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NASA NTRS2020

DEVELOP Poster: Medicine Bow Disasters

The Medicine Bow National Forest (MBNF) consists of approximately 1,383,790 acres of forested land, grassland, and sagebrush steppe in southeastern Wyoming. Cheatgrass (Bromus tectorum), an invasive plant species in the Western US, occurs in the grasslands throughout MBNF. Cheatgrass is known to rapidly colonize disturbed sites and dramatically alter historic fire regimes and nutrient/water dynamics as well as outcompete native plant species that are important forage for mule deer (Odocoileus hemionus) and elk (Cervus canadensis). In 2012, the Squirrel Creek Fire burned approximately 10,587 acres of land within MBNF, exacerbating the spread of cheatgrass. In 2015, the Wyoming Ecological Forecasting DEVELOP team identified areas of high cheatgrass abundance within the fire boundary in order to guide US Forest Service (USFS) herbicide spraying efforts to reduce cheatgrass in 2016. This research used Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) data to create a 2019 probabilistic cheatgrass occurrence map. This map allowed an analysis of the effectiveness of aerial spraying to inform future land management techniques for the USFS. Based on the results of the Generalized Linear Model, we found that treated areas decreased in cheatgrass cover by 36% while untreated areas increased in cheatgrass cover by 6%, suggesting that herbicide treatment has been effective.

Disasters↗
NASA NTRSDate not supplied

Isotopically Tracking Nitrogen Oxides, Nitrous Acid, And Nitric Acid, Particulate Nitrate from Wildfire During FIREX-AQ

Wildfires are an important source of reactive nitrogen species including nitrogen oxides (NOx = NO + NO2) and nitrous acid (HONO), as well as products such as nitric acid (HNO3) and particulate nitrate (p-NO3-). These species have strongly influence air quality and climate. In summer of 2019 (July 25 —August 21), as part of the FIREX-AQ ground mission, we drove ~3000 miles and sampled smoke of different ages in both daytime and nighttime from 5 different wildfires in the western US. Using recently developed methods that have been validated in both laboratory and field settings, we conducted high time resolution collection of NOx, NO2, HONO, HNO3, and p-NO3- for off-line characterization of isotopic composition δ15N, δ18O and Δ17O (=δ17O−0.52 δ18O). δ15N serves as a potential tracer for tracking sources and reactive nitrogen cycling pathways, δ18O and Δ17O provide key information about oxidation pathways (i.e. O3 versus RO2). Our measured δ15N for HONO ranges from -4.9‰ to +5.2‰ and -8‰ to +5.2‰ respectively, in the majority overlapping with our prior lab controlled burning results, which suggests the capability of δ15N for tracing the biomass burning emissions against other sources including vehicular emissions and soil emissions. In addition, our measurements show δ18O and Δ17O for NO2 and HONO vary significantly day vs night, as well as in young smoke vs aged smoke, likely reflecting different oxidizing mechanisms under different smoke conditions. Preliminary results of isotopic signatures of all the above reactive nitrogen species will be presented, and their relationships will be explored to identify wildfire derived reactive nitrogen source signatures and to constrain atmospheric processing pathways (e.g. secondary formation of HONO) for different fires under various smoke conditions depending on fuel types, fire conditions and meteorological conditions.

Jiajue Chai↗
NASA NTRSDate not supplied

Influences of Solar Irradiation and Aerosol Surface Area on Nitrous Acid Production in Western U.S. Wildfire Smoke

Biomass burning has been identified as a primary emission source for a host of gas and aerosol phase compounds which can damage environmental and human health. During FIREX-AQ collaborators from UNH, NASA Langley Aerosol Research Group Experiment (LARGE), and Brown University conducted measurements out of NASA Langley’s mobile laboratory during July and August of 2019. Nitrous acid (HONO) and nitric acid (HNO3) concentrations were measured at nominal 5-minute resolution using a dual mist chamber-ion chromatograph system resulting in approximately 1,200 total samples from five separate fires in the western US. Enhancement ratios between PM2.5 and carbon monoxide were used to discriminate between young and aged smoke plumes. Average HONO concentrations were significantly higher (P << 0.01) in young daytime compared to nighttime smoke while no statistical differences (P > 0.05) were observed between young and aged smoke during day or night. In daytime smoke from the Williams Flats fire (75 km SE of Spokane, WA on the Columbia River) UV-A irradiation was highly correlated with HONO to nitrogen dioxide (NO2) ratios; indicating that heterogenous NO2 to HONO conversion more than compensated for rapid photolytic loss of HONO. Black carbon (BC) may serve as a stable proxy for total available aerosol surface area in biomass burning plumes when total aerosol size distributions are unavailable. During the day HONO/NO2 is weakly correlated to BC when BC abundance exceeds 1 ug/m3 but at lower BC concentrations the relationship breaks down. At night this relationship was stronger, partly due to consistently high BC concentrations. These observations suggest that heterogenous conversion of NO2 to HONO on aerosol is a significant source of HONO in dense smoke plumes. In more diffuse smoke conversion on other surfaces (soil, foliage) becomes more important.

