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DOE OSTI2021

Pigment modulation in response to irradiance intensity in the fast-growing alga Picochlorum celeri

Picochlorum celeri has among the fastest photoautotrophic growth rates (~2 h doubling time in optimal conditions) reported to date for a marine alga. This study comprehensively analyzes the levels of Picochlorum celeri photosynthetic pigments, which can reach up to ~13% of the total particulate organic carbon (POC) under light-limiting conditions. The main Picochlorum celeri pigments identified include: chlorophyll a, chlorophyll b, lutein, β-carotene, canthaxanthin, violaxanthin, neoxanthin, zeaxanthin and antheraxanthin. The ketocarotenoid canthaxanthin can accumulate up to 120 mg L -1 in Picochlorum celeri liquid culture; ~12% of it was found in an extracellular polysaccharide matrix. Using a solar-simulating automated photobioreactor, we monitor the photoacclimation of cultures maintained in unshaded conditions (<0.5 μg mL -1 of total chlorophyll) through transitions from high irradiance (1000 μmoles photosynthetically active radiation (PAR) m -2 s -1 ) to low irradiance (60 μmoles PAR m -2 s -1 ), and conversely from low to high irradiance. Canthaxanthin and zeaxanthin accumulation are among the most rapid modulation responses when cultures are shifted from low to high irradiance. The violaxanthin, antherazanthin, and zeaxanthin (VAZ) pool is ~3-fold higher in high-light cultures, suggesting that the VAZ cycle combined with a dramatic reduction in chlorophyll levels are among the major mechanisms used in Picochlorum celeri to efficiently acclimate to high-irradiance levels. Responsive pigment modulation was also observed in denser cultures (~0.65 g L –1 ) grown under a diel cycle (pond-mimicking conditions). Furthermore, this research provides unique insights into the dynamics of pigment modulation and photoacclimation in response to changing irradiance in a biotechnologically promising alga and will inform future pigment engineering strategies to further improve light capture and biomass accumulation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Organic matter distribution in the icy environments of Taylor Valley, Antarctica

Glaciers can accumulate and release organic matter affecting the structure and function of associated terrestrial and aquatic ecosystems. Here we analyzed 18 ice cores collected from six locations in Taylor Valley (McMurdo Dry Valleys), Antarctica to determine the spatial abundance and quality of organic matter, and the spatial distribution of bacterial density and community structure from the terminus of the Taylor Glacier to the coast (McMurdo Sound). Our results showed that dissolved and particulate organic carbon (DOC and POC) concentrations in the ice core samples increased from the Taylor Glacier to McMurdo Sound, a pattern also shown by bacterial cell density. Fluorescence Excitation Emission Matrices Spectroscopy (EEMs) and multivariate parallel factor (PARAFAC) modeling identified one humic-like (C1) and one protein-like (C2) component in ice cores whose fluorescent intensities all increased from the Polar Plateau to the coast. The fluorescence index showed that the bioavailability of dissolved organic matter (DOM) also decreased from the Polar Plateau to the coast. Partial least squares path modeling analysis revealed that bacterial abundance was the main positive biotic factor influencing both the quantity and quality of organic matter. Marine aerosol influenced the spatial distribution of DOC more than katabatic winds in the ice cores. Certain bacterial taxa showed significant correlations with DOC and POC concentrations. Collectively, our results show the tight connectivity among organic matter spatial distribution, bacterial abundance and meteorology in the McMurdo Dry Valley ecosystem.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Vertical Hydrologic Exchange Flows Control Methane Emissions from Riverbed Sediments

