Ultra-Stable and Durable Piezoelectric Nanogenerator with All-Weather Service Capability Based on N Doped 4H-SiC Nanohole Arrays

Ultra-stable piezoelectric nanogenerator (PENG) driven by environmental actuation sources with all-weather service capability is highly desirable. Here, the PENG based on N doped 4H-SiC nanohole arrays (NHAs) is proposed to harvest ambient energy under low/high temperature and relative humidity (RH) conditions. Finite element method simulation of N doped 4H-SiC NHAs in compression mode is developed to evaluate the relationship between nanohole diameter and piezoelectric performance. The density of short circuit current of the assembled PENG reaches 313 nA cm−2, which is 1.57 times the output of PENG based on N doped 4H-SiC nanowire arrays. The enhancement can be attributed to the existence of nanohole sidewalls in NHAs. All-weather service capability of the PENG is verified after being treated at -80/80 ℃ and 0%/100% RH for 50 days. The PENG is promising to be widely used in practice worldwide to harvest biomechanical energy and mechanical energy.

Road Weather Monitoring System Shows High Cost-Effectiveness in Mitigating Malfunction Losses

Understanding the environmental impacts of road networks and the success of policy initiatives is crucial to a country’s socioeconomic development. In this study, we propose a comprehensive approach to quantitatively assessing whether a given response is effective in mitigating the impacts of environmental shocks on roads. Our approach includes factor analysis, direct and indirect loss quantification, and cost-benefit analysis. Using nationwide data on road malfunctions and weather service performance in China, we found that the macro-level indirect economic losses from road malfunctions were more than the direct losses in multiples ranging from 11 to 21, and that information provided by the weather service could reduce losses, with benefits exceeding costs by a ratio of 51. The results of our study provide a quantitative tool as well as evidence of the effectiveness of sustainability investment, which should provide guidance for future disaster mitigation, infrastructure system resilience, and sustainability-building policy-making.

Impact Based Forecast analysis uses multi-model ensemble data and National Digital Forecast data in ArcMap 10.8.1

The number of people seeking public weather service information is growing, making it a challenge for all bureaus of meteorology around the world. Although, in the last decade, routine public weather service information has brought excellent weather forecast information for people and services to people with rapid, accurate, widely available, and easy to grasp information, which they may get in a variety of places, such as a website or an application. However, in this decade and in the future, it will not be enough. People want information such as what the impact should be and how people react to that impact, which should be displayed on a static Geographic Information System (GIS) map in a standard format. We will investigate and create an IBF map based on multi-model ensemble data and National Digital Forecast (NDF) data in this work. Then, using the GIS software ArcMap 10.8.1, we rank and score the geographic disaster data to determine the impact area. To create the effect area, we will employ primary and advanced methods of ArcMap 10.8.1. The information on the IBF map will be immediately understood by stakeholders and users.

ORFEES - a radio spectrograph for the study of solar radio bursts and space weather applications

Radio bursts are sensitive tracers of non-thermal electron populations in the solar corona. They are produced by electron beams and shock waves propagating through the corona and the Heliosphere, and by trapped electron populations in coronal mass ejections (CMEs) and in quiescent active regions. Combining space borne and ground-based radio spectrographs allows one to track disturbances all the way between the low corona, near or at the sites of particle acceleration, and the spacecraft. Radio observations are therefore a significant tool in probing the solar origin of heliospheric disturbances, which is a central research topic as witnessed by the Parker Solar Probe and Solar Orbiter missions. The full scientific return of these projects needs vigorous ground-based support, which at radio wavelengths covers altitudes up to about a solar radius above the photosphere. Besides research in solar and heliospheric physics, monitoring solar radio bursts also supports space weather services. On occasion radio bursts can themselves be a space weather hazard. The Nan\c{c}ay radio astronomy station in central France has a long tradition of monitoring radio emission at decimetre-to-metre wavelengths. This article describes the radio spectrograph ORFEES ({\it Observations Radiospectrographiques pour FEDOME et l'Etude des Eruptions Solaires}). It observes the whole-Sun flux density between 144 and 1004 MHz, which pertains to regions between the low corona and about half a solar radius above the photosphere. ORFEES is the result of a partnership between Observatoire de Paris and the French Air Force, which operates the experimental space weather service FEDOME. The primary use of the instrument at Paris Observatory is the astrophysical observation. Low-resolution data with rapid availability are presently produced for the French Air Force. Similar information can be made available to a broader range of space-weather service providers. This article gives an overview of the instrument design and the access to the data, and shows a few illustrative observations.

