scholarly journals Impact of Gulfstream-IV Dropsondes on Tropical Cyclone Prediction in a Regional OSSE System

2019 ◽  
Vol 147 (8) ◽  
pp. 2961-2977 ◽  
Author(s):  
Kelly Ryan ◽  
Lisa Bucci ◽  
Javier Delgado ◽  
Robert Atlas ◽  
Shirley Murillo

Abstract Aircraft reconnaissance missions remain the primary means of collecting direct measurements of marine atmospheric conditions affecting tropical cyclone formation and evolution. The National Hurricane Center tasks the NOAA G-IV aircraft to sample environmental conditions that may impact the development of a tropical cyclone threatening to make landfall in the United States or its territories. These aircraft data are assimilated into deterministic models and used to produce real-time analyses and forecasts for a given tropical cyclone. Existing targeting techniques aim to optimize the use of reconnaissance observations and partially rely on regions of highest uncertainty in the Global Ensemble Forecast System. Evaluating the potential impact of various trade-offs in the targeting process is valuable for determining the ideal aircraft flight track for a prospective mission. AOML’s Hurricane Research Division has developed a system for performing regional observing system simulation experiments (OSSEs) to assess the potential impact of proposed observing systems on hurricane track and intensity forecasting. This study focuses on improving existing targeting methods by investigating the impact of proposed aircraft observing system designs through various sensitivity studies. G-IV dropsonde retrievals were simulated from a regional nature run, covering the life cycle of a rapidly intensifying Atlantic hurricane. Results from sensitivity studies provide insight into improvements for real-time operational synoptic surveillance targeting for hurricanes and tropical storms, where dropsondes released closer to the vortex–environment interface provide the largest impact on the track forecast. All dropsonde configurations provide a positive 2-day impact on intensity forecasts by improving the environmental conditions known to impact tropical cyclone intensity.

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e043863
Author(s):  
Jingyuan Wang ◽  
Ke Tang ◽  
Kai Feng ◽  
Xin Lin ◽  
Weifeng Lv ◽  
...  

ObjectivesWe aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status and human mobility status.DesignA retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted.SettingWe use the data for COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily confirmed cases for 1005 US counties.ParticipantsA total of 69 498 cases in China and 740 843 cases in the USA are used for calculating the effective reproductive numbers.Primary outcome measuresRegression analysis of the impact of temperature and relative humidity on the effective reproductive number (R value).ResultsStatistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number (R value) in both China and the USA.ConclusionsHigher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an increase in temperature by 1°C is associated with a reduction in the R value of COVID-19 by 0.026 (95% CI (−0.0395 to −0.0125)) in China and by 0.020 (95% CI (−0.0311 to −0.0096)) in the USA; an increase in relative humidity by 1% is associated with a reduction in the R value by 0.0076 (95% CI (−0.0108 to −0.0045)) in China and by 0.0080 (95% CI (−0.0150 to −0.0010)) in the USA. Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic.


2020 ◽  
Vol 222 (7) ◽  
pp. 1138-1144 ◽  
Author(s):  
Sarah M Bartsch ◽  
Elizabeth A Mitgang ◽  
Gail Geller ◽  
Sarah N Cox ◽  
Kelly J O’Shea ◽  
...  

Abstract Background The protection that an influenza vaccine offers can vary significantly from person to person due to differences in immune systems, body types, and other factors. The question, then, is what is the value of efforts to reduce this variability such as making vaccines more personalized and tailored to individuals. Methods We developed a compartment model of the United States to simulate different influenza seasons and the impact of reducing the variability in responses to the influenza vaccine across the population. Results Going from a vaccine that varied in efficacy (0–30%) to one that had a uniform 30% efficacy for everyone averted 16.0–31.2 million cases, $1.9–$3.6 billion in direct medical costs, and $16.1–$42.7 billion in productivity losses. Going from 0–50% in efficacy to just 50% for everyone averted 27.7–38.6 million cases, $3.3–$4.6 billion in direct medical costs, and $28.8–$57.4 billion in productivity losses. Going from 0–70% to 70% averted 33.6–54.1 million cases, $4.0–$6.5 billion in direct medical costs, and $44.8–$64.7 billion in productivity losses. Conclusions This study quantifies for policy makers, funders, and vaccine developers and manufacturers the potential impact of efforts to reduce variability in the protection that influenza vaccines offer (eg, developing vaccines that are more personalized to different individual factors).


