Kamoru Abiodun Lawal

Accurate sub-seasonal-to-seasonal (S2S) forecasts are critical for mitigating extreme weather impacts and supporting development in West Africa. This study evaluates real-time ECMWF S2S rainfall forecasts during the 2020–2021 West African monsoon (March–October) and uses corresponding hindcasts for comparison. We verify forecasts at 1–4 dekads lead against two satellite-based rainfall datasets (TAMSAT and GPM-IMERG) to cover observational uncertainty. The analysis focuses on spatio-temporal monsoon patterns over the Gulf of Guinea (GoG) and Sahel (SAH). The results show that ECMWF-S2S captures key monsoon features. The forecast skill is generally higher over the Sahel than the GoG, and peaks during the main monsoon period (July–August). Notably, forecasts achieve approximately 80% synchronization with observed rainfall-anomaly timing, indicating that roughly 4 out of 5 dekads have correctly predicted wet/dry phases. Probabilistic evaluation shows strong reliability. The debiased ranked probability skill score (RPSS) is high across thresholds, whereas the average ROC AUC (~0.68) indicates moderate discrimination. However, forecasts tend to under-predict very low rains in the GoG and very high rains in the Sahel. Using multiple datasets and robust metrics helps mitigate observational uncertainty. These results, for the first real-time S2S pilot over West Africa, demonstrate that ECMWF rainfall forecasts are skillful and actionable (especially up to 2–3 dekads ahead), providing confidence for early-warning and planning systems in the region.

Weather and climate forecasting, using climate models, have become essential tools and life-savers in the West African region; in spite of the fact that climate models do not fully comply with attributes of forecast qualities—RASAP: reliability, association, skill, accuracy, and precision. The objective of this paper is to quantitatively evaluate, in comparison to CRU and ERA5 datasets, the RASAP compliance-level of the weather@home2 modeling system (w@h2). Findings from some statistical evaluations show that, to a moderately significant extent, w@h2 model provides useful information during the monsoon seasons; skills to capture the Little Dry Season over the Guinea zone; predictive skills for the onset season; ability to reproduce all the annual characteristics of the surface maximum air temperature over the region; as well as skill to detect heat waves that usually ravage West Africa during the boreal spring. The model displays traces of attributes that are needed for seasonal climate predictions and applications. Deficiencies in the quantitative reproducibility point to the facts that the model does provide a reliability akin to that of regional climate models. This paper further furnishes a prospective user with information on whether the model might be “useful or not” for a particular application.

Weather and climate forecasting is extremely important for improving the socio-economic well-being of the West African region. It safe-guards the region from weather and climate related disasters. Hence, utilization of products from climate models are being encouraged and have therefore become essential tools and life-savers, in spite of the fact that climate models do not fully comply with attributes of forecast qualities - RASAP: reliability, association, skill, accuracy and precision. This paper thus quantitatively evaluates, in comparisons to CRU and ERA5 datasets, the RASAP compliance-level of the weather@home2 modelling system (w@h2: a successor to the well-known weather@home1 modelling system) which now produces an exceptionally large number of ensembles of simulations (>10,000). Having been designed for the investigation of the behavior of extreme weather under anthropogenic climate change, findings show that the performance of w@h2 in terms of climate variability may be more relevant than measures of the mean climatology. To some significant extent w@h2 model provides little, if any, predictive information for precipitation during the dry season, but may provide useful information during the monsoon seasons as well as skill to capture the Little Dry Season over the Guinea zone; predictive skills for the onset season suggest that the model is getting processes right. The w@h2 model is also able to reproduce all the annual characteristics of the surface maximum air temperature over the sub-region with skill to detect heat waves that usually ravage West Africa during the boreal spring. With synchronization > 80% the model has the ability to reliably / accurately simulate the actual anomaly signs of the observed climate parameters which is one of the special attributes of a model that is needed for seasonal climate predictions and applications. The large sample sizes produced by the w@h2 model are able to show that sampling quality of the tails of the distribution is no longer the primary constraint / source of uncertainty. The study further furnishes a prospective user with information on whether the model might be “useful or not” for a particular application.

Quantifying how well Nature-based Solutions can offset anthropogenic climate change impacts is important for adaptation planning, but has rarely been done. Here we show that a widely-applied Nature-based Solution in South Africa – invasive alien tree clearing – reduces the impact of anthropogenic climate change on drought streamflow. Using a multi-model joint-attribution of climate and landscape-vegetation states during the 2015–2017 Cape Town “Day Zero” drought, we find that anthropogenic climate change reduced streamflow by 12–29% relative to a counterfactual world with anthropogenic emissions removed. This impact on streamflow was larger than corresponding reductions in rainfall (7–15%) and reference evapotranspiration (1.7–2%). Clearing invasive alien trees could have ameliorated streamflow reductions by 3–16% points for moderate invasions levels. Preventing further invasive alien tree spread avoided potential additional reductions of 10–27% points. Total clearing could not have offset the anthropogenic climate change impact completely. Invasive alien tree clearing is an important form of catchment restoration for managing changing hydroclimatic risk, but will need to be combined with other adaptation options as climate change accelerates.

Attributing the extent to which Nature-based Solutions (NbS) can offset emerging risk from anthropogenic climate change is a test of effectiveness for climate change adaptation, but has rarely, if ever, been done. Here we show that a widely applied NbS in South Africa – invasive alien tree clearing – can reduce the impact on hydrological drought severity due to human influence on climate, using the Cape Town “Day Zero” drought as an example. Using a multi-model “joint-attribution” framework of coupled climate and landscape states, we find that 12–29% of the hydrological drought severity can be attributed to anthropogenic climate change, compared to 7–15% for reduced rainfall and 1.6-2% for increased reference evapotranspiration. Attributable human influence on meteorological drought was amplified by 5–14% as it propagated through the hydrological system. Clearing invasive alien trees and preventing spread significantly reduced the attributable human influence on hydrological drought severity (2–15% for moderately and 10–27% for fully invaded catchments) but was not sufficient to remove the climate change impact completely. The relative contribution of NbS to drought severity reduction will decrease as climate change progresses. NbS will continue to be important but should be combined with other adaptation options to manage increasing hydro-climatic risk.

This paper identifies fundamental issues which prevent the effective uptake of climate information services in Nigeria. We propose solutions which involve the extension of short-range (1 to 5 days) forecasts beyond that of medium-range (7 to 15 days) timescales through the operational use of current forecast data as well as improve collaboration and communication with forecast users. Using newly available data to provide seamless operational forecasts from short-term to sub-seasonal timescales, we examine evidence to determine if effective demand-led sub-seasonal-to-seasonal (S2S) climate forecasts can be co-produced. This evidence involves: itemization of forecast products delivered to stakeholders, with their development methodology; enumeration of inferences of forecast products and their influences on decisions taken by stakeholders; user-focused discussions of improvements on co-produced products; and the methods of evaluating the performance of the forecast products.We find that extending the production pipeline of short-range forecast timescales beyond the medium-range, such that the medium-range forecast timescales can be fed into existing tools for applying short-range forecasts, assisted in mitigating the risks of sub-seasonal climate variability on socio-economic activities in Nigeria. We also find that enhancing of collaboration and communication channels between the producers and the forecast product users helps to: enhance the development of user-tailored impact-based forecasts; increases users' trusts in the forecasts; and, seamlessly improves forecast evaluations. In general, these measures lead to more smooth delivery and increase in uptake of climate information services in Nigeria.

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.