6 resultados para Inter Session Variability Modelling

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Solar ultraviolet (UV) radiation at wavelengths less than 400 nm is an important source of energy for aeronomic processes throughout the solar system. Solar UV photons are absorbed in planetary atmospheres, as well as throughout the heliosphere, via photodissociation of molecules, photoionization of molecules and atoms, and photoexcitation toexcitation including resonance scattering. In this paper, the solar irradiances data measured by TIMED SEE, as well as the solar proxies such as F10.7 and Mg II, thermosphere neutral density of CHAMP measurements and topside ionospheric plasmas densities from DMSP, are used to analyze solar irradiance effects on the variabilities of the thermosphere and the ionosphere. First, thermosphere densities near 410 km altitude are analyzed for solar irradiance variability effects during the period 2002-2004. Correlations between the densities and the solar irradiances for different spectral lines and wavelength ranges reveal significantly different characteristics. The density correlates remarkably well with all the selected solar irradiances except the lower chromospheric O I (130.4 nm) emission. Among the chosen solar proxies, the Mg II core-to-wing ratio index, EUV (30-120 nm) and F10.7 show the highest correlations with the density for short-term (< ~27 days) variations. For both long- (> ~27 days) and short-term variations, linear correlation coefficients exhibit a decreasing trend from low latitudes towards high latitudes. The density variability can be effectively modeled (capturing 71% of the variance) using multiple solar irradiance indices, including F10.7, SEUV (the EUV 30-120 nm index), and SFUV (the FUV 120-193 nm index), in which a lag time of 1 day was used for both F10.7 and SEUV, and 5 days for SFUV. In our regression formulation SEUV has the largest contribution to the density variation (40%), with the F10.7 having the next largest contribution (32%) and SFUV accounting for the rest (28%). Furthermore, a pronounced period of about 27.2 days (mean period of the Sun's rotation) is present in both density and solar irradiance data of 2003 and 2004, and a pronounced period of about 54.4 days (doubled period of the solar rotation) is also revealed in 2004. However, soft X-ray and FUV irradiances did not present a pronounced 54.4 day period in 2004, in spite of their high correlation with the densities. The Ap index also shows 54-day periodicities in 2004, and magnetic activity, together with solar irradiance, affects the 54-day variation in density significantly. In addition, NRLMSISE00, DTM-2000 and JB2006 model predictions are compared with density measurements from CHAMP to assess their accuracy, and the results show that these models underestimate the response of the thermosphere to variations induced by solar rotation. Next, the equatorial topside ionospheric plasmas densities Ni are analyzed for solar irradiance variability effects during the period 2002-2005. Linear correlations between Ni and the solar irradiances for different wavelength ranges reveal significantly different characteristics. XUV (0-35 nm) and EUV (115-130 nm) show higher correlation with Ni for the long-term variations, whereas EUV (35-115 nm) show higher correlation for the short-term variations. Moreover, partial correlation analysis shows that the long-term variations of Ni are affected by both XUV (0-35 nm) and EUV (35-115 nm), whereas XUV (0-35 nm) play a more important role; the short-term variations of Ni are mostly affected by EUV (35-115 nm). Furthermore, a pronounced period of about 27 days is present in both Ni and solar irradiance data of 2003 and 2004, and a pronounced period of about 54 days is also revealed in 2004. Finally, prompted by previous studies that have suggested solar EUV radiation as a means of driving the semiannual variation, we investigate the intra-annual variation in thermosphere neutral density near 400 km during 2002-2005. The intra-annual variation, commonly referred to as the ‘semiannual variation’, is characterized by significant latitude structure, hemispheric asymmetries, and inter-annual variability. The magnitude of the maximum yearly difference, from the yearly minimum to the yearly maximum, varies by as much as 60% from year to year, and the phases of the minima and maxima also change by 20-40 days from year to year. Each annual harmonic of the intra-annual variation, namely, annual, semiannual, ter-annual and quatra-annual, exhibits a decreasing trend from 2002 through 2005 that is correlated with the decline in solar activity. In addition, some variations in these harmonics are correlated with geomagnetic activity, as represented by the daily mean value of Kp. Recent empirical models of the thermosphere are found to be deficient in capturing most of the latitude dependencies discovered in our data. In addition, the solar flux and geomagnetic activity proxies that we have employed do not capture some latitude and inter-annual variations detected in our data. It is possible that these variations are partly due to other effects, such as seasonal-latitudinal variations in turbopause altitude (and hence O/N2 composition) and ionosphere coupling processes that remain to be discovered in the context of influencing the intra-annual variations depicted here. Our results provide a new dataset to challenge and validate thermosphere-ionosphere general circulation models that seek to delineate the thermosphere intra-annual variation and to understand the various competing mechanisms that may contribute to its existence and variability. We furthermore suggest that the term “intra-annual” variation be adopted to describe the variability in thermosphere and ionosphere parameters that is well-captured through a superposition of annual, semiannual, ter-annual, and quatra-annual harmonic terms, and that “semiannual’ be used strictly in reference to a pure 6-monthly sinusoidal variation. Moreover, we propose the term “intra-seasonal” to refer to those shorter-term variations that arise as residuals from the above Fourier representation.

