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NASA NTRS2020

Land-cover Change in the Caucasus Mountains Since 1987 Based on the Topographic Correction of Multi-temporal Landsat Composites

Mountainous regions are changing rapidly across the world due to both land-use change and climate change. Given the importance of mountainous regions for ecosystem services and endemic biodiversity, monitoring these changes is essential. Satellite data provide a great resource to map land-cover change in mountainous regions, however mapping is especially challenging there because topographic complexity affects reflectance. The so called ‘topographic effect’ has been successfully corrected for in case studies of small areas, but a comparison of large-area classifications and land-cover change analyses with and without topographic correction is missing. Here, we performed a long-term land-cover change assessment for a large mountainous region, i.e., the Caucasus Mountains with topographic correction. Our two goals were 1) to examine the effect of topographic correction on land-cover classification for a large mountainous region, and 2) to assess land-cover changes since 1987 across the Caucasus based on the full Landsat archive. Both the complex topography and the history of land-use changes, especially after the collapse of the Soviet Union in 1991, make the Caucasus Mountains an ideal study area to understand topographic effects on large-area land-cover mapping for the last three decades. First, we compared a non-topographically-corrected Landsat classification for 2015 with a classification that was topographically-corrected with an enhanced C-correction for the same year and assessed the accuracy of both. Second, we derived topographically-corrected Landsat classifications for six dates to assess changes in cropland and forest from 1987 to 2015, based on class probabilities and post-classification comparisons. In regard to our first goal, topographic correction improved the overall accuracy of the classification only by 2% (from 79 to 81%), but disagreement rates were as high as 100% in mountainous regions, especially among forest types. In regard to our second goal, we found that cropland loss was the most prevalent change process since 1987. Cropland loss was particularly widespread in Georgia and Armenia until 2000, and in Azerbaijan until 2005. The North Caucasus (the Russian Federation) had more stable cropland over time, most likely due to different land reforms after the collapse of the Soviet Union, and the prevalence of flat landscapes and very fertile soils, which make cultivation easier than in the South Caucasus. Rates of forest change throughout the Caucasus Mountains were surprisingly low, with forest loss and forest gain was most likely due to cropland abandonment and less grazing pressure. Our results highlight both the importance and the feasibility of topographic correction for accurate large-area land-cover classifications in steep terrain.

Large-area mapping↗

DOE OSTI2024

Are Atmospheric Models Too Cold in the Mountains? The State of Science and Insights from the SAIL Field Campaign

Mountains play an outsized role in water resource availability, and the amount and timing of water they provide depend strongly on temperature. To that end, we ask the question: How well are atmospheric models capturing mountain temperatures? We synthesize results showing that high-resolution, regionally relevant climate models produce 2-m air temperature (T2m) measurements colder than what is observed (a “cold bias”), particularly in snow-covered midlatitude mountain ranges during winter. We find common cold biases in 44 studies across global mountain ranges, including single-model and multimodel ensembles. We explore the factors driving these biases and examine the physical mechanisms, data limitations, and observational uncertainties behind T2m. Our analysis suggests that the biases are genuine and not due to observation sparsity or resolution mismatches. Cold biases occur primarily on mountain peaks and ridges, whereas valleys are often warm biased. Our literature review suggests that increasing model resolution does not clearly mitigate the bias. By analyzing data from the Surface Atmosphere Integrated Field Laboratory (SAIL) field campaign in the Colorado Rocky Mountains, we test various hypotheses related to cold biases and find that local wind circulations, longwave (LW) radiation, and surface-layer parameterizations contribute to the T2m biases in this particular location. We conclude by emphasizing the value of coordinated model evaluation and development efforts in heavily instrumented mountain locations for addressing the root cause(s) of T2m biases and improving predictive understanding of mountain climates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Are Atmospheric Models Too Cold in the Mountains? The State of Science and Insights from the SAIL Field Campaign

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1999

Global Measurements of Stratospheric Mountain Waves from Space

Temperatures acquired by the Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA) during shuttle mission STS-66 have provided measurements of stratospheric mountain waves from space. Large-amplitude, long-wavelength mountain waves at heights of 15 to 30 kilometers above the southern Andes Mountains were observed and characterized, with vigorous wave breaking inferred above 30 kilometers. Mountain waves also occurred throughout the stratosphere (15 to 45 kilometers) over a broad mountainous region of central Eurasia. The global distribution of mountain wave activity accords well with predictions from a mountain wave model. The findings demonstrate that satellites can provide the global data needed to improve mountain wave parameterizations and hence global climate and forecast models.

