scholarly journals STUDY OF OCEAN PRIMARY PRODUCTIVITY USING OCEAN COLOR DATA AROUND JAPAN

2010 ◽  
Vol 2 (-) ◽  
Author(s):  
TAKAHIRO OSAWA ◽  
CHAO FANG ZHAO ◽  
I WAYAN Nuarsa ◽  
I Ketut Swardika ◽  
YASUHIRO SUGIMORI
Keyword(s):  
Neural Network ◽  
Chlorophyll A ◽  
Mixed Layer ◽  
Primary Productivity ◽  
Mixed Layer Depth ◽  
Ocean Color ◽  
Sea Surface ◽  
Layer Depth ◽  
Concentration Data ◽  
Gaussian Shape

Ocean primary production is an important factor for determining the ocean's role in global carbon cycle. In recent years, much more chlorophyll-a concentration data in the euphotic layer were derived from the satellite ocean color sensors. The primary productivity algorithms have been proposed based on satellite chlorophyll measurements (Piatt, 1988; Morel, 1991) and other environmental parameters such as sea surface temperature or mixed layer depth (Behrenfeld and Falkowski, 1997; Esaias, 1996; Asanuma, 2002). In order to estimate integrated primary productivity in the whole water column, the vertical distribution of chlorophyll concentration below the sea surface should be reconstructed based on satellite data. In this paper, the vertical profile data of chlorophyll-a (Chl-a) measured around Japan Islands from 1974 to 1994 were reanalyzed based on the shifted-Gaussian shape proposed by Piatt et al (1988). Using this statistical model (neural network) and the photosynthesis irradiance parameters from Asanuma (2002), the distribution of primary productivity and its seasonal variation around Japan islands were estimated from SeaWiFS data, and the results were compared with in situ data and the other two models estimated from VGPM and mixed layer depth model. Keywords: ocean color, primary productivity, chlorophyll profile, artificial neural network

scholarly journals Global sensitivity analysis of the Indian monsoon during the Pleistocene

2015 ◽  
Vol 11 (1) ◽  
pp. 45-61 ◽  
Author(s):  
P. A. Araya-Melo ◽  
M. Crucifix ◽  
N. Bounceur
Keyword(s):  
Sensitivity Analysis ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Global Sensitivity Analysis ◽  
Indian Monsoon ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
Layer Depth ◽  
Global Sensitivity

Abstract. The sensitivity of the Indian monsoon to the full spectrum of climatic conditions experienced during the Pleistocene is estimated using the climate model HadCM3. The methodology follows a global sensitivity analysis based on the emulator approach of Oakley and O'Hagan (2004) implemented following a three-step strategy: (1) development of an experiment plan, designed to efficiently sample a five-dimensional input space spanning Pleistocene astronomical configurations (three parameters), CO2 concentration and a Northern Hemisphere glaciation index; (2) development, calibration and validation of an emulator of HadCM3 in order to estimate the response of the Indian monsoon over the full input space spanned by the experiment design; and (3) estimation and interpreting of sensitivity diagnostics, including sensitivity measures, in order to synthesise the relative importance of input factors on monsoon dynamics, estimate the phase of the monsoon intensity response with respect to that of insolation, and detect potential non-linear phenomena. By focusing on surface temperature, precipitation, mixed-layer depth and sea-surface temperature over the monsoon region during the summer season (June-July-August-September), we show that precession controls the response of four variables: continental temperature in phase with June to July insolation, high glaciation favouring a late-phase response, sea-surface temperature in phase with May insolation, continental precipitation in phase with July insolation, and mixed-layer depth in antiphase with the latter. CO2 variations control temperature variance with an amplitude similar to that of precession. The effect of glaciation is dominated by the albedo forcing, and its effect on precipitation competes with that of precession. Obliquity is a secondary effect, negligible on most variables except sea-surface temperature. It is also shown that orography forcing reduces the glacial cooling, and even has a positive effect on precipitation. As regards the general methodology, it is shown that the emulator provides a powerful approach, not only to express model sensitivity but also to estimate internal variability and detect anomalous simulations.

