Math Calendar

Tuesday, August 11, 2020
15:30-16:00
HFG Library
Institute Tea
Thursday, August 13, 2020
14:00-15:00
Master thesis defense
Jieyu Chen -Quality control and verification of citizen science wind observations, online

Abstract:

Wind observations collected by citizen weather stations (CWS) arevaluable for forecasting wind and issuing warnings, yet their quality is notguaranteed. Few people have worked on the quality of such wind data so far. Inthis thesis, we develop methods to improve the quality of wind data collectedby CWS. The methods are applied to filter suspect observations and correctsystematic biases, processes that are known as quality control and biascorrection. We focus on the wind speed observations recorded by citizen weatherstations in the province of Utrecht, the Netherlands, and our data is providedby the third-party platform, WOW-NL\footnote{\url{https://wow.knmi.nl/}}.WOW-NL allows users to upload and view their weather observations in real-time.This thesis consists of four parts: (1) pre-processing the raw data; (2)performing standard quality control that checks the internal consistency, theplausible range, and the temporal consistency of observations; (3) correctingthe bias by empirical quantile mapping to reduce the errors mainly caused bylow sensor heights; and (4) implementing spatial quality control that comparesobservations from neighboring stations, where the Earth mover's distance isintroduced to select neighbors. More than one-third of low-quality stations areexcluded from the study before the standard quality control, based on a lack ofdata completeness. About three-quarters of the remaining citizen wind speedobservations pass all quality control tests. We compare the citizen science datawith official data, and use statistical indicators such as Kolmogorovā€“Smirnovstatistic and root mean square error to quantify the improvements in dataquality after each step. Our results show that the bias correctionsubstantially reduces the errors after the standard quality control, and thespatial quality control further improves the data such that it is comparablewith official data. This study demonstrates that the citizen science wind datamatch well with official data after quality control and bias correction. Thismeans that this data can potentially be used in many applications likeanalyzing localized extreme wind events that require denser observationnetworks than currently provided by the official stations.

 

You are very welcome to join the presentation by the followingMicrosoft Team link:

https://teams.microsoft.com/l/meetup-join/19%3ameeting_MmQ3MTA1ODItNzExMi00ZmY3LWFhN2EtNzI4YWRkMzI3ZmU4%40thread.v2/0?context=%7b%22Tid%22%3a%22d72758a0-a446-4e0f-a0aa-4bf95a4a10e7%22%2c%22Oid%22%3a%22c95ff572-96ab-4a70-8b4f-4d6daf773f59%22%7d
Tuesday, August 18, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, August 25, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, September 1, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, September 8, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, September 15, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, September 22, 2020
15:30-16:00
HFG Library
Institute Tea
Thursday, September 24, 2020
16:00-17:00
HFG 611
Applied Mathematics Seminar
Yves van Gennip (TU Delft) - TBA, HFG 611)
Tuesday, September 29, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, October 6, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, October 13, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, October 20, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, October 27, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, November 3, 2020
15:30-16:00
HFG Library
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Tuesday, November 10, 2020
15:30-16:00
HFG Library
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Tuesday, November 17, 2020
15:30-16:00
HFG Library
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Tuesday, November 24, 2020
15:30-16:00
HFG Library
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Tuesday, December 1, 2020
15:30-16:00
HFG Library
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Tuesday, December 8, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, December 15, 2020
15:30-16:00
HFG Library
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Tuesday, December 22, 2020
15:30-16:00
HFG Library
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Tuesday, December 29, 2020
15:30-16:00
HFG Library
Institute Tea
Tuesday, January 5, 2021
15:30-16:00
HFG Library
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Tuesday, January 12, 2021
15:30-16:00
HFG Library
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Tuesday, January 19, 2021
15:30-16:00
HFG Library
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Tuesday, January 26, 2021
15:30-16:00
HFG Library
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Tuesday, February 2, 2021
15:30-16:00
HFG Library
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Tuesday, February 9, 2021
15:30-16:00
HFG Library
Institute Tea