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Submersed macrophytes in Yangtze lakes have experienced large-scale declines due to the increasing human activities during past decades. To seek the key factor that affects their growth, monthly investigations of submersed macrophytes were conducted in 20 regions of four Yangtze lakes during December, 2001-March, 2003. Analyses based on annual values show that the ratio of Secchi depth to mean depth is the key factor (50% of macrophyte biomass variability among these lakes is statistically explained). Further analyses also demonstrate that the months from March to June are not only the actively growing season for most macrophytes, but the key time the factor acts. Five key-time models yielding higher predictive power (r(2) reaches 0.75,0.76,0.77,0.69 and 0.81) are generated. A comparison between key-time models and traditional synchronic ones indicates that key-time models have higher predictive power. Analyses of transparency thresholds during macrophyte growing season and the limitations of the models are presented. The models and other results may benefit the work concerning submersed macrophyte recovery in Yangtze lakes. (c) 2005 Elsevier B.V. All rights reserved.

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Suspended Particulate Matter (SPM) concentrations at various levels within the water column, together with salinity and temperature, were measured using water samples collected from six stations across the Straits of Dover. The sampling programme covered a 16-month period, undertaken during 23 cruises. On the basis of the spatial variability in the concentrations, the water bodies are divided by several boundaries, controlled by tidal and wind conditions. Within the water column, SPM concentrations were higher near the sea bed than in the surface waters. Throughout the cross-section, maximum concentrations occurred adjacent to the coastlines. Temporal variability in the SPM concentration exists on daily and seasonal scales within the coastal waters (4.2 to 74.5 mg L-1): resuspension processes, in response to semi-diurnal tidal cycles (with a period of around 12.4 h) and spring-neap cycles (with a period of 15 days) make significant contributions. Distinctive seasonal/annual concentration changes have also been observed. In the offshore waters, such variability is much less significant (0.9 to 6.0 mg L-1). In the summer the English Coastal Zone is associated with relatively high SPM concentrations: the Central Zone has a low and stable SPM concentration between these zones, there is a Transitional Zone, where there is a rapid response of SPM concentration to wind forcing. Finally, the French Coastal Zone is characterized by variable (sometimes high) SPM concentrations. Because of the zonation, SPM fluxes within the Dover Strait are controlled by different transport mechanisms. Within the Central Zone, the flux can be represented by the product of mean water discharges and SPM concentrations. However, within the coastal zones fluctuations in SPM concentrations on various time-scales must be considered. In order to calculate the maximum and minimum SPM fluxes, 10 cells were divided in the strait. A simple modelling calculation has been proposed for this complex area. The effect of spring-neap tidal cycles and seasonal changes can contribute significantly to the overall flux, which is of the order of 20 x 10(6) t.yr(-1) (through the Dover Strait, towards the North Sea). Such an estimate is higher than most obtained previously. (C) 2000 Ifremer/CNRS/IRD/Editions scientifiques et medicales Elsevier SAS.

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To investigate the seasonal and interannual variations in biological productivity in the South China Sea (SCS), a Pacific basin-wide physical - biogeochemical model has been developed and used to estimate the biological productivity and export flux in the SCS. The Pacific circulation model, based on the Regional Ocean Model Systems (ROMS), is forced with daily air-sea fluxes derived from the NCEP (National Centers for Environmental Prediction) reanalysis between 1990 and 2004. The biogeochemical processes are simulated with a carbon, Si(OH)(4), and nitrogen ecosystem (CoSiNE) model consisting of silicate, nitrate, ammonium, two phytoplankton groups (small phytoplankton and large phytoplankton), two zooplankton grazers (small micrograzers and large mesozooplankton), and two detritus pools. The ROMS-CoSiNE model favourably reproduces many of the observed features, such as ChI a, nutrients, and primary production (PP) in the SCS. The modelled depth-integrated PP over the euphotic zone (0-125 m) varies seasonally, with the highest value of 386 mg C m (-2) d (-1) during winter and the lowest value of 156 mg C m (-2) d (-1) during early summer. The annual mean value is 196 mg C m (-2) d (-1). The model-integrated annual mean new production (uptake of nitrate), in carbon units, is 64.4 mg C m (-2) d (-1) which yields an f-ratio of 0.33 for the entire SCS. The modelled export ratio (e-ratio: the ratio of export to PP) is 0.24 for the basin-wide SCS. The year-to-year variation of biological productivity in the SCS is weaker than the seasonal variation. The large phytoplankton group tends to dominate over the smaller phytoplankton group, and likely plays an important role in determining the interannual variability of primary and new production.