We investigate an ambiguity in the current understanding of the Gulf Stream (GS) transport in response to the North Atlantic Oscillation (NAO). While some investigations (discussed herein) suggest enhanced transport during low NAO phases, other studies suggest enhanced transport in high NAO phases. NAO-induced variability in the western North Atlantic is studied by using a 1/6°-resolution basin-scale Regional Ocean Modeling System (ROMS) model. Results indicate that the western boundary current limb of the GS, upstream of Cape Hatteras, exhibit enhanced transport during low-NAO phases. However, further downstream of Cape Hatteras, after the GS separates from the coast, diminished GS transport is seen during low-NAO phases. The converse is true for high NAO phases for both segments of the GS system. Model results show the Deep Western Boundary Current (DWBC), the northern recirculation gyre and the southern recirculation gyre intensify (weaken) during the high (low) NAO periods. 相似文献
The onset and advance of southwest monsoon are accompanied by the appearance of the offshore trough along the southwest coast of India. This offshore trough escorts a deluge of rainfall to the southwest coast, and sometimes rainfall band moves eastward further into south India. These broad observations were noticed during the summer monsoon of June 2017. Meteorological agencies and media had reported a huge amount of rainfall over the southwest coast of India during the month. But, in the far interior of south India, rainfall was less. Due to the less rainfall, water resources depleted, which affected local farmers and common man of south India. The confused views of the common man on southwest coast rainfall could be due to lack of understanding related to various factors affecting rainfall over the same region. This article is an endeavor to address the preliminary understanding of the southwest coast rainfall during June 2017, with more stress on offshore troughs. The study begins with area-averaged rainfall statistics over south, southwest, and southeast India by employing satellite and rain gauge merged rainfall datasets. Area averaged analysis revealed offshore trough contributed 80 % of rainfall over the South West India, 68 % over South East India, contributing to an overall 75 % over south India in 2017. To identify offshore trough position and strength in the reanalysis and model simulations, a new method called VSV (Vertical Shear of Vorticity) method was introduced. The computed offshore troughs were categorized into Active, Normal, and Feeble based on the strength of meridional gradient of mean sea level pressure and 850 hPa horizontal winds. The contribution due to each category of the offshore trough over different sub-regions was investigated to find out the effect of the offshore trough to total rainfall. Dynamic and thermodynamic features of these categories of the offshore trough were investigated by using proxies like equivalent potential temperature and moisture flux convergence. We found that during active offshore trough an eastward propagation of rain bands persists, which was explained by using moisture flux convergence and equivalent potential temperature at different levels of the atmosphere. 相似文献
The Global/Regional Assimilation and PrEdiction System (GRAPES) is a new-generation operational numerical weather prediction (NWP) model developed by the China Meteorological Administration (CMA).It is a grid-point model with a code structure different from that of spectral models used in other operational NWP centers such as the European Centre for Medium-Range Weather Forecasts (ECMWF),National Centers for Environmental Prediction (NCEP),and Japan Meteorological Agency (JMA),especially in the context of p... 相似文献
Physical phenomena observed before strong earthquakes have been reported for centuries. Precursor signals, which include radon anomalies, electrical signals, water level changes and ground lights near the epicenter, can all be used for earthquake prediction. Anomalous negative signals observed by ground-based atmospheric electric field instruments under fair weather conditions constitute a novel earthquake prediction approach. In theory, the abnormal radiation of heat before an earthquake produces fair weather around the epicenter. To determine the near-epicenter weather conditions prior to an earthquake, 81 global earthquake events with magnitudes of 6 or above from 2008 to 2021 were collected. According to Harrison's fair weather criteria, in 81.48% of all statistical cases, the weather was fair 6 h before the earthquake; in 62.96% of all cases, the weather was fair 24 h before the event. Moreover, most of these cases without fair weather several hours before the earthquake were near the sea. Among the 37 inland earthquakes, 86.49% were preceded by 6 h of fair weather, and 70.27% were preceded by fair weather for 24 h. We conclude that the weather near the epicenter might be fair for several hours before a strong earthquake, especially for inland events.
基于贝叶斯模式平均方法(Bayesian Model Averaging),发展了一个NINO3.4指数的多模式客观权重集合预报方法(简称OBJ)。该方法基于训练期内单个模式的预报结果,用线性回归订正单个预报的偏差,依据模式的预报效果估计单个模式的权重。利用2002年2月—2015年10月美国哥伦比亚大学国际气候与社会研究所(IRI)提供的7个单一模式对NINO3.4指数的预报结果进行OBJ试验,并采用均方根误差对多模式集合平均预报(简称ENS)和OBJ的预报结果进行检验和评估。结果表明,ENS的预报效果优于7个单一模式的预报效果,而OBJ预报效果优于ENS预报效果,其NINO3.4指数的均方根误差比ENS方法降低了4%。将单一模式预报结果按时间划分为训练期和预报期,利用独立样本估计OBJ的参数并进行预报试验,这些试验也表明,OBJ能进一步提高预报精度。 相似文献