CH 4 emissions from inland waters are highly uncertain in the current global CH 4 budget, especially for streams, rivers, and other lotic systems. Previous studies have attributed the strong spatiotemporal heterogeneity of riverine CH 4 to environmental factors such as sediment type, water level, temperature, or particulate organic carbon abundance through correlation analysis. However, a mechanistic understanding of the basis for such heterogeneity is lacking. Here, in this study, we combine sediment CH 4 data from the Hanford reach of the Columbia River with a biogeochemical-transport model to show that vertical hydrologic exchange flows (VHEFs), driven by the difference between river stage and groundwater level, determine CH 4 flux at the sediment–water interface. CH 4 fluxes show a nonlinear relationship with the magnitude of VHEFs, where high VHEFs introduce O 2 into riverbed sediments, which inhibit CH 4 production and induce CH 4 oxidation, and low VHEFs cause transient reduction in CH 4 flux (relative to production) due to reduced advective CH 4 transport. In addition, VHEFs lead to the hysteresis of temperature rise and CH 4 emissions because high river discharge caused by snowmelt in spring leads to strong downwelling flow that offsets increasing CH 4 production with temperature rise. Our findings reveal how the interplay between in-stream hydrologic flux besides fluvial-wetland connectivity and microbial metabolic pathways that compete with methanogenic pathways can produce complex patterns in CH 4 production and emission in riverbed alluvial sediments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Hydrological Controls on Riverbed Methane Emissions: A Numerical Investigation of Hydrodynamic and Ebullitive Mechanisms from Site to Basin Scales

Methane production and emission from riverbed sediments constitute a significant yet underexplored component of the river methane budget. Despite their importance, a mechanistic and quantitative understanding of these processes under dynamic flow conditions remains elusive, particularly at the basin scale. In this study, we investigate the multiscale (site-to-basin) mechanisms governing methane emissions from riverbeds, focusing on the interplay between biogeochemical processes and hydrological dynamics. We developed a reactive transport model that integrates methane production with hydrodynamic and ebullitive pathways and coupled it with a basin-scale groundwater flow model to simulate methane emissions across scales. By incorporating key factors such as vertical hydrological exchange flow (VHEF), particulate organic carbon availability, sediment properties, and temperature sensitivity, our model captures the spatiotemporal variability of methane ebullition at both the site and basin scales. Our results reveal that methane ebullition is strongly modulated by VHEF, with lower flow rates promoting methane accumulation and subsequent ebullition. Sensitivity analyses underscore nonlinear responses of methane fluxes to environmental drivers. Furthermore, these findings emphasize the critical roles of sediment composition, hydrological exchange, and environmental conditions in shaping methane dynamics. Overall, this work advances our understanding of riverine methane emissions and offers insights for guiding climate models and mitigation strategies.

Fluxes↗

NASA NTRS1982

Laboratory upwelled radiance and reflectance spectra of Kerr reservoir sediment waters

Reflectance, chromaticity, and several other physical and chemical properties were measured for various water mixtures of bottom sediments taken from two sites at Kerr Reservoir, Virginia. Mixture concentrations ranged from 5 to 1000 ppm by weight of total suspended solids (TSS) in filtered deionized tap water. The two sets of radiance and reflectance spectra obtained were similar in shape and magnitude for comparable values of TSS. Upwelled reflectance was observed to be a nonlinear function of TSS with the degree of curvature a function of wavelength. Sediment from the downstream site contained a greater amount of particulate organic carbon than from the upstream site. No strong conclusions can be made regarding the effects of this difference on the radiance and reflectance spectra. Near-infrared wavelengths appear useful for measuring highly turbid water with concentrations up to 1000 ppm or more. Chromaticity characteristics do not appear useful for monitoring sediment loads above 150 ppm.

Witte, W. G.↗

NASA NTRS1982

Literature review of organic matter transport from marshes

A conceptual model for estimating a transport coefficient for the movement of nonliving organic matter from wetlands to the adjacent embayments was developed in a manner that makes it compatible with the Earth Resources Laboratory's Productive Capacity Model. The model, which envisages detritus movement from wetland pixels to the nearest land-water boundary followed by movement within the water column from tidal creeks to the adjacent embayment, can be transposed to deal with only the interaction between tidal water and the marsh or to estimate the transport from embayments to the adjacent coastal waters. The outwelling hypothesis postulated wetlands as supporting coastal fisheries either by exporting nutrients, such as inorganic nitrogen, which stimulated the plankton-based grazing food chain in the water column, or through the export of dissolved and particulate organic carbon which provided a benthic, detritus-based food web which provides the food source for the grazing food chain in a more indirect fashion.