Eckermann, Stephen D.↗

NASA NTRS2004

Observational Evidence Against Mountain-Wave Generation of Ice Nuclei as a Prerequisite for the Formation of Three Solid Nitric Acid Polar Stratospheric Clouds Observed in the Arctic in Early December 1999

A number of recently published papers suggest that mountain-wave activity in the stratosphere, producing ice particles when temperatures drop below the ice frost point, may be the primary source of large NAT particles. In this paper we use measurements from the Advanced Very High Resolution Radiometer (AVHRR) instruments on board the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites to map out regions of ice clouds produced by stratospheric mountain-wave activity inside the Arctic vortex. Lidar observations from three DC-8 flights in early December 1999 show the presence of solid nitric acid (Type Ia or NAT) polar stratospheric clouds (PSCs). By using back trajectories and superimposing the position maps on the AVHRR cloud imagery products, we show that these observed NAT clouds could not have originated at locations of high-amplitude mountain-wave activity. We also show that mountain-wave PSC climatology data and Mountain Wave Forecast Model 2.0 (MWFM-2) raw hemispheric ray and grid box averaged hemispheric wave temperature amplitude hindcast data from the same time period are in agreement with the AVHRR data. Our results show that ice cloud formation in mountain waves cannot explain how at least three large scale NAT clouds were formed in the stratosphere in early December 1999.

MOUNTAIN WAVES↗

NASA NTRS1994

Regional-scale flows in mountainous terrain. Part 1: A numerical and observational comparison

This study uses observed data and a numerical simulation to examine the generation of thermally driven flows across the Colorado mountain barrier on meso-beta to meso-alpha scales. The observations were collected from remote surface observing systems at exposed mountaintop locations throughout the state of Colorado, over the summers of 1984-88, as part of the Rocky Mountain Peaks Experiment (ROMPEX). The data show the development of a recurrent circulation system across the Colorado mountain barrier, operating on a diurnal timescale. From the observations, the basic structure of the flow system appears as a daytime inflow toward the highest terrain, and a nocturnal outflow away from it. However, when examined in detail, the flow system exhibits more unusual behavior, especially west of the barrier crest. Here, winds in the early evening are occasionally observed to onset abruptly from an easterly direction, generally counter to the upper-level winds. Observations from ROMPEX for 26 August 1985 are used to provide comparison data for a numerical simulation with the Regional Atmospheric Modeling System (RAMS). This three-dimensional case study experiment is initialized with data from the National Meteorological Center and incorporates two-way interactive grid nesting. From the observed data and case study simulation, four distinct phases of the regional-scale circulation system have been identified. In the development phase, a deep mountain-plains solenoid is generated through terrain heating along the Front Range. This circulation system transforms in the late afternoon transition phase into a westward-propagating density current (WPDC). The third phase, called the 'density-current propagation phase,' occurs as the WPDC moves westward across the mountains, leaving in its wake strong southeasterly flow at the mountaintop level. This current appears to be the cause of the peculiar easterly component winds found in the ROMPEX mountaintop observations along the western slope. In the final late-night adjustment phase, the WPDC dissipates near the western edge of the Colorado mountains and steady southerly flow evolves over the high mountain terrain. This southerly flow is the steady response to the differential heating that develops between the low-lying plains and the intermountain region.

Bossert, James E.↗

DOE OSTI2026

High-resolution mountain topography can inform global snow vulnerability estimates

Snow is changing globally. Computationally intensive snow reanalysis products and downscaled climate model projections allow for the estimation of historical and projected changes in snow over ∼4–10 km resolutions, but these resolutions are coarse relative to the scales needed for water supply and flood planning. Fine-scale digital elevation models (DEMs) are widely available but are underutilized to make first-order assessments of snow vulnerability. Here, we leverage DEMs at a 7.5 arc s (∼250 m) resolution, combining these with historical freezing level height estimates from ERA-5 to derive estimates of changes in the snow-receiving area (SRA) and its variability across global mountain ranges. Results show estimated SRA declines in 29% (1.9 million km2) of the global mountain area from 1982–2020; 66% of the mountainous areas had no change over the historical period. At +1.5 °C of warming relative to the pre-industrial control, global mountain SRA would decline by 9.5% (1.0 million km2) relative to recent conditions. This loss would be approximately doubled with +2 °C of warming. In a +4 °C warming scenario, an additional 34% (3.6 million km2) of SRA would be lost beyond the +2 °C case. Across individual mountain ranges, SRA losses can occur nonlinearly with warming, with some locations that have historically had relatively minor SRA losses at risk of substantially larger losses in warmer climates. Analysis using coarser-resolution DEMs can underestimate or overestimate SRA and its rate of loss, with the largest impacts in relatively warm, low-elevation mountain ranges. Results of this work provide estimates of projected loss in SRA at policy-relevant warming levels; inform the resolutions needed for process-based snow modeling; identify snow vulnerability hotspots; and provide a new integrated approach to snow vulnerability assessment that is achievable at global scales and highlights potential nonlinearities from recent trends to a variety of future warming scenarios.

