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"Meteorological services"
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Bridging the gap: how to adopt opportunistic plant observations for phenology monitoring
Plant phenology plays a vital role in assessing climate change. To monitor this, individual plants are traditionally visited and observed by trained volunteers organized in national or international networks - in Germany, for example, by the German Weather Service, DWD. However, their number of observers is continuously decreasing. In this study, we explore the feasibility of using opportunistically captured plant observations, collected via the plant identification app Flora Incognita to determine the onset of flowering and, based on that, create interpolation maps comparable to those of the DWD. Therefore, the opportunistic observations of 17 species collected in 2020 and 2021 were assigned to “Flora Incognita stations” based on location and altitude in order to mimic the network of stations forming the data basis for the interpolation conducted by the DWD. From the distribution of observations, the percentile representing onset of flowering date was calculated using a parametric bootstrapping approach and then interpolated following the same process as applied by the DWD. Our results show that for frequently observed, herbaceous and conspicuous species, the patterns of onset of flowering were similar and comparable between both data sources. We argue that a prominent flowering stage is crucial for accurately determining the onset of flowering from opportunistic plant observations, and we discuss additional factors, such as species distribution, location bias and societal events contributing to the differences among species and phenology data. In conclusion, our study demonstrates that the phenological monitoring of certain species can benefit from incorporating opportunistic plant observations. Furthermore, we highlight the potential to expand the taxonomic range of monitored species for phenological stage assessment through opportunistic plant observation data.
Journal Article
A Comprehensive Review of Advances in Civil Aviation Meteorological Services
This paper provides a comprehensive review of the development history, current status, and future trends of civil aviation meteorological services. With the rapid growth of global air traffic and the increasing complexity of operational environments, accurate and timely meteorological information has become indispensable for ensuring the efficiency and safety of civil aviation operations. Extreme weather events, in particular, have repeatedly demonstrated their potential to disrupt flight schedules, compromise passenger safety, and incur substantial economic losses, underscoring the critical need for robust meteorological service systems in the aviation sector. Against this backdrop, this paper first introduces the importance of civil aviation meteorological services in ensuring flight safety, improving flight regularity, and reducing operational costs. The development process is then detailed, from early infrastructure construction to the current modern and intelligent development, covering the evolution of observation equipment, forecasting technologies, and service models. When analyzing the current status, the paper discusses challenges such as the difficulty of accurate forecasting under complex weather conditions and multi-departmental collaboration issues, as well as improvement measures and achievements. Finally, it determines future trends, including the application of new technologies, such as artificial intelligence (AI) and big data, the expansion of service scope, and the strengthening of international cooperation, aiming to provide references for further improving the level of civil aviation meteorological services.
Journal Article
Research and Application of Intelligent Weather Push Model Based on Travel Forecast and 5G Message
In the realm of daily activity planning, precise weather forecasting services hold paramount significance. However, the prevalent dissemination of weather forecasts through conventional channels like radio, television, and the internet often yields only generalized regional predictions. This limitation contributes to diminished forecast reach, inadequate accuracy, and a lack of individualization, thwarting the effective distribution of meteorological insights and inhibiting the fulfillment of personalized forecast demands. Addressing these concerns, our study proposes a personalized weather forecasting approach that harnesses machine learning techniques and leverages the 5G messaging platform. By amalgamating projected user travel data, we augment personalized weather reports and extend user coverage to achieve tailored, timely, and high-quality weather services. Concretely, our research commences with an extensive analysis of large-scale user travel behavior data to extract pertinent travel attributes. Subsequently, we construct a user’s future location prediction model—dubbed the Loc-PredModel—by employing the Extreme Gradient Boosting (XGBoost) algorithm to forecast users’ trip destinations and arrival times. Anchored in the anticipated outcomes of user travel behavior, personalized weather data reports are formulated. Experimental results underscore the Loc-PredModel’s remarkable predictive prowess, demonstrating a root mean squared error (RMSE) value of 0.208 and a coefficient of determination (R2) value of 0.935, affirming its efficacy in prognosticating users’ trip destinations and arrival times. Furthermore, our 5G message-driven platform, rooted in intelligent personalized meteorological services, underwent testing within Chengdu city and garnered positive user feedback. Our research effectively surmounts the limitations of conventional weather forecasting platforms by furnishing users with more precise and customized weather information predicated on behavioral analysis and the 5G information ecosystem. This study not only advances the theoretical groundwork of intelligent meteorology but also offers invaluable insights and guidance for future advancement. By providing users with a more personalized and timely intelligent meteorological service experience, our approach exhibits transferability, with the research methodology and model potentially extendable nationwide or even on a larger scale beyond the study’s Chengdu-based scope.
