Attribution and Predictability Assessments

2013 Boulder flood aftermath photo courtesy FEMA

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 predictability of and to improve predictions of extreme phenomena, especially on sub-seasonal to seasonal time scales. Additionally, APA conducts attribution studies of extreme weather phenomena describes the predictability characteristics of those extreme events and identifies sources of their predictability. 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. APA also focuses on the statistical postprocessing of forecasts, whereby discrepancies between past forecasts and observations/analyses are used to make corrections to the real-time forecasts. APA actively partners with the National Weather Service, providing experimental algorithms to operational partners at the Climate Prediction Center, the Meteorological Development Laboratory, the Environmental Modeling Center, and more.

Current Research Activities

IMPROVING understanding of causes and predictability of droughts and floods.
El Nino
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 and linkages to lower latitude climate and weather extremes.
sea surface temperature map
STUDYING global climate sensitivity to recent slowdown in global sea surface temperature increases.
DEVELOPING a publicly-available web repository of model output and observational data that facilitates interpreting and diagnosing causes of evolving weather and climate extremes.
Hoover Dam
EXAMINING anticipated statistical changes of weather and hydroclimate over western N. America in coming decades respective to needs in water and ecosystem management.
hay on te Great Plains
LEADING and facilitating research into understanding climate drivers for regional water balance and hydroclimatic extremes in mountain regions and the Great Plains.
IMPROVING sub-seasonal predictions of high-impact events, such as fire weather and heavy precipitation, through the statistical postprocessing of numerical forecasts.