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Machine learning-based modelling of zenith wet delay using terrestrial meteorological data in the Brazilian territory

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Autor(es):
Albuquerque, Afonso Marques ; Nespolo, Raphael Silva ; Garcia Tommaselli, Antonio Maria ; Martins-Neto, Rorai Perreira ; Imai, Nilton Nobuhiro ; Marra Alves, Daniele Barroca ; Ferreira Gouveia, Tayna Aparecida ; Jerez, Gabriel Oliveira
Número total de Autores: 8
Tipo de documento: Artigo Científico
Fonte: GEOSPATIAL WEEK 2023, VOL. 10-1; v. N/A, p. 7-pg., 2024-01-01.
Resumo

The Zenith Total Delay (ZTD) is one of the primary error sources derived from the neutral atmosphere associated with the GNSS (Global Navigation Satellite Systems) technique. Zenith Wet Delay (ZWD) is the smallest part of the ZTD, but the high variability is caused by spatial-temporal variation, making the modelling of this component a challenging task. Although ZWD is considered an error in GNSS positioning, it is also a variable composed mainly of water vapour and can, therefore, be used for atmospheric investigations, and assists in climate studies for precipitation events. In this work, a model was trained to estimate the delay wet component from surface atmospheric parameters. The training data comes from 29 radiosonde stations around Brazil, for a six-year period (2017 to 2022), with data collected at 12 h UTC (Universal Time Coordinated). The model was validated using the holdout technique, with 70% of the data used in training and 30% for validation (cross-validation analysis). The generated model achieved a RMSE (Root Mean Squared Error) of approximately 38 mm, with an 81% of determination coefficient. (AU)

Processo FAPESP: 21/05285-0 - Novas estratégias de recuperação de perfis provenientes de rádio ocultação GNSS considerando a atmosfera brasileira
Beneficiário:Gabriel Oliveira Jerez
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 21/06029-7 - Sensoriamento remoto de alta resolução para agricultura digital
Beneficiário:Antonio Maria Garcia Tommaselli
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 23/14739-0 - Aprimoramento da Estimativa do GNSS-PWV na Ocorrência de Eventos de Precipitação
Beneficiário:Afonso Marques Albuquerque
Modalidade de apoio: Bolsas no Brasil - Mestrado