scholarly journals The influence of atmospheric circulation on the mid-Holocene climate of Europe: a data-model comparison

2013 ◽  
Vol 9 (5) ◽  
pp. 5569-5592 ◽  
Author(s):  
A. Mauri ◽  
B. A. S. Davis ◽  
P. M. Collins ◽  
J. O. Kaplan
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Data Model ◽  
Climate Model ◽  
Atmospheric Dynamics ◽  
Future Climate Change ◽  
Seasonal Temperature ◽  
Holocene Climate ◽  
Model Simulations

Abstract. The atmospheric circulation is a key area of uncertainty in climate model simulations of future climate change, especially in mid-latitude regions such as Europe where atmospheric dynamics have a significant role in climate variability. It has been proposed that the mid-Holocene was characterized in Europe by a stronger westerly circulation in winter comparable with a more positive AO/NAO, and a weaker westerly circulation in summer caused by anti-cyclonic blocking near Scandinavia. Model simulations indicate at best only a weakly positive AO/NAO, whilst changes in summer atmospheric circulation have not been widely investigated. Here we use a new pollen-based reconstruction of European mid-Holocene climate to investigate the role of atmospheric circulation in explaining the spatial pattern of seasonal temperature and precipitation anomalies. We find that the footprint of the anomalies is entirely consistent with those from modern analogue atmospheric circulation patterns associated with a strong westerly circulation in winter (positive AO/NAO) and a weak westerly circulation in summer (positive SCAND). We find little agreement between the reconstructed anomalies and those from a climate model simulation, which as with most model simulations shows a much greater sensitivity to local radiative forcing from top-of-the-atmosphere changes in solar insolation. Our findings are consistent with data-model comparisons on contemporary timescales that indicate that models underestimate the role of atmospheric circulation in climate change, whilst also highlighting the importance of atmospheric dynamics in explaining interglacial warming.

scholarly journals The influence of atmospheric circulation on the mid-Holocene climate of Europe: a data–model comparison

2014 ◽  
Vol 10 (5) ◽  
pp. 1925-1938 ◽  
Author(s):  
A. Mauri ◽  
B. A. S. Davis ◽  
P. M. Collins ◽  
J. O. Kaplan
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Data Model ◽  
Atmospheric Dynamics ◽  
Future Climate Change ◽  
Seasonal Temperature ◽  
Holocene Climate ◽  
Model Simulations ◽  
Recent Climate

Abstract. The atmospheric circulation is a key area of uncertainty in climate model simulations of future climate change, especially in mid-latitude regions such as Europe where atmospheric dynamics have a significant role in climate variability. It has been proposed that the mid-Holocene was characterized in Europe by a stronger westerly circulation in winter comparable with a more positive AO/NAO, and a weaker westerly circulation in summer caused by anti-cyclonic blocking near Scandinavia. Model simulations indicate at best only a weakly positive AO/NAO, whilst changes in summer atmospheric circulation have not been widely investigated. Here we use a new pollen-based reconstruction of European mid-Holocene climate to investigate the role of atmospheric circulation in explaining the spatial pattern of seasonal temperature and precipitation anomalies. We find that the footprint of the anomalies is entirely consistent with those from modern analogue atmospheric circulation patterns associated with a strong westerly circulation in winter (positive AO/NAO) and a weak westerly circulation in summer associated with anti-cyclonic blocking (positive SCAND). We find little agreement between the reconstructed anomalies and those from 14 GCMs that performed mid-Holocene experiments as part of the PMIP3/CMIP5 project, which show a much greater sensitivity to top-of-the-atmosphere changes in solar insolation. Our findings are consistent with data–model comparisons on contemporary timescales that indicate that models underestimate the role of atmospheric circulation in recent climate change, whilst also highlighting the importance of atmospheric dynamics in explaining interglacial warming.

scholarly journals Atmospheric Dynamics Feedback: Concept, Simulations, and Climate Implications

2018 ◽  
Vol 31 (8) ◽  
pp. 3249-3264 ◽  
Author(s):  
Michael P. Byrne ◽  
Tapio Schneider
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Atmospheric Dynamics ◽  
Future Climate Change ◽  
Coupled Models ◽  
Near Surface ◽  
Circulation Changes