Dow, D. D.↗

NASA NTRS1988

Regional aerosol chemistry of the Amazon Basin during the dry season

The distribution and chemical composition of the atmospheric aerosol over the Amazon Basin forest were determined during the 1985 July-August dry season, using data on the aerosol chemical constituent concentration collected during the NASA Global Tropospheric Experiment Amazon Boundary Layer Experiment 2A mission. The results of the analyses suggest that there is a remarkable compositional and spatial homogeneity of the atmospheric aerosol on an extensive regional scale. Particulate organic carbon is the dominant component of the atmospheric aerosol, exhibiting an average concentration of about 740 nmol/cu m in the mixed layer and about 220 nmol/cu m in free tropospheric air. Oxalate and SO4(2-) exhibited the greatest enrichment in the mixed layer, while Cl(-) showed essentially no enrichment. The aerosol in the Amazonian atmosphere is essentially acid-base neutral, primarily as a result of incorporation of NH(+), which is presumably derived from NH3 released by the forest ecosystem.

Talbot, R. W.↗

NASA NTRS1995

Optical characterization of the oceanic unicellular cyanobacterium Synechococcus grown under a day-night cycle in natural irradiance

The optical properties of the ocenanic cyanobacterium Synechococcus (clone WH8103) were examined in a nutrient-replete laboratory culture grown under a day-night cycle in natural irradiance. Measurements of the spectral absorption and beam attenuation coefficients, the size distribution of cells in suspension, and microscopic analysis of samples were made at intervals of 2-4 hours for 2 days. These measurements were used to calculate the optical properties at the level of a single 'mean' cell representative of the acutal population, specifically, the optical cross sections for spectral absorption bar-(sigma(sub a)), scattering bar-sigma(sub b))(lambda), and attentuation bar-(sigma(sub c))(lambda). In addition, concurrent determinations of chlorophyll a and particulate organic carbon allowed calculation of the Chl a- and C-specific optical coefficients. The refractive index of cells was derived from the observed data using a theory of light absorption and scattering by homogeneous spheres. Low irradiance because of cloudy skies resulted in slow division rates of cells in the culture. The percentage of dividing cells was unusually high (greater than 30%) throughout the experiment. The optical cross sections varied greatly over a day-night cycle, with a minimum near dawn or midmorning and maximum near dusk. During daylight hours, bar-(sigma(sub b)) and bar-(sigma(sub c)) can increase more than twofold and bar-(sigma(sub a) by as much as 45%. The real part of the refractive index n increaed during the day; changes in n had equal or greater effect than the varying size distribution on changes in bar-(sigma(sub c)) and bar-(sigma(sub b)). The contribution of changes in n to the increase of bar-(sigma(sub c))(660) during daylight hours was 65.7% and 45.1% on day 1 and 2, respectively. During the dark period, when bar-(sigma(sub c))(660) decreased by a factor of 2.9, the effect of decreasing n was dominant (86.3%). With the exception of a few hours during the second light period, the imaginary part of the refractive index n' showed little variation over a day-night cycle, and bar-(sigma(sub a)) was largely controlled by variations in cell size. The real part of the refractive index at lambda = 660 nm was correlated with the intracellular C concentration and the imaginary part at lambda = 678 nm with the intracellular Chl a concentration. The C-specfic attenuation coefficient showed significant diel variability, which has implications for the estimation of oceanic primary production from measurements of diel variability in beam attenuation. This study provides strong evidence that diel variability is an important component of the optical characterization of marine phytoplankton.

Stramski, Dariusz↗

NASA NTRS1997

The CORSAGE Programme: Continuous Orbital Remote Sensing of Archipelagic Geochemical Effects

Current and pending oceanographic remote sensing technology allows the conceptualization of a programme designed to investigate ocean island interactions that could induce short-term nearshore fluxes of particulate organic carbon and biogenic calcium carbonate from pelagic island archipelagoes. These events will influence the geochemistry of adjacent waters, particularly the marine carbon system. Justification and design are provided for a study that would combine oceanographic satellite remote sensing (visible and infrared radiometry, altimetry and scatterometry) with shore-based facilities. A programme incorporating the methodology outlined here would seek to identify the mechanisms that cause such events, assess their geochemical significance, and provide both analytical and predictive capabilities for observations on greater temporal and spatial scales.

