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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Quantifying the Impact of BOReal Forest Fires on Tropospheric Oxidants Over the Atlantic Using Aircraft and Satellites (BORTAS) Experiment: Design, Execution, and Science Overview

We describe the design and execution of the BORTAS (Quantifying the impact of BOReal forest fires on Tropospheric oxidants using Aircraft and Satellites) experiment, which has the overarching objective of understanding the chemical aging of airmasses that contain the emission products from seasonal boreal wildfires and how these airmasses subsequently impact downwind atmospheric composition. The central focus of the experiment was a two-week deployment of the UK BAe-146-301 Atmospheric Research Aircraft (ARA) over eastern Canada. The planned July 2010 deployment of the ARA was postponed by 12 months because of activities related to the dispersal of material emitted by the Eyjafjallaj¨okull volcano. However, most other planned model and measurement activities, including ground-based measurements at the Dalhousie University Ground Station (DGS), enhanced ozonesonde launches, and measurements at the Pico Atmospheric Observatory in the Azores, went ahead and constituted phase A of the experiment. Phase B of BORTAS in July 2011 included the same measurements, but included the ARA, special satellite observations and a more comprehensive measurement suite at the DGS. Integrating these data helped us to describe pyrogenic plumes from wildfires on a wide spectrum of temporal and spatial scales. We interpret these data using a range of chemistry models, from a near-explicit gas-phase chemical mechanism to regional and global models of atmospheric transport and lumped chemistry. We also present an overview of some of the new science that has originated from this project.

BORTAS↗
NASA NTRS2014

Prediction of the Arctic Oscillation in Boreal Winter by Dynamical Seasonal Forecasting Systems

This study assesses the skill of boreal winter Arctic Oscillation (AO) predictions with state-of-the-art dynamical ensemble prediction systems (EPSs): GloSea4, CFSv2, GEOS-5, CanCM3, CanCM4, and CM2.1. Long-term reforecasts with the EPSs are used to evaluate how well they represent the AO and to assess the skill of both deterministic and probabilistic forecasts of the AO. The reforecasts reproduce the observed changes in the large-scale patterns of the Northern Hemispheric surface temperature, upper level wind, and precipitation associated with the different phases of the AO. The results demonstrate that most EPSs improve upon persistence skill scores for lead times up to 2 months in boreal winter, suggesting some potential for skillful prediction of the AO and its associated climate anomalies at seasonal time scales. It is also found that the skill of AO forecasts during the recent period (1997-2010) is higher than that of the earlier period (1983-1996).

Arctic Oscillation↗
NASA NTRS2014

The Uncertainty of Biomass Estimates from LiDAR and SAR Across a Boreal Forest Structure Gradient

In this study, weexamined the uncertainty of aboveground live biomass (AGB) estimates based on light detection and ranging (LiDAR) and synthetic aperture radar (SAR) measurements distributed across a low-biomass vegetation structure gradient fromforest to non-forest in boreal-like ecosystems. The conifer-dominant structure gradient was compiled from ground data amassed from multiple field expeditions in central Maine (USA), Aurskog (Norway), and across central Siberia (Russia). Single variable empirical models were built tomodel AGB fromremote sensingmetrics. Using thesemodels, we calculated a rootmean square error (RMSE) and a 95% confidence interval (CI) of the RMSE fromthe difference between the remote sensing AGB predictions and the ground reference AGB estimates within AGB intervals across a 0-100 Mg ha(exp.−1) boreal forest structure gradient. The results show that the error in AGB predictions (RMSE) and the error uncertainty (the CI) from LiDAR and SAR change across a forest gradient. The errors of airborne LiDAR and SAR metrics and spaceborne LiDAR platforms show a general trend of reduced relative errors as AGBmagnitudes increase, particularly from0 to 60 Mg ha (exp.−1). Empirical models relating spaceborne metrics to AGB and estimates of spaceborne LiDAR error uncertainty demonstrate the difficulty of characterizing differences in AGB at the site-level with current spaceborne sensors, particularly below 80 Mg ha (exp.−1) with less than 50-100% error.

