Meteorological Applications最新文献

{"title":"How dependent are quantitative volcanic ash concentration and along-flight dosage forecasts to model structural choices?","authors":"Lauren A. James,&nbsp;Helen F. Dacre,&nbsp;Natalie J. Harvey","doi":"10.1002/met.70003","DOIUrl":"https://doi.org/10.1002/met.70003","url":null,"abstract":"<p>Producing quantitative volcanic ash forecasts is challenging due to multiple sources of uncertainty. Careful consideration of this uncertainty is required to produce timely and robust hazard warnings. Structural uncertainty occurs when a model fails to produce accurate forecasts, despite good knowledge of the eruption source parameters, meteorological conditions and suitable parameterizations of transport and deposition processes. This uncertainty is frequently overlooked in forecasting practices. Using a Lagrangian particle dispersion model, simulations with varied output spatial resolution, temporal averaging period and particle release rate are performed to quantify the impact of these structural choices. This experiment reveals that, for the 2019 Raikoke eruption, structural choices give measurements of peak ash concentration spanning an order of magnitude, significantly impacting decision-relevant thresholds used in aviation flight planning. Conversely, along-flight dosage estimates exhibit less sensitivity to structural choices, suggesting it is a more robust metric to use in flight planning. Uncertainty can be reduced by eliminating structural choices that do not result in a favourable level of agreement with a high-resolution reference simulation. Reliable forecasts require output spatial resolution <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>≤</mo>\u0000 </mrow>\u0000 <annotation>$$ le $$</annotation>\u0000 </semantics></math> 80 km, temporal averaging periods <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>≤</mo>\u0000 </mrow>\u0000 <annotation>$$ le $$</annotation>\u0000 </semantics></math> 3 h and particle release rates <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>≥</mo>\u0000 </mrow>\u0000 <annotation>$$ ge $$</annotation>\u0000 </semantics></math> 5000 particles/h. This suggests that simulations with relatively small numbers of particles could be used to produce a large ensemble of simulations without significant loss of accuracy. Comparison with previous Raikoke simulations indicates that the uncertainty associated with these constrained structural choices is smaller than those associated with satellite constrained eruption source parameter and internal model parameter uncertainties. Thus, given suitable structural choices, other epistemic sources of uncertainty are likely to dominate. This insight is useful for the design of ensemble methodologies which are required to enable a shift from deterministic to probabilistic forecasting. The results are applicable to other long-range dispersion problems and to Eulerian dispersion models.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An asymmetric tropical cyclone rainfall model in the Northern Vietnam coast","authors":"Warinthorn Angkanasirikul,&nbsp;Wei Jian,&nbsp;Edmond Yat-Man Lo","doi":"10.1002/met.70004","DOIUrl":"https://doi.org/10.1002/met.70004","url":null,"abstract":"<p>Rainfall associated with landfalling tropical cyclones (TCs) along the Northern Vietnam coast is examined to develop an asymmetric parametric TC-induced rainfall model starting from the axisymmetric Rain-Climatology and Persistence (R-CLIPER) model. We recalibrated the R-CLIPER model (original R-CLIPER denoted as NHC) against observed rainfall patterns of 14 landfalling TCs from 2001 to 2021 in the Northern Vietnam coast, while relaxing the model's underlying linear relationships. The recalibrated R-CLIPER (denoted as Fit-Ax), still axisymmetric, suggests that some parameters are better correlated with the normalized maximum wind speed using logarithmic and exponential relationships. Fit-Ax reduces the 12-hr total rainfall overall root-mean-square errors (RMSEs) and Bias magnitudes in the before- and after-landfall periods from NHC for the entire 500-km TC domain. We further redistribute the Fit-Ax rainfall intensity across the four quadrants with respect to the TC forward motion to account for the observed large asymmetry in quadrant rainfall (version denoted as Fit-As). The vertical wind shear (VWS) and landfall (before or after) are considered in this redistribution. Fit-As generally outperforms Fit-Ax and NHC in reproducing the observed rainfall distribution for the 14 TCs. At the quadrant level, both Fit-Ax and Fit-As show significant improvement in Bias over NHC. Fit-As is further better overall in RMSE and Skill when weighted by quadrant rainfall volume. In pattern matching, Fit-As produces the best grid-averaged Pearson correlation coefficients for 11 TCs. In addition, its equitable threat scores (ETSs) are best beyond the 20-mm rainfall threshold, with the maximum of 0.299 at the 90-mm rainfall threshold. Thus, our locally fitted asymmetric rainfall model demonstrates improved capability in reproducing the historical TC-induced rainfall along the Northern Vietnam coast.