Critical Southern Ocean climate model biases traced to atmospheric model cloud errors

Hyder, Patrick; Edwards, John M.; Allan, Richard P.; Hewitt, Helene T.; Bracegirdle, Thomas J.; Gregory, Jonathan M.; Wood, Richard; Meijers, Andrew J. S.; Mulcahy, Jane; Field, Paul R.; Furtado, Kalli; Bodas‐Salcedo, Alejandro; Williams, Keith D.; Copsey, Dan; Josey, Simon A.; Liu, Chunlei; Roberts, C. D.; Sánchez, Claudio; Ridley, Jeff; Thorpe, Livia; Hardiman, Steven C.; Mayer, Michael; Berry, David I.; Belcher, Stephen E.

doi:10.1038/s41467-018-05634-2

Cited by 156 publications

(160 citation statements)

References 75 publications

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“…The |CRE| is similar to the CREM pd in Williams and Webb (2009) and the TAFB in Hyder et al (2018). ΔCRE is the magnitude of the mean difference in CRE between the model and observations, while |CRE| is the integrated cluster error.…”

Section: Methodsmentioning

confidence: 63%

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Cluster‐Based Evaluation of Model Compensating Errors: A Case Study of Cloud Radiative Effect in the Southern Ocean

Schuddeboom

Varma

McDonald

et al. 2019

Geophysical Research Letters

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Model evaluation is difficult and generally relies on analysis that can mask compensating errors. This paper defines new metrics, using clusters generated from a machine learning algorithm, to estimate mean and compensating errors in different model runs. As a test case, we investigate the Southern Ocean shortwave radiative bias using clusters derived by applying self‐organizing maps to satellite data. In particular, the effects of changing cloud phase parameterizations in the MetOffice Unified Model are examined. Differences in cluster properties show that the regional radiative biases are substantially different than the global bias, with two distinct regions identified within the Southern Ocean, each with a different signed bias. Changing cloud phase parameterizations can reduce errors at higher latitudes but increase errors at lower latitudes of the Southern Ocean. Ranking the parameterizations often shows a contrast in mean and compensating errors, notably in all cases large compensating errors remain.

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Section: Methodsmentioning

confidence: 63%

“…These approaches can hide compensating errors, giving the false appearance of accuracy (Hyder et al, 2018;Jakob, 2003). These approaches can hide compensating errors, giving the false appearance of accuracy (Hyder et al, 2018;Jakob, 2003).…”

Section: Introductionmentioning

confidence: 99%

Cluster‐Based Evaluation of Model Compensating Errors: A Case Study of Cloud Radiative Effect in the Southern Ocean

Schuddeboom

Varma

McDonald

et al. 2019

Geophysical Research Letters

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“…Figure , and analysis of zonal means of the feedback parameter (not shown), shows that the Mic.MixedPhase subpackage is the leading contributor to the Mic package, although the contribution of the Mic.WarmRain subpackage is nonnegligible. The Mic.MixedPhase subpackage was introduced to reduce the Southern Ocean shortwave bias present in previous UM configurations (Hyder et al, ; Walters et al, ). Until recently, this bias has been common to many climate models, due to the lack of supercooled liquid cloud (Bodas‐Salcedo et al, , ).…”

Section: Package Testing Resultsmentioning

confidence: 99%

Strong Dependence of Atmospheric Feedbacks on Mixed‐Phase Microphysics and Aerosol‐Cloud Interactions in HadGEM3

Bodas‐Salcedo

Mulcahy

Andrews

et al. 2019

J Adv Model Earth Syst

121

132

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We analyze the atmospheric processes that explain the large changes in radiative feedbacks between the two latest climate configurations of the Hadley Centre Global Environmental model. We use a large set of atmosphere‐only climate change simulations (amip and amip‐p4K) to separate the contributions to the differences in feedback parameter from all the atmospheric model developments between the two latest model configurations. We show that the differences are mostly driven by changes in the shortwave cloud radiative feedback in the midlatitudes, mainly over the Southern Ocean. Two new schemes explain most of the differences: the introduction of a new aerosol scheme and the development of a new mixed‐phase cloud scheme. Both schemes reduce the strength of the preexisting shortwave negative cloud feedback in the midlatitudes. The new aerosol scheme dampens a strong aerosol‐cloud interaction, and it also suppresses a negative clear‐sky shortwave feedback. The mixed‐phase scheme increases the amount of cloud liquid water path (LWP) in the present day and reduces the increase in LWP with warming. Both changes contribute to reducing the negative radiative feedback of the increase of LWP in the warmer climate. The mixed‐phase scheme also enhances a strong, preexisting, positive cloud fraction feedback. We assess the realism of the changes by comparing present‐day simulations against observations and discuss avenues that could help constrain the relevant processes.

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“…The model systematically overestimates the OSW in the NH and underestimates the OSW in the SH particularly in the stratocumulus regions of the Southeast Pacific and South Atlantic as well as in the Southern Ocean. Such large biases in the Southern Ocean lead to significant warm sea surface temperature biases in this region when coupled to an ocean model (Bodas‐Salcedo et al, ; Hyder et al, ). In GA7.1, in the NH, the combination of lower N d and enhanced cloud droplet spectral dispersion increases the cloud r eff reducing the cloud albedo.…”

Section: Discussionmentioning

confidence: 99%

Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1

Mulcahy

Jones

Sellar

et al. 2018

J Adv Model Earth Syst

166

212

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Aerosol processes and, in particular, aerosol‐cloud interactions cut across the traditional physical‐Earth system boundary of coupled Earth system models and remain one of the key uncertainties in estimating anthropogenic radiative forcing of climate. Here we calculate the historical aerosol effective radiative forcing (ERF) in the HadGEM3‐GA7 climate model in order to assess the suitability of this model for inclusion in the UK Earth system model, UKESM1. The aerosol ERF, calculated for the year 2000 relative to 1850, is large and negative in the standard GA7 model leading to an unrealistic negative total anthropogenic forcing over the twentieth century. We show how underlying assumptions and missing processes in both the physical model and aerosol parameterizations lead to this large aerosol ERF. A number of model improvements are investigated to assess their impact on the aerosol ERF. These include an improved representation of cloud droplet spectral dispersion, updates to the aerosol activation scheme, and black carbon optical properties. One of the largest contributors to the aerosol forcing uncertainty is insufficient knowledge of the preindustrial aerosol climate. We evaluate the contribution of uncertainties in the natural marine emissions of dimethyl sulfide and organic aerosol to the ERF. The combination of model improvements derived from these studies weakens the aerosol ERF by up to 50% of the original value and leads to a total anthropogenic historical forcing more in line with assessed values.

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Critical Southern Ocean climate model biases traced to atmospheric model cloud errors

Cited by 156 publications

References 75 publications

Cluster‐Based Evaluation of Model Compensating Errors: A Case Study of Cloud Radiative Effect in the Southern Ocean

Cluster‐Based Evaluation of Model Compensating Errors: A Case Study of Cloud Radiative Effect in the Southern Ocean

Strong Dependence of Atmospheric Feedbacks on Mixed‐Phase Microphysics and Aerosol‐Cloud Interactions in HadGEM3

Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1

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