scholarly journals Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

2020 ◽  
Author(s):  
Wei-Lei Wang ◽  
Guisheng Song ◽  
François Primeau ◽  
Eric S. Saltzman ◽  
Thomas G. Bell ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Solar Radiation ◽  
Mixed Layer ◽  
Dimethyl Sulfide ◽  
Mixed Layer Depth ◽  
Environmental Parameters ◽  
Global Scale ◽  
Global Ocean ◽  
Layer Depth

Abstract. Marine dimethyl sulfide (DMS) is important to climate due to the ability of DMS to alter Earth's radiation budget. However, a knowledge of the global-scale distribution, seasonal variability, and sea-to-air flux of DMS is needed in order to understand the factors controlling surface ocean DMS and its impact on climate. Here we examine the use of an artificial neural network (ANN) to extrapolate available DMS measurements to the global ocean and produce a global climatology with monthly temporal resolution. A global database of 57 810 ship-based DMS measurements in surface waters was used along with a suite of environmental parameters consisting of lat-lon coordinates, time-of-day, time-of-year, solar radiation, mixed layer depth, sea surface temperature, salinity, nitrate, phosphate, silicate, and oxygen. Linear regressions of DMS against the environmental parameters show that on a global scale mixed layer depth and solar radiation are the strongest predictors of DMS, however, they capture 14 % and 12 % of the raw DMS data variance, respectively. The multi-linear regression can capture more (∼29 %) of the raw data variance, but strongly underestimates high DMS concentrations. In contrast, the ANN captures ~61 % of the raw data variance in our database. Like prior climatologies our results show a strong seasonal cycle in DMS concentration and sea-to-air flux. The highest concentrations (fluxes) occur in the high-latitude oceans during the summer. We estimate a lower global sea-to-air DMS flux (17.90 ± 0.34 Tg S yr−1) than the prior estimate based on a map interpolation method when the same gas transfer velocity parameterization is used.

scholarly journals Global distribution and variability of subsurface chlorophyll a concentration

2021 ◽  
Author(s):  
Sayaka Yasunaka ◽  
Tsuneo Ono ◽  
Kosei Sasaoka ◽  
Kanako Sato
Keyword(s):  
Chlorophyll A ◽  
Mixed Layer ◽  
Net Primary Production ◽  
Thermal Structure ◽  
Mixed Layer Depth ◽  
Subsurface Layer ◽  
Spatiotemporal Variability ◽  
Shortwave Radiation ◽  
Concentration Data ◽  
Chl A

Abstract. Chlorophyll a (Chl-a) often retains its maximum concentration not at the surface but in the subsurface layer. The depth of the Chl-a maximum primarily depends on the balance between light penetration from the surface and nutrient supply from the deep ocean. However, a global map of subsurface Chl-a concentrations based on observations has not been presented yet. In this study, we integrate Chl-a concentration data not only from recent biogeochemical floats but also from historical ship-based and other observations, and present global maps of subsurface Chl-a concentration with related variables. The subsurface Chl-a maximum deeper than the mixed layer depth was stably observed in the subtropics and tropics (30° S to 30° N), only in summer in midlatitudes (30–40° N/S), and rarely at 45–60° S of the Southern Ocean and in the northern North Atlantic (north of 45° N). The depths of the subsurface Chl-a maxima are deeper than those of the euphotic layer in the subtropics and shallower in the tropics and midlatitudes. In the subtropics, seasonal oxygen increases below the mixed layer implied substantial biological new production, which corresponds to 10 % of the net primary production there. During El Niño, the subsurface Chl-a concentration in the equatorial Pacific is higher in the middle to the east and lower in the west than that during La Niña, which is opposite that on the surface. The spatiotemporal variability of the Chl-a concentration described here would be suggestive results not only for the biogeochemical cycle in the ocean but also for the thermal structure and the dynamics of the ocean via the absorption of shortwave radiation.