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A preliminary observational study on the characteristics of surface turbulent fluxes over the South China Sea Islands","authors":"Qianjin Zhou,&nbsp;Lei Li,&nbsp;Pak Wai Chan,&nbsp;Zhongming Gao,&nbsp;Xiaodong Huang,&nbsp;Xiwen Ouyang,&nbsp;Shaojia Fan","doi":"10.1002/met.70006","DOIUrl":"https://doi.org/10.1002/met.70006","url":null,"abstract":"<p>In recent years, there has been a rise in human activities in oceanic areas, making the land–atmosphere interactions over islands a major scientific concern on a global scale. Examining the observation data from offshore areas enables a more comprehensive understanding of the turbulent fluxes in offshore atmospheric environments, patterns of momentum, energy and material exchange between the atmosphere and underlying surface in an oceanic boundary layer, and development of a heterogeneous atmospheric boundary layer. The related findings will assist in developing theoretical models and parameterization schemes to simulate the influence of heterogeneous surfaces on land–atmosphere interactions on the South China Sea Islands. Existing studies on the turbulent fluxes over the South China Sea Islands were mainly conducted on the Nansha Islands, whereas studies on the waters of the South China Sea are scarce. In this study, we used 10 Hz high-frequency turbulence measurements to calculate the latent and sensible heat fluxes over the South China Sea Islands using the eddy correlation method. These findings were then compared with data from the Dunhuang Gobi, Ordos desert, and Xilingol grassland regions in inland China, along with the observed net radiation and surface heat fluxes. The findings indicate that the energy fluxes over the South China Sea in summer exhibit prominent diurnal variations. The magnitude of either latent or soil heat flux is low, and the net radiation is predominantly transformed into sensible heat flux, which warms the atmosphere. Furthermore, the daily variation curves of sensible and latent heat fluxes are influenced by intermittent turbulence on the islands and reefs, resulting in a less smooth pattern compared with soil heat flux. Although the South China Sea Islands have small land areas and are surrounded by the sea, the land–atmosphere interactions over the underlying surface of this region are similar to those over the underlying surface of grasslands in inland China during summer. The daily mean sensible heat flux on the islands is higher than that in an inland area, and the time lag in its response to sunrise is longer than that in inland areas by approximately 1 h. The overall energy balance ratio is approximately 0.75, c which is in line with the average level, but an energy balance residual of approximately 25% still exists. Furthermore, extreme weather conditions, such as typhoons, can disrupt the diurnal variations of sensible and latent heat fluxes, and the cyclical patterns are subsequently restored.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.70006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of spatio-temporal patterns in extreme rainfall events in the Tropical Andes: A clustering analysis approach","authors":"Gabriela Urgilés,&nbsp;Rolando Célleri,&nbsp;Jörg Bendix,&nbsp;Johanna Orellana-Alvear","doi":"10.1002/met.70005","DOIUrl":"https://doi.org/10.1002/met.70005","url":null,"abstract":"<p>High spatio-temporal variability is a characteristic of extreme rainfall. In mountainous regions like the Tropical Andes, where intricate orography and mesoscale atmospheric dynamics greatly impact rainfall systems, this particularly holds for mountain areas like the Tropical Andes. Thus, the absence of operational rainfall monitoring networks with high spatio-temporal resolution has imposed difficulties for a proper analysis of extreme rainfall events in the Ecuadorian Andes. Nowhere, we present our improved knowledge on rainfall extremes based on newly available rainfall radar data of this region. In our study we employ a clustering approach to identify types of extreme rainfall events and analyze their spatio-temporal characteristics. Based on 3 years of data obtained from an X-band scanning weather radar data, the study was conducted in the southern Ecuadorian Tropical Andes at 4450 m a.s.l. By applying a rainfall threshold, 67 extreme rainfall events were selected. The rainfall characteristics of each extreme rainfall event, such as the amount of rain, its duration, its hour, and month of occurrence were determined and used as input variables of a k-means clustering analysis to group the events into different classes. The result revealed three main classes of extreme rainfall events. The first class is characterized by highest rain intensity and lowest duration. The second class is characterized by its month of occurrence, during the first 5 months of the year. The third class showed lowest rain intensity and highest duration mainly occurred at higher elevations. The typology of events advances our understanding of the spatio-temporal characteristics of extreme rainfall in the Tropical Andes.