in a way similar to microseisms for seismometers, that microbaroms are the main background noise sources recorded in the stratosphere even far from the ocean sources. Finally, we observed a broadband signal above the Andes, between 0.45 and 2 Hz, probably associated with a thunderstorm. The diversity of geophysical phenomena captured in less than a day of observation stresses the interest of high rate pressure sensors on board long-duration balloon missions.

54 ENVIRONMENTAL SCIENCES↗