J. H. Kaspari↗
NASA NTRSDate not supplied

Aerosol observations from SAGE III on the International Space Station: Visualizing Wildfires and Volcanic Eruptions

The Stratospheric Gas and Aerosol Experiment (SAGE III) aboard the International Space Station has been monitoring ozone, aerosols, and other trace gases in the stratosphere and troposphere since its 2017 launch. This presentation describes aerosol observations from SAGE, demonstrating its ability to observe volcanic eruptions and increasingly frequent wildfires, like those that occurred in the western US this year.

Atmospheric aerosols↗
NASA NTRS2018

Fusion of Multiple Low-Resolution NASA Airborne Snow Observatory (ASO) Lidar Data for Forest Vegetation Structure Characterization

Airborne lidar provides timely updated maps for monitoring forest change at high resolution but it has been little used for that purpose due to the scarcity of long-term time-series over a common area. The NASA Jet Propulsion Laboratory Airborne Snow Observatory (ASO) is a landscape-level monitoring system that provides ongoing multi-year remote sensing measurements over mountainous ecosystems to primary quantify snow volume and dynamics. It collects low-resolution lidar data (~1.5 pt/m2) with a nominal weekly frequency up to 12 times a year with measurements that span 2013-2017 over 12 mountain watersheds across the western US that currently face ecological threads. In this work, we present a method to automatically register ASO weekly low-resolution lidar point clouds in order to calculate spatially consistent datasets (~12 pt/m2) adapted to fine scale forestry studies. We test the method using 12 lidar datasets acquired over the Tuolumne River Basin (Sierra Nevada, California) in the spring and summer of 2014. On average, the ASO lidar system provides accurate measurements in terms of geolocation (0.38m and 0.12m for the horizontal and vertical dimension, respectively) but some datasets are biased up to 1.38m and 0.53m, respectively. Our registration method successfully corrected for systematic bias improving the 3D geometry of forest point clouds.

Painter, Thomas H.↗
NASA NTRSDate not supplied

The Abnormally Hot June 2021 in the Western U.S.: A MERRA-2 perspective

An extreme heat wave occurred over much of the western US and Canada in late June 2021. We use daily and monthly near-surface temperature from MERRA-2 Reanalysis to compare the hot conditions of this year with the previous 40 years, particularly over the northwestern US that was severely affected.

T2m↗
NASA NTRS2022

The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model

This work tests the hypothesis that jointly assimilating satellite observations of leaf area index and surface soil moisture into a land surface model improves the estimation of land vegetation and water variables. An Ensemble Kalman Filter is used to test such hypothesis across the Contiguous United States during April 2015 – December 2018. The performance of the proposed methodology is assessed for several modeled vegetation and water variables (evapotranspiration, net ecosystem exchange, and soil moisture) in terms of random errors and anomaly correlation coefficients against a set of independent validation datasets (i.e., Global Land Evaporation Amsterdam Model, FLUXCOM, and International Soil Moisture Network). Results show that the assimilation of leaf area index mostly improves the estimation of evapotranspiration and net ecosystem exchange, whereas the assimilation of surface soil moisture alone improves surface soil moisture content, especially in the western US, in terms of both root mean squared error and anomaly correlation coefficient. The joint assimilation of vegetation and soil moisture information combines the results of individual vegetation and soil moisture assimilations and reduces errors (and increases correlations with the reference datasets) in evapotranspiration, net ecosystem exchange, and surface soil moisture simulated by the land surface model. However, because soil moisture satellite observations only provide information on the water content in the top 5 cm of the soil column, the impact of the proposed data assimilation technique on root zone soil moisture is limited. This work moves one step forward in the direction of improving our estimation and understanding of land surface interactions using a multi-variate data assimilation approach, which can be particularly useful in regions of the world where ground observations are sparse or missing altogether.

Data assimilation↗
NASA NTRSDate not supplied

Aerosol observations from SAGE III on the International Space Station: Visualizing Wildfires and Volcanic Eruptions

The Stratospheric Gas and Aerosol Experiment (SAGE III) aboard the International Space Station has been monitoring ozone, aerosols, and other trace gases in the stratosphere and troposphere since its 2017 launch. This NASA hyperwall presentation focuses on aerosol observations from SAGE, demonstrating its ability to observe volcanic eruptions and increasingly frequent wildfires in recent years, like Raikoke in the Kuril Islands and the western US fires. [Note that presentation would be made on the NASA hyperwall, so not all captions visible to the viewer can be viewed in the PDF.]