Journal Article
A Concept for Multi-Criteria Environmental Assessment of Aircraft Trajectories
Comprehensive assessment of the environmental aspects of flight movements is of increasing interest to the aviation sector as a potential input for developing sustainable aviation strategies that consider climate impact, air quality and noise issues simultaneously. However, comprehensive assessments of all three environmental aspects do not yet exist and are in particular not yet operational practice in flight planning. The purpose of this study is to present a methodology which allows to establish a multi-criteria environmental impact assessment directly in the flight planning process. The method expands a concept developed for climate optimisation of aircraft trajectories, by representing additionally air quality and noise impacts as additional criteria or dimensions, together with climate impact of aircraft trajectory. We present the mathematical framework for environmental assessment and optimisation of aircraft trajectories. In that context we present ideas on future implementation of such advanced meteorological services into air traffic management and trajectory planning by relying on environmental change functions (ECFs). These ECFs represent environmental impact due to changes in air quality, noise and climate impact. In a case study for Europe prototype ECFs are implemented and a performance assessment of aircraft trajectories is performed for a one-day traffic sample. For a single flight fuel-optimal versus climate-optimized trajectory solution is evaluated using prototypic ECFs and identifying mitigation potential. The ultimate goal of such a concept is to make available a comprehensive assessment framework for environmental performance of aircraft operations, by providing key performance indicators on climate impact, air quality and noise, as well as a tool for environmental optimisation of aircraft trajectories. This framework would allow studying and characterising changes in traffic flows due to environmental optimisation, as well as studying trade-offs between distinct strategic measures.
Journal Article
Evaluation of the Direct Economic Value of Typhoon Forecasting for Taiwan’s Agriculture—A Case Study on Farmers’ Decision-Making Behavior
In recent years, extreme weather events have become more frequent and severe, making it crucial to apply meteorological and climate information services to mitigate the associated losses. However, given limited resources, it is essential to assess the potential value these services can generate while considering uncertainties. Since the impact of disasters and weather prediction accuracy is uncertain, and end-users’ decisions of disaster prevention, resource allocation, and operational planning are costly, the expected returns of acting according to weather forecasting information need to outweigh the cost to make decision-makers act. This study evaluates the direct economic value of meteorological information services for agricultural disaster prevention, with a focus on typhoon preparedness, using the cost-loss model. The results show that the current annual economic value of these services is NTD 77.28 million. Significant benefits can be gained by increasing the proportion of avoidable losses and improving forecast accuracy. A 10% increase in the proportion of avoidable losses, possibly due to the application of innovative technology and the extension of leading time, results in an 8% rise in economic value, while a 50% increase leads to a 38% increase. Moreover, enhancing the forecast accuracy, which is currently at 73.18%, by an additional 50% could boost economic value by up to 34%. From a practical perspective, unless agricultural output is completely protected from weather events (such as indoor horticultural crops), the potential for reducing avoidable losses remains limited. Consequently, the findings underscore the importance of government efforts to promote the establishment of additional weather observation stations in order to improve forecast accuracy, boost farmers’ confidence of application from public meteorological information services, and maximize the impact of meteorological services in reducing agricultural losses and enhancing disaster preparedness.
