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Attribution and Predictability Assessments Team

Leads: Tom Hamill and Judith Perlwitz

Policy and decision makers seek accurate knowledge of regional and seasonal differences in climate trends and variations for determining impacts and adaptation decisions in agriculture, water supply, health, energy and other sectors. They also desire the best available science regarding the factors causing high-impact weather and climate related extremes to make informed decisions on how society should invest in critical infrastructure in risk-prone areas while ensuring resilience.

PSD's Attribution and Predictability Assessments Team seeks to understand the physical factors that cause observed regional and seasonal climate trends, and high-impact weather and climate events. We place a special emphasis on understanding the large-scale drivers that influence local and regional extreme events such as floods, droughts, and heat waves. Key tools for our research are observational data as well as experiments with climate and hydrology models of different complexity. Multi-model approaches and large ensembles are required to address the role of proper representation of physical processes in models and to study extreme events. Through our many collaborations, we work to embed climate knowledge in the practice of climate risk management and adaptation to climate change by providing guidance and assistance in the use of climate information, and contributing to assessments of the causes of high-impact events.

Current Research Activities

Improving understanding of causes & predictability of droughts & floods. Exploring sources of subseasonal to seasonal predictability of North American climate.
Characterizing the increase in U.S. precipitation – with focus on increases in heavy precipitation events. Studying causes of recent Arctic warming & linkages to lower latitude climate & weather extremes.
Studying global climate sensitivity to recent slowdown in global sea surface temperature increases. Developing a publicly-available web repository of model output & observational data that facilitates interpreting & diagnosing causes of evolving weather & climate extremes.
Examining anticipated statistical changes of weather & hydroclimate over western N. America in coming decades respective to needs in water & ecosystem management. Leading & facilitating research into understanding climate drivers for regional water balance & hydroclimatic extremes in mountain regions & the Great Plains.