Seasonal climate prediction aimed at boosting economy, reducing losses — NiMet DG

The Director General of the Nigerian Meteorological Agency {NiMet}, Professor Charles Anosike, has reaffirmed that the annual Seasonal Climate Prediction (SCP) of the Agency is targeted at growing the country’s economy and reducing production and infrastructural losses.

Speaking in Abuja, the DG explained that the SCP provides insight into some essential climate parameters and their behaviour within the season.

“NiMet produces the publication annually in fulfilment of its mandate to provide accurate, timely, and quality weather and climate information to advise the federal government and Nigerians on weather and climate-related issues.

“This is mainly to boost economic growth and prevent or reduce production and infrastructural losses. The production process of the SCP involves a science-based use of long-term meteorological data and regional and global forecasting models.”.

He explained that a co-production process involving relevant stakeholders from weather-sensitive sectors such as agriculture, aviation, the blue economy, health, transportation, and power, among others, was implemented to achieve these remarkable user-tailored forecasts.

“The predictions in this edition of Seasonal Climate Prediction {SCP} were based on the strong El Nino phase of the El Nino Southern Oscillation {ENSO} in the first half of 2024 and the projection that that natural phase will most likely persist for the later part of the year.

“The ENSO has a major influence on climate patterns globally. The strong El Nino phase was used for the onset of rains, length of the season, end of the season, and total seasonal rainfall amount.

“Moreover, rainfall temperature, soil moisture data, water balance, farm management practices, and other phonological and soil type information were factored into the forecast,” he stated.

The El Nino Southern Oscillation (ENSO), like every other year, is one of the major drivers of seasonal atmospheric changes and the basis upon which NiMet seasonal climate prediction is produced.

 

 

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