Acker, J. G.↗

NASA NTRS2005

Seasonal And Regional Differentiation Of Bio-Optical Properties Within The North Polar Atlantic

Using data collected during spring and summer seasons in the north polar Atlantic we examined the variability of the spectral absorption, a(lambda), and backscattering, b(sub b)(lambda), coefficients of surface waters and its relation to phytoplankton pigment concentration and composition. For a given chlorophyll a concentration (TChla), the concentrations of photosynthetic carotenoids (PSC), photoprotective carotenoids (PPC), and total accessory pigments (AP) were consistently lower in spring than in summer. The chlorophyll-specific absorption coefficients of phytoplankton and total particulate matter were also lower in spring, which can be partly attributed to lower proportions of PPC, PSC, and AP in spring. The spring values of the green-to-blue band ratio of the absorption coefficient were higher than the summer ratios. The blue-to-green ratios of backscattering coefficient were also higher in spring. The higher b(sub b) values and lower blue-to-green b(sub b) ratios in summer were likely associated with higher concentrations of detrital particles in summer compared to spring. Because the product of the green-to-blue absorption ratio and the blue-to-green backscattering ratio is a proxy for the blue-to-green ratio of remote-sensing reflectance, we conclude that the performance of ocean color band-ratio algorithms for estimating pigments in the north polar Atlantic is significantly affected by seasonal shifts in the relationships between absorption and TChla as well as between backscattering and TChla. Intriguingly, however, fairly good estimate of the particulate beam attenuation coefficient at 660 nm (potential measure of total particulate matter or particulate organic carbon concentration) can be obtained by applying a single blue-to-green band-ratio algorithm for both spring and summer seasons.

Stramska, Malgorzata↗

NASA NTRS2006

Online Simulations and Forecasts of the Global Aerosol Distribution in the NASA GEOS-5 Model

We present an analysis of simulations of the global aerosol system in the NASA GEOS-5 transport, radiation, and chemistry model. The model includes representations of all major tropospheric aerosol species, including dust, sea salt, black carbon, particulate organic matter, and sulfates. The aerosols are run online for the period 2000 through 2005 in a simulation driven by assimilated meteorology from the NASA Goddard Data Assimilation System. Aerosol surface mass concentrations are compared with existing long-term surface measurement networks. Aerosol optical thickness is compared with ground-based AERONET sun photometry and space-based retrievals from MODIS, MISR, and OMI. Particular emphasis is placed here on consistent sampling of model and satellite aerosol optical thickness to account for diurnal variations in aerosol optical properties. Additionally, we illustrate the use of this system for providing chemical weather forecasts in support of various NASA and community field missions.

Colarco, Peter↗

NASA NTRS2013

Underway Sampling of Marine Inherent Optical Properties on the Tara Oceans Expedition as a Novel Resource for Ocean Color Satellite Data Product Validation

Developing and validating data records from operational ocean color satellite instruments requires substantial volumes of high quality in situ data. In the absence of broad, institutionally supported field programs, organizations such as the NASA Ocean Biology Processing Group seek opportunistic datasets for use in their operational satellite calibration and validation activities. The publicly available, global biogeochemical dataset collected as part of the two and a half year Tara Oceans expedition provides one such opportunity. We showed how the inline measurements of hyperspectral absorption and attenuation coefficients collected onboard the R/V Tara can be used to evaluate near-surface estimates of chlorophyll-a, spectral particulate backscattering coefficients, particulate organic carbon, and particle size classes derived from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODISA). The predominant strength of such flow-through measurements is their sampling rate-the 375 days of measurements resulted in 165 viable MODISA-to-in situ match-ups, compared to 13 from discrete water sampling. While the need to apply bio-optical models to estimate biogeochemical quantities of interest from spectroscopy remains a weakness, we demonstrated how discrete samples can be used in combination with flow-through measurements to create data records of sufficient quality to conduct first order evaluations of satellite-derived data products. Given an emerging agency desire to rapidly evaluate new satellite missions, our results have significant implications on how calibration and validation teams for these missions will be constructed.

