Abstract: Over the past two decades, evidence has mounted that the global climate is changing rapidly and natural disastrous events are increasing in number, intensity and severity. Gravity of the situation demands for a paradigm shift from reactive approach to proactive one: From response and recovery to disaster risk reduction (DRR). There are solid reasons for the linkage between climate change and DRR since the former is expected to increase the frequency and intensity of natural disastrous events and the later demands for appropriate actions to take for reducing disaster risks. Therefore, there has been a surge of interest in developing early warning systems (EWS) to cater to the needs of communities that are at high risk of hydro-metrological hazards. However, developing an effective EWS not only need a sound scientific and technical basis, but also a strong focus on the people exposed to risks is a challenging task. Pakistan, a natural hazards prone country, is in great need to have an effective and efficient multi-hazard EWS which uses scientific data to analyze the risk perspective of the hazardous events. For this it is important not only to develop a EWS that is suitable for Pakistan that meets the local conditions such as socio-cultural, political, technological and administrative but they are also essential investments that help saving lives, protecting property and livelihoods, contribute to the sustainability of development, and are far more cost-effective in strengthening coping mechanisms than is primary reliance on post-disaster response and recovery. However, lack of an appropriate and robust people-centred EWS and failure to warn people at risk in advance is one of the main causes for high levels of human, economic and environmental losses. In the natural hazards risk context, the EWS should be capable of automatically detecting, in accordance with specific thresholds, the areas where adverse hydro-metrological hazardous events are expected within the next few days – in case of forecasts – and within the next few weeks – in case of long term predictions - and subsequently should have the ability to issue relevant timely warnings – along with the required actions to be taken and ample information - to the specific communities that are at risk.