974 resultados para seasonal cycle


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In response to the Indian Monsoon freshwater forcing, the Bay of Bengal exhibits a very strong seasonal cycle in sea surface salinity (SSS), especially near the mouths of the Ganges-Brahmaputra and along the east coast of India. In this paper, we use an eddy-permitting (similar to 25 km resolution) regional ocean general circulation model simulation to quantify the processes responsible for this SSS seasonal cycle. Despite the absence of relaxation toward observations, the model reproduces the main features of the observed SSS seasonal cycle, with freshest water in the northeastern Bay, particularly during and after the monsoon. The model also displays an intense and shallow freshening signal in a narrow (similar to 100 km wide) strip that hugs the east coast of India, from September to January, in good agreement with high-resolution measurements along two ships of opportunity lines. The mixed layer salt budget confirms that the strong freshening in the northern Bay during the monsoon results from the Ganges-Brahmaputra river discharge and from precipitation over the ocean. From September onward, the East India Coastal Current transports this freshwater southward along the east coast of India, reaching the southern tip of India in November. The surface freshening results in an enhanced vertical salinity gradient that increases salinity of the surface layer by vertical processes. Our results reveal that the erosion of the freshwater tongue along the east coast of India is not driven by northward horizontal advection, but by vertical processes that eventually overcome the freshening by southward advection and restore SSS to its premonsoon values. The salinity-stratified barrier layer hence only acts as a ``barrier'' for vertical heat fluxes, but is associated with intense vertical salt fluxes in the Bay of Bengal.

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The problem of the peculiar reproductive biology of the cladoceran Daphnia middendorffiana is investigated from a cytological viewpoint, and by direct observation the meiotic phenomena of the eggs both subitaneous and resting is studied. and during maturation, the true mechanism of the succession of reproductive phases of different ecological significance. Samples were collected in the Italian Alpine Lake of Campo 4°.

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The monthly average temperatures at Puttalam Lagoon, Dutch Bay, Portugal Bay towards Kovilmunai and Portugal Bay towards Pallugaturai showed a distinct annual cycle. The peak was in April and values gradually fell till September. There was a further gradual fall in temperature from October to January. The highest temperatures in all four stations were in April. The highest salinities in all the stations were from May to October i.e., during the south-west monsoon. The salinities at Dutch Bay and Portugal Bay were high in March and April corresponding to the highest temperatures reached during these months. Two maxima have been observed in phytoplankton production. A primary maximum in May-June and a secondary maximum in October. The primary and secondary maxima are due to the influx of nutrient laden waters from the rivers Kal Aru and Pomparippu Aru. The phytoplankton producing blooms were Rhizosolenia alata. Rhizosolenia imbricata, Chaetoceros lascinosus, Chaetoceros pervianus, Ch,aetoceros diversus, Coscinodiscus gigas, Thallasionema nitzschioides, Thalassiosira subtilis, Thallassiothrix frauenfeldii, Asterionella japonica, Sceletonema costatum, Bacteriastrum varians and Biddulphia sinensis. Sudden outbursts of a single species were common. These diatoms were species of Chaetoceros and Rhizosolenia, and Thallassiothrix frauenfeldii. Wide fluctuations have been observed in the distribution of phytoplankton but no definite conclusions can be drawn as the period of observation was only one year.

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In Sri Lanka waters, Durairatnam (1963, 1969) had reported on the seasonal variation of plankton at Puttalam lagoon, Dutch Bay, Portugal Bay and in the inshore and off shore waters off Colombo. Similar investigations were carried out at Koddiyar Bay especially in the estuarine waters where the three tributaries of the river Mahaveli empty their waters into the bay. The estuary is perennial. The fishes constituting the estuarine fisheries are mostly shallow water marine species which can tolerate considerable variations of salinities. Prawns and crabs also constitute a very valuable fishery in estuarine waters.