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drivers of sub-seasonal extreme rainfall and their representation in ECMWF forecasts during the Eastern African March-to-May seasons of 2018–2020","authors":"Masilin Gudoshava,&nbsp;Patricia Nyinguro,&nbsp;Joshua Talib,&nbsp;Caroline Wainwright,&nbsp;Anthony Mwanthi,&nbsp;Linda Hirons,&nbsp;Felipe de Andrade,&nbsp;Joseph Mutemi,&nbsp;Wilson Gitau,&nbsp;Elisabeth Thompson,&nbsp;Jemimah Gacheru,&nbsp;John Marsham,&nbsp;Hussen Seid Endris,&nbsp;Steven Woolnough,&nbsp;Zewdu Segele,&nbsp;Zachary Atheru,&nbsp;Guleid Artan","doi":"10.1002/met.70000","DOIUrl":"https://doi.org/10.1002/met.70000","url":null,"abstract":"<p>In recent years, Eastern Africa has been severely impacted by extreme climate events such as droughts and flooding. In a region where people's livelihoods are heavily dependent on climate conditions, extreme hydrometeorological events can exacerbate existing vulnerabilities. For example, suppressed rainfall during the March to May 2019 rainy season led to substantial food insecurity. In order to enhance preparedness against forecasted extreme events, it is critical to assess rainfall predictions and their known drivers in forecast models. In this study, we take a case study approach and evaluate drivers during March to May seasons of 2018, 2019 and 2020. We use observations, reanalysis and predictions from the European Centre for Medium-Range Weather Forecasts (ECMWF) to identify and evaluate rainfall drivers. Extreme rainfall during March to May 2018 and 2020 was associated with an active Madden–Julian Oscillation (MJO) in Phases 1–4, or/and a tropical cyclone to the east of Madagascar. On the other hand, the dry 2019 March to May MAM season, which included a delayed rainfall onset, was associated with tropical cyclones to the west of Madagascar. In general, whilst ECMWF forecasts correctly capture temporal variations in anomalous rainfall, they generally underestimate rainfall intensities. Further analysis shows that underestimated rainfall is linked to a weak forecasted MJO and errors in the location and intensity of tropical cyclones. Taking a case study approach motivates further study to determine the best application of our understanding of rainfall drivers. Communicated effectively, knowledge of rainfall drivers and forecast uncertainty will inform preparedness actions and reduce climate-driven social and economic consequences.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.70000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-resolution CMIP6 analysis highlights emerging climate challenges in alpine and Tibetan Tundra zones","authors":"Bijan Fallah,&nbsp;Masoud Rostami,&nbsp;Iulii Didovets,&nbsp;Zhiwen Dong","doi":"10.1002/met.70001","DOIUrl":"https://doi.org/10.1002/met.70001","url":null,"abstract":"<p>We employ a high-resolution Köppen climate classification dataset to examine shifts in Tundra zones within the Alps and Asia. Our analysis shows substantial reductions in Tundra areas by the mid-21st century under different Shared. Socioeconomic pathways (SSP1-2.6, SSP3-7.0, SSP5-8.5). Tundra zones in the Alps and the Tibetan Plateau are crucial for their unique climates and role as water reservoirs. Characterized by short, mild summers and long, severe winters, these zones are vital for the glaciers and perennial snow. The projected climate instability may significantly reduce alpine snow cover by mid-century with irreversible consequences. A 2°C temperature increase from the 1981–2010 baseline could eliminate the Tundra climate in the Alps and reduce it by over 70% in Asia. This is particularly concerning given that rivers from the Tibetan Plateau sustain nearly 40% of the global population.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-site collaborative forecasting of regional visibility based on spatiotemporal convolutional network","authors":"Wei Tian,&nbsp;Chen Lin,&nbsp;Yunlong Wu,&nbsp;Cheng Jin,&nbsp;Xin Li","doi":"10.1002/met.2206","DOIUrl":"https://doi.org/10.1002/met.2206","url":null,"abstract":"<p>Regional visibility forecasting encounters challenges due to data imbalance, temporal non-linearity and the consideration of multi-scale spatial factors. To tackle these challenges, this study introduces a novel approach for collaborative multi-site visibility forecasting based on spatiotemporal convolutional networks. Firstly, we preprocess the ERA5 reanalysis dataset and ground observation dataset, standardizing the spatiotemporal dimensions. We employ correlation coefficient analysis to select relevant meteorological factors. Subsequently, we create a spatiotemporal convolutional network model (TCN_GCN), which combines the power of temporal convolutional network (TCN) and graph convolutional network (GCN). Additionally, a weighted loss function is incorporated, accounting for the distribution of visibility values. The model is trained with multi-site data, enabling it to learn spatiotemporal visibility patterns across various sites. This empowers the model to generate multi-site visibility forecasts, thereby significantly improving regional visibility forecasting accuracy. Using 50 meteorological stations in Fujian Province, China, as a case study, we assess the model's predictions using key metrics such as mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R²). The experimental results demonstrate that the inclusion of both temporal and spatial features leads to a substantial enhancement in model prediction performance. The TCN_GCN model outperforms other deep learning methods in multi-site visibility forecasting, highlighting its effectiveness and superiority in improving regional visibility forecasting accuracy.