Global Transmissometer Database V3 (Coupled with CTD data)

December 2020

Transmissometer Data collected by: Wilford D. Gardner1, Mary Jo Richardson1 et al.

Data post-processed and Database constructed by: Alexey V. Mishonov1,2,3, Wilford D. Gardner1, Mary Jo Richardson1

ODV collection created by: Alexey Mishonov1,2,3

ODV Software: Schlitzer, Reiner, Ocean Data View, https://odv.awi.de, 2020. 1 Department of Oceanography, Texas A&M University, College Station, TX 77843-3146 2 Cooperative Institute for Satellite Earth System Studies, ESSIC/University of Maryland, College Park, MD 20740-3823 3 National Center for Environmental Information, NESDIS/NOAA, Silver Spring, MD 20910-3282

Please cite this document and database as: Gardner, W.D., A.V. Mishonov, M.J. Richardson, 2020. Global Transmissometer Database V3. https://odv.awi.de/data/ocean/global-transmissometer-database/

ABSTRACT

Our extensive collection of transmissometer data has been organized into a coherent database to address numerous questions about the global distribution of particulate matter using an important inherent optical property - beam attenuation (c), which can be correlated with the concentration of particulate organic carbon (POC) in surface waters and total particulate matter throughout the water column. By interfacing transmissometers with CTDs we have collected 11,684 beam attenuation profiles during 107 cruises conducted during WOCE-World Ocean Circulation Experiment, JGOFS-Joint Global Ocean Flux Study, SAVE-South Atlantic Ventilation Experiment, NEGOM-North-East Gulf of Mexico, and other programs since 1979 and additional corrected beam attenuation data collected at BATS (Bermuda Atlantic Time Series) and HOT (Hawaii Ocean Time-Series) locations. The coverage includes basin-wide transects in the North and South Atlantic, North and South Pacific, Indian, and Southern Oceans, as well as several repeat basin-wide transects on decadal time scales. Transmissometer profiles were uniformly quality controlled, edited, and converted to a common format. Data were loaded into the Ocean Data View (ODV) database management system for geo-referenced data and organized as ODV collection.

The data have been collected as part of numerous field programs funded primarily through NSF to WDG and MJR. Numerous publications using these data are referenced below. Data post-processing and construction of the database were supported by NSF grants OCE-9986762 and OCE-0137171 to WDG, MJR and AVM as part of the JGOFS Synthesis and Modeling Program (SMP), and grant OCE-1536565.

Data are freely available for scientific use as an ODV-collection from the ODV web site as well as from CCHDO and NCEI archives as a set of independent cruises/profiles.

Associated CTD data (temperature, salinity & oxygen) collected on the same cruises are also loaded into this collection. CTD data have been imported from appropriate websites (mostly CCHDO and WOD) and were not a subject for our analyses. All questions regarding those data should be addressed to the respective data originators.

1. Study Areas

Our group has collected transmissometer data since 1979 all around the world (shown in Figure 1) during WOCE (Pacific, Indian and Southern Oceans), JGOFS (North Atlantic Bloom Experiment, Equatorial Pacific, Arabian Sea, Ross Sea, Antarctic Polar front Zone-Pacific sector), SAVE (South Atlantic), GO-SHIP, several Gulf of Mexico expeditions, GEOTRACES, and other programs. Many of these data have been published and a synthesis of the WOCE and JGOFS data was completed as part of our previous NSF-SMP grant (NSF OCE-9986762). This collection includes transmissometer measurements from 107 cruises, including corrected historic data collected at HOT (1991-1995) and BATS (1988-2001) sites. (OCE-0137171).

Figure 1. Global distribution of the data included in Version 3.

2. Optical Data

Beam attenuation data from the areas noted above were collected during 107 cruises from 1979 to 2020 (see Figure 2) and includes 11,684 full-depth profiles. Measurements made during WOCE and other programs up to about year 2000 used a total of 16 different SeaTech transmissometers (serial #: 15D, 26D, 63D, 100D, 102D, 114D, 115D, 148D, 151D, 152D, 156D, 173D, 203D, 264AD, 265D, 266D). Post-WOCE data (after 2000) were collected using one of 14 WetLabs/SeaBird C-STAR transmissometers (327DR, 339DR, 399DR, 490DR, 492DR, 493DR, 507DR, 515DR, 1028DR, 1115DR, 1119DR, 1636DR, 1722DR, 1803DR).