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The seasonal evolution of dissolved inorganic carbon (DIC) and CO2 air-sea fluxes in the Jiaozhou Bay was investigated by means of a data set from four cruises covering a seasonal cycle during 2003 and 2004. The results revealed that DIC had no obvious seasonal variation, with an average concentration of 2035 mu mol kg(-1) C in surface water. However, the sea surface partial pressure of CO2 changed with the season. pCO(2) was 695 mu atm in July and 317 mu atm in February. Using the gas exchange coefficient calculated with Wanninkhof's model, it was concluded that the Jiaozhou Bay was a source of atmospheric CO, in spring, summer, and autumn, whereas it was a sink in winter. The Jiaozhou Bay released 2.60 x 10(11) mmol C to the atmosphere in spring, 6.18 x 10(11) mmol C in summer, and 3.01 x 10(11) mmol C in autumn, whereas it absorbed 5.32 x 10(10) mmol C from the atmosphere in winter. A total of 1.13 x 10(11) mmol C was released to the atmosphere over one year. The behaviour as a carbon source/sink obviously varied in the different regions of the Jiaozhou Bay. In February, the inner bay was a carbon sink, while the bay mouth and the Outer bay were carbon sources. In June and July, the inner and Outer bay were carbon sources, but the strength was different, increasing from the inner to the outer bay. In November, the inner bay was a carbon source, but the bay Mouth was a carbon sink. The outer bay was a weaker CO2 Source. These changes are controlled by many factors, the most important being temperature and phytoplankton. Water temperature in particular was the main factor controlling the carbon dioxide system and the behaviour of the Jiaozhou Bay as a carbon source/sink. The Jiaozhou Bay is a carbon dioxide source when the water temperature is higher than 6.6 degrees C. Otherwise, it is a carbon sink. Phytoplankton is another controlling factor that may play an important role in behaviour as a carbon source or sink in regions where the source or sink nature is weaker.

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In this study, the mechanisms leading to the El Nino peak and demise are explored through a coupled general circulation model ensemble approach evaluated against observations. The results here suggest that the timing of the peak and demise for intense El Nino events is highly predictable as the evolution of the coupled system is strongly driven by a southward shift of the intense equatorial Pacific westerly anomalies during boreal winter. In fact, this systematic late-year shift drives an intense eastern Pacific thermocline shallowing, constraining a rapid El Nino demise in the following months. This wind shift results from a southward displacement in winter of the central Pacific warmest SSTs in response to the seasonal evolution of solar insolation. In contrast, the intensity of this seasonal feedback mechanism and its impact on the coupled system are significantly weaker in moderate El Nino events, resulting in a less pronounced thermocline shallowing. This shallowing transfers the coupled system into an unstable state in spring but is not sufficient to systematically constrain the equatorial Pacific evolution toward a rapid El Nino termination. However, for some moderate events, the occurrence of intense easterly wind anomalies in the eastern Pacific during that period initiate a rapid surge of cold SSTs leading to La Nina conditions. In other cases, weaker trade winds combined with a slightly deeper thermocline allow the coupled system to maintain a broad warm phase evolving through the entire spring and summer and a delayed El Nino demise, an evolution that is similar to the prolonged 1986/87 El Nino event. La Nina events also show a similar tendency to peak in boreal winter, with characteristics and mechanisms mainly symmetric to those described for moderate El Nino cases.

