Weatherreports are essential because they help humans in planning foremergencies and day-to-day responsibilities. According to Fraley,Raftery, Gneiting, Sloughter, and Berroca (2011), the reports help inestablishing weather forecasting that facilitates optimal decisionmaking for varied reasons. For instance, weather-risk finance, shiprouting, electricity generation, agriculture and air traffic controldepend on reliable weather to operate effeciently. I agree thatweather prediction is indispensable in the modern society becausehumans overcome major disasters through foretelling the exact timethey will occur. For example, Vecchi et al. (2013) note that theweather forecasts can determine the NorthAtlantic Hurricane Frequencythrough the application of the ‘hybrid statistical–dynamicalforecast’ approach. The technique involves collecting weatheroccurrences of a given place for about 3-6 years. The patternestablished creates a reliable database for foretelling potentialclimate outcome (Vecchi et al., 2013).
Insome cases, weather forecasting gives inaccurate data andpredictions. Vecchi et al. (2013) assert that the inaccuracies resultfrom low statistical power. To overcome the weakness, the researchersrecommend that scientists should compile the daily weather outcomefor a long period, and then use statistical analyses to identifypossible patterns based on the frequency.
Innormal circumstances, observational, surveys and experimental methodsprovide powerful ways of gathering information. The approaches areespecially useful when collecting weather information of a particularlocation for a past period. Scientists have often used theinformation given by concerned people regarding weather patterns,drought frequencies and planting seasons among other data to predictthe climate of a particular area. For instance, Shirania, Parkhillb,Butlerc, Grovesa, Pidgeond, and Henwooda (2015) state that energybiographies are essential sources of information on foretellingweather patterns in the future.
Nonetheless,this method of data collection might be inaccurate due to theinability of human brains to make accurate records over a long time.Luckily, the bias can be eliminated by using large sample sizes. Thisimplies that researchers should test weather information from theperspectives of many people (Sloughter, Gneiting & Raftery,2010). Once several samples are available, the researcher can thenapply statistical research methods to minimize the information bias.For instance, calculating the mean of the data helps to decrease theinformation inaccuracy (Dunaway, Davis, Padgett, & Scholl, 2015). Using diverse research samples is recommended because each trialacquires a different sample size.
Dunaway,J. L., Davis, N. T., Padgett, J. and Scholl, R. M. (2015),Objectivity and information bias in campaign news. Journalof Communication, 65, 770–792.Doi: 10.1111/jcom.12172
Fraley,C., Raftery, A., Gneiting, T., Sloughter, M. & Berroca, V.(2011). Probabilistic weather forecasting in R. TheR Journal, 3(1),55-63.
Lee,J.A., Haupt S.E.& Young G.S.(2016). Down-selecting numericalweather prediction multi-physics ensembles with hierarchical clusteranalysis. JClimatol Weather Forecasting, 4,156, doi:10.4172/2332-2594.1000156
Shirania,F., Parkhillb, K., Butlerc, C., Grovesa, C., Pidgeond, N. &Henwooda, K. (2015). Asking about the future: Methodological insightsfrom energy biographies. InternationalJournal of Social Research Methodology, 19(4).429-444. DOI: 10.1080/13645579.2015.1029208
Sloughter, J.M., Gneiting T., & Raftery, A.E. (2010). Probabilistic windspeed forecasting using ensembles and Bayesian model averaging.Journalof the American Statistical Association, 105, 25–35.
Vecchi,G.A, Msadek, R., Anderson, W., Chang, Y., Delworth, T., Dixon, K., Gudgel, R., Rosati, A., & Stern, B. et al. (2013).Multiyearpredictions of North Atlantic Hurricane frequency: promise andlimitations. Journalof American Meteorological Society.DOI: http://dx.doi.org/10.1175/JCLI-D-12-00464.1