984 resultados para mixed layer depth


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We applied a primitive equation ocean model to simulate submesoscale activities and processes over the shelf of the northern South China Sea (NSCS) with a one-way nesting technology for downscaling. The temperature and density fields showed that submesoscale activities were ubiquitous in the NSCS shelf. The vertical velocity was considerably enhanced in submesoscale processes and could reach an average of 58 m per day in the subsurface. At this point, the mixed layer depth also was deepened along the front, and the surface kinetic energy also increased with the intense vertical movement induced by submesoscale activity. Thus, submesoscale stirring/mixing is important for tracers, such as temperature, salinity, nutrients, dissolved organic, and inorganic carbon. This result may have implication for climate and biogeochemical investigations.

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海洋上混合层深度(MLD)是刻画海洋上混合层的一个非常重要的物理参量,MLD的准确确定对人们了解上层海洋动力学、热力学等具有重要的科学意义和实用价值。本文概述了影响MLD的几个主要因素,介绍了MLD的定义方法和主要的两类混合层模型。利用2001年月平均资料,分析了中国南海海表风应力、净热通量、蒸发、降雨及蒸降差的时、空分布变化规律。采用国外先进的MITgcm模式及考虑了非局地作用影响的KPP垂直混合模型,通过改变模式的上边界强迫条件,进行了海表风应力、海表净热通量、蒸降差对MLD影响的敏感性分析,结果表明MLD对海表风应力变化最为敏感。 通过网格嵌套方法,采用MITgcm模式及分辨率为1/4°×1/4°的强迫场资料对南海进行数值模拟,分析了海表温度、盐度、流场及混合层深度的时、空分布特征变化规律,探讨了海表风应力、净热通量、蒸降差对海洋上混合层深度的影响。通过模拟结果与实测资料的比较,同时也表明MITgcm模式应用于中国南海区域范围的MLD数值模拟研究是可行的。 基于考虑了地转和均匀背景流场影响的两层流体界面内波频散关系模型,得到一种新的利用SAR遥感图像反演混合层深度的方法。利用该方法对南海北部SAR内波图像进行了MLD的实例反演研究,并和时空同步的CTD资料进行了对比,结果表明考虑地转和均匀背景流场影响的MLD反演算法更为合理,为更准确地利用SAR图像遥感反演混合层深度奠定了基础。

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Several environmental/physical variables derived from satellite and in situ data sets were used to understand the variability of coccolithophore abundance in the subarctic North Atlantic. The 7-yr (1997–2004) time-series analysis showed that the combined effects of high solar radiation, shallow mixed layer depth (<20 m), and increased temperatures explained >89% of the coccolithophore variation. The June 1998 bloom, which was associated with high light intensity, unusually high sea-surface temperature, and a very shallow mixed layer, was found to be one of the most extensive (>995,000 km2) blooms ever recorded. There was a pronounced sea-surface temperature shift in the mid-1990s with a peak in 1998, suggesting that exceptionally large blooms are caused by pronounced environmental conditions and the variability of the physical environment strongly affects the spatial extent of these blooms. Consequently, if the physical environment varies, the effects of these blooms on the atmospheric and oceanic environment will vary as well.

