scholarly journals Representing ozone extremes in European megacities: the importance of resolution in a global chemistry climate model

2013 ◽  
Vol 13 (10) ◽  
pp. 27423-27458
Author(s):  
Z. S. Stock ◽  
M. R. Russo ◽  
J. A. Pyle
Keyword(s):  
Atmospheric Chemistry ◽  
Urban Areas ◽  
Climate Models ◽  
Climate Model ◽  
Surface Ozone ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Ozone Concentrations ◽  
Coarse Resolution ◽  
The Impact

Abstract. The continuing growth of the world's urban population has led to an increasing number of cities with more than 10 million inhabitants. The higher emissions of pollutants, coupled to higher population density, makes predictions of air quality in these megacities of particular importance from both a science and a policy perspective. Global climate models are typically run at coarse resolution to enable both the efficient running of long time integrations, and the ability to run multiple future climate scenarios. However, when considering surface ozone concentrations at the local scale, coarse resolution can lead to inaccuracies arising from the highly non-linear ozone chemistry and the sensitivity of ozone to the distribution of its precursors on smaller scales. In this study, we use UM-UKCA, a global atmospheric chemistry model, coupled to the UK Met Office Unified Model, to investigate the impact of model resolution on tropospheric ozone, ranging from global to local scales. We focus on the model's ability to represent the probability of high ozone concentrations in the summer and low ozone concentrations, associated with polluted megacity environments, in the winter, and how this varies with horizontal resolution. We perform time-slice integrations with two model configurations at typical climate resolution (CR, ~150 km) and at a higher resolution (HR, ~40 km). The CR configuration leads to overestimation of ozone concentrations on both regional and local scales, while it gives broadly similar results to the HR configuration on the global scale. The HR configuration is found to produce a more realistic diurnal cycle of ozone concentrations and to give a better representation of the probability density function of ozone values in urban areas such as the megacities of London and Paris. We discuss the possible causes for the observed difference in model behaviour between CR and HR configurations and estimate the relative contribution of chemical and meteorological factors at the different scales.

scholarly journals Representing ozone extremes in European megacities: the importance of resolution in a global chemistry climate model

2014 ◽  
Vol 14 (8) ◽  
pp. 3899-3912 ◽  
Author(s):  
Z. S. Stock ◽  
M. R. Russo ◽  
J. A. Pyle
Keyword(s):  
Atmospheric Chemistry ◽  
Urban Areas ◽  
Climate Models ◽  
Climate Model ◽  
Surface Ozone ◽  
Global Climate Models ◽  
Ozone Concentrations ◽  
Coarse Resolution ◽  
Highly Nonlinear ◽  
The Impact

Abstract. The continuing growth of the world's urban population has led to an increasing number of cities with more than 10 million inhabitants. The higher emissions of pollutants, coupled to higher population density, makes predictions of air quality in these megacities of particular importance from both a science and a policy perspective. Global climate models are typically run at coarse resolution to enable both the efficient running of long time integrations, and the ability to run multiple future climate scenarios. However, when considering surface ozone concentrations at the local scale, coarse resolution can lead to inaccuracies arising from the highly nonlinear ozone chemistry and the sensitivity of ozone to the distribution of its precursors on smaller scales. In this study, we use UM-UKCA, a global atmospheric chemistry model, coupled to the UK Met Office Unified Model, to investigate the impact of model resolution on tropospheric ozone, ranging from global to local scales. We focus on the model's ability to represent the probability of high ozone concentrations in the summer and low ozone concentrations, associated with polluted megacity environments, in the winter, and how this varies with horizontal resolution. We perform time-slice integrations with two model configurations at typical climate resolution (CR, ~150 km) and at a higher resolution (HR, ~40 km). The CR configuration leads to overestimation of ozone concentrations on both regional and local scales, while it gives broadly similar results to the HR configuration on the global scale. The HR configuration is found to produce a more realistic diurnal cycle of ozone concentrations and to give a better representation of the probability density function of ozone values in urban areas such as the megacities of London and Paris. We find the observed differences in model behaviour between CR and HR configurations to be largely caused by chemical differences during the winter and meteorological differences during the summer.

scholarly journals The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models

2020 ◽  
Vol 6 (2) ◽  
pp. 115-139
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner
Keyword(s):  
High Resolution ◽  
Observational Data ◽  
Climate Models ◽  
Climate Model ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Boreal Winter ◽  
Weather Stations ◽  
High Resolution Models ◽  
The Impact

