scholarly journals Supplementary material to "Robust observational constraint of uncertain aerosol processes and emissions in a climate model and the effect on aerosol radiative forcing"

2019 ◽  
Author(s):  
Jill S. Johnson ◽  
Leighton A. Regayre ◽  
Masaru Yoshioka ◽  
Kirsty J. Pringle ◽  
Steven T. Turnock ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Observational Constraint ◽  
Aerosol Radiative Forcing ◽  
Supplementary Material ◽  
Aerosol Radiative

scholarly journals The importance of comprehensive parameter sampling and multiple observations for robust constraint of aerosol radiative forcing

2018 ◽  
Author(s):  
Jill S. Johnson ◽  
Leighton A. Regayre ◽  
Masaru Yoshioka ◽  
Kirsty J. Pringle ◽  
Lindsay A. Lee ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Model Uncertainty ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Observational Constraint ◽  
Aerosol Radiative Forcing ◽  
Multiple Observations ◽  
Aerosol Radiative

Abstract. Observational constraint of simulated aerosol and cloud properties is an essential part of building trustworthy climate models for calculating aerosol radiative forcing. Models are usually tuned to achieve good agreement with observations, but tuning produces just one of many potential variants of a model, so the model uncertainty cannot be determined. Here we estimate the uncertainty in aerosol effective radiative forcing (ERF) in a tuned climate model by constraining 4 million variants of the HadGEM3-UKCA aerosol-climate model to match nine common observations (top-of-atmosphere shortwave flux, aerosol optical depth, PM2.5, cloud condensation nuclei, concentrations of sulphate, black carbon and organic carbon, as well as decadal trends in aerosol optical depth and surface shortwave radiation.) The model uncertainty is calculated by using a perturbed parameter ensemble that samples twenty-seven uncertainties in both the aerosol model and the physical climate model. Focusing over Europe, we show that the aerosol ERF uncertainty can be reduced by about 30 % by constraining it to the nine observations, demonstrating that producing climate models with an observationally plausible base state can contribute to narrowing the uncertainty in aerosol ERF. However, the uncertainty in the aerosol ERF after observational constraint is large compared to the typical spread of a multi-model ensemble. Our results therefore raise questions about whether the underlying multi-model uncertainty would be larger if similar approaches as adopted here were applied more widely. It is hoped that aerosol ERF uncertainty can be further reduced by introducing process-related constraints, however, any such results will be robust only if the enormous number of potential model variants is explored.

scholarly journals The importance of comprehensive parameter sampling and multiple observations for robust constraint of aerosol radiative forcing

2018 ◽  
Vol 18 (17) ◽  
pp. 13031-13053 ◽  
Author(s):  
Jill S. Johnson ◽  
Leighton A. Regayre ◽  
Masaru Yoshioka ◽  
Kirsty J. Pringle ◽  
Lindsay A. Lee ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Model Uncertainty ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Observational Constraint ◽  
Aerosol Radiative Forcing ◽  
Multiple Observations ◽  
Aerosol Radiative

Abstract. Observational constraint of simulated aerosol and cloud properties is an essential part of building trustworthy climate models for calculating aerosol radiative forcing. Models are usually tuned to achieve good agreement with observations, but tuning produces just one of many potential variants of a model, so the model uncertainty cannot be determined. Here we estimate the uncertainty in aerosol effective radiative forcing (ERF) in a tuned climate model by constraining 4 million variants of the HadGEM3-UKCA aerosol–climate model to match nine common observations (top-of-atmosphere shortwave flux, aerosol optical depth, PM2.5, cloud condensation nuclei at 0.2 % supersaturation (CCN0.2), and concentrations of sulfate, black carbon and organic carbon, as well as decadal trends in aerosol optical depth and surface shortwave radiation.) The model uncertainty is calculated by using a perturbed parameter ensemble that samples 27 uncertainties in both the aerosol model and the physical climate model, and we use synthetic observations generated from the model itself to determine the potential of each observational type to constrain this uncertainty. Focusing over Europe in July, we show that the aerosol ERF uncertainty can be reduced by about 30 % by constraining it to the nine observations, demonstrating that producing climate models with an observationally plausible “base state” can contribute to narrowing the uncertainty in aerosol ERF. However, the uncertainty in the aerosol ERF after observational constraint is large compared to the typical spread of a multi-model ensemble. Our results therefore raise questions about whether the underlying multi-model uncertainty would be larger if similar approaches as adopted here were applied more widely. The approach presented in this study could be used to identify the most effective observations for model constraint. It is hoped that aerosol ERF uncertainty can be further reduced by introducing process-related constraints; however, any such results will be robust only if the enormous number of potential model variants is explored.