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Global climate change is expected to modify the spatial distribution of marine organisms. However, projections of future changes should be based on robust information on the ecological niche of species. This paper presents a macroecological study of the environmental tolerance and ecological niche (sensu Hutchinson 1957, i.e. the field of tolerance of a species to the principal factors of its environment) of Calanus finmarchicus and C. helgolandicus in the North Atlantic Ocean and adjacent seas. Biological data were collected by the Continuous Plankton Recorder (CPR) Survey, which samples plankton in the North Atlantic and adjacent seas at a standard depth of 7 m. Eleven parameters were chosen including bathymetry, temperature, salinity, nutrients, mixed-layer depth and an index of turbulence compiled from wind data and chlorophyll a concentrations (used herein as an index of available food). The environmental window and the optimum level were determined for both species and for each abiotic factor and chlorophyll concentration. The most important parameters that influenced abundance and spatial distribution were temperature and its correlates such as oxygen and nutrients. Bathymetry and other water-column-related parameters also played an important role. The ecological niche of C. finmarchicus was larger than that of C. helgolandicus and both niches were significantly separated. Our results have important implications in the context of global climate change. As temperature (and to some extent stratification) is predicted to continue to rise in the North Atlantic sector, changes in the spatial distribution of these 2 Calanus species can be expected. Application of this approach to the 1980s North Sea regime shift provides evidence that changes in sea temperature alone could have triggered the substantial and rapid changes identified in the dynamic regimes of these ecosystems. C. finmarchicus appears to be a good indicator of the Atlantic Polar Biome (mainly the Atlantic Subarctic and Arctic provinces) while C. helgolandicus is an indicator of more temperate waters (Atlantic Westerly Winds Biome) in regions characterised by more pronounced spatial changes in bathymetry.

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The patterns of copepod species richness (S) and their relationship with phytoplankton productivity, temperature and environmental stability were investigated at climatological, seasonal and year-to-year time scales as well as scales along latitudinal and oceanic–neritic gradients using monthly time series of the Continuous Plankton Recorder (CPR) Survey collected in the North East Atlantic between 1958 and 2006. Time series analyses confirmed previously described geographic patterns. Equatorward and towards neritic environments, the climatological average of S increases and the variance explained by the seasonal cycle decreases. The bi-modal character of seasonality increases equatorward and the timing of the seasonal cycle takes place progressive earlier equatorward and towards neritic environments. In the long-term, the climatological average of S decreased significantly (p < 0.001) between 1958 and 2006 in the Bay of Biscay and North Iberian shelf at a rate of ca. 0.04 year−1, and increased at the same rate between 1991 and 2006 in the northernmost oceanic location. The climatological averages of S correlate positively with those of the index of seasonality of phytoplankton productivity (ratio between the minimum and maximum monthly values of surface chlorophyll) and sea surface temperature, and negatively with those of the proxy for environmental stability (monthly frequency of occurrence of daily averaged wind speed exceeding 10 m s−1). The seasonal cycles of S and phytoplankton productivity (surface chlorophyll as proxy) exhibit similar features in terms of shape, timing and explained variance, but the relationship between the climatological averages of both variables is non-significant. From year-to-year, the annual averages of S correlate negatively with those of phytoplankton productivity and positively with those of sea surface temperature along the latitudinal gradient, and negatively with those of environmental stability along the oceanic–neritic gradient. The annual anomalies of S (i.e. factoring out geographic variation) show a unimodal relationship with those of sea surface temperature and environmental stability, with S peaking at intermediate values of the anomalies of these variables. The results evidence the role of seasonality of phytoplankton productivity on the control of copepod species richness at seasonal and climatological scales, giving support to the species richness–productivity hypothesis. Although sea surface temperature (SST) is indeed a good predictor of richness along the latitudinal gradient, it is unable to predict the increase of richness form oceanic to neritic environments, thus lessening the generality of the species richness–energy hypothesis. Meteo-hydrographic disturbances (i.e. SST and wind speed anomalies as proxies), presumably through its role on mixed layer depth dynamics and turbulence and hence productivity, maximise local diversity when occurring at intermediate frequency and or intensity, thus providing support to the intermediate disturbance hypothesis on the control of copepod diversity.

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Estimating primary production at large spatial scales is key to our understanding of the global carbon cycle. Algorithms to estimate primary production are well established and have been used in many studies with success. One of the key parameters in these algorithms is the chlorophyll-normalised production rate under light saturation (referred to as the light saturation parameter or the assimilation number). It is known to depend on temperature, light history and nutrient conditions, but assigning a magnitude to it at particular space-time points is difficult. In this paper, we explore two models to estimate the assimilation number at the global scale from remotely-sensed data that combine methods to estimate the carbon-to-chlorophyll ratio and the maximum growth rate of phytoplankton. The inputs to the algorithms are the surface concentration of chlorophyll, seasurface temperature, photosynthetically-active radiation af the surface of the sea, sea surface nutrient concentration and mixed-layer depth. A large database of in situ estimates of the assimilation number is used to develop the models and provide elements of validation. The comparisons with in situ observations are promising and global maps of assimilation number are produced.

