GET THE APP

Identifying Climate Change Signals from Downscaled Temperatu | 24958

Journal of Climatology & Weather Forecasting

ISSN - 2332-2594

Abstrato

Identifying Climate Change Signals from Downscaled Temperature Data in Umuahia Metropolis, Abia State, Nigeria

Ozabor F and Nwagbara MO

This study was about Identifying climate change, by adopting the downscaling techniques in Umuahia metropolis. The study adopted ex-post-facto research design and data for maximum and minimum temperatures were collected from the archive of NIMET and for the period 1986-2015. On the other hand large scale predictor’s data were collected from the archive of HadCM3 for these periods 1960-2001 (NCEP) and 1960-2099(HadGCM3). Analyses were done using SDSM, ANOVA, PPMC and MLR. The study unraveled that, Mean sea level pressure (MSLP), Relative humidity at 500 hpa (r500), Relative humidity at 850 hpa (r850), and Temperature at 2 meters above sea level (temp) are the predictors of minimum and maximum temperature in the area. This also showed statistical significance at P<0.05. During validation the monthly sub-model performed better by using these indices for minimum and maximum temperatures respectively R20.85 & 0.70; RMSE 2.14 & 2.72; Rs 0.88 & 0.56; Value 0.00 & 0.00. Conversely, minimum and maximum temperature showed temporal variation for the period 1960-2080 at P<0.05 (F, 284.1) & p<0.05 (F, 227.1) respectively, therefore indicating significant change in temperature characteristics. The study strongly advocate assembling a working group that will work on a regional downscaling project, forging a synergy between Nigerian meteorological agency and the working group, producing a localized GCM, and the need to carry out similar study across the other regions of Nigeria.

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado