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NASA NTRS2021

A Visual Tour of Carbon Export by Sinking Particles

To better quantify the ocean's biological carbon pump, we resolved the diversity of sinking particles that transport carbon into the ocean's interior, their contribution to carbon export, and their attenuation with depth. Sinking particles collected in sediment trap gel layers from four distinct ocean ecosystems were imaged, measured, and classified. The size and identity of particles was used to model their contribution to particulate organic carbon (POC) flux. Measured POC fluxes were reasonably predicted by particle images. Nine particle types were identified, and most of the compositional variability was driven by the relative contribution of aggregates, long cylindrical fecal pellets, and salp fecal pellets. While particle composition varied across locations and seasons, the entire range of compositions was measured at a single well-observed location in the subarctic North Pacific over one month, across 500 m of depth. The magnitude of POC flux was not consistently associated with a dominant particle class, but particle classes did influence flux attenuation. Long fecal pellets attenuated most rapidly with depth whereas certain other classes attenuated little or not at all with depth. Small particles (<100 m) consistently contributed ~5% to total POC flux in samples with higher magnitude fluxes. The relative importance of these small particle classes (spherical mini pellets, short oval fecal pellets, and dense detritus) increased in low flux environments (up to 46% of total POC flux). Imaging approaches that resolve large variations in particle composition across ocean basins, depth, and time will help to better parameterize biological carbon pump models

Carbon flux↗

NASA NTRS2018

Remote Sensing of CDOM, CDOM Spectral Slope, and Dissolved Organic Carbon in the Global Ocean

A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245–715 nm, CDOM spectral slopes in eight visible and ultraviolet wavebands, dissolved and particulate organic carbon (DOC and POC, respectively), and inherent optical, physical, and biogeochemical properties. From field optical and radiometric data and satellite measurements, several semi-analytical, empirical, and machine learning algorithms for retrieving global DOC, CDOM, and CDOM slope were developed, optimized for global retrieval, and validated. Global climatologies of satellite-retrieved CDOM absorption coefficient and spectral slope based on the most robust of these algorithms lag seasonal patterns of phytoplankton biomass belying Case 1 assumptions, and track terrestrial runoff on ocean basin scales. Variability in satellite retrievals of CDOM absorption and spectral slope anomalies are tightly coupled to changes in atmospheric and oceanographic conditions associated with El Niño Southern Oscillation (ENSO), strongly covary with the multivariate ENSO index in a large region of the tropical Pacific, and provide insights into the potential evolution and feedbacks related to sea surface dissolved carbon in a warming climate. Further validation of the DOC algorithm developed here is warranted to better characterize its limitations, particularly in mid-ocean gyres and the southern oceans.

Dissolved organic carbon↗

NASA NTRS2023

Broader Impacts and Outreach Videos on Ocean Physics and Biogeochemistry

This is just a preliminary NF1676 in advance of filming for a project....A convergent team of experts in biology, chemistry, physics, engineering, mathematics, and computational modeling examine how dynamic and coupled phytoplankton-pathogen-particle-predator linkages coalesce to explain the observed high spatial variability in the efficiency of the export of particulate organic carbon (POC) to the deep ocean. They elucidate and quantify the linkages between viruses and ballast minerals to increase understanding of carbon cycling in the oceanic biological carbon pump and the impact of viruses within it. By providing knowledge than can be used to improve the parameterization of carbon export in Earth system models, the project will help reduce uncertainty in regional marine biogeochemical projections, potentially improving marine ecosystem and fisheries management on timescales from seasons to decades. The project includes activities that provide teaching resources and hands-on training to educators within a ‘Tools of Science’ program that provides a simple and succinct way to communicate the process of scientific research to students in a way that is useful to teachers. The project couples laboratory-based experiments on model host-virus-grazer systems with extensive field based observational and manipulative studies on natural populations of diatoms and coccolithophores, the two phytoplankton groups that account for most of the estimated particulate organic matter flux to the deep ocean. Experiments and measurements integrate diagnostic biological and chemical controls on infection and particle coagulation theory with microscale physics and grazing to quantify links to each hypothesized export mechanism under field-relevant turbulent conditions. Cutting-edge engineering and analytical tools are used to diagnose and track infection dynamics while characterizing and quantifying particle aggregation and disaggregation, mineral dissolution, sinking dynamics, grazing rates, and fecal pellet production at unprecedented resolution and under well-defined, microscale physical regimes. Field campaigns elucidate the relative efficiency of hypothesized mechanisms in stimulating POC export in natural blooms, while providing bulk and size-resolved estimates of POC flux.

Daniel B Whitt↗

NASA NTRS2012

Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon?