AbstractThe regional climate response to radiative forcing is largely controlled by changes in the atmospheric circulation. It has been suggested that global climate sensitivity also depends on the circulation response, an effect called the “atmospheric dynamics feedback.” Using a technique to isolate the influence of changes in atmospheric circulation on top-of-the-atmosphere radiation, the authors calculate the atmospheric dynamics feedback in coupled climate models. Large-scale circulation changes contribute substantially to all-sky and cloud feedbacks in the tropics but are relatively less important at higher latitudes. Globally averaged, the atmospheric dynamics feedback is positive and amplifies the near-surface temperature response to climate change by an average of 8% in simulations with coupled models. A constraint related to the atmospheric mass budget results in the dynamics feedback being small on large scales relative to feedbacks associated with thermodynamic processes. Idealized-forcing simulations suggest that circulation changes at high latitudes are potentially more effective at influencing global temperature than circulation changes at low latitudes, and the implications for past and future climate change are discussed.

Evaluation of climate model simulations in representing the precipitation non-stationarity by considering observational uncertainties

2021 ◽  
Author(s):  
Yongjing Wan ◽  
Jie Chen ◽  
Ping Xie ◽  
Chong-Yu Xu ◽  
Daiyuan Li
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Annual Precipitation ◽  
Future Climate Change ◽  
Spatial Distributions ◽  
Model Simulations ◽  
The Mean ◽  
Climate Model Simulations

<p>The reliability of climate model simulations in representing the precipitation changes is one of the preconditions for climate-change impact studies. However, the observational uncertainties hinder the robust evaluation of these climate model simulations. The goal of the present study is to evaluate the capacities of climate model simulations in representing the precipitation non-stationarity in consideration of observational uncertainties. The mean of multiple observations (OBSE) from five observational precipitation datasets is used as a reference to quantify the uncertainty of observed precipitation and to evaluate the performance of climate model simulations. The non-stationarity of precipitation was represented using the mean and variance of annual total precipitation and annual maximum daily precipitation for the 1982–2015 period. The results show that the spatial distributions of annual and extreme precipitation are similar for various observational datasets, while there has less agreement in the variance changes of extreme precipitation. Climate models are capable of representing the spatial distributions of the annual and extreme precipitation amounts at the global scales. In terms of the non-stationarity, climate model simulations are capable of capturing the large-scale spatial pattern of the trend in mean for annual precipitation. On the contrary, the simulations are less reliable in reproducing the change of extreme precipitation, as well as the trend of variance for annual precipitation. Overall, climate models are more reliable in simulating the mean of precipitation than the variance, and they are more reliable in simulating annual precipitation than extreme. Besides, the uncertainties of precipitation for both observations and simulations are much larger in monsoon regions than in other regions. This study suggests that considering observational uncertainties is necessary when using observational datasets as the reference to project future climate change and assess the impact of climate change on environments.</p>

scholarly journals Toward a New Estimate of “Time of Emergence” of Anthropogenic Warming: Insights from Dynamical Adjustment and a Large Initial-Condition Model Ensemble

2017 ◽  
Vol 30 (19) ◽  
pp. 7739-7756 ◽  
Author(s):  
Flavio Lehner ◽  
Clara Deser ◽  
Laurent Terray
Keyword(s):  
Climate Change ◽  
North America ◽  
Atmospheric Circulation ◽  
Climate Model ◽  
Model Ensemble ◽  
Land Area ◽  
Internal Climate Variability ◽  
Detection And Attribution ◽  
Model Evidence

Abstract Time of emergence of anthropogenic climate change is a crucial metric in risk assessments surrounding future climate predictions. However, internal climate variability impairs the ability to make accurate statements about when climate change emerges from a background reference state. None of the existing efforts to explore uncertainties in time of emergence has explicitly explored the role of internal atmospheric circulation variability. Here a dynamical adjustment method based on constructed circulation analogs is used to provide new estimates of time of emergence of anthropogenic warming over North America and Europe from both a local and spatially aggregated perspective. After removing the effects of internal atmospheric circulation variability, the emergence of anthropogenic warming occurs on average two decades earlier in winter and one decade earlier in summer over North America and Europe. Dynamical adjustment increases the percentage of land area over which warming has emerged by about 30% and 15% in winter (10% and 5% in summer) over North America and Europe, respectively. Using a large ensemble of simulations with a climate model, evidence is provided that thermodynamic factors related to variations in snow cover, sea ice, and soil moisture are important drivers of the remaining uncertainty in time of emergence. Model biases in variability lead to an underestimation (13%–22% over North America and <5% over Europe) of the land fraction emerged by 2010 in summer, indicating that the forced warming signal emerges earlier in observations than suggested by models. The results herein illustrate opportunities for future detection and attribution studies to improve physical understanding by explicitly accounting for internal atmospheric circulation variability.