Abstract. Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern global high-resolution models with a horizontal resolution of tens of kilometers, this is an oversight since there are likely grid cells where the physical output of a climate model is compared with a statistically interpolated quantity instead of actual measurements of the climate system. In this paper, we quantify the impact of geographic sampling on the relative performance of high-resolution climate model representations of precipitation extremes in boreal winter (December–January–February) over the contiguous United States (CONUS), comparing model output from five early submissions to the HighResMIP subproject of the CMIP6 experiment. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance. Across the models considered, failing to account for sampling impacts the different metrics (extreme bias, spatial pattern correlation, and spatial variability) in different ways (both increasing and decreasing). We argue that the geographic sampling of weather stations should be accounted for in order to yield a more straightforward and appropriate comparison between models and observational data sets, particularly for high-resolution models with a horizontal resolution of tens of kilometers. While we focus on the CONUS in this paper, our results have important implications for other global land regions where the sampling problem is more severe.

scholarly journals Modelling the impact of megacities on local, regional and global tropospheric ozone and the deposition of nitrogen species

2013 ◽  
Vol 13 (24) ◽  
pp. 12215-12231 ◽  
Author(s):  
Z. S. Stock ◽  
M. R. Russo ◽  
T. M. Butler ◽  
A. T. Archibald ◽  
M. G. Lawrence ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Climate Model ◽  
Surface Ozone ◽  
Global Scale ◽  
Chemical Environment ◽  
Ozone Production ◽  
The Uk ◽  
The Impact ◽  
Local Emissions

Abstract. We examine the effects of ozone precursor emissions from megacities on present-day air quality using the global chemistry–climate model UM-UKCA (UK Met Office Unified Model coupled to the UK Chemistry and Aerosols model). The sensitivity of megacity and regional ozone to local emissions, both from within the megacity and from surrounding regions, is important for determining air quality across many scales, which in turn is key for reducing human exposure to high levels of pollutants. We use two methods, perturbation and tagging, to quantify the impact of megacity emissions on global ozone. We also completely redistribute the anthropogenic emissions from megacities, to compare changes in local air quality going from centralised, densely populated megacities to decentralised, lower density urban areas. Focus is placed not only on how changes to megacity emissions affect regional and global NOx and O3, but also on changes to NOy deposition and to local chemical environments which are perturbed by the emission changes. The perturbation and tagging methods show broadly similar megacity impacts on total ozone, with the perturbation method underestimating the contribution partially because it perturbs the background chemical environment. The total redistribution of megacity emissions locally shifts the chemical environment towards more NOx-limited conditions in the megacities, which is more conducive to ozone production, and monthly mean surface ozone is found to increase up to 30% in megacities, depending on latitude and season. However, the displacement of emissions has little effect on the global annual ozone burden (0.12% change). Globally, megacity emissions are shown to contribute ~3% of total NOy deposition. The changes in O3, NOx and NOy deposition described here are useful for quantifying megacity impacts and for understanding the sensitivity of megacity regions to local emissions. The small global effects of the 100% redistribution carried out in this study suggest that the distribution of emissions on the local scale is unlikely to have large implications for chemistry–climate processes on the global scale.

scholarly journals Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Open Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Current Model ◽  
Global Climate Models ◽  
The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

scholarly journals Assessing Future Spatio-Temporal Changes in Crop Suitability and Planting Season over West Africa: Using the Concept of Crop-Climate Departure

Climate ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 102 ◽  
Author(s):  
Temitope S. Egbebiyi ◽  
Chris Lennard ◽  
Olivier Crespo ◽  
Phillip Mukwenha ◽  
Shakirudeen Lawal ◽  
...  
Keyword(s):  
West Africa ◽  
Linear Correlation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Crop Suitability ◽  
Suitable Area ◽  
The Impact ◽  
Planting Season

The changing climate is posing significant threats to agriculture, the most vulnerable sector, and the main source of livelihood in West Africa. This study assesses the impact of the climate-departure on the crop suitability and planting month over West Africa. We used 10 CMIP5 Global climate models bias-corrected simulations downscaled by the CORDEX regional climate model, RCA4 to drive the crop suitability model, Ecocrop. We applied the concept of the crop-climate departure (CCD) to evaluate future changes in the crop suitability and planting month for five crop types, cereals, legumes, fruits, root and tuber and horticulture over the historical and future months. Our result shows a reduction (negative linear correlation) and an expansion (positive linear correlation) in the suitable area and crop suitability index value in the Guinea-Savanna and Sahel (southern Sahel) zone, respectively. The horticulture crop was the most negatively affected with a decrease in the suitable area while cereals and legumes benefited from the expansion in suitable areas into the Sahel zone. In general, CCD would likely lead to a delay in the planting season by 2–4 months except for the orange and early planting dates by about 2–3 months for cassava. No projected changes in the planting month are observed for the plantain and pineapple which are annual crops. The study is relevant for a short and long-term adaptation option and planning for future changes in the crop suitability and planting month to improve food security in the region.