Taiga↗
NASA NTRS2016

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Landsat-8 snow albedo↗
NASA NTRS2016

Comparison of Mesospheric Winds From a High-Altitude Meteorological Analysis System and Meteor Radar Observations During the Boreal Winters of 2009-2010 and 2012-2013

We present a study of horizontal winds in the mesosphere and lower thermosphere (MLT) during the boreal winters of 2009-2010 and 2012-2013 produced with a new high-altitude numerical weather prediction (NWP) system. This system is based on a modified version of the Navy Global Environmental Model (NAVGEM) with an extended vertical domain up to approximately 116 km altitude coupled with a hybrid four-dimensional variational (4DVAR) data assimilation system that assimilates both standard operational meteorological observations in the troposphere and satellite-based observations of temperature, ozone and water vapor in the stratosphere and mesosphere. NAVGEM-based MLT analyzed winds are validated using independent meteor radar wind observations from nine different sites ranging from 69 deg N-67 deg S latitude. Time-averaged NAVGEM zonal and meridional wind profiles between 75 and 95 km altitude show good qualitative and quantitative agreement with corresponding meteor radar wind profiles. Wavelet analysis finds that the 3-hourly NAVGEM and 1-hourly radar winds both exhibit semi-diurnal, diurnal, and quasi-diurnal variations whose vertical profiles of amplitude and phase are also in good agreement. Wavelet analysis also reveals common time-frequency behavior in both NAVGEM and radar winds throughout the Northern extra tropics around the times of major stratospheric sudden warmings (SSWs) in January 2010 and January 2013, with a reduction in semi-diurnal amplitudes beginning around the time of a mesospheric wind reversal at 60 deg N that precedes the SSW, followed by an amplification of semi-diurnal amplitudes that peaks 10-14 days following the onset of the mesospheric wind reversal. The initial results presented in this study demonstrate that the wind analyses produced by the high altitude NAVGEM system accurately capture key features in the observed MLT winds during these two boreal winter periods.

McCormack, J.↗
NASA NTRS2016

High Upward Fluxes of Formic Acid from a Boreal Forest Canopy

Eddy covariance fluxes of formic acid, HCOOH, were measured over a boreal forest canopy in spring/summer 2014. The HCOOH fluxes were bidirectional but mostly upward during daytime, in contrast to studies elsewhere that reported mostly downward fluxes. Downward flux episodes were explained well by modeled dry deposition rates. The sum of net observed flux and modeled dry deposition yields an upward gross flux of HCOOH, which could not be quantitatively explained by literature estimates of direct vegetative soil emissions nor by efficient chemical production from other volatile organic compounds, suggesting missing or greatly underestimated HCOOH sources in the boreal ecosystem. We implemented a vegetative HCOOH source into the GEOS-Chem chemical transport model to match our derived gross flux and evaluated the updated model against airborne and spaceborne observations. Model biases in the boundary layer were substantially reduced based on this revised treatment, but biases in the free troposphere remain unexplained.

forest↗
NASA NTRS2018

Detecting Early Warning Signals of Tree Mortality in Boreal North America Using Multiscale Satellite Data

Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems.

heat↗
NASA NTRS2018

Impacts of Snow Darkening Effects by Light Absorbing Aerosols on Hydroclimate of Eurasia During Boreal Spring and Summer

In this study, we used the NASA GEOS-5 climate model to investigate the impact of snow darkening by light-absorbing aerosols on the hydro-climate if Eurasia during boreal spring and summer. Two sets of 10-member ensemble model integrations with prescribed sea surface temperature were carried out for 10 simulated years (2002-2011); one includes snow-darkening effects (SDE) by light-absorbing aerosols, and one does not (NSDE). Differences between the two experiments in the hydro-climates over Eurasia were evaluated. Results show that SDE warming is most pronounced during the melting season due to strong snow-albedo feedback in the vicinity of the retreating seasonal snowline. SDE spurs a Wet-First-Dry-Later (WFDL) modulation of the surface energy and water balances, characterized by an accelerated (days-to-weeks) snowmelt along with excessive runoff and a warming and wetting of the land during the early part of the melting season. The fast snowmelt is followed by a prolonged (> months) warming and desiccation of the land, stemming from a deficit of late-season snowmelt water and increased surface evaporation. The prolonged warming and drying of the land atmosphere system persist through the summer, sustained by atmospheric conditions favorable for the development of atmospheric blocking, i.e., higher mid-to-upper tropospheric geopotential height, lower relative humidity, reduced cloudiness and enhanced atmospheric subsidence. Overall, SDE by light absorbing aerosols leads to a warmer and drier boreal summer hydro-climate, increasing the frequency of the top 5% and 1% extreme hot days (as defined by NSDE statistics) over western and northern Eurasia by approximately three-fold and tenfold, respectively.