remote sensing↗

NASA NTRS2019

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412,443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 x 10(exp -4), 5.49 x 10(exp -4), 4.48 x 10(exp -4), 2.51 x 10(exp -4), 8.83 x 10(exp -5), and 1.36 x 10(exp -4)/sr, respectively, and 1.09 x 10(exp -2)/cu.mgm for the chlorophyll-a concentration (Chl-a), 2.09 x 10(exp -3)/m for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (a(sub g) (412)), and 3.7 mg/cu.m for particulate organic carbon (POC). These R(sub rs) values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Concha, Javier↗

NASA NTRS2019

Approach for Propagating Radiometric Data Uncertainties Through NASA Ocean Color Algorithms

Spectroradiometric satellite observations of the ocean are commonly referred to as “ocean color” remote sensing. NASA has continuously collected, processed, and distributed ocean color datasets since the launch of the Sea-viewing Wide-field-of-view Sensor (SeaWiFS) in 1997. While numerous ocean color algorithms have been developed in the past two decades that derive geophysical data products from sensor-observed radiometry, few papers have clearly demonstrated how to estimate measurement uncertainty in derived data products. As the uptake of ocean color data products continues to grow with the launch of new and advanced sensors, it is critical that pixel-by-pixel data product uncertainties are estimated during routine data processing. Knowledge of uncertainties can be used when studying long-term climate records, or to assist in the development and performance appraisal of bio-optical algorithms. In this method paper we provide a comprehensive overview of how to formulate first-order first-moment (FOFM) calculus for propagating radiometric uncertainties through a selection of bio-optical models. We demonstrate FOFM uncertainty formulations for the following NASA ocean color data products: chlorophyll-a pigment concentration (Chl), the diffuse attenuation coefficient at 490 nm (K(sub d,490)), particulate organic carbon (POC), normalized fluorescent line height (nflh), and inherent optical properties (IOPs). Using a quality-controlled in situ hyperspectral remote sensing reflectance (R(sub rs,i)) dataset, we show how computationally inexpensive, yet algebraically complex, FOFM calculations may be evaluated for correctness using the more computationally expensive Monte Carlo approach. We compare bio-optical product uncertainties derived using our test R(sub rs) dataset assuming spectrally-flat, uncorrelated relative uncertainties of 1, 5, and 10%. We also consider spectrally dependent, uncorrelated relative uncertainties in R(sub rs). The importance of considering spectral covariances in R(sub rs), where practicable, in the FOFM methodology is highlighted with an example SeaWiFS image. We also present a brief case study of two POC algorithms to illustrate how FOFM formulations may be used to construct measurement uncertainty budgets for ecologically-relevant data products. Such knowledge, even if rudimentary, may provide useful information to end-users when selecting data products or when developing their own algorithms.

Bio-optics↗

NASA NTRS2019

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412, 443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 × 10−4, 5.49 × 10−4, 4.48 × 10−4, 2.51 × 10−4, 8.83 × 10−5, and 1.36 × 10−4 sr−1, respectively, and 1.09 × 10−2 mg m−3 for the chlorophyll-a concentration (Chl-a), 2.09 × 10−3 m−1 for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (ag (412)), and 3.7 mg m−3 for particulate organic carbon (POC). These Rrs values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Geostationary Ocean Color Imager (GOCI)↗

DOE OSTI2025

Wildfire‐Induced Losses of Soil Particulate and Mineral‐Associated Organic Carbon Persist for Over 4 Years in a Chaparral Ecosystem

