Climate monitoring: data rescue, management, quality and homogenization
In this session, we welcome contributions (oral and poster) in the following major topics:
• Climate monitoring , including early warning systems and improvements in the quality of the observational meteorological networks
• More efficient transfer of the data rescued into the digital format by means of improving the current state-of-the-art on image enhancement, image segmentation and post-correction techniques, innovating on adaptive Optical Character Recognition and Speech Recognition technologies and their application to transfer data, defining best practices about the operational context for digitisation, improving techniques for inventorying, organising, identifying and validating the data rescued, exploring crowd-sourcing approaches or engaging citizen scientist volunteers, conserving, imaging, inventorying and archiving historical documents containing weather records
• Climate data and metadata processing, including climate data flow management systems, from improved database models to better data extraction, development of relational metadata databases and data exchange platforms and networks interoperability
• Innovative, improved and extended climate data quality controls (QC), including both near real-time and time-series QCs: from gross-errors and tolerance checks to temporal and spatial coherence tests, statistical derivation and machine learning of QC rules, and extending tailored QC application to monthly, daily and sub-daily data and to all essential climate variables
• Improvements to the current state-of-the-art of climate data homogeneity and homogenisation methods, including methods intercomparison and evaluation, along with other topics such as climate time-series inhomogeneities detection and correction techniques/algorithms, using parallel measurements to study inhomogeneities and extending approaches to detect/adjust monthly and, especially, daily and sub-daily time-series and to homogenise all essential climate variables
• Fostering evaluation of the uncertainty budget in reconstructed time-series, including the influence of the various data processes steps, and analytical work and numerical estimates using realistic benchmarking datasets
Data Rescue
14:00–14:15
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EMS2024-342
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Onsite presentation
Homogenization
14:30–14:45
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EMS2024-72
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Onsite presentation
14:45–15:00
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EMS2024-231
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Onsite presentation
15:00–15:15
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EMS2024-406
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Onsite presentation
15:15–15:30
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EMS2024-410
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Onsite presentation
Coffee break
Chairpersons: Dan Hollis, Federico Fierli
Quality Control
16:00–16:15
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EMS2024-367
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Online presentation
Monitoring
16:45–17:00
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EMS2024-877
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Onsite presentation
17:00–17:15
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EMS2024-954
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Onsite presentation
GP39
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EMS2024-384
A high density observational dataset of daily meteorological data for the Extended Alpine Region
(withdrawn)