Impact of a quasi-stochastic cellular automaton backscatter scheme on the systematic error and seasonal prediction skill of a global climate model

2008 ◽  
Vol 366 (1875) ◽  
pp. 2559-2577 ◽  
Author(s):  
J Berner ◽  
F.J Doblas-Reyes ◽  
T.N Palmer ◽  
G Shutts ◽  
A Weisheimer
Keyword(s):  
Cellular Automaton ◽  
Systematic Error ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Seasonal Prediction ◽  
Global Climate Models ◽  
Seasonal Forecasts ◽  
The Impact

The impact of a nonlinear dynamic cellular automaton (CA) model, as a representation of the partially stochastic aspects of unresolved scales in global climate models, is studied in the European Centre for Medium Range Weather Forecasts coupled ocean–atmosphere model. Two separate aspects are discussed: impact on the systematic error of the model, and impact on the skill of seasonal forecasts. Significant reductions of systematic error are found both in the tropics and in the extratropics. Such reductions can be understood in terms of the inherently nonlinear nature of climate, in particular how energy injected by the CA at the near-grid scale can backscatter nonlinearly to larger scales. In addition, significant improvements in the probabilistic skill of seasonal forecasts are found in terms of a number of different variables such as temperature, precipitation and sea-level pressure. Such increases in skill can be understood both in terms of the reduction of systematic error as mentioned above, and in terms of the impact on ensemble spread of the CA's representation of inherent model uncertainty.

Testing robustness of co-existing climate states

2021 ◽  
Author(s):  
Charline Ragon ◽  
Valerio Lembo ◽  
Valerio Lucarini ◽  
Christian Vérard ◽  
Jérôme Kasparian ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Water Mass ◽  
Hydrological Cycle ◽  
Initial Conditions ◽  
Frictional Heating ◽  
Horizontal Resolution ◽  
Climate Dynamics ◽  
Mechanical Work ◽  
The Impact

<p><span>The climate can be regarded as a stationary non-equilibrium statistical system (Gallavotti 2006): a continuous and spatially inhomogeneous input of solar energy enters at the top-of-atmosphere and compensates the action of non-conservative forces, mainly occurring at small scales, to give rise to a statistically steady state (or attractor) for the whole climate. </span></p><p><span>Depending on the initial conditions and the range of forcing, all other parameters being the same, some climate models have the property to settle down on different attractors. </span><span>Multi-stability reflects how energy, water mass and entropy can be re-distributed in multiple ways among the climate components, such as the atmosphere, the ocean or the ice, through a different balance between nonlinear mechanisms. </span></p><p><span>Starting from a configuration where competing climate attractors occur under the same forcing, we have explored their robustness performing two kinds of numerical experiment. </span><span>First, we have investigated the impact of frictional heating on the overall energy balance and we have shown that such contribution, generally neglected in the atmospheric component of climate models, has crucial </span><span>consequences on conservation properties: it improves the energy imbalance at top-of-atmosphere, typically non negligible in coarse simulations (Wild et al. 2020), strengthens the hydrological cycle, </span><span>mitigates the mechanical work associated to atmospheric circulation intensity </span><span>and reduces the heat transport peaks in the ocean. </span><span>Second, we have compared two bulk formulas for the cloud albedo, one where it is constant everywhere and the other where it increases with latitude, as implemented in the new version of the atmospheric module SPEEDY in order to improve comparisons with observational data (Kucharski 2013). We have che</span><span>cked that this new parameterization does not affect energy and water-mass imbalances, while reduces global temperature and water-mass transport on the attractor, giving rise to a larger conversion of heat into mechanical work in the atmosphere.</span></p><p><span>In order to perform such studies, we have run the climate model MITgcm on coupled aquaplanets at 2.8 horizontal resolution until steady states are reached (Brunetti el al. 2019) and we have applied the Thermodynamic Diagnostic Tool (<em>TheDiaTo</em>, Lembo et al. 2019). </span></p><p> </p><p><span>References: </span></p><p><span>Brunetti, Kasparian, Vérard, Climate Dynamics 53, 6293 (2019)</span></p><p><span>Gallavotti, </span>Math. Phys. 3, 530<span> (2006)</span></p><p>Kucharski<span> et al.</span>, Bulletin of the American Meteorological Society 94, 25<span> (2013)</span></p><p>Lembo, Lunkeit, Lucarini, Geoscientific Model Development 12, 3805<span> (2019)</span></p><p><span>Wild, </span>Climate Dynamics 55, 553<span> (2020)</span></p>

scholarly journals Process-oriented analysis of aircraft soot-cirrus interactions constrains the climate impact of aviation