climate, mountains↗

DOE OSTI2024

Detecting ecological signatures of long-term human activity across an elevational gradient in the Šumava Mountains, Central Europe

Central European mountains, including the Šumava Mountains located along the Czechia/Germany border, have a long and rich anthropogenic history. Yet, documenting prehistoric human impact in Central European mountain environments remains a challenge because of the need to disentangle climate and human-caused responses in terrestrial systems. Here, we present the first reconstructed water table depths (WTDs) from two sites, Pěkná and Blatenská slať, located in the Šumava Mountains. We compare these local WTD records with new and published pollen, non-pollen palynomorphs (NPPs), plant macrofossils, geochemistry and archeological records to investigate how changes in local hydrology and human activities impacted forest succession and fire activity throughout the Holocene across an elevational gradient. Using a generalized additive model, our results suggest that changes in forest succession and fire activity have been primarily caused by climate throughout the Holocene. However, humans have been utilizing mountain environments and their resources continuously since ∼4600 cal yr BP, thus playing a secondary role in modifying forest succession to increase resources beneficial to both humans and grazers. Over the last 1000 years, we provide evidence of directly observed human-caused modifications to the landscape. These results contribute to a growing body of literature illustrating human activities and landscape modifications in Central European mountains.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1985

Io: Mountains and crustal extension

It is argued that there is good reason to conclude that mountains on Io, like those on Earth, are subject to growth and decay. The decay of mountains will be assisted by the ability of SO sub 2 to rot silicate rock and by explosive escape of sub-surface SO sub 2 from aquifers (Haemus Mons is seen to be covered by bright material, presumably fallout from a SO sub 2 rich plume which had been active on the mountain flanks). On the west side of the massif at 10 degrees S, 270 degrees W a rugged surface consists of long ridges running perpendicular to the downslope direction, suggesting tectonic denudation with crustal blocks sliding down the mountain flank. Tectonic denudation may be assisted, as in the case of the Bearpaw Mountains, Montana by overloading mountain flanks with volcanic products. The surfaces of some massifs exhibit a well developed, enigmatic corrugated terrain, consisting of complex ridge systems. Ridges may bifurcate, anastomose to form closed depressions and form concentric loops. Taken together, observations of morphology, heat flux, surface deposits and styles of volcanism may point to the existence of lithosphere domains with distinct compositions and tectonic regimes.

Heath, M. J.↗

NASA NTRS1989

Lithology and structure within the basement terrain adjacent to Clark Mountains, California, mapped with calibrated data from the airborne visible/infrared imaging spectrometer

The Clark Mountains in eastern California form a rugged, highly dissected area nearly 5000 ft above sea level, with Clark Mountain rising to 8000 ft. The rocks of the Clark Mountains and the Mescal Range just to the south are Paleozoic carbonate and clastic rocks, and Mesozoic clastic and volcanic rocks standing in pronounced relief above the fractured Precambrian gneisses to the east. The Permian Kaibab Limestone and the Triassic Moenkopi and Chinle Formations are exposed in the Mescal Range, which is the only place in California where these rocks, which are typical of the Colorado Plateau, are found. To the west, the mountains are bordered by the broad alluvial plains of Shadow Valley. Cima Dome, which is an erosional remnant carved on a batholithic intrusion of quartz monzonite, is found at the south end of the valley. To the east of the Clark and Mescal Mountains is found the Ivanpah Valley, in the center of which is located the Ivanpah Play. Studies of the Clark Mountains with the airborne visible/infrared imaging spectrometer are briefly described.

