4 resultados para Anomalies of surface temperature

em DigitalCommons - The University of Maine Research


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Physical forcing and biological response within the California Current System (CCS) are highly variable over a wide range of scales. Satellite remote sensing offers the only feasible means of quantifying this variability over the full extent of the CCS. Using six years (1997-2003) of daily SST and chlorophyll imagery, we map the spatial dependence of dominant temporal variability at resolutions sufficient to identify recurrent mesoscale circulation and local pattern associated with coastal topography. Here we describe mean seasonal cycles and interannual variation; intraseasonal variability is left to a companion paper ( K. R. Legaard and A. C. Thomas, manuscript in preparation, 2006). Coastal upwelling dictates seasonality along north-central California, where weak cycles of SST fluctuate between spring minima and late summer maxima and chlorophyll peaks in early summer. Off northern California, chlorophyll maxima are bounded offshore by the seasonally recurrent upwelling jet. Seasonal cycles differ across higher latitudes and in the midlatitude Southern California Bight, where upwelling winds are less vigorous and/or persistent. Seasonality along south-central Baja is strongly affected by processes other than upwelling, despite year-round upwelling-favorable winds. Interannual variation is generally dominated by El Nino and La Nina conditions. Interannual SST variance is greatest along south-central Baja, although interannual variability constitutes a greater fraction of total variance inshore along southern Oregon and much of California. Patterns of interannual chlorophyll variance are consistent with dominant forcing through the widespread depression and elevation of the nutricline during El Nino and La Nina, respectively. Interannual variability constitutes a greater fraction of total chlorophyll variance offshore.

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Six years of daily satellite data are used to quantify and map intraseasonal variability of chlorophyll and sea surface temperature (SST) in the California Current. We define intraseasonal variability as temporal variation remaining after removal of interannual variability and stationary seasonal cycles. Semivariograms are used to quantify the temporal structure of residual time series. Empirical orthogonal function (EOF) analyses of semivariograms calculated across the region isolate dominant scales and corresponding spatial patterns of intraseasonal variability. The mode 1 EOFs for both chlorophyll and SST semivariograms indicate a dominant timescale of similar to 60 days. Spatial amplitudes and patterns of intraseasonal variance derived from mode 1 suggest dominant forcing of intraseasonal variability through distortion of large scale chlorophyll and SST gradients by mesoscale circulation. Intraseasonal SST variance is greatest off southern Baja and along southern Oregon and northern California. Chlorophyll variance is greatest over the shelf and slope, with elevated values closely confined to the Baja shelf and extending farthest from shore off California and the Pacific Northwest. Intraseasonal contributions to total SST variability are strongest near upwelling centers off southern Oregon and northern California, where seasonal contributions are weak. Intraseasonal variability accounts for the majority of total chlorophyll variance in most inshore areas save for southern Baja, where seasonal cycles dominate. Contributions of higher EOF modes to semivariogram structure indicate the degree to which intraseasonal variability is shifted to shorter timescales in certain areas. Comparisons of satellite-derived SST semivariograms to those calculated from co-located and concurrent buoy SST time series show similar features.

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Time series of satellite measurements are used to describe patterns of surface temperature and chlorophyll associated with the 1996 cold La Nina phase and the 1997-1998 warm El Nino phase of the El Nino - Southern Oscillation cycle in the upwelling region off northern Chile. Surface temperature data are available through the entire study period. Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data first became available in September 1997 during a relaxation in El Nino conditions identified by in situ hydrographic data. Over the time period of coincident satellite data, chlorophyll patterns closely track surface temperature patterns. Increases both in nearshore chlorophyll concentration and in cross-shelf extension of elevated concentrations are associated with decreased coastal temperatures during both the relaxation in El Nino conditions in September-November 1997 and the recovery from EI Nino conditions after March 1998. Between these two periods during austral summer (December 1997 to March 1998) and maximum El Nino temperature anomalies, temperature patterns normally associated with upwelling were absent and chlorophyll concentrations were minimal. Cross-shelf chlorophyll distributions appear to be modulated by surface temperature frontal zones and are positively correlated with a satellite-derived upwelling index. Frontal zone patterns and the upwelling index in 1996 imply an austral summer nearshore chlorophyll maximum, consistent with SeaWiFS data from I 1998-1999, after the El Nino. SeaWiFS retrievals in the data set used here are higher than in situ measurements by a factor of 2-4; however, consistency in the offset suggests relative patterns are valid.

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Abundance of the Ommastrephes bartramii winter-spring cohort fluctuated greatly from 1995 to 2004. To understand how abundance was influenced by sea surface conditions, we examined the variations in the proportion of thermal habitats with favourable sea surface temperature (SST). The SST data of both the spawning and feeding grounds were used to calculate the monthly proportion of favourable-SST areas (PFSSTA). Catch per fishing day per fishing boat (catch per unit effort, CPUE) of the Chinese mainland squid-jigging fleet was used as squid abundance index. The relationships between CPUE and monthly PFSSTA at spawning and feeding grounds were analyzed, and the relationship between CPUE and selected PFSSTA was quantified with a multiple linear regression model. Results showed that February PFSSTA at the spawning ground and August to November PFSSTA at the feeding ground could account for about 60% of the variability in O. bartramii abundance between 1995 and 2004, that February was the most important period influencing squid recruitment during the spawning season, and that feeding ground PFSSTA during the fishing season would influence CPUE by causing squid to aggregate. Our forecast model was found to perform well when we compared the model-predicted CPUEs and the average CPUEs observed during August to November in 2005 and 2006 from the Chinese squid-jigging fishery.