Comparison between Atmospheric Reanalysis Models ERA5 and ERA-Interim at the North Antarctic Peninsula Region

Datos Bibliográficos

ID4833103
AutoresFernando L Hillebrand (0000-0002-0182-8526, Universidade Federal do Rio Grande do Sul), Ulisses Franz Bremer (0000-0003-0519-5807, Universidade Federal do Rio Grande do Sul), Jorge Arigony Neto (0000-0003-4848-2064, Universidade Federal do Rio Grande), Cristiano Niederauer Da Rosa (0000-0003-3693-4764, Universidade Federal do Rio Grande do Sul), Claudio W Mendes (0000-0003-1745-348X, Universidade Federal do Rio Grande do Sul), Juliana Costi (0000-0001-6220-2343, Universidade Federal do Rio Grande), Marcos W D De Freitas (0000-0001-9879-2584, Universidade Federal do Rio Grande do Sul), Frederico Schardong (0000-0003-4492-163X, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul)
Año2021
Volumen111
Número4
Páginas1147-1159
Fecha de publicación2021-06-07
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaAnnals of the American Association of Geographers (JOURNAL)
Identificadores de la revistaISSN: 2469-4452 • E-ISSN: 2469-4460
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1080/24694452.2020.1807308
OpenAlexW3094159297
IdiomaEN
Citas recibidas1
Referencias citadas34

The availability of accurate meteorological data is important for the modeling of atmospheric flows, enabling the understanding of climate change in a given environment over time. Therefore, this study aimed to evaluate the quality of the meteorological data of 2 m temperature (T) and mean sea level pressure (MSLP), obtained through the atmospheric reanalysis models ERA5 and ERA-Interim (ERA-i) in the northern region of the Antarctic Peninsula, covering the period from 1979 to 2018. To carry out the statistical process, local observations from nine weather stations installed in the study region were used, with data available from the Scientific Committee on Antarctic Research. Statistical analysis evaluated Pearson’s linear correlation coefficient (R), standard deviation (σ), normalized bias, normalized mean absolute error, and normalized root mean square error. Regarding the difference in T ̄ between weather stations and reanalysis models, we found a better result for ERA5 (ΔT ̄ = −0.34 °C) compared to ERA-i (ΔT ̄ = 0.37 °C); however, for the difference in MSLP ̄ the ERA-i (ΔMSLP ̄ = −0.04 hPa) presented a better response in relation to ERA5 (ΔMSLP ̄ = 0.24 hPa). When verifying the local meteorological observations trend, an increase of T in 0.31 °C decade−1 (Esperanza station) and a reduction of MSLP between −0.56 (Bellingshausen station) and −0.80 hPa decade−1 (Jubany station) were recorded

Atmospheric research · Atmospheric sciences · Climate change · Climatology · Geography · Interim · Meteorology · Peninsula · Physical geography · Sea level · Standard deviation · Statistics · Arctic and Antarctic ice dynamics · Climate variability and models · Cryospheric studies and observations · Environmental Science · Mathematics · Geology