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2206","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142360053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of land surface albedo changes over Iran using remote sensing data","authors":"Omid Reza Kefayat Motlagh,&nbsp;Mohammad Darand","doi":"10.1002/met.2224","DOIUrl":"https://doi.org/10.1002/met.2224","url":null,"abstract":"<p>Albedo is one of the key parameters in climatic studies. Investigating its temporal and spatial behavior can be a tool for understanding environmental changes. The MODIS sensor continuously produces the land surface albedo on a global scale and with the appropriate spatial resolution and makes it available to researchers. In this study, to analyze Iran's surface albedo trend, first, the daily albedo data of the MODIS on Iran in the period from January 1, 2001 to December 30, 2021 with a spatial resolution of 500 m were prepared from the NASA website. After the necessary pre-processing, the long-term seasonal and annual trend of Iran's albedo was calculated at the 90% confidence level using the non-parametric Mann–Kendall test. The findings showed that the albedo trend is positive in the lowland interior areas of Iran and negative in the highland areas. Since the decreasing trend of albedo in highland areas indicates the reduction of snow cover in these areas, this issue can challenge the life and water resources of these areas that rely on the accumulation of snow.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2224","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142045278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative analysis of satellite and reanalysis data with ground-based observations in Northern Ghana","authors":"Josephine Thywill Katsekpor,&nbsp;Klaus Greve,&nbsp;Edmund Ilimoan Yamba,&nbsp;Ebenezer Gyampoh Amoah","doi":"10.1002/met.2226","DOIUrl":"https://doi.org/10.1002/met.2226","url":null,"abstract":"<p>Accurate predictions of streamflow and flood events are contingent upon the availability of reliable hydrometeorological data. In regions characterized by scarcity of ground-based hydrometeorological observations, satellite and reanalysis data assume prominence as alternative predictors. Floods and droughts have emerged as a significant concern in Northern Ghana, yet the scarcity of ground-based hydrometeorological data impedes effective prediction of these hydrological events. Consequently, the identification of suitable surrogate hydrometeorological data holds paramount importance in addressing these challenges. This study, therefore, assessed the accuracy of satellite and reanalysis data against ground-based data in Northern Ghana. Rainfall and mean temperature spanning from 1998 to 2019 and soil moisture datasets from 2019 to 2022 were collected from GMet, ISMN (ground-based), CHIRPS, PERSIANN-CDR, ERA5, ARC2, MERRA-2, TRMM and CFSR (satellite and reanalysis). Employing rigorous statistical measures, namely standard deviation, mean absolute error (MAE) and mean bias error (MBE), the accuracy of these datasets was thoroughly evaluated. The results revealed that CHIRPS and PERSIANN-CDR exhibited superior accuracy in rainfall simulation, with CHIRPS demonstrating particularly consistent congruence with observed data. In terms of mean temperature prediction, ERA5 surpassed MERRA-2 and CFSR. Regarding soil moisture assessments, both ERA5 and CFSR offered satisfactory simulations. Hence, our findings advocate for the preference of CHIRPS (for rainfall data), ERA5 (for temperature data) and a combination of CFSR/ERA5 (for soil moisture data) as dependable primary data sources for streamflow modelling, drought analysis, flood prediction and water resource management in the context of Northern Ghana.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2226","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142002549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The use of vehicle-based observations in weather prediction and decision support","authors":"Amanda R. Siems-Anderson","doi":"10.1002/met.2225","DOIUrl":"https://doi.org/10.1002/met.2225","url":null,"abstract":"<p>Vehicle-based mobile observations are taken across the world every day by operational and research meteorological organizations, public transportation agencies, and private car manufacturers. Whether directly weather-related (e.g., air temperature) or not (e.g., wiper speed), the coverage and frequency of these observations holds the promise of filling in gaps between fixed observing stations and greatly improving situational awareness and weather forecasting, from road surface condition-specific applications and winter road maintenance to urban and street-level numerical weather prediction and beyond. However, in order to take advantage of these observations, the weather, water, and climate enterprise must work together with the transportation enterprise across academic, public, and private sectors to provide a mechanism for obtaining these data, so that the benefits of using these unconventional observations may be realized.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"31 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2225","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141991602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}