Statistical features of the Oceanographic area off south-western Australia, obtained from Bathythermograph data

1986 ◽  
Vol 37 (4) ◽  
pp. 421 ◽  
Author(s):  
LJ Hamilton
Keyword(s):  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
Temperature Fields ◽  
Surface Mixed Layer ◽  
Statistical Features ◽  
Layer Depth ◽  
Leeuwin Current ◽  
South West

A statistical analysis has been made of 26 years of bathythermograph (BT) data to 1980 for the south-west Australian area bounded by 30-35�s. and 110-115�E., a region influenced by the Leeuwin Current. The data indicate that a surface mixed layer exists all year round, with average depth 55 m and standard deviation 37 m. All but 2% of BT casts show a mixed-layer depth (MLD) less than 150 m. MLD are deepest in mid-year, particularly from July to September. Sea surface temperatures (SST) are significantly related to temperature values down to 200 m depth, especially in mid-year, for both eastern and western parts of the area separated by 113�E. Correlations of MLD with SST are significant only in the western part, and then only from January to March, and April to June. Long-term horizontally averaged temperature fields are broadly related through the water column from the surface to 200 m. All results indicate that, especially in mid-year, SST fields are related to subsurface temperature fields, which may be representative of flow structure. Seasonal differences exist between the eastern and western areas, caused by the Leeuwin Current.

scholarly journals Interannual Variability of the Wind-Wave Regime Parameters in the Black Sea

2020 ◽  
Vol 27 (5) ◽  
Author(s):  
P. N. Lishaev ◽  
V. V. Knysh ◽  
G. K. Korotaev ◽  
◽  
◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Black Sea ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
Temperature Fields ◽  
The Black Sea ◽  
Layer Depth ◽  
Upper Mixed Layer

Purpose. The investigation is aimed at increasing accuracy of the temperature field reconstruction in the Black Sea upper layer. For this purpose, satellite observations of the sea surface temperature and the three-dimensional fields of temperature (in the 50–500 m layer) and salinity (in the 2.5–500 m layer) pseudo-measurements, previously calculated by the altimetry and the Argo floats data, were jointly assimilated in the Marine Hydrophysical Institute model. Methods and Results. Assimilation of the sea surface temperature satellite observations is the most effective instrument in case the discrepancies between the sea surface and the model temperatures are extrapolated over the upper mixed layer depth up to its lower boundary. Having been analyzed, the temperature profiles resulted from the forecast calculation for 2012 and from the Argo float measurements made it possible to obtain a simple criterion (bound to the model grid) for determining the upper mixed layer depth, namely the horizon on which the temperature gradient was less or equal to ≤ 0.017 °C/m. Within the upper mixed layer depth, the nudging procedure of satellite temperature measurements with the selected relaxation factor and the measurement errors taken into account was used in the heat transfer equation. The temperature and salinity pseudo-measurements were assimilated in the model by the previously proposed adaptive statistics method. To test the results of the sea surface temperature assimilation, the Black Sea hydrophysical fields were reanalyzed for 2012. The winter-spring period (January – April, December) is characterized by the high upper mixed layer depths, well reproducible by the Pacanowski – Philander parameterization, and also by the low values (as compared to the measured ones) of the basin-averaged monthly mean square deviations of the simulated temperature fields. The increased mean square deviations in July – September are explained by absence of the upper mixed layer in the temperature profiles measured by the Argo floats that is not reproduced by the Pacanowski – Philander parameterization. Conclusions. The algorithm for assimilating the sea surface temperature together with the profiles of the temperature and salinity pseudo-measurements reconstructed from the altimetry data was realized. Application of the upper mixed layer depths estimated by the temperature vertical profiles made it possible to correct effectively the model temperature by the satellite-derived sea surface temperature, especially for a winter-spring period. It permitted to reconstruct the temperature fields in the sea upper layer for 2012 with acceptable accuracy.

scholarly journals The effects of temporal variability of mixed layer depth on primary productivity around Bermuda

1994 ◽  
Vol 99 (C4) ◽  
pp. 7539 ◽  
Author(s):  
W. Paul Bissett ◽  
Mark B. Meyers ◽  
John J. Walsh ◽  
Frank E. Müller-Karger
Keyword(s):  
Mixed Layer ◽  
Primary Productivity ◽  
Temporal Variability ◽  
Mixed Layer Depth ◽  
Layer Depth

