Sub-seasonal to Seasonal Predictability of Extreme Events
Sources of cross-scale predictability of extreme precipitation in the High Plains
We develop and use data sets, models, and information techniques to explore the possible sources of predictability of extreme hydrometeorological and climate events (EHCEs). We are particularly interested in sub-seasonal to seasonal lead-times. When our abilities to predict EHCEs remain constrained, we identify the potential effects of --for example-- droughts, floods, and heatwaves on particular systems at scales relevant for decision and policymaking.
Extreme events in India
Rural and urban water demands will continue on the rise as the population grows, and the consumption of energy and food increases. Agriculture, in particular, poses multiple challenges because of the complexities in managing water resources across jurisdictional and geopolitical boundaries and geospatial scales. Additionally, the acceleration of the human enterprise has progressively deteriorated the environment and, in particular, water (and air) quality. The need for integrated studies, technological developments, and innovation in the nexus water quality and quantity becomes critical to build resilient, secure, and sustainable water, food, energy, and environmental services systems.
The 2019 Flood
Breeding is arguably the most affordable and accessible technology used to improve crop yield in farms around the globe since it has been an activity built upon the ingenuity, persistence, and cultural values in many nations. Breeding also materializes an evolving knowledge from empirical experiences to analytical principles on agricultural responses to environmental changes as mechanisms to built a resilient food-production system and enhance ecosystem resilience. The integration of statistical, data-driven, and numerical models foster applied and basic research activities aimed to deliver decision support tools, as well as to elucidate the underlying principles of plants' adaptive abilities..