Final Report-Quantifying Future Precipitation in the South Central Region for Stakeholder Planning
Dates
Publication Date
2018-11-01
Citation
Jung-Hee Ryu, Katharine Hayhoe, and Sharmistha Swain, 2018-11-01, Final Report-Quantifying Future Precipitation in the South Central Region for Stakeholder Planning: .
Summary
The South-Central U.S. is home to diverse climates and ecosystems, strong agricultural and energy sectors, and fast-growing urban areas. All share a critical need for water, which is becoming an increasingly scarce resource across the region as aquifers are overdrawn and populations grow. Understanding what brings rain to this region, and how the timing and amount of precipitation may be affected by climate change, is essential for effective water planning and management. However, currently available information on long-term precipitation trends for the South Central region is often perceived to be irrelevant to community planners and water managers, due to multiple factors including mismatches between the time horizons used in planning [...]
Summary
The South-Central U.S. is home to diverse climates and ecosystems, strong agricultural and energy sectors, and fast-growing urban areas. All share a critical need for water, which is becoming an increasingly scarce resource across the region as aquifers are overdrawn and populations grow. Understanding what brings rain to this region, and how the timing and amount of precipitation may be affected by climate change, is essential for effective water planning and management. However, currently available information on long-term precipitation trends for the South Central region is often perceived to be irrelevant to community planners and water managers, due to multiple factors including mismatches between the time horizons used in planning versus projections, high levels of uncertainty associated with precipitation projections for the region, and the challenges of presenting scientific information in accessible ways. This project tackled the question of whether it is possible to increase the relevance of long-term precipitation projections to real-world decision-makers in the South Central region. To that end, we expanded our understanding of the natural atmospheric processes that bring moisture to the region and were able to determine that global climate models are able to reproduce the large-scale atmospheric patterns that control the onset and duration of growing-season drought; and that these patterns are likely to become stronger and longer-lasting in the future. We also developed surveys that we distributed to water managers in Texas and Louisiana. The questionnaire included sample data, figures, and maps, and asked participants in-depth questions regarding the time horizons, specific climate indicators, and methods of presentation they found to be most relevant and useful to their work. Finally, we used this information to develop future projections for individual weather stations and a regular grid covering the South Central region, and to summarize these projections using the indicators and methods of presentation prioritized by survey respondents. Gridded regional information was made available via the Southern Regional Climate Center’s data provision portal [http://ice.srcc.lsu.edu] to assist water resources planning and preparedness effortsthroughout the region and the station data was provided to the Environmental Systems Research Institute (ESRI) to be hosted free of charge and the data made available to water planners and the public in the ArcGIS mapping environment. Lessons learned from this work inform long-term projections for our region and beyond, and demonstrate how, through engaging with and soliciting input from stakeholders, it is possible to: (1) develop and test actionable climate science questions such as, “are projections of increased risk of growing-season drought robust?”; and (2) make complex climate information and analyses more approachable, understandable, and actionable for regional policy-makers, planners, and managers through translating information into relevant indicators and time frames.