The SeaTech transmissometer measured the beam attenuation coefficient in the red spectral band (λ = 660 nm). Attenuation of the light beam across the transmissometer’s 25 cm path length (r) was obtained using

the same procedure for all cruises making the data comparable and uniform. In brief, the percent transmission of light (Tr) was measured and then converted to beam attenuation (c) using the equation c = -r-1 * ln(Tr). Beam attenuation (c) is the sum of attenuation due to particles (cp), water (cw), and colored dissolved organic matter (cdom): c = cp + cw + ccdom. According to several studies, ccdom is small enough to be ignored in measurements at 660 nm in open waters. Attenuation due to water cw is essentially constant for the SeaTech instrument at a factory-calibrated value of 0.364 m-1.

Figure 2. Temporal distribution of the data included in Version 3.

WetLabs developed and built the next generation of instruments, naming them C-STAR transmissometers and one could choose the desired wavelength and pathlength. For compatibility with the SeaTech instruments, we used C-STARs with 25 cm path length and similar spectral band (λ = 650 nm). The instruments were calibrated at the factory in particle-free water and adjusted to compensate for the attenuation due to water. A reading was made in particle-free water and then in factory air. Thus, air measurements could be made in the field regularly to monitor sensor stability and determine whether changes in air values resulted from drift in the instrument’s sensor (LED burnout) or from fowled windows. This information is used to correct the C-STAR readings during data post-processing if needed. SeaBird Scientific acquired WetLabs and they updated instrument’s firmware to adjust for temperature hysteresis (Gardner et al., 1985, Bishop 1986, Ohnemus et al., 2018).

Thus,

Cp = - 1/r * ln (((Vsig -Vfielddark) / (Vfact -Vfactdark)) *(Vfactair/Vfieldair))

Where: Vsig is the measured output signal in the field, Vfielddark is the dark value (blocked path) for the instrument in the field, Vfact is the factory-supplied voltage for the instrument in particle-free water, Vfactdark is the factory-supplied dark voltage value, Vfactair is the factory-supplied voltage value for the instrument air measurements, Vfieldair is voltage value for the instrument air measurements in the field.

3. Transmissometer Data reduction

The majority of original raw transmissometer data were acquired during both down and up casts of the CTD/rosette. The down trace is generally the preferred trace because the sensors are less obstructed by the rosette structure during descent, however, water bottles are routinely tripped during the ascent, so it is essential to record transmissometer data at the time and depth of the bottle trip as well. Having both down and up traces provides an opportunity to compare the two profiles to check for instrumental errors in the data and to use the up trace if there are problems with the down trace. Temperature hysteresis can cause slight differences between down and up traces, especially where temperature gradients are large (Gardner et al., 1985; Bishop, 1986; Ohnemus et al., 2018). Compared to the typical signal variability in surface waters, the effect of hysteresis is small.

The data collected by SeaTech instruments were subject to extensive post-processing described in (i) below. The C-STAR data were filtered and binned with the CTD data, which were sampled at 30Hz and binned in standard 2 db pressure intervals and were then post-processed as described in (ii) and thereafter.

(i). The data reduction procedure was applied uniformly to all data. This procedure consisted of several detailed steps using customized software algorithms, which processed down and up casts as briefly described below. This procedure included:

a) Pressure checking and filtering: due to ship heave and roll during the cast, the CTD-probe sometimes experienced a brief reverse excursion, so pressure values were checked for non-monotonic values and depth-inversions were filtered;

b) An initial large-spike removal was performed using two filter windows depending on depth. Window range was set to 0.274-1.245 m-1 (which corresponds to 15300-12000 counts of the raw data) for 0-100 m depth, and 0.274-0.572 m-1 (15300-14200 counts) below 100 m depth;

c) Additional spike checking and removal was performed using a gradient check;

d) Data binning: data were averaged over 2 m depth intervals centered at the even numbers (i.e. 0, 2, 4, 6, ... m depth), but near-surface data between 2 and 6 m depth were often excluded because of air bubbles contamination in surface waters;

e) Instrument calibrations: data were recalculated from the volts to the physical units using the pre-cruise, during-cruise and post-cruise calibration values. When Vfielddark and Vfieldair were taken multiple times during the cruise, the calibration values could be linearly interpolated for every day in the cruise between the dates when calibrations occurred and applied to the data.;

f) Profile minimum determination.