Journal Article
Economic Assessment of Meteorological Information Services for Capture Fisheries in Taiwan
This study evaluates the economic benefits of meteorological information services (MISs) provided by the Central Weather Administration (CWA) in Taiwan, specifically for Taiwan’s capture fishery industry. Using the contingent valuation method (CVM) and conducting in-person interviews, we collected questionnaires from capture fishery practitioners nationwide to gather their subjective evaluations of the meteorological information services provided by the CWA. Based on these evaluations, we further investigated the respondents’ willingness to pay (WTP) for the CWA’s meteorological information services. An empirical analysis of the bid function was conducted to identify the key factors influencing the respondents’ bidding behavior. The empirical findings indicate that the primary factors affecting bids include subjective perceptions (such as forecast accuracy ratings and the ratings of the impacts on fishing production), working location, fishing vessel tonnage, and fishing methods. The median WTP for Taiwanese capture fishery practitioners is Taiwan dollar (TWD) 2111.12 per person per year. Based on the number of capture fishery practitioners in Taiwan in 2019, the total annual economic value of applying MIS in coastal and offshore fisheries is estimated to be between TWD 376 million and TWD 496 million per year.
Journal Article
Analysis of Meteorological Service Effect of a Low-cloud and Low-visibility Weather Process at Shanghai’s two Airports
The emergence of low-cloud and low-visibility can affect air activities, and bring huge economic losses to airlines. Based on the aviation meteorological observation, forecast and airport alert of Pudong and Hongqiao airports, this paper analyses the meteorological service effect of a low-cloud and low-visibility weather process in Shanghai from January 27th to 28th, 2016. The results show that: (1) The absolute error between forecast and actual situation of Pudong and Hongqiao airport presents an obvious normal distribution and the forecast accuracy of Pudong is higher than that of Hongqiao. (2) For the airport with cloud ceiling of 30m∼60m and prevailing visibility of 600m∼800m, the alert of Pudong airport is more accurate and advanced, but for the airport with cloud height of less than 30m and prevailing visibility of 400m∼600m, the airport alert is quite different from the actual situation, and lacks lead time. (3) The alert of Hongqiao airport is accurate for the airport with visibility less than 800m from 03:30 to 10:30 on 28th, and the lead time is relatively high. However, it lacks the lead time for the airport with prevailing visibility greater than 1000m at 11:00 on 28th.
Journal Article
Observing weather and climate from the ground up
Detailed weather observations on local and regional levels are essential to a range of needs from forecasting tornadoes to making decisions that affect energy security, public health and safety, transportation, agriculture and all of our economic interests. As technological capabilities have become increasingly affordable, businesses, state and local governments, and individual weather enthusiasts have set up observing systems throughout the United States. However, because there is no national network tying many of these systems together, data collection methods are inconsistent and public accessibility is limited. This book identifies short-term and long-term goals for federal government sponsors and other public and private partners in establishing a coordinated nationwide \"network of networks\" of weather and climate observations.
eBook
UNLOCKING PRE-1850 INSTRUMENTAL METEOROLOGICAL RECORDS
Instrumental meteorological measurements from periods prior to the start of national weather services are designated “early instrumental data.” They have played an important role in climate research as they allow daily to decadal variability and changes of temperature, pressure, and precipitation, including extremes, to be addressed. Early instrumental data can also help place twenty-first century climatic changes into a historical context such as defining preindustrial climate and its variability. Until recently, the focus was on long, high-quality series, while the large number of shorter series (which together also cover long periods) received little to no attention. The shift in climate and climate impact research from mean climate characteristics toward weather variability and extremes, as well as the success of historical reanalyses that make use of short series, generates a need for locating and exploring further early instrumental measurements. However, information on early instrumental series has never been electronically compiled on a global scale. Here we attempt a worldwide compilation of metadata on early instrumental meteorological records prior to 1850 (1890 for Africa and the Arctic). Our global inventory comprises information on several thousand records, about half of which have not yet been digitized (not even as monthly means), and only approximately 20% of which have made it to global repositories. The inventory will help to prioritize data rescue efforts and can be used to analyze the potential feasibility of historical weather data products. The inventory will be maintained as a living document and is a first, critical, step toward the systematic rescue and reevaluation of these highly valuable early records. Additions to the inventory are welcome.
Journal Article