An Analysis of 2016-2018 Tornadoes and National Weather Service Tornado Warnings across the contiguous United States

Previous work has considered tornado occurrence with respect to radar data, both WSR-88D and mobile research radars, and a few studies have examined techniques to potentially improve tornado warning performance. To date, though, there has been little work focusing on systematic, large-sample evaluation of National Weather Service (NWS) tornado warnings with respect to radar-observable quantities and the near-storm environment. In this work, three full years (2016–2018) of NWS tornado warnings across the contiguous United States were examined, in conjunction with supporting data in the few minutes preceding warning issuance, or tornado formation in the case of missed events. The investigation herein examines WSR-88D and Storm Prediction Center (SPC) mesoanalysis data associated with these tornado warnings with comparisons made to the current Warning Decision Training Division (WDTD) guidance.Combining low-level rotational velocity and the significant tornado parameter (STP), as used in prior work, shows promise as a means to estimate tornado warning performance, as well as relative changes in performance as criteria thresholds vary. For example, low-level rotational velocity peaking in excess of 30 kt (15 m s−1), in a near-storm environment which is not prohibitive for tornadoes (STP > 0), results in an increased probability of detection and reduced false alarms compared to observed NWS tornado warning metrics. Tornado warning false alarms can also be reduced through limiting warnings with weak (<30 kt), broad (>1nm) circulations in a poor (STP=0) environment, careful elimination of velocity data artifacts like sidelobe contamination, and through greater scrutiny of human-based tornado reports in otherwise questionable scenarios.

Sino-Russian Space Weather Effort for Global Air Navigation Safety

This paper covers the role of the China-Russia Consortium in Global Air Navigation Safety, how space weather centers for aviation were established and how are they regulated. We briefly introduce the effects of space weather on aviation in general. A short description of the ICAO-designated space weather service fol-lows. The China-Russia Consortium history, members and the way it integrates into the global service are described afterwards.

National Weather Service Data Needs for Short-Term Forecasts and the Role of Unmanned Aircraft in Filling the Gap: Results from a Nationwide Survey

Inclusion of unmanned aircraft systems (UAS) into the weather surveillance network has the potential to improve short-term (< 1 day) weather forecasts through direct integration of UAS-collected data into the forecast process and assimilation into numerical weather prediction models. However, one of the primary means by which the value of any new sensing platform can be assessed is through consultation with principal stakeholders. National Weather Service (NWS) forecasters are principal stakeholders responsible for the issuance of short-term forecasts. The purpose of the work presented here is to use results from a survey of 630 NWS forecasters to assess critical data gaps that impact short-term forecast accuracy, and explore the potential role of UAS in filling these gaps.NWS forecasters view winter precipitation, icing, flood, lake-effect/enhanced snow, turbulence, and waves as the phenomena principally impacted by data gaps. Of the ten high-priority weather-related characteristics that need to be observed to fill critical data gaps, seven are either measures of precipitation or related to precipitation-producing phenomena. The three most important UAS capabilities/characteristics required for useful data for weather forecasting are real- or near-real-time data, the ability to integrate UAS data with additional data gathered by other systems, and UASs equipped with cameras to verify forecasts and monitor weather. Of the three operation modes offered for forecasters to consider, targeted surveillance is considered to be the most important compared to fixed site profiling or transects between fixed sites.