2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  

Abstract Digital health has revolutionised healthcare, with implications for understanding public reaction to health emergencies and interventions. Social media provides a space where like-minded people can share interests and concerns in real-time, regardless of their location. This can be a force for good, as platforms like Twitter can spread correct information about outbreaks, for example in the 2009 swine flu pandemic. However, social media can also disseminate incorrect information or deliberately spread misinformation leading to adverse public health sentiment and outcomes. The current issues around trust in vaccines is the best-known example. Vaccine hesitancy, traditionally linked to issues of trust, misinformation and prior beliefs, has been increasingly fueled by influential groups on social media and the Internet. Ultimately, anti-vaccination movements have the potential to lead to outbreaks of vaccine-preventable diseases, especially if refusal is concentrated locally, creating vulnerable populations. For example, 2018-19 saw a large increase in incidence of measles in the US and Europe (where cases tripled from 2017), two regions where the disease was already or almost eliminated. In 2019, the World Health Organisation listed anti-vaccination movements as one of the top 10 threats to global public health. HPV vaccination is another example of the impact of anti-vaccination movements. As viral videos originating on YouTube spread across social networks, uptake has tumbled in a number of countries, with Japan, Denmark, Colombia and Ireland being badly hit. In Japan, the government came under sufficient pressure that they de-recommended HPV vaccine, seeing an 80% uptake rate fall below 1% in 2014. There have been reports of successful interventions by national governments. A recent campaign run by the HPV Alliance (a coalition of some 35 private companies, charities and public institutions) in Ireland has seen rates below 40% back up to a national average of 75%. A combination of hard-hitting personal testimonials, social media and traditional media promoted the HPV vaccine. Despite this, systematic engagement and supranational strategies are still in the early stages of being formulated. As misleading information spread through social media and digital networks has undesirable impact on attitudes to vaccination (and uptake rates), urgent actions are required. Analysis and visualisation techniques mining data streams from social media platforms, such as Twitter, Youtube enable real-time understanding of vaccine sentiments and information flows. Through identification of key influencers and flashpoints in articles about vaccination going viral, targeted public health responses could be developed. This roundtable discussion will showcase different ways in which media and social networks, accessible in real-time provide an opportunity for detecting a change in public confidence in vaccines, for identifying users and rumors and for assessing potential impact in order to know how to best respond. Key messages Social media has significantly enhanced our understanding of anti-vaccination movements and potential impact on public health attitudes and behaviors regarding vaccination. Innovative methods of analysing social media data, from digital health, data science and computer science, have an important role in developing health promotions to counter anti-vaccination movements.


2007 ◽  
Vol 22 (6) ◽  
pp. 1157-1176 ◽  
Author(s):  
Chun-Chieh Wu ◽  
Kun-Hsuan Chou ◽  
Po-Hsiung Lin ◽  
Sim D. Aberson ◽  
Melinda S. Peng ◽  
...  

Abstract Starting from 2003, a new typhoon surveillance program, Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR), was launched. During 2004, 10 missions for eight typhoons were conducted successfully with 155 dropwindsondes deployed. In this study, the impact of these dropwindsonde data on tropical cyclone track forecasts has been evaluated with five models (four operational and one research models). All models, except the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model, show the positive impact that the dropwindsonde data have on tropical cyclone track forecasts. During the first 72 h, the mean track error reductions in the National Centers for Environmental Prediction’s (NCEP) Global Forecast System (GFS), the Navy Operational Global Atmospheric Prediction System (NOGAPS) of the Fleet Numerical Meteorology and Oceanography Center (FNMOC), and the Japanese Meteorological Agency (JMA) Global Spectral Model (GSM) are 14%, 14%, and 19%, respectively. The track error reduction in the Weather Research and Forecasting (WRF) model, in which the initial conditions are directly interpolated from the operational GFS forecast, is 16%. However, the mean track improvement in the GFDL model is a statistically insignificant 3%. The 72-h-average track error reduction from the ensemble mean of the above three global models is 22%, which is consistent with the track forecast improvement in Atlantic tropical cyclones from surveillance missions. In all, despite the fact that the impact of the dropwindsonde data is not statistically significant due to the limited number of DOTSTAR cases in 2004, the overall added value of the dropwindsonde data in improving typhoon track forecasts over the western North Pacific is encouraging. Further progress in the targeted observations of the dropwindsonde surveillances and satellite data, and in the modeling and data assimilation system, is expected to lead to even greater improvement in tropical cyclone track forecasts.


2007 ◽  
Vol 135 (7) ◽  
pp. 2506-2524 ◽  
Author(s):  
Philippe Lopez ◽  
Peter Bauer

Abstract The one- plus four-dimensional variational data assimilation (“1D+4DVAR”) method currently run in operations at ECMWF with rain-affected radiances from the Special Sensor Microwave Imager is used to study the potential impact of assimilating NCEP stage-IV analyses of hourly accumulated surface precipitation over the U.S. mainland. These data are a combination of rain gauge measurements and observations from the high-resolution Doppler Next-Generation Weather Radars. Several 1D+4DVAR experiments have been run over a month in spring 2005. First, the quality of the precipitation forecasts in the control experiment is assessed. Then, it is shown that the impact of the assimilation of the additional rain observations on global scores of dynamical fields and temperature is rather neutral, while precipitation scores are improved for forecast ranges up to 12 h. Additional 1D+4DVAR experiments in which all moisture-affected observations are removed over the United States demonstrate that the NCEP stage-IV precipitation data on their own can clearly be beneficial to the analyses and subsequent forecasts of the moisture field. This result suggests that the potential impact of precipitation observations is overshadowed by the influence of other high-quality humidity observations, in particular, radiosondes. It also confirms that the assimilation of precipitation observations has the ability to improve the quality of moisture analyses and forecasts in data-sparse regions. Finally, the limitations inherent in the current assimilation of precipitation data, their implications for the future, and possible ways of improvement are discussed.


