Meteorological data rescue: Citizen science lessons learned from Southern Weather Discovery

Summary

Daily weather reconstructions (called “reanalyses”) can help improve our understanding of meteorology and long-term climate changes. Adding undigitized historical weather observations to the datasets that underpin reanalyses is desirable; however, time requirements to capture those data from a range of archives is usually limited. Southern Weather Discovery is a citizen science data rescue project that recovered tabulated handwritten meteorological observations from ship log books and land-based stations spanning New Zealand, the Southern Ocean, and Antarctica. We describe the Zooniverse-hosted Southern Weather Discovery campaign, highlight promotion tactics, and replicate keying levels needed to obtain 100% complete transcribed datasets with minimal type 1 and type 2 transcription errors. Rescued weather observations can augment optical character recognition (OCR) text recognition libraries. Closer links between citizen science data rescue and OCR-based scientific data capture will accelerate weather reconstruction improvements, which can be harnessed to mitigate impacts on communities and infrastructure from weather extremes.

Highlights

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  Data rescue on Zooniverse allowed rapid transcription of historic weather observations

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  Eight replicate data entries can be used to obtain consensus with minimal errors

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  Transcribed weather observations can dramatically expand OCR character libraries

The bigger picture

Citizen science has the potential to capture historical handwritten scientific tabulated data that are not held in digital databases. However, undertaking a citizen science campaign for that purpose is not well described, which we address here. Our citizen science data rescue approach constrained data keying targets, developed participant instructions using clear examples, established replication levels to maximize completeness and confidence of data transcription, and demonstrated common data rescue pitfalls. We highlight how an effective communications strategy helps to maintain project momentum. Collaborating with industry to enhance optical character recognition (OCR) capability has the benefit of accelerating data rescue progress that can rapidly augment scientific data repositories. The resulting improvements to comprehensive historical weather datasets with global coverage can support models and predictive capabilities that help mitigate impacts on society from extreme weather.

Abstract

Southern Weather Discovery is a citizen science project on Zooniverse that captured handwritten historical weather observations. This descriptor article outlines how we ran that citizen science project, which can be adapted to a wide range of disciplines. We highlight replicated data keying requirements to minimize transcription errors, some common pitfalls to avoid, and the importance of a good communications strategy. Our partnership with industry on optical character recognition shows potential to harness computer vision to accelerate historical scientific data capture.