Snow darkening↗
NASA NTRS2019

Diurnal and Seasonal Solar Induced Chlorophyll Fluorescence and Photosynthesis in a Boreal Scots Pine Canopy

Solar induced chlorophyll fluorescence has been shown to be increasingly an useful proxy for the estimation of gross primary productivity (GPP), at a range of spatial scales. Here, we explore the seasonality in a continuous time series of canopy solar induced fluorescence (hereafter SiF) and its relation to canopy gross primary production (GPP), canopy light use efficiency (LUE), and direct estimates of leaf level photochemical efficiency in an evergreen canopy. SiF was calculated using infilling in two bands from the incoming and reflected radiance using a pair of Ocean Optics USB2000+ spectrometers operated in a dual field of view mode, sampling at a 30 min time step using custom written automated software, from early spring through until autumn in 2011. The optical system was mounted on a tower of 18 m height adjacent to an eddy covariance system, to observe a boreal forest ecosystem dominated by Scots pine. (Pinus sylvestris) A Walz MONITORING-PAM, multi fluorimeter system, was simultaneously mounted within the canopy adjacent to the footprint sampled by the optical system. Following correction of the SiF data for O2 and structural effects, SiF, SiF yield, LUE, the photochemicsl reflectance index (PRI), and the normalized difference vegetation index (NDVI) exhibited a seasonal pattern that followed GPP sampled by the eddy covariance system. Due to the complexities of solar azimuth and zenith angle (SZA) over the season on the SiF signal, correlations between SiF, SiF yield, GPP, and LUE were assessed on SZA <50° and under strictly clear sky conditions. Correlations found, even under these screened scenarios, resulted around ~r2 = 0.3. The diurnal responses of SiF, SiF yield, PAM estimates of effective quantum yield (ΔF/Fm′), and meteorological parameters demonstrated some agreement over the diurnal cycle. The challenges inherent in SiF retrievals in boreal evergreen ecosystems are discussed.

photosynthetic↗
NASA NTRS2019

Boreal Canopy Surfaces from Spaceborne Stereogrammetry

Surface elevation estimates from high resolution spaceborne image (HRSI) stereogrammetry are used to examine fine-scaled structure of boreal forest canopies. These data can depict detailed spatial patterns of vertical forest structure at remote sites across the circumpolar domain where these estimates would otherwise be unavailable. This work examines where these estimates are most effective at describing vertical forest structure to explain which canopy surfaces they represent. We evaluated the variation in canopy surface estimates captured from four general types of HRSI digital surface models (DSMs) across the full range of boreal canopy cover.

Paul M Montesano↗
NASA NTRS2019

The Role of Oceanic Processes in the Initiation of Boreal Winter Intraseasonal Oscillations over the Indian Ocean

Observational analyses and a hierarchy of ocean general circulation model (OGCM) experiments were performed to understand the influence of oceanic processes on the warm sea surface temperature anomalies (SSTAs) prior to the convection initiation of boreal winter intraseasonal oscillations (ISOs), including the Madden-Julian Oscillation (MJO), in the equatorial Indian Ocean. We found 39 strong ISOs that passed over the Indian Ocean Warm Pool region during the November-April season of the 2001-2012 period. 17/39 ISO events initiated in the Seychelles-Chagos Thermocline Ridge (SCTR) before propagating eastward; the remaining events initiated in the southern Arabian Sea (6) or Warm Pool (16) regions. The SCTR event set was notable in that it contained more global-scale MJOs (71-76%), as defined by the RMM and OMI indices, than the WP events (25-44%). Additionally, ~24% (44%) of the SCTR (Warm Pool) events were preceded by strong oceanic process-induced SSTAs of similar magnitude to those of shortwave radiative and turbulent heat fluxes. The Arabian Sea events, however, were not associated with statistically significant SSTA signals prior to convection. Based on a mixed layer heat budget analysis, entrainment and upwelling reduction were the dominant oceanic processes contributing to the warming, in contrast with boreal summer, when horizontal advection dominated. We examined several case studies, including primary MJO events, where oceanic Rossby waves were associated with the entrainment and upwelling reduction. Two simple atmospheric boundary layer convergence models revealed that the SSTAs contributed at least half of the total convergence and suggested that the ocean dynamical effect was responsible for the majority of SSTA-forced convergence for those case studies. These results underscore the need for climate prediction models to accurately represent the ocean structure and processes to include the effects of oceanic predictors.

West, B. Jason↗
NASA NTRS2022

Mineral Inputs, Paleoecological Change, and Holocene Carbon Accumulation at a Boreal Peatland in the Hudson Bay Lowlands, Canada

