Article
Environmental Sciences
Izabela Pawlak, Alnilam Fernandes, Janusz Jaroslawski, Krzysztof Klejnowski, Aleksander Pietruczuk
Summary: This study considers the option of forecasting surface ozone based on measurements of only surface ozone and several weather parameters. This low-cost configuration can increase the number of locations that provide short-term surface ozone forecast important to local communities.
Article
Environmental Sciences
Halima Oufdou, Lise Bellanger, Amal Bergam, Kenza Khomsi
Summary: Forecasting concentration levels, specifically daily average surface ozone concentration, in the Grand Casablanca Region of Morocco is crucial for planning atmospheric protection strategies. After analyzing various statistical models, it was found that parametric models outperformed nonparametric models in predicting ozone pollution. A simple linear regression model with five variables was identified as the most suitable for the available data at Jahid station, providing good predictive quality and ease of implementation.
Article
Computer Science, Artificial Intelligence
Luiz Angelo Steffenel, Vagner Anabor, Damaris Kirsch Pinheiro, Lissette Guzman, Gabriela Dornelles Bittencourt, Hassan Bencherif
Summary: Weather forecast based on deep learning techniques has gained attention, particularly in the field of stratospheric ozone prediction. By studying different Ozone Secondary Events (OSE), accurate and fast prediction models can be developed to forecast stratospheric ozone.
Article
Geosciences, Multidisciplinary
Aoxing Zhang, Tzung-May Fu, Xu Feng, Jianfeng Guo, Chanfang Liu, Jiongkai Chen, Jiajia Mo, Xiao Zhang, Xiaolin Wang, Wenlu Wu, Yue Hou, Honglong Yang, Chao Lu
Summary: We developed an efficient 2-D convolutional neural network-surface ozone ensemble forecast system using 2-D convolutional neural network and weather ensemble forecasts. This system demonstrated comparable performance to current operating forecast systems and met the air quality level forecast accuracies required by the Chinese authorities up to 144-hr lead time. Uncertainties in weather forecasts contributed 38%-54% of the ozone forecast errors at 24-hr lead time and beyond. The 2DCNN-SOEF enabled an ozone exceedance probability metric, which better represented the risks of air pollution given the range of possible weather outcomes. Our ensemble forecast framework can be extended to operationally forecast other meteorology-dependent environmental risks globally, making it a valuable tool for environmental management.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Peng Zhou, Youyue Wen, Jian Yang, Leiku Yang, Minxuan Liang, Tingting Wen, Shaoman Cai
Summary: This paper analyzed the spatial and temporal variation characteristics of total column ozone (TCO) over the Yangtze River Delta Urban Agglomeration, exploring its relationship with meteorological and socio-economic factors. The results showed that TCO exhibited a quasi-latitudinal distribution and was influenced by precipitation and the absorbed aerosol index. The study also constructed mathematical models to fit and predict the future trend of TCO.
Article
Geosciences, Multidisciplinary
Xiaoyu Long, Sang-Ik Shin, Matthew Newman
Summary: In this study, we used statistical downscaling to provide high-resolution predictions of sea level anomalies along the North American coast. By applying a seasonally invariant downscaling operator to monthly hindcasts from six seasonal prediction systems, we achieved significantly improved deterministic skill compared to the original interpolated hindcasts. This improvement was most pronounced in the summer and fall seasons.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Meteorology & Atmospheric Sciences
Claudio Heinrich
Summary: Rank histograms are popular tools for evaluating the reliability of meteorological ensemble forecast systems. The chosen number of bins for a histogram is crucial, as too few or too many bins can affect the judgement of uniformity. Research suggests that fewer bins than the typical ensemble size plus one may be more appropriate, especially when verification data is limited.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
(2021)
Article
Meteorology & Atmospheric Sciences
Bo Christiansen, Shuting Yang, Dominic Matte
Summary: This paper investigates statistical tests to quantify the skill difference between initialized and uninitialized forecasts, finding that different statistics methods may overestimate the role of initialization. Based on the long-term prediction of near-surface temperature, it is found that initialization has a significant effect in small lead times but not for lead times longer than 3 years when considering the results from simple experiments.