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Bernd Kärcher ◽  
Fabian Mahrt ◽  
Claudia Marcolli
Keyword(s):  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Climate Impact ◽  
Global Climate Models ◽  
Soot Particles ◽  
Cloud Ice ◽  
The Impact

AbstractFully accounting for the climate impact of aviation requires a process-level understanding of the impact of aircraft soot particle emissions on the formation of ice clouds. Assessing this impact with the help of global climate models remains elusive and direct observations are lacking. Here we use a high-resolution cirrus column model to investigate how aircraft-emitted soot particles, released after ice crystals sublimate at the end of the lifetime of contrails and contrail cirrus, perturb the formation of cirrus. By allying cloud simulations with a measurement-based description of soot-induced ice formation, we find that only a small fraction (<1%) of the soot particles succeeds in forming cloud ice alongside homogeneous freezing of liquid aerosol droplets. Thus, soot-perturbed and homogeneously-formed cirrus fundamentally do not differ in optical depth. Our results imply that climate model estimates of global radiative forcing from interactions between aircraft soot and large-scale cirrus may be overestimates. The improved scientific understanding reported here provides a process-based underpinning for improved climate model parametrizations and targeted field observations.

scholarly journals Biomass burning related ozone damage on vegetation over the Amazon forest: a model sensitivity study

2015 ◽  
Vol 15 (5) ◽  
pp. 2791-2804 ◽  
Author(s):  
F. Pacifico ◽  
G. A. Folberth ◽  
S. Sitch ◽  
J. M. Haywood ◽  
L. V. Rizzo ◽  
...  
Keyword(s):  
South America ◽  
Biomass Burning ◽  
Net Primary Productivity ◽  
Climate Model ◽  
Surface Ozone ◽  
Sensitivity Study ◽  
Amazon Forest ◽  
Vegetation Productivity ◽  
Ozone Concentrations ◽  
The Impact

Abstract. The HadGEM2 earth system climate model was used to assess the impact of biomass burning on surface ozone concentrations over the Amazon forest and its impact on vegetation, under present-day climate conditions. Here we consider biomass burning emissions from wildfires, deforestation fires, agricultural forest burning, and residential and commercial combustion. Simulated surface ozone concentration is evaluated against observations taken at two sites in the Brazilian Amazon forest for years 2010 to 2012. The model is able to reproduce the observed diurnal cycle of surface ozone mixing ratio at the two sites, but overestimates the magnitude of the monthly averaged hourly measurements by 5–15 ppb for each available month at one of the sites. We vary biomass burning emissions over South America by ±20, 40, 60, 80 and 100% to quantify the modelled impact of biomass burning on surface ozone concentrations and ozone damage on vegetation productivity over the Amazon forest. We used the ozone damage scheme in the "high" sensitivity mode to give an upper limit for this effect. Decreasing South American biomass burning emissions by 100% (i.e. to zero) reduces surface ozone concentrations (by about 15 ppb during the biomass burning season) and suggests a 15% increase in monthly mean net primary productivity averaged over the Amazon forest, with local increases up to 60%. The simulated impact of ozone damage from present-day biomass burning on vegetation productivity is about 230 TgC yr−1. Taking into account that uncertainty in these estimates is substantial, this ozone damage impact over the Amazon forest is of the same order of magnitude as the release of carbon dioxide due to fire in South America; in effect it potentially doubles the impact of biomass burning on the carbon cycle.

Global hydrology modelling and uncertainty: running multiple ensembles with a campus grid

2010 ◽  
Vol 368 (1926) ◽  
pp. 4005-4021 ◽  
Author(s):  
Simon N. Gosling ◽  
Dan Bretherton ◽  
Keith Haines ◽  
Nigel W. Arnell
Keyword(s):  
Climate Change ◽  
Water Resource ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Resource Stress ◽  
Runoff Changes ◽  
Campus Grid ◽  
The Impact

Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this ‘climate model structural uncertainty’ is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change.

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