Explore the vast range of titles available.

Based on the idealized supercell and real case studies in Part I and II, the purpose of this subsequent study is to further investigate the impact of assimilating Geostationary Operational Environmental Satellites‐16 (GOES‐16) derived atmospheric motion vectors (AMVs) in addition to WSR_88D Doppler radar observations on convective scale numerical weather prediction. Five high‐impact weather events that occurred in spring 2018 and 2019 are analyzed using the National Severe Storms Laboratory three‐dimensional variational data assimilation (DA) system. Four types of experiments are implemented and compared: (a) the control experiment (NoDA) without assimilating any observation, (b) the radar DA experiment (RAD), (c) the GOES‐16 AMV DA experiment (AMV), and (d) the experiment assimilating AMVs together with radar data (AMV_RAD). Score metrics aggregated over all cases indicate that AMV_RAD performs slightly better than RAD in 0–3 hr reflectivity and precipitation forecasts especially at higher thresholds, suggesting the added value of GOES‐16 AMVs on radar data. Detailed case examinations also show that AMV_RAD generally exhibits slightly more skillful storm forecast in terms of the areal coverage, storm mode, and storm orientations, owing to improvements in the analysis of boundary locations and localized enhanced divergence signatures. In spite of encouraging objective and subjective evaluation results, AMV_RAD has difficulty in adjusting the moisture gradient associated with dryline and tends to underpredict the associated weak discrete storms. Plain Language Summary With the launch of Geostationary Operational Environmental Satellites‐16 (GOES‐16) in November 2016, the impact of its derived high‐spatiotemporal‐resolution atmospheric motion vectors (AMVs) product in convective‐scale numerical weather prediction has not been extensively explored. In this study, the GOES‐16 AMVs together with WSR‐88D Doppler radar observations are effectively assimilated by a three‐dimensional variational data assimilation scheme developed at NOAA/National Severe Storms Laboratory. Both subjective and objective assessment results for five severe weather events suggest the slightly added forecast skill of GOES‐16 AMVs on conventional radar data for 0–3 hr reflectivity and precipitation forecasts. Key Points GOES‐R derived atmospheric motion vector (AMV) product has the potential to benefit convective scale data assimilation and forecasts The impact of assimilating GOES‐R derived AMVs together with NEXRAD observations on short‐range severe storm forecasts is evaluated The verification results for five severe weather events suggest the added forecast skill of GOES‐16 AMVs over conventional radar data

For decades, researchers have successfully used ground-based surveys to understand localized spatial and temporal patterns in stopover habitat use by migratory birds. Recent technological advances with WSR-88D radar now allow such investigations on much broader spatial scales. Both methods are assumed to accurately quantify patterns in migrant bird communities, yet information is lacking regarding relationships between radar estimates of migration and different ground-based monitoring methods. From 2005 to 2007, we monitored migrant communities on or near two Department of Defense installations in the spring (Ft. Polk Military Complex, LA; U.S. Army Test and Evaluation Command, Yuma Proving Ground, AZ) and on two installations in the fall (Ft. Polk Military Complex, LA; Eglin Air Force Base, FL) using both ground-based transect surveys and radar imagery of birds aloft. We modeled daily changes in migrant abundance and positive and negative species turnover measured on the ground as a function of radar estimates of migrant exodus and input densities. Radar data were not significant predictors of any response variable in any season either in the southeastern or southwestern United States, indicating a disparity between the results obtained using different methods. Multiple unique sources of error associated with each technique likely contributed to the conflicting outcomes, and researchers should take great care when selecting monitoring methods appropriate to address research questions, effects of management practices, or when comparing the results of migration studies using different survey techniques. Por décadas los investigadores han utilizado exitosamente censos terrestres para tratar de entender los cambios espaciales y temporales de migratorios en lugares de paradas. Los recientes avances tecnológicos con el radar WSR-88D, permiten, actualmente, este tipo de investigación en una escala espacial más amplia. Se asume, que ambos métodos indicados cuantifican con precisión los patrones migratorios en comunidades de aves, aunque falta información referente a las relaciones entre los estimados con el radar y los de otros métodos de censos terrestres. De 2005 al 2007, monitoreamos comunidades migratorias durante la primavera, en o cerca de dos instalaciones del Departamento de Defensa (complejo militar Ft. Polk, LA; Comando de Pruebas y Evaluación del ejercito de los EUA, Yuma, Arizona) y otras dos durante el otoño (complejo militar Ft. Polk, LA; la base Eglin de la Fuerza Aérea, Fl), utilizando censos terrestres e imágenes de radar. Modelamos diariamente los cambios en la abundancia de migratorios y los cambios positivos o negativos de especies al usar censos en el terreno y como función de los estimados del radar en el éxodo migratorio y su aportación en las densidades. Los datos del radar no permitieron predecir, de forma significativa, ninguna variable de respuesta, en ninguna de las dos temporadas, y en ninguna de las dos localidades al sureste o suroeste de las Estados Unidos, e indicaron disparidad entre los resultados obtenidos utilizando diferentes métodos. Errores múltiples, asociados a cada técnica, contribuyeron a los resultados conflictivos, por lo que los investigadores deben tener cuidado cuando seleccionen el método de monitoreo más apropiado para contestar preguntas particulares, o el efecto de prácticas de manejo o cuando quieran comparar los resultados de estudios sobre migratorios eme usen diferentes técnicas.