SAGE III↗
NASA NTRS2022

Boulder County Disasters: Mapping Forest Carbon Stocks to Understand Carbon Implications of Treatment and Wildfire

In recent years, record-breaking wildfire activities in the western US illustrate the need for fire mitigation efforts, such as forest fuels reduction treatments. Forests serve as crucial carbon sinks that combat the increasing effects of climate change while fuels reduction treatments may remove carbon from forested systems. As a result, forest managers need to find a balance between fire mitigation and carbon preservation. This project partnered with Boulder County Parks and Open Space (BCPOS) and the University of Colorado, Denver to investigate the 2020 Cal-Wood fire in Boulder County, Colorado. Using remote sensing data from Landsat 8 OLI, SRTM, Sentinel-2 MSI, and LiDAR, we mapped post-fire forest carbon pools and compared these values with values derived from measurements from plots on the ground. Results indicate that the correlations are R2=0.76 for aboveground live carbon, R2=0.44 for standing carbon, and R2=0.43 for aboveground dead carbon (R2=0.43), and R2=0.35 for total carbon (R2=0.35). Additionally, 38.5% of total carbon was stored in dead carbon and 14.4% was stored in live carbon. We next compared the post-fire pools between treated and untreated areas. Our analysis suggests fuels reduction treatments did not reduce carbon loss in the presence of wildfire enough to clearly distinguish the post-fire carbon in the treated and untreated areas. However, our final carbon maps still provide BCPOS and researchers with an opportunity to explore carbon estimation models based on remotely sensed data as well as a framework to evaluate fuels reduction treatment effectiveness and impact on forest carbon stocks for future wildfire events.

Sarah Hettema↗
NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here we apply an Ensemble Kalman Filter DA system as part of the Data Assimilation Research Testbed to a variety of land surface simulations. First, we describe the use of remotely sensed biomass observations to provide improved simulations of plant phenology, carbon and water cycling for regions highly sensitive to climate change (Western US, China, and Arctic). We discuss approaches to account for systemic biases between models and observations, including the use of spatially-varying adaptive ensemble inflation as an alternative approach to re-scaling soil moisture observations. Finally, we discuss a strategy to incorporate complementary observations (snow water equivalent, solar-induced fluorescence) to better constrain the representation of carbon and water cycling across complex terrain.

DART↗
NASA NTRSDate not supplied

Aircraft Engine Particle Emissions during the 2023 NASA-Boeing ecoDemonstrator Field Measurements

Aerosol aircraft emissions are responsible for the formation of contrail cirrus clouds which can alter Earth’s radiation and water budgets exerting substantial effects on climate. However, at present, the impact of aviation on climate forcing remaining uncertain. Recently, NASA has collaborated with Boeing ecoDemonstrator program to improve the understanding of air traffic emissions and the impact of different jet fuel compositions on contrail microphysics. As part of the program, in October 2023 the NASA DC-8 aircraft was used to sample engine exhausts emitted by a Boeing ecoDemonstrator Explorer 737-10 burning sustainable aviation fuel (SAF) and conventional jet fuel over the north western US. In this study, we present unique observations of aerosols properties relevant for contrail-cirrus cloud formation collected during the 2023 ecoDemonstrator research flights and we will discuss the variations of key microphysical contrail parameters in function of different jet fuel compositions and engine conditions.

Francesca Gallo↗
NASA NTRSDate not supplied

Cumulative Distribution Overlap Technique for Artemis Mission Public Entry Risk Assessment

The Artemis missions use a skip-entry profile to accomplish a recovery near the western US coastline, however, the service module debris must still be disposed of safely. For certain contingency return scenarios, the expected dispersed entry profile is biased from the well-analyzed corridor. A novel method is presented for assessing the Cumulative Distribution Function (CDF) of these biased results to ensure they do not contribute additional probabilistic risk to the public. More specifically, the weight of the flight path angle dispersion "tail" of the CDF needs to remain below the well-assessed region. The details of how this method was actually used to screen and plan entry profiles for specific launch windows during the Artemis I mission are shown. This method has potential applicability in other problems where a biased distribution needs to be assessed against a well-defined "core" region.

Reentry↗
NASA NTRSDate not supplied

Cumulative Distribution Overlap Technique for Artemis Mission Public Entry Risk Assessment

The Artemis missions use a skip-entry profile to accomplish a recovery near the western US coastline, however, the service module debris must still be disposed of safely. For certain contingency return scenarios, the expected dispersed entry profile is biased from the well-analyzed corridor. A novel method is presented for assessing the Cumulative Distribution Function (CDF) of these biased results to ensure they do not contribute additional probabilistic risk to the public. More specifically, the weight of the flight path angle dispersion "tail" of the CDF needs to remain below the well-assessed region. The details of how this method was actually used to screen and plan entry profiles for specific launch windows during the Artemis I mission are shown. This method has potential applicability in other problems where a biased distribution needs to be assessed against a well-defined "core" region.