(ii). After the first step all data were loaded into a preliminary database for visual checking and examination, which included:

a) Checking for remaining spikes likely representative of individual large particles;

b) Checking for the "nose"-feature, which sometimes occurred with SeaTech instruments, but not with the WetLabs/SeaBird C-STAR instruments. The “nose” is a smooth, roughly normally distributed (with depth) peak in beam attenuation values that occurred between 200-800 m depth. The manufacturer believed it was due to condensation onto electronic components inside the instrument (not on the windows) and is most likely to occur when the instrument has been heated in the sun on the ship deck prior to deployment. Up casts seldom had the “nose” feature;

c) Checking for excessive noise;

d) Checking for the necessity of a uniform profile shift, which can occur due to “fowled windows,” sensor trend, or instrumental offsets.

(iii). After the second step, data were manually edited:

a) Final removal of any remaining spikes, which passed through the software filtration;

b) Profile editing – when profiles with artifacts such as the “nose” had no associated up profile, or profile has an excessive noise segment due to problems with electrical connectors, we eliminated those segments of the data profile.

(iv). Assessment of general cruise trends and minimum values in profiles:

a) The minimum profile value, its depth and the station bottom depth were analyzed for each profile on every cruise. This allowed detection of any cruise-long decay in the instrument settings. This cruise trend assessment was based on the minimum signal values recorded only at open-ocean, deep-water stations (deeper than 750m);

b) Cruise trend correction and profile normalization were made by shifting the entire profile so that the profile’s minimum value in deep water (defined as the water deeper than 750 m and more than 750 m above the seafloor) was set equal to the cruise’s minimum. For the shallow-water stations (less that 750 m depth) the cruise-mean minimum deep-water value was applied.

(v). Final database loading was performed after all the above steps have been completed. The final database for each cruise was used for further global quality checks and construction of maps and sections.

4. Global Quality check

During our forty-plus years of measurements, multiple transmissometer units have been used to collect data. Sometimes instruments have been switched within the same cruise due to malfunction or use of multiple CTDs. Therefore it is necessary to determine the variability of the data caused by use of multiple instruments. Our basic assumption has been that deep-waters are highly stable and constant in terms of hydro-optical characteristics. We used the minimum beam c values measured in deep water as an absolute minimum value of every cruise. The SeaTech manufacturer (Bartz, personal communication) proposed this approach and we have used it in modified ways during processing of the JGOFS transmissometer data. It has proven to be widely applicable as long as there are some stations in deep water available in the cruise data set.

As a means of comparing data between cruises (which could be seasons or years apart in time), we overlaid beam c profiles obtained during different cruises in places where stations were located in close proximity (within 1° longitude-latitude circle) to each other. We referred to such points as "crossings". A total of 24 crossings with two or more stations measured during different cruises were chosen: 10 in the Atlantic (22 stations), 10 in the Pacific (20 stations) and 4 in the Indian (8 stations) Oceans for data collected prior to 2000 by SeaTech instruments

Comparison of the mid-water part of the beam c profiles (~1000 m to ~4000 m) shows very good agreement of data from different cruises for nearly all crossings. Reproducibility at crossings is better when the same instrument is used on different cruises rather than different instruments, suggesting there may be some small instrumental differences in the data at depth. SeaTech transmissometers may be perfectly calibrated in air over a range of temperatures, but it appears that there may be different responses to pressure that cannot be easily tested for without a simultaneous full-depth deployment of instruments. We made a few simultaneous deployments of two SeaTech transmissometers from the same production batch and found that they produced identical profiles, but that does not guarantee that all SeaTech transmissometers used would track each other throughout the entire water column. The most important data come from the upper 100 m, where the signal is strongest, and although it is not possible to distinguish between temporal and instrumental differences from these data, we do not believe there is much difference in euphotic zone data obtained with different instruments. If differences exist, they appear to occur primarily in deeper water as differing instrumental responses to pressure, and those differences are small.

