Understanding the interplay between multiple climate change risks and socioeconomic development is increasingly required to inform effective actions to manage these risks and pursue sustainable development. We calculate a set of 14 impact indicators at different levels of global mean temperature (GMT) change and socioeconomic development covering water, energy and land sectors from an ensemble of global climate, integrated assessment and impact models. The analysis includes changes in drought intensity and water stress index, cooling demand change and heat event exposure, habitat degradation and crop yield, amongst others. To investigate exposure to multi-sector climate impacts, these are combined with gridded socioeconomic projections of population and those 'vulnerable to poverty' from three Shared Socioeconomic Pathways (SSP) (income <$10/day, currently 4.2 billion people). We show that global exposure to multi-sector risks approximately doubles between 1.5 °C and 2 °C GMT change, doubles again with 3 °C GMT change and is ~6x between the best and worst cases (SSP1/1.5 °C vs SSP3/3 °C, 0.8–4.7bi). For populations vulnerable to poverty, the exposure is an order of magnitude greater (8–32x) in the high poverty and inequality scenarios (SSP3) compared to sustainable socioeconomic development (SSP1). Whilst 85%–95% of global exposure falls to Asian and African regions, they have 91%–98% of the exposed and vulnerable population (depending on SSP/GMT combination), approximately half of which in South Asia. In higher warming scenarios, African regions have growing proportion of the global exposed and vulnerable population, ranging from 7%–17% at 1.5 °C, doubling to 14%–30% at 2 °C and again to 27%–51% at 3 °C. Finally, beyond 2 °C and at higher risk thresholds, the world's poorest are disproportionately impacted, particularly in cases (SSP3) of high inequality in Africa and southern Asia. Sustainable development that reduces poverty, mitigates emissions and meets targets in the water, energy and land sectors has the potential for order-of-magnitude scale reductions in multi-sector climate risk for the most vulnerable.