Trends in stratospheric ozone profiles using functional mixed models

This paper is devoted to the modeling of altitude-dependent patterns of ozone variations over time. Umkehr ozone profiles (quarter of Umkehr layer) from 1978 to 2011 are investigated at two locations: Boulder (USA) and Arosa (Switzerland). The study consists of two statistical stages. First we appro...

Full description

Bibliographic Details
Published in:Atmospheric Chemistry and Physics
Main Authors: Park, A., Guillas, S., Petropavlovskikh, I.
Format: Text
Language:English
Published: 2018
Subjects:
Online Access:https://doi.org/10.5194/acp-13-11473-2013
https://www.atmos-chem-phys.net/13/11473/2013/
id ftcopernicus:oai:publications.copernicus.org:acp20043
record_format openpolar
spelling ftcopernicus:oai:publications.copernicus.org:acp20043 2023-05-15T15:12:30+02:00 Trends in stratospheric ozone profiles using functional mixed models Park, A. Guillas, S. Petropavlovskikh, I. 2018-01-15 application/pdf https://doi.org/10.5194/acp-13-11473-2013 https://www.atmos-chem-phys.net/13/11473/2013/ eng eng doi:10.5194/acp-13-11473-2013 https://www.atmos-chem-phys.net/13/11473/2013/ eISSN: 1680-7324 Text 2018 ftcopernicus https://doi.org/10.5194/acp-13-11473-2013 2019-12-24T09:54:50Z This paper is devoted to the modeling of altitude-dependent patterns of ozone variations over time. Umkehr ozone profiles (quarter of Umkehr layer) from 1978 to 2011 are investigated at two locations: Boulder (USA) and Arosa (Switzerland). The study consists of two statistical stages. First we approximate ozone profiles employing an appropriate basis. To capture primary modes of ozone variations without losing essential information, a functional principal component analysis is performed. It penalizes roughness of the function and smooths excessive variations in the shape of the ozone profiles. As a result, data-driven basis functions (empirical basis functions) are obtained. The coefficients (principal component scores) corresponding to the empirical basis functions represent dominant temporal evolution in the shape of ozone profiles. We use those time series coefficients in the second statistical step to reveal the important sources of the patterns and variations in the profiles. We estimate the effects of covariates – month, year (trend), quasi-biennial oscillation, the solar cycle, the Arctic oscillation, the El Niño/Southern Oscillation cycle and the Eliassen–Palm flux – on the principal component scores of ozone profiles using additive mixed effects models. The effects are represented as smooth functions and the smooth functions are estimated by penalized regression splines. We also impose a heteroscedastic error structure that reflects the observed seasonality in the errors. The more complex error structure enables us to provide more accurate estimates of influences and trends, together with enhanced uncertainty quantification. Also, we are able to capture fine variations in the time evolution of the profiles, such as the semi-annual oscillation. We conclude by showing the trends by altitude over Boulder and Arosa, as well as for total column ozone. There are great variations in the trends across altitudes, which highlights the benefits of modeling ozone profiles. Text Arctic Copernicus Publications: E-Journals Arctic Atmospheric Chemistry and Physics 13 22 11473 11501
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description This paper is devoted to the modeling of altitude-dependent patterns of ozone variations over time. Umkehr ozone profiles (quarter of Umkehr layer) from 1978 to 2011 are investigated at two locations: Boulder (USA) and Arosa (Switzerland). The study consists of two statistical stages. First we approximate ozone profiles employing an appropriate basis. To capture primary modes of ozone variations without losing essential information, a functional principal component analysis is performed. It penalizes roughness of the function and smooths excessive variations in the shape of the ozone profiles. As a result, data-driven basis functions (empirical basis functions) are obtained. The coefficients (principal component scores) corresponding to the empirical basis functions represent dominant temporal evolution in the shape of ozone profiles. We use those time series coefficients in the second statistical step to reveal the important sources of the patterns and variations in the profiles. We estimate the effects of covariates – month, year (trend), quasi-biennial oscillation, the solar cycle, the Arctic oscillation, the El Niño/Southern Oscillation cycle and the Eliassen–Palm flux – on the principal component scores of ozone profiles using additive mixed effects models. The effects are represented as smooth functions and the smooth functions are estimated by penalized regression splines. We also impose a heteroscedastic error structure that reflects the observed seasonality in the errors. The more complex error structure enables us to provide more accurate estimates of influences and trends, together with enhanced uncertainty quantification. Also, we are able to capture fine variations in the time evolution of the profiles, such as the semi-annual oscillation. We conclude by showing the trends by altitude over Boulder and Arosa, as well as for total column ozone. There are great variations in the trends across altitudes, which highlights the benefits of modeling ozone profiles.
format Text
author Park, A.
Guillas, S.
Petropavlovskikh, I.
spellingShingle Park, A.
Guillas, S.
Petropavlovskikh, I.
Trends in stratospheric ozone profiles using functional mixed models
author_facet Park, A.
Guillas, S.
Petropavlovskikh, I.
author_sort Park, A.
title Trends in stratospheric ozone profiles using functional mixed models
title_short Trends in stratospheric ozone profiles using functional mixed models
title_full Trends in stratospheric ozone profiles using functional mixed models
title_fullStr Trends in stratospheric ozone profiles using functional mixed models
title_full_unstemmed Trends in stratospheric ozone profiles using functional mixed models
title_sort trends in stratospheric ozone profiles using functional mixed models
publishDate 2018
url https://doi.org/10.5194/acp-13-11473-2013
https://www.atmos-chem-phys.net/13/11473/2013/
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source eISSN: 1680-7324
op_relation doi:10.5194/acp-13-11473-2013
https://www.atmos-chem-phys.net/13/11473/2013/
op_doi https://doi.org/10.5194/acp-13-11473-2013
container_title Atmospheric Chemistry and Physics
container_volume 13
container_issue 22
container_start_page 11473
op_container_end_page 11501
_version_ 1766343173357961216