We have not had the opportunity to compare profiles using different C-STAR instruments at the same location.

Due to lack of in-situ particle sampling on many cruises and lack of particle-free water for shipboard calibration, the best solution was to set the cruise minimum value to 0. This means we can’t compare particle minima between oceans, however, the uncertainty in measurements at the low minimum values from many different instruments over four decades convinced us this was the best solution. Our filtering data from many oceans shows minimum concentrations of about 5-12 µg l-1 (Gardner et al., 2018a), which is much smaller than concentrations in surface waters and many nepheloid layers.

5. Beam Attenuation coefficient

Sections of transects and maps we produced have been published in the papers listed in references below, most notably in Gardner et al., 2018a, 2018b, 2018c and supporting materials in those papers.

6. Regressions for different regions/programs

This large data set allowed us to assess the relationship between POC and beam cp in various regions and during different seasons. Since beam cp is a function of particle size, shape and index of refraction, one might expect the beam cp to POC relation to vary regionally and temporally during the cycle of a bloom and spatially as regimes with different community structures are encountered (Gundersen et al., 1998; Gardner et al., 2000, 2003, 2006). The beam cp profiles exhibit very little structure below 200-300 m depth except on some continental margins. In areas where resuspension of bottom sediments creates bottom nepheloid layers the beam attenuation signal increases. Regression of beam cp vs. POC does not apply in those regions because much of the material in the water is fine-grained clays as well as POC phytodetritus. We have also used the cp/POC correlations combined with satellite data to estimate POC concentrations in South Atlantic surface waters (Mishonov et al., 2003) and the Gulf of Mexico (Son et al., 2009).

Many of the papers listed below relate beam cp to total particulate matter concentration (PM) throughout the water column (e.g. Gardner et al., 1985; Gardner, 1989; Gundersen et al., 1998). These correlations have enabled us to map nepheloid layers globally (Gardner et al., 2017; 2018a, b, c;)

We invite you to look through these data because there are many other insights to be gained from these files by comparing them with data you have collected.

Papers published by our group using the data included in this database.

Gardner, W.D., P.E. Biscaye, J.R.V. Zaneveld and M.J. Richardson, 1985. Calibration and comparison of the LDGO nephelometer and the OSU transmissometer on the Nova Scotian Rise. Marine Geology, 66: 323-344.

Gardner, W.D., M.J. Richardson, I.D. Walsh, and B.L. Berglund, 1990. In-situ optical sensing of particles for determination of oceanic processes: what satellites can't see, but transmissometers can. Oceanography, 3: 11-17.

Gardner, W.D., I.D. Walsh, and M.J. Richardson, 1993. Biophysical forcing of particle production and distribution during a spring bloom in the North Atlantic. Deep-Sea Research, 40: 171-195.

Gardner, W.D., S.P. Chung, M.J. Richardson, and I.D. Walsh, 1995. The oceanic mixed-layer pump. Deep-Sea Research II, 42: 757-775.

Walsh, I.D., S.P. Chung, M.J. Richardson and W.D. Gardner, 1995. The diel cycle in the Integrated Particle Load in the Equatorial Pacific: A Comparison with Primary Production. Deep-Sea Research II, 42: 465-477.

Chung, S.P., W.D. Gardner, M.J. Richardson, I.D. Walsh, and M.R. Landry, 1996. Beam attenuation and microorganisms: Spatial and temporal variations in small particles along 140°W during 1992 JGOFS-EqPac transects. Deep-Sea Research II, 43: 1205-1226.

Gardner, W.D., 1997. Visibility in the ocean and the effects of mixing. Quarterdeck 5: 4-9. Richardson, M.J. and W.D. Gardner, 1997. Tools of the trade. Quarterdeck 5: 10-15. Archer, D., J. Aiken, W. Balch, R. Barber, J. Dunne, W. D. Gardner, C. Garside, C. Goyet, E. Johnson, D.

Kirchman, M. McPhaden, J. Newton, E. Peltzer, L. Welling, J. White and J. Yoder, 1997. A meeting place of great ocean currents: shipboard observations of a convergent front at 2°N in the Pacific. Deep-Sea Research II, 44: 1827-1849.

