Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations
Southern Ocean (SO) shortwave (SW) radiation biases are a common problem in contemporary general circulation models (GCMs), with most models exhibiting a tendency to absorb too much incoming SW radiation. These biases have been attributed to deficiencies in the representation of clouds during the au...
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ftcopernicus:oai:publications.copernicus.org:acpd74981 2023-05-15T18:07:34+02:00 Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations Kuma, Peter McDonald, Adrian J. Morgenstern, Olaf Alexander, Simon P. Cassano, John J. Garrett, Sally Halla, Jamie Hartery, Sean Harvey, Mike J. Parsons, Simon Plank, Graeme Varma, Vidya Williams, Jonny 2019-04-05 application/pdf https://doi.org/10.5194/acp-2019-201 https://www.atmos-chem-phys-discuss.net/acp-2019-201/ eng eng doi:10.5194/acp-2019-201 https://www.atmos-chem-phys-discuss.net/acp-2019-201/ eISSN: 1680-7324 Text 2019 ftcopernicus https://doi.org/10.5194/acp-2019-201 2019-12-24T09:49:20Z Southern Ocean (SO) shortwave (SW) radiation biases are a common problem in contemporary general circulation models (GCMs), with most models exhibiting a tendency to absorb too much incoming SW radiation. These biases have been attributed to deficiencies in the representation of clouds during the austral summer months, either due to cloud cover or cloud optical thickness being too low. The problem has been the focus of many studies, most of which utilised satellite datasets for model evaluation. We use multi-year ship based observations and the CERES spaceborne radiation budget measurements to contrast cloud representation and SW radiation in the atmospheric component Global Atmosphere (GA) version 7.0 and 7.1 of the HadGEM3 GCM and the MERRA-2 reanalysis. We find that MERRA-2 is biased in the opposite direction to GA (reflects too much SW radiation). In addition, MERRA-2 performs better in terms of absolute SW bias than nudged runs of GA7.0 and GA7.1 in the 60–70° S latitude band. GA7.1 reduces the SO SW radiation biases relative to GA7.0, but significant errors remain at up to 20 W m −2 between 60 and 70° S in the austral summer months. Using ship-based ceilometer observations, we find low cloud below 2 km to be predominant in the Ross Sea and the Indian Ocean sector of the SO. Utilising a novel surface lidar simulator developed for this study, derived from an existing COSP-ACTSIM spaceborne lidar simulator, we find that GA7.0 and MERRA-2 both underestimate low cloud occurrence relative to the ship observations by 18–25 % on average, though the cloud cover in MERRA-2 is closer to observations by about 7 %. Based on radiosonde observations, we also find the low cloud to be strongly linked to boundary-layer atmospheric stability and the sea surface temperature. GA7.0 and MERRA-2 agree well with observations in terms of boundary-layer stability, suggesting that subgrid-scale parametrisations do not generate enough cloud in response to the thermodynamic profile of the atmosphere and the surface temperature. Our analysis shows that MERRA-2 has a much greater proportion of cloud liquid water in the SO in January than GA7.0, a likely key contributor to the difference in SW radiation. We show that boundary-layer stability and relative humidity fields are very similar in GA7.0 and MERRA-2, and unlikely to be the cause of the different cloud representation, suggesting that subgrid-scale parametrisations are responsible for the difference between the models. Text Ross Sea Southern Ocean Copernicus Publications: E-Journals Austral Indian Merra ENVELOPE(12.615,12.615,65.816,65.816) Ross Sea Southern Ocean |
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Open Polar |
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Copernicus Publications: E-Journals |
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ftcopernicus |
language |
English |
description |
