3 resultados para Numerical Weather Prediction
em Aquatic Commons
Resumo:
Caspian Sea with its unique characteristics is a significant source to supply required heat and moisture for passing weather systems over the north of Iran. Investigation of heat and moisture fluxes in the region and their effects on these systems that could lead to floods and major financial and human losses is essential in weather forecasting. Nowadays by improvement of numerical weather and climate prediction models and the increasing need to more accurate forecasting of heavy rainfall, the evaluation and verification of these models has been become much more important. In this study we have used the WRF model as a research-practical one with many valuable characteristics and flexibilities. In this research, the effects of heat and moisture fluxes of Caspian Sea on the synoptic and dynamical structure of 20 selective systems associated with heavy rainfall in the southern shores of Caspian Sea are investigated. These systems are selected based on the rainfall data gathered by three local stations named: Rasht, Babolsar and Gorgan in different seasons during a five-year period (2005-2010) with maximum amount of rainfall through the 24 hours of a day. In addition to synoptic analyses of these systems, the WRF model with and without surface flues was run using the two nested grids with the horizontal resolutions of 12 and 36 km. The results show that there are good consistencies between the predicted distribution of rainfall field, time of beginning and end of rainfall by the model and the observations. But the model underestimates the amounts of rainfall and the maximum difference with the observation is about 69%. Also, no significant changes in the results are seen when the domain and the resolution of computations are changed. The other noticeable point is that the systems are severely weakened by removing heat and moisture fluxes and thereby the amounts of large scale rainfall are decreased up to 77% and the convective rainfalls tend to zero.
Resumo:
This thesis considers a three- dimensional numerical model based on 3-D Navier— Stokes and continuity equations involving various wind speeds (North west), water surface levels, horizontal shier stresses, eddy viscosity, densities of oil and gas condensate- water mixture flows. The model is used to simulate the prediction of the surface movement of oil and gas condensate slicks from spill accident in the north coasts of Persian Gulf.
Resumo:
The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors potentially influence their spatial distribution, including aragonite saturation, alkalinity, pH, currents, water temperature, hard substrate availability and the availability of light at depth. Mesophotic corals and mesophotic coral ecosystems (MCEs) have increasingly been the subject of scientific study because they are being threatened by a growing number of anthropogenic stressors. They are the focus of this spatial modeling effort because the Hawaiian Islands Humpback Whale National Marine Sanctuary (HIHWNMS) is exploring the expansion of its scope—beyond the protection of the North Pacific Humpback Whale (Megaptera novaeangliae)—to include the conservation and management of these ecosystem components. The present study helps to address this need by examining the distribution of mesophotic corals in the Au‘au Channel region. This area is located between the islands of Maui, Lanai, Molokai and Kahoolawe, and includes parts of the Kealaikahiki, Alalākeiki and Kalohi Channels. It is unique, not only in terms of its geology, but also in terms of its physical oceanography and local weather patterns. Several physical conditions make it an ideal place for mesophotic hard corals, including consistently good water quality and clarity because it is flushed by tidal currents semi-diurnally; it has low amounts of rainfall and sediment run-off from the nearby land; and it is largely protected from seasonally strong wind and wave energy. Combined, these oceanographic and weather conditions create patches of comparatively warm, calm, clear waters that remain relatively stable through time. Freely available Maximum Entropy modeling software (MaxEnt 3.3.3e) was used to create four separate maps of predicted habitat suitability for: (1) all mesophotic hard corals combined, (2) Leptoseris, (3) Montipora and (4) Porites genera. MaxEnt works by analyzing the distribution of environmental variables where species are present, so it can find other areas that meet all of the same environmental constraints. Several steps (Figure 0.1) were required to produce and validate four ensemble predictive models (i.e., models with 10 replicates each). Approximately 2,000 georeferenced records containing information about mesophotic coral occurrence and 34 environmental predictors describing the seafloor’s depth, vertical structure, available light, surface temperature, currents and distance from shoreline at three spatial scales were used to train MaxEnt. Fifty percent of the 1,989 records were randomly chosen and set aside to assess each model replicate’s performance using Receiver Operating Characteristic (ROC), Area Under the Curve (AUC) values. An additional 1,646 records were also randomly chosen and set aside to independently assess the predictive accuracy of the four ensemble models. Suitability thresholds for these models (denoting where corals were predicted to be present/absent) were chosen by finding where the maximum number of correctly predicted presence and absence records intersected on each ROC curve. Permutation importance and jackknife analysis were used to quantify the contribution of each environmental variable to the four ensemble models.