A modified method for estimating vertical profiles of turbulent dissipation rate using density inversions in the Kuril Straits

To address the lack of directly measured turbulence data in the Kuril Straits, an existing method was modified to indirectly estimate continuous vertical profiles of turbulent energy dissipation rate ε by using density inversions. A linear relationship was confirmed between directly measured ε and indirectly estimated ε from the existing method, where most of the detected density inversions were discarded as noise. The existing method thus yielded large gaps in the vertical profiles, and the gaps were much greater than the observed mean autocorrelation vertical length scale of about 10 m. To reduce these gaps and produce reasonable estimates for vertical ε profiles, the quality tests were carefully re-examined with directly measured ε data, and one of the quality tests (the water mass test) was excluded because the test rejects real density inversions even with large ε. With this modification, and interpolation and smoothing of the indirectly estimated ε with the mean correlation length scale, continuous vertical ε profiles were obtained. These profiles have an error factor of 3.3 corresponding to one standard deviation of the ratio between directly observed and estimated data, and 95 % of the data were within a factor of 10.5, with the overall correlation coefficient between smoothed directly measured ε and estimated ε equal to 0.80. This method could be useful for areas where 10^?9 < ε < 10^?6.5 W/kg, and where vertical distances between adjacent density inversions are mostly less than the mean autocorrelation scale.     

Estimating photosynthetically available radiation at the ocean surface from ADEOS-II global imager data

A simple, yet efficient and fairly accurate algorithm is presented to estimate photosynthetically available radiation (PAR) at the ocean surface from Global Imager (GLI) data. The algorithm utilizes plane-parallel radiation-transfer theory and separates the effects of the clear atmosphere and clouds, i.e., the planetary atmosphere is modeled as a clear atmosphere positioned above a cloud layer. PAR is computed as the difference between the incident 400–700 nm solar flux at the top of the atmosphere (known) and the solar flux reflected back to space by the atmosphere and surface (derived from GLI radiance), taking atmospheric absorption into account. Knowledge of pixel composition is not required, eliminating the need for cloud screening and arbitrary assumptions about sub-pixel cloudiness. For each GLI pixel, clear or cloudy, a daily PAR estimate is obtained. Diurnal changes in cloudiness are taken into account statistically, using a regional diurnal albedo climatology based on 5 years of Earth Radiation Budget Satellite (ERBS) data. The algorithm results are verified against other satellite estimates of PAR, the National Centers for Environmental Prediction (NCEP) reanalysis product, and in-situ measurements from fixed buoys. Agreement is generally good between GLI and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) estimates, with root-mean-squared (rms) differences of 7.9 (22%), 4.6 (13%), and 2.7 (8%) Einstein/m²/day on daily, weekly, and monthly time scales, and a bias of only 0.8–0.9 (about 2%) Einstein/m²/day. The rms differences between GLI and Visible and Infrared Spin Scan Radiometer (VISSR) estimates and between GLI and NCEP estimates are smaller and larger, respectively, on monthly time scales, i.e., 3.0 (7%) and 5.0 (14%) Einstein/m²/day, and biases are 1.1 (2%) and −0.2 (−1%) Einstein/m²/day. The comparison with buoy data also shows good agreement, with rms inaccuracies of 10.2 (23%), 6.3 (14%), and 4.5 (10%) Einstein/m²/day on daily, weekly, and monthly time scales, and slightly higher GLI values by about 1.0 (2%) Einstein/m²/day. The good statistical performance makes the algorithm suitable for large-scale studies of aquatic photosynthesis.     

Retrieval of chlorophyll-a concentration via linear combination of ADEOS-II Global Imager data

Top-of-atmosphere reflectance measured above the ocean in the visible and near infrared, after correction for molecular scattering, may be linearly combined to retrieve surface chlorophyll-a abundance directly, without explicit correction for aerosol scattering and absorption. The coefficients of the linear combination minimize the perturbing effects, which are modeled by a polynomial, and they do not depend on geometry. The technique has been developed for Global Imager (GLI) spectral bands centered at 443, 565, 667, and 866 nm, but it is applicable to other sets of spectral bands. Theoretical performance is evaluated from radiation-transfer simulations for a wide range of geophysical and angular conditions. Using a polynomial with exponents of −2, −1, and 0 to determine the coefficients, the residual influence of the atmosphere on the linear combination is within ±0.001 in most cases, allowing chlorophyll-a abundance to be retrieved with a root-mean-squared (RMS) error of 8.4% in the range 0.03–3 mgm⁻³. Application of the method to simulated GLI imagery shows that estimated and actual chlorophyll-a abundance are in agreement, with an average RMS difference of 32.1% and an average bias of −2.2% (slightly lower estimated values). The advantage of the method resides in its simplicity, flexibility, and rapidity of execution. Knowledge of aerosol amount and type is avoided. There is no need for look-up tables of aerosol optical properties. Accuracy is adequate, but depends on the polynomial representation of the perturbing effects and on the bio-optical model selected to relate the linear combination to chlorophyll-a abundance. The sensitivity of the linear combination to chlorophyll-a abundance can be optimized, and the method can be extended to the retrieval of other bio-optical variables.     

