Bulletin of the American Meteorological Society

doi: 10.1175/bams-d-21-0121.1pmid: N/A

AbstractAdvanced Quantitative Precipitation Information (AQPI) is a synergistic project that combines observations and models to improve monitoring and forecasts of precipitation, streamflow, and coastal flooding in the San Francisco Bay Area. As an experimental system, AQPI leverages more than a decade of research, innovation, and implementation of a statewide, state-of-the-art network of observations, and development of the next generation of weather and coastal forecast models. AQPI was developed as a prototype in response to requests from the water management community for improved information on precipitation, riverine, and coastal conditions to inform their decision-making processes. Observation of precipitation in the complex Bay Area landscape of California’s coastal mountain ranges is known to be a challenging problem. But, with new advanced radar network techniques, AQPI is helping fill an important observational gap for this highly populated and vulnerable metropolitan area. The prototype AQPI system consists of improved weather radar data for precipitation estimation; additional surface measurements of precipitation, streamflow, and soil moisture; and a suite of integrated forecast modeling systems to improve situational awareness about current and future water conditions from sky to sea. Together these tools will help improve emergency preparedness and public response to prevent loss of life and destruction of property during extreme storms accompanied by heavy precipitation and high coastal water levels—especially high-moisture laden atmospheric rivers. The Bay Area AQPI system could potentially be replicated in other urban regions in California, the United States, and worldwide.

doi: 10.1175/bams-d-22-0221.1pmid: N/A

AbstractClimate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

doi: 10.1175/bams-d-23-0230.1pmid: N/A

AbstractDuring the boreal summer, mesoscale convective systems generated over West Africa propagate westward and interact with African easterly waves, and dust plumes transported from the Sahel and Sahara by the African easterly jet. Once off West Africa, the vortices in the wake of these mesoscale convective systems evolve in a complex environment sometimes leading to the development of tropical storms and hurricanes, especially in September when sea surface temperatures are high. Numerical weather predictions of cyclogenesis downstream of West Africa remains a key challenge due to the incomplete understanding of the clouds–atmospheric dynamics–dust interactions that limit predictability. The primary objective of the Clouds–Atmospheric Dynamics–Dust Interactions in West Africa (CADDIWA) project is to improve our understanding of the relative contributions of the direct, semidirect, and indirect radiative effects of dust on the dynamics of tropical waves as well as the intensification of vortices in the wake of offshore mesoscale convective systems and their evolution into tropical storms over the North Atlantic. Airborne observations relevant to the assessment of such interactions (active remote sensing, in situ microphysics probes, among others) were made from 8 to 21 September 2021 in the tropical environment of Sal Island, Cape Verde. The environments of several tropical cyclones, including Tropical Storm Rose, were monitored and probed. The airborne measurements also serve the purpose of regional model evaluation and the validation of spaceborne wind, aerosol and cloud products pertaining to satellite missions of the European Space Agency and EUMETSAT (including the Aeolus, EarthCARE, and IASI missions).