UNHCR
Early Warning Risk Modeling of Climate-Induced Forced Displacement
© OCHA | Giles Clarke
ABOUT
CLIFDEW-GRID, developed by UNHCR in collaboration with the University of California, Irvine, addresses the growing challenge of climate-induced forced displacement through the first risk index of its kind. Using advanced analytics and forecasting methods, it provides subnational insights into where displacement risks are emerging. Initially applied in Western and Eastern Africa, the platform strengthens understanding of climate-related displacement dynamics and supports CRAF’d partners with a shared evidence base.
OBJECTIVES
CLIFDEW-GRID enables partners to translate risk insights into action. By making displacement risks visible earlier and at subnational level, it supports anticipatory decision-making, more targeted planning, and faster allocation of crisis financing. The platform strengthens how risk signals inform operational response, helping ensure that resources are directed to the right places at the right time.
CLIFDEW created the first subnational climate displacement risk index, enabling UNHCR and its partners to better anticipate and respond to forced displacement across Africa.
Ayman Gharaibeh
Director of Data, UNHCR
“
UPDATES
-
![]()
CLIFDEW-GRID REPORT 2026
With CRAF’d support, UNHCR released a new report on predicting forced displacement in the context of climate change, highlighting the CLIFDEW-GRID model. The machine-learning system combines climate, conflict, and food security data to identify areas at risk of cross-border displacement and support earlier humanitarian response.
-
![]()
CLIFDEW-GRID AT IFMS
At the International Forum on Migration Statistics, CLIFDEW-GRID presented methods to forecast climate- and conflict-driven displacement. With CRAF’d support, the platform helps policymakers anticipate, prevent, and respond, strengthening anticipatory action across contexts.
-
![]()
CLIFDEW-GRID MODELLING
At UNHCR’s workshop on predictive analytics in humanitarian contexts, the CRAF’d-supported CLIFDEW-GRID project showed how grid-level modelling and novel data sources improve displacement forecasting, helping partners anticipate, prevent, and respond more effectively.
-
![]()
CLIFDEW-GRID AT NNF AI
At the Novo Nordisk AI Challenge, CLIFDEW-GRID showed how data science anticipates displacement. The CRAF’d-supported project enables partners to anticipate, prevent, and respond faster, strengthening early action and shifting crisis management from reaction to anticipation.
-
![]()
DATA FOR PEACE
At the Data for Peace Conference, UNHCR showcased CLIFDEW-GRID, demonstrating how this CRAF’d-funded project leverages big data and analytics to anticipate climate-induced displacement, enabling partners to respond faster and strengthen early action for effective crisis management.
-
![]()
WHY CLIMATE DATA MATTERS
UNHCR’s CLIFDEW-GRID project, funded by CRAF’d, is advancing a crucial risk index for climate-induced displacement, focusing on West and East Africa, helping partners anticipate crises, respond faster, and strengthen early action in vulnerable communities.