Green, Robert O.↗

DOE OSTI2026

Mountain Basin Controls on the Snow-to-Streamflow Signal: An AIC-Weighted Multiple Linear Regression Framework

A regression-based analysis quantifies how basin characteristics modulate the snow-to-streamflow signal. First, we use the ERA5-Land reanalysis gridded product (European Centre for Medium Range Weather Forecasts reanalysis 5 -Land component) for 4,655 hydrologic unit code - 10 (HUC10) mountain basins across the western United States (US) for water years 1987–2024. Linear regressions are performed for peak snow water equivalent (SWE) and annual streamflow for each mountain basin. Models use ordinary least squares in Python’s statsmodels package. After which, an Akaike Information Criterion (AIC)–weighted ensemble multiple linear regression (MLR) framework with 47 watershed traits is used to predict the linear regression coefficient of determination (r-squared) defining the ability of peak SWE to predict annual streamflow across all mountain basin. Predictor sets are constrained to avoid multicollinearity by excluding models with variance inflation factors (VIF) greater than 5. Mountain basin traits included in the MLR include seasonal climate, topography, vegetation type and structure, and bedrock geology. Accepted models are considered if their AIC is within 2.0 of the model with the minimum AIC, or best model. To compare predictor influence across acceptable models, we computed standardized regression coefficients. To evaluate structural redundancy among models, we constructed binary inclusion vectors for each acceptable model, denoting whether a predictor was present (1) or absent (0). Core predictor variables are defined as occurring in at least 67% of the acceptable models. For this regional analysis, only one model was found acceptable, with higher snow-to-streamflow translation (higher r-squared) occurring in colder mountain basins with higher relative winter precipitation, more snow accumulation and a lower fraction of annual precipitation that falls in the spring and summer. The second component of the data package uses previously published, high-resolution output from an integrated hydrological model of the East River watershed using the U.S. Geological Survey Groundwater and Surface water Flow model (GSFLOW, doi:10.15485/1998576). East River MLR expands upon the approach described above to explore the response of five streamflow metrics—annual streamflow, runoff efficiency, 7-day minimum flow, low-flow duration, and non-perennial stream fraction to snow system indicators including peak SWE, snow-covered area, snow disappearance date, and the fraction of basin area characterized by low-to-no snow, as well as seasonal precipitation and temperature, and annual hydrologic variables representing soil moisture, evapotranspiration (ET), the partitioning of incoming precipitation to evapotranspiration (ET/P), groundwater storage, and groundwater inflow to streams. MLR was done on all water years (P0: 1987-2024) and for each period as determined in the split analysis using pooled regression techniques (P1: 1987-2011 and P2: 2012-2024) to evaluate shifting predictor variable emphasis on streamflow generation. Results indicate that since 2012, peak SWE has lost statistical strength in its prediction of annual streamflow and runoff efficiency, and the indirect influence of spring temperature has emerged as critically important. Low-flow metrics remain largely influenced by soil moisture, vegetation water use and groundwater inflows with summer precipitation becoming a direct influence on minimum summer flow. Together, these data and Python-based analysis tools provide a framework for identifying the key watershed characteristics that control how streamflow responds to snow from year to year. The package also helps quantify uncertainty in statistical models and assess how snow–streamflow relationships vary across regions and over time. This dataset contains comma-separated values files (.csv), text files (.txt), python code files (.py), figure files (.png), and shapefiles (.cpg, .dbf, .prj, .sbn, .sbx, .shp, .xml). Further details on file contents and MLR execution can be found in the readme file and the FLMD files. Work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Quantifying Groundwater Response and Uncertainty in Beaver‐Influenced Mountainous Floodplains Using Machine Learning‐Based Model Calibration

Abstract Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model‐data integration workflow to address uncertainty in groundwater response to beaver‐induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning‐based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down‐valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down‐valley underflow, from 2 during dry pond periods to 20 during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down‐valley underflow, minimizes the effect of beaver‐induced inundation on water quality. We emphasize the need for field‐scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response. Plain Language Summary Beavers change the flow of water in river corridors by creating ponds, expanding wetlands, and flooding floodplains. This increases surface water area, promotes plant growth, and enhances biodiversity. However, the impact of this flooding on groundwater flow is not well understood, especially in mountainous areas with gravel layers where water moves easily beneath soil. In this study, we used numerical modeling to investigate how beaver ponds influence groundwater in a mountainous floodplain of the Upper Colorado River Basin. We adapted a machine learning method to validate our numerical models using multiple field data sets. Our findings show that beaver ponds significantly increase vertical water flow from the soil to the gravel during wet periods, compared to when the ponds are fully drained. The study also highlights the importance of floodplain structure in controlling both water flow in gravel layers along the river direction and vertical flow from the soil to the gravel with the presence of beavers. To reduce uncertainty in groundwater response, we emphasize the need for more field‐scale measurements of floodplain structure, hydraulic properties, and evapotranspiration changes. Key Points Floodplain structures and hydraulic conductivities are important for groundwater response with beaver ponds in mountainous floodplains Large down‐valley underflow in permeability‐stratified floodplains reduces beaver‐induced impacts on groundwater storage and water quality Machine learning‐based model calibration methods are effective for estimating posterior distributions of groundwater model parameters

