The ANICE (Atmospheric Nitrogen Inputs into the Coastal Ecosystem) project addressed the atmospheric deposition of nitrogen to the North Sea, with emphasis on coastal effects. ANICE focused on quantifying the deposition of inorganic nitrogen compounds to the North Sea and the governing processes. An overview of the results from modelling and experimental efforts is presented. They serve to identify the role of the atmosphere as a source of biologically essential chemical species to the marine biota. Data from the Weybourne Atmospheric Observatory (UK) are used to evaluate the effect of short episodes with very high atmospheric nitrogen concentrations. One such episode resulted in an average deposition of 0.8 mmol N m−2 day−1, which has the potential to promote primary productivity of 5.3 mmol C m−2 day−1. This value is compared to long-term effects determined from model results. The total calculated atmospheric deposition to the North Sea in 1999 is 948 kg N km−1, i.e. 0.19 mmol N m−2 day−1 which has the potential to promote primary productivity of 1.2 mmol C m−2 day−1. Detailed results for August 1999 show strong gradients across the North Sea due to adjacent areas where emissions of NOx and NH3 are among the highest in Europe. The average atmospheric deposition to the southern part of the North Sea in August 1999 could potentially promote primary production of 2.0 mmol C m−2 day−1, i.e. 5.5% of the total production at this time of the year in this area of the North Sea. For the entire study area the atmospheric contribution to the primary production per m2 is about two-third of this value. Most of the deposition occurs during short periods with high atmospheric concentrations. This atmospheric nitrogen is almost entirely anthropogenic in origin and thus represents a human-induced perturbation of the ecosystem. 相似文献
The Multi frequency Scanning Microwave Radiometer (MSMR) onboard Oceasat-1 was used to develop a retrieval method fornear-surface specific humidity by means of multivariate regressiontechnique. The MSMR measures the microwaveradiances in 8 channels at the frequencies of 6.6, 10.7, 18 and 21 GHzfor both vertical and horizontal polarizations. Regression coefficients were derived using the ship reports of the Comprehensive Ocean-Atmosphere Data Set (COADS) for the months of July, October and December, in 1999. Daily near-surface specific humidity data from COADS in 2° × 2° latitude/longitude bins and collocated brightness temperature data from MSMR were used to derive the coefficients. The derived coefficients werevalidated with humidity given in COADS.A linear relationship is established to determine the near-surface specifichumidity from MSMR brightness temperature (Tb) with an rms error of 1.2 g kg-1 for individual situations and an rms errorof 0.84 g kg-1 for monthly time scales over global oceans.The retrieval algorithm is validonly for the open sea regions. 相似文献
Based on the existing Land Surface Physical Process Models(Deardorff, Dickinson, LIU, Noilhan, Seller, ZHAO), a Comprehensive Land Surface Physical Process Model (CLSPPM) is developed by considering the different physical processes of the earth‘s surface-vegetation-atmosphere system more completely. Compared with SiB and BATS, which are famous for their detailed parameterizations of physical variables, this simplified model is more convenient and saves much more computation time. Though simple, the feas... 相似文献
Rock mass classification is analogous to multi-feature pattern recognition problem. The objective is to assign a rock mass to one of the pre-defined classes using a given set of criteria. This process involves a number of subjective uncertainties stemming from: (a) qualitative (linguistic) criteria; (b) sharp class boundaries; (c) fixed rating (or weight) scales; and (d) variable input reliability. Fuzzy set theory enables a soft approach to account for these uncertainties by allowing the expert to participate in this process in several ways. Hence, this study was designed to investigate the earlier fuzzy rock mass classification attempts and to devise improved methodologies to utilize the theory more accurately and efficiently. As in the earlier studies, the Rock Mass Rating (RMR) system was adopted as a reference conventional classification system because of its simple linear aggregation.
The proposed classification approach is based on the concept of partial fuzzy sets representing the variable importance or recognition power of each criterion in the universal domain of rock mass quality. The method enables one to evaluate rock mass quality using any set of criteria, and it is easy to implement. To reduce uncertainties due to project- and lithology-dependent variations, partial membership functions were formulated considering shallow (<200 m) tunneling in granitic rock masses. This facilitated a detailed expression of the variations in the classification power of each criterion along the corresponding universal domains. The binary relationship tables generated using these functions were processed not to derive a single class but rather to plot criterion contribution trends (stacked area graphs) and belief surface contours, which proved to be very satisfactory in difficult decision situations. Four input scenarios were selected to demonstrate the efficiency of the proposed approach in different situations and with reference to the earlier approaches. 相似文献