JOURNAL OF CLIMATE
(2023)
Article
Environmental Sciences
Mingliang Ma, Guobiao Yao, Jianping Guo, Kaixu Bai
Summary: The study reveals four typical variation patterns of surface ozone in China, with seasonal variation associated with UV radiation and meteorological factors, and long-term trends mainly influenced by ozone precursors and weather conditions. Furthermore, the increasing trend of ozone in North China is found to be related to the depletion of nitrogen dioxide and carbon monoxide, as well as the increase in volatile organic compounds.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Engineering, Environmental
Huidong Jin, Weifan Jiang, Minzhe Chen, Ming Li, K. Shuvo Bakar, Quanxi Shao
Summary: Skilful and localised daily weather forecasts are needed by climate-sensitive sectors, which can be provided by downscaling techniques applied to the ensemble forecasts from General circulation models. This study focuses on deep-learning-based downscaling method for ensemble rainfall forecasts and proposes a two-step procedure to enhance the accuracy and skill. The results demonstrate that the developed very deep statistical downscaling model outperforms other models and improves the raw forecasts, although further research efforts are required for skilful seasonal climate forecasts.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Environmental Sciences
Stefano Federico, Rosa Claudia Torcasio, Martina Lagasio, Barry H. Lynn, Silvia Puca, Stefano Dietrich
Summary: This paper presents the performance of a dynamic lightning forecast scheme for Italy, comparing the predictions against ground observational data. Results show the success of the method in forecasting lightning strikes, with the need for careful tuning of the forecast performance depending on the season.
Article
Meteorology & Atmospheric Sciences
Ming Li, Huidong Jin, Quanxi Shao
Summary: The copula-based postprocessing method shows improved forecast skills for rainfall indices in a case study in Queensland, Australia, outperforming other methods in most cases and particularly showing substantial improvements in tropical regions.
WEATHER AND CLIMATE EXTREMES
(2021)
Article
Environmental Sciences
Sini Isokaanta, Santtu Mikkonen, Maria Laurikainen, Angela Buchholz, Siegfried Schobesberger, James D. Blande, Tuomo Nieminen, Ilona Ylivinkka, Jaana Back, Tuukka Petaja, Markku Kulmala, Taina Yli-Juuti
Summary: The study investigates the temperature dependency of tropospheric ozone concentration in the Finnish boreal forest. It finds that factors like weather conditions, long-range transport of precursors, and hydrocarbon concentration influence this dependency. Moreover, it identifies the role of oxygenated volatile organic compounds in the temperature dependence of ozone concentration in a low-NOx environment. The findings highlight the importance of considering multiple factors and the potential of using mixed effects models for ozone prediction.
ATMOSPHERIC ENVIRONMENT
(2022)
Article
Environmental Sciences
Matthew Ninneman, Irina Petropavlovskikh, Peter Effertz, Duli Chand, Daniel Jaffe
Summary: This study uses a statistical model to characterize daily peak 8-hour O-3 concentrations at a rural mountaintop research station in central Oregon. The results show that relative humidity, aerosol scattering, carbon monoxide, and water vapor mixing ratio significantly impact O-3 concentrations.
Article
Meteorology & Atmospheric Sciences
Rasmus Wiuff
Summary: In October 1941, Nazi Germany's High Command realized that the war against the Soviet Union could not be ended before winter. German professor Franz Baur prepared a long-range weather forecast for the winter of 1941/42, predicting it would be normal or milder than normal. However, the winter turned out to be one of the worst, damaging Baur's reputation. Based on original wartime prognoses and Baur's history, this article argues that the judgment against Baur was too harsh and unfair.
