The Late Onset of the 2015 Wet Season in Nigeria

Adefisan

Oni

et al. 2018

Front. Environ. Sci.

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Motivated by the increasing needs for reliable seasonal climate forecasts for enhanced living and protection of property, this study evaluates the predictive skill of the European Center for Medium-range Weather Forecast's Sub-seasonal to Seasonal (ECMWF-S2S) precipitation forecasts during the peak of West Africa Monsoon in Nigeria. It investigates the ability of the ECMWF-S2S model to reproduce the atmospheric dynamics that influence the monsoon variability in West-Africa. Rain gauge values of 46 meteorological stations and 10-member ensemble of ECMWF-S2S forecasts from the Ensemble Prediction System (EPS) version of the ECMWF were subjected to quantitative statistical analyses. Results show that the model has weak capability in predicting wind strength at 700 mb level to depict the African Easterly Jet (AEJ). However, irrespective of the ENSO phases, ECMWF-S2S model is capable of adequately and reliably predicting the latitudinal positions of the Inter-Tropical Discontinuity (ITD), mean sea level pressure component of the thermal lows and sea surface temperature (SST) anomalies over the Pacific and Atlantic Oceans. On inter-annual time-scales, results also show that ECMWF-S2S model performs best over the Savannah in forecasting of rainfall anomalies (synchronization = 75%) and over the Sahel in the prediction of rainfall accumulation. The model may however not be able to forecast extreme precipitation reliably because the disagreement between the model's ensemble members increases as higher rainfall accumulation values are attained. The implication here is that the reproducibility of the atmospheric dynamic by the model is a better measure of rainfall prediction than the actual quantitative rainfall forecasts especially in areas south of latitude 10 • N. The study therefore suggests considering some climate driving mechanisms as predictability sources for the ECMWF-S2S model to enable the atmospheric dynamics to be better represented in the model.

Section: Dataset and Methodsmentioning

confidence: 99%

Evaluation of the ECMWF Sub-seasonal to Seasonal Precipitation Forecasts during the Peak of West Africa Monsoon in Nigeria

Adefisan

Oni

et al. 2018

Front. Environ. Sci.

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“…This only applies to the inter-annual variability of the onset dates. As explained by (Lawal et al 2016) and (Olaniyan et al 2018), synchronization is the percentage of periods in which the observed signs of anomalies coincide with those of simulations and or reforecasts. Furthermore, some measures of statistical significance, such as p value (Mason 2008), are performed for the synchronization and correlation skills that were determined in this study.…”

Section: Data Set and Methodsmentioning

confidence: 92%

“…They are all retrieved from the ECMWF-S2S database, as supported by the World Meteorological Organization (WMO) through the World Weather Research Program (WWRP) and World Climate Research Program (WCRP). The variables from these data sets are the rainfall, SST (Newman et al 2003), the Inter-Tropical Discontinuity (ITD: represented by 15 °C dew point temperature line [Olaniyan et al 2015[Olaniyan et al , 2018Lawal et al 2016]), zonal (u) and meridional (v) winds at 700 and 200 hPa levels to, respectively, track the African Easterly Jet (AEJ: Grist and Nicholson 2001;Afiesimama 2007) and the Tropical Easterly Jet (TEJ: Nicholson et al 2007;Nicholson and Grist 2003;Thorncroft and Blackburn 1999;Druyan and Hall 1996), and thermal low (represented by the coincidence of the hottest 2 m temperature and the lowest MSLP: Lavaysse et al 2006Lavaysse et al , 2009Lavaysse et al , 2010. Here, apart from the temporal and spatial structure of both AEJ and TEJ, the evaluation will also focus on the months when both jets coincide.…”

Section: Data Set and Methodsmentioning

confidence: 99%

“…The onset of the monsoon in West Africa is considered a crucial and integral part of monsoon dynamics, because it provides valuable information for decision-makers. In Nigeria, for instance, almost 68% of the population (about 122 million people) are peasant farmers and completely depend on rains for sustainable farming (Lawal et al 2016). Furthermore, national sectors that are related to water management such as agriculture, health institutions (i.e., managers of waterborne diseases), water resource managers (i.e., dams), and hydro-electricity generation, etc., do greatly benefit from the prediction of the dates of monsoon onset (Bombardi et al 2017).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The influence of global climate drivers on monsoon onset variability in Nigeria using S2S models

Model. Earth Syst. Environ.

