Modeling a large submillimeter-wave observatory

The 25 meter aperture Cornell Caltech Atacama Telescope (CCAT) will provide an enormous increase in sensitivity in the submillimeter bands compared to existing observatories, provided it can establish and maintain excellent image quality. To accomplish this at a very low cost, it is necessary to conduct accurate engineering trades, including the most effective segment and wavefront sensing and control approach, to determine the best method for continuously maintaining wavefront quality in the operational environment. We describe an integrated structural/optical/controls model that provides accurate performance prediction. We also detail the analysis methods used to quantify critical design trades

The Sundowner Winds Experiment (SWEX) pilot study: Understanding downslope windstorms in the Santa Ynez Mountains, Santa Barbara, California

Sundowner winds are downslope gusty winds often observed on the southern slopes of the Santa Ynez Mountains (SYM) in coastal Santa Barbara (SB), California. They typically peak near sunset and exhibit characteristics of downslope windstorms through the evening. They are SB\u27s most critical fire weather in all seasons and represent a major hazard for aviation. The Sundowner Winds Experiment Pilot Study was designed to evaluate vertical profiles of winds, temperature, humidity, and stability leeward of the SYM during a Sundowner event. This was accomplished by launching 3-hourly radiosondes during a significant Sundowner event on 28-29 April 2018. This study showed that winds in the lee of the SYM exhibit complex spatial and temporal patterns. Vertical profiles showed a transition from humid onshore winds from morning to mid-afternoon to very pronounced offshore winds during the evening after sunset. These winds accompanied mountain waves and a northerly nocturnal lee jet with variable temporal behavior. Around sunset, the jet was characterized by strong wind speeds enhanced by mountain-wave breaking. Winds weakened considerably at 2300 PDT 29 April but enhanced dramatically at 0200 PDT 29 April at much lower elevations. These transitions were accompanied by changes in stability profiles and in the Richardson number. A simulation with the Weather Research and Forecasting (WRF) Model at 1-km grid spacing was examined to evaluate the skill of the model in capturing the observed winds and stability profiles and to assess mesoscale processes associated with this event. These results advanced understanding on Sundowner\u27s spatiotemporal characteristics and driving mechanisms

The breakthrough listen search for intelligent life: a wideband data recorder system for the Robert C. Byrd green bank telescope

The Breakthrough Listen Initiative is undertaking a comprehensive search for radio and optical signatures from extraterrestrial civilizations. An integral component of the project is the design and implementation of wide-bandwidth data recorder and signal processing systems. The capabilities of these systems, particularly at radio frequencies, directly determine survey speed; further, given a fixed observing time and spectral coverage, they determine sensitivity as well. Here, we detail the Breakthrough Listen wide-bandwidth data recording system deployed at the 100-m aperture Robert C. Byrd Green Bank Telescope. The system digitizes up to 6 GHz of bandwidth at 8 bits for both polarizations, storing the resultant 24 GB/s of data to disk. This system is among the highest data rate baseband recording systems in use in radio astronomy. A future system expansion will double recording capacity, to achieve a total Nyquist bandwidth of 12 GHz in two polarizations. In this paper, we present details of the system architecture, along with salient configuration and disk-write optimizations used to achieve high-throughput data capture on commodity compute servers and consumer-class hard disk drives

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

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 multimodel ensemble forecast that combined predictions from dozens of 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-wk horizon three to five times larger than when predicting at a 1-wk 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

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Modeling a Large Submillimeter-Wave Observatory Modeling a Large Submillimeter-Wave Observatory

Abstract The 25 meter aperture Cornell Caltech Atacama Telescope (CCAT) will provide an enormous increase in sensitivity in the submillimeter bands compared to existing observatories, provided it can establish and maintain excellent image quality. To accomplish this at a very low cost, it is necessary to conduct accurate engineering trades, including the most effective segment and wavefront sensing and control approach, to determine the best method for continuously maintaining wavefront quality in the operational environment. We describe an integrated structural/optical/controls model that provides accurate performance prediction. We also detail the analysis methods used to quantify critical design trades

Modeling a Large Submillimeter-Wave Observatory

The 25 meter aperture Cornell Caltech Atacama Telescope (CCAT) will provide an enormous increase in sensitivity in the submillimeter bands compared to existing observatories, provided it can establish and maintain excellent image quality. To accomplish this at a very low cost, it is necessary to conduct accurate engineering trades, including the most effective segment and wavefront sensing and control approach, to determine the best method for continuously maintaining wavefront quality in the operational environment. We describe an integrated structural/optical/controls model that provides accurate performance prediction. We also detail the analysis methods used to quantify critical design trades