Most European migratory birds wintering in sub-Saharan Africa have anticipated arrival to the breeding areas over the past decades. This phenological change may be ultimately caused by warming of the Northern Hemisphere via evolutionary changes or phenotypic plasticity in migration behavior. First arrival dates are negatively predicted by temperatures upon arrival to the breeding grounds. This seems puzzling, because migrants should be unable to predict weather conditions at long range. Migrants can enjoy diverse fitness benefits from early arriving. However, if weather conditions at destination cannot be predicted, early arrival can also entail severe costs. If meteorological conditions in Europe during breeding covary with those in sub-Saharan Africa during late winter, long-distance migrants may have a clue to predict meteorological conditions in their breeding areas while they are still in Africa and adjust their migration schedule consequently, an idea that has never been tested. We analyzed the correlation between March–April temperature anomalies (Tan) in Europe and February Tan in the Sahel and sub-Sahel, where long-distance migrants winter or stop-over. Tan in Africa negatively predicted Tan in Europe, the association being particularly strong (unsigned effect size, zr>0.35) for eastern Sahel and northern and eastern Europe, where the risks of early arrival may be larger. However, the strength of the correlations between Tan in the two continents has declined during the last 25 years; thus, possibly, partly compromising adaptive mechanisms of adjustment of migration. The existence of such climatic connectivity leads to several predictions, including that positive Tan in Africa should delay arrival. Consistent with this prediction, we found that first arrival dates of seven long-distance migratory species positively covaried with February Tan in Africa. Thus, while wintering, migrants might be able to predict meteorological conditions at the beginning of the breeding season, and phenotypically adjust migration schedules to optimally tune arrival date.