Sensitive determination of enzymatically labile dissolved organic phosphorus and its vertical profiles in the oligotrophic western North Pacific and East China Sea

Trace concentrations of labile dissolved organic phosphorus (LDOP) in oligotrophic seawater were measured by use of an enzymatic procedure and a nanomolar phosphate analytical system consisting of a gas-segmented continuous flow analyzer with a liquid waveguide capillary cell. LDOP, defined as DOP hydrolyzed by alkaline phosphatase (AP) from Escherichia coli, was quantified as the difference between the phosphate concentrations of the seawater sample with and without AP treatment. For sensitive measurement of LDOP, we found that phosphate contamination derived from commercially available AP must be corrected, and azide treatment before AP treatment proved effective in removing biological effect that occurs during DOP hydrolysis. Field observations at six stations of the western North Pacific and the East China Sea during the boreal summer revealed that, in the upper 200 m of the water column, LDOP concentrations ranged from the detection limit (3 nM) to 243 nM, and phosphate concentrations ranged from 5 to 374 nM. The spatial distribution patterns of LDOP were similar to those of phosphate. Most of the depth profiles for LDOP and phosphate showed concentrations were extremely low, <25 nM, between the surface and the deep chlorophyll maximum layer (DCML) and increased below the DCML. Strongly depleted LDOP and phosphate above the DCML suggest that LDOP is actively hydrolyzed under phosphate-depleted conditions and utilized by microbes.     

Mass balance and sources of mercury in Tokyo Bay

The mass balance and sources of mercury in Tokyo Bay were investigated on the basis of observations from December 2003 to January 2005. Estimated input terms included river discharge (70 kg yr⁻¹) and atmospheric deposition (37 kg yr⁻¹), and output terms were evasion (49 kg yr⁻¹), export (13 kg yr⁻¹) and sedimentation (495 kg yr⁻¹). Thus, the outputs (557 kg yr⁻¹) considerably exceeded the inputs (107 kg yr⁻¹). In addition, the imbalance between the inputs and outputs of mercury was much larger than that of other trace metals (Cd, Cr, Cu, Pb and Zn), which suggests that there are other major inputs of mercury to Tokyo Bay. The mercury concentrations in rivers correlated significantly with the concentrations of Al and Fe, major components of soil. In Japan, large amounts of organomercurous fungicides (about 2500 tons as Hg) were used extensively in fields in the past, and most of the mercury was retained in the soil. In this study, the mercury concentration in rivers was measured primarily in ordinary runoff. These observations lead to the hypothesis that field soil discharged into stormwater runoff is a major source of mercury in Tokyo Bay. As a preliminary approach to validating this hypothesis, we measured the concentrations of mercury and other trace metals in river water during a typhoon. The mercury concentrations in stormwater runoff increased to 16–50 times the mean value in ordinary runoff, which is much higher than the increases for other metals. This tends to support the hypothesis.     

Air-sea exchange of mercury in Tokyo Bay

In Tokyo Bay the concentrations of dissolved gaseous mercury (DGM) in the surface seawater and total gaseous mercury (TGM) over the sea were measured during December 2003, October 2004 and January 2005. Based on these data, the evasional fluxes of mercury from the sea surface were estimated using a gas exchange model. In addition, an automatic wet and dry deposition sampler was used to measure the wet and dry depositional fluxes of mercury from December 2003 to November 2004 at three locations in and near Tokyo Bay. The results indicate that the average DGM and TGM levels of seven locations are 52 ± 26 ng m⁻³ and 1.9 ± 0.6 ng m⁻³, respectively, which shows that the surface seawater in Tokyo Bay is supersaturated with gaseous mercury, leading to an average mercury evasional flux of 140 ± 120 ng m⁻²d⁻¹. On the other hand, the annual average wet and dry depositional fluxes of mercury at three locations were 19 ± 3 μg m⁻²yr⁻¹ and 20 ± 9 μg m⁻²yr⁻¹, respectively. These depositional fluxes correspond to the daily average total depositional flux of 110 ± 20 ng m⁻²d⁻¹. Thus, it is suggested that in Tokyo Bay, the evasional fluxes of mercury are comparable to the depositional fluxes.     

Effects of temporal dynamics and vertical structure of the seagrass Zostera caulescens on distribution and recruitment of the epifaunal encrusting bryozoa Microporella trigonellata

Seagrass is an ephemeral habitat for epifaunal sessile invertebrates attaching on seagrass leaves, and spatial and temporal dynamics of seagrasses strongly affect the distribution of epifauna. Zostera caulescens Miki, a seagrass species endemic to Japan, provides a complex habitat for epifauna with two types of shoots: vegetative, less than 1 m tall, and flowering, 5–7 m tall. We conducted monthly field observations and a manipulative field experiment to investigate the effects of the seagrass vertical structure and its temporal variation on the distribution and recruitment of the encrusting bryozoan Microporella trigonellata. The density of M. trigonellata on the leaves of flowering shoots, located at the seagrass canopy, varied temporally, reaching maximum in summer and minimum in winter. In contrast, M. trigonellata density on the leaves of vegetative shoots near the sea floor was consistently low throughout the study period. Early recruit bryozoans also showed this temporal and vertical variation in density; thus spatial and temporal variation in recruitment determined the distribution of the whole colonies. The field experiment revealed that the recruitment rate of M. trigonellata was significantly higher at the higher position of the water column (3 m above the sea floor) than at the lower position (0.5 m) in June. However, the recruitment rate was higher at the lower position in October when most of the flowering shoots started falling down. The temporal change in bryozoan habitat selection is considered to be adaptive to maintain their population on the seagrass leaves that show complex temporal dynamics.     