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From January 2011 to December 2013, we constructed a comprehensive pCO2 data set based on voluntary observing ship (VOS) measurements in the western English Channel (WEC). We subsequently estimated surface pCO2 and air–sea CO2 fluxes in northwestern European continental shelf waters using multiple linear regressions (MLRs) from remotely sensed sea surface temperature (SST), chlorophyll a concentration (Chl a), wind speed (WND), photosynthetically active radiation (PAR) and modeled mixed layer depth (MLD). We developed specific MLRs for the seasonally stratified northern WEC (nWEC) and the permanently well-mixed southern WEC (sWEC) and calculated surface pCO2 with uncertainties of 17 and 16 μatm, respectively. We extrapolated the relationships obtained for the WEC based on the 2011–2013 data set (1) temporally over a decade and (2) spatially in the adjacent Celtic and Irish seas (CS and IS), two regions which exhibit hydrographical and biogeochemical characteristics similar to those of WEC waters. We validated these extrapolations with pCO2 data from the SOCAT and LDEO databases and obtained good agreement between modeled and observed data. On an annual scale, seasonally stratified systems acted as a sink of CO2 from the atmosphere of −0.6 ± 0.3, −0.9 ± 0.3 and −0.5 ± 0.3 mol C m−2 yr−1 in the northern Celtic Sea, southern Celtic sea and nWEC, respectively, whereas permanently well-mixed systems acted as source of CO2 to the atmosphere of 0.2 ± 0.2 and 0.3 ± 0.2 mol C m−2 yr−1 in the sWEC and IS, respectively. Air–sea CO2 fluxes showed important inter-annual variability resulting in significant differences in the intensity and/or direction of annual fluxes. We scaled the mean annual fluxes over these provinces for the last decade and obtained the first annual average uptake of −1.11 ± 0.32 Tg C yr−1 for this part of the northwestern European continental shelf. Our study showed that combining VOS data with satellite observations can be a powerful tool to estimate and extrapolate air–sea CO2 fluxes in sparsely sampled area.

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We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.

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Regime shifts have been reported in many marine ecosystems, and are often expressed as an abrupt change occurring in multiple physical and biological components of the system. In the Gulf of Alaska, a regime shift in the late 1970s was observed, indicated by an abrupt increase in sea surface temperature and major shifts in the catch of many fish species. This late 1970s regime shift in the Gulf of Alaska was followed by another shift in the late 1980s, not as pervasive as the 1977 shift, but which nevertheless did not return to the prior state. A thorough understanding of the extent and mechanisms leading to such regime shifts is challenged by data paucity in time and space. We investigate the ability of a suite of ocean biogeochemistry models of varying complexity to simulate regime shifts in the Gulf of Alaska by examining the presence of abrupt changes in time series of physical variables (sea surface temperature and mixed layer depth), nutrients and biological variables (chlorophyll, primary productivity and plankton biomass) using change-point analysis. Our study demonstrates that ocean biogeochemical models are capable of simulating the late 1970s shift, indicating an abrupt increase in sea surface temperature forcing followed by an abrupt decrease in nutrients and biological productivity. This predicted shift is consistent among all the models, although some of them exhibit an abrupt transition (i.e. a significant shift from one year to the next), whereas others simulate a smoother transition. Some models further suggest that the late 1980s shift was constrained by changes in mixed layer depth. Our study demonstrates that ocean biogeochemical can successfully simulate regime shifts in the Gulf of Alaska region, thereby providing better understanding of how changes in physical conditions are propagated from lower to upper trophic levels through bottom-up controls.