Walsh, I.D., W.D. Gardner, M.J. Richardson, S-P. Chung, C.A. Plattner and V. Asper, 1997. Particle dynamics as controlled by the flow field of the Eastern Equatorial Pacific. Deep-Sea Research II, 44: 2025-2047.

Chung, S.P. W.D. Gardner, M.R. Landry, M.J. Richardson and I.D. Walsh, 1998. Beam attenuation by microorganisms and detrital particles in the equatorial Pacific. Journal of Geophysical Research, 103: 12,669-12,681.

Gundersen, J.S., W.D. Gardner, M.J. Richardson and I.D. Walsh, 1998. Effects of monsoons on the seasonal and spatial distributions of POC and chlorophyll in the Arabian Sea. Deep-Sea Research II, 45: 2103-2132.

Gardner, W.D., Gundersen, J.S., M.J. Richardson and I.D. Walsh, 1999. The role of diel variations in mixed-layer depth on the distribution, variation, and export of carbon and chlorophyll in the Arabian Sea. Deep-Sea Research II, 46: 1833-1858.

Morrison, J., L.A. Codispoti, S.L. Smith, K. Wishner, C. Flagg, W.D. Gardner, S. Gaurin, S.W.A. Naqvi, V. Manghnani, L. Prosperie and. J. Gundersen, 1999. The oxygen minimum zone in the Arabian Sea during 1995. Deep Sea Research II, 46: 1903-1931.

Gardner, W.D., M.J. Richardson, and W.O. Smith, 2000. Seasonal Patterns of Water Column Particulate Organic Carbon and Fluxes in the Ross Sea, Antarctica. Deep-Sea Research II, 47: 3423-3449.

Gardner, W.D., J.C. Blakey, I.D. Walsh, M.J. Richardson, S. Pegau, J.R.V. Zaneveld, C. Roesler, M.C. Gregg, J.A. MacKinnon, H.M. Sosik and A.J. Williams, III, 2001. Optics, particles, stratification and storms on the New England continental shelf. Journal of Geophysical Research, 106: 9473-9497.

Morrison, J., S. Gaurin, L.A. Codispoti, T. Takahashi, F.J. Millero, W.D. Gardner, and M.J Richardson, 2001. Seasonal evolution of the hydrographic properties during the Antarctic Circumpolar Current at 170°W during 1997-1998, 2001. Deep-Sea Research II, 48: 3943-3972.

Gardner W.D., M.J. Richardson, C.A. Carlson, D.A. Hansell, and A.V. Mishonov, 2003. Determining True Particulate Organic Carbon: Bottles, Pumps and Methodologies. Deep-Sea Research II, 50: 655 – 674.

Mishonov, A.V., W.D. Gardner, and M. J. Richardson, 2003. Remote sensing and surface POC concentration in the South Atlantic. Deep-Sea Research II, 50: 2997-3015.

Gardner, W.D. and M.J. Richardson, 2005. Temporal and spatial variability of particulate matter in the Ross Sea, Spring-Fall 1996-1997. Antarctic Journal of the U.S. 33:259-261.

Zawada, D.G., J.R.V. Zaneveld, E. Boss, W.D. Gardner, M.J. Richardson, and A.V. Mishonov, 2005. A comparison of hydrographically- and optically-derived mixed layer depths. Journal of Geophysical Research, 110, C11001, doi:10.1029/2004JC002417.

Gardner, W.D. A.V. Mishonov, and M.J. Richardson, 2006. Global POC concentrations from in-situ and satellite data. Deep-Sea Research II, 53 (5-7): 718-740. DOI: doi:10.1016/j.dsr2.2006.01.029.

Son, Y.B., W.D. Gardner, A.V. Mishonov, and M.J. Richardson, 2009. Multispectral Remote Sensing Algorithms for Particulate Organic Carbon (POC): the Gulf of Mexico. Remote Sensing of Environment, 113: 50–61. DOI: 10.1016/j.rse.2008.08.011.

Son, Y.B., W.D. Gardner, A.V. Mishonov, and M.J. Richardson, 2009. Model-based remote sensing algorithms for particulate organic carbon (POC) in the Northeastern Gulf of Mexico. Journal of Earth System Science, 118 (1): 1-10.

