Search for: All records

Abstract This study evaluates the impact of assimilating precipitable water vapor (PWV) within an observing system simulation experiment (OSSE) framework to improve forecasts of monsoonal mesoscale convective systems (MCSs) in Arizona. Two contrasting case studies differing in convective forcing, longevity, intensity, and coverage are analyzed using a 40‐member ensemble of 1.8‐km resolution Weather Research and Forecasting (WRF) convective‐permitting model (CPM) simulations including the Data Assimilation Research Testbed (DART) system. Synthetic PWV data are derived from a nature run (NR) and bias corrected using real GPS‐derived PWV observations from a campaign during the North American monsoon (NAM) season 2021. These synthetic PWV are assimilated in an inferior model simulation called the control run (CR) to avoid the identical twin problem. Horizontal GPS station spacing experiments (e.g., superobbed, 50 km, 100 km, and 200 km) are conducted to identify configurations that maximize forecast skills. Assimilating the synthetic PWV reduces mean errors (∼2 mm) and dry bias during the first 4–6 hr of the predictions using analyses improved with PWV data assimilation. The 100‐km GPS network optimally captures convective precipitation patterns, outperforming coarser (200‐km) and finer (50‐km) grids due to an improved representation of moisture and winds afforded by PWV data assimilation at the appropriate scales. Topography strongly influences moisture distribution, with elevation‐dependent biases, overestimation in low elevations (0–500 m), underestimation in midelevations (500–2,000 m), and systematic high‐elevation (>2,000 m) biases due to vertically integrated PWV constraints. This study provides actionable insights for optimizing GPS network design and improving convective‐scale modeling in arid/semiarid regions. 

Abstract. The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.