Excessive rains or prolonged drought can have severe impacts on the economy, agriculture, water resources, spread of diseases and ecosystems in many African countries. As current global numerical weather prediction systems fail to deliver accurate rainfall forecasts over tropical Africa, novel forecasting strategies are needed. Tropical waves are known to modulate precipitation over this region on timescales of a few days to several weeks. The aim of this dissertation is to quantify the influence of all major waves on rainfall variability over Africa, to investigate the involved mechanisms and, to test their potential for forecasting rainfall, with a focus on northern tropical Africa during the extended monsoon season. Despite the importance of rainfall variability for vulnerable societies in tropical Africa, the relative influence of tropical waves for this region is largely unknown. This thesis closes this gap and presents the first systematic comparison of the impact of six wave types on precipitation over northern tropical Africa during the transition and full monsoon seasons, using two satellite products and a dense rain gauge network. Composites of rainfall anomalies based on different datasets show comparable modulation intensities in the West Sahel and at the Guinea Coast, varying from less than 2 to above 7 mm per day depending on the wave type. Tropical disturbances (TDs, including African Easterly Waves, AEWs) and Kelvin waves dominate the 3-hourly to daily timescale and explain 10-30% of precipitation variability locally. On longer timescales (7–20 days), only the Madden-Julian Oscillation (MJO) and Equatorial Rossby (ER) waves remain as modulating factors and explain up to one third of rainfall variability. Eastward inertio-gravity (EIG) waves and mixed Rossby-gravity (MRG) waves are comparatively unimportant. An analysis of wave superposition shows that low-frequency waves (MJO, ER) in their wet phase amplify the activity of high-frequency waves (TD, MRG) and suppress them in the dry phase. Furthermore, this dissertation gives the first systematic comparison of the dynamics and thermodynamics associated with tropical waves affecting rainfall variability over northern tropical Africa: Reanalysis and radiosonde data were analyzed for the period 1981–2013 based on space-time filtering of outgoing longwave radiation. The identified circulation patterns are largely consistent with equatorial shallow water theory. The slow modes, MJO and ER, mainly impact precipitable water, whereas the faster TDs, Kelvin waves, and MRG waves primarily modulate moisture convergence. Monsoonal inflow intensifies during wet phases of the MJO, ER, and MRG waves, associated with a northward shift of the intertropical discontinuity for MJO and ER waves. This study reveals that MRG waves over Africa have a distinct dynamical structure that differs significantly from AEWs. During passages of vertically tilted imbalanced wave modes, such as MJO, TDs, Kelvin, and partly MRG waves, increased vertical wind shear and improved conditions for up- and downdrafts facilitate the organization of mesoscale convective systems. The balanced ER waves are not tilted and rainfall is triggered by large-scale moistening and stratiform lifting. The MJO and ER waves interact with intraseasonal variations of the Indian monsoon and extratropical Rossby wave trains. The latter causes a trough over the Atlas Mountains associated with a tropical plume and rainfall over the Sahara. The presented results unveil which dynamical processes need to be modeled realistically to represent the coupling between tropical waves and rainfall in northern tropical Africa. The potential of tropical waves as predictors for African rainfall was tested. The spatio-temporal correlation patterns of tropical waves highlight their potential for synoptic rainfall forecasting. The observed spatio-temporal properties agree with values predicted by shallow-water theory, with the exception of MRG and EIG waves, which have a strong phase dispersion at low wavenumbers. Unfiltered precipitation fields show correlations patterns that are physically explainable by tropical waves and other atmospheric phenomena such as the position of the tropical rainbelt. These correlations serve as predictors in a logistic regression model. It was shown that this model successfully predicts rainfall occurrence over Africa with a lead time of one day. The statistical model is calibrated and outperforms the climatological forecast and current numerical weather prediction models by about 20%. The fact that tropical waves explain large portions of synoptic to intraseasonal rainfall variability in almost the entire tropics emphasize the potential of the proposed statistical model. This PhD thesis has laid the foundation to exploit this potential and to significantly improve short-term weather forecasts in Africa and throughout the tropics.