ABSTRACT Wildfires can lower soil carbon (C) stocks directly through combustion, but also indirectly during post‐fire recovery if microbial C demands outpace photosynthetic C inputs. However, how much C is respired by soil microorganisms post‐fire may depend on wildfire effects on particulate organic carbon (POC; mostly plant material accessible to microbes) and/or mineral‐associated organic carbon (MAOC; considered C protected by minerals from decomposers), meaning assessment of wildfire impacts on these pools is necessary to predict microbial decomposition rates and, thus, the fate of soil C. Here, we measured POC, MAOC, pyrogenic organic matter C, plant cover, extracellular enzyme activity (EEA), and microbial community abundance and composition 17 days, and 1, 3, and 4 years after the Holy Fire burned 94 km 2 of fire‐adapted chaparral. The wildfire immediately decreased POC by 50% (from 51 ± 21 to 26 ± 6 g C kg −1 ) and MAOC by 33% (from 9.3 ± 0.9 to 6.3 ± 0.9 g C kg −1 ), consistent with MAOC being less vulnerable to loss than POC. POC decreased by another 38% 1 year post‐fire, consistent with increases in microbial abundance and EEA suggesting increased microbial decomposition. Between 1 and 4 years after the fire, cover of the dominant shrub (Arctostaphylos glandulosa) increased from 3.9% ± 1.6% to 16% ± 5.4% (compared to 58% ± 4.6% in unburned plots), marking the end of net soil C losses. Still, soil C did not increase between 1 and 4 years post‐fire, suggesting plant C inputs did not outpace microbial respiration, a finding consistent with isotopically heavier C from microorganisms raising bulk soil δ 13 C values. As global changes favor increases in wildfire frequency and severity, C losses via combustion and decomposition may outpace plant C inputs during the first 4 years post‐fire in chaparral, slowing the replenishment of soil C stocks.

Biodiversity & Conservation↗

NASA NTRS2021

Relationship between circum-Arctic atmospheric wave patterns and large-scale wildfires in boreal summer

Long-term assessment of severe wildfires and associated air pollution and related climate patterns in and around the Arctic is essential for assessing healthy human life status. To examine the relationships, we analyzed the National Aeronautics and Space Administration (NASA) modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Our investigation based on this state-of-the-art atmospheric reanalysis data reveals that 13 out of the 20 months with the highest PM2.5 (corresponding to the highly elevated organic carbon in the particulate organic matter [POM] form) monthly mean mass concentration over the Arctic for 2003–2017 were all in summer (July and August), during which POM of ⩾0.5 μg/cu. m and PM2.5 were positively correlated. This correlation suggests that high PM2.5 in the Arctic is linked to large wildfire contributions and characterized by significant anticyclonic anomalies (i.e. clockwise atmospheric circulation) with anomalous surface warmth and drier conditions over Siberia and subpolar North America, in addition to Europe. A similar climate pattern was also identified through an independent regression analysis for the July and August mean data between the same atmospheric variables and the sign-reversed Scandinavian pattern index. We named this pattern of recent atmospheric circulation anomalies the circum-Arctic wave (CAW) pattern as a manifestation of eastward group-velocity propagation of stationary Rossby waves (i.e. large-scale atmospheric waves). The CAW induces concomitant development of warm anticyclonic anomalies over Europe, Siberia, Alaska, and Canada, as observed in late June 2019. Surprisingly, the extended regression analysis of the 1980–2017 period revealed that the CAW pattern was not prominent before 2003. Understanding the CAW pattern under future climate change and global warming would lead to better prediction of co-occurrences of European heatwaves and large-scale wildfires with air pollution over Siberia, Alaska, and Canada in and around the Arctic in summer.

wildfire↗

DOE OSTI2023

2017 Meander C sediment characterization from the East River, Colorado

This dataset includes characterization data collected on sediment samples from Meander C as part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected to investigate the nature of mineral-organic associations across the meander transect and with depth. Samples were collected in 2017, and analyzed using sequential extractions (water, pyrophosphate, HCl, and dithionite) and density fractionation. Data collected include: texture, pH, root biomass, and metals (Fe, Al, Ca, Si) of bulk sediment samples; C and N of heavy fraction; and extractable OC, Fe, and Al, and organic matter characterization using high-resolution mass spectrometry (FT-ICR-MS) of sequential extractions. Sample locations are included in the ‘sample_metadata.xlsx” file. Sediment characterization data is included in the accompanying csv files: bulk and density fractions (MCB2017_density-and-bulk-fractions.csv), sequential extractions (MCB2017_sequential-extractions.csv), and FT-ICR-MS data from sequential extractions in three files to be read by the R package ftmsRanalysis (MCB2017_FTICRMS-sequential-edata.csv, MCB2017_FTICRMS-sequential-emeta.csv, and MCB2017_FTICRMS-sequential-fdata.csv). Sediment was collected in triplicate; ID’s refer to individual samples.

54 ENVIRONMENTAL SCIENCES↗