Southern Ocean (SO) shortwave (SW) radiation biases are a common problem in contemporary general circulation models (GCMs), with most models exhibiting a tendency to absorb too much incoming SW radiation. These biases have been attributed to deficiencies in the representation of clouds during the austral summer months, either due to cloud cover or cloud optical thickness being too low. The problem has been the focus of many studies, most of which utilised satellite datasets for model evaluation. We use multi-year ship based observations and the CERES spaceborne radiation budget measurements to contrast cloud representation and SW radiation in the atmospheric component Global Atmosphere (GA) version 7.0 and 7.1 of the HadGEM3 GCM and the MERRA-2 reanalysis. We find that MERRA-2 is biased in the opposite direction to GA (reflects too much SW radiation). In addition, MERRA-2 performs better in terms of absolute SW bias than nudged runs of GA7.0 and GA7.1 in the 60–70° S latitude band. GA7.1 reduces the SO SW radiation biases relative to GA7.0, but significant errors remain at up to 20 W m −2 between 60 and 70° S in the austral summer months. Using ship-based ceilometer observations, we find low cloud below 2 km to be predominant in the Ross Sea and the Indian Ocean sector of the SO. Utilising a novel surface lidar simulator developed for this study, derived from an existing COSP-ACTSIM spaceborne lidar simulator, we find that GA7.0 and MERRA-2 both underestimate low cloud occurrence relative to the ship observations by 18–25 % on average, though the cloud cover in MERRA-2 is closer to observations by about 7 %. Based on radiosonde observations, we also find the low cloud to be strongly linked to boundary-layer atmospheric stability and the sea surface temperature. GA7.0 and MERRA-2 agree well with observations in terms of boundary-layer stability, suggesting that subgrid-scale parametrisations do not generate enough cloud in response to the thermodynamic profile of the atmosphere and the surface temperature. Our analysis shows that MERRA-2 has a much greater proportion of cloud liquid water in the SO in January than GA7.0, a likely key contributor to the difference in SW radiation. We show that boundary-layer stability and relative humidity fields are very similar in GA7.0 and MERRA-2, and unlikely to be the cause of the different cloud representation, suggesting that subgrid-scale parametrisations are responsible for the difference between the models. |
format |
Text |
author |
Kuma, Peter McDonald, Adrian J. Morgenstern, Olaf Alexander, Simon P. Cassano, John J. Garrett, Sally Halla, Jamie Hartery, Sean Harvey, Mike J. Parsons, Simon Plank, Graeme Varma, Vidya Williams, Jonny |
spellingShingle |
Kuma, Peter McDonald, Adrian J. Morgenstern, Olaf Alexander, Simon P. Cassano, John J. Garrett, Sally Halla, Jamie Hartery, Sean Harvey, Mike J. Parsons, Simon Plank, Graeme Varma, Vidya Williams, Jonny Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations |
author_facet |
Kuma, Peter McDonald, Adrian J. Morgenstern, Olaf Alexander, Simon P. Cassano, John J. Garrett, Sally Halla, Jamie Hartery, Sean Harvey, Mike J. Parsons, Simon Plank, Graeme Varma, Vidya Williams, Jonny |
author_sort |
Kuma, Peter |
title |
Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations |
title_short |
Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations |
title_full |
Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations |
title_fullStr |
Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations |
title_full_unstemmed |
Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations |
title_sort |
evaluation of southern ocean cloud in the hadgem3 general circulation model and merra-2 reanalysis using ship-based observations |
publishDate |
2019 |
url |
https://doi.org/10.5194/acp-2019-201 https://www.atmos-chem-phys-discuss.net/acp-2019-201/ |
long_lat |
ENVELOPE(12.615,12.615,65.816,65.816) |
geographic |
Austral Indian Merra Ross Sea Southern Ocean |
geographic_facet |
Austral Indian Merra Ross Sea Southern Ocean |
genre |
Ross Sea Southern Ocean |
genre_facet |
Ross Sea Southern Ocean |
op_source |
eISSN: 1680-7324 |
op_relation |
doi:10.5194/acp-2019-201 https://www.atmos-chem-phys-discuss.net/acp-2019-201/ |
op_doi |
https://doi.org/10.5194/acp-2019-201 |
_version_ |
1766179785096036352 |