scholarly journals Review of Wild et al., Global sensitivity analysis of chemistry-climate model budgets...

2019 ◽  
Author(s):  
Anonymous
2015 ◽  
Vol 6 (1) ◽  
pp. 205-224 ◽  
Author(s):  
N. Bounceur ◽  
M. Crucifix ◽  
R. D. Wilkinson

Abstract. A global sensitivity analysis is performed to describe the effects of astronomical forcing on the climate–vegetation system simulated by the model of intermediate complexity LOVECLIM in interglacial conditions. The methodology relies on the estimation of sensitivity measures, using a Gaussian process emulator as a fast surrogate of the climate model, calibrated on a set of well-chosen experiments. The outputs considered are the annual mean temperature and precipitation and the growing degree days (GDD). The experiments were run on two distinct land surface schemes to estimate the importance of vegetation feedbacks on climate variance. This analysis provides a spatial description of the variance due to the factors and their combinations, in the form of "fingerprints" obtained from the covariance indices. The results are broadly consistent with the current under-standing of Earth's climate response to the astronomical forcing. In particular, precession and obliquity are found to contribute in LOVECLIM equally to GDD in the Northern Hemisphere, and the effect of obliquity on the response of Southern Hemisphere temperature dominates precession effects. Precession dominates precipitation changes in subtropical areas. Compared to standard approaches based on a small number of simulations, the methodology presented here allows us to identify more systematically regions susceptible to experiencing rapid climate change in response to the smooth astronomical forcing change. In particular, we find that using interactive vegetation significantly enhances the expected rates of climate change, specifically in the Sahel (up to 50% precipitation change in 1000 years) and in the Canadian Arctic region (up to 3° in 1000 years). None of the tested astronomical configurations were found to induce multiple steady states, but, at low obliquity, we observed the development of an oscillatory pattern that has already been reported in LOVECLIM. Although the mathematics of the analysis are fairly straightforward, the emulation approach still requires considerable care in its implementation. We discuss the effect of the choice of length scales and the type of emulator, and estimate uncertainties associated with specific computational aspects, to conclude that the principal component emulator is a good option for this kind of application.


2014 ◽  
Vol 5 (2) ◽  
pp. 901-943 ◽  
Author(s):  
N. Bounceur ◽  
M. Crucifix ◽  
R. D. Wilkinson

Abstract. A global sensitivity analysis is used to describe the response of the Earth Climate Model of Intermediate Complexity LOVECLIM to components of the astronomical forcing (longitude of perihelion, obliquity, and eccentricity) assuming interglacial boundary conditions. Compared to previous studies, the sensitivity is global in the sense that it considers the full range of astronomical forcing that occurred during the Quaternary. We provide a geographical description of the variance due to the different components and their combinations and identify non-linear responses. The methodology relies on the estimation of sensitivity measures, which due to the computational cost of LOVECLIM cannot be obtained directly. Instead, we use a fast surrogate of the climate model, called an emulator, in place of the simulator. A space filling design (a maximin Latin hypercube constrained to span the range of astronomical forcings characterising the Pleistocene) is used to determine a set of experiments to run, which are then used to train a reduced-rank Gaussian process emulator. The simulator outputs considered are the principal modes of the annual mean temperature, precipitation, and the growing degree days, extracted using a principal component analysis. The experiments are run on two distinct land surface schemes to address the effect of vegetation response on climate. Sensitivity to initial conditions is also explicitly assessed. Precession and obliquity are found to contribute equally to growing degree days (GDD) in the Northern Hemisphere, and the effects of obliquity on the response of Southern Hemisphere temperature dominate precession effects. Further, compared to the original land-surface scheme with fixed vegetation, the LOVECLIM interactive vegetation induces non-linear responses in the Sahel-Sahara and Arctic sea-ice area. Finally, we find that there is no synergy between obliquity and precession.


2020 ◽  
Vol 20 (7) ◽  
pp. 4047-4058 ◽  
Author(s):  
Oliver Wild ◽  
Apostolos Voulgarakis ◽  
Fiona O'Connor ◽  
Jean-François Lamarque ◽  
Edmund M. Ryan ◽  
...  