Ocean color data assimilation has been shown to dramatically improve chlorophyll abundances and distributions globally and regionally in the oceans. Chlorophyll is a proxy for phytoplankton biomass (which is explicitly defined in a model), and is related to the inorganic carbon cycle through the interactions of the organic carbon (particulate and dissolved) and through primary production where inorganic carbon is directly taken out of the system. Does ocean color data assimilation, whose effects on estimates of chlorophyll are demonstrable, trickle through the simulated ocean carbon system to produce improved estimates of inorganic carbon? Our emphasis here is dissolved inorganic carbon, pC02, and the air-sea flux. We use a sequential data assimilation method that assimilates chlorophyll directly and indirectly changes nutrient concentrations in a multi-variate approach. The results are decidedly mixed. Dissolved organic carbon estimates from the assimilation model are not meaningfully different from free-run, or unassimilated results, and comparisons with in situ data are similar. pC02 estimates are generally worse after data assimilation, with global estimates diverging 6.4% from in situ data, while free-run estimates are only 4.7% higher. Basin correlations are, however, slightly improved: r increase from 0.78 to 0.79, and slope closer to unity at 0.94 compared to 0.86. In contrast, air-sea flux of C02 is noticeably improved after data assimilation. Global differences decline from -0.635 mol/m2/y (stronger model sink from the atmosphere) to -0.202 mol/m2/y. Basin correlations are slightly improved from r=O.77 to r=0.78, with slope closer to unity (from 0.93 to 0.99). The Equatorial Atlantic appears as a slight sink in the free-run, but is correctly represented as a moderate source in the assimilation model. However, the assimilation model shows the Antarctic to be a source, rather than a modest sink and the North Indian basin is represented incorrectly as a sink rather than the source indicated by the free-run model and data estimates.

Gregg, Watson↗

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)↗

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↗

NASA NTRS1989

Distributions of Manganese, Iron, and Manganese-Oxidizing Bacteria In Lake Superior Sediments of Different Organic Carbon Content

Profiles of oxygen, soluble and particulate manganese and iron, organic carbon and nitrogen were examined in Lake Superior sediment cores, along with the distribution and abundance of heterotrophic and manganese oxidizing bacteria. Analyses were performed using cores collected with the submersible Johnson Sea Link II. Three cores, exhibiting a range of organic carbon content, were collected from the deepest basin in Lake Superior and the north and south ends of the Caribou trough, and brought to the surface for immediate analysis. Minielectrode profiles of oxygen concentration of the three cores were carried out using a commercially available minielectrode apparatus. Oxygen depletion to less than 1% occurred within 4 cm of the surface for two of the cores, but not until approximately 15 cm for the core from the south basin of the Caribou trough. The three cores exhibited very different profiles of soluble, as well as leachable, manganese and iron, suggesting different degrees of remobilization of these metals in the sediments. Vertical profiles of viable bacteria and Mn oxidizing bacteria, determined by plating and counting, showed that aerobic (and facultatively aerobic) heterotrophic bacteria were present at the highest concentrations near the surface and decreased steadily with depth, while Mn oxidizing bacteria were concentrations primarily at and above the oxic/anoxic interface. Soluble manganese in the pore waters, along with abundant organic carbon, appeared to enhance the presence of manganese oxidizing bacteria, even below the oxic/anoxic interface. Profiles of solid-phase leachable manganese suggested a microbial role in manganese reprecipitation in these sediments.

Richardson, Laurie L.↗

NASA NTRS2013

Ocean Biological Pump Sensitivities and Implications for Climate Change Impacts

The ocean is one of the principal reservoirs of CO2, a greenhouse gas, and therefore plays a crucial role in regulating Earth's climate. Currently, the ocean sequesters about a third of anthropogenic CO2 emissions, mitigating the human impact on climate. At the same time, the deeper ocean represents the largest carbon pool in the Earth System and processes that describe the transfer of carbon from the surface of the ocean to depth are intimately linked to the effectiveness of carbon sequestration.The ocean biological pump (OBP), which involves several biogeochemical processes, is a major pathway for transfer of carbon from the surface mixed layer into the ocean interior. About 75 of the carbon vertical gradient is due to the carbon pump with only 25 attributed to the solubility pump. However, the relative importance and role of the two pumps is poorly constrained. OBP is further divided to the organic carbon pump (soft tissue pump) and the carbonate pump, with the former exporting about 10 times more carbon than the latter through processes like remineralization.Major uncertainties about OBP, and hence in the carbon uptake and sequestration, stem from uncertainties in processes involved in OBP such as particulate organicinorganic carbon sinkingsettling, remineralization, microbial degradation of DOC and uptakegrowth rate changes of the ocean biology. The deep ocean is a major sink of atmospheric CO2 in scales of hundreds to thousands of years, but how the export efficiency (i.e. the fraction of total carbon fixation at the surface that is transported at depth) is affected by climate change remains largely undetermined. These processes affect the ocean chemistry (alkalinity, pH, DIC, particulate and dissolved organic carbon) as well as the ecology (biodiversity, functional groups and their interactions) in the ocean. It is important to have a rigorous, quantitative understanding of the uncertainties involved in the observational measurements, the models and the projections of future changes.

particulates↗