RESUMEN
Precipitation nowcasting, the high-resolution forecasting of precipitation up to two hours ahead, supports the real-world socioeconomic needs of many sectors reliant on weather-dependent decision-making1,2. State-of-the-art operational nowcasting methods typically advect precipitation fields with radar-based wind estimates, and struggle to capture important non-linear events such as convective initiations3,4. Recently introduced deep learning methods use radar to directly predict future rain rates, free of physical constraints5,6. While they accurately predict low-intensity rainfall, their operational utility is limited because their lack of constraints produces blurry nowcasts at longer lead times, yielding poor performance on rarer medium-to-heavy rain events. Here we present a deep generative model for the probabilistic nowcasting of precipitation from radar that addresses these challenges. Using statistical, economic and cognitive measures, we show that our method provides improved forecast quality, forecast consistency and forecast value. Our model produces realistic and spatiotemporally consistent predictions over regions up to 1,536 km × 1,280 km and with lead times from 5-90 min ahead. Using a systematic evaluation by more than 50 expert meteorologists, we show that our generative model ranked first for its accuracy and usefulness in 89% of cases against two competitive methods. When verified quantitatively, these nowcasts are skillful without resorting to blurring. We show that generative nowcasting can provide probabilistic predictions that improve forecast value and support operational utility, and at resolutions and lead times where alternative methods struggle.
RESUMEN
BACKGROUND: Vulnerable preterm infants experience repeated and prolonged pain/stress stimulation during a critical period in their development while in the neonatal intensive care unit (NICU). The contribution of cumulative pain/stressors to altered neurodevelopment remains unclear. The study purpose was to investigate the impact of early life painful/stressful experiences on neurobehavioral outcomes of preterm infants in the NICU. METHODS: A prospective exploratory study was conducted with fifty preterm infants (28 0/7-32 6/7weeks gestational age) recruited at birth and followed for four weeks. Cumulative pain/stressors (NICU Infant Stressor Scale) were measured daily and neurodevelopmental outcomes (NICU Network Neurobehavioral Scale) were examined at 36-37weeks post-menstrual age. Data analyses were conducted on the distribution of pain/stressors experienced over time and the linkages among pain/stressors and neurobehavioral outcomes. RESULTS: Preterm infants experienced a high degree of pain/stressors in the NICU, both in numbers of daily acute events (22.97±2.30 procedures) and cumulative times of chronic/stressful exposure (42.59±15.02h). Both acute and chronic pain/stress experienced during early life significantly contributed to the neurobehavioral outcomes, particularly in stress/abstinence (p<0.05) and habituation responses (p<0.01), meanwhile, direct breastfeeding and skin-to-skin holding were also significantly associated with habituation (p<0.01-0.05). CONCLUSION: Understanding mechanisms by which early life experience alters neurodevelopment will assist clinicians in developing targeted neuroprotective strategies and individualized interventions to improve infant developmental outcomes.