2015 ◽  
Vol 143 (10) ◽  
pp. 4012-4037 ◽  
Author(s):  
Colin M. Zarzycki ◽  
Christiane Jablonowski

Abstract Tropical cyclone (TC) forecasts at 14-km horizontal resolution (0.125°) are completed using variable-resolution (V-R) grids within the Community Atmosphere Model (CAM). Forecasts are integrated twice daily from 1 August to 31 October for both 2012 and 2013, with a high-resolution nest centered over the North Atlantic and eastern Pacific Ocean basins. Using the CAM version 5 (CAM5) physical parameterization package, regional refinement is shown to significantly increase TC track forecast skill relative to unrefined grids (55 km, 0.5°). For typical TC forecast integration periods (approximately 1 week), V-R forecasts are able to nearly identically reproduce the flow field of a globally uniform high-resolution forecast. Simulated intensity is generally too strong for forecasts beyond 72 h. This intensity bias is robust regardless of whether the forecast is forced with observed or climatological sea surface temperatures and is not significantly mitigated in a suite of sensitivity simulations aimed at investigating the impact of model time step and CAM’s deep convection parameterization. Replacing components of the default physics with Cloud Layers Unified by Binormals (CLUBB) produces a statistically significant improvement in forecast intensity at longer lead times, although significant structural differences in forecasted TCs exist. CAM forecasts the recurvature of Hurricane Sandy into the northeastern United States 60 h earlier than the Global Forecast System (GFS) model using identical initial conditions, demonstrating the sensitivity of TC forecasts to model configuration. Computational costs associated with V-R simulations are dramatically decreased relative to globally uniform high-resolution simulations, demonstrating that variable-resolution techniques are a promising tool for future numerical weather prediction applications.


2013 ◽  
Vol 94 (6) ◽  
pp. 859-882 ◽  
Author(s):  
Robert Rogers ◽  
Sim Aberson ◽  
Altug Aksoy ◽  
Bachir Annane ◽  
Michael Black ◽  
...  

An update of the progress achieved as part of the NOAA Intensity Forecasting Experiment (IFEX) is provided. Included is a brief summary of the noteworthy aircraft missions flown in the years since 2005, the first year IFEX flights occurred, as well as a description of the research and development activities that directly address the three primary IFEX goals: 1) collect observations that span the tropical cyclone (TC) life cycle in a variety of environments for model initialization and evaluation; 2) develop and refine measurement strategies and technologies that provide improved real-time monitoring of TC intensity, structure, and environment; and 3) improve the understanding of physical processes important in intensity change for a TC at all stages of its life cycle. Such activities include the real-time analysis and transmission of Doppler radar measurements; numerical model and data assimilation advancements; characterization of tropical cyclone composite structure across multiple scales, from vortex scale to turbulence scale; improvements in statistical prediction of rapid intensification; and studies specifically targeting tropical cyclogenesis, extratropical transition, and the impact of environmental humidity on TC structure and evolution. While progress in TC intensity forecasting remains challenging, the activities described here provide some hope for improvement.


2000 ◽  
Vol 10 (3) ◽  
pp. 562-564 ◽  
Author(s):  
Steven McKay

Recent interest in expanding commercial currant and gooseberry (Ribes L.) plantings in the United States has put pressure on the states with Ribes restrictions to review their regulations. A meeting on 9 January 1998 initiated discussion between the state agriculture regulatory agencies, forest pathologists, and horticulturists. Since then a white pine blister rust (WPBR), Cronartium ribicola J.C. Fischer) World Wide Web (Web) site (McKay, 1998) and list serve have been activated to facilitate communication. Vermont is a state that has no regulations on the books at this time. Connecticut and New York also have mentioned that infection rates are low. Maine retains a Ribes reduction program, and Massachusetts is strictly enforcing their regulations. The following summarizes the general consensus among the majority of regulating states: 1) It is desirable to find a way for both white pines (Pinus L.) and commercial Ribes plantings to coexist. 2) More research is needed to survey existing Ribes and pines, the potential impact of commercial plantings versus the impact of existing Ribes, and the potential impact of escape /volunteer seedlings from immune Ribes cultivars. 3) There is interest in permitting immune Ribes cultivars to be planted. 4) There is interest in having consistency in regulations from state to state.


1982 ◽  
Vol 26 (1) ◽  
pp. 44-48
Author(s):  
Mark S. Hoffman

A study as conducted to assess the impact of the International regulations on throughput in retail checkout workstations using “state-of-the-art” POS (Point Of Sale) equipment. Productivity measures were derived for the various workstation configurations recommended in the German guidelines as well as those designed from empirical sources. A cross-validation of these data to performances from domestic workstations was made to assess the potential impact of similar ergonomic standardization in the United States.


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