Wang, Lijing↗

DOE OSTI2024

Nonsteady Load Responses of Wind Turbines to Atmospheric and Mountain-Generated Turbulence Eddies, With Impacts on the Main Bearing: A Validation Study

Previous computational and field experiments identify three characteristic time scales in the aerodynamic responses of utility-scale wind turbine loads to atmospheric boundary layer (ABL) turbulence: a 30-90 second time scale for the passage of high/low speed "streaks" through the rotor plane, the blade and rotor rotation time scales (approximately 1 to 5 seconds), and a sub-second time scale created by blade rotation through gradients within eddy coherent structure. In the current study we compare aerodynamic load responses from daytime ABL turbulence quantified with large-eddy simulation and a actuator line model of the NREL 5 MW wind turbine with analysis of field data from the NREL/GE 1.5 MW wind turbine 5 kilometers east of the Rocky Mountain Front Range in Colorado. In addition, we contrast the responses to the passage of the mountain-generated eddies embedded within the westerly winds with the ABL eddies embedded within northerly/southerly winds. These analyses are in context with the nonsteady forcing of the main bearing by the aerodynamic generation of nontorque bending moments on the main shaft. Potentially relevant to main bearing failure mechanisms, both computational and field data show that the magnitudes of turbulence-generated nontorque bending moments, that we show generate nonsteady force on the main bearing, are of order, and often larger than, torque (which underlies power). However, the temporal variations in these two responses are uncorrelated, implying that the aerodynamic mechanisms that drive power and main bearing response are fundamentally different. We find this to be the case in the field with both mountain-generated eddies (westerly winds) and ABL-generated eddies (northerly/southerly winds). Whereas the time and length scales are comparable, the mountain eddies were somewhat more energetic than the northerly/southerly ABL eddies. Interestingly, however, the fluctuations in nontorque bending moment that force the main bearing were found to be stronger when forced by the ABL eddies than the mountain eddies. The field studies validate the key results from the computational study and show even stronger response in the nontorque bending moment than in the computer simulations. In all cases, the torque and nontorque bending moments are temporally uncorrelated, torque and power are driven by time variations in rotor-averaged horizontal wind velocity and nontorque bending moments are driven by time changes in the degree of nonuniformity in the distribution of velocity over the rotor plane. Thus the results generalize the mechanisms underlying nonsteady aerodynamic forcing to classes of turbulence eddy types with strength of order or stronger than ABL eddies with transverse scale of order the wind turbine rotor. These include atmospheric turbulence eddies, topography-generated turbulence eddies and, by extension, impacts of turbine-wake-scale turbulence eddies on downstream wind turbine rotors.

17 WIND ENERGY↗

NASA NTRS1985

Atmospheric electric field and current configurations in the vicinity of mountains

A number of investigations have been conducted regarding the electrical distortion produced by the earth's orography. Hays and Roble (1979) utilized their global model of atmospheric electricity to study the effect of large-scale orographic features on the currents and fields of the global circuit. The present paper is concerned with an extension of the previous work, taking into account an application of model calculations to orographic features with different configurations and an examination of the electric mapping of these features to ionospheric heights. A two-dimensional quasi-static numerical model of atmospheric electricity is employed. The model contains a detailed electrical conductivity profile. The model region extends from the surface to 100 km and includes the equalization layer located above approximately 70 km. The obtained results show that the electric field and current configurations above mountains depend upon the curvature of the mountain slopes, on the width of the mountain, and on the columnar resistance above the mountain (or mountain height).

