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Storm runoff from the Marikina River Basin frequently causes flood events in the Philippine capital region Metro Manila. This paper presents and evaluates a system to predict short-term runoff from the upper part of that basin (380 km2). It was designed as a possible component of an operational warning system yet to be installed. For the purpose of forecast verification, hindcasts of streamflow were generated for a period of 15 months with a time-continuous, conceptual hydrological model. The latter was fed with real-time observations of rainfall. Both ground observations and weather radar data were tested as rainfall forcings. The radar-based precipitation estimates clearly outperformed the raingauge-based estimates in the hydrological verification. Nevertheless, the quality of the deterministic short-term runoff forecasts was found to be limited. For the radar-based predictions, the reduction of variance for lead times of 1, 2 and 3 hours was 0.61, 0.62 and 0.54, respectively, with reference to a “no-forecast” scenario, i.e. persistence. The probability of detection for major increases in streamflow was typically less than 0.5. Given the significance of flood events in the Marikina Basin, more effort needs to be put into the reduction of forecast errors and the quantification of remaining uncertainties.  相似文献   
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In autumn 2002 a time-series station was installed in the tidal inlet between the Islands of Langeoog and Spiekeroog (Southern North Sea, NW Germany) to continuously measure physical, chemical, and meteorological parameters, even during extreme weather conditions (gale-force storms, drifting ice). Inside the pole of the station sensor tubes are installed in direction of the prevailing tidal currents. The tubes are equipped with hydrographic sensors (pressure, temperature, conductivity) and allow retrieval of water for nutrient analysis by automated instruments located inside the pole. Dissolved methane and the nutrients ammonia, nitrite, nitrate, phosphate, and silicate are measured at the station.  相似文献   
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This paper investigates the transferability of calibrated HBV model parameters under stable and contrasting conditions in terms of flood seasonality and flood generating processes (FGP) in five Norwegian catchments with mixed snowmelt/rainfall regimes. We apply a series of generalized (differential) split-sample tests using a 6-year moving window over (i) the entire runoff observation periods, and (ii) two subsets of runoff observations distinguished by the seasonal occurrence of annual maximum floods during either spring or autumn. The results indicate a general model performance loss due to the transfer of calibrated parameters to independent validation periods of ?5 to ?17%, on average. However, there is no indication that contrasting flood seasonality exacerbates performance losses, which contradicts the assumption that optimized parameter sets for snowmelt-dominated floods (during spring) perform particularly poorly on validation periods with rainfall-dominated floods (during autumn) and vice versa.  相似文献   
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Most dynamical models of the natural system contain a number of empirical parameters which reflect our limited understanding of the simulated system or describe unresolved subgrid-scale processes. While the parameterizations basically introduce some uncertainty to the model results, they also hold the prospect of tuning the model. In general, a deterministic tuning is related to an inversion of the model which is often impossible or requires considerable computing effort for most climate models. Another way to adjust the model parameters to a specific observed process is stochastic fitting where a set of parameters and model output are taken as random variables. Here, we present a dynamical?Cstatistical approach with a simplified model of the El Ni?o?CSouthern Oscillation (ENSO) cycle whose parameters are adjusted to simulated and observed data by means of Bayesian statistics. As ENSO model, we employ the Schop?CSuarez delay oscillator model. Monte Carlo experiments highlight the large sensitivity of the model results to varied model parameters and initial values. The statistical adjustment is done by Bayesian model averaging of the Monte Carlo experiments. Applying the method to simulated data, the posterior ensemble mean is much closer to the reference data than the prior ensemble mean. The learning effect of the model is evident in the leading empirical orthogonal functions and statistically significant in the mean state. When the method is applied to the observed ENSO time series, the ENSO model in its classical setup is not able to account for the temporally varying periodicity of the observed ENSO phenomenon. An improved setup with continuous adjustment periods and extended parameter range is developed in order to allow the model to learn from the data gradually. The improved setup leads to promising results during the twentieth century and even a weak forecast skill over 6?months. Thus, the described method offers a promising tool for data assimilation in dynamical weather and climate models. However, the simplified ENSO model is barely appropriate for operational ENSO forecasts owing to its limited physical complexity.  相似文献   
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Thermal diffusivity (D) was measured using laser-flash analysis from oriented single-crystal low-sanidine (K0.92Na0.08Al0.99Fe3+ 0.005Si2.95O8), and three glasses near KAlSi3O8. Viscosity measurements of the three supercooled liquids, in the range 106.8 to 1012.3 Pa s, confirm near-Arrhenian behavior, varying subtly with composition. For crystal and glass, D decreases with T, approaching a constant near 1,000 K: D sat ∼ 0.65 ± 0.3 mm2 s−1 for bulk crystal and ∼0.53 ± 0.03 mm2 s−1 for the glass. A rapid decrease near 1,400 K is consistent with crossing the glass transition. Melt behavior is approximated by D = 0.475 ± 0.01 mm2 s−1. Thermal conductivity (k lat) of glass, calculated using previous heat capacity (C P) and new density data, increases with T because C P strongly increases with T. For melt, k lat reaches a plateau near 1.45 W m−1 K−1, and is always below k lat of the crystal. Melting of potassium feldspars impedes heat transport, providing positive thermal feedback that may promote further melting in continental crust.  相似文献   
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Measurements of methane (CH4) so far have always shown supersaturation in the entire North Sea relative to the atmospheric partial pressure and the distribution of surface CH4 reveals a distinct increase towards the shore. Since North Sea sediments presumably are an insignificant source for CH4 the coastal contribution via rivers and tidal flats gains in importance.In this work, CH4 data from the River Weser, the back barrier tidal flats of Spiekeroog Island (NW Germany), and the German Bight are presented. Results from the River Weser are compared to other rivers draining into the German Bight. Measurements in the tidal flat area of Spiekeroog Island highlight this ecosystem as an additional contributor to the overall CH4 budget of the southern North Sea. A tidally driven CH4 pattern is observed for the water column with maximum values during low tide. Tidal flat sediments turn out to be the dominating source because pore waters discharged during low tide are highly enriched in CH4. In contrast, the freshwater contribution to the tidal flats by small coastal tributaries has almost no impact on water column CH4 concentrations. The CH4 level seems to be disturbed irregularly by wind forcing due to elevated degassing and prevention of advective flow when tidal flats remain covered by water.Based on our data, two model calculations were used to estimate the impact of tidal flats on the CH4 budget in the German Bight. Our results demonstrate that the back barrier tidal flats of the east Frisian Wadden Sea contribute CH4 in an order of magnitude between the Wash estuary and River Elbe and thus have to be considered in budget calculations.  相似文献   
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