In a groundbreaking initiative set to advance our grasp of climate dynamics, Benjamin Cash, a distinguished research scientist specializing in Ocean-Land-Atmosphere Studies at George Mason University’s Center for Ocean-Land-Atmosphere Studies (COLA), has secured substantial funding from the National Oceanic and Atmospheric Administration (NOAA). His innovative research project, entitled “Know, Explore, Improve: Hypothesis-driven development of the UFS,” marks a pivotal step toward decoding the complexities of seasonal climate predictability, with a specific emphasis on extreme precipitation events occurring on subseasonal to seasonal (S2S) timescales.
Cash’s research focuses on refining the sophisticated modeling systems within the Unified Forecast System (UFS), an advanced framework designed to integrate atmospheric, oceanic, and terrestrial processes to deliver more reliable weather and climate forecasts. By implementing a hypothesis-driven methodology, Cash aims to systematically identify and ameliorate inadequacies in current modeling approaches, thus enhancing the robustness of S2S predictions particularly concerning precipitation extremes. This endeavor addresses longstanding gaps in our ability to forecast such critical phenomena, which carry profound implications for water resource management, disaster preparedness, and climate resilience.
The funding of over one million dollars will empower Cash and his team to conduct in-depth numerical experiments and data assimilation efforts that tackle the multi-scale interactions inherent in the climate system. Understanding how atmospheric circulations, soil moisture anomalies, ocean states, and land-atmosphere feedbacks intertwine to influence precipitation extremes on intermediate timescales remains a formidable scientific hurdle. The project will leverage high-performance computing resources and novel observational datasets to interrogate these complex interactions, aiming to distill predictive signals from the inherent climate variability and noise.
A key scientific thrust involves dissecting the processes that govern the amplitude, frequency, and duration of extreme precipitation episodes beyond the traditional weather forecast horizon of several days. This involves exploring atmospheric teleconnections, such as the influence of tropical sea surface temperature patterns and midlatitude circulation anomalies, which have shown promise as predictors of S2S climate variations. Improving model representation of these teleconnections and their mechanistic links to localized precipitation extremes could drastically extend the lead time with which communities are warned of hazardous weather conditions.
Moreover, the research is set to refine parameterizations of convection and microphysical processes within atmospheric models. These parametrizations are crucial for accurately simulating cloud formation and precipitation initiation, yet remain an area of significant uncertainty in S2S forecasting. By coupling observational insights with detailed process studies, Cash’s work will support the development of more physically realistic scheme formulations, fostering enhanced simulation fidelity across diverse climatic regimes.
An additional dimension of the research addresses land surface interactions, particularly soil moisture and vegetation dynamics that modulate evapotranspiration and surface energy exchanges. Such land-atmosphere couplings provide critical feedback to atmospheric moisture fluxes and convective triggering mechanisms, influencing the timing and intensity of precipitation extremes. Improved modeling of these interactions within the UFS promises not only better forecasts but also valuable insight into potential shifts in hydrological extremes under evolving climate conditions.
The broader implications of Cash’s project extend well beyond academic circles, promising tangible benefits for sectors vulnerable to climate variability. Improved subseasonal to seasonal forecasts of precipitation extremes can inform agricultural planning, water resource allocation, urban infrastructure design, and emergency response strategies. By increasing forecast lead times and reliability, stakeholders can better anticipate and mitigate the devastating impacts of floods, droughts, and associated socioeconomic disruptions.
Set to begin in August 2025 and run through July 2028, this multi-year initiative is supported by a funding allocation of $1,048,807 from NOAA, underscoring the strategic priority assigned to advancing climate predictability within federal research agendas. Situated in a university renowned for its interdisciplinary expertise, Cash’s work benefits from a collaborative environment with atmospheric scientists, oceanographers, and earth system modelers, fostering integrative approaches essential for addressing the inherent complexity of climate phenomena.
George Mason University, located in the heart of the Washington, D.C. metropolitan area, boasts a rapidly expanding research enterprise with substantial investments in science and technology innovation. As Virginia’s largest public research institution, it offers a dynamic platform for the development of cutting-edge scientific investigations like Cash’s that merge theory, observation, and computational modeling. This research initiative complements the university’s broader mission to harness knowledge for societal benefit and environmental stewardship.
The UFS itself represents a transformative evolution in numerical weather prediction and climate modeling, endorsed by multiple federal agencies as the backbone for operational forecasting. By pursuing a hypothesis-driven research strategy, Cash’s project seeks to elevate the UFS’s capabilities, ensuring that it not only assimilates the latest scientific understanding but also remains adaptable to emergent challenges such as non-linear climate interactions and extreme event attribution.
Anticipated outcomes of this research include refined diagnostic tools, enhanced model diagnostics, and optimized data assimilation techniques that collectively improve forecast skill at subseasonal to seasonal horizons. Through iterative model testing and validation against observational benchmarks, the project will identify key leverage points for targeted improvements, potentially setting new standards in the predictive science community for climate extremes.
As the occurrence and severity of precipitation extremes continue to intensify globally due to anthropogenic climate change, the timing of Cash’s research is particularly salient. Enhanced understanding and prediction of these events can empower societies to better manage risks and adapt resiliently to a changing climate landscape. The proposed advances in the UFS will thus play a critical role in underpinning future climate services and informing policymaking at multiple scales.
In concluding, Benjamin Cash’s NOAA-funded project exemplifies the critical intersection of fundamental science and applied forecasting in the endeavor to decode Earth’s complex climate system. Through this ambitious exploration of subseasonal to seasonal precipitation extremes, driven by mechanistic hypotheses and integrated modeling, the research promises to transform predictive capabilities within the atmospheric sciences. Such progress is vital for enhancing societal preparedness in an era increasingly marked by climatic uncertainty and variability.
Subject of Research: Seasonal predictability and improved subseasonal to seasonal precipitation extremes forecasting through the Unified Forecast System.
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Web References: http://www.gmu.edu/
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Keywords: Earth sciences, seasonal predictability, precipitation extremes, subseasonal to seasonal forecasting, Unified Forecast System, climate modeling, atmospheric science, ocean-land-atmosphere interaction, NOAA funding.