Tzur, I.↗

NASA NTRS1990

Tertiary structure and thermal history of the Harquahala and Buckskin Mountains, west central Arizona - Implications for denudation by a major detachment fault system

A regional geometrical model for the Whipple-Buckskin-Bullard detachment system (referred to as the Whipple detachment system) is developed. Mineral separates from samples collected in the Harquahala and Buckskin mountains, which lie in the footwall of the Whipple detachment system, are analyzed by the Ar-40/Ar-39 age spectrum technique to determine the cooling history of the mountain range and the age of the metamorphism. Based on the cooling history of the mountains and the bedrock geology of the Harquahala Mountains, the initial geometry of the Whipple detachment system is reconstructed. Next, estimates of slip on the detachment fault and extension within the upper plate terrane are used to determine the regional pattern of extension. The data on the cooling history, structural geometry, and extension pattern are combined into a geometrical model which reconciles the geological data, according to which the breakaway zones represented by the Harquahala Mountains were unroofed by movement on the gently to moderately dipping segment of a great normal fault system as it cut through the upper crust.

Richard, Stephen M.↗

NASA NTRS2006

Turbulence and Mountain Wave Conditions Observed with an Airborne 2-Micron Lidar

Joint efforts by the National Aeronautics and Space Administration, the Department of Defense, and industry partners are enhancing the capability of airborne wind and turbulence detection. The Airborne Coherent Lidar (light detection and ranging) for Advanced In-Flight Measurements was flown on three series of flights to assess its capability over a range of altitudes, air mass conditions, and gust phenomena. This report describes the observation of mountain waves and turbulence induced by mountain waves over the Tehachapi and Sierra Nevada mountain ranges by lidar on board the NASA Airborne Science DC-8 (McDonnell Douglas Corporation, Long Beach, California) airplane during two flights. The examples in this report compare lidar-predicted mountain waves and wave-induced turbulence to subsequent airplane-measured true airspeed. Airplane acceleration data is presented describing the effects of the wave-induced turbulence on the DC-8 airplane. Highlights of the lidar-predicted airspeed from the two flights show increases of 12 m/s at the mountain wave interface and peak-to-peak airspeed changes of 10 m/s and 15 m/s in a span of 12 s in moderate turbulence.

Teets, Edward H., Jr.↗

NASA NTRS2006

Turbulence and mountain wave conditions observed with an airborne 2-micron lidar

Joint efforts by the National Aeronautics and Space Administration (NASA), the Department of Defense, and industry partners are enhancing the capability of airborne wind and turbulence detection. The Airborne Coherent Lidar for Advanced In-Flight Measurements (ACLAIM) was flown on three series of flights to assess its capability over a range of altitudes, air mass conditions, and gust phenomena. This paper describes the observation of mountain waves and turbulence induced by mountain waves over the Tehachapi and Sierra Nevada mountain ranges (California, USA) by lidar onboard the NASA Airborne Science DC-8 airplane. The examples in this paper compare lidar-predicted mountain waves and wave-induced turbulence to subsequent aircraft-measured true airspeed. Airplane acceleration data is presented describing the effects of the wave-induced turbulence on the DC-8 airplane. Highlights of the lidar-predicted airspeed from the two flights show increases of 12 meters per second (m/s) at the mountain wave interface and peak-to-peak airspeed changes of 10 m/s and 15 m/s in a span of 12 seconds in moderate turbulence.

Teets, Edward H., Jr.↗

NASA NTRS2007

Turbulence and Mountain Wave Conditions Observed with an Airborne 2-Micron Lidar

Joint efforts by the National Aeronautics and Space Administration (NASA), the Department of Defense, and industry partners are enhancing the capability of airborne wind and turbulence detection. The Airborne Coherent Lidar for Advanced In-Flight Measurements (ACLAIM) was flown on three series of flights to assess its capability over a range of altitudes, air mass conditions, and gust phenomena. This paper describes the observation of mountain waves and turbulence induced by mountain waves over the Tehachapi and Sierra Nevada mountain ranges in southern California by lidar onboard the NASA Airborne Science DC-8 airplane. The examples in this paper compare lidar-predicted mountain waves and wave-induced turbulence to subsequent aircraft-measured true airspeed. Airplane acceleration data is presented describing the effects of the wave-induced turbulence on the DC-8 airplane. Highlights of the lidar-predicted airspeed from the two flights show increases of 12 m/s at the mountain wave interface and peak-to-peak airspeed changes of 10 m/s and 15 m/s in a span of 12 s in moderate turbulence.

Teets, Edward H., Jr.↗