Son, Y.B. and W.D. Gardner, 2010. Determining spatial and temporal variations of surface particulate organic carbon (POC) using in situ measurements and remote sensing data in the Northeastern Gulf of Mexico during El Niño and La Niña. The Sea, Journal of the Korean Society of Oceanography, 15 (2): 51-61.

Son, Y.B. and W.D. Gardner, 2011. Climatological variability of surface particulate organic carbon (POC) and physical processes based on ocean color data in the Gulf of Mexico. Korean Journal of Remote Sensing, 27(3): 235-258.

Son, Y.B., W.D. Gardner, M.J. Richardson, J. Ishizaka, J.H. Ryu, Y.H. Ahn, H.-C. Kim, S.H. Kim, S.H. Lee, 2012. Tracing offshore low-salinity plumes in the northeastern Gulf of Mexico during the summer season by use of multispectral remote-sensing data. Journal of Oceanography, DOI: 10.1007/s10872-012-0131-y.

Boss, E., L. Guidi, M.J. Richardson, L. Stemmann, W.D. Gardner, J.K.B. Bishop, R.F. Anderson, R.M. Sherrell, 2015. Optical techniques for remote and in-situ characterization of particles pertinent to GEOTRACES. Progress in Oceanography, 133, 43-54. doi: http://dx.doi.org/10.1016/j.pocean.2014.09.007.

Gardner, W.D., M.J. Richardson, A.V. Mishonov, 2018a. Global Assessment of Benthic Nepheloid Layers and Linkage with Upper Ocean Dynamics. Earth and Planetary Science Letters, 482: 126–134. https://doi.org/10.1016/j.epsl.2017.11.008.

Gardner, W.D., A.V. Mishonov, M.J. Richardson, 2018b. Decadal Comparisons of Particulate Matter in Repeat Transects in the Atlantic, Pacific, and Indian Ocean Basins. Geophysical Research Letters, 45 (1): 277-286. https://doi.org/10.1002/2017GL076571. Supplemental Material: 8 pp https://doi.org/10.1002/2017GL076571.

Gardner, W.D., M.J. Richardson, A.V. Mishonov, P.E. Biscaye, 2018c. Global comparison of benthic nepheloid layers based on 52 years of nephelometer and transmissometer measurements. Progress in Oceanography, 168: 100-111, ISSN 0079-6611, https://doi.org/10.1016/j.pocean.2018.09.008.

John, S., H. Liang, T. Weber, DeVries, T.F. Primeau, K. Moore, M. Holzer, N. Mahowald, W.D. Gardner, A.V. Mishonov, M.J. Richardson, Y. Faugere, G. Taburet, 2020. AWESOME OCIM: A simple, flexible, and powerful tool for modeling elemental cycling in the oceans. Chemical Geology, 533: 119403. https://doi.org/10.1016/j.chemgeo.2019.119403.

Lerner, P., O. Marchal, P. Lam, W.D. Gardner, A.V. Mishonov, M.J. Richardson, 2020. A Model Study of the Relative Influences of Scavenging and Circulation on 230Th and 231Pa in the western North Atlantic. Deep-Sea Research I, 155: 103159. https://doi.org/10.1016/j.dsr.2019.103159.

Gardner, W.D., M.J. Richardson, A.V. Mishonov, P.J. Lam, Y. Xiang, Sources, Distribution, and Dynamics of Particulate Matter Along Trans-Arctic Sections. Journal of Geophysical Research – Oceans, (submitted 9/2020).

Other papers referenced: Bishop, J.K.B., 1986. The correction and suspended particulate matter calibration of Sea Tech transmissometer data.

Deep-Sea Research, 33: 121-134. Ohnemus, D.C., Lam, P.J., Twining, B.S., 2017. Optical observation of particles and responses to particle

composition in the GEOTRACES GP16 section. Marine Chemistry, 201: 124-136, doi:10.1016/j.marchem.2017.09.004.

Other papers published by our group using transmissometer data outside this database or using other optical instruments (e.g. Lamont nephelometer, backscatter devices) Gardner, W.D. and L.G. Sullivan, 1981. Benthic storms: Temporal variability in a deep ocean nepheloid layer.