Adefisan

Balogun

et al. 2019

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Rainfall onset has a lot of implications on the sustainability of the socioeconomic activities in Nigeria. This study assesses the skills of CMA, ECMWF, and UKMO sub-seasonal-to-seasonal (S2S) models in predicting monsoon onset and its variability over Nigeria. It also investigates the global drivers modulating the variability and their teleconnections with rainfall onset anomaly. All the models, their ensemble members, and the observations were subjected to quantitative statistical analyses from 1998 to 2016. Results show that the three models are able to simulate the Northwards migration of the onset dates adequately with inherent biases and unique characteristics. They are also able to capture the evolution and variability of the global drivers modulating the monsoon onset. While CMA and the ECMWF models improve progressively towards the Sahel, the UKMO model performance is best over the Gulf of Guinea. In addition, despite the fairly poor performance of the models in predicting the variability of onset dates over the Gulf of Guinea and the Sahel, there is a considerable improvement in the correlation skill of the models over the Savannah. Furthermore, results show that only the ECMWF model was able to produce the strength of both the African Easterly Jets (AEJ) and the Tropical Easterly Jet (TEJ) in spatio-temporal mode. These are two of the crucial global drivers modulating the dynamics of West African monsoon. It was also found out that most global drivers, especially the Inter-tropical Discontinuity (ITD) and the Sea Surface Temperature (SST) over the Central Pacific, exhibit direct teleconnection with the onset anomaly. This direct relationship is shown to be strongest over both the Gulf of Guinea and the Sahel. Although the CMA model might have the least skill, it, however, showed that all the S2S models, despite the inherent biases, are able to predict rainfall onset over Nigeria, within the sub-seasonal timescale. Finally, the results show that improvements in multi-model ensembles are valuable added information able to significantly improve model performance.

“…Rainfall variability associated with climate change has impacted socioeconomic activities such as agriculture, food security, water resources management, health sector, hydroelectric power generation, and dam management among others in Nigeria (Bello 2010). Most of the negative effects of rainfall variability are on agriculture since majority of farmers in the country depend on rain-fed agriculture for livelihood (IPCC 2014;Lawal et al 2016). Levels of adaptation of farmers in Nigeria to climate change is low, due to lack of adequate education, assets, information, and income (Madu 2016), and consequently agriculture is more vulnerable to climate change impact.…”

Section: Introductionmentioning

confidence: 99%

Impact of Moisture Flux and Vertical Wind Shear on Forecasting Extreme Rainfall Events in Nigeria

African Handbook of Climate Change Adaptation

Ajayi

Lawal

et al. 2021

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This chapter investigates extreme rainfall events that caused flood during summer months of June–September 2010–2014. The aim is to determine the impact of horizontal moisture flux divergence (HMFD) and vertical wind shear on forecasting extreme rainfall events over Nigeria. Wind divergence and convective available potential energy (CAPE) were also examined to ascertain their threshold values during the events. The data used include rainfall observation from 40 synoptic stations across Nigeria, reanalyzed datasets from ECMWF at 0.125° × 0.125° resolution and the Tropical Rainfall Measuring Mission (TRMM) dataset at resolution of 0.25° × 0.25°. The ECMWF datasets for the selected days were employed to derive the moisture flux divergence, wind shear, and wind convergence. The derived meteorological parameters and the CAPE were spatially analyzed and superimposed on the precipitation obtained from the satellite data. The mean moisture flux and CAPE for some northern Nigerian stations were also plotted for 3 days prior to and 3 days after the storm. The result showed that HMFD and CAPE increased few days before the storm and peak on the day of the storms, and then declined afterwards. HMFD values above 1.0 × 10−6 g kg−1 s−1 is capable of producing substantial amount of rainfall mostly above 50 mm while wind shear has a much weaker impact on higher rainfall amount than moisture availability. CAPE above 1000 Jkg−1 and 1500 Jk−1 are favorable for convection over the southern and northern Nigeria, respectively. The study recommends quantitative analysis of moisture flux as a valuable short-term severe storm predictor and should be considered in the prediction of extreme rainfall.