scholarly journals Historical greenhouse gas concentrations

2016 ◽  
Author(s):  
Malte Meinshausen ◽  
Elisabeth Vogel ◽  
Alexander Nauels ◽  
Katja Lorbacher ◽  
Nicolai Meinshausen ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Radiative Forcing ◽  
Sulfur Hexafluoride ◽  
Climate Model ◽  
Future Climate Change ◽  
Large Set ◽  
Mixing Ratios ◽  
Surface Mixing ◽  
Cooling Effects

Abstract. Atmospheric greenhouse gas concentrations are at unprecedented, record-high levels compared to pre-industrial reconstructions over the last 800,000 years. Those elevated greenhouse gas concentrations warm the planet and together with net cooling effects by aerosols, they are the reason of observed climate change over the past 150 years. An accurate representation of those concentrations is hence important to understand and model recent and future climate change. So far, community efforts to create composite datasets with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since 1980s. Here, we provide consolidated data sets of historical atmospheric (volume) mixing ratios of 43 greenhouse gases specifically for the purpose of climate model runs. The presented datasets are based on AGAGE and NOAA networks and a large set of literature studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved, and include seasonality over the period between year 0 to 2014. We assimilate data for CO2, methane (CH4) and nitrous oxide (N2O), 5 chlorofluorocarbons (CFCs), 3 hydrochlorofluorocarbons (HCFCs), 16 hydrofluorocarbons (HFCs), 3 halons, methyl bromide (CH3Br), 3 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen triflouride (NF3) and sulfuryl fluoride (SO2F2). We estimate 1850 annual and global mean surface mixing ratios of CO2 at 284.3 ppmv, CH4 at 808.2 ppbv and N2O at 273.0 ppbv and quantify the seasonal and hemispheric gradients of surface mixing ratios. Compared to earlier intercomparisons, the stronger implied radiative forcing in the northern hemisphere winter (due to the latitudinal gradient and seasonality) may help to improve the skill of climate models to reproduce past climate and thereby reduce uncertainty in future projections.

scholarly journals Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Joseph Leedale ◽  
Adrian M. Tompkins ◽  
Cyril Caminade ◽  
Anne E. Jones ◽  
Grigory Nikulin ◽  
...  
Keyword(s):  
Climate Change ◽  
Malaria Transmission ◽  
Climate Models ◽  
Climate Model ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Climate Projections ◽  
Model Ensemble ◽  
East African Community ◽  
Recent Climate

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

scholarly journals Sustainable Energy Development under Climate Change

2018 ◽  
Vol 10 (9) ◽  
pp. 3269 ◽  
Author(s):  
Chih-Chun Kung ◽  
Bruce McCarl
Keyword(s):  
Climate Change ◽  
Sustainable Energy ◽  
Energy Development ◽  
Future Climate ◽  
Policy Implications ◽  
Future Climate Change ◽  
Human Society ◽  
Energy Needs ◽  
Broad Array

The world faces unprecedented threats from climate change and increasing variability, which severely impacts human society and the natural environment. To reduce future climate change and ensure our economies can grow in a sustainable way, sustainable energy development is considered to be an effective approach. In this context, sustainable energy development involves augmenting our energy supplies and managing demands in a fashion that societal energy needs are met with a minimal effect on greenhouse gas emissions and a nominal resultant contribution to future climate change. In this Special Issue, research papers focus on the role of sustainable energy development (while addressing important dimensions of sustainability), which mandates an inter-disciplinary perspective in all articles. We collected 11 such papers that have analyzed a broad array of topics related to bioenergy, wind power, industrial innovation, and climate change mitigation. These papers show the varied application of renewable energy and climate change energy responses, while providing meaningful decision-making information and policy implications.

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