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
(2023)
Article
Computer Science, Information Systems
Duarte Raposo, Andre Rodrigues, Jorge Sa Silva, Fernando Boavida
JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT
(2017)
Editorial Material
Computer Science, Information Systems
Jorge Sa Silva, Antonio Loureiro, Antonio Skarmeta, Fernando Boavida
INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT
(2018)
Article
Computer Science, Information Systems
Ricardo Silva, Jorge Sa Silva, Fernando Boavida
COMPUTER COMMUNICATIONS
(2014)
Review
Chemistry, Analytical
Ngombo Armando, Andre Rodrigues, Vasco Pereira, Jorge Sa Silva, Fernando Boavida
Article
Computer Science, Theory & Methods
Jose Marcelo Fernandes, Jorge Sa Silva, Andre Rodrigues, Fernando Boavida
Summary: The article discusses the importance of considering humans as system beneficiaries or active components in smart systems. It surveys existing approaches to unobtrusive sensing of human beings and identifies open issues and challenges in this area.
ACM COMPUTING SURVEYS
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
D. Dias, J. Sa Silva, F. Boavida, V. Ferreira
2017 IEEE INTERNATIONAL CONFERENCE ON MICROWAVES, ANTENNAS, COMMUNICATIONS AND ELECTRONIC SYSTEMS (COMCAS)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
D. Nunes, J. Sa Silva, A. Figueira, H. Dias, A. Rodrigues, V. Pereira, F. Boavida, S. Sinche
2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY (CIT)
(2016)
Proceedings Paper
Engineering, Multidisciplinary
A. Figueira, D. Nunes, R. Barbosa, A. Reis, H. Aguiar, S. Sinche, A. Rodrigues, V. Pereira, H. Dias, C. Herrera, D. Raposo, J. Sa Silva, F. Boavida
PROCEEDINGS OF THE SIXTH IEEE GLOBAL HUMANITARIAN TECHNOLOGY CONFERENCE GHTC 2016
(2016)
Proceedings Paper
Engineering, Multidisciplinary
A. Reis, D. Nunes, H. Aguiar, H. Dias, R. Barbosa, A. Figueira, S. Sinche, D. Raposo, V. Pereira, J. Sa Silva, F. Boavida, A. Rodrigues, C. Herrera
PROCEEDINGS OF THE SIXTH IEEE GLOBAL HUMANITARIAN TECHNOLOGY CONFERENCE GHTC 2016
(2016)
Proceedings Paper
Computer Science, Information Systems
Fiorella Guadagni, Noemi Scarpato, Ferroni Patrizia, Grazia D'Ottavi, Fernando Boavida, Mario Roselli, Graziano Garrisi, Andrea Lisi
INTERNET OF THINGS: IOT INFRASTRUCTURES, IOT 360, PT II
(2016)
Proceedings Paper
Computer Science, Hardware & Architecture
D. Raposo, A. Rodrigues, J. Sa Silva, F. Boavida, J. Oliveira, C. Herrera, C. Egas
2016 IEEE 17TH INTERNATIONAL SYMPOSIUM ON A WORLD OF WIRELESS, MOBILE AND MULTIMEDIA NETWORKS (WOWMOM)
(2016)
Proceedings Paper
Computer Science, Theory & Methods
David Nunes, Jorge Sa Silva, Carlos Herrera, Fernando Boavida
WIRED/WIRELESS INTERNET COMMUNICATIONS, WWIC 2016
(2016)
Proceedings Paper
Engineering, Industrial
Ricardo Silva, Jorge Sa Silva, Fernando Boavida
2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT)
(2015)
Proceedings Paper
Computer Science, Information Systems
Luis J. Mariscal, Alicia Trivino, Fernando Boavida
WIRED/WIRELESS INTERNET COMMUNICATIONS, WWIC 2015
(2015)
Proceedings Paper
Computer Science, Theory & Methods
Andre Rodrigues, Jorge Sa Silva, Fernando Boavida
WIRED/WIRELESS INTERNET COMMUNICATIONS
(2014)