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The modelled El Nino-mean state-seasonal cycle interactions in 23 coupled ocean-atmosphere GCMs, including the recent IPCC AR4 models, are assessed and compared to observations and theory. The models show a clear improvement over previous generations in simulating the tropical Pacific climatology. Systematic biases still include too strong mean and seasonal cycle of trade winds. El Nino amplitude is shown to be an inverse function of the mean trade winds in agreement with the observed shift of 1976 and with theoretical studies. El Nino amplitude is further shown to be an inverse function of the relative strength of the seasonal cycle. When most of the energy is within the seasonal cycle, little is left for inter-annual signals and vice versa. An interannual coupling strength (ICS) is defined and its relation with the modelled El Nino frequency is compared to that predicted by theoretical models. An assessment of the modelled El Nino in term of SST mode (S-mode) or thermocline mode (T-mode) shows that most models are locked into a S-mode and that only a few models exhibit a hybrid mode, like in observations. It is concluded that several basic El Nino-mean state-seasonal cycle relationships proposed by either theory or analysis of observations seem to be reproduced by CGCMs. This is especially true for the amplitude of El Nino and is less clear for its frequency. Most of these relationships, first established for the pre-industrial control simulations, hold for the double and quadruple CO2 stabilized scenarios. The models that exhibit the largest El Nino amplitude change in these greenhouse gas (GHG) increase scenarios are those that exhibit a mode change towards a T-mode (either from S-mode to hybrid or hybrid to T-mode). This follows the observed 1976 climate shift in the tropical Pacific, and supports the-still debated-finding of studies that associated this shift to increased GHGs. In many respects, these models are also among those that best simulate the tropical Pacific climatology (ECHAM5/MPI-OM, GFDL-CM2.0, GFDL-CM2.1, MRI-CGM2.3.2, UKMO-HadCM3). Results from this large subset of models suggest the likelihood of increased El Nino amplitude in a warmer climate, though there is considerable spread of El Nino behaviour among the models and the changes in the subsurface thermocline properties that may be important for El Nino change could not be assessed. There are no clear indications of an El Nino frequency change with increased GHG.

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A time series of the observed transport through an array of moorings across the Mozambique Channel is compared with that of six model runs with ocean general circulation models. In the observations, the seasonal cycle cannot be distinguished from red noise, while this cycle is dominant in the transport of the numerical models. It is found, however, that the seasonal cycles of the observations and numerical models are similar in strength and phase. These cycles have an amplitude of 5 Sv and a maximum in September, and can be explained by the yearly variation of the wind forcing. The seasonal cycle in the models is dominant because the spectral density at other frequencies is underrepresented. Main deviations from the observations are found at depths shallower than 1500 m and in the 5/y–6/y frequency range. Nevertheless, the structure of eddies in the models is close to the observed eddy structure. The discrepancy is found to be related to the formation mechanism and the formation position of the eddies. In the observations, eddies are frequently formed from an overshooting current near the mooring section, as proposed by Ridderinkhof and de Ruijter (2003) and Harlander et al. (2009). This causes an alternation of events at the mooring section, varying between a strong southward current, and the formation and passing of an eddy. This results in a large variation of transport in the frequency range of 5/y–6/y. In the models, the eddies are formed further north and propagate through the section. No alternation similar to the observations is observed, resulting in a more constant transport.

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A number of urban land-surface models have been developed in recent years to satisfy the growing requirements for urban weather and climate interactions and prediction. These models vary considerably in their complexity and the processes that they represent. Although the models have been evaluated, the observational datasets have typically been of short duration and so are not suitable to assess the performance over the seasonal cycle. The First International Urban Land-Surface Model comparison used an observational dataset that spanned a period greater than a year, which enables an analysis over the seasonal cycle, whilst the variety of models that took part in the comparison allows the analysis to include a full range of model complexity. The results show that, in general, urban models do capture the seasonal cycle for each of the surface fluxes, but have larger errors in the summer months than in the winter. The net all-wave radiation has the smallest errors at all times of the year but with a negative bias. The latent heat flux and the net storage heat flux are also underestimated, whereas the sensible heat flux generally has a positive bias throughout the seasonal cycle. A representation of vegetation is a necessary, but not sufficient, condition for modelling the latent heat flux and associated sensible heat flux at all times of the year. Models that include a temporal variation in anthropogenic heat flux show some increased skill in the sensible heat flux at night during the winter, although their daytime values are consistently overestimated at all times of the year. Models that use the net all-wave radiation to determine the net storage heat flux have the best agreement with observed values of this flux during the daytime in summer, but perform worse during the winter months. The latter could result from a bias of summer periods in the observational datasets used to derive the relations with net all-wave radiation. Apart from these models, all of the other model categories considered in the analysis result in a mean net storage heat flux that is close to zero throughout the seasonal cycle, which is not seen in the observations. Models with a simple treatment of the physical processes generally perform at least as well as models with greater complexity.