Hurricane: The Cause and How to Predict them Essay

Published: 2020-04-22 15:25:15
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The official preparations for hurricane activity start during February 1st, which is 4 months before the occurrence of expected hurricane activity (Elsner, Murnane & Gagger 2006 1). There are various approaches available in order to predict the even of hurricane in a certain area. The topographical settings, rainfall, and ocean activities are the factors observed in order to gaze upon the future coming of such disaster.

Reference to hurricane history are sometimes done in order to obtain any possible potential pattern for prediction; however, this process is not reliable since landfall forecast have a very little time span approximately past half century (1). Bayesian is an approach wherein we utilize the available data by joining the old data and time series observations (1). Due to the vase catastrophe being dealt by these hurricanes, it is indeed essential to know the procedures of predicting such occurrence in order to attain earlier preparations.

In this paper, we shall tackle about hurricanes prediction approaches and it main etiologies. The factors that contribute to their occurrence are primarily indicated. In the end of the paper, the following questions should be answered: a. Determine the etiologies behind the occurrence of hurricane as well as the contributing factors involved in this causation. b. Provide the different methods or techniques in predicting hurricane occurrence. Methods

Covering first an assessment protocol, we have obtained the following two predictors of United States hurricanes related to seasonal activity, which are Atlantic SST or AMO-Atlantic Multidecadal Oscillation (based on interpreted data that is used to compute alterations located at north of the Equator) and (NAO) North Atlantic Oscillation (calculated from sea level pressure at Gibraltar and at a station over southwest Iceland) (Elsner, Murnane & Gagger 2006 1). SOI or Southern Oscillation Index are usually insignificant but shows negative value under impending El Nino, since it is anti-correlated with equatorial SSTs (2).

Another function of SOI is its strongest activity related to approaching hurricane activity, thus allowing hurricane predictions for the month of August-October (2). Bayesian Regression model uses NAO and AMO related to the number of hurricanes that occurred as the basis of hurricane prediction (2). According to Chao, Alves & Tolman (2004), another procedure in predicting hurricane is through (NOAA) National Oceanic and Atmospheric Administrations (NWW3) or WAVEWATCH III, which measures wind forecast as well as ocean waves (652).

(NAH) North Atlantic Hurricanes & (NPH) North Pacific Hurricanes are the models utilized in order to monitor preexisting hurricanes. NAH runs 4 times a day at 000, 0600, 1200 and 1800 UTC (655). Another means of predicting hurricane occurrence is through (CBLAST) Coupled Boundary Layer Air-Sea Transfer. It is a high-resolution computer model that observes the air-sea interactions. These factors directly affect hurricane intensity are not yet possible in the current operational forecast model (Science Daily 2004).

The effect of air-sea interactions on hurricane structure and intensity change is the main focus of the CBLAST. The overall modeling system is comprised of an atmospheric model, a surface wave model, and an ocean circulation model, all of which combine to form an innovative way of modeling storms (Science Daily 2004). Results The results of the following studies involve the results of NAO, AMO and SOI. Using the Bayesian regression, the results obtained for the mean are NAO (-0. l66) during October to January, AMO (+0. 455) during January, SOI (+0.

177) during August October and NAO (-0. 202) during May to June (Elsner, Murnane & Gagger 2006 3). The implication noted for these results are the increased activity of NAO during October to January as well as May to June. The SOI has been observed in order to prove lesser influence from other associating factors. These prove right in the results of methodology. AMO is also indicated to be high during January, and even higher than NAO. The predicator NAO is a dominant predicting agent for hurricane causations. With NAH, it properly predicted lower wave heights.

It is found during testing that for hurricane wave predictions, it is not enough to just add the intensity of under resolved systems (Alves & Tolman 2004 655). CBLAST experiences alterations in momentum, energy, heat, mass and the coupled nature of the wave boundary layer in terms of hurricane detection. The air interactions would even shift and change indicating possible hurricane formation (CBLAST DRI). Discussion Hurricane etiologies are essential factors to understand especially in correlation with hurricane prediction.

These wind and climatic formation is an intense low-pressure area that is produced over warm ocean bodies especially during summer and early fall. Their main contributing factor is water vapor that evaporated in the ocean surface because of intense heat during this season. Water vapor acts as the fuel of hurricane by producing latent heat of condensation. The low-pressure area that forms causes the wind to spin in an inward spiral motion. The direction of its spin directs on the innermost low pressure, which is developed into an eye (WeatherStreet 2007).

The catastrophic effects of hurricane include house wreckage, pulling out of trees, complete roof failure on many buildings, some buildings destroyed, severe window and door damage, mobile homes destroyed, fortunately it also have effects on the coral systems. Coral bleaching is one the drastic effects of high temperature, it induces the destruction of endosymbiotic algae and/or reduces the photosynthetic pigment present in this algae. These creatures are vulnerably to high temperature occurrence in the ocean. Hurricane formation is greatly dependent on war sea temperature, particularly temperatures of greater than 26 degrees Celsius.

These heat produced by the climatic conditions, especially during summer, induces the bleaching coral effect. The formation of hurricane decreases the temperature of the sea causing the bleaching to stop spreading however, if the storm is in great intensity, it begins damaging the corals as well. The scope of this damage can occur 30-90 km from the hurricanes eyes (Manzello et. al). Hurricane occurrence is still under semi-predictive state. Even with the present of high gadgets and various systematically arranged models, still the activity and the occurrence of such phenomena are sometimes outside the human hands.

Preparation is the best thing that we can do; ensuring the foundations of our home, being aware of various precautionary measures and the news, saving up resources just in case catastrophic scenario results and scarcity arises and other preparation tasks. This phenomenon can be very devastating and if you are not prepared for its arrival, chances are, the worst scenario might occur.

Works Cited Chao, Yung Y. , Jose-Henrique G. Alves, and Hendrik L. Tolman. An Operational System in Predicting HUrricane-Generated Wind Waves in the North Atlantic Ocean. Weather and Forecasting 20 (10 Sep. 2004):

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