Aerosol Radiative Forcing and Forcing Efficiency in the UVB for Regions Affected by Saharan and Asian Mineral Dust

2009 ◽  
Vol 66 (4) ◽  
pp. 1033-1040 ◽  
Author(s):  
O. E. García ◽  
A. M. Díaz ◽  
F. J. Expósito ◽  
J. P. Díaz ◽  
A. Redondas ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Radiative Forcing ◽  
Climate Model ◽  
Mineral Dust ◽  
Global Climate ◽  
Global Climate Model ◽  
Aerosol Radiative Forcing ◽  
Benchmark Database ◽  
Aerosol Radiative

Abstract The influence of mineral dust on ultraviolet energy transfer is studied for two different mineralogical origins. The aerosol radiative forcing ΔF and the forcing efficiency at the surface ΔFeff in the range 290–325 nm were estimated in ground-based stations affected by the Saharan and Asian deserts during the dusty seasons. UVB solar measurements were taken from the World Ozone and Ultraviolet Data Center (WOUDC) for four Asian stations (2000–04) and from the Santa Cruz Observatory, Canary Islands (2002–03), under Gobi and Sahara Desert influences, respectively. The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth at 550 nm was used to characterize the aerosol load τ, whereas the aerosol index provided by the Total Ozone Mapping Spectrometer (TOMS) sensor was employed to identify the mineral dust events. The ΔF is strongly affected by the aerosol load, the values found being comparable in both regions during the dusty seasons. Under those conditions, ΔF values as large as −1.29 ± 0.53 W m−2 (τ550 = 0.48 ± 0.24) and −1.43 ± 0.38 W m−2 (τ550 = 0.54 ± 0.26) were reached under Saharan and Asian dust conditions, respectively. Nevertheless, significant differences have been observed in the aerosol radiative forcing per unit of aerosol optical depth in the slant path, τS. The maximum ΔFeff values associated with dust influences were −1.55 ± 0.20 W m−2 τS550−1 for the Saharan region and −0.95 ± 0.11 W m−2 τS550−1 in the Asian area. These results may be used as a benchmark database for establishing aerosol corrections in UV satellite products or in global climate model estimations.

scholarly journals Robust observational constraint of uncertain aerosol processes and emissions in a climate model and the effect on aerosol radiative forcing

2020 ◽  
Vol 20 (15) ◽  
pp. 9491-9524 ◽  
Author(s):  
Jill S. Johnson ◽  
Leighton A. Regayre ◽  
Masaru Yoshioka ◽  
Kirsty J. Pringle ◽  
Steven T. Turnock ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Probability Distributions ◽  
Cloud Droplet ◽  
Credible Interval ◽  
Observational Constraint ◽  
So2 Emissions ◽  
Aerosol Radiative Forcing ◽  
Standard Deviation Range ◽  
Hadley Centre

Abstract. The effect of observational constraint on the ranges of uncertain physical and chemical process parameters was explored in a global aerosol–climate model. The study uses 1 million variants of the Hadley Centre General Environment Model version 3 (HadGEM3) that sample 26 sources of uncertainty, together with over 9000 monthly aggregated grid-box measurements of aerosol optical depth, PM2.5, particle number concentrations, sulfate and organic mass concentrations. Despite many compensating effects in the model, the procedure constrains the probability distributions of parameters related to secondary organic aerosol, anthropogenic SO2 emissions, residential emissions, sea spray emissions, dry deposition rates of SO2 and aerosols, new particle formation, cloud droplet pH and the diameter of primary combustion particles. Observational constraint rules out nearly 98 % of the model variants. On constraint, the ±1σ (standard deviation) range of global annual mean direct radiative forcing (RFari) is reduced by 33 % to −0.14 to −0.26 W m−2, and the 95 % credible interval (CI) is reduced by 34 % to −0.1 to −0.32 W m−2. For the global annual mean aerosol–cloud radiative forcing, RFaci, the ±1σ range is reduced by 7 % to −1.66 to −2.48 W m−2, and the 95 % CI by 6 % to −1.28 to −2.88 W m−2. The tightness of the constraint is limited by parameter cancellation effects (model equifinality) as well as the large and poorly defined “representativeness error” associated with comparing point measurements with a global model. The constraint could also be narrowed if model structural errors that prevent simultaneous agreement with different measurement types in multiple locations and seasons could be improved. For example, constraints using either sulfate or PM2.5 measurements individually result in RFari±1σ ranges that only just overlap, which shows that emergent constraints based on one measurement type may be overconfident.

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