Interannual and Decadal Variabilities of NPIW Salinity Minimum Core Observed along JMA’s Hydrographic Repeat Sections

We investigated the variation of the North Pacific Intermediate Water (NPIW) distribution in the western North Pacific, focusing on the intermediate salinity minimum (S < 34.2) core observed along the meridional hydrographic sections including the 137°E repeat section by the Japan Meteorological Agency. This core is a cross-section of a low salinity tongue extending westward along the recirculation in the subtropical gyre. The core size shows remarkable variabilities in interannual and decadal time scales. The salinity change in the density layer during the period of core expansion (shrinking) represents the spatial salinity change in the tongue toward the west (east). Thus, we conclude that the core size variation is associated with the zonal wobble of the tongue having thicker distribution to the east, rather than temporal changes of the water mass itself. The core size at 137°E is well correlated with the meridional gradient of the depth in the isopycnal surface at the salinity minimum representing the recirculation intensity, suggesting a relation with the intensity of the subtropical gyre. A significant lag-correlation between the gradient and the wind forcing over the North Pacific suggests that the first mode baroclinic Rossby waves excited in the central North Pacific propagated westward to change the intensity of the recirculation in interannual time scales. In decadal time scales, it is found that the wind stress curl and heat flux fields in the North Pacific precede the recirculation by about 11 years.     

Algorithm and validation of sea surface temperature observation using MODIS sensors aboard terra and aqua in the western North Pacific

A regional algorithm to estimate SST fields in the western North Pacific, where small oceanographic disturbance are often found, has been developed using Moderate Resolution Imaging Spectroradiometers (MODIS) aboard Terra and Aqua. Its associated algorithm, which includes cloud screening and SST estimation, is based on an algorithm for the Global Imager (GLI) aboard Advanced Earth Observing Satellite-II (ADEOS-II) and is tuned for MODIS sensors. For atmospheric correction, we compare Multi-Channel SST (MCSST), Nonlinear SST (NLSST), Water Vapor SST (WVSST) and Quadratic SST (QDSST) techniques. For NLSST, four first-guess SSTs are investigated, including the values for MCSST, climatology with two different spatial resolutions, and near-real-time objective analysis. The results show that the NLSST method using high-resolution climatological SST as a first-guess has both good quality and high efficiency. The differences of root-mean-square error (RMSE) between the NLSST models using low-resolution climatology and those using high-resolution climatology are up to 0.25 K. RMSEs of the new algorithm are 0.70 K/0.65 K for daytime (Aqua/Terra) and 0.65 K/0.66 K for nighttime, respectively. Diurnal warming and the stratification of the ocean surface layer under low wind are discussed.     

Evaluation of ADEOS-II GLI ocean color atmospheric correction using SIMBADA handheld radiometer data

The performance of the “version 2” Global Imager (GLI) standard atmospheric correction algorithm, which includes empirical absorptive aerosol correction and sun glint correction, was evaluated using data collected with handheld above-water SIMBADA radiometers during 23 cruises of opportunity (research vessels, merchant ships), mostly in the North Atlantic and European seas. A number of 100 match-up data sets of GLI-derived and SIMBADA-measured normalized water-leaving radiance (nL _W ) and aerosol optical thickness (AOT) were sorted out, using objective selection criteria, and analyzed. The Root-Mean-Square (RMS) difference between GLI and SIMBADA nL _W was about 0.32 μW/cm²/nm/sr for the 412 nm band, showing improvement by 30% in RMS difference with respect to the conventional “version 1” GLI atmospheric correction algorithm, and the mean difference (or bias) was reduced significantly. For AOT, the RMS difference was 0.1 between GLI estimates and SIMBADA measurements and the bias was small (a few 0.01), but the ?ngstr?m exponent was systematically underestimated, by 0.4 on average, suggesting a potential GLI calibration offset in the near infrared. The nL _W differences were not correlated to AOT, although performance was best in very clear conditions (AOT less than 0.05 in the 865 nm band). Despite the relatively large scatter between estimated and measured nL _W , the derived chlorophyll-a concentration estimates, applying the same ratio algorithm (GLI OC4V4) to GLI and SIMBADA, were consistent and highly correlated in the range of 0.05–2 μg/l. The large variability in chlorophyll-a concentration estimate for clear clean water areas (e.g. with the concentration range lower than about 0.05 μg/l) turns out to be due to the nature of the “band ratio” based in-water algorithm.