3 resultados para Winter storms
em DigitalCommons - The University of Maine Research
Resumo:
A three-dimensional, regional coupled atmosphere-ocean model with full physics is developed to study air-sea interactions during winter storms off the U. S. east coast. Because of the scarcity of open ocean observations, models such as this offer valuable opportunities to investigate how oceanic forcing drives atmospheric circulation and vice versa. The study presented here considers conditions of strong atmospheric forcing (high wind speeds) and strong oceanic forcing (significant sea surface temperature (SST) gradients). A simulated atmospheric cyclone evolves in a manner consistent with Eta reanalysis, and the simulated air-sea heat and momentum exchanges strongly affect the circulations in both the atmosphere and the ocean. For the simulated cyclone of 19-20 January 1998, maximum ocean-to-atmosphere heat fluxes first appear over the Gulf Stream in the South Atlantic Bight, and this results in rapid deepening of the cyclone off the Carolina coast. As the cyclone moves eastward, the heat flux maximum shifts into the region near Cape Hatteras and later northeast of Hatteras, where it enhances the wind locally. The oceanic response to the atmospheric forcing is closely related to the wind direction. Southerly and southwesterly winds tend to strengthen surface currents in the Gulf Stream, whereas northeasterly winds weaken the surface currents in the Gulf Stream and generate southwestward flows on the shelf. The oceanic feedback to the atmosphere moderates the cyclone strength. Compared with a simulation in which the oceanic model always passes the initial SST to the atmospheric model, the coupled simulation in which the oceanic model passes the evolving SST to the atmospheric model produces higher ocean-to-atmosphere heat flux near Gulf Stream meander troughs. This is due to wind-driven lateral shifts of the stream, which in turn enhance the local northeasterly winds. Away from the Gulf Stream the coupled simulation produces surface winds that are 5 similar to 10% weaker. Differences in the surface ocean currents between these two experiments are significant on the shelf and in the open ocean.
Resumo:
Optimized regional climate simulations are conducted using the Polar MM5, a version of the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5), with a 60-km horizontal resolution domain over North America during the Last Glacial Maximum (LGM, 21 000 calendar years ago), when much of the continent was covered by the Laurentide Ice Sheet (LIS). The objective is to describe the LGM annual cycle at high spatial resolution with an emphasis on the winter atmospheric circulation. Output from a tailored NCAR Community Climate Model version 3 (CCM3) simulation of the LGM climate is used to provide the initial and lateral boundary conditions for Polar MM5. LGM boundary conditions include continental ice sheets, appropriate orbital forcing, reduced CO2 concentration, paleovegetation, modified sea surface temperatures, and lowered sea level. Polar MM5 produces a substantially different atmospheric response to the LGM boundary conditions than CCM3 and other recent GCM simulations. In particular, from November to April the upper-level flow is split around a blocking anticyclone over the LIS, with a northern branch over the Canadian Arctic and a southern branch impacting southern North America. The split flow pattern is most pronounced in January and transitions into a single, consolidated jet stream that migrates northward over the LIS during summer. Sensitivity experiments indicate that the winter split flow in Polar MM5 is primarily due to mechanical forcing by LIS, although model physics and resolution also contribute to the simulated flow configuration. Polar MM5 LGM results are generally consistent with proxy climate estimates in the western United States, Alaska, and the Canadian Arctic and may help resolve some long-standing discrepancies between proxy data and previous simulations of the LGM climate.
Resumo:
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.