Abstract. Projections of future atmospheric composition change and its impacts on air quality and climate depend heavily on chemistry–climate models that allow us to investigate the effects of changing emissions and meteorology. These models are imperfect as they rely on our understanding of the chemical, physical and dynamical processes governing atmospheric composition, on the approximations needed to represent these numerically, and on the limitations of the observations required to constrain them. Model intercomparison studies show substantial diversity in results that reflect underlying uncertainties, but little progress has been made in explaining the causes of this or in identifying the weaknesses in process understanding or representation that could lead to improved models and to better scientific understanding. Global sensitivity analysis provides a valuable method of identifying and quantifying the main causes of diversity in current models. For the first time, we apply Gaussian process emulation with three independent global chemistry-transport models to quantify the sensitivity of ozone and hydroxyl radicals (OH) to important climate-relevant variables, poorly characterised processes and uncertain emissions. We show a clear sensitivity of tropospheric ozone to atmospheric humidity and precursor emissions which is similar for the models, but find large differences between models for methane lifetime, highlighting substantial differences in the sensitivity of OH to primary and secondary production. This approach allows us to identify key areas where model improvements are required while providing valuable new insight into the processes driving tropospheric composition change.


2019 ◽  
Author(s):  
Aryeh Feinberg ◽  
Moustapha Maliki ◽  
Andrea Stenke ◽  
Bruno Sudret ◽  
Thomas Peter ◽  
...  

Abstract. An estimated 0.5–1 billion people globally have inadequate intakes of selenium (Se), due to a lack of bioavailable Se in agricultural soils. Deposition from the atmosphere, especially through precipitation, is an important source of Se to soils. However, very little is known about the atmospheric cycling of Se. It has therefore been difficult to predict how far Se travels in the atmosphere and where it deposits. To answer these questions, we have built the first global atmospheric Se model by implementing Se chemistry into an aerosol–chemistry–climate model, SOCOL-AER. In the model, we include information from the literature about the emissions, speciation, and chemical transformation of atmospheric Se. Natural processes and anthropogenic activities emit volatile Se compounds, which oxidize quickly and partition to the particulate phase. Our model tracks the transport and deposition of Se in 7 gas-phase species and 41 aerosol tracers. However, there are large uncertainties associated with many of the model's input parameters. In order to identify which model uncertainties are the most important for understanding the atmospheric Se cycle, we conducted a global sensitivity analysis with 34 input parameters related to Se chemistry, Se emissions, and the interaction of Se with aerosols. In the first bottom-up estimate of its kind, we have calculated a median global atmospheric lifetime of 4.4 d (days), ranging from 2.9–6.4 d (2nd–98th percentile) given the uncertainties of the input parameters. The uncertainty in the Se lifetime is mainly driven by the uncertainty in the carbonyl selenide (OCSe) oxidation rate and the lack of tropospheric aerosol species other than sulfate aerosols in SOCOL-AER. In contrast to uncertainties in Se lifetime, the uncertainty in deposition flux maps are governed by Se emission factors, with all four Se sources (volcanic, marine biosphere, terrestrial biosphere, and anthropogenic emissions) contributing equally to the uncertainty in deposition over agricultural areas. We evaluated the simulated Se wet deposition fluxes from SOCOL-AER with a compiled database of rainwater Se measurements, since wet deposition contributes around 80 % of total Se deposition. Despite difficulties in comparing a global, coarse resolution model with local measurements from a range of time periods, past Se wet deposition measurements are within the range of the model's 2nd–98th percentile at 79 % of background sites. This agreement validates the application of the SOCOL-AER model to identifying regions which are at risk of low atmospheric Se inputs. In order to constrain the uncertainty in Se deposition fluxes over agricultural soils we should prioritize field campaigns measuring Se emissions, rather than laboratory measurements of Se rate constants.


2019 ◽  
Author(s):  
Oliver Wild ◽  
Apostolos Voulgarakis ◽  
Fiona O'Connor ◽  
Jean-François Lamarque ◽  
Edmund M. Ryan ◽  
...  

Abstract. Projections of future atmospheric composition change and its impacts on air quality and climate depend heavily on chemistry-climate models that allow us to investigate the effects of changing emissions and meteorology. These models are imperfect as they rely on our understanding of the chemical, physical and dynamical processes governing atmospheric composition, on the approximations needed to represent these numerically, and on the limitations of the observations required to constrain them. Model intercomparison studies show substantial diversity in results that reflect underlying uncertainties, but little progress has been made in explaining the causes of this or in identifying the weaknesses in process understanding or representation that could lead to improved models and to better scientific understanding. Global sensitivity analysis provides a valuable method of identifying and quantifying the main causes of diversity in current models. For the first time, we apply Gaussian process emulation with three independent global chemistry transport models to quantify the sensitivity of ozone and hydroxyl radicals (OH) to important climate-relevant variables, poorly-characterized processes and uncertain emissions. We show a clear sensitivity of tropospheric ozone to atmospheric humidity and precursor emissions which is similar for the models, but find large differences between models for methane lifetime, highlighting substantial differences in the sensitivity of OH to primary and secondary production. This approach allows us to identify key areas where model improvements are required while providing valuable new insight into the processes driving tropospheric composition change.


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