Significance This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.
The response of the lower marine atmospheric boundary layer to sharp changes in sea surface temperature was studied in the Frontal Air‐Sea Interaction Experiment (FASINEX) with aircraft and ships measuring mean and turbulence quantities, sea surface temperature, and wave state. Changing synoptic weather on 3 successive days provided cases of wind direction both approximately parallel and perpendicular to a surface temperature front. For the wind perpendicular to the front, both wind over cold‐to‐warm and warm‐to‐cold surface temperatures occurred. For the cold‐to‐warm case, the unstable boundary layer was observed to thicken, with increased convective activity on the warm side. For the warm‐to‐cold case, the surface layer buoyant stability changed from unstable to neutral or slightly stable, and the sea state and turbulence structure in the lower 100 m were immediately altered, with a large decrease in stress and slowing of the wind. Measurements for this case with two aircraft in formation at 30 and 100 m show a slightly increased stress divergence on the cold side. The turbulent velocity variances changed anisotropically across the front: the streamwise variance was practically unchanged, whereas the vertical and cross‐stream variances decreased. Model results, consistent with the observations, suggest that an internal boundary layer forms at the sea surface temperature front. The ocean wave, swell, and microwave radar backscatter fields were measured from several aircraft which flew simultaneously with the low‐level turbulence aircraft. Significant reductions in backscatter and wave height were observed on the cold side of the front.
The effects of the sea surface temperature (s.s.t.) front at the edge of the Gulf Stream on the marine atmospheric boundary layer (MABL) are investigated using a numerical model to study the modification effects of an oceanic front on the MABL structure. The situation simulated is flow from over cold shelf water to over the warm water of the Gulf Stream. The initial temperature and humidity profiles of the air are specified to be near neutral over the cold water and are therefore typical of undisturbed conditions. The differential in s.s.t. across the oceanic front creates a horizontal variation in the surface perturbation pressure and the stability. The surface perturbation pressure and turbulent fluxes modulate the flow and produce horizontal variations in horizontal wind components with associated vertical motions. A thermally direct cell is produced as a result of the s.s.t. difference across the front. The isotherms slope upward towards the warm water. Entrainment of inversion layer air and upward vertical motion over the warm water cause the MABL to be deeper there. A layer of cloud forms over warm water and is associated with mixed layer deepening rather than lowering of the condensation level. Turbulent fluxes in the MABL show considerable spatial variation. Surface stress is much larger over the front and over the warm water than over the cold water. This is mostly caused by wind speed changes associated with the front. Changes in the drag coefficient due to changes in surface roughness and stability are much less important.Mean budgets for temperature and total water indicate that there is a balance between horizontal advection and turbulent flux divergence. The U momentum budget shows that once the geostrophic balance terms are subtracted, the balance is mainly between the pressure gradient force associated with the induced temperature field and turbulent friction, with horizontal advection and the Coriolis force acting on the geostrophic departure playing minor roles. The V momentum budget shows a balance between horizontal advection, Coriolis force and friction.Although there are few data for comparison, the results are in qualitative agreement with observations in the area. This study shows that the s.s.t. front at the Gulf Stream edge produces marked local changes in the nearby atmospheric surface layer. 29
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. Significance Statement This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.