The Hudson Bay Lowlands (HBL) is a vast contiguous peatland extending over >370,000 km2 in Canada's boreal-subarctic, and is the traditional land of the Omushkego Cree. It is currently undergoing climatic warming alongside other anthropogenic stressors, and contains a large below-ground carbon pool. Understanding how climate variability and multiple stressors impact peat accumulation in this region is critical to discerning how northern peatlands will respond to future climate and land-use changes. Pollen- and macrofossil-based paleoecological reconstructions, and analyses of aluminum (Al) and titanium (Ti) fluxes in a Holocene-aged peat core (VM375) taken from a bog in the Attawapiskat watershed were conducted to link ecosystem changes with hydroclimate and long-term carbon storage. Peat initiation is dated to 5780 cal yr B.P., coincident with land emergence driven by glacial isostatic adjustment. From 4500 to 4200 cal yr B.P., apparent rate of carbon accumulation increased, and was linked to more rapid rates of peat accretion and increases in minerotrophic indicators in the pollen record. This increase in peat accretion and shift in vegetation composition co-occur with higher rates of mineral influx as shown by Ti and Al concentrations, which may have supplied nutrients. A fen to bog transition takes place ~3300 cal yr B.P., with increases in Sphagnum spores and macrofossils, and a decline in the apparent rate of carbon accumulation relative to the earlier half of the record, where paleoecological proxies indicate treed wetland and fen stages. Since peat inception, the total carbon stock of the 260-cm peat column is 110 kg C m−2. This multi-proxy record shows an association between changing peat types and variability in apparent rates of carbon accumulation, and supports the hypothesis that mineral nutrients either supplied by surface hydrology or by eolian deposition played a role in Holocene peat carbon accumulation in eastern North American boreal peatlands.

Dust↗
NASA NTRS2024

Integrating State Data Assimilation and Innovative Model Parameterization Reduces Simulated Carbon Uptake in the Arctic and Boreal Region

Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic‐boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8‐day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. To further reduce the remaining bias in GPP after LAI bias correction, we re‐parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.

land data assimilation↗
NASA NTRS2002

Verification of satellite radar remote sensing based estimates of boreal and subalpine growing seasons using an ecosystem process model and surface biophysical measurement network information

We employ daily surface Radar backscatter data from the SeaWinds Ku-band Scatterometer onboard Quikscat to estimate landscape freeze-thaw state and associated length of the seasonal non-frozen period as a surrogate for determining the annual growing season across boreal and subalpine regions of North America for 2000 and 2001.

boreal growing season radar monitoring boreal ecol↗
NASA NTRS1997

NSCAT Observation of Spring Thaw in Alaskan Boreal Forest

The focus of this effort is the assessment of spaceborne scatteromter observations for monitoring landscape freeze/thaw transitions in the boreal forest thereby providing a means for estimating growing season duration.

Spring thaw Alaskan boreal forest NSCAT temperatur↗
NASA NTRS1994

(abstract) Characterization of Tree Water Status and Dielectric Constant Changes of North American Boreal Forests in Combination with Synthetic Aperture Radar Remote Sensing

The occurrence and magnitude of temporal and spatial tree water status changes in the boreal environment were studied in a floodplain forest in Alaska and in four forest types of Central Canada. Under limited water supply conditions from the rooted soil zone in early spring (freeze/thaw transition) and during summer, trees show declining water potentials. Coincidental change in tree water potential, tree transpiration and tree dielectric constant had been observed in previous studies performed in Mediterranean ecotones. If radar is sensitive to chances in tree water status as reflected through changes in dielectric constant, then radar remote sensing could be used to monitor the water status of forests. The SAR imagery is examined to determine the response of the radar backscatter to the ground based observations of the water status of forest canopies. Comparisons are made between stands and also along the large North-South gradient between sites. Data from SAR are used to examine the radar response to canopy physiological state as related to vegetation freeze/thaw and growing season length.

remote sensing imaging↗
NASA NTRS2018

Convective Influence on the Humidity and Clouds in the Tropical Tropopause Layer During Boreal Summer

The impact of convection on the humidity and clouds in the tropical tropopause layer (TTL) during boreal summer 2007 is investigated in simulations of detailed cloud microphysical processes and their effects on the water vapor (H2O) profile along backward trajectories from the 379 K potential temperature (100‐hPa pressure) surface. Convective influence is determined by tracing the trajectories through time‐dependent fields of satellite‐based convective cloud top height. The simulated H2O mixing ratios at the 100‐hPa level and cloud occurrence fractions in the middle to upper (16–18 km) TTL exhibit a pronounced maximum over the Asian monsoon region as in observations; these local enhancements are virtually absent in the simulation without convection, indicating that convection is the dominant driver of the localized H2O and cloud maxima in the Asian summer monsoon region. Convection moistens the 100‐hPa level by 0.6 ppmv (~15%) averaged over the 10°S–50°N domain and increases tropical (10°S–30°N) mean cloud occurrence in the middle to upper TTL by ~170%. Nearly all of the convective enhancements in H2O and clouds are due to the effect of convective saturation; convectively detrained ice crystals have negligible impact. Parcels are most frequently hydrated by deep convection in the southern sector of the Asian monsoon anticyclone and subsequently dehydrated downstream of convection to the west, shifting the locations of final dehydration northwest of the cold temperature region in the northern Tropics. Infrequent, extreme deep convective systems (cloud tops exceeding 380 K) have a disproportionately large effect on TTL humidity and clouds.

Humidity↗