[HTML][HTML] LinkClimate: An interoperable knowledge graph platform for climate data

J Wu, F Orlandi, D O'Sullivan, S Dev - Computers & Geosciences, 2022 - Elsevier
Climate science has become more ambitious in recent years as global awareness about the
environment has grown. To better understand climate, historical climate (eg archived …

Evaluating the reliability of air temperature from ERA5 reanalysis data

B McNicholl, YH Lee, AG Campbell… - IEEE Geoscience and …, 2021 - ieeexplore.ieee.org
The reliability of European Remote Sensing 5 (ERA5) satellite-based air temperature data is
under investigation in this letter. To evaluate this, the ERA5 data will be compared with land …

Improving tourism analytics from climate data using knowledge graphs

J Wu, J Pierse, F Orlandi… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Climate change has been deemed to be one of the greatest challenges facing humans in
the 21st century, with extreme weather events taking place more regularly than before. While …

Boosting climate analysis with semantically uplifted knowledge graphs

J Wu, F Orlandi, D O'Sullivan… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Nowadays, the fast expansion of heterogeneous climate data resources accessible on the
Internet has led to substantial data fragmentation on the web. For example, station-based …

Precipitation forecasting: from geophysical aspects to machine learning applications

ECL Oliveira, AV Nogueira Neto, APP Santos… - Frontiers in …, 2023 - frontiersin.org
Intense precipitation events pose a significant threat to human life. Mathematical and
computational models have been developed to simulate atmospheric dynamics to predict …

The observational evidence of association between types of aerosol mode-cloud-precipitation interaction over Iran

M Rezaei, M Farajzadeh, S Kant - Atmospheric Pollution Research, 2023 - Elsevier
The present study quantifies for the first time the statistical relationship between aerosol
properties with Cloud microphysical Properties (CPs), and consequently effect on …

Measurement of industrial smoke plumes from satellite images

J Wu, C O'Sullivan, F Orlandi… - IGARSS 2023-2023 …, 2023 - ieeexplore.ieee.org
Reducing industrial greenhouse gas (GHG) emissions has become imperative for mitigating
the adverse effects of climate change. Accurate measurement and monitoring of industrial …

Augmenting weather sensor data with remote knowledge graphs

J Wu, F Orlandi, MS Pathan… - IGARSS 2022-2022 …, 2022 - ieeexplore.ieee.org
The latest analytical models are becoming frequently used in meteorological science
research. For instance, machine learning and deep learning models are being trained for …

Efficient forecasting of precipitation using LSTM

MS Pathan, M Jain, YH Lee… - 2021 Photonics & …, 2021 - ieeexplore.ieee.org
Precipitation is one of those many critical elements of the hydrological cycle that has a direct
impact on human life in many aspects. An accurate and early detection of a future …

How accurate are the machine learning models in improving monthly rainfall prediction in hyper arid environment?

F Baig, L Ali, MA Faiz, H Chen, M Sherif - Journal of Hydrology, 2024 - Elsevier
Arid regions like the United Arab Emirates (UAE) face a dire challenge of scarce water
resources and unpredictable climate patterns. This study investigates the efficacy of …