Reentry↗
NASA NTRS2007

Evaluation of the MOCAGE Chemistry Transport Model during the ICARTT/ITOP Experiment

We evaluate the Meteo-France global chemistry transport 3D model MOCAGE (MOdele de Chimie Atmospherique a Grande Echelle) using the important set of aircraft measurements collected during the ICARRT/ITOP experiment. This experiment took place between US and Europe during summer 2004 (July 15-August 15). Four aircraft were involved in this experiment providing a wealth of chemical data in a large area including the North East of US and western Europe. The model outputs are compared to the following species of which concentration is measured by the aircraft: OH, H2O2, CO, NO, NO2, PAN, HNO3, isoprene, ethane, HCHO and O3. Moreover, to complete this evaluation at larger scale, we used also satellite data such as SCIAMACHY NO2 and MOPITT CO. Interestingly, the comprehensive dataset allowed us to evaluate separately the model representation of emissions, transport and chemical processes. Using a daily emission source of biomass burning, we obtain a very good agreement for CO while the evaluation of NO2 points out incertainties resulting from inaccurate ratio of emission factors of NOx/CO. Moreover, the chemical behavior of O3 is satisfactory as discussed in the paper.

Bousserez, N.↗
NASA NTRS1999

Towards a Global Aerosol Climatology: Preliminary Trends in Tropospheric Aerosol Amounts and Corresponding Impact on Radiative Forcing between 1950 and 1990

A global aerosol climatology is needed in the study of decadal temperature change due to natural and anthropogenic forcing of global climate change. A preliminary aerosol climatology has been developed from global transport models for a mixture of sulfate and carbonaceous aerosols from fossil fuel burning, including also contributions from other major aerosol types such as soil dust and sea salt. The aerosol distributions change for the period of 1950 to 1990 due to changes in emissions of SO2 and carbon particles from fossil fuel burning. The optical thickness of fossil fuel derived aerosols increased by nearly a factor of 3 during this period, with particularly strong increase in eastern Asia over the whole time period. In countries where environmental laws came into effect since the early 1980s (e.g. US and western Europe), emissions and consequently aerosol optical thicknesses did not increase considerably after 1980, resulting in a shift in the global distribution pattern over this period. In addition to the optical thickness, aerosol single scattering albedos may have changed during this period due to different trends in absorbing black carbon and reflecting sulfate aerosols. However, due to the uncertainties in the emission trends, this change cannot be determined with any confidence. Radiative forcing of this aerosol distribution is calculated for several scenarios, resulting in a wide range of uncertainties for top-of-atmosphere (TOA) forcings. Uncertainties in the contribution of the strongly absorbing black carbon aerosol leads to a range in TOA forcings of ca. -0.5 to + 0.1 Wm (exp. -2), while the change in aerosol distributions between 1950 to 1990 leads to a change of -0.1 to -0.3 Wm (exp. -2), for fossil fuel derived aerosol with a "moderate" contribution of black carbon aerosol.

Tegen, Ina↗
NASA NTRS2019

A Double Bootstrap Approach to Superposed Epoch Analysis to Evaluate Response Uncertainty

The association between climate variability and episodic events, such as the antecedent moisture conditions prior to wildfire or the cooling following volcanic eruptions, is commonly assessed using Superposed Epoch Analysis (SEA). In SEA the epochal response is typically calculated as the average climate conditions prior to and following all event years or their deviation from climatology. However, the magnitude and significance of the inferred climate association may be sensitive to the selection or omission of individual key years, potentially resulting in a biased assessment of the relationship between these events and climate. Here we describe and test a modified double-bootstrap SEA that generates multiple unique draws of the key years and evaluates the sign, magnitude, and significance of event-climate relationships within a probabilistic framework. This multiple resampling helps quantify multiple uncertainties inherent in conventional applications of SEA within dendrochronology and paleoclimatology. We demonstrate our modified SEA by evaluating the volcanic cooling signal in a Northern Hemisphere tree-ring temperature reconstruction and the link between drought and wildfire events in the western United States. Finally, we make our Matlab and R code available to be adapted for future SEA applications.

Dendroclimatology↗
NASA NTRS2010

A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling of the varying AOD. These results demonstrate how the MISR and MODIS aerosol products are complementary. The underlying technique also provides one method for combining these products in such a way that takes advantage of the strengths of each, in the places and times when they are maximal, and in addition, yields an estimate of the associated uncertainties in space and time.

Chatterjee, Abhishek↗