Science, 213: 329-331. Gardner, W.D., 1983. Suspended sediment transport in Baltimore Canyon and adjacent slope. In: Canyon and Slope

Processes Study, Vol. II, MMS Final Report, p. 135-241. Gardner, W.D., J.K.B. Bishop and P.E. Biscaye, 1984. Nephelometer and current observations at the STIE site,

Panama Basin. Journal of Marine Research, 42: 207-219. Gardner, W.D., L.G. Sullivan and E.M. Thorndike, 1984. Long-term photographic, current, and nephelometer

observations of manganese nodule environments in the Pacific. Earth and Planetary Science Letters, 70: 95-109.

Richardson, M.J., P.E. Biscaye, W.D. Gardner and N.G. Hogg, 1987. Suspended particulate matter transport through the Vema Channel. Marine Geology, 77: 171-184.

Gardner, W.D., 1989. Baltimore Canyon as a modern conduit of sediment to the deep sea. Deep-Sea Research, 36: 323-358.

Gardner, W.D., 1989. Periodic resuspension in Baltimore Canyon by focusing of internal waves. Journal of Geophysical Research, 94: 18185-18194.

Richardson, M.J., G.L. Weatherly, and W.D. Gardner, 1993. Benthic storms in the Argentine Basin. Deep-Sea Research, 40: 957-987.

Laine, E.P., W.D. Gardner, M.J. Richardson, and M. Kominz, 1994. Abyssal currents and advection of resuspended sediment along the northeastern Bermuda Rise. Marine Geology, 119: 159-171.

Gardner, W.D., Biscaye, P.E. and Richardson, M.J., 1997. A Sediment trap Experiment in the Vema Channel to Evaluate the Effect of Horizontal Particle Fluxes on Measured Vertical Fluxes. Journal of Marine Research, 55: 995-1028.

Boss, E., W.S. Pegau, W.D. Gardner, J.R.V. Zaneveld, A.H.B. Barnard, M.S. Twardowski, G.C. Chang, and T.D. Dickey, 2001. The Spectral Particulate Attenuation and Particle Size Distribution in the Bottom Boundary Layer of a Continental Shelf. Journal of Geophysical Research, 106: 9509-9516.

Karageorgis, A.P., W.D. Gardner, D. Georgopoulos, A.V. Mishonov, E. Krasakopoulou, C. Anagnostou, 2008. Particle dynamics in the Eastern Mediterranean Sea: A synthesis based on light transmission, PMC, and POC archives (1991-2001). Deep-Sea Research I, 55: 177-202. DOI: 10.1016/j.dsr.2007.11.002.

Ross, C.B., W.D. Gardner, M.J. Richardson, V.L. Asper, 2009. Currents and sediment transport in the Mississippi Canyon and effects of Hurricane Georges. Continental Shelf Research, 29: 1384–1396.

Karageorgis, A.P., Gardner, W.D., Mikkelsen, O.A., Georgopoulos, D., Ogston, A.S., Assimakopoulou, G., Krasakopoulou, E., Oaie, Gh., Secrieru, D., Kanellopoulos, Th.D., Pagou, K., Anagnostou, Ch., Papathanassiou, E., 2014. Particle sources over the Danube River Delta, Black Sea based on distribution, composition and size using optics, imaging and bulk analyses. Journal of Marine Systems, 131: 74–90.

Karageorgis A.P., Georgopoulos D., Gardner W.D., Mikkelsen, O.A., Velaoras D., 2015. How schlieren affects beam transmissometers and LISST-Deep: an example from the stratified Danube River delta, NW Black Sea. Mediterranean Marine Science, 16/2: 366-372. DOI: 10.12681/mms.1116 http://www.medit-mar-sc.net/index.php/marine/article/view/1116.

Gardner, W.D., B.E. Tucholke, M.J. Richardson, P.E. Biscaye, 2017. Benthic storms, nepheloid layers, and linkage with upper ocean dynamics in the Western North Atlantic. Marine Geology, 385: 304-327. (Invited Review article), http://dx.doi.org/10.1016/j.margeo.2016.12.012