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The south-central U.S. exists in a zone of dramatic transition in terms of eco-climate system diversity. Ecosystems across much of the region rely on warm-season convective precipitation. These convective precipitation is subject to large uncertainties under climate change scenario, possibly leading to gradual or sudden changes in habitats, and ecosystems. The convective precipitation in this region, occurring on a range of time and space scales, is extremely challenging to predict in future climate scenario. In this project, we established a unique, cutting-edge, dynamic downscaling capability to address the challenge of predicting precipitation in the south-central U.S. in current and future climate scenarios....
Precipitation amounts and frequencies are major regulators of soil heat-load profiles as the interval between rainfall events allows for increased heat storage during cloudless periods. The extreme drought of 2011 and the subsequent Flash Drought that occurred in summer, 2012, developed in part due to soil temperature dynamics across the landscape of the Southern High Plains. The negative impacts of highly variable soil temperatures on ecosystem process can be easily seen in family gardens. Most gardeners across the SHP realize that mulching has a beneficial impact on the success of any gardening effort as mulch reduces the heat storage of the soil thereby providing for a more stable temperature while also reducing...
The U.S. Great Plains is known for frequent hazardous convective weather and climate extremes. Across this region, climate change is expected to cause more severe droughts, more intense heavy rainfall events, and subsequently more flooding episodes. These potential changes in climate will adversely affect habitats, ecosystems, and landscapes as well as the fish and wildlife they support. Better understanding and simulation of regional precipitation can help natural resource managers mitigate and adapt to these adverse impacts. In this project, we aim to achieve a better precipitation downscaling in the Great Plains with the Weather Research and Forecast (WRF) model and use the high quality dynamic downscaling results...
We have developed an online, interactive course to provide an integrative understanding climate change called “managing for a changing climate”. Content includes the components of the physical climate system, the range of natural climate variability, external drivers of climate change such as anthropogenic contributions of greenhouse gases, climate models and projections, climate assessments, economics, policy, and vulnerability, and impacts and decision making. Over 50 short videos (3-10 min) have been created with expert guests from a variety of academic, government, and industry institutions. The course has been offered as a freely available for anyone worldwide three times with over 1000 total registrants; and...
The establishment of the South Central Climate Science Center (SCCSC) heralded new forms of partnership among Tribal nations and members of the climate science and conservation communities. But communicating key concepts such as risk and vulnerability is a culturally specific practice. So these new relationships call for pluricultural conversations about climate change and variability. To contribute to the goal of mutual understanding, this project developed and implemented a series of five workshops -- four in Oklahoma and one in New Mexico -- that introduced Tribal members and employees across the region to the SC CSC as a resource for their climate adaptation practices. Not counting members of the research team,...
Abstract: The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated...
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...
In recent years, climate projections have been used to research the climate system as well as provide guidance for climate adaptation decisions and impact assessments. There are numerous methods to produce the locally relevant climate projections for use in impact assessments. Since there are no standard methods to derive locally relevant projections, one must consider multiple approaches. In order to provide additional clarity regarding the use of available climate projections, this project assessed how the inputs that define the projections (e.g., historical climate data, downscaling method, etc.) contribute to the variability among different climate projections for temperature and precipitation variables. This...
Categories: Publication; Types: Citation; Tags: South Central CASC
The purpose of this project was to enhance the knowledge of local tribal environmental professionals related to planning for the increased frequency of weather events as a result of climate change. Beyond expanding knowledge, the objective of this workshop introduce the Division of Regional and City Planning faculty and students to the planning needs of tribal communities related to climate change. As a secondary objective, the grantees sought to lay a foundation for building relationships with the regional BIA offices and the tribal environmental professionals for future planning and research activities.
Led by university members of the South Central Climate Adaptation Science Center (South Central CASC), this project developed and implemented a program for professional development of graduate students, post-docs, and early-career environmental professionals who were conducting climate-related research for the south-central U.S. The project built upon the successes and feedback from previous trainings conducted in 2014 and 2016. The one-week program of workforce development focused on the following: (1) introducing a new cohort of early-career researchers to the goals, structure, and unique research-related challenges of the South Central CASC and its place within the U.S. Department of the Interior’s CASC network,...
Abstract: Statistical downscaling (SD) is commonly used to provide information for the assessment of climate change impacts. Using as input the output from large-scale dynamical climate models and observation-based data products, SD aims to provide a finer grain of detail and to mitigate systematic biases. It is generally recognized as providing added value. However, one of the key assumptions of SD is that the relationships used to train the method during a historical period are unchanged in the future, in the face of climate change. The validity of this assumption is typically quite difficult to assess in the normal course of analysis, as observations of future climate are lacking. We approach this problem using...
Categories: Publication; Types: Citation; Tags: South Central CASC