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Tese de Doutoramento, Física, 17 de Dezembro de 2013, Universidade dos Açores.

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Under global warming, the predicted intensification of the global freshwater cycle will modify the net freshwater flux at the ocean surface. Since the freshwater flux maintains ocean salinity structures, changes to the density-driven ocean circulation are likely. A modified ocean circulation could further alter the climate, potentially allowing rapid changes, as seen in the past. The relevant feedback mechanisms and timescales are poorly understood in detail, however, especially at low latitudes where the effects of salinity are relatively subtle. In an attempt to resolve some of these outstanding issues, we present an investigation of the climate response of the low-latitude Pacific region to changes in freshwater forcing. Initiated from the present-day thermohaline structure, a control run of a coupled ocean-atmosphere general circulation model is compared with a perturbation run in which the net freshwater flux is prescribed to be zero over the ocean. Such an extreme experiment helps to elucidate the general adjustment mechanisms and their timescales. The atmospheric greenhouse gas concentrations are held constant, and we restrict our attention to the adjustment of the upper 1,000 m of the Pacific Ocean between 40°N and 40°S, over 100 years. In the perturbation run, changes to the surface buoyancy, near-surface vertical mixing and mixed-layer depth are established within 1 year. Subsequently, relative to the control run, the surface of the low-latitude Pacific Ocean in the perturbation run warms by an average of 0.6°C, and the interior cools by up to 1.1°C, after a few decades. This vertical re-arrangement of the ocean heat content is shown to be achieved by a gradual shutdown of the heat flux due to isopycnal (i.e. along surfaces of constant density) mixing, the vertical component of which is downwards at low latitudes. This heat transfer depends crucially upon the existence of density-compensating temperature and salinity gradients on isopycnal surfaces. The timescale of the thermal changes in the perturbation run is therefore set by the timescale for the decay of isopycnal salinity gradients in response to the eliminated freshwater forcing, which we demonstrate to be around 10-20 years. Such isopycnal heat flux changes may play a role in the response of the low-latitude climate to a future accelerated freshwater cycle. Specifically, the mechanism appears to represent a weak negative sea surface temperature feedback, which we speculate might partially shield from view the anthropogenically-forced global warming signal at low latitudes. Furthermore, since the surface freshwater flux is shown to play a role in determining the ocean's thermal structure, it follows that evaporation and/or precipitation biases in general circulation models are likely to cause sea surface temperature biases.

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This study examines the effect of seasonally varying chlorophyll on the climate of the Arabian Sea and South Asian monsoon. The effect of such seasonality on the radiative properties of the upper ocean is often a missing process in coupled general circulation models and its large amplitude in the region makes it a pertinent choice for study to determine any impact on systematic biases in the mean and seasonality of the Arabian Sea. In this study we examine the effects of incorporating a seasonal cycle in chlorophyll due to phytoplankton blooms in the UK Met Office coupled atmosphere-ocean GCM HadCM3. This is achieved by performing experiments in which the optical properties of water in the Arabian Sea - a key signal of the semi-annual cycle of phytoplankton blooms in the region - are calculated from a chlorophyll climatology derived from Sea-viewing Wide Field-of-View Sensor (SeaWiFS) data. The SeaWiFS chlorophyll is prescribed in annual mean and seasonally-varying experiments. In response to the chlorophyll bloom in late spring, biases in mixed layer depth are reduced by up to 50% and the surface is warmed, leading to increases in monsoon rainfall during the onset period. However when the monsoons are fully established in boreal winter and summer and there are strong surface winds and a deep mixed layer, biases in the mixed layer depth are reduced but the surface undergoes cooling. The seasonality of the response of SST to chlorophyll is found to depend on the relative depth of the mixed layer to that of the anomalous penetration depth of solar fluxes. Thus the inclusion of the effects of chlorophyll on radiative properties of the upper ocean acts to reduce biases in mixed layer depth and increase seasonality in SST.