Towards a revised climatology of summertime dimethylsulfide concentrations and sea–air fluxes in the Southern Ocean

2016 ◽  
Vol 13 (2) ◽  
pp. 364 ◽  
Author(s):  
Tereza Jarníková ◽  
Philippe D. Tortell
Keyword(s):  
High Resolution ◽  
Southern Ocean ◽  
Chlorophyll A ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Cloud Formation ◽  
Layer Depth ◽  
High Resolution Data ◽  
Mean Values ◽  
Data Coverage

Environmental context The trace gas dimethylsulfide (DMS) is emitted from surface ocean waters to the overlying atmosphere, where it forms aerosols that promote cloud formation and influence Earth’s climate. We present an updated climatology of DMS emissions from the vast Southern Ocean, demonstrating how the inclusion of new data yields higher regional sources compared with previously derived values. Our work provides an important step towards better quantifying the oceanic emissions of an important climate-active gas. Abstract The Southern Ocean is a dominant source of the climate-active gas dimethylsulfide (DMS) to the atmosphere. Despite significant improvements in data coverage over the past decade, the most recent global DMS climatology does not include a growing number of high-resolution surface measurements in Southern Ocean waters. Here, we incorporate these high resolution data (~700000 measurements) into an updated Southern Ocean climatology of summertime DMS concentrations and sea–air fluxes. Owing to sparse monthly data coverage, we derive a single summertime climatology based on December through February means. DMS frequency distributions and oceanographic properties (mixed-layer depth and chlorophyll-a) show good general coherence across these months, providing justification for the use of summertime mean values. The revised climatology shows notable differences with the existing global climatology. In particular, we find increased DMS concentrations and sea–air fluxes south of the Polar Frontal zone (between ~60 and 70°S), and increased sea–air fluxes in mid-latitude waters (40–50°S). These changes are attributable to both the inclusion of new data and the use of region-specific parameters (e.g. data cut-off thresholds and interpolation radius) in our objective analysis. DMS concentrations in the Southern Ocean exhibit weak though statistically significant correlations with several oceanographic variables, including ice cover, mixed-layer depth and chlorophyll-a, but no apparent relationship with satellite-derived measures of phytoplankton photophysiology or taxonomic group abundance. Our analysis highlights the importance of using regional parameters in constructing climatological DMS fields, and identifies regions where additional observations are most needed.

scholarly journals Seasonal and inter-annual variability of the sea surface temperature and mixed layer depth in the southern Bay of Bengal

2013 ◽  
Vol 4 (1) ◽  
pp. 70
Author(s):  
R. Ranith ◽  
L. Senthilnathan ◽  
M. Machendiranathan ◽  
T. Thangaradjou ◽  
A. Saravanakumar
Keyword(s):  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Bay Of Bengal ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
Climate Change Scenarios ◽  
Layer Depth ◽  
South West Monsoon

Argo float data supplemented with satellite measurements was used to study the seasonal and inter-annual variation in wind speed, sea surface temperature (SST) and mixed layer depth (MLD) of the southern Bay of Bengal from 2003 through 2010. Due to persistence of wind, clear sky and high insolation an increase in SST by about 2°C is evident during summer months (March-May) and is followed by shallowed MLD with a minimum depth of 9.3 m during summer 2004. MLD reached the maximum depth during monsoon season (November-December) and often extends to post monsoon (February) owing to strong monsoon wind, cloudy sky and SST plummeted by 3°C. During the inter-monsoon period (August-October) the MLD shallowed and maintained a depth of 20–30 m all through the study period. High wind accompanied with moderate temperature (SST) due to the south west monsoon leads to decreased MLD with an average depth of 44 m in July. Analysis of wind speed, SST and MLD suggested that out of various meteorological parameters wind speed and induced mixing are highly influential in MLD formation. Reduced occurrence and amplitude of MLD deepening noticed in recent years can be attributed to the evident climate change scenarios. Large scale upper ocean variability observed from the present study has innumerable antagonistic consequences on the marine ecosystem which is evident from various events of seagrass burns and coral bleaching which have occurred in the last decade.

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