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The cold equatorial SST bias in the tropical Pacific that is persistent in many coupled OAGCMs severely impacts the fidelity of the simulated climate and variability in this key region, such as the ENSO phenomenon. The classical bias analysis in these models usually concentrates on multi-decadal to centennial time series needed to obtain statistically robust features. Yet, this strategy cannot fully explain how the models errors were generated in the first place. Here, we use seasonal re-forecasts (hindcasts) to track back the origin of this cold bias. As such hindcasts are initialized close to observations, the transient drift leading to the cold bias can be analyzed to distinguish pre-existing errors from errors responding to initial ones. A time sequence of processes involved in the advent of the final mean state errors can then be proposed. We apply this strategy to the ENSEMBLES-FP6 project multi-model hindcasts of the last decades. Four of the five AOGCMs develop a persistent equatorial cold tongue bias within a few months. The associated systematic errors are first assessed separately for the warm and cold ENSO phases. We find that the models are able to reproduce either El Niño or La Niña close to observations, but not both. ENSO composites then show that the spurious equatorial cooling is maximum for El Niño years for the February and August start dates. For these events and at this time of the year, zonal wind errors in the equatorial Pacific are present from the beginning of the simulation and are hypothesized to be at the origin of the equatorial cold bias, generating too strong upwelling conditions. The systematic underestimation of the mixed layer depth in several models can also amplify the growth of the SST bias. The seminal role of these zonal wind errors is further demonstrated by carrying out ocean-only experiments forced by the AOCGCMs daily 10-meter wind. In a case study, we show that for several models, this forcing is sufficient to reproduce the main SST error patterns seen after 1 month in the AOCGCM hindcasts.

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A dynamic size-structured model is developed for phytoplankton and nutrients in the oceanic mixed layer and applied to extract phytoplankton biomass at discrete size fractions from remotely sensed, ocean-colour data. General relationships between cell size and biophysical processes (such as sinking, grazing, and primary production) of phytoplankton were included in the model through a bottom–up approach. Time-dependent, mixed-layer depth was used as a forcing variable, and a sequential data-assimilation scheme was implemented to derive model trajectories. From a given time-series, the method produces estimates of size-structured biomass at every observation, so estimates seasonal succession of individual phytoplankton size, derived here from remote sensing for the first time. From these estimates, normalized phytoplankton biomass size spectra over a period of 9 years were calculated for one location in the North Atlantic. Further analysis demonstrated that strong relationships exist between the seasonal trends of the estimated size spectra and the mixed-layer depth, nutrient biomass, and total chlorophyll. The results contain useful information on the time-dependent biomass flux in the pelagic ecosystem.

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The Antarctic continental shelf seas feature a bimodal distribution of water mass temperature, with the Amundsen and Bellingshausen Seas flooded by Circumpolar Deep Water that is several degrees Celsius warmer than the cold shelf waters prevalent in the Weddell and Ross Seas. This bimodal distribution could be caused by differences in atmospheric forcing, ocean dynamics, ocean and ice feedbacks, or some combination of these factors. In this study, a highly simplified coupled sea ice–mixed layer model is developed to investigate the physical processes controlling this situation. Under regional atmospheric forcings and parameter choices the 10-yr simulations demonstrate a complete destratification of the Weddell Sea water column in winter, forming cold, relatively saline shelf waters, while the Amundsen Sea winter mixed layer remains shallower, allowing a layer of deep warm water to persist. Applying the Weddell atmospheric forcing to the Amundsen Sea model destratifies the water column after two years, and applying the Amundsen forcing to the Weddell Sea model results in a shallower steady-state winter mixed layer that no longer destratifies the water column. This suggests that the regional difference in atmospheric forcings alone is sufficient to account for the bimodal distribution in Antarctic shelf-sea temperatures. The model prediction of mixed layer depth is most sensitive to the air temperature forcing, but a switch in all forcings is required to prevent destratification of the Weddell Sea water column.